V O LU M E
T H I RT Y
S E V E N
INTERNATIONAL REVIEW OF
RESEARCH IN MENTAL RETARDATION FAMILIES
Board of Associate Editors
PHILIP DAVIDSON University of Rochester School of Medicine and Dentistry
ELISABETH DYKENS Vanderbilt University
MICHAEL GURALNICK University of Washington
RICHARD HASTINGS University of Wales, Bangor
LINDA HICKSON Columbia University
CONNIE KASARI University of California, Los Angeles
WILLIAM McILVANE E. K. Shriver Center
GLYNIS MURPHY University of Kent
TED NETTELBECK Adelaide University
MARSHA MAILICK SELTZER University of Wisconsin-Madison
JAN WALLANDER Sociometrics Corporation
V O LU M E
T H I RT Y
S E V E N
FAMILIES A Volume in
INTERNATIONAL REVIEW OF
RESEARCH IN MENTAL RETARDATION Edited by
LARAINE MASTERS GLIDDEN Psychology and Human Development St. Mary’s College of Maryland St. Mary’s City MD 20686, USA
MARSHA MAILICK SELTZER Waisman Center University of Wisconsin-Madison Madison, WI 53705
AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier
Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 84 Theobald’s Road, London WC1X 8RR, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2009 Copyright ß 2009, Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email:
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CONTENTS
Contributors Foreword Preface
Section I. Longitudinal Comparisons 1. Mothers and Fathers Together: Contrasts in Parenting Across Preschool to Early School Age in Children with Developmental Delays
ix xiii xv
1
3
Keith Crnic, Anita Pedersen y Arbona, Bruce Baker, and Jan Blacher 1. 2. 3. 4. 5.
The Father in the Family Setting the Stage: Stress, Well-Being, and Parenting The Collaborative Family Study: A Context for Contrasts Parental Stress and Children with ID Parental Psychological Well-Being in the Context of ID 6. Parenting Behavior with Children with ID 7. An Integrated Perspective 8. Summary and Conclusions References
2. The Transition to Adulthood for Individuals with Intellectual Disability
8 9 10 11 17 19 22 25 26
31
Frank J. Floyd, Catherine L. Costigan, and Vivian E. Piazza 1. Introduction 2. Method 3. Results 4. Discussion 5. Conclusion References
32 37 42 54 58 58
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3. By Choice or By Chance: Longitudinal Perspectives on Resilience and Vulnerability in Adoptive and Birth Parents of Children with Developmental Disabilities
61
Laraine Masters Glidden and Brian M. Jobe 1. Introduction 2. Hypothesis Testing: Chronic Sorrow or Crisis and Recovery 3. Parental Long-Term Adjustment: Multiple Variables Measured Multiple Times 4. Parental Long-Term Adjustment: Transition to Adulthood 5. Chronic Sorrow or Crisis and Recovery: Conclusions from Mean-Level Differences 6. Parental Long-Term Adjustment: The Importance of Personality in Predicting Resilience 7. Summary, Conclusions, and Directions for Future Research in the Study of Resilience References
62
87 90
Section II. Methodological and Sample Diversity
95
4. Socioeconomic Position, Poverty, and Family Research
97
71 73 78 79 81
Eric Emerson and Chris Hatton 1. Introduction 2. Socioeconomic Position and Poverty 3. Socioeconomic Position, Poverty, and the Prevalence of Intellectual and Developmental Disability 4. The Impact of Socioeconomic Position on Family Functioning and Child Well-Being 5. The Impact of Socioeconomic Position Among Families Supporting a Child with Intellectual or Developmental Disabilities 6. Moving Forward: Methodological and Conceptual Issues Associated with Incorporating Socioeconomic Position into Family Research 7. Conclusions References
98 98 100 104
106
112 119 120
Contents
5. Using Large-Scale Databases to Examine Families of Children with Intellectual and Developmental Disabilities
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Robert M. Hodapp and Richard C. Urbano 1. Studying Families of Persons with Specific Disabilities 2. Three Large-Scale Approaches to Family Research 3. Two Examples of Using Large-Scale Administrative Databases to Answer Family-Related Questions 4. Comparing Different Types of Large-Scale Databases 5. Summary and Conclusion References
6. A Rich Mosaic: Emerging Research on Asian Families of Persons with Intellectual and Developmental Disabilities
133 135 165 169 172 173
179
Subharati Ghosh and Sandy Magan˜a 1. Introduction 2. Cross-Cultural Model of Family Functioning 3. Review of the Literature Within the Cross-Cultural Model 4. Summary and Conclusions References
7. Biomarkers in the Study of Families of Children with Developmental Disabilities
180 181 182 206 209
213
Marsha Mailick Seltzer, Leonard Abbeduto, Jan S. Greenberg, David Almeida, Jinkuk Hong, and Whitney Witt 1. 2. 3. 4.
Introduction Fragile X Syndrome and Related Conditions Cortisol Profiles in Parents of Children with Disabilities Summary and Conclusions: Next Steps in Research on Biomarkers in Families of Individuals with Developmental Disabilities References
8. Siblings of Children with Intellectual Disabilities: Normal, Average, or Not Too Different?
214 216 229
239 242
251
Zo Stoneman 1. Siblings of Typically Developing Children 2. Research on Siblings of Children with Intellectual Disabilities 3. Use of Comparison Groups in Sibling Disability Research
253 255 258
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4. Methodological Considerations in Conducting Comparison Group Sibling Research 5. Same or Not Too Different from Average? 6. The Case (or the Lack Thereof ) for Sibling Interventions 7. Concluding Thoughts References
Section III. Interventions 9. Family Support Interventions for Families of Adults with Intellectual and Developmental Disabilities
277 280 283 284 286
297 299
Tamar Heller and Abigail Schindler 1. Introduction 2. Impact of Having a Family Member with I/DD 3. Family Support Public Policies and Programs 4. Family Support Psychosocial Interventions 5. Conclusion References
10. Interventions Aimed at Improving Child Language by Improving Maternal Responsivity
300 301 311 317 324 325
333
Nancy Brady, Steven F. Warren, and Audra Sterling 1. Responsivity is a Multilevel Construct 2. Responsivity Relates to Child Outcomes 3. Interventions Aimed at Improving Responsivity 4. Summary and Conclusions References Index Contents of Previous Volumes
335 339 344 351 353 359 367
CONTRIBUTORS
Numbers in parentheses indicate the pages on which the authors’ contributions begin.
Leonard Abbeduto (213) Department of Educational Psychology, and Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA David Almeida (213) Department of Human Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA Anita Pedersen y Arbona ( 3) Department of Psychology, Arizona State University, Tempe, Arizona 85287, USA Bruce Baker ( 3) Department of Psychology, UCLA, Los Angeles, California 90095, USA Jan Blacher ( 3) Graduate School of Education, University of California, Riverside, California 92521, USA Nancy Brady ( 333) Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, Kansas 66045, USA Catherine L. Costigan ( 31) Department of Psychology, University of Victoria, STN CSC, Victoria, British Columbia V8W 3P5, Canada Keith Crnic ( 3) Department of Psychology, Arizona State University, Tempe, Arizona 85287, USA Eric Emerson (97) Institute for Health Research, Lancaster University, Lancaster LA1 4YT, United Kingdom Frank J. Floyd ( 31) Department of Psychology, Georgia State University, Atlanta, Georgia 303025010, USA Subharati Ghosh (179) University of Wisconsin-Madison, School of Social Work, Madison, Wisconsin 53705, USA ix
x
Contributors
Laraine Masters Glidden (61) Department of Psychology, St. Mary’s College of Maryland, St. Mary’s City, Maryland 20686, USA Jan S. Greenberg (213) Waisman Center, and School of Social Work, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA Chris Hatton (97) Institute for Health Research, Lancaster University, Lancaster LA1 4YT, United Kingdom Tamar Heller (299) Department of Disability and Human Development, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois 60608-6904, USA Robert M. Hodapp (131) Department of Special Education, Peabody College and Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, Tennessee 37203, USA Jinkuk Hong (213) Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA Brian M. Jobe (61) Department of Psychology, University of Maryland, Baltimore County, Catonsville, Maryland 21228, USA Sandy Magan˜a (179) University of Wisconsin-Madison, School of Social Work, Madison, Wisconsin 53705, USA Vivian E. Piazza ( 31) Department of Psychology, Georgia State University, Atlanta, Georgia 303025010, USA Abigail Schindler (299) Department of Disability and Human Development, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois 60608-6904, USA Marsha Mailick Seltzer (213) Waisman Center, and School of Social Work, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA Audra Sterling ( 333) Director, Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, Kansas 66045, USA
Contributors
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Zo Stoneman (251) Institute on Human Developement and Disability, College of Family and Consumer Sciences, University of Georgia, Athens, GA 30602 Richard C. Urbano (131) Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, and Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA Steven F. Warren ( 333) Director, Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, Kansas 66045, USA Whitney Witt (213) Department of Population Health Sciences, and Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
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FOREWORD
The International Review of Research in Mental Retardation has been published for more than 40 years. During this time, the field of mental retardation has changed dramatically in both its science and its services. Although psychology, education, medicine, sociology, law, and other disciplines have always been constituent players, more than ever now, these contributions are coordinated and collaborative with expertise from different disciplines contributing essential methods and knowledge to solve problems. My own career has spanned approximately the same time period as that of this International Review series, and I am proud to have played a role in its continued production and success. I first published in Volume 13 in 1985, and then over the years, with coauthors, wrote three more chapters, including the one in this volume. I do not intend it to be my last. This volume, however, is my last one as Series Editor. I was both honored and eager to take on the Editor role in 1997 and assume responsibility for the subsequent 16 volumes that were produced during my Editorship. Without the good fortune of working with knowledgeable and committed colleagues who served on the Board of Associate Editors, and who guest-edited theme volumes, there would have been fewer volumes of lesser quality. I, and the field, owe a special debt of gratitude to these individuals whom I recognize here (alphabetical order): Len Abbeduto, Phil Davidson, Elisabeth Dykens, Mike Guralnick, Richard Hastings, Linda Hickson, Bob Hodapp, Connie Kasari, Johnny Matson, Bill McIlvane, Glynis Murphy, Ted Nettelbeck, Marsha Seltzer, Harvey Switzky, Rick Urbano, Jan Wallander. Three individuals in this list deserve special recognition. Harvey Switzky took on the task of editing a theme volume with such zeal and determination that he solicited manuscripts from more experts in the field of personality and motivation than could be accommodated in a single volume. He had no hesitation in agreeing to be the guest editor of two volumes, 28 and 31. Second, it has been a delight to work with Marsha Seltzer as coeditor on the current volume. As always, she was not only conscientious with regard to the tasks that confronted us, but also creative about how to organize the volume and invite colleagues who would make valuable contributions. Finally, Bob Hodapp is the new Series Editor. I know that he cares as much about the International Review as I have done and still do, and that he has the intellectual vigor and professional resources to make it even better than it is. We will all look forward to Volume 38, the first of what I hope will be many volumes that he will edit.
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Finally, various members of the editorial department at Academic Press have been supportive of our efforts, and I would particularly like to thank Barbara Makinster, Niki Levy, and Mica Haley whose essential roles in bringing volumes from ideas to books were critical. None of it could have been done without them. LARAINE MASTERS GLIDDEN
PREFACE
Research on families of children and adults with intellectual and developmental disabilities (IDD) has attracted substantial attention, especially following the movement away from out-of-home residence that typified the deinstitutionalization and normalization trends that began in the 1960s and continue in the present. Although most children with IDD have always lived with their families, when substantial numbers of them began to live in institutions, those individuals and the issues surrounding their residential status tended to dominate research. In 1966, when volume 1 of the International Review was published, more than twice as many articles were published on mental retardation and institutions (66) than on mental retardation and families (31). In 2008, the numbers told quite a different story. A PsychInfo search found 178 articles on mental retardation and families and only 54 on mental retardation and institutions. Surprisingly, although the International Review has published many chapters on families, no single volume has been dedicated to this topic. The current volume redresses that issue. We have organized this volume into three sections that reflect three important dimensions of research in IDD: longitudinal research; methodological and sample diversity; and interventions. In this preface, we briefly summarize the important themes of each of the chapters and the way these themes relate to the sections and to other chapters. Longitudinal Research. Three chapters constitute the section on longitudinal research. In the first chapter, Crnic, Pedersen y Arbona, Baker, and Blacher focus on the preschool to early school age period, based on data from their longitudinal Family Collaborative Project. Their research is longitudinal in that it not only follows the sample over time, but also compares mothers and fathers, and children with and without developmental delay. The authors are particularly concerned about giving more visibility to fathers and comparing the developmental trajectories of mothers and fathers to explain how they similarly or differently influence the development of their children. Continuing along the developmental trajectory, Floyd and Costigan focus on the transition to adulthood in individuals with IDD based on data from a longitudinal investigation of individuals who were first studied during their elementary school years and who are now in their early 20s, on average. The findings indicate limited evidence of complete independence
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from parents, and the authors conceptualize the stage of emerging adulthood characterized by interdependence rather than independence. The third chapter in this section, by Glidden and Jobe, is yet another example of longitudinal family research. Here the focus is on the long-term adjustment of parents who adopt children with IDD, as well as the more typical birth families. Profiles of resiliency are prominent among the findings, dispelling the myth of chronic sorrow and suggesting that parents adapt to the challenge. In addition, these authors point to the importance of bringing parental personality characteristics into models of resilience and vulnerability. Methodological and Sample Diversity. The section on methodological and sample diversity demonstrates that samples in family studies come from many different national, racial and ethnic groups; from different family members; and from methods that vary from physiological to secondary analyses of large datasets. This level of methodological rigor has now set the standard for family research on IDD. In Chapter 4, the first of five chapters in this section, Emerson and Hatton amass large amounts of data from many countries to remind us that IDD is embedded in a family context, which is itself part of an exosystem and macrosystem with life-altering consequences. Persons with IDD are far more likely to experience poverty, and poverty and its concomitants are likely to be contributing factors to the development of the disability. The authors of Chapters 5 and 6 focus on different types of methodological diversity—from demographic to physiological approaches. In Chapter 5, Hodapp and Urbano argue effectively that large-scale databases are a valuable resource for answering important questions about families of children with IDD. They review different types of databases relevant to the families and provide illustrative examples from their own work. In contrast, Seltzer, Abbeduto, Greenberg, Almeida, Hong and Witt move us in a different direction in Chapter 6 with an emphasis on biomarkers as indicators of adverse reactions in maternal caretakers. They review their work along with that of other investigators on the FMR1 gene and on cortisol, and reiterate that these methodologies have much to tell us about families and IDD. In Chapters 7 and 8, the diversity is of samples rather than of method. Stoneman focuses on research on the siblings of children with IDD, with an extensive review of published studies and an emphasis on the methodological complexity and obstacles in conducting this kind of research. She discusses approaches for constituting comparison groups and thus, provides the reader with a very useful set of strategies for either conducting or evaluating sibling research. In the Ghosh and Magan˜a chapter, the focus shifts from diversity in samples studied in family research to ethnic and racial diversity. They review the emerging body of research on Asian families who have a son
Preface
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or daughter with IDD. By including studies of families of Asian-descent who live in the US and the UK, as well as Asian families who live in Asian countries, considerations of cultural values, acculturation, and cross-cultural stress are examined within a cross-cultural stress and coping model. Interventions. Families of children with IDD are often involved in interventions aimed at improving the functioning and abilities of their children. We conclude this volume with two chapters on family interventions. The first, by Brady, Warren, and Sterling, examines interventions aimed at improving child language via improving maternal responsivity. Here the focus is on young children with IDD. Through an extensive review of past research, this chapter demonstrates that such interventions can have a major impact on maternal responsivity, and to a lesser extent, on child language outcomes. The second chapter on family interventions, by Heller and Schindler, is focused on interventions involving families of adults with IDD. Rather than using the family as an agent fostering behavioral change, this chapter reviews family support interventions, as well as public policies and services aimed at supporting families as long-term caregivers for their adult children with IDD. Together, these two chapters illustrate how the expectations of families change over the course of life. Finally, we would have been unable to produce this volume without the help of many expert reviewers whose efforts often go unacknowledged because of the anonymity of the review process. We thank the following individuals (alphabetical listing) who lent their expertise despite the many demands on their time. This volume is greatly improved because of them: Don Bailey, Debbie Carran, Derek Chapman, Monica Cuskelly, Elisabeth Dykens, Anna Esbensen, Frank Floyd, Glen Fujiura, Jan Greenberg, Chris Hatton, Penny Hauser-Cram, Jinkuk Hong, Julie Lounds Taylor, Malin Olsson, Gael Orsmond, Susan Parish, Leann Smith, Patricia Walsh, and Susan Ellis Weismer. LARAINE MASTERS GLIDDEN MARSHA MAILICK SELTZER
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S E C T I O N
O N E
LONGITUDINAL COMPARISONS
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C H A P T E R
O N E
Mothers and Fathers Together: Contrasts in Parenting Across Preschool to Early School Age in Children with Developmental Delays Keith Crnic,* Anita Pedersen y Arbona,* Bruce Baker,† and Jan Blacher‡ Contents 8 9 10 11 17 19 20 20 22 22 25 26 26
1. 2. 3. 4. 5. 6.
The Father in the Family Setting the Stage: Stress, Well-Being, and Parenting The Collaborative Family Study: A Context for Contrasts Parental Stress and Children with ID Parental Psychological Well-Being in the Context of ID Parenting Behavior with Children with ID 6.1. Previous research 6.2. Behavioral trajectories in CFS 6.3. Conclusions regarding father interactive behavior 7. An Integrated Perspective 8. Summary and Conclusions Acknowledgments References
Abstract Much of our understanding of families and parenting of children with intellectual disabilities (ID) reflects the thoughts, beliefs, attitudes, and behaviors of mothers with relatively little focus on the ways in which fathers contribute to and are affected by this unique context. In this chapter, we address the importance of fathers as a source of critical developmental influence, and contrast fathers and mothers of children with ID along three important dimensions of parent functioning (stress, well-being, and interactive behavior). The contrasts
* { {
Department of Psychology, Arizona State University, Tempe, Arizona 85287, USA Department of Psychology, UCLA, Los Angeles, California 90095, USA Graduate School of Education, University of California, Riverside, California 92521, USA
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37001-9
#
2009 Elsevier Inc. All rights reserved.
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explore the developmental trajectories of these parenting constructs over time from the perspective of an emerging new complexity in conceptual models of family and parent adaptation. Data from the Collaborative Family Study are used to explore paternal and maternal stress, well-being, and behavior across the preschool through transition to school-age developmental period, and findings are discussed within the context of the broader literature in each area.
Over the past several decades, there has been a surge in interest in the study of families of children with developmental disabilities. Indeed, research, as well as policy and applied considerations have brought strong attention to the myriad of issues that families face, the variety of factors that shape familial response, and the actual multiplicity of responses that families have to the presence of a child with developmental disabilities (DD), or specifically intellectual disability (ID). Our understanding of the complexity of family functioning in the context of a child with DD is quite early in its development, yet the richness of our emerging conceptual models is encouraging. This richness, however, is limited by the fact that much of this understanding reflects the thoughts, beliefs, attitudes, and behaviors of mothers with relatively little focus on how fathers may contribute to and be affected by this unique context. Certainly, the relative lack of attention to fathers is not unique to family and parenting research with populations of children with developmental disabilities. Research with typically developing children and families has had much the same limitation, although there has been substantial progress made in the basic developmental literature with even an entire journal now devoted to the study of fathers (Fathering: A Journal of Theory, Research, & Practice about Men as Fathers). Recent efforts to bridge the gap in understanding maternal and paternal processes in families with a child with developmental disabilities also have begun to offer a number of intriguing observations regarding similarities and differences between mothers and fathers, particularly with respect to issues of perceived stress, psychological well-being, and actual parenting behavior with their children. In this chapter, we offer an historical perspective on families and adaptation, and follow that with a discussion of newer, more complex models that necessarily include notions of more systemic developmental frameworks that involve fathers as well as mothers. We discuss the explicit role of fathers in the family, and subsequently use data from our Collaborative Family Study (CFS) to explore longitudinally contrasts of mothers and fathers across three major domains of parental functioning that have been at the heart of many studies of families of children with ID: stressful experience, psychological well-being, and parental interactive behavior with children with ID. We end with an attempt to offer some integrative thoughts about our current research models and conceptual approaches to understanding parenting in families if children with ID.
Mothers and Fathers Together
5
An historical perspective. To understand the current state of the field, it is important to offer a brief historical perspective on research with families of children with DD and the perspectives which have driven our conceptual frameworks. Early studies of families of children with intellectual and developmental disabilities focused primarily on the negative impact of the child on their family (see Blacher & Baker, 2002). Parents (again, primarily mothers) of children with mental retardation (using the language of the period) were found to suffer from a litany of negative outcomes including guilt, depression, stress, self-blame, financial problems, emotional tension, religious doubts, and concerns about caretaking (Kanner, 1953; Murray, 1959). The birth of the disabled child was seen as a crisis that invoked a grieving process, during which the parent must progressively let go of the hopes and dreams that he or she had for the child (Olshansky, 1962). ‘‘Chronic sorrow’’ emerged, as at each developmental milestone parents would be reminded that their child was different from others (Olshansky, 1962). Wolfensberger and Menolascino (1970) described the development of a series of crises in the family of a handicapped child: a ‘‘novelty shock crisis’’ as a first response to the news of their child’s disability, followed by a ‘‘reality crisis’’ as the daily stresses of raising the child cause strain in the family, and finally a ‘‘value crisis’’ as parents realize that their child will never be like typically developing children. Although research in the late twentieth century did not make as negative predictions of family adjustment, parents of handicapped children were found to have smaller social networks than other families (Kazak & Wilcox, 1984) and exhibited higher stress levels than families of typical children (Kazak, 1987). Much of this early conceptual work featured the predominant pathological models of that time, and it was anticipated that the negative effects were ubiquitous across functional category and across family members. Never was there a sense that fathers and mothers may actually have different experiences and effects, nor were there considerations that the nature of such experience and effect might actually change over time. Only in the last several years has the largely negative perception of the impact of the child with developmental or intellectual disability on the family begun to change (Blacher & Baker, 2007). Indeed, current research models examine both stresses and strengths in these families (Baker, Blacher, Kopp, & Kraemer, 1997; Blacher & Baker, 2007). For example, biological parents of children with intellectual disability initially show high levels of depression. However, over time, these depression levels appear to decrease and become similar to the more normative levels of parents who choose to adopt children with intellectual disability (Glidden & Schoolcraft, 2003). Further, some families who were interviewed regarding their child with developmental delays believe the child brings happiness to the family, facilitates family closeness, provides an opportunity to learn new information, and is a source of personal growth and inner strength (Hastings &
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Taunt, 2002; Sandler & Mistretta, 1998; Stainton & Besser, 1998). Some of our work has shown that it is not a child’s status as disabled that is stressful in itself, but rather behavior problems that may or may not be associated with their disability (Baker, Blacher, Crnic, & Edelbrock, 2002; Blacher & Baker, 2007). Moreover, parents who perceived their child with disabilities as having a positive impact on the family were less stressed, even if that child had behavior problems (Blacher & Baker, 2007). These studies offer promising early signs that parent beliefs and family perceptions can buffer the potential adversity associated with the high-risk child with intellectual disability on his or her family. The new complexity. Whether our attention is focused on families and typically developing children or on families and children with intellectual disability, the course of development is marked by considerable variability in outcomes, and great diversity in developmental pathways is to be expected (Cicchetti & Rogosh, 1996). Past are the days when simple main effect, single point-in-time pathology-based models offer meaningful understandings of family response to children with ID. Instead, efforts to model the complex transactional phenomena that characterize family processes are now more commonplace in the literature that addresses families of high-risk children. These approaches accept as given that processes of equifinality and multifinality help explain long term prediction to family and child adaptation under conditions of risk. Indeed, attention to both adaptational successes and failures on stage salient issues for specific developmental periods reflects an important strategy for explicating those processes that contribute to risk trajectories (Sameroff, 2000). Equifinality and multifinality are complex theoretical constructs that define the nature of open systems in determining individual (or family) outcomes or end states. Multifinality posits that diverse outcomes are likely to result from any one starting point or source of influence, and any one component may function differently depending upon the organization of the system in which it operates. Equifinality, in contrast, posits that given quite diverse starting points similar outcomes can eventuate such that a variety of developmental progressions may end in a given adaptation or condition. Although both system concepts are important, a focus on multifinality is most germane to understanding what happens over time in families of children with ID. As has become more clear with the identified range of familial adaptations (Blacher & Baker, 2007), the beginning state does not dictate the end state, and there is a vast array of factors that can account for the variety in child, parent, and family outcomes at any one point in time. Therefore, the manner in which continuities in development are characterized across adaptational domains is critical in understanding key pathways of influence in family and child functioning. Given the potential for multiple pathways to exist in any adaptive or maladaptive outcome, identifying specific risk conditions and developmental
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processes that increase the likelihood of maladaptation is an important goal. This is true not only for enhancing our knowledge of such conditions in general, but for eventual prevention/intervention planning. In this respect, processes of mediation and moderation are central to the new complexity in modeling, especially when addressed within a longitudinal framework. Certainly, the presence of risk alone does not dictate or ensure some poor outcome; rather a variety of transacting mediators and moderators of risk are most likely to account for key outcomes. Sameroff (2000) has argued that continuities in competence or maladaptation over time cannot be simply related to continuities in underlying pathology or health. He further suggests that to the extent that experience becomes more organized, problems in adaptation are likely to diminish; but should experience become more chaotic, problems in adaptation will increase. This implicates the presence of transacting mediators and moderators of experience that over time are key to understanding the nature of family, parental, and child adaptational response to the presence of ID. As one explicit example of the new complexity in frameworks that attempt to explain adaptational outcomes, we have recently proposed a model for understanding the emergence of dual diagnosis in children with early undifferentiated developmental delay (Baker et al., 2002; Crnic, 2001; Crnic, Hoffman, Gaze, & Edelbrock, 2004). Figure 1.1 presents a simplified expression of the basic model components. This model (see Fig. 1.1) attempts to capture the complex longitudinal relations between risk and emerging dual diagnosis (or social competence) in young children with early undifferentiated developmental delay, but suggests that the pathway through which developmental delay leads to dual diagnosis flows through ongoing family processes and children’s emerging regulatory capacities. Although the presence of developmental delay retains a slim direct pathway, the true pathway of influence is through risk’s effect on family process over time, and family processes’ effect in turn
Family processes
Psychopathology or competence
Developmental delay
Child self regulation
Figure 1.1 A family process model for emerging dual diagnosis or social competence in young children with DD.
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on children’s regulatory abilities. The richness of this model is in the depth of both family process and children’s regulatory conceptualizations, each of which is multiply determined. It is beyond the scope of this chapter to delve deeply into the many pathways that operate within this multifaceted model. And although the nature of self-regulatory processes in children with DD is not well understood, nor has it been the emphasis of much investigation, we will focus in this chapter only on key components of the family process domain, with an explicit eye on the contrasts and comparisons between mothers and fathers over time in key adaptational factors: stress, well-being, and actual parenting as represented by parent behavior during interactions with their children in a naturalistic home context. Parent and family processes have proven to be key mediators and moderators of risk and adaptation across a variety of populations and domains (Rubin & Burgess, 2002; Cui & Conger, 2008; Kwok, Haine, Sandle, Ayers, Wolchi, et al., 2005; Owen, Thompson, & Kaslow, 2006); including families of children with ID (Gerstein, Crnic, Blacher, & Baker, 2009; Hauser-Cram, Warfield, Shonkoff, & Krauss, 2001). As such, greater understanding of the complex ways in which parenting operates to exert its influence on children’s competence over time continues to be of great interest, and even more so within an understudied population such as families of children with ID.
1. The Father in the Family Our models of parenting and family functioning have basically been built on the foundation of mothering. This is certainly understandable from a variety of perspectives, not the least of which are the historical, cultural, and social norms that dictate the primacy of mothering in the childrearing process. Families in which a child has DD or ID are no different in this respect. Nonetheless, and irrespective of the developmental status of the child, fathers have recently begun to gain greater prominence in family research (Day, Lewis, O’Brien, & Lamb, 2005) despite the fact that mothers remain the primary caregivers in most families (Pleck, 1997). The role of fathers in raising children has increased since the 1960s (Robinson, 1988; Yeung, Sandberg, Davis-Kean, & Hofferth, 2001), and studies addressing the quality of the father–child relationship indicate that infants demonstrate similar attachment patterns with their fathers as they do with their mothers (Fox, Kimmerly, & Schafer, 1991) and warmth from fathers is similarly related to children’s developmental well-being as is warmth from mothers (Lamb, 1986). Fathers are also now more expected to be an equal coparent to the mother (Pleck & Pleck, 1997) and provide physical and emotional care to children (Goldscheider & Waite, 1991).
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With the growing attention to fathers, it is all the more important to determine the extent to which parenting processes are uniform across mothers and fathers. Although basic similarities certainly exist as noted above, there are also processes in which parenting diverges across gender. In many ways, it appears that fathers interact with, perceive and respond to their families quite differently than do mothers. Indeed, fathers are more likely to engage in play activities when interacting with their children, whereas mothers spend more time in caregiving activities (Roggman, Boyce, Cook, Christiansen, & Jones, 2004). During play, fathers engage in more active and physical play, whereas mothers use more verbal and didactic play techniques as well as more toys and objects during play (MacDonald & Parke, 1984, 1986). Mothers and fathers appear to perceive differences in their parenting styles, as Winsler, Madigan, and Aquilino (2005) reported that fathers perceived their spouses as more authoritative, more permissive, and less authoritarian than themselves, and mothers perceived themselves to be only more authoritative than fathers. Interesting, they noted that parents who share similar parenting styles are more accurate at reporting on their spouses’ parenting styles than are parents with differing styles. Research also indicates that fathers experience stress differently than mothers. For example, fathers may be more strongly affected by environmental stressors than mothers (Krishnakumar & Buehler, 2000). This latter point is particularly salient given the risks and stresses often associated with the presence of a child with ID in the family. Research on fathers of children with disabilities is scarce, more so even than research on fathers in general. Nonetheless, the need for greater attention to fathers is apparent, as both mothers and fathers of children with intellectual disabilities perceive fathers as being significantly involved with playtime, discipline, nurturing, and decisions regarding service provision (Simmerman, Blacher, & Baker, 2001). But, as we review below, there is some emerging evidence that fathers and mothers of children with ID may differ in some respects along a number of important parenting dimensions and it may be that differences in stress contexts and responses is a critical determinant of parenting (Hauser-Cram et al., 2001). Still, the extent and degree of such differences between fathers and mothers of children with developmental disabilities are not well understood and require greater examination.
2. Setting the Stage: Stress, Well-Being, and Parenting Of course, parenting contrasts could be addressed across an almost unlimited number of domains, each of which would contribute importantly to our emerging framework of parent and family functioning in the context
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of a child with DD or ID. This chapter focuses specifically on three major domains of interest in family functioning: the nature of stressful experience, parental psychological well-being, and actual parenting behavior in interactions with children. These facets of parental functioning in families of children with ID, and particularly stress, have been predominant in the literature over time. But despite their ubiquitous nature, we continue to have fairly limited understanding of these domains for families of children with ID and almost no focus on their function over time (with notable exceptions). The lack of attention to the stability and continuity of these parenting domains is relatively shocking given the challenges inherent in caring for high-risk children and potential for developmental and behavioral change in children with ID across the early childhood period.
3. The Collaborative Family Study: A Context for Contrasts Over the past decade, we have explored parenting processes in mothers and fathers of children who were early identified as having global developmental delays. The goal of CFS was to examine family processes and children’s emerging regulatory capacities in the prediction of social competence or psychopathology (dual diagnosis) in children with ID. The risk for psychopathology in children with ID is much higher than that in the typically developing population of children (Pfeiffer & Baker, 1994), and we have proposed a complex transactional pathway of influence model (see Fig. 1.1) through which we attempt to explain the emergence of dual diagnosis in children with ID. Central to our model are a variety of important parenting constructs, and we devote extensive measurement to explicating the nature of parents’ experience and actions for both mothers and fathers. As such, CFS is ideally suited to explore contrasts between mothers and fathers along parenting domains of critical interest to families and to do so within the framework of the ‘‘new complexity.’’ One of the major strengths of the CFS is its longitudinal emphasis, and the opportunities that multiple measurements across time provide. Our sample of families of children with early identified developmental delays (N ¼ 109) and families of typically developing children (N ¼ 136) have to date been seen nine times across a 6-year age span. Parents and children were assessed within weeks of children’s birthdays at ages 3 years through age 9, and midyear assessments were also taken at ages 3.5 and 4.5. Our approach to measurement was both multimethod and multimodal. Parents completed an array of questionnaires and interviews, and parents and children were observed in naturalistic and structured home-based observations as well as structured lab-based observational assessments. Children
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regularly were assessed across domains of competence and behavior problems. Both mothers and fathers were involved in all levels of measurement with the exception of the lab-based structured interactions at ages 3, 4, and 5 which were mother-only. With repeated longitudinal assessments of constructs involving stress, parental well-being, and parenting behavior during home-based interactions with children, CFS affords an opportunity to contrast results with the existing literature in the field. These contrasts detail the nature of parental functioning with a specific eye toward understanding mother and father similarities or differences. But CFS also affords the unique opportunity to explore such contrasts over time, measuring parenting across the preschool period and into early school age. And although our focus is on the contrasts between mothers and fathers on parenting domains, there is actually precious little available longitudinal research on either mothers or fathers to guide our thinking about family adaptational response to the risks associated with parenting a child with ID. One notable exception is the Early Intervention Collaborative Study, which has collected data longitudinally from early childhood to adolescence in a relatively large sample of families of children with ID (Hauser-Cram et al., 2001; Kersh, Hedvat, HauserCram, & Warfield, 2006; Mitchell & Hauser-Cram, 2008; Shonkoff, Hauser-Cram, Krauss, & Upshur, 1992). In the sections to follow, we detail comparisons in the CFS data between mothers and fathers on key measurements of interest in the field: stress, wellbeing, and parenting behavior. Our specific focus will address these parenting processes across child ages 3–6, a period of time for which we have complete analyses. Beyond the simple comparisons across the four age periods, we describe, we examine latent growth curves for our parenting constructs, and contrast these curves between mothers and fathers. In each section, we present and discuss our longitudinal analyses within the framework of the existing literature.
4. Parental Stress and Children with ID The history of research on family stress response is rich with findings that parents of children with ID are more stressed than are parents of typically developing children (Baker et al., 1997; Blacher & Baker, 2002; Crnic, Greenberg, Ragozin, Robinson, & Basham, 1983; Crnic & Low, 2002; Fidler, Hodapp, & Dykens, 2000). In addition to the stress of the diagnosis and adjustment, there are also increased caregiving demands (Crnic, Friedrich, & Greenberg, 1983), additional financial strain (Gunn & Berry, 1987; Parish, Seltzer, Greenberg, & Floyd, 2004), and handling attitudes of professionals and schools in their reaction to the child (Blacher &
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Hatton, 2007). Stress, however, is not a unidimensional construct. Stress can be operationalized in many ways, and often the source or context of the stressor is a key defining unit (Crnic & Low, 2002; Hauser-Cram et al., 2001). General life stress (Crnic & Greenberg, et al., 1983), stress specific to having children with developmental disabilities (Holroyd, 1974), and more recently stresses directly tied to parenting and child rearing (Abidin, 1995) all have contributed to the expanding knowledge base. This expansion has included work on parenting stress in families of children with ID, although only a handful of studies have included fathers’ reports and perceptions. Although the research on stress in families of children with ID is relatively consistent in noting higher stress in these families, the sources of that stress have been questioned and are in fact somewhat less clear than may seem apparent. Glidden (Clayton, Glidden, & Kiphart, 1994; Glidden, 1993) has thoughtfully noted the potential confounding of stressors (the demands on parents) and actual experience of stress (parent appraisal and response to the demands) that is commonplace in the literature. Over time, research has shown that not all stressors are equal, and that the demands associated with intellectual disability per se do not seem to be nearly as stressful as the demands associated with having to address child behavior problems (Baker, McIntyre, Blacher, Crnic, Edelbrock, et al., 2003). Rather than attempt an exhaustive review of stress research in families of children with ID at this point, we will focus instead on those more recent studies that have included information from both mothers and fathers. As noted, the major focus of the research on stress has been a comparative one in which parents of children with ID were compared with parents of typically developing children. In general, the data are consistent in continuing to indicate that families of children with ID report higher stress regardless of the source, and this seems true whether the respondent is the mother or father (Baker et al., 2003; Dyson, 1997; Roach, Orsmond, & Barratt, 1999). Of greater interest, however, are those studies that examined contrasts between the mothers and fathers of the children with ID, and those few studies do not provide such a consistent picture. Indeed, a number of studies indicate that mothers and fathers differ on some dimensions of stress (Nachshen, Woodford, & Minnes, 2003; Trute, Hiebert-Murphy, & Levine, 2007); but there are many other studies that suggest more similarity than difference between parents (Dyson, 1997; Girolametto & Tannock, 1994; McCarthy, Cuskelly, van Kraayenoord, & Cohen, 2006; Rimmerman, Turkel, & Crossman, 2003; Saloviita, Ita¨linna, & Leinonen, 2003). Perhaps the most compelling and comprehensive data to date contrasting stress in mothers and fathers of children with ID have emerged from the Early Intervention Collaborative Study. In their 2001 monograph, HauserCram et al. examined parenting stress over time along two dimensions (child-related and parenting related) for both mothers and fathers of children with ID. Exemplifying notions of the new complexity, Hauser-Cram et al.
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explored the developmental trajectories of parental stress across early preschool ages to child age 10, as well as detailing factors that differentially account for maternal and paternal stressful experience. Their results indicated that although mothers and fathers shared some elements of stressful experience in the context of the risk associated with ID (increasing child-related and parent-related stress), the rates at which the stresses increased and the multiplicity of factors associated with the increases frequently differed for mothers and fathers. Indeed, moderators of stressful experience were somewhat different not only between parents, but at different time points in children’s development, suggesting the clear advantage of longitudinal perspectives for capturing the true complexity of parental well-being in the context of risk. These findings suggest the need to account for fathers’ and mothers’ experiences separately: Although they certainly share some perspectives, there are many ways in which the two diverge to create unique parenting contexts for children with ID. Data from CFS can also be brought to bear on the issues regarding stress, adding to the base of information that not only details contrasts between mothers and fathers of children with ID at certain developmental periods, but also across the critical 3-year transitional period for children and families (child ages 3–6) that represents preschool through the transition to school age. It is important to note that the findings from Baker et al. (2003) mentioned above represent CFS data, but these findings specifically address stresses associated with family impact at two times points during the preschool period, and mother–father contrasts were not specifically drawn. Here, we extend our approach with stress measurements over time that addresses the everyday minor stresses of childrearing that have proven across a variety of studies to have immense adaptational significance for parents (Crnic & Low, 2002). Portions of the stress data we report here have been specifically addressed in other work (see Gerstein et al., 2009). For this chapter, we have extended our measurements beyond the three measurement points (ages 3–5) in the Gerstein et al. (2009) report to a fourth measurement period at age 6 years. Tables 1.1 and 1.2 provide the means and standard deviations for all parenting constructs that we will discuss. The findings regarding daily parenting stress factors are straightforward and compelling. First, across the four measurement periods, there are no significant differences on daily hassles between parents of children with ID and those that are typically developing regardless of whether the parent is a mother or father (see Table 1.1). Risk, then, does not differentiate the daily hassles of parenting across the preschool to early school-age developmental period. However, within-group comparisons between mothers and fathers tell quite a different story. After age 3, mothers and fathers of children with ID differ from one another such that mothers report significantly more daily hassles of parenting than do fathers (see Table 1.1). Of interest, mothers and fathers of typically developing children show exactly the same pattern (see Table 1.1).
Table 1.1 Results of individual t-test comparisons across typically developing (TD) and developmentally delayed (DD) status groups (parent report measures) 36 months TD
Parent daily hassles Mother 45.18 (9.85) Father 43.36 (9.46) Well-being Mother 20.25 (19.31) Father 18.44 (15.78)
48 months
60 months
72 months
DD
t
TD
DD
t
TD
DD
t
TD
DD
t
47.00 (13.87) 44.19 (12.76)
1.05
47.28 (10.46) 43.73 (11.50)
49.92 (14.76) 43.98 (14.93)
1.43
47.21 (10.76) 43.04 (10.54)
50.18 (13.95) 46.33 (13.64)
1.64
47.08 (11.04) 43.13 (9.30)
50.37 (15.02) 45.65 (13.16)
1.71
23.00 (18.36) 16.38 (13.83)
0.98
20.21 (18.93) 17.69 (15.69)
26.65 (23.32) 16.62 (15.25)
2.05*
22.35 (19.39) 20.40 (18.50)
26.85 (24.54) 16.17 (15.03)
1.39
18.75 (16.73) 16.44 (15.28)
22.96 (21.75) 17.67 (18.81)
1.45
0.48
0.85
0.12
0.43
Note. Bolded means for fathers indicate significant differences from paired maternal factor; *p < 0.05.
1.70
1.51
1.38
0.44
Table 1.2 Results of individual t-test comparisons across typically developing (TD) and developmentally delayed (DD) status groups (observed parenting variables) 36 months TD
48 months DD
Opportunity for interaction Mother 4.03 4.11 (0.83) (0.78) 4.08 Father 3.92 (0.86) (0.92) Detachment Mother 2.43 2.71 (0.84) (1.01) Father 2.71 2.98 (1.03) (1.13) Positive parenting Mother 7.71 7.03 (2.22) (2.15) Father 7.04 6.49 (2.43) (2.17) Negative parenting Mother 3.01 3.06 (0.78) (0.93) Father 2.67 2.73 (0.69) (0.55)
60 months
72 months
t
TD
DD
t
TD
DD
t
TD
DD
t
0.71
3.93 (0.78) 3.56 (0.97)
4.02 (0.74) 3.36 (1.04)
0.78
3.78 (0.82) 3.49 (1.09)
3.83 (0.87) 3.20 (1.25)
0.36
3.48 (0.90) 3.10 (1.04)
3.65 (0.92) 3.12 (1.20)
1.28
2.45 (0.93) 2.82 (0.96)
2.49 (0.85) 2.89 (1.06)
2.40 (0.94) 2.77 (1.12)
2.49 (0.97) 2.92 (1.22)
2.55 (0.97) 3.25 (1.13)
2.54 (0.96) 3.02 (1.19)
7.04 (2.07) 6.37 (1.99)
6.84 (2.05) 6.00 (2.13)
6.72 (1.89) 6.23 (2.16)
6.29 (2.22) 5.72 (2.26)
6.50 (1.94) 5.48 (1.92)
6.38 (1.82) 5.75 (2.24)
2.95 (0.87) 2.53 (0.58)
3.15 (0.98) 2.62 (0.54)
2.94 (0.99) 2.59 (0.82)
3.62 (1.37) 2.83 (0.98)
3.23 (1.13) 2.57 (0.66)
3.56 (1.20) 3.07 (1.02)
1.19
2.09* 1.59
2.10* 1.46
0.43 0.51
1.26
0.34 0.40
0.63 1.15
1.45 0.96
Note. Bolded means for fathers indicate significant differences from paired maternal factor; *p < 0.05, **p < 0.01.
1.53
0.62 0.77
1.45 1.40
3.88** 1.65
0.12
0.09 1.20 0.42 0.78
1.89 3.65**
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To examine the complexity of these stress factors and their relations across time, as well to examine all of the other parenting variables in this chapter, latent growth curves for mother and father stress, well-being, and parenting behaviors were developed. Latent growth curve modeling (LGCM) is an analytic technique that combines aspects of confirmatory factor analysis and structural equation modeling (Curran, Stice, & Chassin, 1997). LGCM is an ideal tool for the current longitudinal study as it maps how variables change over time (Muthe´n, 2002). LGCM creates two latent variables representing the growth curve for each individual: an intercept (initial value), and a slope (rate of change over time). LGCM requires at minimum three waves of data to estimate linear growth curves, with curvilinear and quadratic growth estimations possible when four or five data waves are used, respectively. Given that the current study included four data waves, it was possible to test curvilinear growth models. However, given the small amount of existing literature on change in parenting over time, growth curves of parent variables were expected to obey more linear than curvilinear trajectories. Indeed, it would be of additional interest to explore the possible curvilinear or quadratic nature of parenting trajectories in future research; however, such approaches were beyond the scope of the current study. Longitudinal growth models of parenting stress produced significant intercepts for both mothers and fathers, and significant slope for mothers. These are presented in Table 1.3 for each factor of interest. Intercept values were set to reflect the initial stress measurement period at child age 3, and the stress slopes are of most interest as they indicate the nature of change in these indices across time. For daily parenting stress, only mothers’ stress demonstrates a significant slope, indicating that their stress increases significantly across time (see Table 1.3). Father’s daily parenting stress is not only lower, but is more stable across this period (see Table 1.3). It seems apparent that stress response in parents with children with ID is multifaceted. Daily parenting stress differs from many other stress contexts for these families in that it is not a factor that differentiates the nature of risk. Parents view the daily chores of parenting and the challenges inherent in childrearing tasks similarly whether the child has a disability or does not. In contrast, parent gender does differentiate regardless of risk such that mothers perceive more daily parenting stress than do fathers across the preschool to early school-age period. But not only do mothers of children with ID experience higher daily parenting stress than fathers at most periods, their stress is also increasing over time whereas fathers’ stress is not. It is not surprising that mothers’ parenting stress is greater than that reported by fathers, as there is strong precedence for such findings as mothers continue to be primary care providers and the parenting context may yet still be more salient to mothers than fathers for the experience of parenting stress (Crnic & Low, 2002; Girolametto & Tannock, 1994; Roach et al., 1999;
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Table 1.3 Longitudinal growth curves parameters for parenting variables Intercept
Parent daily hassles Mother Father Well-being Mother Father Opportunity for interaction Mother Father Detachment Mother Father Positive parenting Mother Father Negative parenting Mother Father
Slope
47.70** 44.27**
1.07** 0.58
23.42** 16.25**
0.32 0.06
4.15** 3.92**
0.16** 0.32**
2.63** 2.96**
0.06 0.00
6.98** 6.32**
0.21** 0.26**
3.05** 2.65**
0.19** 0.09*
*p < 0.05, **p < 0.01.
Warfield, 2005). Whether there are elements specific to child disability that create conditions for fathers to perceive less daily stress than mothers remains to be determined, but it does appear that fathers and mothers are traveling somewhat separate stress trajectories as their children with ID age.
5. Parental Psychological Well-Being in the Context of ID Depression, anxiety, and distress have each been a focus of research on parents of children with ID. Of course, the implication is that the presence of such a child may create the context for such problematic responses. We have learned over the past two decades that such simple associative notions do not account for the range of parental response to children with ID. Nevertheless, a wealth of research has established the inverse connection between stress and well-being (Emerson, 2003), and there is a sizeable literature to suggest that mothers of children with ID report more depression and/or greater distress (Bristol, Gallagher, & Schopler, 1988; Fisman,
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Wolf, & Noh, 1989; Moes, Koegel, Schreibman, & Loos, 1992), although some studies indicate the conditional nature of this association (Emerson, 2003; Glidden & Schoolcraft, 2003). In families of children with ID, the nature of parent’s experience of distress across time is not clear, nor is it obvious that fathers and mothers share such experience to any degree. A few recent studies that include data on fathers and mothers have begun to address the issues, but findings conflict to some degree on the contrasts between mothers’ and fathers’ psychological well-being. Olsson and Hwang (2008) explored parental well-being in Swedish families of children with ID and found that mothers reported less well-being than fathers as well as less well-being than mothers of typically developing children. In contrast, however, Ha, Hong, Seltzer, and Greenberg (2008) reported no differences in well-being between mothers and fathers of children with ID in data extracted from a population-based study (Study of Midlife in the United States) despite similar findings that both parents of children with ID report less well-being than parents of typically developing children. The divergence in findings with respect to mothers and fathers of children with ID may reflect major design, measurement, and sampling differences between these two studies, but both contribute substantially to the emerging new complexity in understanding parent and family adaptations. Olsson and Hwang (2008) indicate that the connection between the presence of a child with ID and lower well-being was mediated by health issues for the mothers and the presence of economic hardship. Further, the inclusion of protective factors increased the predictive power of models for well-being of both mothers and fathers. Ha et al. (2008) found that parental age was a critical moderator of well-being, as younger parents reported less well-being that did older parents. Other recent work from the EICS has likewise contributed to creating more complex understandings of parental well-being. The importance of higher-quality marital relationships for parental well-being was demonstrated by Kersh et al. (2006), as both mothers and fathers reporting higher marital quality also demonstrated greater well-being (fewer depressive symptoms) in families of children with ID. But adding support to the need to address both fathers and mothers in research models of families of children with ID, parenting efficacy was differentially predicted. For mothers, marital quality was key while for fathers, greater social support predicted increased parenting efficacy. In a study of both adoptive and birth parents of children with ID (both mothers and fathers), Glidden, Billings, and Jobe (2006; Glidden & Jobe, this volume) demonstrated that parental coping strategies predicted levels of parental well-being, and do so somewhat differently for mothers and fathers. Parents’ use of positive reappraisal strategies was related to higher well-being whereas the use of escape-avoidant strategies predicted lower well-being, but for mothers only. These recent studies that include fathers in the research models expand our understanding of the complexity of parent psychological response in the
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presence of a child with ID. However, despite suggestions that developmental change may be operative, there remains little empirical attention to the ways in which well-being can be understood across time. Emerging data from CFS begin to fill this void, and suggest indeed that there may well be developmental processes operative. Data in Table 1.1 show that fathers and mothers of children with ID are actually quite similar to parents of typically developing children with respect to their reported well-being over time, with the single exception of maternal well-being at child age 48 months. With respect to contrasts between mothers and fathers of children with ID, mothers and fathers differ in well-being at child ages 4 and 5, but not at 3 and 6. Fathers consistently report more well-being (i.e., fewer psychological symptoms) than mothers at each period, but the differences are especially dramatic when children are 4 and 5 years of age (see Table 1.1). But whereas these contrasts suggest that differences across developmental periods exist for fathers and mothers, the latent growth curve analyses suggest that neither father nor mother well-being changes significantly in any direction over this 3-year period of time, as evidenced by nonsignificant slope parameters across parent genders (see Table 1.3). Parental well-being in the context of child risk is certainly a complex phenomenon that is not yet entirely understood. Variations in study findings that address group differences (ID vs typically developing samples) as well as those few studies that address contrasts between mothers and fathers in families of children with ID suggest that the nature of parental well-being is indeed characterized by complexity, but differences in study methods and samples further complicate the picture. Minimally, in families of children with ID, there are indications that mothers and fathers do differ in their well-being during early childhood, but early indications are that these differences are mediated and moderated by a number of salient individual and contextual conditions (Emerson, 2003; Glidden et al., 2006; Olsson & Hwang, 2008).
6. Parenting Behavior with Children with ID One area that lags far behind others with respect to families of children with ID are studies of the quality of actual parenting behavior with the children. This is especially true regarding studies in which fathers’ behavior is involved. Of course, such work is expensive, time consuming, and complex to execute. Nonetheless, few methods provide more validity and depth in understanding the true nature of parenting. Whether the approach to observation is naturalistic or structured, observations of parenting offer a valuable window through which to gauge parenting across a broad range of child rearing contexts and challenges.
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6.1. Previous research The history of observational studies of parenting in families of children with ID, like each of the areas we have discussed, is primarily a study of mothering. One notable exception to this rule is an impressive study by Floyd, Costigan, and Phillippe (1997) in which not only were mothers and fathers a key part of the observational protocols, but the observational measurement was longitudinal over a 2-year span. Floyd et al. (1997) found considerable similarity between mothers’ and fathers’ interactions with their children as no significant differences emerged for the proportions of commands and noncompliance, positive and negative behaviors, and for the levels of positive and negative reciprocity between mother–child and father–child interactions at either of the measurement periods. There was generally moderate stability in parenting behavior over time in this schoolaged sample for both mothers and fathers. The only major difference that emerged was that mothers were much more involved with their children than were fathers. Earlier, Girolametto and Tannock (1994), in a study of 20 married couples, had also reported many similarities between mothers and fathers in interactive behavior with their children with developmental delays. Fathers differed from mothers, however, along some dimensions of behavioral directiveness in that they used more topic control and response control with their children. Recently, de Falco, Esposito, Venuti, and Bornstein (2008) studied father–child play interactions with children with Down syndrome. Applying the emotional availability scales (Biringen, Robinson, & Emde, 1998) to the observed interaction sequences to index the affective quality of the interactions, these investigators found that father play was associated with more child exploration and symbolic play. Further, fathers and children representing high emotional availability were more likely to show more symbolic play and less exploratory play than were those dyads with low emotional availability. Although the findings to date addressing father behavior are instructive, there has been far too little exploration of fathers’ interactive behavior with children with ID. Certainly, there seem to be clear similarities with mothers, but there are also a myriad of reasons to suggest that father behavior may be different across time and context (Lamb, 2004). Data from CFS provide not only comparisons between mother behavior and father behavior, but allow for exploration of the stability and continuity of fathering behavior across the critical transition period from preschool to early school age.
6.2. Behavioral trajectories in CFS We will focus on four dimensions of parenting behavior: opportunity for interaction, detachment, positivity, and negativity. Each of these behaviors was rated during naturalistic in-home observations that lasted approximately
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1.5 h. Ratings were made after observing 10 min of interaction, and each behavior was rated on a five-point scale that ranged from low on the dimension to high. Opportunity for interaction reflected the degree to which parents put themselves in the position to have opportunities to engage the child, and therefore was similar in nature to parental involvement. Detachment addressed the degree to which, given the opportunity to be engaged, parents paid relatively little attention to the child, were not responsive or reactive to child behavior, and seemed affectively disengaged. Positivity and negativity reflected the extent to which these affective approaches to the child characterized the emotional tone of the interaction. Comparative data are presented in Table 1.2. Our data indicate that both mothers and fathers of children with ID behave similarly with their children to mothers and fathers of typically developing children across this developmental period with a few notable exceptions. Mothers of children with ID were somewhat more detached and less positive at age 3 than were mothers of typically developing children, and were significantly more negative at 60 months. Fathers of children with ID were significantly more negative than their father counterparts when children were age 6. In contrast to the relative few, albeit important, comparative differences between risk groups, mother–father differences were quite a bit more dramatic across this developmental period. Focusing expressly on parents of children with ID, fathers were substantially less involved than mothers after age 3, were less positive at some periods (i.e., ages 4 and 6), and were more detached when the children were age 4 (see Table 1.2). Although this may not seem an encouraging portrayal of fathers of children with ID, fathers were significantly less negative than mothers at each time period. Further, fathers of typically developing children in our study show a nearly identical pattern of differences from mothers, with the exception that fathers of typically developing children show significantly more detachment at every period and are likewise less positive than mothers at every period (see Table 1.2). Data from our latent growth curve analyses, presented in Table 1.3, are relevant again here. The intercepts were set at age 3 and all were significant, indicating that initial values of each observed variable were above zero. However, the slope values are of most interest for they represent change over time in each observed variable. Indications are that both mothers and fathers show significant decreases in positivity across time, increases in negativity, and decreases in opportunity for interaction. Detachment did not produce meaningful growth curves, indicating rather stable functioning across time. Analyses testing the difference between the latent growth curves across parent gender indicated that initial values of father and mother opportunity for interaction did not differ (recall that intercepts were set to age 3 values), but fathers’ involvement decreases more steeply than does mothers’ over the 3-year period (see Table 1.3). In contrast, fathers are significantly less negative overall (at age 3), and their negativity shows a
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tendency to decrease somewhat less steeply than does mothers. Mothers are more positive than fathers overall (at age 3), but the trajectories of positivity do not differ between mothers and fathers of children with ID.
6.3. Conclusions regarding father interactive behavior No simple conclusions can be drawn as there is simply too little empirical information available about fathers’ behavior in families of children with ID and there is not sufficient consistency in the studies that are available. Nonetheless, it appears as though fathers and mothers share some fundamental similarities in their parenting behavior, but there are behavioral domains in which differences are present as well. What does seem to emerge is that fathers show less involvement, and that seems to be the case across developmental periods (early childhood through adolescence) and across risk status (fathers of typically developing children are less involved and more detached as well). In the population of families with typically developing children, fathers remain less involved than mothers, and that relative difference remains the same across development (Yeung et al., 2001). The lesser involvement apparent across risk conditions or populations would therefore suggest that fathers are not reacting to the ID per se. Mothers may be gatekeeping parenting roles (Allen & Hawkins, 1999), or fathers may perceive that children require less from them as they age and become more competent. However, lower levels of father involvement do not necessarily indicate that fathers are less competent parents than mothers. It should also be noted that in the CFS project, the vast majority of observational coders were women. While not evidencing a clear bias given the reliability standards that were consistently met, it is nevertheless the case that our coders’ internal models of caretaking may have been more favorably skewed toward quality in mothering as opposed to fathering. Research indicates that although fathers may not contribute at the same rate to caregiving activities, when they do they are competent care providers (Ladd, Profilet, & Hart, 1992). Regardless, the way that child risk may affect fathering remains far from well understood. Recent empirical efforts have begun to explicate both the nature of fathers’ behavior with their children with ID and explore the mechanisms that underlie mother–father differences, but much effort is still needed to further clarify the nature and function of father–mother behavioral differences.
7. An Integrated Perspective Stress, well-being, and parenting behavior are all key factors in parental functioning and have each been studied widely in the context of families of children with ID. Each has also been implicated in processes that determine
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family adaptation (Blacher & Baker, 2002), and eventually children’s developmental competencies across a range of functional domains (Hauser-Cram et al., 2001). But the near exclusive focus on mothers as representatives of ‘‘parenting’’ has been a major limitation in the study of family adaptation and belies the full range of influences that operate to affect children’s developmental functioning over time. The inclusion of fathers in studies of families of children with ID recognizes the important complexity in processes addressing the multifinality inherent in family adaptation and function. Attention to fathers across the range of key parenting attributes affords the opportunity to build more comprehensive models that facilitate a greater understanding of the complex developmental factors to which high-risk children are exposed and to which families must respond across time. Further, the inclusion of fathers allows us to potentially expand research with families of children with ID into related systemic constructs such as coparenting (McHale, Khazan, Errera, Rotman, DeCourcey, et al., 2002) and crossover influences (Gerstein et al., 2009; Hauser-Cram et al., 2001). Certainly, findings from the few studies to date that address fathers of children with ID, as well as the CFS findings we have shared in this volume, suggest that we cannot treat parenting in families of children with ID as uniform across parameters of gender, construct, or time. Complex patterns of parenting emerge through comparisons with parents in families of typically developing children and between fathers and mothers in families of children with ID. What appears to stand out in the research to date is that there is both tremendous variability and similarity in father and mother experience in families of children with ID. Across constructs of stress, well-being, and parenting behavior, considerable similarity exists between fathers’ and mothers’ experience relative to parents of typically developing children; perhaps more so than would be anticipated given the history of research in this arena. In the CFS data presented, fathers of children with ID differed from fathers of typically developing children on only a single dimension of the 24 contrasts that were examined (negativity at child age 6). That level of difference is at the level of chance occurrence. Contrasts between groups of mothers produced a total of four significant differences; certainly above chance levels but again less than might be expected. While the between-group differences are instructive, it is the withingroup father–mother comparisons that are the primary interest of this chapter. In this regard, the evidence again points to complexity in the nature of parenting differences between mothers and fathers. Certainly, the studies to date suggest that fathers are more similar than different to mothers along dimensions of stress, well-being, and even behavior (e.g., Ha et al., 2008; Hauser-Cram et al., 2001; Rimmerman et al., 2003; CFS data presented here). Yet, there are important differences that are apparent as well that can be seen in the CFS data we have reported here and in the
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rather limited published research that exists. Fathers appear somewhat less stressed than mothers, particularly in family-related contexts (Baker et al., 2003; Hauser-Cram et al., 2001), report higher well-being in some cases (Olsson & Hwang, 2008), but also seem to be somewhat less involved in parenting (Floyd et al., 1997) than are mothers of children with ID. In the EICS data, fathers’ stress increased at a greater rate than did mother parenting stress (Hauser-Cram et al., 2001) but data from the CFS that we have presented here found the opposite across similar developmental periods. The inconsistencies across the available research are somewhat vexing, but given the dearth of research these may reflect variations in samples, method, measurements, and developmental periods that have been the focus of inquiry. The lack of reliability apparent across findings may indeed resolve when additional studies are available to replicate the early work which has been done. Previously in this chapter, we raised the notion of a ‘‘new complexity’’ in the approach to understanding parenting and family adaptation. This new complexity operates at the level of design and methodology as well as basic conceptualizations of multiple processes that describe and determine parent functioning. It is precisely these complex processes that likely help explain apparent similarities and differences between fathers and mothers as well as how differences in parenting will influence children’s developmental competencies. More thoughtful studies and approaches are emerging, and are exemplified by the work of Hauser-Cram and colleagues (Hauser-Cram et al., 2001; Kersh et al., 2006; Mitchell & Hauser-Cram, 2008) in identifying developmental pathways in families of children with ID; Emerson (2003, this volume) and Olsson and Hwang (2003, 2008) in explicating complex social economic models; Floyd and his colleagues in their multimodal multimethod longitudinal study of mothers and fathers (Floyd et al., 1997; this volume); Glidden’s work in contrasting adoptive and birth parents as a natural experiment context for variation (Glidden et al., 2006; this volume); Seltzer and her colleagues on life-span perspectives in families of offspring with ID (Ha et al., 2008; Seltzer, Floyd, Greenberg, Lounds, Lindstromm, et al., 2005); and our own work addressing early family contributions to children’s regulatory capacities and emerging behavior problems (Baker et al., 2003; Baker, Fenning, Crnic, Baker, & Blacher, 2007; Crnic, 2001). The list above is certainly not exhaustive, but each of these programs of research address sophisticated developmental processes that describe not only the multifinality inherent in the study of these families and children but a variety of mediational and moderational mechanisms of effect across time that determine the nature of the multifinal outcomes. Consistent with the best of basic developmental and contextual theories (Lerner, 2002; Sameroff, 2000), these approaches are in-line with Guralnick’s (2001) developmental systems perspective for addressing family and child
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functioning for children with ID. Surely the work included above and presented herein suggests that we can no longer accept simple main effect models of influence to understand the nature of parenting. Nor can we accept these approaches to explain differences between mothers and fathers of children with ID and the implications of those differences for children with ID. Important moderators and mediators exist that explicate underlying mechanisms of effect. Indeed, it is tempting to posit an array of intervening variables that may meaningfully predict these unique trajectories of mothering and fathering. The list is potentially enormous; and might include socioeconomic status, child gender, child behavior problems, or diagnostic status; teacher perceptions and feedback, resource availability, and available coping mechanisms among many others. But rather than specifically address these vital questions, we have sought in this chapter to raise the questions of whether mothers and fathers indeed show unique trajectories of adaptation. Next, it will be critical to continue to identify the most salient factors in the family system that drives these differentiations. In contrast, where mothers and fathers show similar development of parenting over time, it will be important to identify those family factors that determine the importance of such synchrony for family and child adaptations over time? Meaningful examination of these and other important questions requires new and rigorous empirical inquiry into longitudinal perspectives that address the multiple pathways of influence that operate to explain the breadth and variety in parent, family, and child adaptation.
8. Summary and Conclusions CFS represents a specific attempt to address these new complexities in family models in relation to prediction of children’s problematic behavior and developmental competencies across the early to middle childhood period. We have presented here longitudinal data with four measurement points across a critical 3-year transitional period in children’s lives. In presenting growth models of stress, well-being, and parenting behavior, we have attempted to focus attention on both the dynamic and divergent nature of parenting over time for fathers and mothers of children with ID. Transactional theory suggests that different factors exert their influence on development at different points in time, and such processes seem to be reflected in the variability of differences between parents along each of the time periods assessed. It remains to our future efforts to pursue the implications of these transactional processes for the well-being of children with ID and their families.
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ACKNOWLEDGMENTS Research presented in this report was supported from a grant from the National Institutes of Health, NICHD (#34879), Keith Crnic, principal investigator, and Bruce Baker, Jan Blacher, and Craig Edelbrock as co-PIs.
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C H A P T E R
T W O
The Transition to Adulthood for Individuals with Intellectual Disability Frank J. Floyd,* Catherine L. Costigan,† and Vivian E. Piazza* Contents 32 32 34 37 37 37 38 40 40 42 42 48 50 51 54 58 58
1. Introduction 1.1. Transition to adulthood 1.2. Previous research 1.3. Purpose of present study 2. Method 2.1. Family interaction project 2.2. Participants 2.3. Procedures 2.4. Measures 3. Results 3.1. Moderate versus mild intellectual disability 3.2. Behavior problems in childhood 3.3. Gender 3.4. Perceptions of adulthood 4. Discussion 5. Conclusion References
Abstract The transition to adulthood is a potentially formative period of the life course for individuals with intellectual disability. In this investigation, we examined the transition using traditional criteria for launching and role functioning and also explored how the concept of emerging adulthood applies to young adults who have intellectual disability. The targets were 140 young adults (ages 18–33 years, mean ¼ 24 years) who participated in a long-term follow-up of a longitudinal investigation of family and child development for children with mild
* {
Department of Psychology, Georgia State University, Atlanta, Georgia 30302-5010, USA Department of Psychology, University of Victoria, STN CSC, Victoria, British Columbia V8W 3P5, Canada
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37002-0
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2009 Elsevier Inc. All rights reserved.
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and moderate intellectual disability. Overall, there was limited evidence of launching and financial independence for the young adults, with most living with parents and few able to support themselves financially. As expected, greater progress toward independence occurred for individuals with mild as opposed to moderate intellectual disability. However, relatively few adult outcomes were predicted by childhood behavior problems, and there were few gender differences. Despite this situation, most of the parents reported that the target individual had ‘‘reached adulthood’’ and, similar to normative samples, they focused on criteria for adulthood that emphasized independent thought and free choice over role transitions and financial independence. The findings suggest an expanded view of emerging adulthood for individuals with intellectual disability who are transitioning into adulthood characterized by interdependence rather than independence.
1. Introduction 1.1. Transition to adulthood The transition from adolescence to young adulthood is a challenging period of life for most young adults, and it may be uniquely difficult for individuals with intellectual disability. The transition is traditionally viewed as a developmental task for which the major challenge is individuation and establishing independence from the family of origin (Erickson, 1968). Along with ‘‘launching’’ from the family, the period is usually associated with role transitions that include the completion of formal schooling, financial independence, and a shift in attachments to a new family with marriage and parenthood. Although these life events are normative for typically developing young adults, they may be unattainable for individuals with intellectual disability who have significant limitations in cognitive abilities, social skills, and independent life skills, and who rely on substantial supports in their daily lives. More commonly, however, individuals with mild intellectual disability are generally expected to attain some degree of independent functioning despite the limitations associated with their disability and with limited supports (Tymchuk, Lakin, & Luckasson, 2001). Research has documented the difficulties experienced by adults with intellectual disability, but there is relatively little information about the transition to adulthood for these individuals as a potentially formative period of the life course. The meaning of this transition also is complex for the parents of individuals with intellectual disability. Parents face dilemmas over conflicting expectations about decreased involvement along with the need to provide ongoing guidance and care to the young adult (Thorin, Yovanoff, & Irvin, 1996). As the parents age, caregiving for adult children with developmental disabilities can subject parents to financial and occupational stress, and can make them vulnerable to poor health and diminished psychological
The Transition to Adulthood for Individuals with Intellectual Disability
33
well-being (Heller, Caldwell, & Factor, 2007). However, parents also report anticipated rewards associated with their children’s transition to adulthood, including optimism about success in living out of the family home, and positive feelings about family relationships (Glidden & Jobe, 2007; Jobe & Glidden, 2008). Also, in a longitudinal study of adolescents and young adults with an autism spectrum disorder, two-thirds of whom also had intellectual disability, mothers reported that both the quality of their relationships with the child and their own psychological well-being improved over time (Lounds, Seltzer, Greenberg, & Shattuck, 2007). Furthermore, although it was expected that the transition of completing high school would be stressful for the mothers because of increased care demands, instead, this event predicted improvement in the mothers’ psychological functioning over time. Thus, for many parents, anticipated negative outcomes might not be realized. In contrast to the traditional developmental stage models, recent developmental theory and research on the transition to adulthood has identified an interim period between adolescence and adulthood, spanning the decade of the 20’s, during which adulthood is emerging, but not yet attained. Arnett (2000) contends that emerging adulthood is a separate stage of development that has unique characteristics from both adolescence and adulthood. Most notably, it is a period of identity exploration in which individuals test out a world view, consider various occupational identities, and explore feelings about intimate love and commitment. The period is characterized by instability and change in the form of frequent transitions in residence, relationships, work, and education. Individuals in this stage see their lives as having open possibilities, with various directions available to them. The focus for the individual is on the self, with limited obligations to others. Individuals in this period report feeling in between adolescence and adulthood. That is, when asked to report whether they have achieved adulthood, the majority of individuals in their late teens and early twenties say that this event has not occurred or has occurred only partially, even when they have moved from the parents’ home, completed school, taken full-time employment, and established some degree of independence (Arnett, 2001). Consistently, in a study of parents of college students (Nelson, Padilla-Walker, Carroll, Madsen, Barry, et al., 2007), most parents also reported that their son or daughter had not yet fully reached adulthood. The construct of emerging adulthood challenges traditional notions of young adulthood and raises questions about the criteria that serve as indicators that adulthood has been achieved. For example, Arnett (2001) asked various age groups to endorse indicators of adulthood from a list of 38 possible criteria gleaned from developmental literature and pilot studies. The most frequently endorsed criteria were consistent across samples of teens, young adults, and adults in midlife. These groups indicated that adulthood is demarcated most notably by ‘‘individualism,’’ reflected in
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qualities of character, including accepting responsibility for one’s behavior, independent decision making, deciding on one’s beliefs and values, financial independence, and establishing a relationship with parents as an equal adult. All groups also endorsed the capacity to raise children and care for a family as an important indicator of adulthood, though the physical ability to bear or father children was infrequently endorsed. Middle-aged respondents in this study concurred with younger samples from earlier studies, but also added norm compliance, such as avoiding drunk driving, as a criterion. The most striking feature of this research is that the above factors were contrasted with chronological age or traditional notions of role transitions, such as finishing school, taking full-time employment, marriage, and parenthood, which received the lowest rates of endorsement by all three age groups. Furthermore, the Nelson et al. (2007) study of parents of college-age children found that the most frequently endorsed indicators by parents of young adults were similar to those endorsed by the young adults about themselves, though the importance ratings differed somewhat. Thus, there appears to be considerable consensus as to the criteria for achieving adulthood. Despite these consistent findings across groups, the notion of emerging adulthood and the criteria for achieving adulthood might differ greatly for young adults who have intellectual disability. Having studied mostly U.S. college student samples, Arnett (2000) acknowledged that this period of exploration might be limited to particular cultures and particular socioeconomic circumstances that can afford a prolonged period of development before fully assuming adult responsibilities. It might also apply only to individuals with average or above intellectual functioning who are encouraged to introspect about issues of identity, personal beliefs, and values and also have opportunities to pursue these interests. Individuals with intellectual disability may instead be encouraged to assume more conventional, prescribed beliefs and standards. They also may live in restricted settings in which there is less opportunity to develop and pursue personal preferences. Accordingly, compared to college students, expectations about independence and individualism might be different for young adults with intellectual disability, as they probably are not judged by the same standards. In particular, there likely is an expectation for much more connectedness with family and other caregivers who provide support, and a goal such as establishing equality in relationships with parents might not be relevant. Thus, it seems likely that the markers of having achieved adulthood would differ given the limited opportunities for functioning without supports.
1.2. Previous research Although there is limited research on how individuals with intellectual disabilities experience the transition to adulthood, some important relevant findings come from longitudinal studies of development from childhood to
The Transition to Adulthood for Individuals with Intellectual Disability
35
adulthood. Most notably, Richardson and Koller (1996) summarized the findings from a study of the cohort of children from Aberdeen, Scotland who were followed-up when the participants reached 22 years old. Schooling for this cohort ended at age 15–16 years, so they had been out of school and were expected to move into employment and other adult roles for the past 7 years. The entire sample was divided into those with ‘‘severe’’ versus ‘‘mild’’ intellectual disability as children, which was roughly equivalent to obtaining IQ scores below or above 50. The majority of the severe group remained in the disability service system and, thus, they were not followed further to examine young adult roles because their lives were highly restricted. Among the participants with mild intellectual disability, approximately two-thirds were not placed in MR services and most had worked after leaving school. However, compared to a typically developing sample matched for similar background characteristics, the mild disability group had spent more time unemployed, they had more job turnover, and they spent more time out of the labor force due to injury or serving time in prison. Among this group, 26% of the men and 52% of the women had married, and most married individuals had one or two children, rates that were similar to the comparison group. Nevertheless, the authors reported that there was more evidence of marital problems among individuals with intellectual disability, which were related to financial, employment, and sexual difficulties. Having married was related to higher IQ scores, and among those never married, only 20–25% were involved in opposite-sex relationships. In addition to describing young adult functioning, a goal of the Richardson and Koller research was to predict adult functioning from demographics and earlier childhood functioning. There were some differences in adult functioning for men and women, with women twice as likely to marry and men more likely to experience work injuries or imprisonment. More notably, the predictive findings isolated childhood level of intellectual disability and the presence of childhood behavioral disturbances as later predictors of adult functioning. Among the entire sample with severe and mild disability, level of intellectual functioning and the occurrence of behavioral disturbances were stable from childhood to adulthood. Thirty-seven percent could be diagnosed unequivocally with intellectual disability in adulthood, 45% showed some impairment in one or more areas of adaptive functioning, and only 18% showed no evidence of intellectual disability. Among those who had only mild intellectual disability, those who also had significant behavior disturbances as children were more likely to need supportive services as adults. However, among those not receiving adult services, adult functioning in most domains, such as employment, marriage, and social functioning, could not be predicted from childhood characteristics. Thus, the effects of childhood intellectual functioning and behavior disturbance accounted for being tracked into relatively sheltered
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Frank J. Floyd et al.
versus relatively independent adult lives, but they did not account for the quality of role functioning for those who took on independent adult roles. In a smaller study with a US sample, Bernheimer, Keogh, and Guthrie (2006) reported similar patterns of young adult functioning and childhood predictors. These investigators examined predictors of developmental status, personal–social functioning, and life satisfaction at an average age of 22 years for a sample that was recruited at age 3 with unspecified developmental delays. In adulthood, 57% lived in the family home, 30% lived in a supported setting, and 13% lived independently. Developmental status was highly stable over time, in that status at age 22 was significantly predicted by status at ages 3 and 7 years. Also, poorer adaptive functioning in young adulthood was predicted by temperament and internalizing behavior problems at age 7 years. Interestingly, greater life satisfaction as self-rated by the young adults was predicted by poorer functioning in childhood in terms of lower developmental status and more behavior problems. The authors cautioned that life satisfaction does not necessarily indicate better quality of life in terms of independence and enriching experiences. However, they acknowledged that the more restrictive lives for lower functioning individuals living in supported settings might be positive in terms of pleasant living conditions and opportunities for social involvement that might be less available for those living more independent, but marginalized lives. This unexpected finding was further illuminated by the results of a longitudinal investigation by Chen, Lawlor, Duggan, Hardy, and Eaton (2006). These investigators followed-up a large (n ¼ 1681) sample that had been originally recruited for a perinatal study, 86 of whom had intellectual disability and 178 of whom had borderline intellectual functioning at age 4. The participants were 27–33 years old at the follow-up. As expected, individuals with intellectual disability or borderline functioning as young children had more emotional and behavioral problems in adulthood than those with average and higher IQ scores. Similar to the pattern in the Bernheimer et al. (2006) study, the borderline group exhibited more adult problems than the individuals with lower cognitive functioning who were identified as having intellectual disability. The authors drew similar conclusions about possible greater life stress and difficult challenges for individuals who are expected to manage typical adult roles, but do not have the ability or supports needed for success. Together, these investigations raise important questions about possible unique experiences in the transition to adulthood for individuals with intellectual disability. The research findings suggested that young adults with intellectual disability fall below normative expectations for independence and role assumption in making the transition to adulthood and, as such, the transition might be considered incomplete. However, the studies did not consider how the stage of emerging adulthood might apply to these young
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37
adults, possibly with unique characteristics from normative samples. For example, in focusing on role transitions and functioning in adult roles as criteria for obtaining adulthood status, the research has not considered the personal individualism criteria identified as paramount in normative studies of emerging adulthood. Another consistent finding was that both the level of intellectual disability and the presence of significant behavior problems in childhood are stable characteristics that can affect whether individuals are able to assume adult roles. However, it is unknown whether these characteristics also predict other individualism factors that are part of the adult transition.
1.3. Purpose of present study The purpose of the present study was to investigate the transition to adulthood for individuals identified in childhood with mild or moderate intellectual disability using both traditional criteria for launching and role functioning and also exploring whether criteria associated with individualism, as identified in studies of emerging adulthood, are applicable to this group. In particular, we examined whether within a fairly narrow range of mild and moderate levels of intellectual disability, the level of disability and the occurrence of childhood behavioral disturbances predicted progress in the transition to adulthood. We expected that those with mild intellectual disability and those without a history of behavior problems would be likely to attain higher levels of independence in adulthood. Based on suggestive findings about possible gender differences in the Richardson and Koller (1996) study, we explored possible gender differences in the outcomes. In addition, we examined the extent to which individualism criteria, such as making decisions based on personal standards and values, were identified as criteria for adulthood and their relative importance in relation to traditional indices of adult role transitions.
2. Method 2.1. Family interaction project The Family Interaction Project is a longitudinal study of child and family adaptation and family influences on the development of children with mild and moderate intellectual disability. The initial wave of data collection, Time 1, occurred in 1988–1989, when a sample of 171 families with a 6–18-year-old child with intellectual disability (the target child) was recruited for the study. They completed measures of family relationships, stress and coping, and individual functioning for the family members. At Time 2, in 1990–1991, approximately 18 months after the initial
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assessment, the families completed the same battery of measures. A 5-year follow-up assessment was conducted at Time 3, 1993–1995. At this time, an additional group of 29 families with children ages 6–12 were recruited into the study in order to provide representation for the full school-age range at that time point. Finally, at Time 4, 2001–2005, the entire sample of 200 families was targeted for a long-term follow-up. The timing for the followup averaged 13.75 years (SD ¼ 1.24) after the initial assessment for families recruited at Time 1, and 8.93 years (SD ¼ 1.09) later for families recruited at Time 3. Comparison samples of families of children without intellectual disability participated at Times 1 and 3, but were not included in the longterm follow-up and, thus, are not included in this report. The families initially were recruited into the study through mailings sent to the homes of children enrolled in special education classes for mild or moderate intellectual disability in public schools within a 100-mile radius of the university research office. Interested families returned a postcard or telephoned the research office. At the initial assessment, the families provided contact information as well as names and addresses of friends and relatives who could help to find them in the future, which was updated at each follow-up point. This information, along with updated mail records and internet-based searches, was used to locate families for the Time 4 follow-up. We were able to locate 96% of the original sample, 83% of which agreed to participate, 5.5% were unable to participate because of factors such as the death of the target child, and 11.5% declined. Compared to those who did not participate, participating families at Time 4 were more likely to have two parents living in the home, X2(1, N ¼ 191) ¼ 5.62, p < 0.01, the mother’s education was higher, t(188) ¼ 3.40, p < 0.001, and the target child was somewhat younger, t(189) ¼ 2.25, p < 0.05. There were no differences, however, in level of intellectual disability or gender of the target child, age of the mother or father, father’s education, yearly income, ethnicity, number of siblings, or length of the parents’ marriage.
2.2. Participants Caregiver interviews at Time 4 were available for 160 target individuals with intellectual disability ranging in age from 14 to 33 years old. For the current report, we restricted the sample to 140 of the target individuals who were 18 years and older because questions about the transition to adulthood were most relevant after that age. Descriptive information about the sample is presented in Table 2.1. The average age of these target individuals was 24, and approximately 60% were over age 22, which marks the end of their eligibility for formal educational services. There were approximately equal numbers of male and female target participants. At the initial data collection (Time 1 or Time 3), two-thirds were two-parent families and the average family income was $28,500 (SD ¼ $21,579). The majority of the parents
39
The Transition to Adulthood for Individuals with Intellectual Disability
Table 2.1 Characteristics of the sample
Total (N ¼ 140)
Mean target age 24.16 (3.59) at Time 4 (SD) % female 52.1% 68.8% % two-parent family at initial assessment $28,500 Mean income at (21,579) initial assessment (SD) % European American Mothers (%) 84.4 Fathers (%) 93.3 % African American Mothers (%) 11.9 Fathers (%) 3.8
Moderate intellectual disability (N ¼ 44)
Mild intellectual disability (N ¼ 96)
25.25 (3.89)
23.66 (3.35)
52.3% 79.5%
52.1% 63.8%
$29,186 (19,386)
$28,196 (22,626)
90.5 97.2
81.7 91.2
4.8 2.8
15.1 4.4
were White (84.4% of mothers and 93.3% of fathers); 11.9% of mothers and 3.8% of fathers were African American, and 3.7% of mothers and 2.9% of fathers were from another ethnic/racial background. 2.2.1. Earlier child characteristics: Level of disability and child behavior problems The level of intellectual disability for the child at the time of enrollment into the study was determined by school assessment records and enrollment in programs for children with mild versus moderate intellectual disability. The IQ score of the target as above or below approximately 55 (the standard cutoff as used in DSM-IV) was verified from the child’s most recent Individualized Educational Progress report at the time of recruitment into the study. Among the sample 18 years or older seen at the Time 4 follow-up, 68.6% of the target individuals had been enrolled in programs for mild intellectual impairment and 31.4% had been enrolled in programs for moderate intellectual impairment. There were no differences in the gender composition of these groups, X2(1, N ¼ 140) ¼ 0.98, ns, though individuals with mild disability were younger than individuals with moderate disability, t(138) ¼ 2.48, p < 0.01 (see Table 2.1). The occurrence of significant behavior problems in childhood was determined by parent and teacher reports on the Child Behavior Checklist (CBCL, parents) or Teacher Report Form (TRF, teachers) (Achenbach &
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Rescorla, 2001) at entry into the study. As recommended for determining possible clinical levels of problem behaviors (Achenbach & Rescorla, 2001), the cutoff for significant behavior problems was a t-score 63 on the internalizing, externalizing, or total problems scale as reported by either the parent or the teacher. Among the participants 18 years or older at the Time 4 follow-up, 37.1% had been designated with significant behavior problems at entry to the study, and 60.7% were not reported to have significant behavior problems. There were no differences in the target children’s gender, X2(1, N ¼ 137) ¼ 0.35, ns, or age, t(135) ¼ 0.11, ns, based on their history of behavior problems.
2.3. Procedures At Time 4, the mother (n ¼ 122), father (n ¼ 14), or primary caregiver (n ¼ 3) for the target with intellectual disability completed a 60-min telephone interview. In addition, one target individual himself (whose parents were both deceased) provided factual information for the interview, but was not administered questions about caregivers’ opinions. During the interview, demographic information was updated and information about living arrangements, work, marriage, family formation, stress, and health for the target was obtained. The interview also included questions about contact with and involvement by the other nuclear family members with the target individual. Much of the interview was based on a protocol developed by Seltzer, Krauss, Hong, and Orsmond (2001) in their research on aging mothers with adult children with intellectual disability. In addition, the follow-up assessment included batteries of questionnaires mailed to the family members and a face-to-face interview with the target, but this information was not included in the current report. As in previous waves of data collection, the participants received small monetary incentives for completing the research.
2.4. Measures 2.4.1. Time 4 independent living The questions about independent living included current residence (e.g., with parent or relative, supervised group home, independent house, or apartment), history of living arrangements, dating and marital status, and number of children for the target. The questions also covered current enrollment in school, school completion, hours spent in school, receipt of special services at school, and mainstreamed classes. Employment questions asked about current employment, history of employment, age at first job, number of jobs, length of time in jobs, participation in a structured employment setting (i.e., sheltered workshop or supported employment), and participation in a day activities program.
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41
2.4.2. Time 4 family contact and involvement Parents or caregivers reported on the frequency of contact with the target individuals. These responses were categorized as ‘‘daily or regular,’’ ‘‘weekly,’’ ‘‘monthly,’’ or ‘‘infrequently.’’ The parent or caregiver also rated the frequency of involvement of the mother, father, and focus sibling in six areas. The focus sibling was either the sibling who was nominated by the parent or caregiver as the ‘‘closest’’ to the target individual, when one existed, or otherwise was the sibling who was randomly selected as the ‘‘focus sibling’’ in earlier waves of this research. Often, the former ‘‘focus sibling’’ and the ‘‘closest sibling’’ were the same person. The six involvement items included: direct caregiving, participation in activities with target, initiation of activities with target, participation in family discussions about target, participation in decisions about target, and expressions of concern about target. Frequency ratings were made on a four-point scale, where 1 ¼ ‘‘not at all,’’ 2 ¼ ‘‘rarely,’’ 3 ¼ ‘‘sometimes,’’ and 4 ¼ ‘‘very often.’’ 2.4.3. Time 4 health and stress The reporter rated the current physical health of the target as ‘‘excellent,’’ ‘‘good,’’ ‘‘fair,’’ or ‘‘poor.’’ Stress was assessed by a list of 13 major life events such as family transitions, interpersonal problems, and deaths. The reporter indicated whether each event had occurred for the target within the past 6 years. Scores for this measure were the total number of major stressful events during this time period. 2.4.4. Perceptions of adulthood The parents who were reporters were asked the following questions about adulthood: ‘‘Do you feel that your child has entered young adulthood?,’’ which was coded ‘‘yes’’ or ‘‘no,’’ and ‘‘If so, what indicator or indicators tell you that this has happened?’’ the responses to which were recorded verbatim. We conducted a content analysis of the responses about indicators of adulthood and identified 16 types of indicators that accounted for all responses. The list of 16 indicators was then used by a second independent coder to recode the parents’ responses. The coders agreed on 90% of their evaluations; disagreements were resolved by consensus. The 16 criteria for adulthood are listed in Table 2.4, classified into five groups based on the categories of criteria used by Arnett and others with normative samples (i.e., Arnett, 2001; Nelson et al., 2007): individualism/relational maturity, role transitions, biological/age, family capacities, and norm compliance.
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3. Results 3.1. Moderate versus mild intellectual disability 3.1.1. Independent living The descriptive statistics for the measures of independent living are presented in Table 2.2. On the whole, relatively few of the young adults were living independently and supporting themselves financially. However, chi-squared tests revealed significant differences associated with the level of the child’s intellectual disability at entry into the study on several of these indices, and the differences were consistent with the expectation that individuals with moderate intellectual disability would demonstrate less independent functioning than those with mild intellectual disability. 3.1.1.1. Residence First, irrespective of level of disability, the majority of the sample members, 66.0%, lived with a parent or other relative. For the remainder, as shown in Table 2.2, most people with mild intellectual disability lived independently in a house or apartment, and most people with moderate intellectual disability lived in a group home, X2(5, N ¼ 139) ¼ 27.06, p < 0.001. The same pattern held when we restricted the analysis to those over 22 years old; 50.9% with mild intellectual disability and 56.7% with moderate intellectual disability lived with a parent, and most others with mild intellectual disability, 37.7%, lived independently, whereas most others with moderate intellectual disability, 33.3%, lived in a group home, X2(4) ¼ 20.79, p < 0.000. Among those who currently lived with a parent, the majority had never lived anywhere else (81.5%), though seven individuals had lived independently, then returned to the parent’s home. 3.1.1.2. Schooling The parents and caregivers reported that, overall, 56.8% of the sample had completed school, 29.5% were currently in school, and 13.7% were not currently in school, but also had not completed school, suggesting that they had dropped out or discontinued school temporarily. There was a significant effect of disability level for school status, X2(2, N ¼ 139) ¼ 9.32, p < 0.01. Individuals with moderate intellectual disability were more likely to be currently attending school compared to those with mild intellectual disability, whereas those with mild disability were more likely to have finished school or left school without completing a degree (see Table 2.2). Again, the same pattern occurred when we examined only individuals who were older than 22 years: approximately one quarter (N ¼ 19; 22.6%) were currently in school, and these individuals were more likely to have moderate (57.9%) than mild intellectual disability. The average age of the individuals still in school was 22.07 (SD ¼ 2.35), ranging from 18 to 26 years. They spent between 2 and 40 h per week in
43
The Transition to Adulthood for Individuals with Intellectual Disability
Table 2.2 Percentages and means and standard deviations related to independent living, family contact, health, and stress by disability level X2 or t-test statistic
Independent living Current living arrangements Parent home Other relative home Group home Independently Nonrelative foster care Prison Current school status Currently in school Finished school Not in school, but did not finish Hours per week in schoola Enrolled in special programa Number of school services receiveda Mainstreamed for any classa Ever been employed Currently employed Age at time of first jobb Less than 18 19–22 years 23–25 years 26 or older Number of jobs heldb Spent time looking for workb
Moderate intellectual disability (N ¼ 44)
Mild intellectual disability (N ¼ 96)
58.1% 2.3% 32.6% 2.3% 4.7%
58.3% 4.2% 6.2% 29.2% 1.0%
0%
1.0%
46.5%
21.9%
46.5% 7.0%
61.5% 16.7%
1.68
25.29 (11.7)
18.93 (11.5)
0.95
85.0%
85.7%
0.87
2.7 (2.2)
2.2 (1.6)
4.13
10.0%
19.0%
8.07** 4.64* 25.71***
38.1% 26.2%
64.2% 45.7%
6.2% 31.2% 31.2% 31.2% 1.50 (0.89) 50.0%
48.1% 44.4% 5.6% 1.9% 2.84 (1.94) 71.4%
27.06***
9.32**
2.67** 2.33
(continued)
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Frank J. Floyd et al.
Table 2.2 (continued) X2 or t-test statistic
Longest duration of job heldb Less than 6months 6 months–1 year 1–2 years 2–3 years 3 or more years Relationship status Single, never married, not dating Single, never married, but dating Had been married or engaged Age at first datec Has a child Attends day activity program Attends a sheltered workshop Works with support in community Family contact and involvement Contact with parents Daily/regular Weekly Monthly Infrequently Not at all Direct caregivingd Mothers Fathers Siblings
Moderate intellectual disability (N ¼ 44)
Mild intellectual disability (N ¼ 96)
12.5%
23.6%
12.5% 31.2% 12.5% 31.2%
25.5% 16.4% 16.4% 18.2%
86.4%
66.3%
13.6%
16.8%
0%
16.8%
1.76þ 8.05** 8.08**
19.33 (4.06) 2.3% 38.1%
17.81 (2.13) 21.1% 16.0%
15.05***
35.7%
8.6%
0.03
28.6%
27.1%
65.9% 17.1% 9.8% 4.9% 2.4%
73.6% 13.2% 8.8% 2.2% 2.2%
3.50 (0.94) 2.88 (1.21) 2.51 (1.00)
3.16 (1.09) 2.36 (1.16) 2.22 (1.01)
4.17
9.27**
1.24
1.72þ 2.27* 1.53
x
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The Transition to Adulthood for Individuals with Intellectual Disability
Table 2.2
(continued) X2 or t-test statistic
Participate in decision makingd Mothers 1.58 Fathers 1.39 Siblings 0.87 Participate in family discussionsd Mothers 1.01 Fathers 0.14 Siblings 2.21* Express concern about futured Mothers 1.38 Fathers 1.17 Siblings 0.40 Participate in activitiesd Mothers 0.51 Fathers 0.91 Siblings 1.36 Initiate activities with targetd Mothers 0.62 Fathers 0.90 Siblings 1.36 Health status Excellent Good Fair Poor
3.01
Number of stressful life events 0–2 3–4 5 or more
6.66*
Moderate intellectual disability (N ¼ 44)
Mild intellectual disability (N ¼ 96)
3.76 (0.66) 3.10 (1.20) 2.28 (0.94)
3.53 (0.83) 2.77 (1.20) 2.11 (1.04)
3.37 (0.73) 2.88 (1.18) 2.59 (0.85)
3.51 (0.74) 2.91 (1.19) 2.97 (0.90)
3.24 (0.82) 2.71 (1.12) 2.46 (1.00)
3.44 (0.76) 2.96 (1.07) 2.54 (1.11)
3.57 (0.86) 3.07 (1.21) 2.74 (1.02)
3.50 (0.70) 2.87 (1.16) 3.00 (0.96)
3.50 (0.83) 2.88 (1.08) 2.58 (1.00)
3.41 (0.77) 2.68 (1.13) 2.84 (1.00)
29.3% 56.1% 7.3% 7.3%
23.7% 50.5% 18.3% 7.5%
47.7% 34.1% 18.2%
26.0% 43.8% 30.2%
þ
p< 0.10, *p < 0.05, **p < 0.01, ***p < 0.001. Among those currently in school: N ¼ 20 moderate disability and N ¼ 21 mild disability. b Only among those ever been employed: N ¼ 16 moderate disability and N ¼ 61 mild disability. c Among those who have dated: N ¼ 9 moderate disability and N ¼ 62 mild disability. d Rated on a scale from 1 to 4. a
school, which did not differ depending on disability level, t(36) ¼ 1.68, ns. The majority were enrolled in some special program, regardless of disability status, X2(1, N ¼ 41) ¼ 0.95, ns (see Table 2.2). In addition, there were no differences
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in the number of services received in school between those with mild and moderate intellectual disability, t(39) ¼ 0.87, ns. Only 14.6% of individuals who were still in school were mainstreamed for any class, and this did not differ between those with mild and moderate intellectual disability, X2(1, N ¼ 41) ¼ 4.13, ns. Among the 19 individuals over age 22 years who were still in school, the parents’ and caregivers’ descriptions indicated that only one of these individuals, who had mild intellectual disability, was enrolled in college. The remaining school experiences consisted of part-time training programs, often in conjunction with a supported employment or activity program. 3.1.1.3. Employment Approximately half (56.2%) of the sample had been employed at some point, and 39.7% were currently employed. Individuals with mild intellectual disability were more likely to have ever been employed compared to those with moderate disability, X2(1, N ¼ 137) ¼ 8.07, p < 0.01, and they also were more likely to be currently employed, X2(1, N ¼ 136) ¼ 4.64, p < 0.05. The pattern held only in part for the subsample of individuals over age 22 years; those with mild disability, 67.9%, were more likely to have ever been employed compared to those with moderate disability, 44.8%, X2(1, N ¼ 82) ¼ 4.16, p < 0.05, but the percentages of individuals who were currently employed did not significantly differ, mild ¼ 48.1%, moderate ¼ 34.5%, X2(1, N ¼ 81) ¼ 1.40, ns. Among those in the full sample who had been employed (N ¼ 16 with moderate and N ¼ 61 with mild intellectual disability), the age at which they began their first job differed depending on disability level, X2(3, N ¼ 71) ¼ 25.71, p < 0.001, with the mild disability group more likely to have taken a first job by age 18 years, and the moderate disability group more likely to have taken a first job later, after age 23 years. In addition, individuals with mild disability had held more jobs than individuals with moderate disability, t(75) ¼ 2.67, p < 0.01. There was no difference based on disability status in the number of individuals who had spent time looking for work, X2(1, N ¼ 70) ¼ 2.33, ns, or in the longest amount of time spent in one job, X2(4, N ¼ 71) ¼ 4.17, ns. 3.1.1.4. Family formation At the time of the follow-up, the majority of the young adults, 76.1%, were single and not dating, though this status was more common for people with moderate as opposed to mild intellectual disability, X2(2, N ¼ 139) ¼ 9.27, p < 0.01. As shown in Table 2.2, the mild disability group was somewhat more likely to be dating, and though the age at which they began dating was somewhat younger, the difference across groups was only a trend, t(69) ¼ 1.76, p < 0.08. Only 16.8% of the young adults had ever been engaged or married, all of whom were in the mild disability group. Similarly, most young adults (84.8%) had not had children, and having a child was more common for people with mild than moderate intellectual disability, X2(1, N ¼ 138) ¼ 8.05, p < 0.01 (see Table 2.2).
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3.1.1.5. Use of support services As expected, those with mild intellectual disability were less likely to be engaged in either a day activity program, X2(1, N ¼ 136) ¼ 8.08, p < 0.01, or a sheltered workshop, X2(1, N ¼ 135) ¼ 15.05, p < 0.001 compared to those with moderate intellectual disability. In fact, the people with moderate intellectual disability were as likely to be engaged in a day activity program or sheltered workshop as to have employment (see Table 2.2). However, there was no group difference in the percentage working with support in the community, X2(1, N ¼ 138) ¼ 0.03, ns (see Table 2.2). Also, more of the individuals with moderate intellectually disability (54.5%) than individuals with mild intellectual disability (27.7%) had a guardian appointed by the court, X2(1, N ¼ 138) ¼ 9.38, p < 0.01.
3.1.2. Family contact and involvement Most parents, 71.2%, had daily contact with the individuals with intellectual disability, and the amount of contact was not associated with the level of disability, X2(4, N ¼ 132) ¼ 1.24, ns. As expected, the amount of direct caregiving by the parents was greater for individuals with moderate than mild level of disability, though the effect was significant only for the fathers, t(144) ¼ 2.27, p < 0.05, and was just a trend for the mothers, t(131) ¼ 1.72, p < 0.09 (see Table 2.2). Direct caregiving by a sibling did not differ significantly depending on level of disability, t(125) ¼ 1.53, ns. Other forms of indirect caregiving, including making decisions, expressing concern, and having family discussions about the individual with intellectual disability, did not show differences across the groups, with one exception. Contrary to expectations about caregiving, the siblings of targets with mild disability were more likely to participate in family discussions about the target than siblings of targets with moderate intellectual disability, t(124) ¼ 2.21, p < 0.05 (see Table 2.2). The frequencies of social involvement by mothers, fathers, and siblings did not differ depending on level of disability (see Table 2.2), including both participating in and initiating activities with the individual with intellectual disability. 3.1.3. Health and stress The reporters indicated that the majority of the young adults were in good or excellent health, 78.3%. Ratings of health did not differ according to disability level, X2(3, N ¼ 138) ¼ 3.01, ns. However, individuals with mild as opposed to moderate intellectual disability experienced more stressful life events, X2(2, N ¼ 140) ¼ 6.66, p < 0.05. As shown in Table 2.2, individuals with moderate intellectual disability were most likely to have experienced two or fewer stressful events during the past year, whereas individuals with mild intellectual disability were almost twice as likely as the moderate group to have experienced five or more events. In the overall sample, the most common events were a family move to a new location, 61.2%, and a death
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in the family, 62.1%. Three specific items were more frequent among those with mild compared to moderate disability: having a relative move into the household, 24.0% versus 9.1%, experiencing trouble with a supervisor at work, 28.9% versus 12.8%, and experiencing a death in the family, 67.7% versus 50.0%. 3.1.4. Summary: Moderate versus mild intellectual disability Overall, there was limited evidence of launching and financial independence for the young adults with intellectual disability, with most living with parents and few able to support themselves financially. Nevertheless, there was some support for the hypothesis that level of intellectual disability would be associated with attainment in this area, with less attainment for individuals with moderate as opposed to mild intellectual disability. Specifically, as compared to individuals with mild intellectual disability those with moderate intellectual disability tended to remain in school and were not employed, and those who were employed held fewer jobs and started working at a later age. They were single, never married, and did not have children. They also were more likely to live in a supervised setting, to participate in supervised activity programs, and to receive direct care from their parents. However, perhaps because of their more structured lives, they were less likely to experience stressful events, particularly in the form of relatives moving into the home, conflicts with work supervisors, and bereavement.
3.2. Behavior problems in childhood The presence of significant behavior problems in childhood was not independent of level of intellectual disability, X2(1, N ¼ 137) ¼ 4.62, p < 0.05. Behavior problems were more common among the children with mild intellectual disability, 44.1%, than among the children with moderate intellectual disability, 25.0%. However, the effects of behavior problems on functioning in adulthood did not appear to be fully confounded with the effects of intellectual disability level. Compared to disability level, the presence of behavior problems showed fewer associations with adult functioning and most of the effects that did emerge differed from the effects of level of intellectual disability. The exceptions, however, concerned the measures of independent living. 3.2.1. Independent living Only four of the variables associated with independent living showed differences depending on childhood behavior problems and, contrary to expectations, all effects suggested greater independence for those with childhood behavior problems. Specifically, significant effects occurred for current residence, X2(5, N ¼ 136) ¼ 12.79, p < 0.05, hours spent in school, t(36) ¼ 2.70, p < 0.01, and current relationship status, X2(2, N ¼ 136) ¼ 6.21, p < 0.05,
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as well as a trend for differences in participation in a day activity program, X2(1, N ¼ 133) ¼ 3.00, p < 0.08. In contrast to the nonproblem group, those who had childhood behavior problems were more likely to be living independently, 32.7% versus 11.9%, and were less likely to live with a parent or relative, 46.2% compared to 66.7%. They also spent fewer hours in school, 15.87 (SD ¼ 12.16) vs 25.63 (SD ¼ 10.16). Although most employment variables did not differ across the groups, those with behavior problems were less likely to participate in a day activity program, 15.4% versus 28.4%. They also were more likely to be dating or to have married, 36.5% versus 21.5%. However, because three of these effects were consistent with differences associated with level of intellectual disability, we repeated all analyses examining the effects of behavior problems only among the individuals with mild intellectual disability. These analyses failed to confirm any of these significant effects, all p > 0.10. Thus, the apparent greater independent functioning for individuals with childhood behavior problems might have been accounted for, at least in part, by their higher level of intellectual ability. 3.2.2. Family contact and involvement The measures of frequency of family contact, the amount of direct caregiving, and the amount of indirect caregiving in the form of decision making generally were not associated with childhood behavior problems. Only for the mothers were participation in family discussions and expressing concern about the future different depending on childhood behavior problems. Mothers participated in more family discussions about individuals who had a history of behavior problems, 3.67 (SD ¼ 0.59) versus those without a history of behavior problems, 3.31 (SD ¼ 0.79), t(127) ¼ 2.79, p < 0.01. Similarly, mothers expressed more concern about the future for individuals that had a history of behavior problems, 3.57 (SD ¼ 0.64) versus those without behavior problems, 3.22 (SD ¼ 0.64), t(129) ¼ 2.25, p < 0.05. Levels of social involvement (both participation in activities and initiation of activities) for mothers and fathers did not differ according to childhood behavior problems. However, siblings were more likely to initiate activities with targets who did not have a history of behavior problems, 2.91 (0.91), compared to siblings of targets who had behavior problems, 2.52 (1.09), t(121) ¼ 2.12, p < 0.05. Similarly, there was a trend in which siblings were more likely to participate in activities with targets who did not have a history of behavior problems, 3.05 (0.93), compared to siblings of targets who had behavior problems, 2.71 (1.06), t(122) ¼ 1.86, p < 0.09. 3.2.3. Health and stress Health and stress were associated with childhood behavior problems and, in this case, those who had had behavior problems were doing more poorly than those with no significant problems. That is, when the individual had shown
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significant behavior problems as a child, the reporters were less likely to rate the individual’s current health as excellent, 9.6% versus 36.1%, and were more likely to rate health as only ‘‘good,’’ 69.2% versus 41.0%, X2(3, N ¼ 135) ¼ 13.72, p < 0.01. In addition, those with a history of childhood behavior problems experienced more stressful life events, X2(2, N ¼ 137) ¼ 6.42, p < 0.05. The individuals with behavior problems were more likely to have experienced five or more stressors during the past year, 34.6% versus 21.2%, and were less likely to have only two or fewer stressors, 21.2% versus 41.2%. In this case, the stressors that were more common among the behavior problem group compared to the nonproblem group included birth of a new child in the family, 50.5% versus 23.5%, debt or decrease in income for self or family, 53.8% versus 29.4%, and legal problems, 32.7% versus 16.5%. 3.2.4. Summary: Behavior problems in childhood Although we had anticipated that the occurrence of behavior problems in childhood would be associated with limited attainment in launching and independence, this was not the case. Instead, greater independent living and involvement in adult romantic relationships, together with less involvement in supervised activity programs, suggested that this group was functioning somewhat more independently than those without behavior problems. These effects appeared to be accounted for, at least in part, by the greater occurrence of mild as opposed to moderate intellectual disability for individuals who had significant behavior problems in childhood. Behavior problems in childhood continued to have implications for family relationships in adulthood, with more concerns expressed by mothers and less social participation by siblings. Also, the greater adult independence for individuals with childhood behavior problems occurred in the context of poorer health and greater stress in the form of financial and legal problems.
3.3. Gender Gender was independent of disability status, X2(1, N ¼ 140) ¼ 0.00, ns, and behavior problem history, X2(1, N ¼ 137) ¼ 0.89, ns. The gender of the target individual showed almost no associations with adult functioning. 3.3.1. Independent living There were only two trends for differences between men and women in the variables related to independent living, both of which concerned family formation. There was a trend for women, 35.6%, to be more likely to be dating or married compared to men, 18.2%, X2(2, N ¼ 139) ¼ 5.31, p < 0.07, and a trend for women, 20.5%, to be more likely to have children compared to men, 9.2%, X2(1, N ¼ 138) ¼ 3.41, p < 0.06. There were no differences between men and women in terms of individuals’ school status
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(e.g., currently in school, completed school), in the percentage who were enrolled in special programs at school, the number of services received at school, or the hours spent in school. There were also no differences in current or past employment status, the number of jobs held, the age at first job, or the longest time in a job. Similarly, no differences were evident in the use of support services (i.e., day activity programs, sheltered workshops, or supportive employment in the community). 3.3.2. Family contact and involvement The target individuals’ contact with their families also did not differ by gender, nor did the amount of time mothers, fathers, or siblings spent in direct caregiving activities. In addition, there were no differences for any family member based on gender in terms of indicators of indirect care (participation in family discussions, participation in decision making, expressions of concern), participation in activities, or the initiation of activities. 3.3.3. Health and stress There were no differences in health status or the experience of stressful life events for men versus women. Although there was an overall lack of difference in the number of stressful life events experienced, one specific item did differ between men and women. Men were more likely to experience trouble with supervisors at work, 31.0% versus 15.8%, X2(1, N ¼ 139) ¼ 3.72, p < 0.05. 3.3.4. Summary: Gender By and large, gender was not a factor in predicting adult functioning. Apart from trends for greater progress in family formation by women, work and school attainments, involvement by parents and siblings, use of support services, and indicators of well-being were all similar for men and women.
3.4. Perceptions of adulthood Among the individuals over the age of 18, fully 85.6% of the respondents indicated that the target individual had ‘‘reached adulthood.’’ This status was unrelated to the level of intellectual disability, X2(1, N ¼ 139) ¼ 0.90, ns, the presence of childhood behavior problems, X2(1, N ¼ 136) ¼ 0.45, ns, gender, X2(1, N ¼ 139) ¼ 0.06, ns, or age, t(137) ¼ 0.18, ns. In addition, contrary to expectations, adulthood status also was not significantly related to indices of independent living, including whether or not the young adult lived with the parents, was currently in school, had finished school, or had ever been employed (see Table 2.3). There was a trend, however, for those who were seen as having reached adulthood to be currently employed, X2(1, N ¼ 136) ¼ 3.21, p ¼ 0.07.
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Table 2.3 Independent living based on perceptions of adulthood status Has not entered adulthood (N ¼ 20) (%)
Current living arrangements Parent Other relatives Group home Independently Nonrelative foster care Prison Currently in school Completed school Ever employed Currently employed
65.0 0 10.0 25.0 0 0 35.0 50.0 45.0 20.0
Has entered adulthood (N ¼ 119) (%)
57.1 4.2 14.3 21.8 1.7 0.8 26.1 60.5 57.1 42.0
Regarding the indicators of having reached adulthood, the frequencies for the 16 categories of open-ended responses are listed in Table 2.4. Consistent with findings for typical samples, the majority of the parents’ responses could be classified as forms of individualism (Arnett, 2001) or relational maturity (Nelson et al., 2007). These criteria emphasized the target thinking and behaving as a responsible adult. As with endorsements made by typical samples, the individualism/relational maturity criteria were mentioned more frequently than were adult role transitions, such as living independently or having married, taken a job, had a child, or become financially selfsufficient. Also similar to findings for typical samples, biological markers of maturity received relatively little emphasis by these parents. The specific criteria mentioned by these parents overlapped with factors found in typical samples, but also showed unique concerns for the parents of young adults with intellectual disability. As shown in Table 2.4 under the broad category of individualism/relational maturity, the most common reasons for being considered an adult were normative behaviors such as acting independently and making decisions independently from the parents, and also behaving in a responsible manner, which includes being considerate of others, assuming responsibilities, and being a reliable worker. However, unlike typical samples, the parents’ responses also emphasized the development of cognitive reasoning skills. Many parents mentioned that thinking in a ‘‘mature’’ way was an important consideration, which included reasoning through situations before reacting and using good judgment. They also noted that the young adults had begun to plan for the future. Interestingly, about 5% of the parents realized the child had reached adulthood when the individual began to refer to her/himself as an adult.
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Table 2.4
Indicators of the transition to adulthood
Category/criterion
Frequency
Individualism/relational maturity Separation from parent(s)/resisting control Self–care Responsible/considerate behavior Mature thinking Independent decision making Future orientation and goals Considers self an adult Role transitions Independent living Adult roles Financial independence Socializing out of home Dating or interest in dating Biological/age Physical development Age Family capacities Cares for child Norm compliance Reduction in problem behavior
68 (58.6%) 15 (13.5%) 14 (12.6%) 14 (12.6%) 12 (10.8%) 8 (7.2%) 8 (7.2%) 6 (5.4%) 37 (31.9%) 12 (10.8%) 11 (9.9%) 3 (2.7%) 8 (7.2%) 8 (7.2%) 17 (14.7%) 11 (9.9%) 6 (5.4%) 14 (12.6%) 13 (11.7%)
Note. N ¼ 111 parents who responded to the question about indicators of adulthood. Frequencies (percentages) for broad categories, in italic, indicate mention of at least one criterion within the broad category.
The responses categorized as role transitions also both overlapped with and differed from criteria used by typical samples. Consistent with typical samples, although moving from the parents’ home was not more likely to have occurred for those who had ‘‘reached adulthood,’’ the parents frequently mentioned this event as a criterion for adulthood. Other typical adult roles such as marriage and parenthood also were mentioned, though with relatively low frequencies that probably reflected the low frequencies of occurrence in this sample. Similarly, financial independence was rarely mentioned as a criterion, and in two of the three cases where it was mentioned, the individuals were only partially independent from the parents financially. It is also notable that over 10% of the parents mentioned indicators that are typically associated with adolescence rather than adulthood, including socializing with peers away from the family and dating. A series of chi-squared tests for the individual criteria and ANOVAs for the total number of events mentioned in each broad category generally
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failed to detect significant differences associated with level of disability or presence of childhood behavior problems. There also were no significant gender differences. There was only one significant difference associated with disability level, and one associated with behavior problems. Because only one individual with moderate intellectual disability had a child, the ability to care for a child was mentioned as a sign of adulthood only in the mild group, and the rate of 17.9% in this group significantly differed from the zero rate in the moderate group, X2(1, N ¼ 111) ¼ 6.78, p < 0.01. Also, whereas age was never mentioned as a criterion of adulthood for individuals who had significant childhood behavior problems, it was a criterion for 9% of those without behavior problems, X2(1, N ¼ 108) ¼ 4.04, p < 0.05.
4. Discussion From the traditional view of the transition to adulthood as growth toward independence and self-sufficiency, the young adults with mild and moderate intellectual disability in this investigation showed only limited progress. Most lived in the parents’ home or other supervised setting, only one-third were employed, few could support themselves economically, the majority were not dating, and only 11% had ever married despite having reached the legal age for emancipation and, in most cases, having finished school. The circumstances for this sample are consistent with population estimates both in the US and abroad (see Emerson, 2007; Fujiura, 2003) that indicate limited employment and economic self-sufficiency for individuals with intellectual disability. On the other hand, from the perspective of emerging adulthood, the circumstances for these young adults with intellectual disability greatly paralleled the experiences of recent samples of young adults without disabilities who, as college students and employees in the early stages of career development, maintain financial dependence on their parents and delay traditional adult role transitions until late in their 20’s or afterwards. Indeed, similar to normative samples, the parents in the current sample focused on criteria for adulthood that emphasized independent thought and free choice over role transitions and financial independence. Although the concept of emerging adulthood might be a relevant framework to describe the development of individuals with intellectual disability, this period clearly has unique qualities that distinguish it from development for young adults without intellectual disability. Most notably, although we used Arnett’s (2001) categories of individualism and role transitions to classify most of the criteria for achieving adulthood, many of the specific criteria seemed to be calibrated to account for the limitations in cognitive abilities associated with intellectual disability. It seemed that the
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parents accommodated their ideas of adulthood to capture the changes they perceived in their children, which meant that they were able to frame adulthood in a way that their child qualified. Also, the exceptionally high rate of endorsement by parents of the child having reached adulthood might have been lower if the parents were given the response option of ‘‘in some ways yes and some ways no,’’ which is the most frequently endorsed response in studies with normative samples (e.g., Nelson et al., 2007). Nevertheless, the option of reporting that the son or daughter had not reached adulthood might have implied that the individual is still a child, which has derisive connotations and, thus, may have been seen as an unacceptable response by many parents. Most strikingly, perhaps, is that when the parents focused on their children as adults, they focused on the emerging strengths and abilities that their children exhibited rather than their deficits and limitations. It seems that ‘‘the glass is half full’’ for many parents. As such, this perspective would seem to underlie other findings showing that parents find many rewarding features in the child’s transition to adulthood (e.g., Glidden & Jobe, 2007). Another qualification concerns the transitional nature of this period of development. Whereas emerging adulthood is seen as a temporary period for typical samples before they fully assume adult responsibilities for selfsufficiency and independence, it is unlikely that the parents held this expectation for their child with intellectual disability. That is, the experience of needing supports to foster self-direction might not be a temporary stage before adulthood, but rather another form of adult functioning. In this regard, the present findings extend traditional notions not only about a period of emerging adulthood, but also about adult maturity, independence, and individualism in the context of support. These young adults with intellectual disability are transitioning into an adulthood characterized by interdependence rather than independence. The critical role of supports in the lives of individuals with intellectual disability was strongly evident in the present sample. Supports were available to some degree from school and from some employment settings, but, for most individuals, the system of formal support services was no longer available, and informal supports were of primary importance. This situation was most apparent in the role of family members, who tended to be in daily contact with and provided high levels of caregiving to the young adults with intellectual disability. Edgerton’s (1967) seminal work on the lives of the first wave of adults with mild and moderate intellectual disability who moved to the community indicated that the ability to access informal supports was key to maintaining the appearance of competence. Whyte (1998) noted that the support persons for Edgerton’s sample were concerned and involved people from the community, none of whom were family members. She contrasted this type of support with the central role of the family in her study of individuals identified as
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‘‘mentally incompetent’’ in rural Uganda. The situation in which most of the present sample seemed well connected with family support likely reflects the growth in the role of family care since the time of Edgerton’s research. Indeed, the participants in the Edgerton study had lived in institutions before moving into the community, a situation which is virtually unknown in the US presently. The current findings are only partially consistent with the lives of similar-aged individuals from the Richardson and Koller (1996) report of the Aberdeen, Scotland sample. In that study, full employment, marriage, and parenthood were much more common. In part, the difference might reflect different sampling, wherein individuals in need of care were excluded from most analyses in the Richardson and Koller (1996) report. It might also reflect a different social structure, expectations, and opportunities, with earlier completion of schooling and, thus, a longer period for entering adult roles. Nevertheless, because the individuals with intellectual disability functioned more poorly in these roles than matched controls, the investigators concluded that, similar to the picture from the current sample, the individuals with disability were not doing well in meeting the challenges of transitioning to independent adult functioning. Also similar to Richardson and Koller (1996), there was limited ability to predict adult role functioning from childhood characteristics. The association between moderate as opposed to mild intellectual disability and more limited functioning in adulthood was as expected. More striking, however, was the occurrence of only a few associations between childhood behavior problems and adult functioning. Furthermore, the associations that occurred suggested an unexpected pattern of greater independent functioning for those with behavior problems as children, which was partially accounted for by their higher levels of intellectual functioning. The high rates of occurrence of behavior problems has received considerable attention in research with children who have disabilities because they are the most important concurrent correlates of stress and maladjustment for family members (Baker, Blacher, Crnic, & Edelbrock, 2002; Floyd & Gallagher, 1997), and peer and school-related problems for the children (Hastings & Oakford, 2003). It is possible that for at least some young adults, the link between childhood behavior problems and adult independence occurred because the family would no longer tolerate the young adult in their homes and, thus, the children were living independently. However, although siblings tended to be less involved socially, childhood behavior problems were not associated with less contact or less caregiving by family members in young adulthood. Helping families to better manage child behavior problems might be a key to reducing family stress concurrently, which likely creates a more nurturing learning environment for the child. In this way the occurrence of significant behavior problems in childhood might not foretell poor adjustment in adulthood if the behavior problems do not persist into adulthood.
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The findings also underscore a warning from other predictive studies (e.g., Bernheimer et al., 2006) about the potential negative consequences of independence for young adults with intellectual disability, wherein greater independence was associated with poorer health and more stressful life events such as financial and legal problems. The situation in which the individuals who are most capable of achieving autonomy are also most subjected to stress is an irony of the system of formal supports that might also apply to informal supports. Individuals with relatively higher levels of ability in at least some areas are least likely to be identified as needing formal supports and, similarly, their needs might not be recognized by families. Also, to the extent that mild intellectual disability frequently is associated with underprivileged family circumstances such as poverty (Emerson, 2007) and a relatively low rate of employment for mothers (Parish, Seltzer, Greenberg, & Floyd, 2004), the families might have relatively few resources to share. Nevertheless, it is not clear that our goal should be simply to reduce or eliminate stress from the lives of young adults with disabilities. As Bernheimer et al. (2006) argue, the lack of stress is not necessarily indicative of a preferable quality of life when it is also associated with restrictive circumstances and limited opportunities. Furthermore, recent research on stress and coping among adults with intellectual disability (Hartley & MacLean, 2005) reveals that many individuals access supports to manage stress quite successfully, consistent with the notion that stress can provide opportunities for growth. Underlying the goal of independence is the assumption that this goal is universally valued as a critical criterion for adult competence. However, cross-cultural studies have challenged this assumption in circumstances where interdependent family relationships are emphasized. For example, Whyte’s (1998) study of rural Uganda indicated that relational competence (i.e., social competence) has a culture-specific meaning, which in rural Uganda includes receptiveness to guidance, civility, and being able to help relatives, among other attributes. In addition, as a collectivist culture, relational competence for individuals is seen as an asset for the family and, in turn, the support provided by relatives is a form of caring for the self by caring for one’s own people. Another example comes from studies of family relationships in Japan, which Rothbaum, Pott, Azuma, Miyake, and Weisz (2000) described as characterized by a developmental path of symbiotic harmony in which accommodation and family commitment are valued over individuation and independence. There is no cultural equivalent to the notion of ‘‘launching’’ in the form of moving away from the family and toward peers in adolescence and shifting one’s commitment from the family of origin to a nuclear family created through marriage in adulthood. Instead, union and connection with the family are emphasized throughout development. Thus, although ‘‘launching’’ in young adulthood might be a normative goal in the US, more interdependent lives for young adults and their
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families are a common in other cultural circumstances, and might be a viable alternative for young adults with intellectual disability and their families.
5. Conclusion We believe that the conceptualization of the transition to adulthood as an emerging period of development for young adults with intellectual disability reflects a life-course approach that treats development in this group as an ongoing process throughout the lifespan. Previous research on the measurement of abilities emphasizes the fact that cognitive, language, and adaptive skills asymptote relatively early on for these individuals. However, as with normative groups, life continues to unfold both for the individuals and for their families, and recent family research across the lifespan is beginning to address this unfolding story.
REFERENCES Achenbach, T. M., & Rescorla, L. A. (2001). Manual for ASEBA school-age forms and profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, and Families. Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55, 469–480. Arnett, J. J. (2001). Conceptions of the transition to adulthood: Perspectives from adolescence through midlife. Journal of Adult Development, 8, 131–143. Baker, B. L., Blacher, J., Crnic, K., & Edelbrock, L. (2002). Behavior problems and parenting stress in families of three-year-old children with and without developmental delays. American Journal on Mental Retardation, 107, 433–444. Bernheimer, L. P., Keogh, B. K., & Guthrie, D. (2006). Young children with developmental delays as young adults: Predicting developmental and personal–social outcomes. American Journal on Mental Retardation, 111, 263–272. Chen, C. Y., Lawlor, J. P., Duggan, A. K., Hardy, J. B., & Eaton, W. W. (2006). Mild cognitive impairment in early life and mental health problems in adulthood. American Journal of Public Health, 96, 1772–1778. Edgerton, R. B. (1967). The cloak of competence. Berkeley, CA: University of California Press. Emerson, E. (2007). Poverty and people with intellectual disabilities. Mental Retardation and Developmental Disabilities Research Reviews, 13, 107–113. Erickson, E. H. (1968). Identity: Youth and crisis. New York, NY: Norton. Floyd, F. J., & Gallagher, E. M. (1997). Parental stress, care demands, and use of support services for school-age children with disabilities and behavior problems. Family Relations, 46, 359–371. Fujiura, G. T. (2003). Continuum of intellectual disability: Demographic evidence for the ‘‘Forgotten Generation’’. Mental Retardation, 41, 420–429. Glidden, L. M., & Jobe, B. M. (2007). Measuring daily parental rewards and worries in the transition to adulthood. American Journal on Mental Retardation, 112, 275–288.
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Hartley, S. L., & MacLean, W. E. (2005). Perceptions of stress and coping strategies among adults with mild mental retardation: Insight into psychological distress. American Journal on Mental Retardation, 110, 285–297. Hastings, R. P., & Oakford, S. (2003). Student teachers’ attitudes towards the inclusion of children with special needs. Educational Psychology, 23, 87–94. Heller, T., Caldwell, J., & Factor, A. (2007). Aging family caregivers: Policies and practices. Mental Retardation and Developmental Disabilities Research Reviews, 13, 136–142. Jobe, B. M., & Glidden, L. M. (2008). Predicting maternal rewards and worries for the transition to adulthood of children with developmental disabilities. Journal on Developmental Disabilities, 14, 69–79. Lounds, J., Seltzer, M. M., Greenberg, J. S., & Shattuck, P. T. (2007). Transition and change in adolescents and young adults with autism: Longitudinal effects on maternal well-being. American Journal on Mental Retardation, 112, 401–417. Nelson, L. J., Padilla-Walker, L. M., Carroll, J. S., Madsen, S. D., Barry, C. M., & Badger, S. (2007). ‘‘If you want me to treat you like an adult, start acting like one!’’ Comparing the criteria that emerging adults and their parents have for adulthood. Journal of Family Psychology, 21, 665–674. Parish, S. L., Seltzer, M. M., Greenberg, J. S., & Floyd, F. J. (2004). Economic implications of caregiving at midlife: Comparing parents with and without children who have developmental disabilities. Mental Retardation, 42, 413–426. Richardson, S. A., & Koller, H. (1996). Twenty-two years: Causes and consequences of mental retardation. Cambridge, MA: Harvard University Press. Rothbaum, F., Pott, M., Azuma, H., Miyake, K., & Weisz, J. (2000). The development of close relationships in Japan and the United States: Paths of symbiotic harmony and generative tension. Child Development, 71, 1121–1142. Seltzer, M., Krauss, M., Hong, J., & Orsmond, G. (2001). Continuity or discontinuity of family involvement following residential transitions of adults who have mental retardation. Mental Retardation, 39(3), 181–194. Thorin, E., Yovanoff, P., & Irvin, L. (1996). Dilemmas faced by families during their young adults’ transitions to adulthood: A brief report. Mental Retardation, 34, 117–120. Tymchuk, A. J., Lakin, K. C., & Luckasson, R. (2001). Life at the margins: Intellectual, demographic, economic, and social circumstances of adults with mild cognitive limitations. In A. J. Tymchuk, K. C. Lakin, & R. Luckasson (Eds.), The forgotten generation (pp. 21–38). Baltimore, MD: Brookes. Whyte, S. R. (1998). Slow cookers and madmen: Competence of heart and head in rural Uganda. In R. Jenkins (Ed.), Questions of competence: Culture, classification, and intellectual disability (pp. 153–175). Cambridge: Cambridge University Press.
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C H A P T E R
T H R E E
By Choice or By Chance: Longitudinal Perspectives on Resilience and Vulnerability in Adoptive and Birth Parents of Children with Developmental Disabilities Laraine Masters Glidden* and Brian M. Jobe† Contents 1. Introduction 1.1. Unique methodology and the rationale 1.2. Project Parenting overview 1.3. Background and data collection procedures 2. Hypothesis Testing: Chronic Sorrow or Crisis and Recovery 2.1. Depression 3. Parental Long-Term Adjustment: Multiple Variables Measured Multiple Times 3.1. Questionnaire on Resources and Stress 3.2. DEP5 3.3. Family strengths 3.4. Subjective well-being 4. Parental Long-Term Adjustment: Transition to Adulthood 5. Chronic Sorrow or Crisis and Recovery: Conclusions from Mean-Level Differences 6. Parental Long-Term Adjustment: The Importance of Personality in Predicting Resilience 6.1. Adoptive/birth status, personality, and adjustment in mothers and fathers 6.2. Parental long-term adjustment: Behavioral ratings 6.3. Coder impression items 6.4. Adoptive/birth similarities and differences 6.5. Disability/no disability similarities and differences
* {
62 63 66 66 71 72 73 74 76 76 77 78 79 81 82 83 83 86 86
Department of Psychology, St. Mary’s College of Maryland, St. Mary’s City, Maryland 20686, USA Department of Psychology, University of Maryland, Baltimore County, Catonsville, Maryland 21228, USA
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37003-2
#
2009 Elsevier Inc. All rights reserved.
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7. Summary, Conclusions, and Directions for Future Research in the Study of Resilience 7.1. Methodological considerations 7.2. Individual differences and personality 7.3. Mothers and fathers: Same and different 7.4. Concluding remarks Acknowledgments References
87 87 88 88 89 90 90
Abstract We studied adoptive and birth mothers and fathers of children with developmental disabilities longitudinally for 18 years to examine factors that relate to resilience and vulnerability in parental initial and long-term adjustment. For the most part, birth parents, especially fathers, did not differ in long-term adjustment from adoptive parents who willingly made the decision to rear children with developmental disabilities. We concluded, therefore, that the results are more consistent with a model of crisis and recovery than with one of chronic sorrow. We found that parental personality characteristics, especially Neuroticism, which encompasses emotional stability/instability, are predictive of long-term adjustment and recommended that they should be included in models of resilience and vulnerability.
Obstacles cannot crush me. Every obstacle yields to stern resolve. He who is fixed to a star does not change his mind. (Leonardo da Vinci) Patience and perseverance have a magical effect before which difficulties disappear and obstacles vanish. ( John Quincy Adams) When it gets dark enough you can see the stars. (Lee Salk) I’m a great believer in luck, and I find the harder I work, the more luck I have. (Thomas Jefferson) It is clear that it is not life events but our perceptions of those events, filtered through our personal experiences, beliefs, and values that give them meaning. (Garland, 1993)
1. Introduction The opening quotations of this chapter suggest that the outcomes of our lives are determined not mostly by chance but rather more by identifiable personal characteristics and behaviors. These characteristics lead us to reframe those events that collectively might be considered ‘‘bad luck’’ and use them to our advantage. We can turn lemons into lemonade, crisis into challenge. Some call these characteristics determination, hardiness, courage. Psychologists write about resilience. Resilient individuals are likely to achieve positive outcomes despite adverse individual or contextual
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circumstances (Luthar, Cicchetti, & Becker, 2000). They cope well in stressful situations, and are able to surmount obstacles that might lead others to desperation, hopelessness, and depression. They can, as Lee Salk wrote, reframe negative events to focus on the positive. Parenting a son or daughter with intellectual or other developmental disabilities (IDD) is one context that has historically been viewed as adverse. Indeed, research and clinical writings of 30–50 years ago viewed this circumstance as a chronic stressor (Holt, 1958; Jackson, 1974; Olshansky, 1962), an event from which the family never recovered. Although this view is less dominant than it once was, even recent writings state it explicitly or by implication (Helff & Glidden, 1998). However, in the current chapter, we take a more nuanced position. Our aims are to examine two views of the longitudinal trajectory of parental well-being, to evaluate the evidence for each of those views, and finally, to propose important variables that undergird resilience in the face of the demands of rearing a child with IDD. We do this primarily through our experiences with a 20-year longitudinal study of parents rearing at least one child who, at the time of entry into the sample, had a diagnosis of IDD or was functioning at a level consistent with IDD. Approximately half of these children had been born into their families. The others had been adopted by their parents and these parents knew about their disabilities prior to the adoption.
1.1. Unique methodology and the rationale Our choice of this unique design was dictated by our analysis of research methodologies that we believed led to overly negative conclusions about the outcomes of families who were rearing children with IDD that had been born to them. Two features of the then-dominant methodologies, either separately or together, were responsible. In many studies, families were considered at only one point in time, soon after their child was diagnosed (Beckman, 1983; Erickson & Upshur, 1989). They were often in crisis at that early time and the negative conclusions that focused on maladjustment failed to consider that responses of sorrow and depression were normative as an initial reaction. These initial conclusions, however, were never modified, because families were not followed through time. A second common methodological feature of many studies conducted 20 or more years ago was the nature of comparison groups, or lack thereof. Research on families rearing a child with IDD without comparison groups frequently reached conclusions about negative impact (Farber, 1959; Flynt & Wood, 1989; Fortier & Wanlass, 1984). Without a frame of reference, these conclusions were, at best, speculative, and, at worst, misleading. They were dominated by a pathology assumption. Unfortunately, research with comparison groups did not achieve a substantially better result. Frequently, investigators compared families rearing children
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with IDD with families rearing typically developing children (Bristol, Gallagher, & Schopler, 1988; Erickson & Upshur, 1989). Although this approach was more methodologically sophisticated than using no comparison group, it often led to a more subtle, but equally problematic result. Glidden (1993) published on this systemic flaw using the Questionnaire on Resources and Stress (Holroyd, 1987) as a case study. She claimed that many measures mixed demands (the environment acting on the individual to produce a potential stressor) and the results of those demands (stresses or strains, hereafter called stress). Because the rearing of a child with IDD is almost always more demanding than the rearing of a typically developing child, many investigators assumed that greater demands led to greater stress and drew the (possibly erroneous) conclusion that families with children with IDD manifested maladjustment (see Friedrich, Wilturner, & Cohen, 1985; Wilton & Renaut, 1986 for two of many possible examples). Although this problem is one of biased measuring instruments and not typically developing comparison groups per se, it was a common flaw in research in the 1980s and earlier. Parallel and concurrent with this research on families rearing children with IDD born to them, investigators began to describe families who had adopted children with IDD (Coyne & Brown, 1985; Glidden, 1989; Marx, 1990). Almost always, the results of these adoptions were positive, with reports of low adoption disruption (child leaving family before adoption is finalized) or dissolution (child leaving family after adoption is finalized), and high levels of positive adoptive parent well-being. For example, Marx described the results of an evaluation of the adoptive placements of 98 children with developmental disabilities. Parents reported many satisfactions including positive growth and development in the adopted children, changes for the better in other family members, and evidence of positive attitude change toward persons with IDD in neighbors and other community members. Even the difficulties were often expressed in terms of gain. For example, one single mother explained how she screened the men she dated by their reactions to her adopted daughter with Cornelia de Lange syndrome. Although this mother was distressed by the awkward or indifferent reactions of some men, when she found one that was interested and involved, she knew that it could be a positive and enduring relationship. These results gave impetus to the methodology used in the current research design in which families who had adopted children with IDD were compared with families rearing similar children by birth. By using this comparison, we hoped to keep constant the demands of child rearing. With constant demands, differences in parental well-being are more reasonably attributable to the psychological circumstances of the child’s entry into the family and other parental and family characteristics. Figure 3.1 displays the model and guiding framework of the research program. It depicts two pathways that may be activated when a child with IDD enters the family. The lower pathway represents the demands, that is, the realistic burdens,
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Resilience and Vulnerability
Existential issues
Intervening variables Commitment to the child Preparation for the child Child with disability enters the family
Child characteristics relative to parent preferences Parents’ personal attributes
Adjustment, adaptation, coping
Family strength Social support
Reality issues
Figure 3.1 A guiding framework for predicting adjustment in families rearing children with IDD. Adoptive and birth families both experience reality crises, but only birth families are expected to experience existential crises (adapted from Glidden, 1989).
that caring for a child with IDD entails. These demands may include extraordinary surgical, medical, and therapeutic routines; gathering information to become expert in the child’s condition; engaging with a variety of health and educational professionals, including advocating for services; understanding and budgeting for the sometimes expensive services that may be optimal; and so forth (Busby & Massey, 2006; Turnbull, Poston, Minnes, & Summers, 2007). Both adoptive and birth parents must adjust to these demands, although even here adoptive families may have advantages in that most of them will have financial subsidies for having adopted a special-needs child, and both pre- and postadoptive services organized by the adoption agency will help to alleviate some of the demands (Kramer & Houston, 1998; Schweiger & O’Brien, 2005; Wind, Brooks, & Barth, 2007). The upper pathway represents the existential issues that must be resolved with the advent of a child with IDD. For birth families, this represents shock, grief, reactions of ‘‘Why me?,’’ sadness, disappointment, feelings of inadequacy and isolation—all reactions that have frequently been termed existential crises (Roos, 1985). Many variables intervene between reality demands and existential issues, and we have listed a few in Fig. 3.1. Typically, parents who have made a decision to adopt a child with IDD would not experience existential crises and, therefore, would not be subject to the upper pathway. Thus, the comparison of adoptive and birth families keeps the reality demands relatively constant and if adoptive–birth differences
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in parental adjustment and well-being are observed, they are potentially attributable to stress arising from the failure to fully resolve existential crises rather than the demands of caring for a child with IDD. In other words, adoptive families could serve as an optimal adjustment group. Therefore, to the degree that birth families resemble adoptive families in adjustment outcomes such as depression, subjective well-being, effective coping strategies, and other reactions to stress, we can describe their adjustment as resilient, given the reality demands of their lives. If, on the other hand, birth parents consistently report poorer outcomes than adoptive parents, even though reality demands are equivalent, it is reasonable to assume that at least some of these differences are attributable to the psychological consequences of the unexpected diagnosis and its lifelong consequences.
1.2. Project Parenting overview Along with the research of other investigators as already described, a British study by the first author (Glidden, 1989) and its two follow-up data collections 3 (Glidden & Pursley, 1989) and 6 (Glidden & Johnson, 1999) years later (12 years after the adoptions), demonstrated an important foundation for a comparison of birth and adoptive families: Families who adopt children with IDD have excellent outcomes not only initially, but over time. For example, in one of many interview questions, we asked parents whether they would ‘‘definitely do the adoption again,’’ ‘‘definitely not’’ do it again, or were ‘‘uncertain.’’ Only 3% of mothers said that they would definitely not do it again, whereas 86% said that they definitely would do it again. Indeed, 3 years later Glidden and Pursley reported that 11 families, representing 35% of the follow-up sample, had adopted or were long-term fostering at least one additional child with a disability. In the 6-year follow-up, 50% of the families had adopted or were long-term fostering an additional child, and 82% of those additional children had IDD. These positive findings were mirrored by results from other investigators (Goetting & Goetting, 1993; Groze, 1996; Lightburn & Pine, 1996). Thus, the conclusion that adoptive families could effectively serve as a positive parenting comparison group was warranted.
1.3. Background and data collection procedures Beginning in 1987, adoptive parents who were eligible to participate were identified in six states and the District of Columbia, initially through both public and private adoption agencies, and eventually also via referral from already participating adoptive families. Inclusionary criteria were that (1) the target adopted child was between 1 and 12 years of age at time of study entry, and (2) when the decision to adopt had been made, the child had one of the following diagnoses or characteristics: developmental delay,
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developmental disability, or a condition with a developmental disability prognosis (e.g., Down syndrome, cerebral palsy, fetal alcohol syndrome). Because the pool of eligible adoptive families was much smaller than the pool of comparable birth families, birth families were recruited later, with the goal to match the two groups as closely as possible. Families were interviewed about no more than two children who met the inclusionary criteria, but only the earlier-born or adopted children are considered in this chapter. 1.3.1. Initial data collection By 1991, 249 families, 123 adoptive and 126 birth, had been identified and interviewed. At this entry into the project, frequently labeled Time 2 in other publications and here for consistency (Flaherty & Glidden, 2000; Glidden, Kiphart, Willoughby, & Bush, 1993), we used a semistructured protocol to interview at least one parent from each family about her or his reaction to the diagnosis (birth families) or placement (adoptive families) of the child, frequently labeled Time 1 in other publications, as well as about current functioning (Time 2). We obtained information about the parents’ background in areas of education, work, religious affiliation and participation, relationship/marital history and status, race, ethnicity, and other personal and family characteristics. Table 3.1 presents family, parent, and child data for these 249 families, with characteristics displayed separately for adoptive and birth families. The sample was quite diverse in many respects. For example, although the mean education level for both adoptive and birth mothers and fathers was 1–2 years beyond high school, this mean masked a large range. Some parents had not completed high school whereas others had advanced graduate, medical, or legal degrees. Adoptive parents were similar to birth parents in education level, occupational status, and ethnicity, but there were some notable significant differences. Adoptive mothers were older and more likely to be single than birth mothers. Adoptive fathers also were older than birth fathers. Finally, adoptive families had more total children, but fewer children born to them, than did birth families. The adopted children with IDD were similar to their birth counterparts in age, type of disability, level of functioning, and sex distribution. However, birth children were more likely to be of Anglo-European background than were adoptive children, reflecting a substantial number of transracial adoptive placements. Because of these differences, all analyses were conducted with relevant covariates, as well as without them. With only a few exceptions, the covariates were not significant, and the results were comparable to the analyses without the covariates. The exceptions are noted in the text. Also as part of this interview was the administration of several standardized inventories, the most important of which for this chapter is the Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961).
Table 3.1 Demographic comparison of birth and adoptive families at Time 2 (study entry) Adoptive
Birth
Variables
Mean
SD
Mean
Income Number of total children
$40,000 5.20
4.03
$40,000 2.76
1.55
Number of biological children Mothers (N ¼ 248) Age
1.80
1.91
2.71
1.48
42.27
6.98
35.26
5.93
Race/ethnicity (% Caucasian, non-Hispanic) Marital status (% in relationship) Education level (in years) Occupational status Fathers (N ¼ 203) Age Race/ethnicity (% Caucasian, non-Hispanic) Marital status (% in relationship) Education level (in years) Occupational status Children (N ¼ 249) Sex (% male) Age of diagnosis or placement (in months) Race/ethnicity (% Caucasian, non-Hispanic) Diagnosis Down syndrome Cerebral palsy DD, unknown origin Other Level of functioning Severe/profound Mild/moderate Borderline
81%
85%
75%
87%
SD
13.55
2.37
13.66
2.25
45.99
20.23
47.19
18.74
44.32
7.34
36.89
6.06
Significance
t(247) ¼ 6.33, p < 0.001 t(247) ¼ 4.17, p < 0.001 t(245) ¼ 8.52, p < 0.001 NS t(246) ¼ 2.24, p < 0.05 NS NS
85%
89%
t(200) ¼ 7.59, p < 0.001 NS
99%
100%
NS
14.03
2.96
14.18
2.32
NS
48.09
20.29
48.17
18.93
NS
53% 81.23
39.07
58% 73.81
34.25
NS NS
60%
85%
38% 16% 10%
41% 13% 8%
36%
38%
17% 53% 30%
14% 60% 26%
X2(1) ¼ 11.76, p < 0.01 NS
NS
Note: Income is presented as median, due to skewness of income data. Marital status was considered ‘‘single’’ if: single, separated-no cohabiting, or widowed. ‘‘In a relationship’’ was considered: married, separated, but cohabiting, or cohabiting. Total N ¼ 249 (adoptive ¼ 123; birth ¼ 126).
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The BDI was administered twice during the interview. We administered it first and retrospectively when parents were narrating their reactions to the child’s diagnosis (birth parents) or placement (adoptive families) (Time 1) .We administered it also later in the interview when we were discussing their current functioning (Time 2). In addition to inventories embedded in the interview, parents completed other instruments that had been mailed in advance. One of these—an adapted form of the Questionnaire on Resources and Stress (QRS; Holroyd, 1987)—will be described later in this chapter. 1.3.2. Subsequent data collections Contact was maintained with families following the initial data collection and, 5–6 years later, consenting families provided additional information in two phases. These new data consisted of some repeated measurement (e.g., BDI, QRS) and some new information (e.g., personality, subjective well-being). As in previous publications (Glidden, Billings, & Jobe, 2006; Glidden & Schoolcraft, 2003), we refer to this data collection as Time 3. Finally, approximately 5–6 years after the Time 3 data collection, consenting families provided new information, some of it repeated measurement and some on new instruments with new methods, including videotaped family interactions. This time of measurement was the final one and is referred to as Time 4 (Corrice & Glidden, 2009; Glidden & Jobe, 2007; Jobe & Glidden, 2008). Characteristics for the Time 4 sample are displayed in Table 3.2. Although the Time 4 sample consisted of only 57% of the original sample, detailed analyses of respondents and nonrespondents revealed that attrition was not selective. Of 37 comparisons between respondents and nonrespondents, only two were significant for fathers, one was significant for mothers, and two were significant for the target child. Nonrespondent mothers had completed less education (13.12 years) than respondent mothers (13.94 years), with a similar difference for nonrespondent (14.88 years) and respondent fathers (13.67 years). In addition, fathers who remained in the sample at Time 4 had significantly lower scores (less disharmony) on the Family Disharmony scale of the QRS than fathers who were lost to the study. Lastly, the two child differences were age- and diagnosisrelated. Families who dropped out of the research had target children who were a year older than families who remained in the sample. In addition, families with children with Down syndrome were less likely to drop out. Although these differences reflected some changes in the sample composition over time, they are relatively minor. Importantly, no significant differences were found on family income, occupational status, race/ethnicity of parents or children, child level of functioning, or any of the family or parent functioning variables measured at Time 2 with the exception of the father’s perception of Family Disharmony described previously. Therefore, we have concluded that the sample that remained after 12 years was mostly representative of the sample that we recruited at the outset of the data collection.
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Laraine Masters Glidden and Brian M. Jobe
Table 3.2 Demographic comparison of birth and adoptive families at Time 4 Adoptive
Birth
Variables
Mean
SD
Mean
SD
Significance
Income Number of biological children Mothers (N ¼ 137) Age (in years)
$60,000 0.65
1.19
$75,000 1.07
1.09
NS t(136) ¼ 2.17, p < 0.05
52.54
6.33
47.68
5.37
Race/ethnicity (% Caucasian, non-Hispanic) Marital status (% in relationship) Education level (in years) Occupational status Fathers (N ¼ 79) Age (in years) Race/ethnicity (% Caucasian, non-Hispanic) Marital status (% in relationship) Education level (in years) Occupational status Child (N ¼ 143) Sex (% male) Age (in years) Race/ethnicity (% Caucasian, non-Hispanic) Diagnosis Down syndrome Cerebral palsy DD, unknown origin Other Level of functioning ABS, Part 1 ABS, Part 2
86%
85%
t(135) ¼ 4.86, p < 0.001 NS
70%
77%
NS
14.49
2.70
14.66
2.86
NS
41.03
12.07
42.42
12.78
NS
54.53
6.21
48.58
5.46
95%
90%
t(76) ¼ 4.58, p < 0.001 NS
95%
98%
NS
15.91
3.44
15.45
2.73
NS
45.01
14.58
43.06
9.70
NS
54% 18.12 60%
3.12
62% 17.54 87%
3.18
NS NS NS
NS 40% 15% 12% 32% 87.87 92.98
41% 13% 8% 38% 19.23 14.44
82.18 92.57
17.12 13.33
NS NS
Note: Income is presented as median, due to skewness of income data. Marital status was considered ‘‘single’’ if: single, separated-no cohabiting, or widowed. ‘‘In a relationship’’ was considered: married, separated, but cohabiting, or cohabiting. ABS ¼ Adaptive Behavior Scale, Part 1 measures adaptive behavior and Part 2 measures maladaptive behavior. High scores indicate better functioning for both variables.
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2. Hypothesis Testing: Chronic Sorrow or Crisis and Recovery Two alternative views of parental reaction to the diagnosis of disability have dominated the research and writing of the last 50 years. Consistent with vulnerability and psychopathology, many investigators wrote about ‘‘chronic sorrow’’ (Olshansky, 1962; Solnit & Stark, 1961), lifelong stress and distress as a result of the inability to adapt to losing the expected perfect child. More recently, however, a strengths perspective has guided research agendas, and the chronicling of resilience, and of rewards and satisfactions after the initial crisis, has become more usual (Abbott & Meredith, 1986; Flaherty & Glidden, 2000; Hastings & Taunt, 2002; Trute & Hauch, 1988). We label this latter model ‘‘crisis and recovery.’’ One can test these two alternatives with a variety of outcome variables. For purposes of illustration, in Fig. 3.2 we present the patterns of parental depression that the proponents Chronic sorrow model
Depression
A
Lifespan Crisis and recovery
Depression
B
Lifespan
Figure 3.2 (A) and (B) Two models depicting the hypothetical lifespan trajectory for parents who receive a diagnosis of IDD for their child. Current evidence is more consistent with a model of crisis and recovery.
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Laraine Masters Glidden and Brian M. Jobe
of each view would predict over two points of time: initial diagnosis and several years after initial diagnosis. In both Fig. 3.2A and B, depression is high at initial diagnosis, predicted by both views. But some years later, the chronic sorrow view predicts that depression would remain high (Fig. 3.2A) whereas the crisis and recovery view (Fig. 3.2B) predicts that it would decline to lower levels.
2.1. Depression In Fig. 3.3A and B, we display the depression data from our longitudinal study. In Fig. 3.3A we present the data for adoptive and birth mothers and fathers for Times 1 and 2 only. Because the families entered the study at Time 2, these data represent the entire sample. In Fig. 3.3B we present the data for all four time points, though only for the mothers on whom we have
BDI score
A
18 16 14 12 10 8 6 4 2 0
Adoptive mother Birth mother Adoptive father Birth father
1
2 Time
B 16 14
BDI score
12 10 Adoptive Birth
8 6 4 2 0 1
2
3
4
Time
Figure 3.3 Two line graphs depict the trajectory of depression for adoptive and birth mothers and fathers at Times 1 and Time 2 for the BDI (A) and for adoptive and birth mothers at Times 1–4 for BDI (B).
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data for all times. Several points are worth noting. Most importantly, of course, is the pattern of change from Time 1 to Time 2. Both birth (but not adoptive) mothers and fathers display high levels of depression initially, with a large and significant decline over the 5–6 year interval between the two times of measurement. Moreover, this pattern is typical of most, although not all, of the birth parents (Glidden & Schoolcraft, 2003). Another important observation from Fig. 3.3B, and one which has methodological implications, is that depression scores do increase significantly from Time 2 to Time 3, a 5–6 year interval, and they do so for both birth and adoptive mothers. Without the adoption comparison group, this increase might have been interpreted as another indication of birth parent maladjustment. We do not know what caused this increase in both groups, but we can speculate. It could have been age related in that at Time 3, most of the children are in early to midadolescence, an age reported to be particularly difficult for many parents with the likelihood of escalating physical and psychological demands. However, when we segmented the sample by the age of the children, we did not obtain a significant effect for age. A methodological artifact may be responsible, at least in part, for this increase. Because families entered the study at Time 2, it is possible that parents who were feeling particularly positive at that time chose to participate and that therefore, their Time 2 scores are not representative because they are too low. The increase at Time 3, then, could reflect only regression toward the mean. These longitudinal data are wholly consistent with a crisis and recovery model and indicate parental resilience in adjusting to the demands of rearing children with IDD. Although initially the typical parental response is depression, we believe that depression is the normative response to an unexpected and unwelcomed life event that has major consequences for parents and other family members. Most birth mothers exhibited this initial depression and most recovered from it and reported scores in the nondepressive range (<13 on the BDI). Specifically, at Time 2, 96% of the birth mothers had scores in the nondepressed range, comparable to the 95% of nondepressed adoptive mothers. By Time 4, maternal depression had increased somewhat but was still quite low, 13% for birth mothers and 9% for adoptive mothers. In fact, some birth mothers did not report depression even at Time 1. These most-resilient mothers continued to exhibit the lowest depression scores across all follow-up time points (Glidden & Jobe, 2006). We will focus on predictors of this kind of resilience later in this chapter.
3. Parental Long-Term Adjustment: Multiple Variables Measured Multiple Times The chronic sorrow model predicts that birth parents will be less well adjusted than adoptive parents not only initially, but also in the long term. We collected data at least twice on several variables other than the
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Laraine Masters Glidden and Brian M. Jobe
depression data already presented and we have data for mothers and for fathers and, therefore, were able to directly compare adoptive and birth status for both parents. We have published some of these data along with emphases on etiological differences (Cahill & Glidden, 1996; Corrice & Glidden, 2009; Flaherty & Glidden, 2000; Glidden & Cahill, 1998) or in combination with other variables not discussed in the current chapter (Glidden et al., 2006). Here we focus on nine measures that represent the following adjustment outcomes: demands, resources, and stress as measured by The Questionnaire on Resources and Stress; depression as measured by DEP5 (Glidden & Floyd, 1997); family pride and accord as measured by the Family Strengths Inventory (Olson, McCubbin, Barnes, Larsen, Muxen, et al., 1985), and subjective well-being (Andrews & Withey, 1976).
3.1. Questionnaire on Resources and Stress The Questionnaire on Resources and Stress (Holroyd, 1987) was completed by both mothers and fathers at Times 2–4. We administered it in an adapted form described by Glidden (1993). In Table 3.3 we display the means for all adoptive and birth mothers and fathers at all three times for three scales of the QRS. These three scales measure parental responses independent of the level of functioning of the child with IDD, and thus are relatively pure measures of psychological stress rather than reality demands, as determined by Clayton, Glidden, and Kiphart (1994). Sample items include Our family agrees on important matters in the Family Disharmony scale; Caring for (target child) gives one a feeling of self-worth in the Lack of Personal Reward scale; and It is easy for me to relax in the Personal Burden scale. Importantly, separate adoptive/birth status (2) Time (3) MANOVAs for mothers and fathers revealed no overall significant adoptive/birth main effects. However, because we wished a very conservative test of our belief that crisis and recovery was the prevailing model, we planned univariate comparisons for each of the QRS scales. We did find that birth mothers reported significantly more personal burden at Time 4 than did adoptive mothers (F(1,124) ¼ 5.81, p < 0.05), although this difference was no longer significant when the covariates of mother age, number of children, and child ethnicity were included in the analysis (F(1,121) ¼ 2.55, p > 0.05). For adoptive and birth fathers, none of the univariate comparisons for any of the QRS scales, at any of the times of measurement, produced significant differences, with the exception of birth fathers having lower family disharmony than adoptive fathers in the covariance analysis. Overall, then, this pattern of results in which only 1 of 18 adoptive/birth comparisons demonstrated a poorer outcome for birth, in contrast to adoptive, parents, mothers specifically, is far more consistent with a crisis and recovery model than with a chronic sorrow model.
Table 3.3 Comparison of birth and adoptive mothers and fathers on Holroyd factors and DEP5 at Times 2–4 Adoptive Variables
Mean
Birth SD
Family Disharmony (Time 2) Mother 0.51 0.81 Father 0.40 0.62 Family Disharmony (Time 3) Mother 0.55 1.05 Father 0.77 1.01 Family Disharmony (Time 4) Mother 0.67 1.11 Father 0.87 1.17 Lack of Personal Reward (Time 2) Mother 0.62 1.10 Father 0.60 1.04 Lack of Personal Reward (Time 3) Mother 0.55 0.88 Father 1.07 1.57 Lack of Personal Reward (Time 4) Mother 0.87 1.14 Father 1.03 1.30 Personal Burden (Time 2) Mother 3.55 1.33 Father 2.73 1.17 Personal Burden (Time 3) Mother 3.47 1.40 Father 2.30 1.12 Personal Burden (Time 4) Mother 3.22 1.15
Mean
SD
Significance
0.83 0.35
1.10 0.65
NS NS
0.77 0.59
1.17 0.89
NS NS
0.79 0.44
1.30 0.71
NS NS
0.96 0.56
1.15 0.93
NS NS
0.77 0.62
0.85 0.92
NS NS
1.00 0.79
1.24 1.12
NS NS
3.99 2.74
1.39 1.11
NS NS
3.99 2.76
1.59 1.18
NS NS
3.79
1.43
F(1,124) ¼ 5.81, p < 0.05 NS
Father 2.50 DEP5 (Time 2) Mother 1.10
1.17
2.50
1.40
1.22
1.99
1.77
Father 0.83 DEP5 (Time 3) Mother 1.30 Father 0.93 DEP5 (Time 4) Mother 0.93
0.79
1.18
1.47
F(1,124) ¼ 6.79, p < 0.01 NS
1.61 1.11
1.89 1.32
1.84 1.49
NS NS
1.44
1.71
1.80
1.655
1.15
1.56
F(1,124) ¼ 5.97, p < 0.05 NS
Father
1.13
Note: N for adoptive mothers (N ¼ 55) and birth mothers (N ¼ 71). N for adoptive fathers (N ¼ 30) and birth fathers (N ¼ 34). Parent was included if data were available at all times of collection. A repeated measures ANOVA (adoptive/birth [2] mother/father [2] Time [3]) was conducted. Overall adoptive/birth differences for mothers (F(12,113) ¼ 1.22, p > 0.05) and fathers (F(12,51) ¼ 1.00, p > 0.05).
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3.2. DEP5 The DEP5 is a five-item inventory of depression derived from items on the QRS. Glidden and Floyd (1997) demonstrated its convergent and discriminant validity with multisample studies using two different well-regarded depression inventories—the BDI and the Depression scale of the Symptom Checklist-90D (Derogatis, 1983). Sample items include I get upset with the way my life is going and I get almost too tired to enjoy myself. In Table 3.3 we display the DEP5 means for all adoptive and birth mothers and fathers at all three times of measurement. As with the other QRS-derived measures, adoptive and birth mothers and fathers are more similar on the DEP5 than they are different. For fathers, the adoptive–birth main effect was not significant and none of the univariate comparisons at any of the three points in time were significant. However, for mothers, at two of the three times of measurement birth mothers reported significantly more depression than did adoptive mothers, differences that were no longer significant when the covariates were included in the analyses. These patterns strongly support the crisis and recovery model for fathers, but are somewhat equivocal for mothers.
3.3. Family strengths The Family Strengths Inventory (Olson et al., 1985) consists of two factors—pride and accord—with sample items such as Things work out well for us as a family and There are many conflicts in our family (reverse scored). We administered it at Times 2 and 3 to both adoptive and birth mothers and fathers. The means are displayed in Table 3.4. As with the QRS and DEP5 results already described, the adoptive/birth differences are not the same for mothers and fathers. Birth mothers report significantly lower levels of family pride and accord than do adoptive mothers, whereas adoptive and birth fathers do not differ significantly from one another. Again, the father data are not at all consistent with a chronic sorrow model, but suggest that whatever crisis may have occurred for birth fathers is not persistent. Indeed, the means for fathers are above the 50th percentile on the norms for this instrument. The reports from mothers, however, do not lead to the same conclusion. The birth mothers’ perceptions of family strength are lower than those of the adoptive mothers, a finding that is consistent with a chronic sorrow model. However, two qualifications are noteworthy. The adoptive/birth difference for mothers for Time 3 Accord is not significant in the covariance analysis (F(1,159) ¼ 2.44, p > 0.05) and the birth mothers’ reported levels of family strength are at the 40th percentile of the norms for the instrument, whereas the adoptive mothers’ means are at the 67th percentile. Thus, it appears that adoptive mother scores are elevated even more than birth mother scores are depressed.
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Table 3.4 Comparison of birth and adoptive mothers and fathers on family strengths (pride and accord) at Times 2 and 3 Adoptive Variables
Mean
Birth SD
Mean
SD
Significance
2.83
29.78
5.13
Father 31.10 FS Pride (Time 3) Mother 30.73 Father 30.29 FS Accord (Time 2) Mother 17.81
3.43
30.75
3.96
F(1,162) ¼ 11.53, p < 0.001 NS
6.85 3.56
29.76 29.20
4.56 4.71
NS NS
3.64
15.47
4.85
Father 17.45 FS Accord (Time 3) Mother 16.85
4.00
16.61
3.84
F(1,162) ¼ 12.23, p < 0.001 NS
4.11
15.27
4.62
3.77
16.84
4.22
FS Pride (Time 2) Mother 31.99
Father
16.52
F(1,162) ¼ 5.39, p < 0.05 NS
Note: N for adoptive mothers (N ¼ 81) and birth mothers (N ¼ 83). N for adoptive fathers (N ¼ 42) and birth fathers (N ¼ 44). Parent was included if data were available at all times of collection. A repeated measures ANOVA (adoptive/birth [2] mother/father [2] Time [3]) was conducted. Overall adoptive/birth differences for mothers (F(4,159) ¼ 4.07, p < 0.01) and fathers (F(4,81) ¼ 0.67, p > 0.05).
3.4. Subjective well-being Subjective well-being (SWB) has been measured in a multitude of ways by different investigators (Andrews & Withey, 1976). We used two different seven-point Likert scales to measure three types of SWB: Global (G), Current (N), and Child-Related (CR). One scale was based on seven faces ranging from broadly smiling (1) to broadly frowning (7) and the other was based on word descriptors from Delighted (1) to Terrible (7). Because results were similar for both the Delighted to Terrible and Faces scales, we combined them for purposes of analysis. Table 3.5 displays the means for SWB for the Global, Current, and Child-Related items for adoptive mothers and fathers, at both Time 3 and Time 4. Two adoptive/ birth status (2) Time of measurement (2) MANOVAs, one for mothers and one for fathers, demonstrated only one significant main effect and no significant interactions. For mothers only, the adoptive/birth status factor was significant (F(3,138) ¼ 4.00, p ¼ 0.01). Follow-up univariate tests showed that birth mothers reported lower levels of SWB-Global at Time 3 than did
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Table 3.5 Comparison of birth and adoptive mothers and fathers on subjective wellbeing (pride and accord) at Times 3 and 4 Adoptive Variables
Mean
Birth SD
Mean
SD
Significance
0.81
2.66
0.95
Father 2.26 0.75 SWB-Global (Time 4) Mother 2.42 0.90 Father 2.33 0.96 SWB-Current (Time 3) Mother 2.67 0.89 Father 2.65 0.86 SWB-Current (Time 4) Mother 2.79 0.90 Father 2.54 0.97 SWB-Child-Related (Time 3) Mother 2.53 0.89 Father 2.40 1.01 SWB-Child-Related (Time 4) Mother 2.73 1.22 Father 2.74 1.37
2.28
0.76
F(1,140) ¼ 4.72, p < 0.05 NS
2.67 2.50
1.08 1.13
NS NS
2.77 2.65
1.01 0.85
NS NS
2.68 2.89
0.98 1.33
NS NS
2.62 2.58
1.02 1.00
NS NS
2.64 2.67
1.12 1.37
NS NS
SWB-Global (Time 3) Mother 2.34
Note: N for adoptive mothers (N ¼ 66) and birth mothers (N ¼ 76). N for adoptive fathers (N ¼ 39) and birth fathers (N ¼ 36). Parent was included if data were available at all times of collection. A repeated measures ANOVA (adoptive/birth [2] mother/father [2] Time [3]) was conducted. Overall adoptive/birth differences for mothers (F(6,135) ¼ 4.07, p < 0.05) and fathers (F(6,68) ¼ 0.85, p > 0.05).
adoptive mothers (F(1,140) ¼ 4.72, p < 0.05), a difference that was no longer significant in the covariance analysis (F(1,137) ¼ 2.07, p > 0.05).
4. Parental Long-Term Adjustment: Transition to Adulthood At the Time 4 measurement, we introduced a new outcome variable that specifically focused on the transition to adulthood, appropriate because of the age of the target children with IDD. At this point in the lifespan, parents are concerned about their children’s futures as those children approach adulthood. Parents recognize that their children will transition out of school and into a world of services that in the United States are no longer federally mandated. Although this time may be one of concern and worry, parents may
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also begin to garner rewards related to their adult children’s successes as they conquer obstacles related to independent living, employment, and community adjustment. Recognizing that both positive and negative reactions may coexist, we developed an inventory, the Transition Daily Rewards and Worries Questionnaire (TDRWQ), to measure both. In four studies with 847 respondents, we described this 28-item inventory with four factors: Positive Future Orientation, Community Resources, Financial Independence, and Family Relations (with and without siblings) (Glidden & Jobe, 2007). Examples of items from each of the factors are, respectively: ‘‘I am excited by the prospects for my child’s future; I feel that school programs have not prepared my child for independent living; I am afraid that my child will depend on me forever; I am sad that my child is missing out on important family interactions; I am pleased that my children seem to have a close relationship.’’ Respondents rate their agreement or disagreement with the item on a five-point Likert scale anchored by strongly disagree (1) and strongly agree (5). The items were either a reward (positive) or a worry (negative), and the worries were reverse scored when the factors were computed. Thus, higher scores indicate fewer worries and more rewards. We reported extensive psychometric data on the TDRWQ, demonstrating the internal consistency and test-retest reliability as well as the concurrent, discriminant and convergent validity. In Table 3.6 we display the means and SDs for each of the TDRWQ factors for adoptive and birth mothers and fathers. Multivariate analyses indicated no overall significant effect for adoptive/birth status for either mothers or fathers and none of the 10 follow-up univariate tests, five for mothers, and five for fathers, yielded a significant difference for adoptive and birth mothers and fathers. In fact, in the covariance analysis, birth mothers and fathers reported significantly higher scores on the family relations with siblings factors than did adoptive mothers and fathers (F(1,93) ¼ 4.15, p < 0.05 and F(1,61) ¼ 5.04, p < 0.05 for mothers and fathers, respectively). Therefore, we concluded that at Time 4, when the children with IDD were, on average, 18 years old, adoptive and birth parents had similar perceptions of the rewards and worries related to their son or daughter’s transition to adulthood. These results, then, do not provide support for the chronic sorrow model, but are wholly consistent with a model of crisis and recovery.
5. Chronic Sorrow or Crisis and Recovery: Conclusions from Mean-Level Differences Overall, we believe that our comparisons of adoptive and birth parents provide more support for a trajectory of crisis and recovery following the diagnosis of a child with IDD than for a trajectory of chronic sorrow.
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Table 3.6 Comparison of birth and adoptive mothers and fathers on Transition Daily Rewards and Worry Questionnaire at Time 4 Adoptive Variables
Mean
Birth SD
Positive Future Orientation Mother 3.35 0.89 Father 3.41 0.94 Community Resources Mother 2.82 0.87 Father 3.00 0.94 Financial Independence Mother 3.00 1.12 Father 3.01 1.11 Family Relations Mother 4.07 0.87 Father 4.03 0.89 Family Relations with Siblings Mother 3.91 0.75 Father 3.84 0.70
Mean
SD
Significance
3.12 3.15
0.92 0.94
NS NS
2.80 2.64
0.80 0.79
NS NS
2.84 2.79
1.04 1.05
NS NS
4.15 4.14
0.67 0.81
NS NS
4.14 4.01
0.63 0.66
NS NS
Note: N for adoptive mothers (N ¼ 66/44 with siblings) and birth mothers (N ¼ 77/54 with siblings). N for adoptive fathers (N ¼ 37/30) and birth fathers (N ¼ 43/36). Parent was included if data were available at all times of collection. Overall adoptive/birth differences for mothers (F(4,138) ¼ 1.31, p > 0.05; F(1,97) ¼ 2.74, p > 0.05) and fathers (F(4,75) ¼ 1.07, p > 0.05; F(1,65) ¼ 1.09, p > 0.05).
For fathers, the data are unequivocal. No significant differences emerged in comparisons of adoptive and birth fathers on 15 different variables, 10 of which were measured during at least two time points. This pattern led to our categorical rejection of a chronic sorrow model. All findings pointed to birth fathers with functioning similar to adoptive fathers who had made a choice to adopt children with IDD and thus should not be experiencing the kinds of existential crises that might typify birth fathers. The data for mothers are more equivocal, although more consistent with a crisis and recovery trajectory than with a chronic sorrow trajectory. Of the 15 variables on which adoptive and birth mothers were compared, 10 did not result in significant differences at any time point after the initial crisis of diagnosis. Two of the variables that did result in significant differences (QRS scale of Personal Burden and DEP5) actually were highly correlated, in part, because two of their items overlap. Additionally, two of the five variables significantly differed only at one time point of multiple measurements. Finally, in analyses using the covariates of parent age, number of children in the family, and child ethnicity, only two highly correlated
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variables were significantly different for adoptive and birth mothers: Adoptive mothers reported more Family Pride and Family Accord at Time 2 than did birth mothers. In sum, then, we conclude that, for the most part, both mothers and fathers experience negative and sometimes crisis-proportion reactions to the diagnoses of their children with IDD, and that the typical pattern is recovery from these crises. Nonetheless, not all parents recover quickly and to the same extent. The degree of the recovery, and which variables influence it, is an important dimension in the study of parents and families. In the next section, we focus on these individual differences and on a single variable that effectively predicts long-term adjustment.
6. Parental Long-Term Adjustment: The Importance of Personality in Predicting Resilience We concluded in the previous section that there was some evidence that birth mothers had slightly poorer adjustment outcomes than did adoptive mothers. Nonetheless, for the most part, the data supported a crisis and recovery model rather than a chronic sorrow model given that adoptive/ birth status did not predict adjustment outcomes for most variables. Nevertheless, there were large ranges of functioning in the sample. At Time 4, for example, although the mean maternal BDI score was 5.71, the range was 0–24. Other adjustment variables also showed substantial variability for both mothers and fathers. Therefore, it is essential to look beyond adoptive/birth status, groups constituted by a historical difference of almost two decades, to determine what currently important variables might contribute to the variance in adaptation and adjustment over time. Certainly, there is no scarcity of candidates. Many investigators have focused on characteristics of the child with IDD, including phenotypic differences (Dykens, 1999; Glidden & Schoolcraft, 2007) and on the resources that the family can access (Emerson, Graham, & Hatton, 2006; Emerson & Hatton, this volume; Olsson, 2008). Although these and other investigators have provided evidence that both of these dimensions can influence outcome, we chose a somewhat different emphasis: parental personality. There is little disagreement that personality characteristics can influence the way we experience the world and we began this chapter with this popular wisdom exemplified in quotations from well-known personages. By definition, personality traits are consistent in different contexts and relatively stable across time. They constitute approaches to organizing our perceptions and our behaviors in a wide variety of circumstances. Many investigators believe that a factor approach to personality is a valuable heuristic tool, and the FiveFactor model of personality has been investigated extensively (Costa &
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McCrae, 1988; Piedmont, 1998). This model claims that all of personality can be described in terms of the ‘‘Big Five’’ factors and their facets. Briefly, these domains include: Neuroticism—general mental and emotional stability/instability with characteristics of anxiety, hostility, depression, vulnerability, and a variety of maladaptive coping responses; Extraversion—positive emotions, warmth, gregariousness, fun-loving; Openness—valuing of ideas, aesthetics, fantasy, and novel experience; Agreeableness—compassion, trust, altruism, compliance, and helpfulness; and Conscientiousness—orderliness, self-discipline, responsibility, and achievement orientation. Individual personality traits as well as combinations of traits or profiles can predict many life outcomes including depression and wellbeing (Block, 1993; Costa & McCrae, 1980). In recent years, we have reported on the influence that parental personality as measured by the NEO-FFI (Costa & McCrae, 1992; McCrae & Costa, 2007) exerts on depression (Glidden & Schoolcraft, 2003), subjective well-being (Glidden et al., 2006), and transition rewards and worries (Jobe & Glidden, 2008). For the most part, Neuroticism and Extraversion have had the greatest predictive value, with high levels of Neuroticism associated with poorer adjustment outcomes, and high levels of Extraversion associated with better adjustment.
6.1. Adoptive/birth status, personality, and adjustment in mothers and fathers Given that adoptive/birth status was a relatively poor predictor of long-term adjustment, but there were nonetheless substantial individual differences in adjustment, we turned to personality as an explanation of at least some of these individual differences. We performed a series of regression analyses for the following maternal and paternal adjustment variables at Time 4: BDI (mothers only), DEP5, SWB-Global, SWB-Current, SWB-Child, and three Holroyd scales of Family Disharmony, Lack of Personal Reward, and Personal Burden. Each of the regressions had the same basic structure. We wanted to assess the degree of variance that personality traits predicted after we had controlled for adoptive/birth status. So, we first entered Adoptive/Birth status, followed by stepwise inclusion of the Big Five personality factors. We obtained quite different patterns of results for fathers and for mothers. For fathers, adoptive/birth status did not significantly predict any of the seven adjustment outcomes, and only one personality factor predicted one adjustment outcome: Neuroticism predicted 12% of the variance in depression as measured by DEP5 (F(2,70) ¼ 4.81, p < 0.001). For mothers, adoptive/birth status initially significantly predicted depression as measured by both the BDI and the DEP5; it also predicted the Holroyd QRS Personal Burden scale which contains item overlap with DEP5. However, for the BDI, adoptive/birth status became nonsignificant
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when personality variables were entered, and in the final model, Neuroticism predicted 24% of the variance in BDI. However, for both DEP5 and Personal Burden, adoptive/birth status remained significant after the personality variables were entered. Again, the only personality factor that was a significant predictor for these two variables was Neuroticism. However, for one other variable, Holroyd Lack of Personal Reward, Extraversion predicted 10% of the variance. Mothers with lower levels of Extraversion reported higher levels of Lack of Personal Reward. This scale contains items that focus on respondents feeling a sense of worth as a result of caring for their son or daughter with IDD. The item, I am pleased when others see that my care of [child’s name] is important, is prototypical. As with all of the QRS scales, high scores are negative, and a parent responding false to this item, would get one point. Thus, higher levels of Extraversion are associated with resilience and lower levels with vulnerability. The results of these analyses are quite consistent with earlier ones. Adoptive/birth status had no predictive power for the long-term adjustment of fathers, and some predictive power for the long-term adjustment of mothers. For both mothers and fathers, the trait of Neuroticism was the strongest predictor for our outcome variables, especially those measuring depressive outcomes. This result is certainly consistent with the findings reported by other investigators (Belsky, Crnic, & Woodworth, 1995; Costa & McCrae, 1980; Zonderman, Herbst, Schmidt, Costa, & McCrae, 1993).
6.2. Parental long-term adjustment: Behavioral ratings In addition to the measures at Time 4 that we have already described, a geographically accessible subset of 45 families of the longitudinal sample was videotaped during an approximately 30-min family interaction. These 45 families were matched with 46 families rearing children without disabilities on child developmental level, and family characteristics of income, race, ethnicity, and marital status. Table 3.7 displays the characteristics for parents and children for the two groups. Trained coders from the Oregon Social Learning Laboratory conducted both microanalysis of these videotapes providing second-by-second codes, and overall impressions of the parents and child participants in the family interaction. The detailed behavioral ratings are beyond the scope of this chapter, but we will consider the coder impressions of the parents.
6.3. Coder impression items Each parent was rated on 30 items, consisting of both positive and negative features. Examples of items are parent/child relationship seemed good, withdrew from interaction in a negative way, seemed irritable or angry, and encouraged desired
Table 3.7
Demographic comparison of project parenting and comparison families at Time 4 Longitudinal sample (n ¼ 45)
Comparison sample (n ¼ 46)
Variables
Mean
SD
Mean
SD
Significance
Incomea Occupational statusb
$60,000.00 44.41
14.02
$82,000.00 48.36
12.57
NS NS
Mothers (n ¼ 90) Age (in years)
49.09
5.81
34.07
5.39
t(87) ¼ 12.63, p < 0.001 NS NS
Ethnicity (% Caucasian) Marital statusc (% in relationship) Education (in years) Fathers (n ¼ 53) Age (in years) Ethnicity (% Caucasian) Marital statusc (% in relationship) Education (in years) Children (n ¼ 91) Sex (% male) Age (in years) Race/ethnicity (% Caucasian, non-Hispanic) a b c
80% 75%
84% 87%
14.73
3.25
15.29
2.02
NS
50.13
8.14
38.33
4.99
t(66) ¼ 7.29, p < 0.001 NS NS NS
84% 99%
87% 100%
15.10
3.40
15.49
2.78
56% 18.18
3.20
50% 6.48
3.55
78%
84%
Income is presented as median, due to skewed income data. The MSE12 is an index of occupational status ranging from 13 to 88 (Featherman & Stevens, 1982). ‘‘In a relationship’’ if married; separated, but cohabiting; cohabiting; all others coded as single.
NS t(89) ¼ 16.50, p < 0.01 NS
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Table 3.8
Factor analysis of coder impressions data with varimax rotation
Behavioral Parent Inventory–Coder Impressions (BPI–CI) Factor
Positive Factor 1 Emotional atmosphere pleasant Parent/child relationship with Target A seemed good Rater liked mom/dad Mom/dad appears tensed–relaxed Mom/dad appears humorless–humorous Mom/dad appears cold–warm Mom/dad appears rude–polite Mom/dad appears unpleasant–pleasant Mom/dad appears uninvolved–involved Mom/dad appears rejecting–accepting Mom/dad appears distant–close Negative Factor 1 Mom/dad withdrew from interaction in negative way Mom/dad treated another person with respect Mom/dad indicated physical aggressiveness to another person Mom/dad seemed down or depressed Mom/dad showed indications of problematic or excessive alcohol or drug use Mom/dad demonstrated antisocial attitude Negative Factor 2 Mom/dad used hostile behavior toward another person Mom/dad used aversive techniques to get his/her way Mom/dad provoked another into argument Mom/dad seemed irritable or angry Mom/dad made unreasonable requests of Target A Positive Factor 2 Mom/dad encourage positive behavior Mom/dad overtly friendly or pleasant to Target A Mom/dad appears uncooperative–cooperative Mom/dad appears critical–encouraging Mom/dad appears unaffectionate–affectionate
Loading
0.53 0.59 0.74 0.59 0.66 0.76 0.48 0.67 0.44 0.73 0.78 0.72 0.49 0.90 0.77 0.93 0.72 0.74 0.74 0.59 0.76 0.41 0.80 0.56 0.43 0.73 0.51
or positive behaviors. Reliability of the ratings was satisfactory with 90.3% agreement between two raters (Glidden, Turek, Hill, & Bamberger, 2009). A factor analysis with varimax rotation produced two positive and two negative factors, containing 28 of the 30 items. Table 3.8 displays the final factor structure with each of the factors labeled. The two positive factors, 1 and 4, overlapped substantially, but Factor 4 contained items that specified
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characteristics or behaviors that involved another person, whereas Factor 1 also included characteristics that were more individual or global in nature such as tense/relaxed and pleasant emotional atmosphere. Similarly, of the two negative factors, Factor 3 items were more likely to involve another person (Glidden et al., 2009).
6.4. Adoptive/birth similarities and differences Using just the sample of 45 families rearing children with IDD, we compared the adoptive and birth mothers and fathers with each other on each of the four factors of the newly constructed Behavioral Impressions of Parents– Coder Inventory (BIP–CI). Coders formed generally positive views of parents, providing high ratings of both adoptive and birth mothers and fathers on the positive factors and low ratings on the negative factors. Means ranged from 5.32 to 5.76 on a seven-point scale for the two positive factors, and 1.07–1.51 on the negative factors. Indeed, particularly for Negative Factor 2, the floor effect and very low variance for fathers convinced us not to conduct parametric analyses of those data. We did, however, conduct MANOVAs for mothers on all four factors and for fathers on three factors. No significant differences emerged between adoptive and birth mothers or adoptive and birth fathers.
6.5. Disability/no disability similarities and differences We were also interested in whether scores on the BIP–CI differed for the families who were rearing children with IDD and the comparison families. As with the longitudinal sample, coders generally rated comparison parents positively, with the presence of many positive characteristics and the absence of negative ones. Separate MANOVAs for mothers and fathers, comparing the two samples on the four factors, did not yield significant multivariate results for either mothers or fathers. However, we examined the univariate tests, nonetheless, as we were more concerned about falsely accepting the null hypothesis (claiming that there were no differences between longitudinal and comparison groups) than falsely rejecting it. For mothers, the multivariate results approached significance (F(4,85) ¼ 2.15, p ¼ 0.08), and we found that mothers raising children without disabilities in the comparison group were rated significantly higher on Positive Factor 1 than mothers rearing children with disabilities (F(1,88) ¼ 5.38, p < 0.05). For fathers, none of the univariate tests between disability and no disability groups were significant.
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7. Summary, Conclusions, and Directions for Future Research in the Study of Resilience We believe that there are several important messages to be derived from the research that we have described in this chapter. Some of these messages involve recommendations with regard to best methodological approaches and others have implications for how we regard families and how best to support them. In this final section, we summarize our findings, drawing conclusions where appropriate, and suggesting directions for future research.
7.1. Methodological considerations Comparison groups should be carefully chosen, selected on the basis of the questions posed. Research designs that compare families rearing children with disabilities with families rearing children without disabilities must differentiate between differences in demands and the reactions to those demands. As we have written here and elsewhere, many frequently used measuring instruments confound demands with stresses, thereby biasing the findings toward significant differences by disability status. Those differences are likely to lead to the conclusion that the families with children with IDD are not doing as well as families with typically developing children. This confounding will be especially misleading if the measures selected to operationalize adjustment contain a mixture of demands and stresses, as many of them do (Clayton et al., 1994; Glidden, 1993). Similarly, designs that include families rearing children with disabilities of differing etiology, for example, Down syndrome versus autism, can be equally problematic for the same reason. Demands may be greater in the case of autism (e.g., intensive behavioral interventions), but these greater demands do not necessarily lead to lower well-being or increased depression. Again, it is essential that the dependent variables selected to reflect adjustment do not confuse demands with stresses. Our choice of an adoptive family comparison avoids the problems of confounding demands and stresses, but does introduce a different difficulty. It is unlikely that families who have knowingly adopted children with IDD are a random sample of the population of all families. In our analyses and conclusions, we made the assumption that there were not pre-existing differences between adoptive and birth families that would influence the outcomes that we measured. This assumption was a bold one, and it is unlikely that it was true. Although we demonstrated similarities on variables such as education level, income, and occupational status, there were notable differences. Adoptive parents were older than were birth parents, and they had more children. These variables were generally not predictive of our
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outcomes, and, in fact, when included as covariates sometimes reduced adoptive/birth differences. However, there may have been other variables on which adoptive and birth parents differed that we did not measure and that could have been predictive of adjustment outcomes. Despite these potential difficulties, we believe that the results of this adoptive/birth comparison inform the field, because it was a conservative test of the birth family experience. That is, we expected that adoptive parents would be better adjusted than birth parents, and the results demonstrated that, for the most part, they were not. Thus, we believe that, typically, parents recover from the crises that characterize their reaction to the disability diagnoses.
7.2. Individual differences and personality Parental personality must be recognized as a determinant of outcomes related to resilience and vulnerability. We have demonstrated that it most certainly operates as a main effect, and we suspect that it is both a mediator and moderator of many other variables. For example, adults low in Neuroticism and high in Extraversion report a positive sense of well-being and display an assured and confident manner in their interactions. They are optimistic about the future and adapt easily to changing circumstances. In contrast, adults who are high in Neuroticism and low in Extraversion approach the world from a negative and pessimistic orientation. They tend to react with distress at events that their low Neuroticism/high Extraversion counterparts might perceive as challenges, but also, opportunities. Rather than assured and confident in their orientation, individuals with a high Neuroticism/low Extraversion profile are likely to be insecure and anxious. Thus, whereas we believe that personality is a mediator between demands and adjustment, we also consider that it is likely to moderate the influence of demands on adjustment. We urge researchers to take it into account in future investigations and begin to explore the ways in which personality interacts with other variables to change both positive and negative outcomes.
7.3. Mothers and fathers: Same and different In the most general sense, mothers and fathers had similar reactions in their adaptation and adjustment to their children with IDD. Birth mothers and fathers both initially reported existential crises which they resolved over time and differences with adoptive parents were minimal in the long term. However, we also found differences between mothers and fathers. In the current chapter, we concluded that fathers demonstrated crisis and recovery in all our measured variables, whereas the data for mothers were more mixed, although still more consistent with crisis and recovery than chronic sorrow. (Note, however, that our sample of mothers was larger and the power of our tests of adoptive/birth differences greater for mothers, almost always above
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0.80 and frequently reaching 0.90. In contrast, the observed power for the tests involving fathers was lower, approximately 0.60 for most tests.) We, and other investigators, have reported other differences between mothers and fathers. For example, Glidden et al. (2006), in a study of coping strategies and personality, found similarities in the frequencies with which mothers and fathers reported using different coping strategies. Planful Problem Solving was the most frequently used and Escape-Avoidance the least frequently used strategy as reported by both mothers and fathers. However, we also found that, after controlling for personality, different coping strategies were associated with different outcomes for mothers and fathers. Most dramatically, for mothers more use of Escape-Avoidance strategies was associated with higher levels of depression and lower levels of SWB. Conversely, for fathers, Escape-Avoidance either did not predict these outcome variables or predicted them in the opposite direction from mothers: High Escape-Avoidance strategy use significantly predicted higher levels of current SWB. Therefore, we must be mindful of both the way mothers and fathers are alike and also how they are different. The current longitudinal research reminds us of both of these eternal truths.
7.4. Concluding remarks During the more than two decades since the beginning of the research program we have summarized in this chapter, investigators have moved gradually toward a sophisticated view of family adaptation and adjustment, toward a lifespan orientation, and toward the use of multi-informant and multi-method approaches to studying families. All these trends have enriched our understanding of how children with IDD influence their families and how families influence the children. By comparing families who chose to adopt children with IDD with families rearing similar children by birth, we have been able to contribute a unique perspective to this sophisticated view. The similarities in long-term functioning between these adoptive and birth mothers and fathers provide compelling evidence of the positive adaptations that the typical birth family makes and the resilience that parents demonstrate in their journey from initial crisis to long-term adjustment. Many variables influence the parents and other family members on this journey, and our focus on parental personality is not intended as an argument that other emphases would not be fruitful. From individual child characteristics related to, as well as unrelated to, the disability to the most macrolevel variables such as the national or international context, families are influenced in the way they react to the disability initially, as well as how they envision, plan, and create their futures. More than 10 years ago, for example, Glidden, Rogers-Dulan, and Hill (1999) proposed a model to guide the study of religion and ethnicity and their roles in the adjustment of
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families to disability. That we have neglected these two variables in our current summary does not imply that we think they are unimportant, and we urge that research should go not in one direction but many. Just as some investigators may pursue the role of individual children’s adaptive and maladaptive behavior on family adjustment, others should explore the impact of public policy and national wealth and poverty. These latter variables are essential to study as they surely determine outcomes when the investigative focus is on an international scale.
ACKNOWLEDGMENTS The research described in this chapter was supported by Grant No. 21993 from the National Institute of Child Health and Human Development, and by faculty development grants from St. Mary’s College of Maryland, both to the first author.
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Glidden, L. M., & Jobe, B. M. (2006). The longitudinal course of depression in adoptive and birth mothers of children with intellectual disabilities. Journal of Policy and Practice in Intellectual Disabilities, 3, 139–142. Glidden, L. M., & Jobe, B. M. (2007). Measuring parental daily rewards and worries in the transition to adulthood. American Journal on Mental Retardation, 112, 275–288. Glidden, L. M., & Johnson, V. E. (1999). Twelve years later: Adjustment in families who adopted children with developmental disabilities. Mental Retardation, 37, 16–24. Glidden, L. M., Kiphart, M. J., Willoughby, J. C., & Bush, B. A. (1993). Family functioning when rearing children with developmental disabilities. In A. P. Turnbull, J. M. Patterson, S. K. Behr, D. L. Murphy, J. G. Marquis, & M. Blue-Banning (Eds.), Cognitive coping, families and disability: Participatory research in action (pp. 183–194). Baltimore, MD: Paul Brookes. Glidden, L. M., & Pursley, J. T. (1989). Longitudinal comparisons of families who have adopted children with mental retardation. American Journal on Mental Retardation, 94, 272–277. Glidden, L. M., Rogers-Dulan, J., & Hill, A. E. (1999). The child that was meant or punishment for sin: Religion, ethnicity, and families with children with disabilities. In L. M. Glidden (Ed.), International Review of Research in Mental Retardation (Vol. 22, pp. 267–288). San Diego, CA: Academic Press. Glidden, L. M., & Schoolcraft, S. A. (2003). Depression: Its trajectory and correlates in mothers rearing children with intellectual disability. Journal of Intellectual Disability Research, 47, 250–263. Glidden, L. M., & Schoolcraft, S. A. (2007). Family assessment and social support. In J. W. Jacobson, J. A. Mulick, & J. Rojahn (Eds.), Handbook of intellectual and developmental disabilities (pp. 391–422). New York, NY: Springer. Goetting, A., & Goetting, M. G. (1993). Adoptive parents to children with severe developmental disabilities: A profile. Children and Youth Services Review, 15, 489–506. Groze, V. (1996). A 1 and 2 year follow-up study of adoptive families and special needs children. Children and Youth Services Review, 18, 57–82. Hastings, R. P., & Taunt, H. M. (2002). Positive perceptions in families of children with developmental disabilities. American Journal on Mental Retardation, 107, 116–127. Helff, C., & Glidden, L. M. (1998). More positive or less negative? Trends in research on adjustment of families rearing children. Mental Retardation, 36, 457–465. Holroyd, J. (1987). Questionnaire on Resources and Stress. Brandon, VT: Clinical Psychology Publishing. Holt, K. S. (1958). The home care of severely retarded children. Pediatrics, 22, 744–755. Jackson, P. L. (1974). Chronic grief. American Journal of Nursing, 74, 1288–1291. Jobe, B. M., & Glidden, L. M. (2008). Predicting maternal rewards and worries for the transition to adulthood of children with developmental disabilities. Journal on Developmental Disabilities, 14, 69–80. Kramer, L., & Houston, D. (1998). Supporting families as they adopt children with special needs. Family Relations, 47, 423–432. Lightburn, A., & Pine, B. A. (1996). Supporting and enhancing the adoption of children with developmental disabilities. Children and Youth Services Review, 18, 139–162. Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The construct of resilience: A critical evaluation and guidelines for future work. Child Development, 71, 543–562. Marx, J. (1990). Better me than somebody else: Families reflect on their adoption of children with developmental disabilities. In L. M. Glidden (Ed.), Formed families: Adoption of children with handicaps (pp. 141–174). New York, NY: Haworth. McCrae, R. R., & Costa, P. T. Jr. (2007). Brief versions of the NEO-PI-3. Journal of Individual Differences, 28, 116–128.
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Socioeconomic Position, Poverty, and Family Research Eric Emerson and Chris Hatton Contents 1. Introduction 2. Socioeconomic Position and Poverty 3. Socioeconomic Position, Poverty, and the Prevalence of Intellectual and Developmental Disability 4. The Impact of Socioeconomic Position on Family Functioning and Child Well-Being 5. The Impact of Socioeconomic Position Among Families Supporting a Child with Intellectual or Developmental Disabilities 5.1. Socioeconomic position and between-group differences in well-being 5.2. Socioeconomic position and within-group differences in well-being 5.3. Socioeconomic position as a moderating variable 6. Moving Forward: Methodological and Conceptual Issues Associated with Incorporating Socioeconomic Position into Family Research 6.1. Models 6.2. Measures of socioeconomic position and poverty 6.3. Analytic strategies 6.4. Sampling 7. Conclusions References
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Abstract In this chapter, we argue that research related to families supporting people with intellectual or developmental disabilities should pay greater attention to issues relating to their socioeconomic position and their experience of poverty. To these ends we (1) clarify our use of the terms ‘‘socioeconomic position’’ and ‘‘poverty’’; (2) briefly review the literature on the relationship between Institute for Health Research, Lancaster University, Lancaster LA1 4YT, United Kingdom International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37004-4
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socioeconomic position, poverty, and the prevalence of intellectual and developmental disabilities; (3) briefly review the literature on the impact of exposure to low socioeconomic position and/or poverty; (4) provide an overview of current research addressing issues relating to socioeconomic position and poverty and family functioning and the well-being of family members with intellectual or developmental disabilities; and (5) discuss key methodological and conceptual issues associated with incorporating socioeconomic position into family research. We conclude by discussing key conceptual and methodological issues relevant to incorporating the study of socioeconomic position and poverty within family research.
1. Introduction Our aims in writing this chapter are twofold. First, we wish to argue that research related to families supporting people with intellectual or developmental disabilities should pay greater attention to issues relating to their socioeconomic position and their experience of poverty. Second, we aim to discuss key conceptual and methodological issues relevant to such an enterprise. Much of our discussion will focus on the research undertaken in, and particularly relevant to, the world’s high-income countries (and, in particular, Anglophone high-income countries). As such, we will be replicating the global inequalities evident in research relating to people with intellectual or developmental disabilities (Emerson, Fujiura, & Hatton, 2007; Emerson, McConkey, Walsh, & Felce, 2008). We will, however, wherever possible, attempt to extend our discussion to research relevant to the situation of families of people with intellectual or developmental disabilities in low and middle income countries.
2. Socioeconomic Position and Poverty All societies are hierarchically structured, with key social institutions (e.g., the labor market, education, and legal systems) operating to position individuals within a social hierarchy. A person’s position in this hierarchy shapes their (and their children’s) access to and control over key resources (e.g., wealth, social connections, health, skills, access to educational, health, and welfare services) that play an important role in determining their health and well-being and maintaining or improving their position in the social hierarchy and the position of their children (Graham, 2007). We will use the term socioeconomic position to refer to the position occupied in a social hierarchy by an individual or family. As such, socioeconomic position lies
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on a continuum or gradient running from high to low. It is important to keep two things in mind. First, socioeconomic position is not an inherent property of individuals or families, but the result of the interaction between the impact of powerful social institutions in stratifying the social order and people’s active involvement in recreating and maintaining the social hierarchy through cultural and social practices (Graham, 2007). Second, socioeconomic position intersects with certain characteristics of individuals and families that are also likely to be important in understanding the wellbeing of families supporting a child with intellectual or developmental disabilities. For example, parental disability, poorer parental health, minority ethnic status, and single parent-headed households are all associated with an increased risk of occupying a lower socioeconomic position and experiencing poverty (Graham, 2007; Lister, 2004; Seccombe, 2000). People occupying lower socioeconomic positions may have difficulty accessing resources that are necessary to enable them to live lives that are considered appropriate or decent within their society. That is, they may experience poverty (Lister, 2004; Spicker, 2007). Following the classic Townsend approach to defining relative poverty (Townsend, 1979), we will use the term poverty to refer to the situation of individuals or families who are unable ‘‘due to lack of resources, to participate in society and to enjoy a standard of living consistent with human dignity and social decency’’ (Fabian Commission on Life Chances and Child Poverty, 2006). Although poverty can be categorized as a simple construct of either poor or not poor, clearly there are degrees of poverty. At its most extreme, poverty may involve such a level of deprivation of resources that health or life itself is significantly threatened (a situation often referred to as ‘‘absolute’’ poverty). Numerous different approaches have been taken to measuring poverty. These include income-based poverty lines (usually based on a judgment of the income necessary to buy a ‘‘standard’’ basket of goods or maintain an ‘‘acceptable’’ standard of living), relative income, financial strain, and material hardship (Emerson, Graham, & Hatton, 2006; Lister, 2004; Shaw, Galobardes, Lawlor, Lynch, Wheeler, et al., 2007; Spicker, 2007). This issue will be explored in greater detail in later sections of this chapter. Socioeconomic position and poverty both describe key aspects of the social positioning of people (or families) in a particular society at a particular point in time. They are not, however, static constructs. Societies change over time, as do the key social institutions that help create and maintain social stratification. Some people experience considerable social mobility, moving up or down the social hierarchy over time (Graham, 2007; Nunn, Johnson, Monro, Bickerstaffe, & Kelsey, 2007). People move in and out of poverty. As we shall see, these dynamic aspects of socioeconomic position and poverty are critical to understanding their impact on people’s life chances, health, and well-being.
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3. Socioeconomic Position, Poverty, and the Prevalence of Intellectual and Developmental Disability Although families supporting a person with intellectual or developmental disabilities are located at all points across the social hierarchy, they are—in general—significantly more likely than other families to be located in lower socioeconomic positions and to experience poverty (Chapman, Scott, & Stanton-Chapman, 2008; Durkin, 2002; Emerson, 2004, 2007; Emerson, Einfeld, & Stancliffe, 2009; Fujiura, 1998; Heber, 1970; Heikura, Taanila, & Hartikainen, 2008; Leonard & Wen, 2002; Murphy, Boyle, Schendel, Decoufle, & Yeargin-Allsop, 1988; Parish, Rose, Andrews, Grinstein-Weiss, & Richman, 2008; Roeleveld, Zielhuis, & Gabreels, 1997). To illustrate this point, Fig. 4.1 presents data on the ascertained prevalence of intellectual and developmental disabilities by neighborhood deprivation among all children aged 4–15 years of age in England. Data for this figure were extracted from the English National Pupil Database in 2008 and represent odds ratios adjusted to take account of child age, gender, and ethnicity against a reference group of children living in the 10% most affluent neighborhoods in England. Figure 4.2 presents data on the prevalence of maternal report of child intellectual disability among 2–7-year-old children in Mongolia, Thailand, and Macedonia (data extracted from the 6 Mild intellectual disability Severe intellectual disability
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Profound multiple intellectual disability Autistic spectrum disorder
Odds ratio
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Figure 4.1 Odds of intellectual and developmental disability by area deprivation decile (1 ¼ most deprived, 10 ¼ most affluent) among English children age 4–15 (reference group ¼ children in most affluent decile). Data source: English School Census, Spring 2008. N ¼ 6.2 million.
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Household asset quintile
Figure 4.2 Prevalence of maternal reported child intellectual disability by household deprivation quintile (1 ¼ most derived, 5 ¼ most affluent) in Mongolia, Thailand, and Macedonia. Data source: UNICEF Multiple Indicator Cluster Survey, 2005–2008. N ¼ 4910 (Mongolia), 16,564 (Thailand), and 2887 (Macedonia).
third round of UNICEF’s Multiple Indicator Cluster Surveys: http://www. childinfo.org/mics3_background.html). Two key observations arise from these data. First, the prevalence of intellectual disability is strongly related to socioeconomic position across a diverse range of countries, using different methods of ascertainment and different sampling strategies. Second, the strength of association between socioeconomic position and intellectual and developmental disabilities varies significantly by type and severity of disability (Baird et al., 2006; Chapman et al., 2008; Leonard & Wen, 2002; Murphy et al., 1988; Roeleveld et al., 1997). Consistent with previous research, stronger associations are found as the severity of intellectual disability decreases, with no apparent association between socioeconomic position and the prevalence of autistic spectrum disorder and profound multiple intellectual disability. The relevance of this evidence is clear. For some groups of families supporting children with intellectual or developmental disabilities (e.g., autistic spectrum disorders, profound multiple intellectual disability) exposure to low socioeconomic position or poverty will be similar to that in the wider population of families. For others, and especially for families supporting children or adults with less severe intellectual disabilities, rates of exposure will be significantly greater than in the wider population. Although socioeconomic gradients in the prevalence of intellectual disability have been repeatedly documented, less is known about the causal
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processes that underlie these gradients. Existing evidence points to the possible importance of (1) the additional costs associated with raising a child with intellectual disability leading to low socioeconomic position or poverty (Inclusion Europe, 2006; Inclusion International, 2006); (2) exposure to low socioeconomic position or poverty increasing the incidence of intellectual disability; and (3) selection effects with variation in other factors (e.g., low parental cognitive ability) contributing independently to risk of child intellectual disability and risk of low socioeconomic position/poverty. Previous research has documented some of the additional direct and indirect costs associated with raising a disabled child (Burchardt & Zaidi, 2008; Dobson & Middleton, 1998; Dobson, Middleton, & Beardsworth, 2001; Newacheck & Kim, 2005; Parish & Cloud, 2006; Tibble, 2005). Direct costs include the additional costs associated with transport, child care, equipment, wear and tear on clothing, and furnishings. Indirect costs primarily reflect the financial impact of reduced rates of maternal employment among families with a disabled child (Loprest & Davidoff, 2004; Parish, Seltzer, Greenburg, & Floyd, 2004; Porterfield, 2002). Other research has documented the modest long-term financial impact on families of raising a children with mild to borderline intellectual disability (Parish et al., 2004), and some limited (and rather dated) evidence that supporting a child with intellectual disability may reduce social mobility (Farber, 1968, 1970). If these additional costs are not compensated by receipt of welfare benefits or other forms of support (e.g., informal support from the extended family, support from charitable organizations), it is plausible to assume that they will have an impact on the incidence and duration of episodes of poverty (Inclusion Europe, 2006; Inclusion International, 2006). However, this possible explanation is challenged by the data presented above and elsewhere. First, it appears reasonable to assume that additional costs would, in general, be associated with the severity of disability or its social impact on family functioning. As such, the lack of a social gradient in the prevalence of autistic spectrum disorder or profound multiple intellectual disability in England, and the increasing strength of the social gradient as the severity of intellectual disability decreases, would appear inconsistent with the ‘‘additional costs’’ hypothesis, unless these costs were fully compensated for by welfare benefit receipt. Current opinion suggests that this is unlikely to be the case (Emerson, Madden, Robertson, Graham, Hatton, et al., 2009). Second, it is notable that the social patterning of intellectual disability is already well established among young children with early signs of cognitive delay. For example, half of all 3-year-old children in the UK with early signs of cognitive delay have been exposed to repeated episodes of income poverty (Emerson, Graham, McCulloch, Blacher, Hatton, et al., 2009). If the additional costs of caring were to account for the emergence of very
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strong social gradients in cognitive delays in early childhood, it must be accepted that within the first 3 years of a child’s life the additional costs associated with a bringing up a child with mild cognitive delays is sufficient to have a significant impact on the socioeconomic position of the majority of families in such situations. We do not find this argument plausible. In contrast, an alternative body of research suggests that growing up in poverty is associated with increased exposure to a wide range of material and psychosocial hazards (e.g., preterm, low birth weight, fetal growth restriction, exposure to a range of toxins and teratogens, poorer nutrition including reduced rates of breast feeding, poor housing conditions, exposure to less than optimal parenting, poorer educational opportunities, injury and accidents, exposure to more hazardous neighborhoods) that may impair cognitive development (Aber, Bennett, Conley, & Li, 1997; Bradshaw, 2001; Duncan & Brooks-Gunn, 2000; Irwin, Siddiqi, & Hertzman, 2007; Linver, Brooks-Gunn, & Kohen, 2002a; Marmot & Wilkinson, 2006; McLoyd, 1998). Finally, it is possible that the social patterning of the prevalence of intellectual disability may reflect selection processes, with other factors independently increasing the incidence of both child intellectual disability and family poverty (Heber, 1970). For example, limited intellectual functioning among parents is likely to increase the risk of intellectual disability in their children through (direct) genetic and (indirect) environmental pathways. Spinath, Harlaar, Ronald, and Plomin (2004), for example, in the first large-scale twin study of the genetic influences on mild and borderline intellectual disability, have reported significantly higher than average heritability estimates with concordance rates for monozygotic twins of 74%, compared to 45% among same sex dizygotic twins. Limited parental intellectual functioning may also, without support, be associated with less than optimal parenting skills (IASSID Special Interest Research Group on Parents and Parenting with Intellectual Disabilities, 2008) and increase the risk of exposure to low socioeconomic position or poverty through exclusion from the workforce (Maughan, Collishaw, & Pickles, 1999; Seltzer, Floyd, Greenberg, Lounds, Lindstrom, et al., 2005). Of course, these three possibilities (additional costs leading to low socioeconomic position, exposure to low socioeconomic position increasing the incidence of intellectual disability, selection effects) are not mutually exclusive and it is likely that none are sufficient in themselves to account for the association between socioeconomic position and the social patterning of intellectual disability. Indeed, untangling the relative contribution of these various pathways to the observed socioeconomic gradients in child disability is critical for deepening our understanding of the issue and for supporting the development of ‘‘evidence-based’’ social policies that could reduce the social inequalities faced by children with intellectual disabilities and their families.
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4. The Impact of Socioeconomic Position on Family Functioning and Child Well-Being There now exists a wealth of evidence documenting (in the general population) the negative impact of exposure to low socioeconomic position and/or poverty on attainment, productivity, health, well-being, and social exclusion (Bartley, 2004; Blau, 1999; Bornstein & Bradley, 2003; Bradley & Corwyn, 2002; Bradshaw, 2001; Brooks-Gunn & Duncan, 1997; Commission on the Social Determinants of Health, 2007; Duncan & Brooks-Gunn, 2000; Duncan, Brooks-Gunn, & Klebanov, 1994; Duncan, Yeung, Brooks-Gunn, & Smith, 1998; Galobardes, Lynch, & Davey Smith, 2004, 2008; Ghate & Hazel, 2002; Graham, 2007; Grantham-McGregor et al., 2007; Irwin et al., 2007; Lister, 2004; Marmot, 2005; Marmot & Wilkinson, 2006; McLoyd, 1998; Smith, Brooks-Gunn, & Klebanov, 1997; Wilkinson, 2005; Wilkinson & Pickett, 2009; World Health Organization, 2008). Four important themes emerge from these disparate and voluminous literatures that are relevant to our present concerns. First, evidence is accumulating that highlights the extent to which the negative outcomes associated with the experience of low socioeconomic position or poverty are related to the duration and depth of exposure (Ackerman, Brown, & Izard, 2004; Jarjoura, Triplett, & Brinker, 2002; Lynch, Kaplan, & Shema, 1997; Marmot & Wilkinson, 2006; McLeod & Shanahan, 1996; Petterson & Albers, 2004; Smith & Middleton, 2007). As a result, it is important to determine the extent to which specific groups are exposed to different poverty trajectories (e.g., transient, recurrent, or persistent poverty) or different levels of social mobility and the kinds of trigger events associated with poverty transitions or social mobility. For example, current evidence suggests that higher rates of poverty persistence are found among children in lone parent families and workless households, children belonging to minority ethnic groups, and younger children (Bradbury, Jenkins, & Micklewright, 2001b; Cappellari & Jenkins, 2002; Gottschalk & Danziger, 2001; Hill & Jenkins, 2001; Jenkins, Rigg, & Devicienti, 2001; Schluter, 2001; Smith & Middleton, 2007; Tsakloglou, 2003). It also suggests that, although their relative importance varies across types of households and by gender (Smith & Middleton, 2007), entries into and exits from poverty are primarily influenced by changes in labor-related income and employment status and secondarily by changes in household composition (e.g., birth into a poor household, separation, and repartnering) (Bane & Ellwood, 1986; Bradbury, Jenkins, & Micklewright, 2001a; Duncan et al., 1993; Jenkins et al., 2001; Smith & Middleton, 2007). To date, we are not aware of any studies that have investigated aspects of poverty dynamics among families supporting a child with intellectual or developmental disabilities.
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Second, it is clear that the negative outcomes associated with exposure to low socioeconomic position and/or poverty are mediated through a multiplicity of pathways. These include, but are not limited to, increased risk of exposure to a range of material and psychosocial hazards such as adverse birth outcomes, exposure to a range of toxins and teratogens, poorer nutrition, poor housing conditions, exposure to less than optimal parenting, poorer educational and occupational opportunities, injury and accidents, adverse life events, poorer health and welfare services, and poorer quality neighborhoods (Aber et al., 1997; Bradley, Corwyn, McAdoo, & Garcıa, 2001; Bradshaw, 2001; Chen, Martin, & Matthews, 2006; Conger & Conger, 2002; Conger, Conger, Elder, Lorenz, Simons, et al., 1992; Conger & Donnellan, 2007; Cubbin & Smith, 2002; Duncan & BrooksGunn, 2000; Evans & Kantrowitz, 2002; Kawachi & Berkman, 2003; Lanphear, Hornung, Khoury, Yolton, Baghurst, et al., 2005; Linver et al., 2002a; Marmot & Wilkinson, 2006; McLoyd, 1998; Miller & Korenman, 1994; Pickett & Wilkinson, 2007; Smith et al., 1997; Wilkinson & Pickett, 2009; World Health Organization, 2008). The significance of these two observations is reflected in the development of life course models in health and social research that emphasize the importance of cumulative risk of exposure to a wide variety of potentially interchangeable psychosocial and material hazards across the life course (Bartley, 2004; Davey Smith, 2002; Graham, 2007; Marmot & Wilkinson, 2006; Pickles, Maughan, & Wadsworth, 2007). Third, although the negative outcomes associated with exposure to low socioeconomic position and/or poverty may be mediated through a multiplicity of pathways, many of these pathways are rooted in family functioning and parenting practices (Bradley & Corwyn, 2002; Conger & Conger, 2002; Conger & Donnellan, 2007; Linver, Brooks-Gunn, & Kohen, 2002b). Conger and colleagues, in their family stress model, suggest that economic pressures associated with exposure to low socioeconomic position/poverty have a negative impact on parental well-being and family functioning that influence child development through their impact on parenting processes (Conger & Conger, 2002; Conger & Donnellan, 2007; Conger et al., 1992). In contrast, family investment models suggest that the link between socioeconomic position and child development may be mediated through the increased opportunity of wealthier families to invest in their child’s development and future (Bradley & Corwyn, 2002; Bradley et al., 2001; Davis-Kean, 2005; Linver et al., 2002b; Yeung, Linver, & Brooks-Gunn, 2002). These models are not, of course, mutually exclusive. They do, however, illustrate the variety of potential pathways through which the negative outcomes associated with exposure to low socioeconomic position and/or poverty may be mediated. Finally, it is clear that any risk arising from exposure to psychosocial or material hazards associated with low socioeconomic position/poverty may be moderated by a range of factors. Some children and their families are
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more resilient than others. Again, there exists a wide ranging and extensive literature on the issues of vulnerability and resilience in the face of adversity (Coleman & Hagell, 2007; Grant et al., 2006; Haskett, Nears, Ward, & McPherson, 2006; Luthar, 1999, 2003, 2006; Luthar & Brown, 2007; Luthar, Cicchetti, & Becker, 2000; Rutter, 1985, 1987, 1999, 2000; Schoon, 2006; Werner & Smith, 1992). A key message from this literature is that resilient functioning in children and young people is likely to reflect the complex interplay between individual characteristics and attributes (e.g., temperament, intelligence, personality, coping style, religiosity), the relationships with and characteristics of their families (e.g., supportive parenting style, family cohesion) and their relationships with and characteristics of the wider social context in which they are living (e.g., sense of belongingness to the local community, quality of educational and leisure services, neighborhood safety). Of course, many of the factors associated with resilient functioning are also related to socioeconomic position and/or poverty. As a result, the impact of low socioeconomic position/poverty on well-being is likely to operate through both increasing the cumulative risk of exposure to a variety of material and psychosocial hazards and by undermining the resilience of the person exposed. For example, children in poorer families are more likely than other children to have poor physical, emotional, or behavioral health, a likely source of concern for parents (Irwin et al., 2007; Keating & Hertzman, 1999; Marmot & Wilkinson, 2006). Parents in poorer socioeconomic circumstances are also likely to face greater difficulties than other parents when faced with such concerns as a result of a number of potential factors such as limited financial resources (particularly in nonsocialized health-care systems), limited social capital that may facilitate access to responsive and effective health care, limited geographical access to responsive and effective health care (which may be located in more affluent communities), and limited personal capital (e.g., negotiation skills that can often ease access to responsive and effective health care).
5. The Impact of Socioeconomic Position Among Families Supporting a Child with Intellectual or Developmental Disabilities In the preceding sections, we have summarized evidence indicating that (1) exposure to low socioeconomic position and/or poverty has a pervasive detrimental impact on attainment, productivity, health, and well-being and (2) people with intellectual disabilities and their families are significantly more likely than their nondisabled peers to be exposed to such circumstances during childhood. Unless people with intellectual disabilities and their
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families are somehow immune to the types of process that link socioeconomic position/poverty to health and well-being in the general population, we should therefore expect exposure to low socioeconomic position/poverty to be at least as important to understanding the functioning and well-being of families supporting a child with intellectual disabilities as it is for understanding the functioning and well-being of other families. There is, unsurprisingly, little or no evidence to suggest that such immunity exists. For example, we have recently demonstrated that the form of the relationship between breadth of exposure to socioeconomic risk and the prevalence of diagnosable mental health disorders is very similar for children with and without intellectual disabilities (Emerson & Hatton, 2007b). Indeed, the data presented in Fig. 4.3 suggest that, if there are any between-group differences, the association between socioeconomic 30% Emotional disorder
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Figure 4.3 Prevalence of emotional and conduct disorder among British children (age 5–16 years) with and without intellectual disability by level of exposure to social risk. Data source: 1999 and 2004 ONS Surveys of Child and Adolescent Mental Health in Britain. N ¼ 18,415.
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adversity and mental health appears to be stronger among children with intellectual disabilities (these differences were not, however, statistically significant). In Fig. 4.4, we present new data on the association between cumulative exposure to material disadvantage (number of socioeconomic risk factors experienced at child age 9 months and 3 years) and maternal mental health among a sample of approximately 13,000 UK mothers of 3-year-old children, 3% of whom were supporting a child with early signs of cognitive delay. Here, the form of the relationship is virtually identical for mothers of children with and without developmental delay. Given the lack of evidence of ‘‘immunity,’’ consideration of issues related to socioeconomic position and poverty may be relevant to (1) understanding differences in family functioning and family well-being between families who are and are not supporting a child with intellectual disabilities (or between subgroups of families supporting a child with intellectual or developmental disabilities); (2) understanding variation in family functioning and family well-being within the population of families supporting a child with intellectual disabilities; and (3) understanding the operation of specific processes within the population of families supporting a child with intellectual disabilities.
5.1. Socioeconomic position and between-group differences in well-being Given that exposure to low socioeconomic position and/or poverty has a pervasive detrimental impact on attainment, productivity, health, and well-being, and that families supporting a child with intellectual disabilities
Prevalence of possible mental health problem
35% 30% 25% 20% 15% 10% 5% 0% 0 1−2 3−4 5−6 7−8 Index of material disadvantage ECD
TD
Linear (ECD)
Linear (TD)
Figure 4.4 Prevalence of possible mental health problems among mothers of 3-yearold British children with and without cognitive delays by level of exposure of material disadvantage. Data source: UK Millennium Cohort Survey. N ¼ 12,689.
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are more likely to be exposed to such circumstances, it seems plausible to suggest that the health and social inequalities faced by families supporting a person with intellectual disabilities may—in part—be attributable to their poorer socioeconomic position. This is a proposition that our research group has been actively exploring over recent years. Numerous studies have reported higher rates of distress and lower rates of well-being among the mothers and, occasionally, fathers of children with intellectual or developmental disabilities (Baker, Blacher, Kopp, & Kraemer, 1997; Blacher & Hatton, 2007; Crnic, Friedrich, & Greenberg, 1983; Singer, 2006), with much of this of work reflecting a ‘‘stress reaction’’ model (Crnic et al., 1983). For example, Cummins concluded ‘‘mothers [of children with intellectual disabilities] are paying a very high price for providing care . . . [and] are at extreme risk of being highly stressed, clinically depressed, and with a subjective quality of life that is way below normal’’ (Cummins, 2001). We have tested the alternative proposition that, given the established link between low socioeconomic position and mental health/well-being (Fryers, Melzer, & Jenkins, 2003; Muntaner, Eaton, Miech, & O’Campo, 2004), this association may be wholly or partly attributable to the poorer socioeconomic position and increased risk of exposure to poverty of parents of children with intellectual disability. To date, we have reported data that suggest that increased risk of exposure to low socioeconomic position/ poverty may account for (1) over 50% of the risk for lower self-efficacy and self-esteem and 100% of the increased risk of unhappiness among a nationally representative sample of approximately 7000 British mothers of children with and without intellectual disability (Emerson, Hatton, Blacher, Llewellyn, & Graham, 2006); (2) 50% of the increased risk for probable psychiatric disorder among a nationally representative sample of approximately 4000 Australian mothers of 4–5-year-old children with disabilities (Emerson & Llewellyn, 2008); and (3) 31–62% of the increased risk for probable psychiatric disorder among a nationally representative sample of approximately 13,000 UK mothers of 3-year-old children with early cognitive delay (Emerson, McCulloch, Graham, Blacher, Llewellyn, et al., in press). More recently, Olsson and Hwang (2008) have also reported that social and material hardship and poorer general health accounted for the increased risk of poorer maternal well-being in a sample of Swedish families. These results represent a direct challenge to narrow versions of ‘‘stress reaction’’ models by suggesting that the poorer well-being of parents of children with intellectual disabilities may result as much from their exposure to socioeconomic adversity as it does from exposure to any specific stresses associated with their child’s disability. With regard to children, our research suggests that increased exposure to low socioeconomic position/poverty may account for (1) 20–50% of the increased risk for poorer health and mental health among two nationally
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representative cohorts of British children and adolescents with intellectual disabilities (Emerson & Hatton, 2007a,b,c); (2) 29–43% of the increased risk for conduct difficulties, 28–48% of the increased risk for emotional difficulties and 36–43% of the increased risk for peer problems among a nationally representative cohort of 6–7-year-old Australian children with intellectual disabilities or borderline intellectual functioning (Emerson, Einfeld, et al., in press); and (3) a significant proportion of increased rates of self-reported antisocial behavior and smoking among adolescents with intellectual disability (Dickinson et al., 2007; Emerson & Turnbull, 2005). The association between socioeconomic position/poverty and children’s emotional and behavioral health is also relevant to our understanding of parental well-being given the link between child behavior and maternal well-being (Baker, Blacher, & Olsson, 2005; Baker, McIntyre, Blacher, Crnic, Edelbrock, et al., 2003; Blacher & Hatton, 2007).
5.2. Socioeconomic position and within-group differences in well-being All of the above results also provide evidence that exposure to poverty or low socioeconomic position accounts for part of the variation in well-being within groups of mothers of children with intellectual disabilities. Additional evidence is provided by some studies that have specifically addressed variation in well-being among mothers of children with intellectual and developmental disabilities (Eisenhower & Blacher, 2006; Emerson, 2003; Floyd & Saitzyk, 1992; Flynt & Wood, 1989; Gallimore, Weisner, Bernheimer, Guthrie, & Nihira, 1993; Hatton, Azmi, Caine, & Emerson, 1998; Herman & Thompson, 1995; Johnston et al., 2003; Llewellyn et al., 2003; Park, Turnbull, & Turnbull, 2002; Smith, Oliver, & Innocenti, 2001; Witt, Riley, & Coiro, 2003). It should be noted, however, that many other studies have failed to report an association between socioeconomic position/poverty and the well-being of parents of children with intellectual disability. Potential reasons for this variation in the existing literature will be discussed below.
5.3. Socioeconomic position as a moderating variable The evidence reviewed above is consistent with the notion that socioeconomic position/poverty are important social determinants of health and well-being. There is also evidence to suggest that socioeconomic position may also influence (moderate) some of the associations that are often central to the concerns of family researchers. For example, we have previously presented evidence to suggest that socioeconomic position may moderate the association between child disability status and maternal well-being with markedly stronger associations being apparent in more affluent families
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Odds ratio for poor mental health
Socioeconomic Position
6 5 4 3 2 1 0
0 1 2+ Index of persistent material disadvantage
Odds ratio for poor physical health
6 5 4 3 2 1 0
1 2+ 0 Index of persistent material disadvantage
Figure 4.5 Odds ratios for poorer maternal health outcomes being associated withchild developmental delay at age 3 by level of exposure to persistent material disadvantage. Data source: UK Millennium Cohort Survey. N ¼ 12,689.
(Emerson, 2003; Hatton & Emerson, 2009). The data in Fig. 4.5 are indicative of similar associations with regard to the relationship between early cognitive delays and the physical and mental health of mothers of 3-year-old children in the UK. As exposure to persistent material hardship increases, the strength of these associations diminishes. These contemporary observations are consistent with those made nearly half a century ago that higher socioeconomic position was associated with more negative reactions to the diagnosis of intellectual disability (Farber, 1960, 1970). They are also consistent with more recent evidence that parents with higher socioeconomic position report that raising a child with intellectual disabilities has a greater negative impact on the child’s siblings than do poorer parents (Blacher, Neece, & Baker, 2008; Mulroy, Robertson, Aiberti, Leonard, & Bower, 2008). The potential moderating effects of socioeconomic position are also apparent from studies of intervention effectiveness. For example, studies of the effectiveness of group-based behavioral parent training programs have suggested that such programs may be significantly less effective for more disadvantaged parents in general (Lundahl, Risser, & Lovejoy, 2006) and among parents of children with intellectual or developmental disabilities (Harris, Alessandri, & Gill, 1991).
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6. Moving Forward: Methodological and Conceptual Issues Associated with Incorporating Socioeconomic Position into Family Research Given the evidence summarized above it is somewhat surprising that family research in the field of intellectual and developmental disabilities has, in general, paid little attention to issues related to socioeconomic position and poverty (Emerson, Graham, et al., 2006). For example, the two chapters addressing family research in the recent Handbook of Developmental Disabilities (Blacher & Hatton, 2007; Lounds & Seltzer, 2007) contained just one mention of the potential importance of socioeconomic position. This omission is particularly puzzling given that consideration of poverty and socioeconomic position were central to the pioneering work on families by Farber in the 1960s (Farber, 1960, 1968, 1970), early studies of the epidemiology of intellectual disability (Heber, 1970), formed the basis for selection into landmark early intervention programs (e.g., Abecedarian Project, Milwaukee Project, Perry Preschool Project), and were emphasized both by Uri Bronfenbrenner in his seminal paper on the ecology of human development (Bronfenbrenner, 1977) and by Keith Crnic and colleagues in their oft cited application of ecological models to family research in the field of intellectual and developmental disabilities (Crnic et al., 1983). As the latter suggested over 25 years ago, ‘‘utilitarian resources, including such factors as SES and income, can have potentially powerful effects on adaptation’’ (p. 134). Since that time, however, the research agenda relating to families supporting a person with intellectual and developmental disabilities has been increasingly dominated by rather narrow psychological models of ‘‘stress and coping’’ within which aspects of social context are oft relegated to the status of background noise that, at best, needs controlling for. The dominant paradigm within this research agenda is to search for ever more proximal causes of (or mediating pathways to) human functioning, the discovery of which is taken to ‘‘account’’ for the operation of more distal causes. Of course, the identification of mediating pathways is critically important in developing a more nuanced account of the interrelationships among the variables of interest and for identifying the possibility of ‘‘downstream’’ interventions to address social problems. It is an error, however, to consider that evidence of mediation reduces the significance or social importance of distal variables. Indeed, a radically different view is often taken in public health research, for example on the social determinants of health, where the research agenda focuses explicitly on identifying the distal causes of more proximal events, or, in the words of Professor Sir Michael Marmot (Chair of the World Health Organization Special Commission on the Social Determinants of Health) ‘‘the causes of
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the causes’’ (Commission on the Social Determinants of Health, 2007). Such an approach opens up the possibility of developing ‘‘upstream’’ interventions that may have a pervasive impact on the health and well-being of populations. Of course, both approaches are necessary to develop a more comprehensive understanding of the situation of families and to support the development of ethical and effective social policies (Seccombe, 2002). Integrating consideration of socioeconomic position and poverty into family research has implications for (1) the use of theoretical models that explicitly link broader social and contextual factors to family functioning and well-being; (2) the use of appropriate measures of socioeconomic position and poverty; (3) the application of analytic strategies that distinguish between distal and proximal effects; and (4) sampling strategies.
6.1. Models The first requirement of any attempt to integrate consideration of issues relating to socioeconomic position and poverty into family research is the development and use of theoretical models that explicitly link these factors to the outcomes of interest (e.g., family well-being, parenting practices, child well-being). Influential models in this area include the family stress model developed by Conger and colleagues (Conger & Conger, 2002; Conger & Donnellan, 2007; Conger et al., 1992) and Pearlin’s stress and coping model (Pearlin, Mullan, Semple, & Skaff, 1990; Pearlin, Schieman, Fazio, & Meersman, 2005; Pearlin & Schooler, 1978). The family stress model suggests that the effects of poverty are mediated through the impact of economic pressures or stresses on parental well-being. Poorer parental well-being is hypothesized to lead both directly to less nurturing and involved parenting and indirectly to the same intermediate outcome via increased parental conflict and reduced warmth/support. Less nurturing and involved parenting is hypothesized to lead to poorer child outcomes. Similarly, Pearlin’s approach draws attention to the important role played by socioeconomic position on determining cumulative exposure to stressors over the life course (Pearlin et al., 2005). In Fig. 4.6, we present an elaboration of a slightly simplified version of the family stress model that also draws on conceptual models from health inequalities research and the study of resilience. Specifically, we have attempted to draw attention to the associations among socioeconomic position, access to economic resources and human and social capital, and neighborhood environments. Aspects of both parental human and social capital/neighborhood environments may have direct effects on each of the intermediate outcomes in the mediating pathway and (perhaps more importantly) may serve to moderate the links between the intermediate outcomes in the mediating pathway. Thus, for example, the link between household economic resources (income and assets) and experienced material and social
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Low socio-economic position
Reduced social capital (networks, support), poorer neighbourhood resources and environmental safety/quality
Low income and assets
Greater material and social hardship
Reduced parental well-being and family functioning
Less optimal parenting style and practices
Poorer child outcomes
Reduced human capital (knowledge, skills, problem solving abilities, coping styles)
Figure 4.6 Modified family stress model illustrating the associations between socioeconomic position, access to economic resources, and human and social capital and neighborhood environments.
hardship will depend, in part, on aspects of both human capital (e.g., family values, problem-solving abilities, coping styles, and behaviors) and social capital (e.g., availability of compensatory support from family, friends, and neighbors). In addition, aspects of human capital (e.g., parenting knowledge, parenting self-efficacy) and social capital (e.g., availability of parenting-related support from family, friends, and neighbors) are also likely to have a direct effect on parenting behaviors independent of household economic resources (although they may be correlated due to their common association with socioeconomic position). Such a model suggests changes to what should be investigated in family research. One line of enquiry may concern families’ perceptions of their place in relevant social hierarchies, the impact of this on their health and well-being, and the family practices and behaviors that result from these perceptions. Research with adults with intellectual disabilities suggests that awareness of stigma and low social status can have a significant effect on mental health and well-being (Dagnan & Sandhu, 1999; Dagnan & Waring, 2004; Jahoda, Trower, & Pert, 2001). Such considerations are highly likely to be relevant to other family members and to be possibly moderated by socioeconomic position.
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The more contextualized model of family functioning in Fig. 4.6 also suggests framing family research on ‘‘culture’’ beyond categorizations based on ethnicity. Research attempting to account for variations in family well-being across ethnic groups clearly needs to include socioeconomic position alongside cultural explanations for such differences. Equally, family research within ethnic groups (including majority ethnic groups) needs to explicitly examine variations in family cultures according to variations in socioeconomic position. The use of such models provides essential frameworks for the design and analysis of quantitative research and can also provide important guides for qualitative investigations of the nature of parenting under conditions of adversity (Parish, Magaha, & Cassiman, 2008; Russell, Harris, & Gockel, 2008).
6.2. Measures of socioeconomic position and poverty We addressed issues of the measurement of socioeconomic position and poverty in detail in a previous volume of this series (Emerson, Graham, et al., 2006). There also exist a number of excellent general reviews of this area (Galobardes, Shaw, Lawlor, Davey Smith, & Lynch, 2006; Galobardes, Shaw, Lawlor, Lynch, & Davey Smith, 2006a,b; Lister, 2004; Shaw et al., 2007). In this section, we focus on four critical aspects of the measurement of socioeconomic position and poverty relating to families. 6.2.1. Measure the key components of socioeconomic position separately In the introduction, we argued that socioeconomic position results from the stratifying operations of key social institutions, in particular through regulation of education (a key determinant of acquired human capital) and the labor market. The result of occupying a particular socioeconomic position is evident in relation to key aspects of living such as command over economic and social resources. There exist a number of composite measures of socioeconomic position. The most common of these is the Hollingshead four-factor index of social status, which combines data on the educational attainment and occupation of all employed adults in a household into a single score. Although widely used in US child development research (Ensminger & Fothergill, 2003), it has a poor theoretical or empirical rationale. In addition, there exists an emerging consensus that it is important to measure and analyze the impact of the central components of socioeconomic position (education, occupation, economic resources) separately in order to disentangle their effects on outcomes of interest (Aber et al., 1997; Duncan & Magnuson, 2003; Ensminger & Fothergill, 2003; Galobardes, Shaw, et al., 2006b). This is particularly relevant in research related to families supporting a child with intellectual or developmental disabilities
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where there are particular reasons for treating parental education as a distinct variable given its likely association with parental intellectual functioning. 6.2.2. Measure hardship or financial strain rather than income The effects of low income are moderated by the extent to which the family can buffer the impact of low income through spending savings, accruing debt and through the effects of ‘‘in-kind’’ support from friends and relatives. These effects are likely to be particularly influential in moderating the impact of short-term poverty spells (Adelman, Middleton, & Ashworth, 2003; Magadi & Middleton, 2005). The use of income-based measures of poverty is likely to underestimate poverty rates among families supporting a child with intellectual or developmental disabilities as existing equivalence scales do not take account of any additional costs associated with raising a disabled child (Burchardt & Zaidi, 2008; Zaidi & Burchardt, 2003). Indeed, increased levels of material and social hardship among families supporting a child with disabilities have been reported even when income and other potential confounding factors have been taken into account (Emerson & Hatton, 2007d). As a result, increasing attention has been paid to the direct measurement of aspects of material and social hardships arising from economic disadvantage (Gordon, 2000; Gordon, Levitas, & Pantazis, 2005; Mack & Lansley, 1985; Mayer & Jencks, 1988; Nolan & Whelan, 1996; Parish, Rose, et al., 2008; Saunders, Naidoo, & Griffiths, 2007) and financial strain (Headey, 2006). Hardship measures are commonly based on the identification of items/events that a family would like to own/experience (and are deemed typical or essential for family life in that society), but cannot be due to financial constraints. Indicators of hardship provide a more direct measure of poverty, are easier to collect and are typically more strongly associated with indicators of family well-being than measures of income (Emerson, Hatton, et al., 2006; Emerson, McCulloch, et al., in press; Olsson & Hwang, 2008; Parish, Rose, et al., 2008). 6.2.3. Measure cumulative or repeated exposure to socioeconomic disadvantage Life course models of health inequalities emphasize the impact on health and well-being of cumulative exposure to multiple stressors or hazards over time (Bartley, 2004; Davey Smith, 2002; Galobardes, Shaw, et al., 2006b; Graham, 2007; Marmot & Wilkinson, 2006; Pearlin et al., 2005), an emphasis supported by analyses of the impact on child well-being of exposure to persistent poverty (Ackerman et al., 2004; Jarjoura et al., 2002; Lynch et al., 1997; Marmot & Wilkinson, 2006; McLeod & Shanahan, 1996; Petterson & Albers, 2004; Smith & Middleton, 2007). As a result, there may be considerable value in the use of derived indices of exposure over time to aspects of socioeconomic disadvantage. For example, in our current analyses we have reported that risk of early cognitive delays is
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associated with repeated exposure to material disadvantage over and above the effects of individual exposures (Emerson, Graham, et al., 2009). As noted above, however, it is important that such cumulative risk indices do not conflate different aspects or dimensions of socioeconomic position. Similarly, within poverty research increasing attention is being paid to the development of indicators of poverty based on poverty persistence (Middleton, Barnes, & Millar, 2003). 6.2.4. Measure area-level aspects of social deprivation and social capital In addition to household-level measures of socioeconomic position/ poverty, there exist an increasing number of well-constructed measures of area or neighborhood-level deprivation (Eibner & Sturm, 2005; Kreiger, Williams, & Moss, 1997; Noble et al., 2004; Trewin, 2003). These are of interest for two reasons. First, in many societies deprivation and affluence are inequitably geographically distributed. As a result, it is possible to use area-based measures of deprivation as proxy measures for household-level deprivation. This is particularly relevant as such measures can often be easily derived from census-defined areas, or postal or zip code data. It should be kept in mind, however, that the association between household poverty and neighborhood poverty is often complex. For example, the conjunction between family and neighborhood poverty varies with ethnicity, with 27% of poor African American children and 20% of poor Hispanic children compared with just 3% of poor European American children living in poor neighborhoods (Magnuson & Duncan, 2002). Second, the impact of area-level or ‘‘neighborhood effects’’ is of interest in its own right. Thus, for example, there is now clear evidence to suggest that, once any effects due to household-level socioeconomic position/ poverty are taken into account, growing up in poorer neighborhoods is itself associated with poorer educational attainment and increased risk of adverse behavioral and emotional outcomes for children (Leventhal & Brooks-Gunn, 2000; Sampson, Morenoff, & Gannon-Rowley, 2002; Seccombe, 2000). There also exist a number of indicators of the extent of inequality (rather than deprivation) within populations (Kawachi & Kennedy, 1997; Shaw et al., 2007), the most commonly used of which is the Gini coefficient. This hypothetically varies from 0 (perfect equality) to þ 1 (perfect inequality). Gini coefficients of income inequality currently vary from approximately 0.2 in Japan and Scandinavia, 0.3 in Australia, Canada, and the UK, 0.4 in the US, Mexico, and Singapore, 0.5 in many South American countries to a high of 0.7 in Namibia (United Nations Development Programme, 2007). Such measures are of use in disentangling the effects of exposure to deprivation (e.g., living in poverty) and the impact of living in cities, regions, or
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nations that vary with degree to their overall level of stratification or inequality (Wilkinson, 2005; Wilkinson & Pickett, 2009). We have recently used area-level indicators of deprivation in two studies of the emotional and behavioral needs of young people with intellectual disabilities (Emerson, Robertson, & Wood, 2005, 2007) and in a study of the life experiences of adults with intellectual disabilities (Emerson, Malam, Davies, & Spencer, 2005). The results of these analyses suggested that when controlling for household-level deprivation, adults with intellectual disabilities who lived in poorer neighborhoods were more likely to live in unsuitable accommodation, be less satisfied with their education, have been bullied at school, have less access to services, be an unpaid carer for another adult, engage in a more restricted range of community-based activities, not feel safe, be a victim of crime, smoke, and be less happy. We are unaware of any studies that have investigated the impact of variations in income inequality on the health or well-being of people with intellectual or developmental disabilities or their families.
6.3. Analytic strategies The use of more sophisticated models that identify pathways that mediate the impact of socioeconomic position on family functioning or well-being (and moderating relationships that suggest that such relationships may be conditional on the presence of other variables) requires a more sophisticated approach to statistical analysis. As we have noted above, to achieve a more nuanced understanding of family well-being it is critical that we identify both proximal and distal factors associated with variation in well-being. This requires that analytic techniques allow for the identification of potential mediation effects (e.g., through the use of hierarchical regression methods) (MacKinnon, Fairchild, & Fritz, 2007). The use of standard regression techniques runs the risk of discounting the importance of distal variables (e.g., socioeconomic position) if the model also includes variables related to potential mediating pathways (e.g., parental health and well-being, parenting practices, exposure to adverse life events). As we have argued above, between-group analyses (e.g., comparing the well-being of families supporting children with/without intellectual disabilities, or children with different causes of intellectual disabilities) will need to control for the possible impact of multiple confounding variables (e.g., differential exposure to multiple indicators of socioeconomic position). In such instances, it is suggested that researchers may wish to attend to more recent developments in statistical techniques such as propensity score matching (Blackford, 2007; Emerson, Einfeld, et al., in press; Emerson, McCulloch, et al., in press; Oakes & Johnson, 2006).
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6.4. Sampling Finally, addressing the potential importance of socioeconomic position in family research requires the use of sampling strategies that ensure the participation of families from a diverse range of socioeconomic positions (the potential impact of socioeconomic position is obviously difficult to detect in samples that show little variation in the variables of interest). However, ensuring representative participation (or adequate variation in socioeconomic position) is likely to prove problematic given that families in poorer circumstances are, in general, less likely to volunteer to participate in social research and more likely to drop out following enrolment (Groves, 2006; Groves & Couper, 1998). Possible strategies to overcome these difficulties include the development of longer-term collaborative relationships between researchers and community-based organizations supporting more disadvantaged families (Markey, Santelli, Johnson, Turnbull, & Turnbull, 2001), purposive sampling or oversampling in more disadvantaged areas (Groves, 2006), the use of weights and other statistical methods to take account of differential recruitment and retention rates (Brick & Kalton, 2005; Groves, 2006), and the secondary analysis of administrative data sets and well-constructed population-based samples (Emerson, Einfeld, et al., in press; Emerson & Hatton, 2007d; Emerson, Hatton, et al., 2006; Urbano & Hodapp, 2007).
7. Conclusions In the preceding sections, we have argued that research related to families supporting people with intellectual or developmental disabilities should pay greater attention to issues relating to their socioeconomic position and their experience of poverty. We have also discussed key conceptual and methodological issues relevant to such an enterprise. It is absolutely clear that, in the general population, exposure to low socioeconomic position and/or poverty has a pervasive detrimental impact on attainment, productivity, health, and well-being. There is no evidence to suggest that families supporting a person with intellectual or developmental disabilities are ‘‘immune’’ to such processes. There is extensive evidence to suggest that they are more likely than other families to be exposed to such circumstances. Addressing these issues will be necessary for developing a more nuanced understanding of the situation of families supporting a person with intellectual or developmental disabilities, for developing evidence-based social policies that address some of the root causes of family problems (Seccombe, 2002), and for reducing the chances of overpathologizing the role of disabled people in such families.
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C H A P T E R
F I V E
Using Large-Scale Databases to Examine Families of Children with Intellectual and Developmental Disabilities Robert M. Hodapp*,† and Richard C. Urbano*,‡ Contents 1. Studying Families of Persons with Specific Disabilities 2. Three Large-Scale Approaches to Family Research 2.1. Large-scale approach 1: National surveys 2.2. Large-scale approach 2: National Vital Statistics System databases 2.3. Large-scale approach 3: Examinations, surveys, or records targeted to a specific city, state, or region 3. Two Examples of Using Large-Scale Administrative Databases to Answer Family-Related Questions 3.1. Divorce in families of children with Down syndrome 3.2. Demographic characteristics of African American versus White mothers of newborns with Down syndrome 4. Comparing Different Types of Large-Scale Databases 4.1. National data sets versus data sets specific to a region, state, or city 4.2. Sample versus population 4.3. Quality of the data 5. Summary and Conclusion Acknowledgments References
133 135 136 148 156 165 166 167 169 169 170 171 172 173 173
Abstract In this chapter, we argue for the increased use of large-scale databases to examine families of individuals with disabilities. To date, three main approaches have been employed. First, researchers have analyzed data from among the wide * { {
Vanderbilt Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, Tennessee 37203, USA Department of Special Education, Peabody College, Vanderbilt University, Nashville, Tennessee 37203, USA Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37005-6
#
2009 Elsevier Inc. All rights reserved.
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array of national surveys that have been supported by the National Institutes of Health (NIH), Centers for Disease Control and Prevention (CDC), US Census Bureau, Department of Education, and other (mostly federal) agencies. In the second approach, national Vital Statistics records have been examined, including information about all of the United States’ births or deaths in a particular calendar year. In the third approach, examinations have been more targeted to all families of children or adults with disabilities residing in a particular city, state, region, or area. Though each has its own strengths and weaknesses, all three large-scale approaches can address many questions about families of children and adults with disabilities. We end this chapter by providing two examples of how we have used Tennessee administrative data sets to answer questions about the structure and characteristics of families of children with Down syndrome; we also discuss continuing issues concerning the use of large-scale databases to tell us about the nature and functioning of families of individuals with disabilities.
In reviewing the history of research and writing on families of persons with disabilities, one can pinpoint three distinct generations. In the first generation, prior to the 1980s, most families were considered to be doing poorly. Mothers and fathers were thought to suffer from depression and other psychiatric problems; couples from inadequate time and energy, putting them at risk for divorce; siblings from not receiving enough parental attention; and families as a whole from economic immobility. This perspective has been referred to as the ‘‘bad things’’ model of parent and family reactions to having a child with disabilities (Hodapp & Ly, 2005). In a marked break, a second tradition began in the early 1980s, when Crnic, Friedrich, and Greenberg (1983) proposed that children with disabilities constitute an added stressor in the family system. Like sickness, moving, having a new baby, natural disasters, or other major events that occur to one or all members, families can react positively, negatively, or in some combination to any important life event. Crnic et al. (1983), then, considered the earlier ‘‘bad things’’ perspective as overly pessimistic and overly deterministic. They noted that families react in different ways, and that reactions are often determined by characteristics of the child, by the family’s internal and external resources, and by how that family conceptualizes the child and the child’s disability (Minnes, 1988). Over the past few years, we seem to have witnessed a third generation of disability family research, although exactly how to characterize this new research remains debatable. Some would argue that we are moving beyond stress-and-coping perspectives to encompass the more positive, lifeaffirming aspects that children with disabilities provide to families and family members (Dykens, 2006; Glidden & Schoolcraft, 2007). Others posit that the third generation moves beyond White, middle-class families, to encompass issues of family poverty (Emerson, 2007; Stoneman, 2007) and ethnicity (Magana, this volume). Still others highlight the third generation’s more
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life-span perspective (Seltzer, Greenberg, Orsmond, & Lounds, 2005), or the burgeoning interest in families of individuals with different genetic etiologies, psychiatric conditions, timings of the child’s diagnosis, or other personal characteristics (Hodapp, 2004; Seltzer, Abbeduto, Krauss, Greenberg, & Swe, 2004). While not taking a position as to the ‘‘true’’ nature of this third generation, we note instead that today’s new research is characterized by increased complexity. No longer does it seem sufficient to include as outcomes only high levels of maternal stress or other negative measures. Similarly, no longer is it sufficient to study only families who are White or middleclass, persons with disabilities who are only children, or persons with disabilities who are comprised only of persons with some mixed or unknown causes of intellectual disabilities. But these more complex research questions, in turn, make more salient the question of practicality: In essence, our notions of what constitutes upto-date family research have increasingly outdistanced our abilities to perform such studies. From the measurement side, we continue to have poor and inconsistently used measures of stress (Glidden, 1993; Glidden & Schoolcraft, 2007) and virtually no disability-related measures of other, more positive constructs. Similarly, we have only a few studies that focus on larger samples that might allow for more sophisticated statistical approaches. And, although a few notable projects have followed over time families when offspring were either children (Eisenhower, Baker, & Blacher, 2009; Section 1, this volume) or adults (Seltzer, Floyd, Greenberg, Lounds, & Hong, 2005; Taylor, Greenberg, Seltzer, & Floyd, 2008), the vast majority of studies of families of offspring with disabilities are not longitudinal, making the problem of ‘‘what caused what’’ more difficult to discern. Although contributors to this volume tackle different aspects of these issues, we here focus on the problem of sample sizes in disability family research. Although our discussion will also explore these issues more generally, we focus most of our attention on families of children with Down syndrome or with other, specific causes for their intellectual disabilities. After presenting the problem, we next discuss three distinct types of largescale data sets, before providing examples of the types of issues such data sets can address for the field of disability family studies.
1. Studying Families of Persons with Specific Disabilities As the family field has progressed over the past two decades, it has become increasingly apparent that families of individuals with different types of disability are not equal. Compared to families of children with
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other disabilities, families of children and adults with Down syndrome generally cope better, a phenomenon often referred to as the ‘‘Down syndrome advantage’’ (Hodapp, Ly, Fidler, & Ricci, 2001; Seltzer & Ryff, 1994). Conversely, in most studies, families of persons (usually children) with autism fare worse (Dumas, Wolf, Fisman, & Culligan, 1991; Olsson & Hwang, 2001; Sander & Morgan, 1997). Several within-group findings are also of interest. Consider Seltzer, Greenberg, Krauss, Gordon, and Judge’s (1997) finding concerning the siblings of adults with intellectual disabilities versus with mental illness. When siblings spent more time with, and reported themselves closer to, their brother/sister with disabilities, they more often also reported better coping and less depression when the brother/sister with disabilities had intellectual disabilities, but more depression and lower levels of coping when the brother/sister had mental illness. As predicted by the ‘‘A’’ (or child characteristics) term of the ‘‘Double ABCX’’ model concerning child, parent, and family perceptions as correlates of parent stress (McCubbin & Patterson, 1983; Minnes, 1988), both between-group and within-group studies suggest that certain characteristics of the person with disabilities relate to differential levels of family coping. In these and other family studies, however, examinations of both child and family characteristics run headlong into the problem of sufficient sample size. As Urbano (2009) notes, the general rule of thumb concerns the size of the smallest group, with most statisticians suggesting that one may examine in, say, a regression analysis only 1/10th the number of predictors as participants. But this 1/10th rule applies to the smaller group: thus, if one is examining families of 40 children with Down syndrome and 60 families of children with mixed causes of their intellectual disabilities, then one may examine only four independent predictors (i.e., 40 divided by 10), not six predictors (60 divided by 10), or 10 predictors (100—the combined subject number—divided by 10). Although such issues are further complicated by effect sizes, normal (or non-normal) distributions, and other statistical concerns (Green, 1991), it remains the case that more complicated explanations can only be derived through the use of increasingly larger sample sizes. Within family research, this problem becomes exacerbated by low prevalence rates and high numbers of potential child and family predictors. From one side, many different conditions associated with intellectual disabilities occur relatively rarely. Although exact numbers are only sometimes available, prevalence rates of many conditions are often on the order of 1 per 10,000–1 per 50,000 live births. In our own state of Tennessee, for example, there are about 85,000 births per year. If a disorder occurred at a rate of 1 per 10,000 births, only eight or nine children would be expected; a disorder occurring in 1 per 50,000 births would likely have years with no births at all. Even for the most common conditions—Down syndrome and autism spectrum disorders (ASD)—relatively few births occur throughout the state each year. For Down syndrome, which has historically been
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thought to occur in 1 per 800–1000 live births, the highest recorded prevalence rate was noted by Canfield et al. (2006) at 1 per 733 births. Given this number, one would expect approximately 116 births per year throughout the entire state. Given the most recent estimates that approximately 1 per 150 children has autism spectrum disorder, one would expect 567 births per year. These relatively small numbers must be appreciated within the context of the many variables that might relate to family coping. Concerning offspring characteristics, family coping might be related to the offspring with disability’s gender, age, overall level of functioning, behavior problems, school placements, associated health problems, appearance, or age of diagnosis. Parent–family functioning or specific aspects of that functioning (e.g., coping of the nondisabled siblings) might also relate to maternal marital status, maternal and/or paternal age or education, maternal age at birth, family SES, family size, presence of an older sister or brother, age spacing among the siblings, the presence of a same-sex sibling as the child with disabilities, and/or the presence of older or younger nondisabled siblings. Many child and family predictors thus potentially influence family functioning, even though the field mostly employs small-scale studies and often examines disability subgroups (e.g., certain genetic disorders) for which prevalence rates are fairly low. We are rapidly exceeding the four or five variables that can be examined in most small-scale family studies. In reaction to this problem, studies have been attempted that employ one of three distinct data sets. Each serves to increase sample sizes, is underutilized in disability family research, and has important strengths and weaknesses that remain mostly unexamined. We now turn to these three research approaches.
2. Three Large-Scale Approaches to Family Research The following three large-scale approaches have been used in family research. The first involves the use of large-scale national surveys, often with a specific disability component (usually an extra survey or callback); the second employs national vital statistics data; the third uses targeted examinations (MADDS), surveys (California’s CDER), or administrative databases (our Tennessee studies) of a particular city, state, or region. Before describing and evaluating each, we begin by noting that, with the exception of some of the targeted examinations, most large-scale studies are not predominantly focused on either disabilities or on family issues. Consider, for example, the disability-related questions present in official administrative records. Although in most states the official birth records
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conform to the guidelines of the CDC and its National Center for Health Statistics (NCHS), these records cannot capture any congenital anomaly that is not observable at the infant’s birth. Thus, while 12 birth defects (formerly, 22) are currently captured, no designation is provided for fragile X syndrome, autism, or Prader–Willi syndrome. Records from when the child is older, including hospital discharge records, do capture these conditions, but much of the specificity often included in small-scale behavioral studies—including detailed attention to diagnoses (e.g., ADI-R diagnosis in autism; different genetic subtype of fragile X or Prader–Willi syndromes)— often is not collected in these studies. From the other direction, questions or information found in most largescale data sets focus little on family issues. Consider family demographics. For several decades, the field has known that, as a group, mothers cope worse when they are single parents, less educated, in poor marriages, and in lower SES households (Beckman, 1983). But such family characteristics are poorly characterized in at least some national surveys. In the National Survey of Children with Special Health Care Needs of 2005–2006 (NS-CSHCN), a recent survey specifically asking whether a child in the family has Down syndrome, autism, or other conditions, many family questions are either missing or asked indirectly. No question asks respondents (usually mothers) how old they are, and education is asked in terms of the most highly educated person in the household (‘‘What is the highest level of school that anyone in the household has completed or the highest degree anyone in the household has received?’’; CW10Q04—italics in original). Marital status must be inferred from two different questions, one asking about whether the respondent is the biological mother (S10Q00) and another asking if the respondent lives with other adults (including the biological father; S10Q02). Despite these limitations, all three types of large-scale studies are useful in understanding many family-related questions.
2.1. Large-scale approach 1: National surveys Table 5.1 provides an overview of the most well-known national surveys in the United States. Although not a comprehensive listing, these surveys have produced much of what we know about the health and well-being of children in this country. A similar set of surveys exists in European countries (Walsh, 2008). The first noteworthy aspect of Table 5.1 is who produces these surveys. With only a few exceptions, these national surveys are a product of different agencies of the United States federal government. As a part of the government’s mission to track demographic characteristics, health, economic conditions, education, and other aspects of the US population, various federal departments commission surveys. Lead departments and centers
Table 5.1
Summary of national surveys
Survey
Sponsoring agency
Date
Description
Disabilities
National Health Interview Survey
CDC/NCHS
Yes A household interview 1957–present, survey that collects data with a revised on a broad range of questionnaire health topics. Its annual in use from sample size is n ¼ 35,000 1996 households (87,500 persons).
National Health Interview Survey– Disability Survey
1994–1995 DHHS, CDC, NICHD, SAMHSA, DOE, Health Care Financing Administration, SSA, DOT, Robert Wood Johnson Foundation
Yes A two-phase personal household interview survey about disabilities in the American population. Phase I was administered at the same time as NHIS. Phase II (also called the Disability Followback Survey— DFS) was based on responses to Phase I survey and requested
Categories
Types of ID Functioning
Yes Mental retardation, developmental delay (any kind), ADD/ ADHD, Down syndrome, cerebral palsy, learning disability, autism Yes Learning disability, cerebral palsy, Down syndrome, mental retardation, autism
Yes
Yes
(continued)
Table 5.1
Survey
(continued) Sponsoring agency
Date
Description
Disabilities
Categories
Types of ID Functioning
more detailed information in the areas of ‘‘utilization and need for services, functional assessment, including emotional and behavioral development, and the impact of the child’s disability on the family.’’ No Learning ‘‘Functional A continuing survey US Census Bureau 1983–present, Survey of disability, Limitations and with monthly with a revised Income and mental Disability’’ interviewing that is questionnaire Program retardation, Topical designed to measure the in use from Participation developmental Module; June– economic situation of 1996 (SIPP) disability, September 07, people in the US. Data ADHD, other June– are collected in 2.5–4(open-ended) September 05, year-long panels with June– sample sizes ranging September 03, from n ¼ 14,000 Junehouseholds to September 02, n ¼ 36,700 households 1996 panel, surveyed multiple times 1993 panel, (waves) in each panel. October– The most recent panel
Yes
CDC/NCHS National Health and Nutrition Examination Survey (NHANES)
Began in 1960s but took current form in 1999
CDC/NCHS
1973–1995, 2002, 2006– present
National Survey of Family Growth (NSFG)
January 94/95, began in February 2004 October– and consists of 46,500 January 93/94 households, to be interviewed eight times. In addition to the core questionnaire, various topical modules are used to gain information on specific topics. Each wave contains a new topical module. No One question Mental A combination of survey retardation, questions and physical developmental examinations designed problems to assess the health and (example given nutritional status of of cerebral adults and children in the palsy) United States. Annual sample of n ¼ 5000 persons. No No No A personal interview survey examining family planning behaviors. First five cycles focused only on women 15–44 years old. In 2002, the survey included men for the
Yes
No
(continued)
Table 5.1
(continued)
Survey
Sponsoring agency
Date
National Survey of Children’s Health (NSCH)
CDC/NCHS, MCHB (HRSA)
2003, 2007– present
National Survey of Children
CDC/NCHS, MCHB (HRSA)
2000–2001, 2005–2006
Description
Disabilities
first time, with a nationally representative sample of n ¼ 4928 men and 7643 women. In 2006, the program began a continuous survey that aims at a sample of n ¼ 4400 interviews. Yes A random-digit dialing telephone survey of 102,353 households with children under 18 years old (in 2003’s survey). One child under 18 is randomly selected from eligible households to be included in the survey. Examines a broad range of indicators of child health and wellbeing. Yes A national telephone survey similar to NSCH, but examines the health
Categories
Types of ID Functioning
No Learning disability, ADD/ADHD, autism spectrum disorder/ pervasive developmental disorder, developmental disability, speech problems, cerebral palsy Yes ADD/ADHD, autism spectrum
Yes
Yes
functional status of children with special health care needs under the age of 18. In 2005– 2006, 40,804 interviews were completed.
with Special Health Care Needs (NSCSHCN)
Pregnancy Risk CDC Assessment Monitoring System (PRAMS)
1987–present
University of National Wisconsin Survey of Families and
1987–1988, 1992–1994, 2001–2003
A mailed survey of women No who have had a recent live birth (selected from state birth certificate files) that collects statespecific data on maternal experiences of pregnancy and childbearing. Annual state sample sizes are between 1300 and 3400 women. Yes A personal interview survey of 10,007–13,007 households designed to
disorder/ pervasive developmental disorder, Down syndrome, mental retardation/ developmental disability, cerebral palsy No No
No
No
Yes
Visual impairment, deafness, physical
(continued)
Table 5.1
(continued)
Survey
Households (NSFH)
National Education Longitudinal Study of 1988 (NELS)
Behavioral Risk Factor Surveillance System (BRFSS) Youth Risk Behavior Surveillance System (YRBSS)
Sponsoring agency
Date
Description
Disabilities
Categories
disabilities, cerebral palsy, mental retardation Learning A longitudinal survey of a Yes—on 1988 DOE’s Institute of 1988, with disability, parent nationally representative follow-ups in Education mental questionnaire sample of eight graders 1990, 1992, Sciences retardation, (n ¼ 25,000). Teachers, 1994, and (National emotional parents, and 2000 Center for problems, administrators also Education speech responded to questions. Statistics) problems Yes, only on adult No CDC 1984–present A continuing telephone respondents health survey about health- and risk-related behaviors in the United States. No No CDC 1990–present School-based survey of 9th–12th graders about health-related behaviors. Provides national, state, local, and tribal surveys of representative samples.
Types of ID Functioning
provide a data resource on family life in the US.
No
No
No
No
No
No
NICHD National Longitudinal Study of Adolescent Health (Add Health)
Study on Midlife in the United States (MIDUS)
National Institute on Aging
1994–1996, 2001–2002
MIDUS I: 1995–1996 MIDUS II: 2004–2005
Yes—Wave III A school-based, longitudinal study of adolescent health-related behaviors. Surveyed 7th–12th graders in school, with additional school administration, parent, and sibling surveys, along with an in-home adolescent interview. Yes—MIDUS II Investigated the role of behavioral, psychological, and social factors in understanding age-related differences in physical and mental health. This study included over 7000 Americans aged 25–74 through phone interviews and selfadministered questionnaires. It is comprised of three samples: the national sample of main
ADD/ADHD, speech problems
No
ADHD, learning Yes disabilities, cerebral palsy, Down syndrome, mental retardation, other developmental disabilities
Yes, but mostly for physical disabilities
Yes
(continued)
Table 5.1
Survey
(continued) Sponsoring agency
Date
2000–2009 National Center National for Education Longitudinal Research in the Transition US Department Study of Education (NLTS2)
Description
Disabilities
respondents, siblings of these respondents, and twins whose cotwin was in the national sample. Yes This study looks at the transition from secondary school to early adulthood through data collected in interviews, surveys, and assessments with students, parents, and schools. Information is collected repeatedly over the course of 10 years about a nationally representative sample of 12,000 students who were aged 13–16 at the start of the study, in 2000.
Categories
Types of ID Functioning
No Learning disability, speech impairment, mental retardation, emotional disturbance, hearing impairment, visual impairment, orthopedic impairment, autism, traumatic brain injury, multiple disabilities, deaf/blindness
Yes
Office of Special 2000–2006 Special Education Education Programs Elementary (OSEP) in the Longitudinal US Department Study of Education as (SEELS) part of the national assessment of IDEA 97
Yes A randomly selected national group of students in special education who were aged 6–12 in 1999 were assessed at three points in time. Information about these students was collected as they transitioned from elementary to middle school and from middle to high school. Three primary data collection activities were used: parent telephone interviews, direct student assessments, and school surveys.
2001–2007, Institute of Early 1998–2007, Education Childhood 2010–2016 Sciences of the Longitudinal US Department Program of Education (¼ECLS)
Three longitudinal studies Yes that examine child development, school readiness, and early school experiences through data from the families and schools. The
No Learning disability, speech impairment, mental retardation, emotional disturbance, hearing impairment, visual impairment, orthopedic impairment, autism, traumatic brain injury, multiple disabilities, deaf/blindness Yes Deaf/blindness, Down syndrome, Turner syndrome, spina bifida, ADHD,
Yes
Yes
(continued)
Table 5.1
(continued)
Survey
National Survey of America’s Families (NSAF)
Sponsoring agency
Urban Institute
Date
1997, 1999, 2002
Description
Disabilities
three studies follow students from birth through kindergarten, kindergarten through eighth grade, and kindergarten through fifth grade. A national, cross-sectional Yes survey of approximately 42,000 civilian, noninstitutionalized children and adults less than 65 years old. Two components consist of telephone surveys and area samples for households without telephones. Provides quantitative measures of child, adult, and family well-being with an emphasis on lowincome families.
Categories
Types of ID Functioning
developmental delay, cerebral palsy, mental retardation, autism
Physical, learning, or mental health conditions
No
Yes
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147
include the Department of Health and Human Services (DHHS), Centers for Disease Control and Prevention (CDC), National Institutes of Child Health and Human Development (NICHD), the Department of Education (DOE, including its Institute for Educational Studies, or IES), the US Census Bureau, the CDC’s National Center for Health Statistics (NCHS), the Substance Abuse and Mental Health Services Administration (SAMHSA), and the Health Care Finance Administration. A second feature of these surveys is their size and comprehensiveness. As noted in Table 5.1’s study descriptions (fourth column), these surveys are all large in scope, examining from 10,000 to over 100,000 American families. These families are contacted via phone calls or mailings that go throughout the country. Researchers are careful to sample from all 50 states, to attempt to match characteristics of the study sample to characteristics of the overall US population, and to oversample from (and/or to weight the responses of) families from minority, low SES, rural, or other groups which are of particular interest. Because individual surveys emphasize specific sets of topics, different surveys allow for analyses of different issues that are more or less effective. For this group of mostly child-related national surveys, the focus is most often on public health issues. Most surveys thus ask detailed questions about the child’s health, sickness, use of doctors or hospitals, method of payment, and other issues that are directly germane to public health concerns. In contrast, the age of the mother or the mother’s marital status, while clearly important for service utilization (Garland, Lau, Yeh, McCabe, Hough, et al., 2005; Thompson & May, 2006), might be considered as more indirectly related to public health. Whatever the reason, many demographic variables related to mothers and families seem to be asked in insufficient detail in many of these surveys. What is the status of disability in these surveys? As seen in the table, the extent to which surveys ask about disabilities varies widely. Although a few surveys ask no questions about disabilities, most ask at least a few questions. Such questions, however, generally relate to overall disability categories— mental retardation, LD, or ADHD—as opposed to individual causes or conditions (Down syndrome, spina bifida). Similarly, the National Survey of America’s Families (NSAF), from which we are learning much about the SES and economic hardships of families of children with disabilities (Parish, Rose, Grinstein-Weiss, Richman, & Andrews, 2008), asks only about whether the child has a disability, not the type of the disability per se. But exceptions do exist. Notably, the National Health Survey–Disability Survey (1994–1995) asked questions about Down syndrome, autism, spina bifida, cerebral palsy, and other conditions (Hendershot, Larson, & Lakin, 2003), and the National Survey of Children’s Special Health Care Needs (NS-CSHCN) asks about 16 specific health and disability conditions. In addition, some surveys (MIDUS) asked fewer questions about disabilities
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at their first wave of data collection, but featured more detailed questions at a second or subsequent wave (e.g., Ha, Hong, Seltzer, & Greenberg’s, 2008 examination of families of offspring with developmental disability versus mental health problems using the MIDUS-2 data set). Similarly, the three surveys from the Department of Education (NLTS-2; SEELS; ECLS) all ask about the child’s specific types of disability and, in some cases, about specific causes (e.g., ECLS’s questions about Down syndrome, Turner syndrome). One might also ask about the use of such surveys in disability research. The 1994–1995 National Health Survey–Disability Survey resulted in a book entitled Using survey data to study disability: Results from the National Health Interview Survey on Disability (Altman, Barnartt, Hendershot, & Larson, 2003). Most chapters provide information about work and health among adults with disabilities, use of support services, economic costs of disabilities, health of other family members (siblings), duration and timing of disabilities, access to health care and insurance. Similarly, the NS-CSHCN survey, for which data collection occurred in 2005–2006 and documentation about the study was produced in late 2007, promises to help researchers, practitioners, and policymakers in their understandings of children with special health care needs. A recent call for NS-CSHCN studies, for a supplement of Pediatrics (AUCD, 2008), highlights this interest from the pediatric and public health community. For the most part, however, even these surveys have been inadequately used by disability family researchers. Part of this neglect arises because several of these surveys are considered within the domain of public health, somehow apart from more traditional disability family studies. To some extent this perception is accurate, in that these surveys contain few questions relating to parental stress and/or rewards of parenting the offspring with disabilities, family structure, marital adjustment, or other issues. Still, even given these limitations—which, in fairness, characterize virtually all large data sets (of whatever category)—these national data sets are vastly underutilized in the field of disability family studies.
2.2. Large-scale approach 2: National Vital Statistics System databases National Vital Statistics System data sets aggregate data from across the country, including all 50 states, New York City (which has separate data from the rest of New York state), the District of Columbia, and five US territories. Such data are also in standard form; official birth data, then, include the same fields, coded in the same ways, from one state to another. States also have cooperative agreements with federal vital statistics officials to send high-quality data at set times throughout the year. As noted on the National Vital Statistics System (2008) web site, the goal is ‘‘. . .to make data available as widely as possible while protecting respondent confidentiality,
Using Large-Scale Databases
149
assuring data quality, and conforming to state laws and regulations on re-release of vital statistics data.’’ The most prominent of these data sets involves official birth, death, marriage, divorce, and fetal death data sets. As shown in Table 5.2, such data sets provide fairly detailed information—on millions of people—about a wide variety of issues. To take an example, official birth records involve much more than one sees on a standard birth certificate. Instead, every state’s birth records provide information about the mother (age, race, education, marital status, address), maternal prenatal practices (number and beginning month of prenatal checkups; whether the mother smoked), and the newborn (date of birth, birth order, gender, birth weight, estimated gestational age, birth complications, congenital anomalies). Although not explicitly focused on family issues, many of these variables can be used in family studies as either predictors (maternal age, education level, race, newborn prematurity, or adverse birth outcomes) or outcomes (marital status, birth order). To give an example, several groups have expressed concern that Down syndrome may be ‘‘disappearing’’ over time. The idea has been that, if all women were to receive prenatal testing, all would know that they are carrying a fetus with Down syndrome and all would abort. Such concern, exacerbated by the American College of Obstetrics and Gynecology’s (2007) recommendation to commence prenatal screening of all pregnant women, has greatly concerned many parents and professionals. In addition to articles in the popular press (Carmichael, 2008), professional articles have also questioned whether children with Down syndrome will continue to be born (Collins, Muggli, Palma, & Halliday, 2008) and what stance parents, care providers, and scientists should take toward prenatal testing of pregnant women of any age (Boys, Cunningham, McKenna, Robertson, Weeks, et al., 2008; Buckley & Buckley, 2008). Without taking a stand on this controversy, we note that a first question concerns the age-distribution of mothers of newborns with the syndrome currently. Since most women aged 35 and above are now encouraged to receive prenatal testing, does it continue to be the case that mothers who are older versus younger than age 35 have increased risks for delivering newborns with Down syndrome? We can directly examine this issue by perusing across several recent years the ‘‘Births Final’’ data from the National Vital Statistics System. Down syndrome is one of the congenital birth defects routinely noted in these official birth records, and crosstabulated rates (per 100,000 live births) of Down syndrome are provided by the age category of the mother when giving birth (i.e., <20 years, 20–24, 25–29, 30–34, 35–39, 40). From examinations of US births from two recent years (2003 and 2004), Fig. 5.1 shows that Down syndrome births continue to occur at much higher rates to mothers who are above 40 years of age as compared to younger women. Granted, such rates would be even
150
Table 5.2 Survey
National Vital Statistics System Date
Annually, with the exceptions of 1951–1954, National Vital 1956–1966, and 1968-1972 (50% sample); Statistics System: 1967 (20–50% sample); 1972–1984 (100% Natality (NVSS-N) sample from selected states, 50% sample from others)
Description
A data set comprised of all recorded births in the United States, two cities (NYC and DC), and five territories (Guam, Puerto Rico, the Virgin Islands, American Samoa, and the Commonwealth of Northern Mariana Islands). The 2003 revised standard form to collect information requests the following data: Demographic data of parents: for example, date of birth, race/ethnicity, education for mother and father; residence of mother Pregnancy data: for example, prenatal care, maternal use of WIC, weight gain during pregnancy, pregnancy history, cigarette smoking before and during pregnancy, insurance, risk factors (diabetes, hypertension, prior poor pregnancy outcome, etc.), infections during pregnancy Delivery data: for example, time of birth, date of birth, location of birth, place of birth (hospital, home birth, birthing center, etc.), attendant at birth (M.D., D.O., midwife, etc.), onset of labor, method of delivery, problems during labor and delivery Newborn data: for example, sex, Apgar score, estimated gestation, birth weight, congenital
National Vital Statistics System: Mortality (NVSS-M)
Annually, beginning in 1968
anomalies (anencephaly, spina bifida, limb reduction defect, cleft lip/palate, Down syndrome, suspected chromosomal disorder, hypospadias, etc.), newborn conditions at birth, breastfeeding at discharge A data set comprised of all recorded deaths in the United States, two cities (NYC and DC), and five territories (Guam, Puerto Rico, the Virgin Islands, American Samoa, and the Commonwealth of Northern Mariana Islands). The files include demographic, geographic, and cause-of-death data. The 2003 revised standard form to collect information requests the following data: Demographic information of deceased: for example, sex, age (years if over 1-year old, months/days if under 1-year old, hours/minutes if under 1day old), social security number, date of birth, birthplace, marital status, parents’ names, race/ ethnicity, education, occupation Death information: for example, place of death, method of disposition, date/time of death pronouncement, date/time of actual death, cause of death, contribution of tobacco to death, pregnancy status if female, manner of death, autopsy
151
(continued)
Table 5.2
(continued)
152
Survey
Date
Description
National Vital Statistics System: Fetal Death
Annually, 1982–present; 1994–present includes data from Puerto Rico, Virgin Islands, and Guam
A data set comprised of all recorded fetal deaths in the United States, two cities (NYC and DC), and five territories (Guam, Puerto Rico, the Virgin Islands, American Samoa, and the Commonwealth of Northern Mariana Islands). The 2003 revised standard form to collect information requests the following data: Demographic data of mother: for example, date of birth, race/ethnicity, education, residence, marital status; and of father: for example, date of birth, birthplace Pregnancy data: for example, prenatal care, maternal use of WIC, weight gain during pregnancy, pregnancy history, cigarette smoking before and during pregnancy, insurance, risk factors (diabetes, hypertension, prior poor pregnancy outcome, etc.), infections during pregnancy Delivery data: for example, time of delivery, date of delivery, location of delivery, place of delivery hospital, home birth, birthing center, etc., attendant at delivery (M.D., D.O., midwife, etc.), onset of labor, method of delivery, problems during labor and delivery, maternal morbidity
National Vital Statistics System: Linked Birth– Infant Death
1983–1991; 1995–2002; to be compiled annually in future
National Vital Statistics System: Marriage and Divorce
1957–present, with detailed state reporting discontinued in 1996
153
Fetal data: for example, sex, estimated gestation, birth weight, congenital anomalies (anencephaly, spina bifida, limb reduction defect, cleft lip/palate, Down syndrome, suspected chromosomal disorder, hypospadias, etc.) Death data: for example, cause of death (maternal conditions/diseases, complications of placenta/ cord/membranes, pregnancy complications, fetal anomaly, fetal injury, fetal infection, other fetal disorders), time of death, autopsy/ histological placental examination, method of disposition A data set ‘‘comprised of linked birth and death certificates for infants born in the United States who died before reaching one year of age’’ (http://www.cdc.gov/nchs/products/ elec_prods/subject/linkedbd.htm). Information regarding the number of marriages and divorces in the United States is still collected annually, but detailed state reporting was discontinued in 1996 due to limitations in state reporting (only 41 states participated in the marriage registration system and 31 in the divorce registration system) and budgetary constraints. (continued)
Table 5.2 Survey
(continued) Date
National Death Index 1979–present (NDI)
Description
A central computerized index of death record information compiled from computer files submitted by the State vital statistics offices. Data records are added to the file annually, approximately 12 months after the end of a calendar year. Data are available solely for statistical purposes in medical and health research.
155
Using Large-Scale Databases
400
Number per 100,000 live births
350 2003
2004
300 250 200 150 100 50 0 <20
Figure 5.1
20–24 25–29 30–34 35–39 Maternal age groups
40+
US Down syndrome births by maternal age.
higher were abortion not available (Olsen, Cross, & Gensburg, 2003), especially given that the median age of American women when giving birth has generally risen over the past three decades. Nevertheless, US birth records make clear that mothers who are older continue to be disproportionately more likely than younger mothers to deliver infants with Down syndrome (data from Martin, Hamilton, Sutton, Ventura, Menacker, et al., 2005, 2006). It is also important to note, however, that Fig. 5.1 provides only the rates of Down syndrome per 100,000 live births in each maternal age group. But most births occur to mothers who are much younger than 40 years of age. Across the overall population of Tennessee births (i.e., non-Down syndrome births), the median age of mothers is 26 years, and only a very small percentage of births occur to mothers aged 40 and above (1.2% during the years from 1990 to 2005). In comparison, mothers are older when they give birth to a newborn with Down syndrome, but even these mothers are mostly below 40. Thus, the median age of these mothers is 30 years when they deliver their child with Down syndrome, with 12.6% of these mothers age 40 and above. Mothers of newborns with Down syndrome, then, continue to be older than mothers of non-Down syndrome newborns, but most newborns with Down syndrome continue to be born to mothers who are below 40. Collected in a uniform fashion throughout the United States, vital statistics data involve large numbers of subjects and are invaluable for telling
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us about a host of family issues. By providing aggregate-level data online, certain questions can be easily addressed, including issues such as the trends during recent years in the age of the mother when giving birth to the child with Down syndrome. At the same time, other questions are more difficult to answer for two reasons. First, although aggregate-level data are readily and easily provided, most national data sets make it much more difficult to access responses of any single individual. Even when individual data (referred to as ‘‘microdata’’) are provided, individual identifiers are hidden to ensure confidentiality. When considering protected health information, all personal identifiers (e.g., names, full addresses, identification numbers) are hidden about all individuals. In other cases, information is partially hidden, as when the home zip codes of individuals who have a certain condition are limited to only the first three digits (since providing the full, five-digit zip code for a person with a rare condition could conceivably be used to identify that individual). Although important for privacy reasons, such practices make impossible the use of certain information in analyses or limit the level of detail. A second, related problem concerns the so-called ‘‘linking’’ of data from one data set to another. Although we discuss this issue below, largescale data sets become much more powerful when they can be linked together. Again, the inability in most situations to link public use data sets makes national vital statistics data less useful for many types of family studies.
2.3. Large-scale approach 3: Examinations, surveys, or records targeted to a specific city, state, or region Although this category is probably the most heterogeneous, studies of this type focus on an area smaller than the entire country. This area might be a state, region, city, or several-county area within a specific state. Beyond this characterization, the data sets involved in these projects differ markedly. A first domain of difference relates to the exact catchment area. As Table 5.3 illustrates, the well-known Metropolitan Atlanta Developmental Disabilities Study (MADDS) examines children within a five-county area in and around Atlanta, Georgia, whereas the Client Development Evaluation Report (CDERS), Developmental Disabilities Information System (DDIS), the Wisconsin Longitudinal Study (WLS), and Pregnancy to Early Life Longitudinal Data System (PELL) projects examine individuals within the states of California, New York, Wisconsin, and Massachusetts, respectively. Our own work, involving linked birth, death, marriage, divorce, and hospital discharge data sets, focuses on records from within the state of Tennessee over a multiyear period. Obviously, each of these areas differs in size, number of inhabitants, and the inhabitants’ racial, ethnic, educational, and other characteristics.
Table 5.3
State and regional databases
Survey
Sponsoring agency
Date
Description
Disabilities Categories
Developmental Disabilities Information System (DDIS)
New York State OMRDD
1978–?
Yes A one-time survey completed by service agencies (both governmental and private) of all known developmentally disabled persons in New York State who were actively receiving services or who were known to service providers. The survey requested data regarding sociodemographics, service provision, disabilities (developmental, psychiatric, and physical), and various measures of functioning, including the MDPS-AF. As of
Types of ID
Publications using No the dataset refer to the following disability categories: autism, cerebral palsy, epilepsy, mental retardation, other neurological impairments, other undetermined.
Functioning
Yes
(continued)
Table 5.3
(continued)
Survey
Client Development Evaluation Report (CDER)
Sponsoring agency
Date
Description
Disabilities Categories
July 1981, n ¼ 36,334 (n ¼ 12,523 youth under 22 years; n ¼ 23,811 adults 22 years and older) Yes An annual assessment 1979–present, California instrument for use with with major Department of clients with revisions in Developmental developmental 2008 Services disabilities clients being (comparisons served by the prior to and California Department after these of Developmental revisions are Services. impossible) It consists of two parts: a diagnostic element that reports the diagnoses, severity, and etiology of each client’s disabilities and an evaluation element that examines the client’s level of functioning. Each year’s data set contributes a snapshot of the developmentally
Types of ID
No MR, cerebral palsy, autism, epilepsy/ seizure disorder, other developmental disability
Functioning
Yes—motor, independent living, social, emotional, cognitive, communicative
Metropolitan Atlanta Developmental Disabilities Study (MADDS)
Division of Public 1984–1990 Health, Georgia Department of Human Resources, National Center for Environmental Health, CDC, Agency for Toxic Substances and Disease Registry
disabled population in California during that year. The number of individual subjects varies from year to year; for example, there was a 64.6% increase in number of people served by DDS from January 1996 to December 2006. Yes A ‘‘population-based epidemiologic study of the prevalence of mental retardation, cerebral palsy, hearing loss, vision impairment, and epilepsy’’ in n ¼ 89,534 10-year-old children with and without disabilities.
Mental retardation, cerebral palsy, hearing loss, vision, impairment, epilepsy
Not known
Not known
(continued)
Table 5.3
(continued)
Survey
Sponsoring agency
Date
Description
Disabilities Categories
Metropolitan Atlanta Developmental Disabilities Surveillance Program (MADDSP)
CDC
1991–present
‘‘An ongoing system for Yes monitoring the occurrence of selected developmental disabilities’’ in children of various ages. From 1991 to 1994, the system monitored children age 3– 10 years. Starting in 1996, the system monitored n ¼ 33,309 8-year olds and n ¼ 289,456 3–10-year olds. As of 2000, only children who meet the following criteria are included: 8-years old during the study year whose parents reside in the five-county metropolitan Atlanta
Mental retardation, cerebral palsy, hearing loss, vision impairment; beginning in 1996, also autism
Types of ID
Functioning
Not known
Assumed, but not known
MADDS FollowUp (MADDSFU)
CDC
Wisconsin Longitudinal Study (WLS)
National Institute on Aging
area, and who has one or more of the five developmental disabilities. 1997–2000 A follow-up study with Yes the original 10-yearold children from MADDS, now aged 21–25 years that requested information ‘‘about their health, living arrangements, socialization, employment, quality of life, service utilization, and independence.’’ Yes 1957, 1975, and A long-term study of a random sample of 1992 for 10,317 men and original women who graduated respondents; from Wisconsin high 1957, 1977, schools in 1957. Survey and 1994, for data were collected siblings when they were 18, 36, and 54 years of age. Data examined the life course from late
Mental retardation, cerebral palsy, hearing loss, vision impairment, epilepsy
Not known
No Mental retardation, developmental disabilities, cerebral palsy
Yes
Yes
(continued)
Table 5.3
(continued)
Survey
Pregnancy to Early Life Longitudinal Data System (PELL)
Sponsoring agency
BU School of Public Health, Massachusetts Department of Public Health, CDC
Date
1998–2005
Description
Disabilities Categories
adolescence through the early/mid-1960s in the context of ability, aspiration, and achievement. A companion sample contains comparable data for a randomly selected sibling of most respondents. Because this is a system of ‘‘A unique, innovative linked databases, it does not population-based directly address these longitudinal questions. Individual data reproductive data sets may contain this system, with multiple information. linked data sets that can be used for crosssectional and longitudinal analyses’’ (n > 640,000 births and fetal deaths). Linked data sets include birth records, fetal death records, birthrelated hospital
Types of ID
Functioning
discharge records, child and maternal death records, child and maternal emergency department visits, Early Intervention Program records, MA Birth Defects Monitoring Program, and successive maternal deliveries. Future linkages may include WIC enrollment data, Bureau of Substance Abuse Services treatment data, Census data, newborn hearing screening data, and IDEA data.
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Projects also vary in the degree to which data are oriented to both disabilities and family concerns. As its name implies, the MADDS project was specifically designed to examine children with five different disability conditions (more were subsequently added). As such, any new testings, records, questionnaires, and other measures were all related to disabilities. Similarly, the CDER and DDIS, as questionnaires used by California and New York’s departments on developmental disabilities, are also directly focused on disabilities. The WLS, while it began as a mostly ‘‘nondisability’’ survey (and study), has recently gone back and asked increasingly disabilityrelated questions in later waves of data collection. Finally, PELL and the Tennessee administrative databases, even though they can be used to answer disability-related questions, were not primarily devised for this purpose. A similar issue concerns the amount of attention devoted to family issues. As certain of these projects are focused on public health concerns (e.g., MADDS and PELL) and others are sponsored by state departments of developmental disabilities (CDERS and DDIS) or departments of health (Tennessee administrative databases), fewer questions are usually devoted to family issues. Granted, several projects have produced studies on families, most prominently the Wisconsin Longitudinal Study’s many studies involving life-span issues of families of individuals with disabilities (Seltzer, Greenberg, Floyd, Pettee, & Hong, 2001). Other studies arising from these data sets have also produced some family findings, especially when specific aspects of the mother or maternal prenatal practices confer higher-than-expected risks of intellectual disability. Consider Decoufle and Boyle’s (1995) finding that maternal education was the best predictor of having a child with intellectual disabilities, or Drews, Murphy, Yeargin-Allsopp, and Decoufle’s (1996) result that maternal smoking during pregnancy was associated with slightly more than a 50% increase in the prevalence of idiopathic intellectual disabilities. With the exception of the WLS studies, however, most studies using this category of data set have focused on the person with disabilities themselves, not on their mothers, fathers, siblings, or the family as a whole. Despite the limitations in these databases, it is also important to highlight their common strengths. The most important of these strengths involves linkage, or the ability to link together the data from a single individual across multiple data sources. Such linkages can be performed in several different ways. One might, for example, link across different types of data. By linking the CDER to the death records, Strauss, Shavelle, Baumeister, and Anderson (1998) were able to determine that adults moving from institutional to community settings had higher-than-expected death rates in the period directly after moving, a controversial finding that speaks to the need for better transitional supports for these individuals. In contrast, one might examine the same type of data for the same individual at different times, or even create from the birth records unique families consisting of those newborns who were born to the same mother (Urbano, 2007).
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This ability to link all individuals’ information—both within and across data sources—is simultaneously difficult to accomplish and one of the hallmark advantages of this third approach to large-scale databases. On the one hand, the task is incredibly difficult, involving computer programs for linking hundreds of thousands or more pairs of individual records. Depending on the type of records to be linked, the laws of the state or region, and the IRB approvals obtained, the number and quality of the variables available for linking will vary. In practice, multiple identifying variables are used by the linkage process. As one might expect, highly specific identifiers (social security number, insurance IDs, medical record numbers) produce the most efficient and accurate linkage matches. However, less unique identifiers (names, addresses, dates, diagnoses, phone numbers) can be used by themselves or in conjunction with unique identifiers to produce linked data sets. The comparisons of multiple linking variables are combined to classify pairs of records as matched, uncertain, or unmatched. This combination process may be deterministic (using specific decision rules) or probabilistic (using mathematical formulas) (see Tu, Mason, & Song, 2007; Urbano, 2007). These linkage processes result in new data sets that contain information collected from multiple sources. When such linkage is achieved, the benefits are enormous. Examining records within a single record type (e.g., hospital discharge records), one might accumulate the hospitalizations of mothers of children with disabilities ‘‘longitudinally’’ over a multiyear span to create a maternal health profile. In essence, although the researcher has not followed the mother over time, the records have. Crossing from one data set to another, one might determine if the birth of a child with a specific birth defect predisposed the couple to become divorced. Combining within- and acrossrecord linkage, one might determine if a child with disabilities born at one time led parents to have more children at a later time (the so-called ‘‘replacement child’’ talked about in psychoanalytic literature), or for siblings to become hospitalized, or for parents to divorce. Given that these questions are being asked of such large-scale databases—which often include hundreds of children with a specific disability and many thousands of potential comparison group cases—these databases can be useful for addressing a large number of family-related questions.
3. Two Examples of Using Large-Scale Administrative Databases to Answer Family-Related Questions So far, our discussion of the uses of large-scale databases has remained mostly general. We have discussed the promises and limitations of national surveys, national vital statistics, and state–city–regional databases. We have
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emphasized the importance of linkage and the problem that at least some of these databases have not emphasized family-related outcomes (and, therefore, asked fewer and less detailed questions about families and family functioning). Our overall argument has been that large-scale databases allow researchers to address heretofore unanswerable questions. We now attempt to move from general to specific by providing two examples from our own recent studies. Both studies utilize data from the Tennessee Department of Health. The first linked birth, hospital discharge, and divorce data, the second used data from Birth alone. Both rely on multiple years of data, dating in both cases from 1990 until 2002. Both studies are focused on the families of children with Down syndrome. It is also important to provide a brief description of the state itself. Tennessee is the 17th largest state in the nation, with 6.04 million residents and an ethnic–racial breakdown of roughly 80% White, 16% African American, and the remainder ‘‘other’’ (Hispanic heritage is coded separately, and these individuals comprise 3.2% of the state’s population). In terms of land area, the state approximates a parallelogram, with ‘‘long’’ sides on the top and bottom, and right-tilted ‘‘short’’ sides along the sides. As a result, although the state is only about 120 miles from top to bottom, traveling from the state’s southwestern-most point (Memphis) to its northeastern-most point (Tri-Cities area) covers almost 500 miles. Although the state has five prominent cities (Memphis, Nashville, Chattanooga, Knoxville, and Clarksville), the majority of the state’s land mass is rural. Overall, 67 of the state’s 95 counties are considered to be rural by the federal government.
3.1. Divorce in families of children with Down syndrome Our first example concerns divorce in families of children with Down syndrome (Urbano & Hodapp, 2007). Although it has long been thought that families of children with disabilities experience high levels of marital discord and divorce, recent meta-analyses indicate that divorce may occur only slightly more often in families of children with versus without disabilities (Risdal & Singer, 2004). In Down syndrome, different studies have compared divorce levels of these families to those of families of children without disabilities. Findings vary widely, with researchers noting that, compared to families of same-aged nondisabled children, families of children with Down syndrome have more (Gath, 1977), less (Cunningham, 1996; Gath & Gumley, 1986), or equal (Carr, 1988) amounts of divorce. To identify individuals in the birth data set having a diagnosis of Down syndrome, birth and hospital records were linked. The diagnosis of Down syndrome came from either the birth or the hospital records. To create family records, birth records were linked on maternal identifiers. Using Tennessee electronic birth records from 1990 to 2002, we identified 647 families of children with Down syndrome, 361,154 families of nondisabled
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children (Comparison Group), and 10,283 families of children with other birth defects (this last group was comprised of newborns whose disabilities were identified at birth and listed as one of the 21 remaining congenital birth defects). Divorce rates among families of children with Down syndrome were slightly lower than in families of the other two groups. But two other aspects of this study were, to us, even more interesting. First, in examining when divorces occurred, we noticed a major difference in relation to the age of the ‘‘index child’’ (the child with Down syndrome or with congenital birth defects in those two groups, a randomly selected child in the comparison group). Whereas only 17.4% and 14.9% of divorces occurred when the target child was below 2 years of age in the comparison and other birth defects groups, almost one-third (32.7%) of divorces occurred before the child reached 2 years in the group with Down syndrome. A second noteworthy finding concerned the connections among the maternal variables of low education, young age at the birth of the child, and rural status. Although it has long been known that younger and less educated couples are more prone to divorce (Bramlett & Mosher, 2002), this pattern was especially true among families of children with Down syndrome. Most striking of all was the connection to rural status. Among fathers of children with Down syndrome who did not have a high school education and who lived in rural areas, 40.9% experienced divorce; such percentages were much higher compared to fathers of children with Down syndrome who also lived in rural areas but were more educated (2.2%) or who lived in more urban areas but also did not have their high school degrees (17.0%) (similar, albeit less striking, findings also occurred for less educated, rural mothers of these children). In short, less educated, rural parents of children with Down syndrome may be particularly at risk for divorce, and service systems may need to develop better strategies to reach this hard-to-reach group.
3.2. Demographic characteristics of African American versus White mothers of newborns with Down syndrome A second policy-relevant issue concerns the ethnic–racial backgrounds and needs of families of children with Down syndrome (Hodapp & Urbano, 2008). It has been recognized that life expectancies of African Americans may be much shorter compared to Whites with Down syndrome (Friedman, 2001), and such racial disparities in health may also extend to infant mortality (Rasmussen, Wong, Correa, Gambrell, & Friedman, 2006). To date, however, few studies examine the service needs of families of these children. Although Tennessee administrative databases do not record service needs per se, we do have many variables that strongly relate to such needs.
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Among parents of children with disabilities more generally, older mothers generally report lower stress levels (Flynt & Wood, 1989), whereas unmarried mothers report higher levels (Beckman, 1983; Williford, Calkins, & Keane, 2007). In addition, higher levels of parental education—particularly graduating (vs not graduating) from high school or earning a bachelor’s degree—lead to higher lifetime earnings, with recent studies noting that the earlier timing of advanced degrees may be particularly advantageous (Elman & O’Rand, 2004). Throughout these studies, younger, unmarried, and/or less educated mothers seem to be experiencing more difficulties in knowing about, accessing, and receiving needed services. Furthermore, most studies also report that mental health services are used less often by families who are African American (e.g., Garland et al., 2005). Using official Tennessee birth records from 1990 to 2002, we were able to examine some of these issues in relation to African American versus White mothers of newborns with Down syndrome. Our study compared 726 White (not Hispanic) to 144 African American (not Hispanic) mothers of newborns with Down syndrome; maternal characteristics included age at infant’s birth, education levels, and marital status. Compared to White mothers, African American mothers of newborns with Down syndrome were younger, with many more African American (vs White) mothers giving birth at 23 years or younger (37.5% vs 22.8%). Moreover, within the African American group, the first quartile (25% line) was at 21 years (the first quartile was at 24 years in the White group). Not surprisingly, in both groups those mothers who were younger also had less education and were less likely to be married. Among both the African American and the White mothers, groups of younger (23 years) versus older (24) mothers showed much higher percentages who were not high school graduates (African American ¼ 44.4% younger vs 12.2% older; White ¼ 34.5% younger vs 8.6% older). Similar findings accrued for marital status, with the rate of married women at the time of birth increasing rapidly from the younger to the older periods for both the African American (14.8% vs 50.0% married) and White (61.8% vs 89.4% married) groups. In both the divorce and maternal demographic studies, the use of Tennessee’s vital statistics databases, linked together over multiyear spans, was critical for addressing heretofore difficult-to-address questions. Indeed, even when considering the current state of the art concerning families of children with disabilities more generally, we know only basic information about these families. In the more specific case of families of children with Down syndrome, we know even less. Although our approach is not the only way to study these issues, large-scale administrative databases that cover all of the state’s citizens—including those mothers of children with Down syndrome who are younger, less educated, African American, and/or unmarried—constitute an important source of information about these less-often studied groups.
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4. Comparing Different Types of Large-Scale Databases In considering the three approaches to large-scale research on families of children with disabilities, we have been struck by how all three have both their strengths and their weaknesses. And yet, given the need for basic information about the families of children with many types of disabilities, we also feel that these data sources—even with their admitted weaknesses— can be exceptionally useful for family researchers. As we outline three issues to consider when using large-scale databases in family research, then, our aim is not to champion one type of large-scale approach, but instead to argue for the inclusion of large-scale approaches to help answer family questions.
4.1. National data sets versus data sets specific to a region, state, or city A first basic differentiator concerns the nature of the political-geographic population being studied. National studies encompass the entire country, whereas examinations–surveys–administrative databases of cities, multiple counties, states, or even regions cover smaller areas. In terms of numbers of participants, the national vital statistics records cover by far the most participants, with both the large-scale surveys and the studies examining smaller areas including fewer participants (and using administrative records, surveys, testings, or some combinations of all of these). Beyond numbers, however, are the specific demographic characteristics of the participants of each less-than-national study. Some of this is obvious: In our own work, for example, we have avoided analyses of Hispanic groups, as Tennessee has (until recently) had insufficient numbers for appropriate analyses. In the same way, we would expect large-scale researchers in states with mostly White populations, or populations with mostly one Hispanic group (e.g., Cuban Americans in Florida), or states with a group not highly represented in other states (ethnic Hawaiians in Hawaii; Mormons in Utah) to be cautious in both their analyses and interpretations. The more difficult issue arises when a state or region does have sufficient numbers of a particular group or subgroup, and the researcher must consider the degree to which that state’s subgroup is typical of that group in the remainder of the country. Consider the issue of living in a rural area. As noted earlier, 67 of Tennessee’s 95 counties are considered to be rural by the federal government. Additionally, in our divorce study, rural, less educated fathers (and mothers) of children with Down syndrome were much more
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likely to divorce. Our question—and the question of every less-thannational study—concerns the degree to which Tennessee’s rural population is the same or different from rural parents of these children in Wyoming, Maine, Alaska, or Montana. As one progresses in such analyses, it also becomes clear that many such issues become more complex. To continue the example of the effects on families of living in a rural area, we have routinely used federal criteria to categorize Tennessee’s 95 counties into ‘‘rural’’ and ‘‘nonrural’’ (Office of Rural Health Policy, 2001). But as researchers of rural families have long appreciated, ‘‘ruralness’’ may constitute more of a continuum than a discrete category; these researchers have categorized all US counties in terms of ‘‘Beale codes.’’ Assigned by the USDA’s Economic Research Service, Beale codes measure a county’s degree of ruralness on a scale ranging from 1 (most rural) to 9 (least rural). These codes, named after Calvin Beale (the USDA researcher who invented the system), have versions based on the status of the county as measured in the 2000 Census (2003 Beale codes) and in the 1990 Census (1993 Beale codes). Beale codes constitute but one example of how an important demographic issue, once examined, has its own history of advances that, in turn, can be applied to families of individuals with disabilities.
4.2. Sample versus population In perusing Table 5.1’s listing, one is struck by the size and scope of these (mostly) federally sponsored, nationally based surveys. Featuring welldesigned sampling plans and what must be a cadre of callers and data collectors, these studies routinely examine 100,000 or more individuals. Even the recently completed National Survey of Children with Special Health Care Needs (NS-CSHCN) of 2005–2006 examined approximately 40,000 children with disabilities, with this group a subset of the original 190,000 calls. Strangely, however, even large initial samples dwindle rapidly. In contemplating performing our own study of Down syndrome from NS-CSHCN data, we have discovered that this data set contains data on 396 children and their parents. Although this number is fairly large and constitutes roughly 1% of all children with special health care needs, there are probably insufficient numbers of children to compare across each year of the 0–17-year age-span (396/18 ¼ 22 children per age group). In contrast, vital statistics and other administrative records have the advantage of covering the entire population, either of the country at large or from a particular state or region. Over the past few years, for example, it is thought that approximately 99% of all US births are recorded in state official birth records (Schoendorf & Branum, 2006). These records do not, however, ask many of the targeted, detailed questions asked in the NS-CSHCN survey.
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4.3. Quality of the data In advocating for the use of large-scale data sets in child development research, Brooks-Gunn, Berlin, Levanthal, and Fuligni (2000) entitled their article ‘‘Relying on the kindness of strangers.’’ With only a few exceptions, most large-scale data sets do indeed, rely on other people— what Urbano (2007) called ‘‘SED’’ (Somebody Else’s Data)—to generate these massive data sets. But within many areas of social science, there is a profound unease about such ‘‘ill-gotten’’ data. Most developmental or clinical psychologists, special educators, psycholinguists, or other social science researchers plan the study beforehand, decide which are the best measures to use, recruit and ‘‘run’’ participants, then analyze the data. Beyond arguing that social science can handle—and is even strengthened by—a mixture of research approaches and methods, we also highlight two more substantive issues. First, there is the issue of a mismatch between the collected variables and the interests of the researcher who is now performing secondary data analyses of those variables (Friedman, 2007). Depending on the degree to which the original and subsequent investigators were interested in similar topics, the data set will often seem to be missing one or more key variables. More often, perhaps, is the case in which the original data set has some, but not all, of the relevant variables. Thus, a largescale national survey might ask one or two questions about maternal stress, but not give the entire parenting stress index (Abidin, 1990), or one question about maternal depression, but not the Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961). or even short-form depression screeners. Another difficult question concerns the quality of the data. In both formal reviews and in informal conversations with colleagues, we have found that certain social scientists entirely dismiss the idea of using state or national administrative records in disability family research. To them, it seems obvious that these records are worthless. Such records were collected by other people, were not originally designed for research purposes, and are obviously of poor quality. The general consensus often seems that one cannot use these records in any reputable study. We address this issue by pointing out the growing body of literature evaluating vital statistics records. These studies compare information as it appears on official birth records and in the hospital’s own medical records. The conclusion from these studies seems much more nuanced. Some variables show almost perfect agreement: basic information about the newborn (date of birth, plurality, birth order, sex, race) and the mother (mother’s marital status, county of birth, date of birth, number of children living and deceased) are virtually identical from across the two data sources (Piper, Mitchell, Snowden, Hall, Adams, et al., 1993). In contrast, other pieces of information are often ‘‘close, but not always exact,’’ including
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infant birth weight and the number and beginning month of prenatal checkups. Finally, a few variables seem poorly captured by official birth records. Variables with the most missing or questionable values include any aspect of the father, estimated gestational age, alcohol use, obstetric procedures, and delivery events (Northam & Knapp, 2006; Zollinger, Przybylski, & Gamache, 2006). Some of this information improves when the state’s practice is to have trained birth recorders extract such information from the hospital’s birth records (e.g., when recording obstetric procedures or delivery events). Although large-scale, already-collected data may not be perfect, we feel that Tennessee’s vital statistics records (the data with which we have the most experience) provide reasonably good, high-quality data. At the same time, we do need to use care when drawing conclusions about certain people (e.g., fathers) or issues (e.g., maternal alcohol use). For our own work examining families of children with Down syndrome, we have also followed up the birth records with hospital discharge records, attempting to identify children with Down syndrome who were missed in the birth records from their subsequent hospitalizations.
5. Summary and Conclusion As we proceed on this ‘‘third generation’’ of disability family research, we face the dual problem of too few subjects and too many potential variables. Already ubiquitous in family studies, this issue is becoming even more problematic, as we increasingly appreciate that families of children with different types or causes of intellectual disabilities differ and that family outcomes relate to multiple, even interacting factors. Although one might simply proceed with small-N studies—and mostly ignore the complexity that now seems commonplace in predicting family outcomes—this solution seems inadequate. The approach advocated in this chapter supplements our small-N studies with other studies that utilize large-scale databases. In the same way that epidemiological studies have been used to identify interesting events in populations, such as outbreaks of disease (epidemics), geographic clusters (salmonella contamination from a restaurant salad bar), or factors associated with adverse birth outcomes (e.g., smoking and preterm deliveries), so too can large-scale databases be used to study families of persons with disabilities. Those databases might include national surveys, national vital statistics databases, or regional–state–local surveys or administrative databases, but each involves a larger-scale, more epidemiological approach to family research. Hundreds or even thousands of families of persons with disabilities can be included, thereby allowing one to examine large numbers of predictors.
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More importantly, however, such large-scale studies help move the field into mostly unexamined territories. Partly due to our reliance on small-scale samples—often gathered from families residing in or near the researcher— the field of disability family studies has often ignored some basic, almost rudimentary questions. We know little, for example, about families of children with disabilities or with a specific type of disability (e.g., Down syndrome, autism) when that family lives in a rural area, or is of a minority group, of lower SES or of parents with lower levels of education. In addition, we know little about family questions that extend beyond epidemiological–public health concerns, questions such as how having a child with Down syndrome influences parent work choices, sibling school achievement, or the family’s moving from one service area to another. Granted, large-scale data sets cannot answer all of these questions and do not constitute a panacea for the field of disability family studies. As we noted throughout this chapter, all three types of large-scale data sets and approaches have their own strengths and weaknesses, and none should supplant other, more in-depth studies. Such large-scale research should, however, now take a more prominent place within the multitude of approaches. Ultimately, if we are to fully understand families of children with disabilities, we are going to need all approaches and researchers, working together, to answer different family questions. Nothing less seems acceptable as we proceed with this third, more complex generation of studies of families of individuals with disabilities.
ACKNOWLEDGMENTS This chapter was supported by Health Resources and Services Administration (HRSA) grant R40MC08957 and NICHD grant P30HD15052. We thank Samantha Goldman and Mollie Griggs for editorial assistance and Laraine Glidden, Marsha Seltzer, Derek Chapman, and two anonymous reviewers for their thoughtful, detailed comments.
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Urbano, R. C. (2009). Using state administrative databases to study Down syndrome. (in press). Urbano, R. C., & Hodapp, R. M. (2007). Divorce in families of children with Down syndrome: A population-based study. American Journal on Mental Retardation, 112, 261–274. Walsh, P. N. (2008). Health indicators and intellectual disability. Current Opinion in Psychiatry, 21, 474–478. Williford, A. P., Calkins, S. D., & Keane, S. P. (2007). Predicting change in parenting stress across early childhood: Child and maternal factors. Journal of Abnormal Child Psychology, 35, 251–263. Zollinger, T. W., Przybylski, M. J., & Gamache, R. E. (2006). Reliability of Indiana birth certificate data compared to medical records. Annals of Epidemiology, 16, 1–10.
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A Rich Mosaic: Emerging Research on Asian Families of Persons with Intellectual and Developmental Disabilities Subharati Ghosh and Sandy Magana Contents 180 181 182 182 185 187 194 197 204 206 209
1. Introduction 2. Cross-Cultural Model of Family Functioning 3. Review of the Literature Within the Cross-Cultural Model 3.1. Environmental context factors 3.2. Cultural context factors 3.3. Appraisal 3.4. Coping 3.5. Resources 3.6. Adaptation 4. Summary and Conclusions References
Abstract In this chapter, we review research on families of Asian descent who are caring for family members with intellectual and developmental disabilities (IDD). Our review includes research conducted in Asia as well as research on Asian immigrants in the United States and United Kingdom. This pan-ethnic group is of particular importance because Asia is the largest continent in the world, and Asians represent one of the largest immigrant groups to the United States and Western Europe. We review research within a cross-cultural stress and coping model that includes unique environmental and cultural contexts. We also examine the process of acculturation and differing experiences of Asian immigrant families with respect to the stress and coping model. We identify areas in which future research is needed to flesh out our knowledge about stress and coping among Asian families. Overall, our findings reveal a rich cultural mosaic of Asian families and their experiences. University of Wisconsin-Madison, School of Social Work, Madison, Wisconsin 53705, USA International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37006-8
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1. Introduction Family has the most prominent and arguably, the most important influence on the lives of people with intellectual and developmental disabilities (IDD). The majority of individuals with IDD coreside with their caregivers, who continue to be their primary source of support through life (Braddock, 1999; Fujiura, 1998). For those who live in supported or independent homes, contact with family members persists and continues to affect the well-being of caregivers who are primarily the parents of adults with IDD (Blacher & Baker, 1994; Seltzer, Krauss, Hong, & Orsmond, 2001). However, much of our knowledge about family experiences while caring for an individual with IDD comes from an organized body of literature from the West, particularly United States and United Kingdom. Therefore, the primary goal of this chapter is to bring together the emerging body of information about Asian caregivers, as experienced in both their country or origin and their experiences as immigrants in the United States and United Kingdom. We begin with a brief introduction to Asia to set the chapter in context. Asia is the world’s largest and most diverse continent; yet, the term represents more of a geographic landmass than a culturally homogenous region. The use of term Asia to describe this vast land carries the potential to obscure the enormous diversity among the regions it encompasses. Asia is comprised of 54 countries of which approximately 10 are transcontinental, shared with Europe, each with a unique ecology and history that has shaped its sociopolitical and cultural environments, making it virtually impossible to identify a homogenous Asian culture (Encyclopedia Britannica, 2008). Asians are one of the highest represented immigrant groups, both in the United States and the United Kingdom, with major immigration from countries like China, South Korea, India, and Vietnam, bringing into their host country a variety of cultural and religious beliefs. Understanding the unique environmental, cultural, and religious context of Asian families is important to gain a more complete picture of families of children with an IDD worldwide. We present a review of research on families of persons with IDD that are of Asian descent. Although parts of Israel, the Middle East, and Russia are considered to be in Asia, our focus is primarily on South, East, and Southeast Asia. We included in our review both studies that have been conducted in Asian countries and those that have been conducted in the United States or United Kingdom with Asian immigrant families. We found an unexpected wealth of research on families of children with IDD in East Asia (i.e., China, Hong Kong, Taiwan, and Japan), South Asia (i.e., Pakistan, India, Nepal, and Afghanistan), and Southeast Asia (Malaysia and Thailand).
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However, studies conducted in the United States and the United Kingdom on Asian immigrant families are not in abundance. From research in the United States, we report on families from China and South Korea in East Asia, Vietnam in Southeast Asia, and India in South Asia. From studies in the United Kingdom, we report on families from South Asia, primarily from Pakistan, Bangladesh, and India. To organize the findings from studies conducted in Asia and with Asian immigrants, we use a cross-cultural model of family functioning as a framework. We begin by presenting an over view of this framework.
2. Cross-Cultural Model of Family Functioning To understand the unique caregiving demands and their consequences on caregivers, research studies have used several theoretical models. These include Lazarus and Folkman’s (1984) model of stress, appraisal, and coping, and Pearlin’s (1989) stress process model. Each of these models helps us to understand how adaptation in the face of a stressful experience is mediated or moderated by social and psychological resources and coping strategies. The commonality in these models is their use of similar domains such as context or background, stress, appraisal, resources and coping, and well-being or adaptive outcomes. Some cross-cultural researchers argue that culture permeates all of these domains (Chun, Moos, & Cronkite, 2006; Glidden, Rogers-Dulan, & Hill, 1999). For example, Chun et al. outline a stress and coping model for Asians in which examples of the cultural value of collectivism is highlighted throughout the domains. Similarly, Glidden et al. (1999) present a model in which the domains are imbedded within religion and ethnicity. Other researchers include cultural factors in some of the domains, but consider many factors to be more universal in nature (Alegria et al., 2004). In an epidemiological study of Asian Americans and Latinos in the United States, Alegria et al. developed a cross-cultural model that incorporated universal as well as culture specific variables. For example, they include a number of contextual variables that can be universally applied such as persistent poverty, language, neighborhood environment, and discrimination, as well as unique cultural variables such as familism and acculturation as components of the psychosocial domain. We present a cross-cultural model that is based on the stress and coping models of Lazarus and Folkman (1984) and Pearlin (1989) borrowing more of the cross-cultural aspects outlined by Alegria et al., Chun et al., and Glidden et al. According to our adapted model (Fig. 6.1) the primary stressor is caring for a child with the disability. Characteristics of the child include maladaptive behaviors that may increase the level of stress on the family caregiver. According to our model, there are two components that make up the context of caregiving. These are the environmental context and the
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Context: environment (political, geo-physical, economic)
C o n t e x t
Appraisal: loss of face, fate, end of blood line, possession by spirit
Child with IDD: behaviors, diagnosis, etc.
Coping strategiesproblem and emotion focused, collectivist coping
Adaptation: physical and psychological health outcomes
C o n t e x t
Resources- formal and informal Context: culture (beliefs, religion, values, acculturation)
Figure 6.1
Cross-cultural model of family functioning.
cultural context. The environmental context includes factors such as the availability of resources in the country or region, persistent poverty, and societal lack of knowledge about disabilities that may contribute to or exacerbate the stress experienced. The cultural context factors may include religious and cultural values and beliefs. Imbedded within the contextual setting, are stressors that may have a direct effect on adaptation, and/or may be mediated by other domains in the model such as how the caregiver appraises the stressor, the resources she uses and how she or he copes with the stressor. We will use this framework to review the literature on Asian and Asian immigrant families. In the first two sections, the environmental and cultural context factors, we will discuss the broader macrosetting within Asia. In the subsequent sections, appraisal, coping, resources, and adaptation, we will discuss the research on families of children with IDD in Asia and with Asian immigrants in the United States and/or United Kingdom.
3. Review of the Literature Within the Cross-Cultural Model 3.1. Environmental context factors In this section, we review literature on some of the macroenvironmental factors affecting families of children with IDD in Asian countries. The environmental factors impact many aspects of caring for a child with a
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disability. For example, environmental factors may contribute to the cause of disability and may determine the amount of resources the family may have available to care for a child with IDD. 3.1.1. Environmental factors leading to disabilities Phenomena that may be unique to developing countries including those within Asia are socioeconomic, geophysical and political conditions that contribute to the cause of IDD. Reports on Asian countries by the World Health Organization (WHO) discuss the role of nutritional deficiency, diseases, congenital defects, chemical wars (e.g., Agent Orange in Vietnam) and lack of access to maternal and child health care as factors contributing to IDD. We briefly describe some of these factors in this section. Nutritional deficiency, for example lack of iodine in the diet, is known to be one of the leading causes of IDD including cretinism, mental retardation, and developmental disabilities among children in Central Asia. A report by the WHO estimated that approximately 2 billion people in its 192 member countries live in areas of chronic iodine deficiency, China being one of them. Its geography and population makes China one of the most vulnerable countries in the world for IDD due to iodine deficiency (Ericsson, Gebre-Medhin, & Sonnander, 2008). Malnutrition is also known to be a leading cause of IDD in developing countries, and several Asian countries are no exception to it. Governments in these countries are often dependent on external aid agencies to provide the basic services for its citizens. However, funding from international aid organizations tends to be targeted at specific illnesses or disabilities, thus families of children with IDD rarely benefit from funding. For example in Afghanistan, even though disability services have been identified as a health priority within the National Development Program, these services appear to be focused only on traumatic injuries. Those that are related to congenital causes receive low status and attention from medical staff (Armstrong & Ager, 2005). Lack of adequate maternal and child health-care services is also known to be one of the primary causative factors in giving birth to children with IDD. As in Afghanistan, lack of adequate health services coupled with extremists’ attitudes toward women, have resulted in women being poorly equipped to either plan their pregnancies or remain healthy throughout pregnancy, often delivering their child in the absence of trained professionals (Chanmugam, Ahsfaq, & Shinwari, 2001). Consequently, Armstrong and Ager (2005) found that long-term IDD, such as cerebral palsy is common in Afghanistan. Finally, chemical warfare is known to have long-term consequences on mental and physical health, genetic aberrations that are sometimes passed on from one generation to the next. An example is Agent Orange used during the Vietnamese War. According to Vietnamese Ministry of Foreign Affairs, approximately 4.8 million Vietnamese people were exposed to Agent
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Orange, resulting in 400,000 deaths and disabilities, and 500,000 children born with birth defects such as cleft palate, mental retardation, hernias, and extra fingers and toes. Therefore, we can conclude that the greater social, political, and physical environmental context has an important contribution to the cause of disability. As researchers we must be sensitive to these contextual factors, because they underscore macroenvironmental factors from which there is no easy escape for these families, and having a child with IDD may be one of the many life challenges they have to struggle with. 3.1.2. The impact of environment on the availability and accessibility of services Environmental factors are also known to affect the availability and accessibility of services, including diagnostic, rehabilitative and long-term care for people with IDD. As the world’s largest continent, Asia has its own share of political and economic struggles. It has some of the world’s poorest economies, and countries that are still trying to establish a stable government. Political strife in several Asian countries has led to the deterioration of the health-care system, for example in Afghanistan and Nepal. A recent national survey of health resources in Afghanistan found that approximately 12% of the health facilities were not operational and 35% of the functional facilities needed rebuilding or major repairs (Afghanistan, Ministry of Health, 2002). Similarly in Nepal, a decade long Maoist insurgency has hampered the delivery of basic services and restricted development and assistance. The net result of war and destruction in these countries is the inability of the governments to provide some of the basic services to its citizens. Therefore, where basic needs are not being met, it is unlikely that specialized services will be provided for children and adults with IDD. In a review of disability issues in East Asia, Takamine (2004) stated that persons with disabilities constitute the most marginalized group in the Asian and Pacific region. This is especially true for children and young people with disabilities who face overwhelming barriers to participation in education and skill development programs. However, for the government to implement programs it is necessary to know the prevalence of disability. As pointed out by Takamine (2004), the majority of countries in East Asia and the Pacific region lack data of the prevalence of disability as data are not substantiated by any statistical methods. Similarly, there are also some concerns about the validity of prevalence data in some countries (particularly in central Asia), with some evidence of falsification for political purposes, coupled with a deeply ingrained culture of secrecy (WHO, 2008). Therefore, policy makers and personnel formulating policies and implementing programs to meet the needs of people with disability face a dearth of valid disability statistics. There are several implications of the lack of disability statistics. First, the prevalence of disability is not known, and
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second, due to lack of adequate data, health-care needs tend to receive lesser priority, consequently there is a lower state expenditure on health. For example, World Health Statistics, 2008 reports South East Asian countries having the lowest total expenditure on health as a percentage of Gross Domestic Product (4%) compared to Africa, America, Europe, Mediterranean, and Western Pacific region in the year 2005. Finally, to afford exceptional services for children with IDD, the cost of care exceeds affordability. In the face of expensive specialized services, stringent government finance, and lack of state commitment to most state provided services, Asian countries tend to serve only a small proportion of people with IDD. In a study on Indian mothers of children with IDD, Gupta and Singhal (2005) found that demand for service far exceeded the supply of available professionals, and the cost attached to accessing these services to be very high. Similarly, Kumar and Akbar (2004) found almost 76% of the mothers of children who have IDD with comorbid disabilities reported not receiving needed government benefits. This brief overview sensitizes us as researchers to be cognizant of the greater socioeconomic and political context within which many Asian families function and its impact on caregivers’ accessibility of services. The purpose of this overview is to highlight some enduring challenges that future research must account for while conducting cross-cultural studies. Knowledge of the context can facilitate better sampling and control of confounding factors that are likely to affect caregivers well-being, as well as caution researchers to not attribute differences in experience primarily to culture and religion. The role of environmental factors in determining the use of services by families with a child with IDD will be discussed in greater detail below.
3.2. Cultural context factors In this section, we begin with a brief description of culture and religion and subsequently provide an overview of some of the cultural factors that may influence caregivers’ appraisal of a child with IDD, and its effect on their coping strategies. These factors also interact with the environmental context of the family. Culture is considered to be a socially constructed, dynamic system of social beliefs, and values that enhance survival and adaptation as well as provide meaning to a group (Wong, Wong, & Scott, 2006). Furthermore, it is transmitted and adapted from one generation to another (Triandis, 1995). Religion is an aspect of culture that is highly influential in the beliefs of particular groups. We define religion as a body of knowledge or a system of belief that prescribes a way of life, a belief in the higher order with or without a form or entity. An important consideration is that beliefs and
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values may vary within a culture due to factors such as socioeconomic status, family background, and religion (Erickson, Devlieger, & Sung, 1999). Glidden et al. (1999) proposed a model of religion, ethnicity, and disability. The model extends the ecological perspectives of family adaptation and adjustment to include religion as it interacts with the cultural context within which the family lives. According to the model, as families interpret the meaning of having a child with a disability, and garner coping resources to deal with their life tasks, their adjustment and adaptation are influenced by their family characteristics, ethnicity, religious beliefs, and practices operating at a macrolevel. According to these authors, it is the interaction of the above factors that impacts adaptation over the lifespan. We similarly hypothesize that religion as part of the cultural context impacts caregivers’ stress, and may influence their coping strategies and use of resources to adapt to a child with a disability. We discuss some of the prevalent religious and cultural beliefs among Asians that are likely to affect several aspects of the stress process. 3.2.1. Religious beliefs Confucianism has had tremendous influence on the culture, history, and governments of East and Southeast Asia, particularly in China, Japan, Korea, Taiwan, Singapore, and Vietnam. Important aspects of Confucianism are also shared by other Eastern belief systems and religions such as Taoism, Buddhism, and Hinduism. Some of the common themes across these belief systems include the notion of social harmony, filial piety (including to ancestors), and beliefs in past life and reincarnation (Tews & Merali, 2008; Twoy, Connolly, & Novak, 2007). Christianity and Islam may also influence beliefs in families with a child with a disability such as the belief in an afterlife for the child or for the family who is tested by being given a child with a disability. Some of these themes play out in beliefs about disability. 3.2.2. Collectivism versus individualism Collectivism as a cultural construct is prevalent across Asian societies. However, it needs to be acknowledged that these beliefs are not unique to Asia, but are also evident in countries such as those in Latin America. In this review article, we specifically look at how the concept of collectivism shapes caregiver experiences within an Asian context. In societies oriented toward individualism, individual rights, concern for oneself and one’s family, and personal autonomy are emphasized, while in collectivist societies the in-group and fulfillment of social roles are considered important (Chun et al., 2006). Although individuals and families may be on a continuum between these two orientations, research has found that in general, European Americans are more individualistic than people in non-Western and underdeveloped countries (Oyserman, Coon, & Kemmelmeier, 2002). Chun and colleagues argue that in the framework
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of a stress and coping model, collectivist-oriented individuals, such as many who are of Asian descent, are more likely to want to please family members and make decisions based on the family needs than persons from individualist societies. While there is a conception that greater reliance on the family in collectivist cultures should lead to greater family support, it could also produce the opposite effect. For example, if having a child with a disability is considered shameful in a particular society, this could reflect badly on the family and lead to lower levels of family support. We will explore these issues in the research on families who have a child with an IDD when discussing resources and informal social supports and coping.
3.3. Appraisal Appraisal is the process through which a person evaluates whether a situation is stressful or whether there is a potential for harm or more positive outcomes (Lazarus & Folkman, 1984). The way an event is appraised by a person directly contributes to her or his adaptive response, and use of coping strategies and resources to address the situation. Cultural beliefs and explanatory models about disability are part of the appraisal process and contribute to how parents respond to having a child with an IDD. 3.3.1. Beliefs and explanatory models in Asian countries Kleinman (1980) developed the concept of a cultural explanatory model of health that is based on shared beliefs, values and attitudes about deviance, and normative development which then determines health-seeking behaviors among the group. The majority of studies we found on Asian families were ethnographic in their methods and focus on cultural beliefs and explanatory models. As a result, our review reflects more of this type of research. We begin this section by discussing findings from China, where many of studies we reviewed were conducted, specifically exploring some of the cultural explanatory models associated with the birth of a child with a disability. In a study by Lam and Mackenzie (2002) in China, mothers of children with Down syndrome who participated in a qualitative study were found to blame themselves for their child’s Down syndrome. These mothers sought explanations ranging from medications ingested during pregnancy, to reflecting on whether they had done anything wrong in the past to deserve such a child. Some mothers attributed the birth of the child to heaven’s punishment for their ancestors’ wrongdoing and resisted looking at or even touching the child. Similar findings were reported in an ethnographic study of 15 mothers caring for a child with IDD in China (Holroyd, 2003). Some of the mothers attributed the birth of their child with IDD to a violation of the natural order of events as it challenged the concept of reciprocity and
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communicated images of discontinuity and kinship obligations prevalent among societies dominated by the Confucian culture. Mothers took on the blame of giving birth to a child with IDD, especially when the disability was evident at birth. Some mothers were blamed for causing the disability because there is a belief that disabilities stem from something the woman or her side of the family has done. For example, one woman described how her friend who had a child with autism was blamed for causing autism in her son because the child physically resembled the mother’s side of the family. The study also found evidence of folk beliefs. Some mothers in the study reported that many in their culture believed that disability in a child results if pregnant women had engaged in activities such as digging a hole, attending a funeral, participating in funeral customs or viewing a dead body. Culture not only contributes to attributions about cause, but also shapes people’s attitudes toward persons with IDD. These attitudes have been noted by Peters (1980) in a field study conducted in a rural Tamang community of Nepal. Nepal is a country in South Asia where Hinduism is predominantly practiced; however, the Tamang are primarily Buddhists. Peters found gendered differences in acceptance of a man or a woman with IDD, depending on their ability to fulfill social roles. For example, the study found greater acceptance of women with an IDD, compared to a man with a similar condition. Peters attributed this to the prevalent worldview among the Tamang in which a women’s status is dependent on the ability to conduct basic household chores. Therefore, a lack of social skills need not jeopardize her social status or position, as long as she is able to competently fulfill household responsibilities. In contrast, men with IDD were treated differently because of cultural expectations for men to be intelligent in order to fulfill their social roles. Men with IDD are forbidden from inheriting property and are accorded lower social status. Because this study was conducted in the late 1970s, it would be interesting to see if these gendered patterns persist today. However, irrespective of the gendered social status, Peters found a widely shared notion among the Tamang that people with IDD must be treated kindly otherwise it reflects poor taste. The wealthy often offer assistance and provide foster care to those with IDD because of the widely shared belief that assistance to the needy will earn merit for a better rebirth. These beliefs are consistent with the Buddhist belief in the law of Karma, or the cycle of life, among the Tamang who are followers of Vajrayana Buddhism (Peters, 1980). Although the previously mentioned study was conducted more than 25 years ago, a more recent study of parents of children with IDD in Nepal reported similar findings about beliefs toward people with disabilities (Shrestha & Weber, 2002). For example, the authors reported that there was a prevailing belief that good deeds result in good life and families were concerned about improving the lives of their family member with IDD.
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Islamic beliefs of causality and treatment of those with IDD were reported in a study of 30 caregivers and rehabilitation workers from Kabul, Afghanistan (Armstrong & Ager, 2005). The authors found variations in beliefs of causation. Service providers reported that people in urban areas placed greater emphasis on medical causes like poor prenatal care and sought rehabilitative services, whereas those in rural areas appeared to be centered on folk Islam and superstitions like fate, possession by a spirit (djinn), the will of Allah, belief in divine punishment or sin. These beliefs encouraged families to seek treatment from the folk sector, such as visiting shrines or making pilgrimages, and rarely to seek rehabilitation services (Armstrong & Ager, 2005). Overall, the findings of the studies reviewed in this section lend attention to the importance of cultural beliefs about the cause of disability, which shape attitudes toward those with disability and decisions about the treatment. To summarize, in the studies conducted in China and Nepal, common beliefs of causality were attributed to sins from the past life, violation of Confucian ethics, ancestors’ wrongdoings and blaming the mother for being a causal agent to the child’s disability. These similarities in beliefs about causality arise from common doctrines about the cycle of life, rebirth and karma, among the Buddhists, Hindus, and those who are influenced by Confucian philosophy. In contrast, Islamic cultures may attribute disability to fate or possession by spirits, as seen in the study by Armstrong and Ager (2005). Although cultural beliefs are important, it needs to be emphasized that values and beliefs regarding disability cannot be generalized to everyone in a social group and will vary by education level, knowledge about disabilities, and access to modern medical services. 3.3.2. Immigrant families, acculturation, and beliefs An important concept to consider when discussing immigrant families is the process of acculturation (Blacher & Mink, 2003). Acculturation can be thought of as the process that occurs when a group from one culture comes into contact with a group from another culture (Berry, 2006). Although both groups may change their original cultural patterns, immigrants are most frequently expected to adapt and change to the majority culture of the host country. Social, economic, and environmental conditions are different than in their countries of origin, and immigrant groups may retain some elements of their original culture while changing others, and acquire new cultural practices from the host country (Berry, 2006). In the following section, we will discuss studies of Asian immigrant families to the United States and United Kingdom and in the process will discuss some of the issues around acculturation that becomes evident in our review of research on cultural and religious beliefs regarding IDD. Families in the USA studies are more likely to be from East or Southeast Asia, whereas families in the UK studies more likely to be from South Asian countries.
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We begin by reviewing two studies that focused on general public attitudes of Asian immigrants in the United States about disabilities, and then we review research on attitudes and beliefs of immigrant parents of children with an IDD. In an effort to understand the beliefs about disabilities among Korean American women, Erickson et al. (1999) interviewed 30 Korean American women who were college undergraduate and graduate students and had lived an average of 17 years in the United States. These researchers found that most of the women held beliefs about the causes and treatment of disabilities that were consistent with those of American mainstream culture. With respect to beliefs about the cause of disability, the women identified culture specific folk beliefs (e.g., fate, imbalance of the body, punishment from God), but were less likely to endorse these beliefs themselves. However, many simultaneously held Western medical beliefs and Eastern cultural beliefs [i.e., the use of prayer to God or ancestors, herbal medicines (deer antlers or royal jelly), and visits to herbal doctors or acupuncturists] about treatment. When asked to rank what disabilities would be considered most severe in Korean culture and which ones would affect the person’s life the most, mental retardation was the disability ranked as most severe among 18 physical and mental disabilities (e.g., Alzheimer’s disease, mental illness, blindness, deafness, cerebral palsy, paralyzed and missing limbs). The authors attribute this to the importance of intelligence and soundness of the mind in Korean culture (Erickson et al., 1999). However, it should be noted that parents in Western cultures are likely to rank mental retardation as most severe as well. Nevertheless, these findings demonstrate how acculturation may affect Korean immigrant women’s belief about people with disabilities and treatment. These young women have acquired beliefs from their host culture, lessened their adherence to some from their country of origin, yet retained others. A study of Vietnamese Americans that sought to learn about attitudes toward children with disabilities interviewed 43 Vietnamese adults living in California who were primarily midlife and older adults (Huer, Saenz, & Doan, 2001). The researchers examined the relationship of acculturation with these attitudes by comparing two groups, those who responded to the questionnaire in Vietnamese and those who responded in English, presuming that those who responded in English were more acculturated. Findings from the study contradicted stereotypical statements in the literature about how Vietnamese think about disabilities. For example, both groups in the study were unlikely to endorse the statements, ‘‘if I had a child with a disability, I would feel shame,’’ and ‘‘children with disabilities were a punishment from God.’’ The one statement that the two groups differed on was ‘‘Once someone is disabled, little can be done for them.’’ The English speaking group was less likely to endorse this statement, suggesting that they had greater hope than the Vietnamese speaking group. These authors theorize that because there is a relative scarcity of
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services and knowledge about disabilities in Vietnam, the less acculturated group may be less hopeful (Huer et al., 2001). Providing evidence of cultural change, an in-depth study of five Chinese immigrant parents of children with developmental disabilities found that all but one set of parents accepted the child’s disability with a hopeful and positive attitude (Parette, Chuang, & Huer, 2004). The other set of parents reported struggling with accepting the child’s disability and one of the accepting set of parents indicated that while they were positive and hopeful, some members of their family had difficulty accepting the facts related to the child’s disability. The authors contrasted these findings with cultural beliefs among Asian families and reported that at least for these five families, the cultural beliefs did not hold up (Parette et al., 2004). The interaction of culture, belief, and context in shaping experiences of immigrant families has been noted in a qualitative study of Korean and Korean American mothers of young children with IDD. The authors found differences in appraisal between the two groups about public attitudes toward their children (Cho, Singer, & Brenner, 2003). Korean mothers reported experiencing a great deal of stigma when taking their child out in public, whereas the Korean American mothers viewed societal responses more positively. Part of this difference has been attributed to the differences in the social and cultural context within which families function in Korea and in America. The authors attribute the less stigmatizing experiences among Korean American caregivers to perceived tolerance, free public intervention, educational, and case managements services, as opposed to the lack of social tolerance of disability within Korean societies. In spite of differences in appraisal, Cho et al. found both groups of mothers to have similar beliefs about the cause of disability, believing that they were responsible for their child’s disability due to poor prenatal practices (referred to as Tae Gyo). The similarities in beliefs among the two groups may be due to the immigrant caregivers’ recent immigration history to the United States. Demographic characteristics show that respondents on average had 5–9 years of residence in the United States and, as indicated by Castles and Miller (2003), culturally distinct settler groups almost always maintain their language and some elements of their homeland culture at least for a few generations. Therefore, it is likely that they have not yet been acculturated to American beliefs about causation. The study also found that many of the Korean Americans believed that the child’s disability was part of a divine plan that would benefit the family (Cho et al., 2003). These beliefs may be attributed to the importance of the Korean Christian Church in the lives of immigrant Koreans in the United States that has likely shaped the caregivers’ beliefs. However, it needs to be cautioned that beliefs in the divine plans among devout Christian Koreans are not unique to them. Similar findings have also been noted among devout Christian African Americans (Rogers-Dulan & Blacher, 1995) and Latino (Heller, Markwardt, Rowtiz, & Farber, 1994) caregivers to children with IDD.
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Much like Cho, Singer, and Brenner (2000), other studies also found evidence of the retention of cultural values from the home country. An ethnographic study of Southeast Asian (primarily from Vietnam and Cambodia) parents of children in a Head Start program found that parents had distinct differences in their beliefs about disabilities than the Head Start teachers (Hwa-Froelich & Westby, 2003). These parents only considered more obvious impairments such as blindness, deafness, and physical conditions to be disabilities, whereas intellectual disabilities were attributed to stubbornness, laziness, fate, or the child’s nature (Hwa-Froelich & Westby, 2003). Similarly, a qualitative study of Chinese American parents of children with developmental disabilities found that the parents had a difficult time accepting the child’s disability which delayed diagnosis and pursuit of services (Shen-Ryan & Smith, 1989). They also blamed themselves for the child’s disability or attributed the cause to cultural factors such as fate, beliefs in harm caused due to a pregnant women’s exposure to physical labor or to God’s will. Some mothers referred to colds and fevers with respect to the cause of their child’s disability which fits with the Chinese view of the dual forces of Yin and Yang and their relationship to excessive heat causing fevers and excessive cold causing chills (Shen-Ryan & Smith, 1989). Several parents used Western medical treatment while simultaneously using Chinese culturally specific cures as in the previous study. For example, one parent took her child with epilepsy to a medium to offer incense to drive the evil spirit away and another couple had their child wear silver bangles with charms on both hands to bring good luck to the child. The authors found that one third of the parents believed in the hot and cold dichotomy in treating illness (Shen-Ryan & Smith, 1989). The greater reliance on cultural beliefs may be attributed to the less acculturated parents in the study. Even though no formal measure of acculturation was used, the study demographics showed that of the 59 families, 53 were first generation immigrants to the United States. In 55 of the families, both parents had difficulty in speaking English and approximately 95% spoke in Chinese at home, thereby suggesting that these families were relatively less acculturated compared to immigrant families with several years of experience in the United States. Demonstrating retention of certain cultural values, a study that examined parental attributions of Asian American families (from East and Southeast Asia) toward their child with Down syndrome found some interesting differences between Asian American and White American families (Ly, 2008). In both groups, parents rated the performance of their child in completing a puzzle. Asian American parents were more likely to attribute lower ability and effort to their child’s performance and indicated more anger and blame toward the child than the White American group. However, the Asian American parents were more likely to simultaneously provide more encouragement to children they considered to have low
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ability and effort. The authors note that these findings are similar to studies of typically developing Chinese children and their parents in which parents display more anger and issue more punishment toward children whom they perceive as failing, as compared to Chinese American and White American parents (Hess, Chang, & McDevitt, 1987, as cited in Ly, 2008). A study of Indian immigrants also emphasized strong retention of cultural values (Gabel, 2004). Gabel interviewed 20 Hindu Indian immigrants in the United States exploring their concept of mental retardation. Her sample was a highly educated group of 12 women and 8 men, and two of these participants had a member in the family with an IDD. Gabel argued that with the exception of one participant who held a psychology degree from a Western university, all of the participants held similar cultural perceptions and beliefs about IDD regardless of whether they were recent immigrants or had been in the United States for as long as 20 years. Reflecting the Hindu belief in reincarnation, most of the participants believed that a child in the family with an IDD was a gift from God that was meant as a lesson for sins committed in a previous life. For example, the mother of a child with an IDD in the study took comfort in the belief that her daughter may have been a relative in a previous life who came back to give her the problems she may have given this relative in the past life, and teach her a lesson that she needed to learn (Gabel, 2004). These findings are very similar to those previously reported of families in China and other cultures who believe in re-incarnation, karma, etc. It is important to note that South Asians, who immigrate to the United States, primarily from India, are different socioeconomically than many South Asians who immigrate to the United Kingdom, who are frequently from Pakistan, Bangladesh and India. These differences may be due to differences in migration patterns (Castles & Miller, 2003), greater proximity to the United Kingdom from South Asia and higher immigration standards in the United States for Asians than those in the United Kingdom. Asian families must have substantial resources to overcome these distance and legal barriers to move to the United States. In contrast, low-income South Asians are drawn to the United Kingdom to fulfill many of the labor needs of this region. Despite these socioeconomic differences, a study of South Asians in the United Kingdom using both qualitative and quantitative measures reported similar findings about causal attributions but found evidence of much variability in attributions about the cause of autism, ranging from God’s will and magic to mental health, illness, and physical causes (Dobson, Upadhyaya, McNeil, Venkateswaran, & Gilderdale, 2001). Another UK study using both quantitative and qualitative measures focused on the experiences of South Asian mothers whose children had severe disabilities (Hatton, Akram, Robertson, Shah, & Emerson, 2003). Open-ended comments revealed that mothers had difficulties dealing with
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the beliefs of family members. These beliefs ranged from the mothers being responsible for not taking care of themselves during the prenatal period, to djinn, an Islamic belief that the person is possessed by a spirit, to the belief that God sent the child. To summarize this section on cultural beliefs about disability among immigrant families, there is some evidence of acculturative changes in beliefs among Asian immigrant families. There are some differences in beliefs about disability between immigrant groups who are at different levels of acculturation, and between families who immigrated compared to families in their country of origin. Many immigrant family members retain beliefs from their countries of origin while simultaneously adopting new beliefs and attitudes. Across the different cultural groups, mothers are often blamed for causing their child’s disability. Other similarities across cultural groups are consistent on families of children with IDD in Asia. For example, the belief that the child is a result of wrongdoing in a past life, or sent by God either to teach parents a lesson, or as a gift, was found in both the Asian and Asian American studies. Therefore, as researchers, it is important while conducting crosscultural studies to take into consideration the context from which the sample is drawn from, as well as strengthen sampling strategies to better reflect acculturative processes and differences in experiences.
3.4. Coping According to the Lazarus and Folkman’s model (1984) as soon as an event is appraised as stressful or harmful to one’s well-being, it immediately triggers coping strategies to help a person adapt successfully. In the caregiving literature, coping has been identified as a mediator in the stress adaptation relationship. It is the process through which the individual manages the demands of the person–environment relationship that are appraised as stressful (Lazarus & Folkman, 1984) and involves a constant change in the cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person. The concept of coping is important in a caregiving context primarily because caregiving involves a variety of tasks that challenge a caregiver’s physical and psychological abilities. Under these circumstances, it is important to identify the types of coping strategies used by caregivers and their success in alleviating the stressfulness of the situation so that future and ongoing services can be tailored to meet their needs. 3.4.1. Western versus Eastern conceptions of coping From a Western viewpoint, Lazarus and Folkman (1984) suggested two forms of coping: problem-focused and the emotion-focused coping. As the name suggests, problem-focused coping involves strategies that are used for
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solving problems, for example, seeking treatment or services. These include efforts directed at defining the problem, generating alternative solutions, weighing the alternatives in terms of their costs and benefits, choosing among alternatives and acting upon them (Lazarus & Folkman, 1984). In contrast, emotion-focused coping involves strategies that are aimed at reducing or managing the emotional distress that is associated with the situation (Carver, Scheier, & Weintraub, 1989). A more Eastern viewpoint on coping as expressed by Chun et al. (2006) includes the cultural value of collectivism. Individuals from collectivist cultures are socialized to be interdependent in their relationships with others and use the family as a source of ego strength and social support (Yeh, Kwong Arora, & Wu, 2006). Other elements of collectivist cultures are having respect for elders and authority figures, foregoing one’s individual needs to maintain social harmony, and fatalism, or a belief that control lies in external forces (Yeh et al., 2006). These cultural attributions directly shape how individuals cope with a stressful situation. Of course, Asian cultures are not the only ones that may have a more collectivist orientation. Research on Latino families of children with IDD also indicates collectivist orientations in the stress and coping process through the cultural value of familism (Magana, 1999). Chun et al. (2006) provide a clear explanation of how coping strategies vary by culture. According to Chon et al., coping strategies that confront or modify external stressors are more common in the individualistic cultures, whereas coping strategies that avoid external stressors and instead modify internal psychological states are more common in collectivistic cultures. Individuals from collectivistic cultures have more external locus of control and a greater tendency to attribute stressors to bad luck. Therefore, there may be a greater tendency to rely on cognitive or avoidance-focused coping that reflects their desire to control internal states. 3.4.2. Research on coping strategies of families in Asia The relationship between cultural attributions and coping strategies employed is evident from some of the studies we reviewed. For example, in societies where the birth of a child is associated with loss of face or end of bloodline, caregivers are often overwhelmed by feelings of shame. Parents tend to hide the birth of a child with such a condition, denying themselves any external sources of support thus leaving themselves dependent on selfreliant strategies. This phenomenon was observed among Chinese mothers, who found them to be primarily dependent on self-reliant strategies (Lam & Mackenzie, 2002) and internal coping strategies (Shek & Tsang, 1993) instead of seeking support from husbands and relatives. The tendency to depend on self-reliant coping strategies or avoidant coping strategies is consistent with traditional Chinese beliefs of maintaining face or nondisclosure of shameful family affairs to outsiders, and the importance of control
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over emotional expression (Lam & Mackenzie, 2002). However, it needs to be emphasized that coping strategies are subject to change, partly driven by knowledge of the disability or exposure to similar others. Therefore, Lam and Mackenzie (2002) found mothers, when exposed to families under similar situations, appraised their life circumstances more favorably. In contrast to the passive coping strategies evident among Chinese caregiving mothers, our review also showed the use of problem-focused strategies, such as active coping and planning (active coping involves taking direct action, increasing one’s efforts, and trying to execute a coping attempt in a step wise fashion; planning involves coming up with action strategies and decide on the best steps to handle a problem), often shaped by cultural attributions. For example, where the birth of a child with IDD is attributed to folk beliefs, parents often seek problem-focused coping strategies, such as seeking alternate folk treatments and visiting herbalists (Holroyd, 2003). Others like Shrestha and Weber (2002) found variations in coping strategies, based on causal attribution of IDD in a child to the law of Karma. The basic tenet of the law that good deeds result in good life was found to motivate families to proactively seek treatment for the son or a daughter with IDD. As a result, parents explored all possibilities for treatment from traditional methods to seeking modern medical care. Traditional treatments included visiting temples and shrines. The authors also discuss a parallel belief among the Nepalese where disability is thought to have resulted from past sin and the affected individuals and their families are blamed for their condition (the cycle of birth). Overall, the findings of the studies reviewed in this section bring attention to the importance of cultural beliefs about the cause of disability that shapes coping strategies. As in the studies conducted in China and Nepal, common beliefs of causality were attributed to sins from the past life, violation of Confucian ethics, ancestors’ wrongdoings and blaming the mother for being a causal agent to the child’s disability that likely shapes parental coping strategies. While some come to depend on passive coping, there are others who seek active coping strategies. These similarities in beliefs about causality arise from common doctrines about the cycle of life, rebirth and karma, among the Buddhists, Hindus and those who are influenced by Confucian philosophy. In contrast, Islamic cultures may attribute disability to fate or possession by spirits, as seen in the study by Armstrong and Ager (2005). Interestingly, the studies reviewed found that irrespective of religious affiliation, those who adhered to cultural beliefs in causation of disability sought culturally appropriate treatment options, such as visiting shrines or seeking herbal cures. Although cultural beliefs are important, it needs to be emphasized that the values and beliefs regarding disability cannot be generalized to everyone in a social group and will vary by education level, knowledge about disabilities, and access to modern medical services.
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We found one study that addressed coping among Asian immigrant families. In the United States, researchers compared coping strategies of Asian American and White parents of children with autism using the Family Crisis-Oriented Personal Evaluation Scales (Twoy et al., 2007). Both groups were of high SES; however, the Asian American parents were more likely to use reframing strategies and the White parents were more likely to use passive appraisal. The authors did not identify what Asian countries were represented among the Asian American parents, but attributed these differences to the influence of beliefs such as Confucianism, Taoism, and Buddhism that may have shaped their values. The authors argue that the values of harmony, with nature and interpersonal relationships and family unity may contribute to parents reframing into a positive view (Twoy et al., 2007). Overall, in our review of coping strategies, we found varied use of coping mechanisms among caregiving parents. There was some evidence of the role of culture in shaping coping strategies, but at the same time, the findings sensitize us to the need for more rigorous research on coping, with sufficient acknowledgement of the context, including socioeconomic status, levels of education, availability of services, public knowledge about causation, etc., within which families function.
3.5. Resources According to Lazarus and Folkman’s (1984) model, the ways people cope depend heavily on the resources that are available to them and the constraints that inhibit the use of these resources (Lazarus & Folkman, 1984). A resourceful person is one who has many resources and/or is clever in finding ways of using them to counter demands. Thus, resources are drawn upon, whether they are readily available to the person or whether they exist as competencies needed for finding resources (Lazarus & Folkman, 1984). We will include in the resource section two types of resources, informal social support (family and friends), and formal social support (services). 3.5.1. Informal social support A common finding across studies conducted in China is the loss of social support following the birth of a child (Holroyd, 2003; Lam & Mackenzie, 2002; Pearson & Chan, 1993). As noted earlier, the birth of a child with an IDD among the Chinese is associated with loss of face or an end to the bloodline. As a result, parents rarely disclose the diagnosis to outsiders (Holroyd, 2003; Lam & Mackenzie, 2002; Pearson & Chan, 1993) denying themselves needed support from friends. In societies where there is a strong moralistic view associated with the birth of a child with disability, a belief that parents should bear the responsibility with no sympathy or support often isolates the parents (Chen & Tang, 1997). These causal attributions
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directly affect social support resources that parents can garner which demonstrates the link between appraisal and resources. For example, mothers in these studies reported friends drifting away, and in several cases their own mothers severed ties, reducing their social support network (Holroyd, 2003; Lam & Mackenzie, 2002). Relatives who were accepting of the child provided care, whereas those who did not preferred to avoid contact (Shek & Tsang, 1993). Shek and Tsang reported that almost half of the mothers in their study never sought help from friends, relatives, parents and parents-in-law and a third never accessed professional help. Pearson and Chan (1993) attributed lack of support from parent-in-laws to the traditional belief of blaming a daughter-in-law for giving birth to a child with disabilities, especially when it is a boy. Chang and Hsu (2007) reported that immediate family and training center staff were the primary support sources, while relatives, self-help groups and professionals were less frequently perceived as sources of support. Therefore, family relationships, instead of being helpful to parents in raising their child with an IDD, may be perceived as a source of stress (Chang & Hsu, 2007). These patterns may appear to be at odds with the notion of collectivism in Asian societies in which parents of children with disabilities might be expected to rely on family for support. However, they are consistent with one aspect of collectivism which is that the individuals’ behavior and characteristics reflect on the family, which can have a negative impact on social support for parents who have children with an IDD. For example, to save a family’s honor, parents may be reluctant to disclose the diagnosis of the child with IDD, even to close family members. An explanation by Chun et al. (2006) may further substantiate the outcomes. According to Chun et al. (2006), it is likely that people from collectivistic cultures, compared to individualistic cultures would utilize more collective coping such as support seeking because of their interconnectedness with the in-group. On the other hand, it has also been hypothesized that these individuals desire to protect group harmony and not burden the group thereby discouraging support seeking behaviors. In contrast to the experiences of Asian mothers in their home country, immigrant mothers tended to perceive greater support. A study that compared Korean parents to Korean American parents of children with IDD found that the Korean mothers had limited amounts of informal social support, again contradicting the theory that those with a collectivist orientation would be more likely to rely heavily on support from their families (Shin, 2002). Similar to the studies cited earlier on social support in China, the researchers found that the Korean mothers received negative messages from their family networks which compelled the mothers to restrict discussion of their child with people in their network. Consequently, the informal network was perceived as less helpful. In contrast, the Korean American mothers were able to rely on the support from friends in addition to family members (Shin, 2002). This may be attributed to greater exposure to
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knowledge about cause and services to individuals with IDD, or to perceived anonymity from being away from the extended family in Korea (reducing the probability of negative messages), and a close knit Korean American community in the United States that may have fostered community support to a parent with a child with IDD. 3.5.2. Formal social support In this section, we discuss interactions that families have with the service systems both in Asia and in the United States and United Kingdom. The use of formal services is dependent on the availability of services. As indicated in our introductory section on context, we did find that several Asian countries are lacking in resources. Therefore, it is highly probable that the lack of resources have an effect on resource use, thus showing the importance of the environmental context. 3.5.2.1. Service access and use in Asia As indicated, there is dearth of specialized services for individuals with IDD in several Asian countries. Therefore once diagnosed, parents are often challenged by the lack of rehabilitation services in the community. This is evident across several studies reviewed in this chapter. In a qualitative study, McCabe (2007) reported on the lack of educational services available to children with autism in China, and parental response to these adverse conditions. The author commented on the nature of elementary classrooms in China that has approximately 40–70 students taught by one teacher. Thus, teachers understandably feel unable to provide individualized support to students with special needs (McCabe, 2007). Moreover, even in cities where there is a specialized school, it is not necessarily large enough to accept all children with special educational needs (McCabe, 2007). A survey carried out in 2001 of children 0–6 years old found that only 4.5% of children with IDD were receiving special education in six provinces, while an overwhelming majority were receiving education at home (China Statistics Press, 2003). Parents in McCabe’s study reported advocating for their children to attend school, but were often turned away. Despite the lack of services, they went to great lengths to advocate for their children, including borrowing money, making financial sacrifices, moving, transferring work positions, and missing work (McCabe, 2007). Studies in Taiwan also highlighted difficulties in access and availability of services for people with IDD (Chang & Hsu, 2007; Lin, Yen, Li, & Wu, 2005). Factors identified by families as barriers to accessing services included the inconvenience of services availability, the time-consuming nature of accessing services, lack of transportation facilities, difficulties in finding appropriate services, and discontinuity of care because of changing referrals and affordability (Lin et al., 2005). Parents reported their frustration
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with the unavailability of services and dissatisfaction with services that were available for their children with IDD (Chang & Hsu, 2007; Lin et al., 2005). A study of 25 Chinese and 12 Malay mothers of children with an IDD found that the Chinese mothers used services more than the Malay mothers (Ow, Tan, & Goh, 2004). Although groups were similar on informal support sources, the authors found them to differ on sources of formal support. Both groups identified immediate family, especially support from spouse, to be most helpful. However, none of the Malay Muslims identified any formal source of support. Even though the authors primarily attribute this to ethnic and religious differences, we provide other plausible suggestions. First, the study was conducted in Singapore, with 75.2% of the population being of Chinese ethnicity, and the Malay Muslims make up only 14% of the population. Therefore, it is likely that Malay caregivers may have developed close kin networks to help each other and rarely seek support from outside. Second, the lower use of formal services may further suggest that perhaps services in Singapore are not adequate or appropriate to meet the needs of the Malay Muslims. In Shrestha and Weber’s (2002) study, Nepalese caregivers also reported difficulties in availability and accessibility of services that would facilitate diagnosis and treatment. The lack of formal diagnostic services led families to seek these services in major cities, neighboring countries and in some cases, Western countries. Schools generally lacked assessment capacity, and parents often changed schools to find ones that would respond better to their child, or took it upon themselves to set up schools in their villages with the help of family and community. Difficulties with accessibility arose due to concentration of services in cities which limits access to families in rural areas. While this problem is also evident in Western countries such as United States (Lishner, Richardson, Levine, & Patrick, 2008), there are some unique barriers to service accessibility in several developing countries such as Nepal. Barriers to access include unavailability of private or public transportation and lack of assistive devices to facilitate transportation. Services in rural areas are absent and are primarily located in Katmandu (the capital of the country) region. Because consumer goods and services, leisure activities, and almost all aspects of public life are usually designed for nondisabled persons, people with disabilities and their families find themselves consistently requiring the exceptional, that is more expensive, and there is usually insufficient money to allow families to pay for goods that would make life easier. Caregivers therefore often resort to walking for hours carrying the disabled person along. In an effort to meet the needs of the child with IDD, Nepalese mothers in the study worked with the community to establish special schools that were more local (Shrestha & Weber, 2002). Similar constraints to service accessibility and availability are reported by Daley (2004) in a study of parents and health-care providers of children with autism in India. Parents reported delays in treatment that were in part due to
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unavailability of physicians or diagnostic centers. Similar to the Nepalese families, families in India often traveled considerable distances to seek diagnosis and treatment. Because of prevalent stereotypes and misconceptions about violent and unmanageable behavior of children with autism, a diagnosis of autism often closed doors to educational opportunities. More recently, autism has been given legal recognition as a disorder in India, making children with autism and their families eligible for benefits available to children with already recognized disabilities, which may increase the availability of services that were previously not provided to families of children with autism (Daley, 2004). The lack of availability of rehabilitation services to address the needs of children with IDD in Afghanistan was reported by Armstrong and Ager (2005). The lack of services is driven by political events that have shaped Afghanistan, such as war and ethnic conflict that resulted in the deterioration of health services ever since the Soviet invasion in 1979. Furthermore, rehabilitation workers interviewed in this study were primarily aware of traumatic brain injury as a disability but were not as familiar with IDD from other causes (Armstrong & Ager, 2005). The future of the child with IDD is a pressing concern for parents across societies, and is also evident in the west (Freedman, Krauss, & Seltzer, 1997). However, while parents in the United States or United Kingdom may have options for long-term support of people with disabilities, such as setting up trusts and residential facilities, such options are rarely if available in Asian countries. For example, it has been estimated that there are approximately 62,000–87,000 persons with various degrees of IDD in Hong Kong (HKSARS, 2001), but only about 5300 residential facilities for adults with moderate to severe ID, and a waiting list of 3500. This unavailability of long-term care facilities impacts future planning for adult children, and parents often resort to culturally appropriate long-term plans or coping strategies. For example, in Holroyd’s (2003) study of Chinese caregivers, parents often hoped that their child would die before they do because of their inability to identify alternative long-term placement for their adult children with IDD. For those who did plan for long-term placement, factors motivating decisions were quite consistent with what has been observed in the literature in the West (Freedman et al., 1997). Two studies explored factors related to out-of-home placement and found that the fear among parents that nobody would take care of their child, the parent’s own aging concerns, not wanting to impose a long-term burden on close relatives and in some cases, a belief that an out-of-home placement provides better care influenced parents decision making (Chiu & Hung, 2006; Ow & Fu, 1999). In addition to those reported above, Ow and Fu (1999) identified other factors that included scarcity of long-term residential facilities and the lack of systematic efforts by social service agencies to help families with future planning. Parents in general preferred to rely on family
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members to care for their adult child with IDD. However, siblings were sometimes reluctant to assume care due to the dangers of leaving their sister or brother with IDD home alone without supervision and the difficulties associated with behavior problems of the sibling with IDD; relatives from the parents’ cohort were often dealing with their own aging, preventing them from taking on a caregiving role (Ow & Fu, 1999). Shrestha and Weber (2002) also studied long-term planning by families with a child with IDD in Nepal and found that planning was often thwarted because of a lack of vocational services and out-of-home placements. There are no reservation policies for government jobs as none is provided by law. The Disabled Protection and Welfare Act 1982, and the Disabled Protection and Welfare Rule 1994 stated that the government would establish homes in different parts of the country for persons with disability and the elderly. According to Shrestha and Weber the 9th national development plan (1998–2002) has emphasized that this residential provision is necessary. Yet, these homes have not yet been established and disability laws are not well defined. Under these circumstances, the study found that parents hoped that their child would remain at home or with siblings. Parents often made alternative plans that were culturally accepted such as making arrangements with a sibling, or marrying off a son with IDD to a woman from lower socioeconomic strata. This guaranteed the son with IDD a secured future when the parents are no longer able to care for him. However, marriage of a daughter with IDD was rarely an option and mothers expected the daughters to die before the parents did (Shrestha & Weber, 2002). Overall, the findings from the above studies report that there is a lack of basic services and knowledge about disabilities in many Asian countries. These factors may serve to reinforce traditional beliefs of causality, care, and treatment among families and their communities. At the same time, these studies also find evidence that parents of children with IDD become strong advocates and engage in intense help-seeking activities on behalf of their child. 3.5.2.2. Service access and use among immigrant families We found that immigrant families reported barriers to accessing services in the United States and the United Kingdom, but when they received services, many were satisfied with them. For example, a qualitative study of eight Korean immigrants in the United States found that the mothers of children with developmental disabilities were generally satisfied and impressed with services they received (Park & Turnbull, 2001). The mothers did report being frustrated with language barriers when interacting with the school professionals. Several of these mothers relied on their husbands to interact with the professionals, as the husbands had better command of English. Five of the eight mothers preferred a noninclusive environment for their child at
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school, believing that the child would get more one-on-one attention and would have a better chance of being cured (Park & Turnbull, 2001). A study of Chinese American parents of children with developmental disabilities found that the parents lacked knowledge about disabilities which may have led to later diagnoses for their children (Shen-Ryan & Smith, 1989). Language barriers with service professionals further exacerbated their lack of knowledge as they were unable to obtain adequate explanations about their child’s disability. One study focused on whether there were cultural differences between Asian American parents and non-Asian parents on skills needed to obtain services (Huang, Delambo, Kot, Ito, Long, et al., 2004). This study examined advocacy skills of parents of young children with developmental disabilities and found that Asian American parents reported significantly lower assertiveness and self-advocacy skills than did the non-Asian American parents (Huang et al., 2004). The authors also found a correlation between self-advocacy skills and receipt of formal supports and services. The authors attributed the differences to the immigrant experiences, language barriers, and lower awareness of the special needs of their children (Huang et al., 2004). In the United Kingdom, a study that compared South Asian families to White families on service use found that 83% of South Asian adults with IDD lived at home with their families, while only 48% of White adults with IDD did (McGrother, Bhaumik, Thorp, Watson, & Taub, 2002). The South Asian families reported significantly higher rates of unmet needs regarding day care, speech therapy, a social worker, home help, and sitting services than the White families even after adjusting for age, sex, city/ county dwelling, and level of ID. The authors attribute the underutilization of services to lack of knowledge about IDD and of services available, religious and cultural attitudes and beliefs, lack of culturally appropriate service provision, and more social support from extended family (McGrother et al., 2002). However, relationships between these explanations and service use were not tested in this study. Language was reported as a major barrier for South Asian families in a UK study that focused on the experiences of family members first learning about the child’s diagnosis (Hatton et al., 2003). This study found that of the 136 South Asian families of children with severe IDD in the study, 67% received disclosure of their child’s disability by professionals in English and only 33% received any written information. The parents were from Bangladesh, India, and Pakistan and spoke a variety of languages. The main issues about services raised by older Indian and Black parents of children with an IDD in a UK study were lack of information about available services, poor communication between parents and service providers, language barriers, inability to access services, lack of knowledge about how to obtain services and cost (Hubert, 2006). These families also reported
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positive aspects about services they were receiving. For example, the majority of people with IDD attended day centers and the parents were satisfied with the care their adult children received. Those parents that used respite services were satisfied as well (Hubert, 2006). In summary, we found similarities between Asian immigrant families in the United Kingdom and the United States on service issues. For some, use of services is associated with heightened satisfaction, whereas others experience formidable barriers. For example, language barriers, and lack of knowledge about services and how to access them seem to be important issues in both countries. Some of the studies suggest that cultural beliefs and access issues may be a contributing factor to late diagnosis of the child with the IDD and lower service utilization among Asian immigrant families. Future research should test these suggested relationships. This section identified two trends in the literature on Asian caregivers. First, much of the literature on Asians in their own country of origin points to stressors experienced by caregivers due to lack of formal services for their child with a disability, whereas the literature on immigrant families examined stressors experienced due to barriers to language in the host country. Being cognizant of these factors may help researchers to better account for the contextual factors that are likely to affect service use and strategically plan to better existing services.
3.6. Adaptation Caregiving has social, psychological and physical consequences for the caregiver. Lazarus and Folkman (1984) defined three kinds of adaptation outcomes that are a consequence of caregiving. These are social, morale, and somatic health. Social functioning is often conceptualized from a sociological perspective as the manner in which the individual fulfills his or her roles. Less frequently, social functioning is defined from a psychological perspective, as satisfaction with interpersonal relationships. Morale is concerned with how people feel about themselves and their conditions in life. Finally, somatic health refers to physical functioning and absence of illness. Of these three, morale in the form of psychological well-being and burden has been studied the most in the general caregiving literature of families with children with IDD. Those studies that examined psychological well-being of caregivers showed similar findings to those in the West. For example, Shu, Lung, and Chang (2000) found higher rates of depression in mothers of children with autism, compared to those who do not have children with autism. Similarly, other researchers also found evidence of depression among family caregivers (siblings included) for individuals with IDD (Ali & Al-Shatti, 1994; Ghatwala & Gupta, 2004; Ishizaki et al., 2005). Likewise, Taiwanese parents of children with IDD experienced a lower quality of life when
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compared to the general population (Chou, Lin, Chang, & Schalock, 2007). In one study of parents of children with IDD in Pakistan, authors discussed the possible link between resource constraints which force parents to spend large sums of money for medical care, special education and other specialized services for their child, and parental psychological distress (Ali and Al-Shatti, 1994). Even though research studies did not specifically look at the effect of context on caregivers’ adaptation, our review did find indirect evidence of the environmental context on caregiver’s well-being. In a study (Hatton, Azmi, Caine, & Emerson, 1998) where researchers interviewed 54 South Asian families (Pakistan, Bangladesh, India and east Africa) of adolescents and adults with learning difficulties living in the United Kingdom, findings show South Asian caregivers as having a higher levels of psychiatric distress than those reported in other UK studies of parents of children with disabilities. The authors attributed the heightened distress to high levels of unmet service needs in addition to low socioeconomic status of the South Asians immigrants. Similar patterns were also observed by Emerson, Robertson, and Wood (2004) in their comparative study of South Asian immigrant families in the United Kingdom to White families of adolescents with IDD. In the study, South Asian immigrants were four times more likely than White families to be above the threshold of depression, indicating a psychiatric disorder. Again, the families recruited were primarily from poorer neighborhoods. In contrast to the above two studies, a study that examined differences between South Asians and White families from a registry of caregivers of persons with an IDD in Leicestershire, United Kingdom, found that although the South Asian families had a more difficult time managing financially compared with Whites, there were no differences in the caregivers’ levels of stress, general health status, and smoking habits (McGrother et al., 2002). The mixed findings may suggest the varied nature of adaptation to stressors and that some of these stressors may be unmeasured in the studies. Even though the studies indicate the importance of context on caregiver adaptation, more research is needed to further explore these relationships, if we are to develop culturally competent services for ethnically diverse families. In contrast to the studies in United Kingdom, a study that compared Korean mothers to Korean American mothers of children with IDD found significant differences in psychological distress between the two groups (Cho et al., 2003). The Korean American mothers of children with disabilities had rates of depressive symptoms that were comparable to those of Korean American women in general and significantly lower than the rates for the Korean mothers of children with disabilities (Cho et al., 2003). The qualitative data revealed that the Korean mothers expressed more everyday stress than the Korean Americans, and experienced shame and humiliation when their children displayed behavior problems in public
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(Cho et al., 2003). Again, the findings from this study lend attention to the importance of the caregiving context for Korean women. While Korean women in their country of origin have to battle stigma, this may not be so for the Korean American women, thus differently affecting their well-being. In general, our review found a limited amount of research on adaptation. We identify below some of the limitations that may have contributed to the lack of research about adaptive outcomes. First, most of the studies on caregiving have explored beliefs about disabilities and social support or service use. Second, very few studies have used validated scales, making it difficult to have objective measures of psychological and physical health. Third, more research is needed on the cultural expression of stress. This is particularly important in the Asian context, because cultural norms call for suppression of feelings of distress which may lead to more somatic symptoms or different manifestations of distress. Therefore, it is not known whether there are differences in the manifestation of stress.
4. Summary and Conclusions Research on Asian families who have a child with an IDD provides important information that helps to fill in knowledge within a cross-cultural stress and coping framework. We first examined reports about the environmental context which highlighted the socioeconomic, political, and resource challenges that many Asian countries face which would be expected to shape the family experience. These reports were not studies of families of children with IDD, but gave a more macro- and policy-oriented picture of the how people with an IDD may be considered in Asian countries. We then presented information on the cultural context, and discussed ways that culture and religion might be related to the stress and coping process for families of children with an IDD. The family’s experiences are expected to be imbedded in the environmental and culture contexts which influences all aspects of the stress and coping process. We found majority of studies done on families in Asia drew from the cultural context and examined what we refer to as the appraisal process which includes beliefs about disability. These beliefs are expected to shape how families cope, to some extent the use of resources, and wellbeing outcomes. While Asia is a diverse continent representing many countries, religions, and cultures, the studies we reviewed reported many common beliefs and experiences for these families across Asian cultures. These commonalities were particularly observed in countries influenced by Chinese Confucian thought which shares beliefs and values with religions that originate in South Asia such as Hinduism and Buddhism. Some of the common beliefs about the cause of
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disability included mothers being blamed and blaming themselves for the birth of the child with IDD, the child being a result of past sins of ancestors, or resulting from misdeeds of the parents in a past life. It is important to note that not all Asian families and societies see shame in the birth of a child with an IDD. For example, a parallel interpretation of Confucian and Eastern religious thought that was discussed is the idea that people with disabilities should be treated well because of the value of doing good deeds and the concept of karma which is that your future experiences will be the consequences of your deeds and actions. Thus some studies reported on the belief that treating people with disabilities positively is believed to result in positive experiences in the future. While belief in reincarnation and karma are not part of Islamic religious tradition, one study reported that the birth of a child with an IDD may be the will of Allah or the result of possession by a spirit. Beliefs that the child’s disability is the result of the will of god or a gift from god were also reported among Korean Americans who are Christian. An important limitation of this research is that these studies often did not take into account the environmental conditions that may contribute to cultural beliefs about disability. For example, where there is limited knowledge about disabilities and resources for persons with disabilities, communities may rely more heavily on cultural beliefs. Also, authors may have suggested cultural explanations for phenomena that in fact have more environmental and structural origins. We found limited studies that examined coping strategies of Asian caregivers. We found some evidence of passive, self-reliant and avoidant coping strategies among Asian caregivers which in the context of the Western conceptualizations of coping (e.g., problem-focused and emotion-focused coping) would be categorized as emotion-focused coping. However these strategies may fit better in a collectivist coping explanation in which these tendencies are consistent with traditional Chinese beliefs of maintaining face or nondisclosure of shameful family affairs to outsiders. We also found evidence of the use of what Westerners refer to as problem-focused coping in which mothers used planning and help seeking. However, these active coping strategies often had a cultural twist in which caregivers might seek alternative folk remedies such as seeing an herbalist. Overall, the use of coping strategies needs further investigation. Use of instruments that measure collectivist coping from an Asian perspective as identified by Wong et al. (2006) would deepen our understanding of coping among Asian and Asian immigrant families of children with IDD. Research on the use of resources by Asian families was more extensive than research on coping. With respect to informal social support, studies reported a link between cultural attributions and the use of this resource. Negative attributions frequently lead to stigma and shame among parents of children with IDD, which resulted in restricted social support networks,
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and limited ability to rely on the family for support. Again, these restricted informal support networks appear contrary to collectivist values which encourage reliance on family for support. However, these findings tap into another aspect of collectivist cultures which includes individuals’ forbearance of their needs for the good of the group. Some of the studies we reviewed discussed the relationship between beliefs in causes about disabilities and the seeking formal social support by family members. Families who wished to hide that they have a child with a disability often were slow to accept the disability and slow to seek diagnosis and services. However what was most striking about help seeking among families is that in many Asian countries services for people with IDD were extremely limited, costly, and often concentrated in larger cities. These factors greatly thwarted the effort of families to obtain services for their children. Also apparent was that many families made great sacrifices to advocate for and obtain services for their child. Families in both the United Kingdom and United States who were receiving services reported satisfaction with them. However, language and socioeconomic status served as barriers for families wishing to receive services for their child with IDD. In the United Kingdom, Asian families, who were primarily from South Asia, were economically disadvantaged and had greater unmet service needs than White families. The research on adaptation as defined by Lazarus and Folkman of Asian families of children with IDD was extremely limited. Similar to studies of Western families of children with IDD, studies of Asian families found that parents of children with IDD had higher rates of depression, and lower levels of quality of life than other parents. There was emerging evidence that adaptation for Asian immigrant parents was more positive than for Asian parents who resided in their countries or origin. More studies are needed in both Asia and among Asian immigrants on other aspects of adaptation such as social functioning and somatic or physical health and the relationships of other factors in the stress-coping model to adaptation. For example, what is the relationship between environmental context, certain cultural beliefs, and passive coping strategies to well-being outcomes? In conclusion, these studies provide a rich mosaic of the experiences of Asian families caring for a child with an IDD. For service providers who wish to provide culturally competent services to Asian immigrants, understanding distinct cultural beliefs and their underlying philosophies, overcoming language barriers and helping mothers with information about disabilities that is accessible and available to all family members will go a long way. Families and communities in Asian countries would more than likely welcome assistance in knowledge about disabilities and capacity building toward meeting the needs of people with an IDD and their families.
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C H A P T E R
S E V E N
Biomarkers in the Study of Families of Children with Developmental Disabilities Marsha Mailick Seltzer,*,† Leonard Abbeduto,*,‡ Jan S. Greenberg,*,† David Almeida,§ Jinkuk Hong,* and Whitney Witt*,} Contents 1. Introduction 2. Fragile X Syndrome and Related Conditions 2.1. Biochemical alterations and phenotypic correlates 2.2. Stress and well-being of parents of individuals with FXS 2.3. Limitations of the FMR1 biomarkers and measures of psychological well-being 2.4. Summary and directions for future research 3. Cortisol Profiles in Parents of Children with Disabilities 3.1. Stress and cortisol 3.2. Measurement of daily stress and the diurnal rhythm of cortisol 3.3. Study samples: Parents of children with disabilities and comparison group parents 3.4. Daily stress in parents of children with disabilities and the comparison group 3.5. Cortisol in parents of children with disabilities and the comparison group 3.6. Summary and directions for future research 4. Summary and Conclusions: Next Steps in Research on Biomarkers in Families of Individuals with Developmental Disabilities 4.1. Cellular aging 4.2. Allostatic load 4.3. Avenues for future research * { { }
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Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA School of Social Work, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA Department of Human Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA Department of Population Health Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37007-X
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Abstract Research during the past 20 years on families of children with developmental disabilities (DD) has yielded a rich body of knowledge about the risk and protective factors that result in profiles of family resilience versus vulnerability at various stages of the family life course. Virtually all of this research has been based on data collected from self-report or observational measures, and has examined family interactions, family relationships, and the psychosocial wellbeing of individual family members. The present chapter focuses on different sources of data, namely biomarkers, which have the potential to expand our understanding of the biological mechanisms by which the stress of parenting a child with developmental disabilities can take its toll on parents’ physical and mental health. We focus on two examples: (1) variations in the FMR1 gene, FMRP, and FMR1 messenger RNA in mothers of children with fragile X syndrome and the association of these measures with maternal depression and anxiety and (2) profiles of cortisol in mothers of children with disabilities and the association of cortisol with daily measures of caregiving stress. These biomarkers extend past behavioral and psychosocial measures of family adaptations.
1. Introduction The demands of parenting a child with a developmental disability can take a significant toll on the physical, financial, and psychological well-being of the rest of the family (Orsmond, Lin, & Seltzer, 2007; Seltzer, Greenberg, Floyd, & Hong, 2004), although profiles of resilience are frequently noted (Glidden & Schoolcraft, 2003). Selye (1956), the father of modern stress research, distinguished between external demands, or stressors, and the individual’s physiological response to these demands, which he referred to as the stress syndrome. Glidden (1993) expanded on this distinction, particularly as it applies to family research within the field of developmental disabilities. Previous family research investigating the challenges of parenting a child with developmental disabilities has relied largely on self-report indicators of the stress syndrome, such as perceived physical health or perceived level of distress (Abbeduto, Seltzer, Shattuck, Krauss, Orsmond, et al., 2004; Seltzer, Greenberg, Floyd, Pettee, & Hong, 2001). The pathways of influence between parenting stressors and parental physiological functioning remain virtually unexplored among parents of individuals with developmental disabilities. The study of biomarkers thus has the potential to add to our
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understanding of caregiving stress by giving insight into the mechanisms by which caregiving demands takes a toll on health and well-being. According to an NIH study group (Biomarkers Definitions Working Group, 2001), a biomarker is ‘‘a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.’’ Only a few studies on parenting a child with a disability have incorporated biomarkers into the research design. For example, one recent study by Gallagher, Phillips, Drayson, and Carroll (2009) reported that parents of children with developmental disabilities mounted a poor antibody response to pneumococcal vaccination, particularly in the context of high levels of child behavior problems. Another study that incorporated biomarkers was conducted by Epel et al. (2004), who reported that, in parents who have a child with autism or other developmental or chronic disability, longer duration of caregiving was associated with greater telomere shortening (a sign of cellular aging) and elevated oxidative stress, controlling for maternal age. In addition, this study estimated the toll taken by perceived parenting stress, and concluded that cellular aging was accelerated by 9–17 years in the highest stress group, relative to those in the lowest stress group (Epel et al., 2004). These patterns provide strong evidence of the link between the experiences of parents of children with disabilities and their biological functioning. The purpose of the present chapter is to review research on two other types of biomarkers that have been used to investigate associations between parenting stress and parental psychosocial well-being. We first review research on parents of children with fragile X syndrome and examine how variation in their profiles of the FMR1 gene, FMRP levels, and FMR1 messenger RNA are associated with parental levels of depression, anxiety, and other dimensions of psychological well-being. In this example, variation in the biomarker is conceptualized as increasing vulnerability to parenting stress. Next, we examine how daily parenting stress is associated with dysregulation of cortisol, a stress hormone, in parents of children with disabilities. In this example, variation in the biomarker is conceptualized as the consequence of parenting stress. Thus, in this chapter, we aim to review literature on biomarkers as both antecedents to and consequences of the stress that is associated with parenting a child with disabilities. We note that the biomarkers discussed in this chapter are just two examples of a wide range of biomarkers that can be included in family research, and the selection of the particular biomarker in a given study should be guided by an understanding of the biology of the specific disorder (in the case of antecedents) and by hypotheses regarding the physiological impacts of parenting a child with a disability (in the case of consequences).
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2. Fragile X Syndrome and Related Conditions Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability (Crawford, Acuna, & Sherman, 2001) and the single leading known cause of autism (Demark, Feldman, & Holden, 2003). FXS results from a mutation in the 50 -untranslated region of the FMR1 gene located on the X chromosome (Brown, 2002). In the healthy allele, there are approximately 55 or fewer repetitions of the CGG sequence of nucleotides comprising the FMR1 gene (Nolin, Glicksman, Houck, Brown, & Dobkin, 1994). In FXS, there is an expansion to 200 or more repetitions. Importantly, lesser variations in the FMR1 gene are also associated with adverse phenotypic consequences. Individuals who have between 55 and 200 CGG repeats in the gene are said to carry the premutation. The premutation can expand to the full mutation when passed on from mother to child (Nolin et al., 1996). In addition, a sizeable proportion of individuals with the premutation display many of the same behavioral features of individuals with FXS, albeit typically in a less severe form (Bailey, Sideris, Roberts, & Hatton, 2008). The premutation is also associated with elevated risk for two disorders that do not occur in individuals with the FMR1 full mutation: primary ovarian insufficiency (POI), which includes premature menopause, and Fragile X-associated Tremor–Ataxia syndrome (FXTAS), a late-onset neurodegenerative disorder (Cornish, Turk, & Hagerman, 2008). Families that include one or more children who have FXS or even the FMR1 premutation, therefore, are likely to experience elevated levels of stress and non-normative life experiences as a (direct or indirect) result of the characteristics and behaviors of their affected children (Murphy & Abbeduto, 2005). FXS is, therefore, a multigenerational disorder and its effects on families do not emanate only from the affected children, but also from parents and grandparents. In the case of a child with FXS, the child will have inherited the problem gene from his or her mother, who would be a carrier of either the premutation or the full mutation (Nolin et al., 1996). In the case of children with the FMR1 premutation, sons will have inherited the gene from their mothers and daughters from either their mother or father (Nolin et al., 1996) (for more details of the inheritance profile of the FMR1 gene, see Hagerman, 1999). Some parents (and grandparents) of children with an expanded FMR1 allele will thus be affected by many of the same challenges as their children, which may well make them less able to deal with life stressors, including those associated with their child’s condition (Esbensen, Seltzer, & Abbeduto, 2008). Consequently, understanding the functioning of any individual in a family affected by an FMR1 expansion will require examination of his or her own genetic status and experiences within the family.
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To date, the identification of biomarkers of risk in FXS and related conditions has been conceptualized largely in terms of the prediction of trajectories of cognitive, linguistic, and social-affective development in affected individuals. We believe, however, that it is also useful to view those biomarkers as predictors of risk for the family and for individuals trying to meet various family roles, especially the role of parent, which is the focus of the remainder of this section on FXS and related conditions. In addition to reviewing the published literature, we present new data from our own research linking FMR1 biomarkers and parental psychological well-being.
2.1. Biochemical alterations and phenotypic correlates Variation in FMR1 CGG repeat size is a useful biomarker of various types of risk that could affect parents, as it defines differences between ‘‘healthy’’ and ‘‘affected’’ and between full mutation and premutation carriers. At the same time, however, there are a variety of additional ‘‘downstream’’ biochemical processes that may be even better indicators of risk because they not only reflect the effects of the FMR1 expansion, but also the moderating effects of various background genes and environmental events (Belmonte & Bourgeron, 2006). Thus, we now briefly review studies of the measurable biochemical changes associated with variation in the FMR1 gene and the phenotypic correlates of those variations. Although these studies have not focused specifically on individuals who are parents of affected children, they provide a useful context for understanding parental well-being in families with members who carry an FMR1 expansion. We then review the published studies of psychological well-being in parents, with an emphasis on studies that have included FMR1 biomarkers. Throughout our review, we consider both the full mutation and the premutation case. We do so because although premutation carriers are more likely than full mutation carriers to be having children and raising families: (1) individuals with the full mutation are not sterile and (2) studies in which mothers have been recruited through an affected child have found more than 10% of the mothers to be carriers of the FMR1 full mutation (e.g., Bailey, Raspa, Olmsted, & Holiday, 2008). 2.1.1. FMR1 full mutation The full mutation typically leads to hypermethylation and transcriptional silencing so that the FMR1 gene does not produce, or produces at greatly reduced levels, the protein (FMRP) it normally would (Oostra & Willemsen, 2003). FMRP is an RNA-binding protein that regulates translation of biochemical ‘‘messages’’ into proteins at the synapse ( Jin & Warren, 2003) and thus, it is involved in important ways in experience-dependent neural development and functioning (Klintsova & Greenough, 1999). The function of FMRP appears to be largely inhibitory in that it prevents activity
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in various biochemical pathways and thereby ensures that neural activation occurs in a ‘‘controlled’’ manner (Cornish et al., 2008). In a sense, reduced FMRP leads to exaggerated biochemical reactions that adversely affect neural function. It is known, for example, that lowering the level of FMRP leads to activity in the mGluR5 pathway that would otherwise be blocked (Huber, Gallagher, Warren, & Bear, 2002), which then leads to long-term depression (LTD), or reduced responsiveness to stimuli, in the hippocampus and other regions of the brain involved in learning and memory (Bear, Huber, & Warren, 2004). In addition to intellectual disability, the FMRP deficit in FXS leads to a characteristic behavioral phenotype, which includes both neurocognitive and social-affective features. In the neurocognitive domain, the full mutation is associated with especially severe delays or impairments in sequential processing (Burack et al., 1999; Dykens, Hodapp, & Lecman, 1987), working memory (Ornstein, Schaaf, Hooper, Hatton, Mirrett, et al., 2008), and attention (Bailey, Raspa, et al., 2008), particularly inhibitory control and inattentiveness (Cornish, Scerif, & Karmiloff-Smith, 2007). In the socialaffective domain, hyperarousal (Wisbeck, Huffman, Freund, Gunnar, Davis, et al., 2000), hyperactivity (Baumgardner, Reiss, Freund, & Abrams, 1995; Dykens, Hodapp, Ort, & Finucane, 1989; Freund, Reiss, & Abrams, 1993; Mazzocco, Pennington, & Hagerman, 1993), and anxiety (Bailey, Sideris, et al., 2008), particularly social anxiety (Bregman, Leckman, & Ort, 1988; Mazzocco, Baumgardner, Freund, & Reiss, 1998), are frequent in individuals with the full mutation. Autistic-like behaviors are also common in FXS (Bailey, Hatton, & Skinner, 1998; Bailey, Hatton, Skinner, & Mesibov, 2001; Bailey, Mesibov, Hatton, Clark, Roberts, et al., 1998; Feinstein & Reiss, 1998), with 25% to 50% of affected individuals meeting diagnostic criteria for comorbid autism (Bailey, Roberts, Hooper, Mirrett, Roberts, et al., 2004; Brown et al., 1982; Demark et al., 2003; Hatton et al., 2006; Kaufmann et al., 2004; Lewis et al., 2006a; Rogers, Wehner, & Hagerman, 2001; Sabaratnam, Murthy, Wijeratne, Buckingham, & Payne, 2003). Numerous studies have found that variations in both the neurocognitive and social-affective features of the phenotype are correlated with FMRP level among those with the full mutation (e.g., Bailey, Hatton, Skinner, et al., 2001; Bailey, Hatton, Tassone, Skinner, & Taylor, 2001; Cohen, Nolin, Sudhalter, Ding, Dobkin, et al., 1996; Kwon et al., 2001; Loesch, Huggins, Bui, Epstein, Taylor, et al., 2002; Loesch, Huggins, & Hagerman, 2004; Loesch et al., 2005; Menon, Kwon, Eliez, Taylor, & Reiss, 2000), making FMRP level a useful biomarker of risk for individuals with the FMR1 full mutation. In terms of parental well-being, the FMRP level of a parent with the FMR1 full mutation could be viewed as a biomarker of the psychological resources available to deal with stressful experiences and thus, as an indicator of vulnerability or risk for less optimal outcomes.
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The full mutation leads to FXS in about 1 in 4000 males and 1 in 6000– 8000 females (Crawford et al., 2001). On average, males and females have similar phenotypes, although with milder effects in females (Bailey, Raspa, et al., 2008). This sex difference in affectedness is the result of the fact that males have a single X chromosome, whereas females have two. Moreover, the process of X inactivation early in embryological development in females results in the ‘‘turning off’’ of one X chromosome in each cell, which effectively reduces the impact of the FMR1 mutation in females relative to males (Tassone, Hagerman, Chamberlain, & Hagerman, 2000). The relative proportions of active and inactive mutation-carrying X chromosomes contribute to differences in affectedness among females, making the activation ratio another useful biomarker of vulnerability to parenting stress, albeit only for females. 2.1.2. FMR1 premutation There is a complex pattern of alterations in several biochemical processes important for neural development in individuals carrying the FMR1 premutation. In particular, there appears to be a decrease in FMRP levels for some, but not all, individuals who have large premutations (i.e., >100 CGG repeats; Tassone et al., 2000). Perhaps more importantly, Tassone et al. (2000) have found levels of FMR1 messenger RNA (mRNA) that are 2–8 times the levels seen in individuals with the healthy FMR1 allele, with a correlation between mRNA levels and CGG repeat number (Allen, He, Yadav-Shah, & Sherman, 2004). This elevation is thought to lead to RNA toxicity, which in turn has numerous adverse phenotypic consequences (Greco et al., 2006; Hagerman & Hagerman, 2004). Not surprisingly, such substantial alterations in neural development and function are associated with numerous adverse physical and behavioral outcomes, including some not found in FXS (Cornish et al., 2008). Nearly one-fourth of women with the premutation are affected by POI, a condition associated with premature menopause (i.e., before age 40) and decreased fertility (Cronister, Schreiner, Wittenberger, Amiri, Harris, et al., 1991). The condition is also accompanied by increased levels of several hormones and endocrine problems (Welt, Smith, & Taylor, 2004). Interestingly, the risk of POI has been found in a recent study (Sullivan et al., 2005) to be associated with premutation size in a nonlinear manner, increasing with CGG repeat number up to 100 CGG repeats, but declining a bit thereafter. Thus, there is much to be learned about the relationship between POI and the biomarkers discussed thus far. Moreover, although it is reasonable to suppose that the hormonal changes associated with POI as well as the psychological impact of early menopause and decreased fertility could affect psychological well-being and adaptation to the role of parent of a special needs child, this area has yet to be investigated.
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Males and, to a lesser extent, females with the premutation are also at elevated risk during late adulthood for FXTAS (Hagerman & Hagerman, 2004). FXTAS is characterized by intention tremor and ataxia, which become increasingly severe with age (Hagerman, Ono, & Hagerman, 2005). The disorder also has cognitive and social-affective features, including problems in memory and executive function and increased anxiety and disinhibition (Berry-Kravis et al., 2007; Cornish et al., 2008; Grigsby et al., 2006). These physical and psychological challenges will no doubt affect the quality of life of individuals with FXTAS; however, the condition might have other indirect effects on the family. The mother of a young child with FXS, for example, might have to deal with the emotional and financial demands of simultaneously caring for an affected parent and these additional demands may further limit her ability to deal effectively with the needs and challenges of her own child. Unfortunately, empirical tests of this and other possible indirect effects of FXTAS on families have yet to be conducted. Other features of the FMR1 premutation phenotype are similar, but less severe, than are those observed in the full mutation case (Bailey, Raspa, et al., 2008). Males with the premutation have problems (relative to typically developing age-matched peers) in several cognitive domains, including executive function, long-term memory, and social perception (Aziz et al., 2003; Cornish et al., 2008; Hessl et al., 2007; Moore et al., 2004). These males are also at elevated risk for various forms of psychopathology, such as ADHD, anxiety, obsessive–compulsive disorders, and autism (Aziz et al., 2003; Goodlin-Jones, Tassone, Gane, & Hagerman, 2004; Hessl et al., 2005). Females with the premutation, especially those with larger premutations (and thus, lower FMRP and higher FMR1 mRNA levels), are at elevated risk for anxiety, depression, obsessive–compulsive disorder, and features of autism (Goodlin-Jones et al., 2004; Hessl et al., 2005). There is little evidence, however, in support of a cognitive phenotype for premutation females (Allen et al., 2005; Moore et al., 2004; Steyaert, Borghgraef, & Fryns, 2003). Again, it is reasonable to suppose, although this has yet to be investigated empirically, that many of the features of the premutation phenotype we have described can limit a parent’s psychological resources and thereby increase his or her vulnerability to parenting stress. In addition to differences between premutation carriers and individuals with a healthy FMR1 allele, there is considerable variation at both the genetic and behavioral levels among individuals who have the premutation. Moreover, there is strong evidence of correlations between measurable biochemical variables and several important features of the premutation phenotype. FMRP correlates with cognition and brain activation patterns in premutation cases (Loesch et al., 2004; Moore et al., 2004). More recently, FMR1 mRNA levels have been found to correlate with measures of psychopathology in males and females with the premutation (Hessl et al., 2005). CGG repeat size and activation ratio have also been found to
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correlate with depression and other symptoms of psychopathology in females ( Johnston et al., 2001), although recent evidence (described below) suggests that the relationship may be nonlinear. Thus, these variables are likely to be useful indices of potential vulnerability to stress and lower levels of well-being among parents of individuals with an FMR1 expansion.
2.2. Stress and well-being of parents of individuals with FXS Nearly all of the studies on stress and well-being in parents of individuals with FXS or FMR1-related conditions have focused on mothers. These studies have clearly demonstrated that mothers of children, adolescents, and young adults with FXS display high rates of stress and mental health symptoms and lower quality of life as compared with mothers of similarly aged typically developing individuals, although there is considerable interindividual variability in the former group. In one such study, Roberts et al. (2009) estimated the rates of psychopathology in 93 mothers of children who carried the premutation and had children with FXS, and compared them with mothers of unaffected children. The comparison group was selected from the National Comorbidity Survey Replication (NCS-R), which includes more than 9000 respondents 18 years of age and older who were interviewed during 2001 and 2002 (http://www.umich.edu/ ncsum). Structured psychiatric interviews with the mothers of the children with FXS yielded higher rates of lifetime major depressive disorder, lifetime panic disorder (without agoraphobia), and current agoraphobia without panic disorder than age- and gender-matched subset of NCS-R participants. In another study, Head, Chavis, Serafin, Maddocks, and Abbeduto (2008) conducted clinical interviews with 33 mothers of children with FXS and found a lifetime rate of major depressive disorder that was lower than that in the Roberts et al. study, but still in excess of that expected for women in the general population. Head et al. also found, however, that the most frequent diagnosis was lifetime anxiety disorder, which was observed in 70% of the women, which is well in excess of expectations for the general population. Studies using self-report measures of currently experienced (rather than lifetime history of ) mental health symptoms (e.g., the Symptom Checklist-90-R—SCL-90-R), and measuring additional negative facets (e.g., parenting stress) and positive facets (e.g., optimism) of well-being, have also suggested that a relatively high proportion of biological mothers of individuals with FXS have psychological symptoms severe enough to warrant a psychiatric diagnosis or professional intervention (e.g., Bailey, Sideris, et al., 2008). There is also evidence that mothers of individuals with FXS may have more stress and mental health challenges, as a group, than mothers parenting individuals with several other types of developmental disabilities. In a study focused on currently experienced psychological well-being, Abbeduto et al. (2004)
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found that mothers of adolescents and young adults with FXS were more pessimistic about their child’s future and believed that their children felt less close to them compared to mothers of age-matched individuals with Down syndrome. In addition, the mothers of the youth with Down syndrome displayed better functioning than a comparison group of mothers of agematched youth with autism on virtually every measure administered in the Abbeduto et al. study. In contrast, the mothers of the youth with FXS seldom differed from the mothers of the youth with autism. In general, mothers of youth with autism have been found to be among the most stressed of those parenting a son or daughter with developmental disabilities (Esbensen et al., 2008). It should be noted that the FXS sample in the Abbeduto et al. study did not include any son or daughter who met criteria for autistic disorder and thus, a more inclusive sample of mothers would be expected to fare even more poorly on measures of psychological well-being (Lewis et al., 2006b). Thus, it appears that mothers of individuals with FXS, as a group, fall on the upper end of the risk continuum. In addition to documenting the extent of psychological challenges among mothers parenting sons and daughters with FXS, researchers have begun to address the sources of these challenges. In fact, there is now compelling evidence that, in addition to elevated risk conferred by the biomarkers of FXS, maternal psychological distress and well-being can be traced, at least in part, to characteristics of the son or daughter with FXS, most notably the extent of challenging behavior. Indeed, there is evidence that currently manifested symptoms of depression (Abbeduto et al., 2004; Bailey, Sideris, et al., 2008; Orland, Griffith, Abbeduto, Brown, & Dobkin, 2008), anxiety (Orland et al., 2008; Roberts et al., 2009), and parenting stress (Bailey, Raspa, et al., 2008; Johnston et al., 2003) are predicted by concurrently measured child challenging behavior, as are more general measures of maternal well-being, such as optimism and quality of life (Bailey, Sideris, et al., 2008). Although other personal and contextual factors, such as number of affected children, parent education, and income also contribute to the prediction of such measures, child challenging behavior consistently emerges as a strong predictor of currently manifested symptoms of psychological distress for mothers of individuals with FXS (Esbensen et al., 2008), as it does for mothers parenting children with other developmental disabilities. In contrast to the many studies examining child and other environmental contributions to maternal psychological well-being for mothers carrying an FMR1 expansion, few parenting studies have included relevant maternal biomarkers. Moreover, most studies addressing the contribution of maternal genotype to well-being have relied on CGG repeat size as the only biomarker of interest, and with inconsistent results. In one study focused on currently manifested mental health symptoms, Johnston et al. (2001) found a positive correlation between self-reported
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symptoms of depression on the SCL-90-R and CGG repeat number in a sample of mothers carrying the premutation who had children with FXS. In contrast, Bailey, Raspa, et al. (2008) administered a large battery of selfreport measures and conducted clinical interviews to assess the currently experienced levels of well-being of 108 mothers who carried the premutation (n ¼ 95) or full mutation (n ¼ 13) and who had a child with FXS. Bailey did not find any contribution of maternal CGG repeat number to the mothers’ currently experienced levels of maternal well-being. In particular, there was no difference between premutation and full mutation mothers in scores on the well-being measures, and no correlation between maternal CGG repeat number and well-being for the premutation mothers. Abbeduto and colleagues have recently examined the relationship between FMR1 allele size and currently manifested mental health symptoms in a small sample (n ¼ 27) of mothers of adolescents and young adults with FXS. Characteristics of the sample are provided in Table 7.1. All were biological mothers identified through their adolescent or young adult son or daughter with FXS. The sample of mothers was largely White, in their 40s, married, and carried the premutation. The mothers completed the SCL90-R, which yields several t-scores, including for depression and anxiety. Table 7.1 Families of adolescents or young adults with FXS: selected characteristics of mothers, children, and families Characteristic
Maternal Number of CGG repeats Age (in years) IQa Educationb Child Challenging behaviorc Family Incomed Number of children Number of children w/DD % Single parent a b c
d
Mean
SD
Min.
Max.
98.7 45.3 109.4 5.6
24.7 6.6 13.6 1.7
70 33.5 86 3
155 61.7 134 8
9.1
9.6
40
2
7.9 2.3 1.6 22
2.7 1.2 0.6 –
3 1 1 –
11 5 3 –
Based on administration of the Kaufmann Brief Intelligence Test. Based on a rating scale of from 1 (grade 8 or less) to 8 (advanced graduate degree), with a rating of 6 signifying a college graduate. Based on scores from the Problem Behavior Scale of the Scales of Independent Behavior—Revised. Scores derived from administrations to teacher and/or father. Lower scores reflect greater problems with challenging behaviors. Not available for three children. Based on a rating scale of from 1 (annual income $10,000 or less) to 16 (annual income $150,000 or more) in $10,000 increments. Not available for three children. Not available for one family.
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The target child’s father or teacher or both completed the Problem Behavior Scale of the Scales of Independent Behavior—Revised, which assesses behavior problems. It should be noted that these mothers were functioning relatively well according to their SCL-90-R scores, as only eight met the definition of ‘‘caseness’’ (i.e., a t-score of 63 or above, reflecting the likelihood of symptoms severe enough to warrant a diagnosis) for depression and three for anxiety, although other data we collected suggested that many more mothers had dealt with mental health problems at previous points in their lives. Similarly, the mean score of the adolescents and young adults with FXS fell at the edge of the ‘‘normal’’ range on the Problem Behavior Scale, suggesting that, as a group, they too were functioning relatively well. As can be seen in Table 7.2, SCL-90 depression scores were significantly correlated with several maternal characteristics, child challenging behavior, and family characteristics. In contrast, scores for anxiety were correlated with a more narrow set of variables, suggesting the possibility of different causal pathways for depression and anxiety in this population. Most importantly for present purposes, maternal FMR1 allele size (i.e., CGG repeat Table 7.2 Families of adolescents or young adults with FXS: bivariate correlations between maternal mental health measures and selected characteristics of mothers, children, and families Characteristic
Maternal Number of CGG repeats Age (in years) IQa Educationb Child Challenging behaviorc Family Incomed Number of children Number of children w/DD
Depression (SCL-90-R)
Anxiety (SCL-90-R)
0.58**** 0.34* 0.42** 0.42**
0.49*** 0.27 0.41** 0.30
0.35*
0.31
0.41** 0.10 0.03
0.26 0.06 0.00
* p 0.10, ** p 0.05, *** p 0.01, **** p 0.005, with all tests two-tailed. a Based on administration of the Kaufmann Brief Intelligence Test. b Based on a rating scale of from 1 (grade 8 or less) to 8 (advanced graduate degree), with a rating of 6 signifying a college graduate. c Based on scores from the Problem Behavior Scale of the Scales of Independent Behavior—Revised. Scores derived from administrations to teacher and/or father. Lower scores reflect greater problems with challenging behaviors and thus, the negative correlation reflects the fact that higher rates of maternal mental health symptoms are associated with higher rates of child challenging behavior. Not available for three children. d Based on a rating scale of from 1 (annual income $10,000 or less) to 16 (annual income $150,000 or more) in $10,000 increments. Not available for three children. Not available for one family.
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number) was correlated with both maternal depression and anxiety in this sample of mothers, consistent with the notion of a genetic susceptibility to some types of mental health problems in premutation cases. Surprisingly, however, the correlation between allele size and SCL-90-R scores was negative; that is, larger FMR1 expansions in the premutation range were associated with fewer and/or less intense symptoms of depression and anxiety. A negative relationship also emerged when allele size in mothers meeting criteria for caseness was compared against those not meeting caseness criteria, although only for depression, t(1,24.06) ¼ 2.54, p ¼ 0.018, with the former averaging fewer CGG repeats. Abbeduto and colleagues also explored the relationships displayed in Table 7.2 in a series of regression analyses and found that maternal CGG repeat number and child challenging behavior made independent contributions to current symptoms of maternal health as assessed by the SCL-90-R. In a regression that included four predictor variables (maternal CGG repeat number and IQ, child challenging behavior, and family income) and SCL-90-R anxiety scores as the dependent variable, b was 0.51 for maternal repeat number, t ¼ 2.6, p ¼ 0.018, and 0.41, t ¼ 2.3, p ¼ 0.033 for child behavior. In the same analysis for SCL-90-R depression scores, b was 0.57 for maternal repeat number, t ¼ 3.1, p ¼ 0.006, and 0.46, t ¼ 2.7, p ¼ 0.016 for child behavior. Regressions including additional maternal and family variables did not change the results appreciably. Thus, smaller maternal premutations and more serious child challenging behaviors predicted worse current levels of mental health in the mothers. Moreover, the negative relationship between mental health and CGG repeat number was not explained by correlated differences on any of the other variables, although the small sample size precluded an examination of all variables of interest or their interactions. The findings reported by Abbeduto and colleagues are consistent with a model in which the FMR1 premutation is thought to confer increased risk for mental health problems over and above the contribution of child challenging behaviors and other factors ‘‘external to the mother.’’ Nevertheless, the findings regarding premutation size are surprising in that they suggest that it is only the smaller premutations that increase vulnerability to psychological distress. This interpretation must be considered speculative until the biological mechanisms underlying differences in risk and premutation size are more fully understood. Caution is also required because our finding is at odds with those of Johnston et al. (2001) who found a positive correlation between maternal repeat number and currently manifested symptoms of depression. Nevertheless, it is important to note that Roberts et al. (2009) also found a negative correlation between lifetime mental health problems and repeat number in their larger sample of biological mothers of children with FXS, suggesting that our findings did not emerge because of some unidentified idiosyncratic feature of
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our sample. Roberts et al. suggested that the larger FMR1 premutations might serve a protective function. Ultimately, understanding the pathways from maternal genetic status to mental health outcomes will require that researchers move beyond CGG repeat number and instead rely on biomarkers that capture more ‘‘downstream’’ biochemical processes (e.g., FMRP and mRNA levels), reflecting the influence of other background genes and environmental events as well as the FMR1 mutation. Moreover, it is likely that the use of a combination of several biomarkers may well be most informative, as each reflects somewhat different biochemical processes and thus, each may make a unique contribution to maternal mental health. This possibility is illustrated in a recent study by Hessl et al. (2005), who found a positive correlation between FMR1 mRNA levels and self-reported current symptoms of anxiety (measured by the SCL-90-R) for a sample of women with the premutation (largely mothers of children with FXS); however, this correlation emerged only for women who had activation ratios reflecting a higher proportion of active X chromosomes containing the premutation (rather than the healthy allele). Such findings serve as a reminder of the complexity of development, even in the case of a single-gene disorder (Belmonte & Bourgeron, 2006) and thus, of the need to create a comprehensive battery of well-characterized and understood biomarkers when attempting to evaluate risk. It is important, as well, to reiterate that other factors, such as child challenging behavior, also contribute to maternal mental health. Indeed, contextual factors, such as number of affected children in the family and family income, as well as maternal characteristics, such as education, have been found to contribute to psychological well-being (Abbeduto et al., 2004). Moreover, other genes make independent contributions to mental health and may well interact with the FMR1 gene to affect risk. Thus, maternal FMR1 status is only part of the picture needed to understand an individual’s risk for mental health challenges or the most effective path to prevention or treatment. In concluding this section, it is interesting to consider a study by Franke et al. (1998), which demonstrates a particularly creative approach to investigating the role of biological variables in the psychological distress and wellbeing of mothers of individuals with FXS. These investigators included mothers who themselves carried the FMR1 premutation and relied on diagnostic interviews and observation to determine whether they met criteria for various psychiatric disorders. Franke et al. also included several control groups of women (e.g., mothers of children with autism, premutation women without affected children) in an attempt to parse out the contributions of maternal genetic status, parenting per se, and parenting a child with FXS. In general, the women who carried the premutation and who had children with FXS were found to be at greatest risk for several psychiatric
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conditions. They were the most likely to be diagnosed with an anxiety disorder or a major depressive episode, and they were more likely to be so diagnosed than were women who had the premutation, but had no affected children. Again, such findings suggest that, although the biochemical alterations associated with the FMR1 expansion do increase the risk of mental health challenges, there are many other factors that contribute, including, of course, those associated with parenting a son or daughter with FXS.
2.3. Limitations of the FMR1 biomarkers and measures of psychological well-being It is important to acknowledge that although significant correlations between the FMR1-related biomarkers and measures of neurocognitive and social-affective functioning and mental health problems have been found in numerous studies, the magnitude of the correlations generally suggests that these biomarkers are accounting for only a rather small proportion of phenotypic variance. These modest correlations may reflect the fact that the biomarkers are calculated only from peripheral blood rather than from neural tissue, which obviously cannot be sampled except under ‘‘unusual’’ circumstances, such as from postmortem tissue under autopsy. Although estimates of FMRP and other FMR1 biomarkers from lymphocytes can be assumed to be virtually identical to their distribution in brain for males with the full mutation, they can provide only approximations for females and mosaic males (Brown, 2002). In studies of mothers of affected children, then, the biomarkers contain considerable error, a problem that is compounded by the small numbers of participants in most studies. It is likely, therefore, that the current set of biomarkers available in human studies will seriously underestimate the contribution of genetic variation in stress and well-being among parents of individuals with FXS and related conditions. Throughout this section, we have noted considerable variation in the ways in which psychological well-being has been measured, and these variations in measurement strategy may have important consequences for understanding the ways in which FMR1 biomarkers confer risk. Importantly, some investigators measure whether a participant has met criteria for a clinical diagnosis at some point during his or her life whereas other investigators use current symptoms of a clinical condition that are nonetheless below the threshold for receipt of a clinical diagnosis. It is possible, for example, that for individuals who are prone to depression, anxiety, or other conditions, carrying an FMR1 expansion functions as an additional ‘‘hit,’’ pushing them from subthreshold levels to clinical levels of mental health concerns. In this case, the most sensitive measure of the role of the biomarker would be lifetime history of psychiatric diagnosis rather than an index of current symptom severity. Unfortunately, there are not yet a
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sufficient number of studies and there are too many inconsistencies in results across studies, including those employing the same measurement strategy, to discern a clear pattern between these two types of measurement strategies. Substantially more research on this issue is needed.
2.4. Summary and directions for future research There is considerable evidence from decades of research that the biomarkers we have considered are broadly predictive of ‘‘affectedness’’ in individuals with an FMR1 expansion. Those with a full mutation typically display a characteristic phenotype that includes high rates of intellectual disabilities and social-affective problems, including anxiety and autism. Individuals who carry the premutation are at risk for milder cognitive and socialaffective symptoms, but also for conditions, such as POI and FXTAS, that do not occur in the full mutation case. The biomarkers we have considered also appear to be predictive of psychological well-being in women who carry the premutation and are raising sons and daughters with FXS, although the relations among the biomarkers and psychological symptoms are complex and inconsistent across studies. In the case of these mothers, it appears that they have poorer mental health outcomes, as a group, because of a genetic vulnerability to mental health problems and are less well equipped to deal with the stresses of life, including those that arise (directly and indirectly) from parenting a child with challenging behavior. Knowing that the FMR1 expansion produces a vulnerability to psychological stress in mothers, however, is only the beginning of an explanation. Additional research is needed to determine more fully the causal pathways and mediators involved in producing mental health outcomes for these mothers. There is a need for research at multiple levels of analysis, from that focusing on biochemical processes at the synapse and the structural and functional integrity of neural systems, to that focused on the ways in which the psychological and biological characteristics of a woman who carries the problematic allele affects her reactions to stress at various points in development both before and after the birth of her affected child, as well as the ways in which those reactions are tempered by the broader context in which she lives. There is also a need for more research on mothers who carry the full mutation. Most studies focused on maternal well-being have generally included only women with the premutation or have included so few women with the full mutations that drawing conclusions has been difficult. From a clinical perspective, it is important to understand the mental health challenges and needs of women across the full range of FMR1 expansions, especially as one might suppose that full mutation carriers may be even more vulnerable to the stresses of parenting an affected child. From a basic science perspective, there is still much we do not know how about how the various
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biomarkers considered here map onto phenotypic outcomes and the ways in which these biomarkers operate similarly and differently across full mutation and premutation cases. Research is also needed on other members of the family and the ways in which the FMR1 biomarkers can help us understand family risk more broadly. How do fathers who carry the FMR1 premutation deal with parenting stress? Do they display the same vulnerabilities as mothers? What of siblings who carry the premutation? Are they less able to deal with challenges within the family relative to siblings who carry the healthy allele? As we address these questions and continue to learn more about the pathways from gene to behavior in FXS we may be able to move beyond conceptions of risk for individuals and toward conceptions of risk for families that take into account the genetic and psychological vulnerabilities of all family members and the dynamic relationships among them. Finally, it is important to acknowledge that establishing biomarkers of risk in families affected by FXS and its associated disorders does not provide a direct path to intervention. Although such biomarkers can be useful indicators of who is likely to be most in need of interventions or preventive supports, there remains considerable work to be done in specifying the nature of those interventions and supports. No doubt, psychoeducational therapeutic programs and psychopharmacological agents used to treat depression and anxiety disorders should be evaluated in individuals with FMR1 expansions. In addition, a variety of promising pharmaceuticals that target neural pathways that are specifically impaired in FXS are beginning to be tested and hold promise (Hagerman et al., 2009). Nevertheless, the path from identification of biomarkers of risk in carriers of FMR1 expansions to treatment is likely to involve many steps and considerable scientific effort.
3. Cortisol Profiles in Parents of Children with Disabilities Whereas the biomarkers of FXS and the premutation appear to increase the vulnerability of parents to poor mental health outcomes and to reduced ability to deal with caregiving stress, other biomarkers are useful indicators of the consequences of parenting children with disabilities. One such biomarker that has been shown to be a sensitive measure of the effects of life stressors is cortisol, which is produced in the adrenal cortex and is an indicator of the activity of the hypothalamic–pituitary–adrenocortical (HPA) axis. A large body of research has demonstrated that disruption of the HPA axis is associated with physical and mental health problems (Gunnar & Vasquez, 2001), suggesting its widespread physiological effects. Cortisol plays a vital role in linking stress exposure to health problems
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(McEwen, 1998). However, prior to our own research (Seltzer et al., 2009), this pathway had not been examined in parents of children with disabilities. Therefore, in this section of the chapter, we review the literature on cortisol and stressful life circumstances, drawing from studies of other subgroups of the population, and then we present data from our program of research, which has examined cortisol in parents of children with disabilities.
3.1. Stress and cortisol Cortisol normally peaks shortly after waking in the morning and then gradually declines throughout the rest of the day. Diurnal cortisol (i.e., the pattern of cortisol expressed throughout the day) provides a window into individuals’ chronobiology (Keenan, Licinio, & Veldhuis, 2001). The early morning and evening levels of cortisol reflect daily engagement and disengagement, respectively, of the brain with peripheral physiology, and hence with the external environment. Failure to activate the HPA axis in the morning may indicate difficulty in responding to the ordinary challenges that are faced every day. Failure to deactivate the HPA axis in the evening may indicate difficulty in disengaging from external demands, leading to inhibition of restoration and recovery processes associated with sleep (Sapolsky, Krey, & McEwen, 1986). (Note that the phrases ‘‘failure to activate’’ and ‘‘failure to deactivate’’ do not imply that cortisol is under the intentional control of the individual; rather, these phrases reflect physiological processes.) Short-term increases in cortisol are thought to reflect a ‘‘normal’’ physiological response to exposure to a stressor (Sapolsky et al., 1986). However, individual differences as well as variation in the nature of stressors may influence the magnitude of such responses, leading to exaggerated (hyper) or diminished (hypo) responsiveness. The impact of variation in cortisol reactivity is thought to accumulate over time in response to repeated or chronic stressor exposure, thereby leading to persistently high or low levels of circulating cortisol (which in turn can influence multiple aspects of physiological functioning). Both hyper- and hyporesponsive cortisol reactivity are symptomatic of poor physical health, generally interpreted as wear and tear on the HPA axis (Kiecolt-Glaser et al., 1986; Segerstrom & Miller, 2004). The measurement of daily cortisol rhythms provides a useful window into stress physiology, yielding information about overall levels and fluctuations in cortisol levels across the day, and the association of these characteristics of cortisol with exposure to stressful experiences. Daily stressors have been shown to be important predictors of individual and family functioning (Crnic & Greenberg, 1990; DeLongis, Folkman, & Lazarus, 1988). Studying cortisol in parents of children with disabilities offers a new opportunity to examine how daily life experiences influence
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daily physiology and are significantly associated with indicators of health and well-being. Research has shown that individuals who experience acute stressors display elevations in cortisol levels at waking and 30 min after waking as compared to individuals who do not experience acute stress (Dickerson & Kemeny, 2004). For example, Kirschbaum, Pirke, and Hellhammer (1993) demonstrated that when research participants were given a stressful laboratory task such as having to give a speech or perform mental arithmetic, this led to a two- to fourfold elevation in cortisol levels above their baseline level. However, a different pattern of cortisol is evident in the context of chronic life stressors. Although exposure to acute stressors leads to elevations in cortisol, hypoactivity of the HPA axis has been documented in the face of chronic stressors, such as unemployment, bereavement, environmental disasters, chronic fatigue syndrome, fibromyalgia, PTSD, and parenting children with cancer (Baum, Schaeffer, & Lake, 1985; Demitrack et al., 1991; Griep, Boersma, & de Kloet, 1993; Jacobs, Mason, Kosten, Kasl, Ostfeld, et al., 1987; Meewisse, Reitsma, De Vries, Gersons, & Olff, 2007; Miller, Chen, & Zhou, 2007; Ockenfels, Porter, Smyth, Kirschbaum, Hellhammer, et al., 1995; Scott & Dinan, 1998). Pruessner, Hellhammer, and Kirschbaum (1999) found that teachers scoring high on burnout showed lower overall cortisol secretion relative to peers who are low on burnout. Adam and Gunnar (2001) found that mothers who worked more hours and had more children at home had lower morning cortisol values and a less pronounced decline in cortisol levels across the day than mothers working fewer hours and having fewer children. Similarly, in a study of parents of children with cancer, Miller, Cohen, and Ritchey (2002) found that these parents had lower levels of cortisol secretion 1-h postawakening than parents of healthy children, and showed a flatter diurnal decline in cortisol. In a meta-analysis of 37 studies of 828 people with PTSD and 800 controls, Meewisse et al. (2007) found that individuals with PTSD had significantly lower levels of cortisol than controls who had not been exposed to trauma. Thus, cortisol shows a different pattern with chronic than acute stressful life events: Acute stressful life events are associated with sharper elevations in the morning rise of cortisol, whereas chronic stressful life circumstances are associated with a flatter pattern of low levels of cortisol throughout the day, that is, a lower morning rise and a less pronounced decline at the end of the day. Apart from our program of research (described in the next section), no previous study has extended the investigation of cortisol dysregulation to parents dealing with the demands of caring for a child with disabilities. However, based on past research on other populations experiencing chronically stressful life circumstances, we hypothesized that parents of children with disabilities would exhibit patterns of hypoactivation of cortisol.
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3.2. Measurement of daily stress and the diurnal rhythm of cortisol Our research protocol for the measurement of daily caregiving challenges and salivary cortisol is based on the methods developed by Almeida, Wethington, and Kessler (2002) for the National Study of Daily Experiences (NSDE), one of the projects that comprise the National Survey of Midlife in the United States (MIDUS; Carol Ryff, PI). MIDUS is a national probability sample of English-speaking, noninstitutionalized adults who were aged 25–74 in 1994 (MIDUS I; Brim, Ryff, & Kessler, 2004). Follow-up data were collected from 2003 to 2005 (MIDUS II; n ¼ 4032). A subset of MIDUS II sample members was also included in the National Study of Daily Experiences (NSDE; David Almeida, PI), which is the source of data for the daily diary study analyses we present in this chapter. The NSDE consists of 15–25-min telephone interviews at the end of each of 8 consecutive days. The NSDE daily telephone interview includes questions about daily experiences in the past 24 h concerning the number of stressors and positive events, and daily measures of positive and negative affect (Almeida et al., 2002). As part of the NSDE, salivary cortisol samples are collected 16 times (i.e., four times each day on days 2–5 of the 8-day study). Respondents receive a Home Saliva Collection Kit 1 week prior to their initial phone call. Sixteen numbered and color-coded ‘‘salivettes’’ are included in the collection kit, each containing a small absorbent wad, about 3/4 of an inch long, as well a detailed instruction sheet. In addition to written instructions, telephone interviewers review the collection procedures and answer any questions. The four saliva samples collected each day are scheduled to provide data about the characteristic diurnal rhythm of cortisol: one upon wakening, one 30 min after getting out of bed, one before lunch, and one at bed time. Data on the exact time respondents provided each saliva sample are obtained from the nightly telephone interviews and on a paper–pencil log sent with the collection kit. In addition, approximately 25% of the respondents received a ‘‘smart box’’ to store their salivettes. These boxes contain a computer chip that recorded the time respondents opened and closed the box. The correlations between self-reported times and the times obtained from the ‘‘smart box’’ ranged from 0.75 for the evening occasion to 0.95 for the morning, substantiating the reliability of the self-reported times of saliva collection. Measures of salivary cortisol derived from the samples include the absolute values at each of the four collection times (upon awakening, 30 min later, before lunch, before bedtime), as well as two parameters of diurnal rhythm: morning rise and daily decline. Morning rise is an indicator of how high an individual’s cortisol rises, measured from awakening to 30 min after awakening. Daily decline refers to the slope from the typically
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highest point in the day, measured at 30 min after awakening, through the collection before bed.
3.3. Study samples: Parents of children with disabilities and comparison group parents All parents in the MIDUS study were asked if any of their children had a developmental or a mental health problem, and if so, which child had the condition and the name of the particular diagnosis the child had received. Approximately one in ten (10.5%) MIDUS participants responded affirmatively, of whom nearly half (46.3%) had a child with a developmental problem, about the same number (42.7%) had a child with a mental health problem, and the remaining 11% had a child with another type of neurological disability. A subsample of the MIDUS II participants who also participated in the NSDE (n ¼ 806 at the time of the present analysis) had a child with a developmental or mental health problem (n ¼ 82). About half (47.6%) had developmental disorders and the others (52.4%) had mental health diagnoses. Among the developmental disorders were intellectual disability, cerebral palsy, Down syndrome, hydrocephalus, muscular dystrophy, pervasive developmental disorders, specific genetic disorders (e.g., cri du chat syndrome), ADHD, seizure disorders, traumatic brain injury, etc. Among the mental health diagnoses were schizophrenia, bipolar disorder, depression, anxiety disorders, eating disorders, alcohol and drug abuse, etc. Thus, the present sample was characterized by a heterogeneous set of disabilities. We selected as a comparison group a sample of NSDE respondents who had at least one living child, but no child with a disability or chronic health condition, and who never provided care to a family member. For this comparison group, we selected the 82 individuals most similar to the parents of children with a disability with respect to parent gender, parent age, number of children in the household, child age, whether the target child lives with the parent, parent marital status, and parent educational attainment (see Seltzer et al., 2009 for details of the methods and findings). Table 7.3 portrays the characteristics of the sample of parents of children with disabilities and the comparison group, and shows that the two groups were very similar. As shown in Table 7.3, the sons and daughters in both groups were nearly 30 years of age and their parents were in their late 50s, on average. Most of the parents were mothers (almost 60%), and nearly all were nonHispanic whites. The two groups were similar with respect to marital status (about 80% were married) and employment status (about 60% were employed), and both groups averaged about 2 years of education beyond high school. The one variable on which the two groups differed was the percentage who had children still living at home, with the comparison
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Table 7.3 Parents of children with disabilities: descriptive statistics (mean with standard deviation in parenthesis) of parents of children with disabilities (n ¼ 82) and comparison group parents (n ¼ 82)
Variables
Parent’s characteristics Age Gender (1 ¼ female/0 ¼ male) Race (1 ¼ non-Hispanic white/ 0 ¼ others) Marital status (1 ¼ married/ 0 ¼ not married) Employment status (1 ¼ employed/0 ¼ not employed) Years of education Total household income Number of children Child’s characteristics Age Gender (1 ¼ female/0 ¼ male) Living with parents (1 ¼ yes/0 ¼ no)
Parents of children with disabilities
Comparison group
57.4 (13.0) 0.59 (0.50) 0.96 (0.19)
57.4 (13.1) 0.59 (0.50) 0.97 (0.16)
0.79 (0.41)
0.84 (0.37)
0.57 (0.50)
0.61 (0.49)
14.4 (2.65) $74,400 (49,800) 3.29 (1.91)
14.5 (2.35) $78,300 (50,100) 3.21 (1.26)
29.3 (13.4) 0.40 (0.49) 0.41 (0.50)
29.9 (13.4) 0.40 (0.49) 0.32 (0.47)
group less likely to have coresident children than the group of parents of individuals with disabilities (32% vs 41%), which is to be expected given the ability differences between the two groups of children.
3.4. Daily stress in parents of children with disabilities and the comparison group As described in Seltzer et al. (2009), this sample of parents of children with disabilities diverged considerably in daily experiences from parents in the comparison group, despite demographic similarity. As shown in Table 7.4, parents of children with disabilities reported a significantly higher number of days during the daily diary study when they had arguments and a higher number of days when they experienced tense moments but avoided arguments, relative to the comparison group. The former also reported experiencing a greater number of stressors each day, a greater number of days when they experienced at least one stressor, a greater severity of stressors, and a greater number of stressors that occurred at home, than the comparison group. The parents of children with disabilities also reported
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Table 7.4 Parents of children with disabilities: mean comparisons between parents of children with disabilities (n ¼ 82) and comparison group parents (n ¼ 82) on type and severity of stressors, mood, and symptoms
Variables
Stressors Argumentsa Avoided argumentsa Number of stressors/day (mean) Days with any stressors (%) Work stressorsa Home stressorsa Network stressorsa,b Severity of stressors (mean)c Positive events Number of positive events/day (mean) Days with any positive event (%) Affect Negative affectd Positive affecte þ a b c d e
Parents of children with disabilities
Comparison group
Mean
SD
Mean
SD
t-test
0.13 0.18 0.74
0.15 0.17 0.64
0.08 0.13 0.52
0.12 0.13 0.42
2.36* 2.21* 2.60**
0.50 0.07 0.13 0.02 2.51
0.26 0.10 0.14 0.07 1.32
0.40 0.08 0.09 0.01 2.09
0.25 0.14 0.11 0.03 1.00
2.49** 0.57 2.30* 1.28 2.27*
1.09
0.66
1.04
0.63
0.49
0.69
0.28
0.69
0.26
0.13
0.20 2.57
0.18 0.73
0.14 2.78
0.15 0.66
2.17* 1.88þ
p ¼ 0.06, * p < 0.05, ** p < 0.01. Reflects the percent of days in the daily diary study when the type of stress was reported. Defined as stress in the lives of individuals in the respondent’s social support network. Severity was rated from ‘‘not at all stressful’’ to ‘‘very stressful.’’ The negative affect scale (10 items) measured anxiety, hostility, and depression on a five-point scale from ‘‘none of the time’’ to ‘‘all of the time.’’ The positive affect scale (10 items) measured enthusiasm, alertness, and vitality. The rating scale was the same as for negative affect.
significantly elevated levels of negative affect, reflecting more anxiety and depression on a daily basis, than the comparison group, and a marginally lower level of positive affect. However, the parents of children with disabilities did not differ from the comparison group in all respects; they were not different in the number of days when they experienced a stressor at work or when members of their social support network experienced stress, and they reported an equal number of positive events per day and days with a positive event during the 8-day diary study.
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Thus, parents of children with disabilities had daily lives that were similar to the norm in their experience of positive events, stressors at work, and stress experienced by members of their social support network. However, their lives were characterized by elevated levels of negative affect, stressors at home, arguments, tense moments, and several other measures of stressful life circumstances that were assessed during the 8-day diary study. We next asked whether there is a ‘‘biological signature’’ of this level of daily stress, namely whether parents of children with disabilities differed from the comparison group in their level and pattern of cortisol.
3.5. Cortisol in parents of children with disabilities and the comparison group Using multilevel modeling, we examined group differences in the diurnal rhythm of cortisol. We found that parents of children with disabilities and comparison parents did not differ significantly in the slope of the morning rise, but parents of children with disabilities exhibited significantly less pronounced daily decline slopes (see Fig. 7.1; the full results of the multilevel models are available in Seltzer et al., 2009). This pattern indicates that parents of children with disabilities are significantly less likely to deactivate the HPA axis at the end of the day than their counterparts in the comparison group, suggesting inhibition of restoration and recovery processes for parents of children with disabilities. This pattern remained significant even after controlling for the residential status of the child. We also examined whether the amount of time parents spent with their children on a given day predicted variation in diurnal pattern of cortisol and other indicators of daily psychological well-being. Specifically, we investigated if there were within-person associations between time spent with children, on the one hand, and negative affect and the cortisol measures, on the other, and compared parents of children with disabilities and unaffected parents. For this analysis, we focused only on the coresident subgroup to ensure a closer association between daily contact with children and parental psychological and biological response. We found that there was a significant interaction between parental status (having a child with a disability vs having unaffected children) and time spent with coresident children, with respect to parental well-being outcomes and cortisol (see Seltzer et al., 2009 for the data). On days when they spent more time with their children, parents of children with disabilities reported significantly higher levels of negative affect compared to days when they spent less time with their children, whereas parents in the comparison group did not evidence a difference in negative affect based on the amount of time they spent with their children. In addition, parents of children with disabilities had a less pronounced daily decline of cortisol on days when they spent more time with their children as compared to days
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25 Parents of children with disabilities 20
Comparison group parents
15
10
5
0 6am 7am 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm 9pm 10pm 11pm 12am
Figure 7.1 Diurnal rhythm of cortisol in parents of children with disabilities and comparison group parents.
they spent less time, whereas the opposite pattern was evident for the parents in the comparison group. These findings suggest that parents of children with disabilities were less likely to deactivate the HPA axis during days when they spent more time with their children than on days when they spent less time with their children. Based on these analyses, we have tentatively concluded that there indeed is a biological signature of parenting a child with disabilities. Such parents experience elevated levels of stress and are less likely to show the characteristic daily decline pattern of cortisol, particularly on days when they spend more time with their coresident children. These findings suggest that, at the end of the day, the brain is less likely to be disengaged from peripheral physiology in parents of children with disabilities than in parents whose children do not have disabilities. However, in this analysis, parents of children with disabilities did not differ from the norm in the slope of their morning rise of cortisol, suggesting that they ‘‘gear up’’ for the day’s challenges as well as their peers who do not have children with disabilities. This pattern of normative daily rise but flatter daily decline is only partially characteristic of a classic chronic stress response. One explanation for this partial chronic stress response concerns the heterogeneity of the diagnoses represented in the sample. Some of the diagnoses are chronic and long-lasting, while others are more transitory. Furthermore, some of the diagnoses reflect developmental problems,
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whereas others reflect mental health problems. The heterogeneity in child diagnosis encompasses diverse behavioral phenotypes, which likely have diverse effects on parents’ daily lives and biological responses. The heterogeneity of the sample with respect to the types of child disabilities is one important limitation of the present study. The fact that the sample was drawn from a nationally representative study is one of its most important strengths.
3.6. Summary and directions for future research Thus far, our research incorporating the biomarker of cortisol into studies of parents of children with disabilities has revealed two preliminary conclusions. First, parenting a child with a disability leaves a biological signature and cortisol is one biomarker that detects this signature. Specifically, we observed differences between parents of children with disabilities and parents of unaffected children in one important aspect of their physiological response, namely deactivation of the HPA axis at the end of the day. Parents of children with disabilities were significantly less likely to deactivate their HPA axis at the end of the day than unaffected parents, and this was particularly the case on days when they spent more time with their children. These findings may suggest a pileup of stress during the day. It is also possible that these findings suggest an adaptive response to long-term exposure to stressors. Future longitudinal research that explores the relationship between the pattern of cortisol evident in this analysis and the health of mothers of individuals with disabilities will be useful in elucidating possible adaptive effects. Second, we believe that it will be profitable to disaggregate samples of parents of children with disabilities according to the specific diagnosis of their child. We are currently applying this same daily diary and cortisol collection methodology in studies focusing on distinct groups defined by the specific developmental disability of their child—autism, fragile X syndrome, and Down syndrome. Past research (e.g., Abbeduto et al., 2004; Dykens, Hodapp, & Finucane, 2000; Ly & Hodapp, 2002) has shown that these three groups of mothers differ in their level of self-reported parenting stress, with mothers of individuals with autism reporting the highest level of parenting stress, mothers of individuals with Down syndrome reporting the lowest levels of parenting stress, and mothers of individuals with FXS close to the level experienced by those whose child has autism. By extending this line of comparative self-report research to include the biomarker of cortisol, we will be able to determine the extent to which self-reported differences in stress correlate with the biological data. These studies are currently ongoing. Within the sample of mothers of individuals with FXS, we will be particularly interested to separate those whose son or daughter has a comorbid autism diagnosis from those
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who have FXS only, and to determine whether the biomarkers of fragile X alter the pattern of maternal stress reactivity as evidenced in their cortisol patterns.
4. Summary and Conclusions: Next Steps in Research on Biomarkers in Families of Individuals with Developmental Disabilities In this chapter, we have highlighted only a small subset of the potential array of biomarkers that might prove to be fruitful in the investigation of the biopsychosocial impact of parenting children with developmental disabilities. Therefore, one important agenda for future research is to expand the range of biomarkers incorporated in family research in the field of developmental disabilities. Past research on other populations points the way toward biomarkers that would potentially be profitable in advancing developmental disabilities family research. For example, cellular aging and allostatic load are both promising biomarkers that are receiving increasing attention in research. Such biomarkers can increase our understanding of the mechanisms by which exposure to stressors takes a psychosocial and biological toll to ultimately impact health. These biomarkers may help to identify family members at increased risk for morbidity and mortality, as well as those who evidence profiles of resilience.
4.1. Cellular aging Telomere length is a promising measure of cellular aging. Specifically, telomeres are the distal structures of chromosomes. They serve to protect chromosome ends from damage during replication, but shorten with each cell division. Telomere attrition has therefore been proposed as a biomarker of cellular aging (Bekaert, De Meyer, & Van Oostveldt, 2005; Harley, Vaziri, Counter, & Allsopp, 1992) because telomeres shorten naturally with each cell division and, when exhausted, are associated with cell death (Hayflick, 1965). Moreover, cells subjected to oxidative stress in vitro show an accelerated rate of telomere attrition (Serra, Grune, Sitte, Saretzki, & Von Zglinicki, 2000; von Zglinicki, Saretzki, Docke, & Lotze, 1995), suggesting that oxidative stress, such as that associated with depression (Forlenza & Miller, 2006; Irie, Asami, Ikeda, & Kasai, 2003) and perceived stress (Irie, Asami, Nagata, Miyata, & Kasai, 2001) may hasten human aging at the cellular level through accelerated telomere attrition (Epel et al., 2004). One implication of this process is that biological, or cellular, aging may proceed at a dramatically different pace in different individuals with similar chronological ages, and this may be a function of stressor exposure.
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The utility of telomere length as a biomarker has been established through studies demonstrating correlations between reduced telomere length and aging-related illnesses, including cardiovascular ailments (Nakashima, Ozono, Suyama, Sueda, Kambe, et al., 2004), metabolic dysfunctions (Demissie et al., 2006; Gardner et al., 2005; Valdes et al., 2005), cancer (Broberg, Bjork, Paulsson, Hoglund, & Albin, 2005), and dementia (Panossian et al., 2003; von Zglinicki et al., 2000). Short telomeres have also been linked to significantly higher mortality rates from infectious disease and heart disease (Cawthon, Smith, O’Brien, Sivatchenko, & Kerber, 2003). Epel et al. (2004) were the first to show that telomere length is inversely correlated with the duration of parenting a child with developmental disabilities. Much research remains to be conducted. There is substantial individual variability in response to stressful life events, likely related to individual differences in stress appraisal and biological reactivity (Biondi & Picardi, 1999). Therefore, there is a need to understand both cellular aging and the self-perceived impact of stress among parental caregivers of children with developmental disabilities.
4.2. Allostatic load A different approach to examining the physiology of stress is via a composite index, referred to as allostatic load. It is operationalized by biomarkers of cardiovascular, immune, and HPA axis dysfunction, with higher allostatic load indicating greater dysfunction (Singer & Ryff, 2001). Conceptually, allostatic load reflects the impact of psychosocial experience, including stress, on health, and has been shown to result in adverse health outcomes over the life course (McEwen, 1998, 2000; Singer & Ryff, 2001). Higher exposure to stress has been shown to result in poorer cardiovascular functioning, poorer immune response, and a more dysregulated HPA axis (Singer & Ryff, 2001). Higher levels of allostatic load are, in turn, associated with declines in physical and cognitive functioning (Seeman, Singer, Rowe, Horwitz, & McEwen, 1997) and an increased risk of mortality (Seeman, McEwen, Rowe, & Singer, 2001). Although, on average, elevated levels of stress are associated with higher levels of allostatic load, there is great diversity in individual response to stress, including presumably in response to the challenge of parenting a child with a developmental disability. Composite measures of allostatic load have not yet been incorporated in studies of parents of children with developmental disabilities, although several first steps have been taken with components of allostatic load, including cortisol (reflective of HPA function; Seltzer et al., 2009) and antibody response to pneumococcal vaccination (reflective of immune function; Gallagher et al., 2009). Finally, by incorporating measures such as allostatic load into research on parenting children with disabilities, and investigating individual differences,
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it may also be possible to discover pathways to resiliency in such parents by identifying the characteristics of families whose allostatic load scores are normative.
4.3. Avenues for future research Future research should prioritize longitudinal studies that have the potential to clarify the long-term impact of childhood developmental disability, and variations in parental risk, on parents’ health across the life course. Virtually all studies on parents of children with developmental disabilities have examined only concurrent relationships between biomarkers and psychological outcomes. As a result, we do not know which factors move an individual from having a biological vulnerability to actually having an anxiety disorder, depression, or other adverse mental health outcome. Knowledge of such ‘‘triggering’’ factors will be critical for preventing adverse outcomes in parents of children with disabilities. It is likely that these factors will include both parental background genes and exposure to various stressors over the life course. In addition, studies will need to employ interdisciplinary methodologies that allow for the examination of dynamic and complex effects of caregiving on the family. Current methods often do not account for the direct, indirect, and interactive effects of childhood developmental disability on the family. Future research should provide a critical link between subjective measures of parenting stress and objective measures of parents’ physiological response in order to improve understanding of both disease risk among parent caregivers and the implications of parental psychobiology for the quality of life of children with developmental disabilities. Furthermore, quantitative studies—which examine the complex interrelationships between the physiological, behavioral, and social factors that contribute to caregiver vulnerability and resiliency, as well as qualitative studies, which examine the ‘‘lived experience’’ of parents of children with developmental disabilities—will be essential to develop interventions to improve the well-being of such families. Finally, allostatic load, cortisol, and other biomarkers that serve as indices of the effects of caregiving demands on parents have the potential to be useful in evaluating the effects of various psychosocial and pharmacological treatments. In fact, these biomarkers may be especially sensitive indicators of treatment effectiveness as they reflect changes in adaptation to stressors that may precede changes in measurable psychological and behavioral outcomes. Although the inclusion of biomarkers in family interventions may not be immediately on the horizon, successful interventions that enable parents to better cope with stress may be enhanced by the inclusion of biomarkers, with better coping hopefully leading to altered physiological reactions to stress, and ultimately to reduction in mental and physical health symptoms.
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ACKNOWLEDGMENTS This research was supported by grants from the National Institute of Child Health and Human Development (R01HD024356 and R03HD048884, L. Abbeduto, PI; P30 HD03352, M. M. Seltzer, PI) and the National Institute on Aging (P01AG020166, C. D. Ryff, PI, and R01AG019239, D. Almeida, PI) to conduct a longitudinal follow-up of the MIDUS (Midlife in the US) investigation. The original MIDUS study was supported by the John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development. We also acknowledge the contributions of Jyoti Savla, Robert Stawski, and Julie Lounds Taylor to the research on parenting and cortisol.
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Siblings of Children with Intellectual Disabilities: Normal, Average, or Not Too Different? Zo Stoneman Contents 1. Siblings of Typically Developing Children 1.1. The developmental course of sibling relationships 1.2. The developmental effects of being a sibling 2. Research on Siblings of Children with Intellectual Disabilities 2.1. Foundations of sibling disability research 2.2. Research questions and guiding theory 3. Use of Comparison Groups in Sibling Disability Research 3.1. Comparing siblings of children with and without disabilities 3.2. Comparability of sibling groups 3.3. Are child and sibling social address variables important when comparing sibling groups? 3.4. Are demographic confounds important in disability sibling research? The case of SES 3.5. Family form, race, and ethnicity 4. Methodological Considerations in Conducting Comparison Group Sibling Research 4.1. Statistical controls as a ‘‘solution’’ to dissimilar sibling groups 4.2. Strategies for matching comparison samples 5. Same or Not Too Different from Average? 5.1. Small differences? 5.2. ‘‘Average’’ siblings are a statistical creation and probably exist only on computer printouts 6. The Case (or the Lack Thereof ) for Sibling Interventions 7. Concluding Thoughts References
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Institute on Human Development and Disability, College of Family and Consumer Sciences, University of Georgia, Athens, GA 30602 International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37008-1
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Abstract This chapter provides an examination of research focused on siblings of children with intellectual disabilities, with particular focus on the methodological complexities of comparing siblings of children with disabilities to siblings of typically developing children. Sibling comparison group research is discussed in the context of a brief overview of selected research on typically developing siblings. The emphasis is on the manner in which comparison groups of typically developing children are constituted and the degree to which complexities inherent in sibling comparison group research affect the conclusions that can be drawn from the research literature. The final sections of the chapter discuss strategies for constituting comparison groups and provide an argument for the importance of family process research that focus on understanding the family and societal processes that shape individual and sibling outcomes.
Siblings have recently captured the attention and imagination of social science researchers. After being forgotten family members, they have moved to the forefront of family research (Deater-Deckard, Dunn, & Lussier, 2002). The recent emergence of siblings as a major family research topic is in contrast to a long, rich global history of cultural stories and writings about siblings, including folk tales, novels, essays, poems, and even sacred religious texts (i.e., Cain and Abel of the Old Testament). An interest in siblings may be new to family researchers, but an understanding of the importance of siblings to the lives and happiness of children has been a part of lay knowledge for a long time. The emotions and images associated with siblings are wide ranging. The terms brother and sister powerfully communicate the ideals of love, loyalty, and devotion, but also call forth thoughts of rivalry, competition, and betrayal. In the special issue on siblings of the Journal of Family Psychology, Dunn (2005) lauded progress in sibling research for its increased sophistication and richness of findings, including the emergence of longitudinal sibling data. Researchers have come to recognize that siblings are important to children’s lives and to their development (McHale, Kim, & Whiteman, 2006). Siblings are children’s most frequent out-of-school companions, sharing family vacations, joys, sorrows, stresses, and life transitions (McHale et al., 2006; Stoneman, Brody, & MacKinnon, 1984). Feelings that siblings develop toward each other in childhood show consistency over time (Brody, Stoneman, & McCoy, 1994; Kim, McHale, Osgood, & Crouter, 2006). Siblings develop intimate knowledge of each other’s lives and often know things about each other, both positive and negative, that are not shared with parents or significant others. Parallel to the growth of sibling research in the general family literature is an increasing interest in siblings among disability family researchers, as evidenced by a special section on siblings of individuals with disabilities in the journal Mental Retardation (October 2005; now titled Intellectual and Developmental Disabilities). As is the case with typically developing children, children with intellectual disabilities and their siblings spend large amounts
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of time together in the context of their home and family (Stoneman & Brody, 1993; Stoneman, Brody, Davis, & Crapps, 1987). One of the major questions posed by sibling disability researchers focuses on understanding the ways in which life experiences, sibling relationships, and individual child outcomes differ for children when they have a sibling with a disability. The purpose of this chapter is to provide an examination of this body of research with particular focus on the methodological complexities of comparing siblings of children with disabilities to siblings of typically developing children. Siblings of children with intellectual disabilities are the primary focus of the chapter. Adult sibling research is not addressed. Research focused on siblings of children with autism spectrum disorders (ASDs) is also considered to a limited extent because of shared methodological and conceptual issues. The initial sections of the chapter provide a brief overview of selected research on typically developing siblings. The findings and themes emerging from this work will be revisited later in the chapter when methodological issues concerning sibling relationships involving children with intellectual disabilities are considered. An overview of comparison group research is provided, with emphasis on the manner in which comparison groups of typically developing children are constituted. The final sections of the chapter examine the degree to which complexities inherent in sibling comparison group research affect the conclusions that can be drawn from the existing research literature.
1. Siblings of Typically Developing Children 1.1. The developmental course of sibling relationships It is surprising that a relationship embodied with such strong cultural meaning has been so slow to come to the attention of developmental and family researchers. Until the early 1980s, developmental and family theorists had paid little attention to the sibling relationship. Although a few early theorists, such as Adler (1929), stressed the importance of siblings as sources of developmental influence, their work had minimal impact on research. Most researchers considered mothers to be the prime socializers of children and designed their research accordingly. As a result, studies of mothers and their children dominated the research agenda, to the almost total exclusion of studies focusing on the wider family system, including fathers and siblings. The work of Dunn and her colleagues (e.g., Dunn & Kendrick, 1982), as well as Bank and Kahn, Sutton-Smith, and Lamb (Bank & Kahn, 1982; Lamb & Sutton-Smith, 1982; Sutton-Smith & Rosenberg, 1970), helped to bring siblings into the developmental limelight. Throughout life, sibling relationships are characterized by intense, often contradictory emotions. During childhood, siblings can be trusted best
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friends, sharing confidences and supporting each other during difficult times. They also can be hostile combatants, requiring frequent parental oversight and intervention. Howe, Aquan-Assee, and Bukowski (2001) noted that the intimate knowledge that siblings have of each other can be used to delight and amuse a brother or sister, or to aggravate and provoke conflict. High levels of loving warmth and angry conflict are frequently present in the same relationship (Furman & Buhrmester, 1985). DeaterDeckard et al. (2002) suggested that it is these intense emotions, both positive and negative, that make the sibling relationship so powerful. The roots of the sibling relationship develop early. During the second year of life, toddlers begin to show concern when infant siblings are distressed; attempts to comfort a distressed infant increase significantly during the preschool years (Dunn, 1983). Older siblings can serve as attachment figures for their younger brothers and sisters (Stewart, 1983). In the United States, sibling caregiving begins in early childhood, with children as young as 4 years of age demonstrating caregiving behaviors directed toward younger siblings (Volling, Herrera, & Poris, 2004). In addition to positive, prosocial behaviors, children’s first experiences of conflict occur in the family, often involving siblings (Perlman, Garfinkel, & Turrell, 2007). During childhood, sibling relationships tend to be high in conflict as compared to other important relationships, such as those with parents or peers (Buhrmester, 1992). Sibling conflict declines during middle and late adolescence (Buhrmester, 1992; Kim et al., 2006), but so does sibling positivity, warmth, companionship, and closeness (Brody et al., 1994; Buhrmester, 1992; Dunn, 1996). Both of these trends plausibly occur because across the same developmental period sibling relationships decline in intensity, primarily because the siblings spend less time together as the children become more involved with their friends and with numerous activities and commitments that draw them away from the family context (Buhrmester, 1992; Dunn, 1996). Young siblings spend most of their time together; adolescent siblings much less so. Buhrmester stressed that as children age the form and character of the sibling relationship changes, but strong emotional attachments remain. Although siblings sometimes play and talk together as equals, older siblings often assume dominant roles such as that of manager, teacher, and helper while younger siblings, by choice or necessity, assume nondominant complementary roles (Brody, Stoneman, MacKinnon, & MacKinnon, 1985; Stoneman et al., 1984). Children’s sibling relationships are distinguishable from relationships with parents and peers because they include both complementary and egalitarian roles (McHale et al., 2006). Roles evolve developmentally. As siblings mature, their interactions become more egalitarian and less asymmetrical (Buhrmester, 1992; Buhrmester & Furman, 1990; DeHart et al., 1997). These changes represent an important developmental shift in sibling relationships as over time older siblings relinquish their dominant and
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caregiving roles (Buhrmester, 1992). Buhrmester suggested that this role shift may cause the younger sibling to feel ‘‘emancipated from the often oppressive authority’’ (p. 36) of older children who have been told by parents to watch over their younger siblings. Similarly, he suggested that older siblings are likely to feel liberated being relieved of the responsibility of looking out for and entertaining younger children.
1.2. The developmental effects of being a sibling In addition to being interested in understanding the sibling relationship for its own sake, developmental researchers have investigated the effects of siblings on the social, emotional, cognitive and language development of their brothers and sisters. Hartup (1989) suggested that the natural discrepancies between the skill and competency levels of siblings of different ages, similar to the competency discrepancies of mixed-aged peers, can provide an ideal context for learning. There is evidence that even very young children are attuned to the behaviors and the physical presence of their older siblings. In an early study, Samuels (1980) found that infant siblings (17–28 months) increased their motor exploration of unfamiliar environments when their older siblings were present. Children help their toddler-aged siblings acquire new skills, teaching them through modeling and direct instruction how to solve problems, focus and sustain attention, play games, and manipulate toys (Azmitia & Hesser, 1993; Klein, Feldman, & Zarur, 2002). Children compare themselves with their siblings to evaluate their abilities and achievements, yielding judgments that can increase or decrease their self-esteem (Tesser, 1980). When children enter kindergarten, their social skills are more advanced if they have at least one sibling (Downey & Condron, 2004). During the school years, more warmth and less conflict in youths’ siblings relationships has been found to be positively associated with the quality of relationships with best friends (McCoy, Brody, & Stoneman, 1994). These and similar findings suggest that sibling effects can be important for understanding variability in the development of children within the family context.
2. Research on Siblings of Children with Intellectual Disabilities 2.1. Foundations of sibling disability research Most of the researchers studying siblings of children with intellectual disabilities have been motivated by a belief that the outcomes and processes for these children would be different than those for typically developing siblings. Until quite recently, this difference was almost unvaryingly assumed to be negative. Early researchers, guided by a pathological model, looked for negative mental
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health outcomes that were believed to accrue to nondisabled siblings (e.g., Cohen, 1962; Farber, 1959, 1960; Farber & Jenne´, 1963; Jordan, 1962; Kaplan, 1969; SanMartino & Newman, 1974; Schild, 1964). Much of this research had its roots in clinical practice, based on observations of siblings who were referred because of behavior or other problems. Confronted with these children, researchers became interested in understanding what they perceived to be the patterns of family dysfunction that led to negative child outcomes, focusing on the child with an intellectual disability as the precipitating cause. Siblings and families constituting study samples were generally drawn from clinic populations, skewing findings toward a nonrepresentative group of families who were experiencing significant problems for which they had sought professional help (Stoneman, 1993). In direct reaction to this negative bias, disability researchers began to call for a focus on family strengths (e.g., Summers, Behr, & Turnbull, 1989), arguing that written parent narratives and oral life stories consistently included benefits to families from the presence of children with intellectual disabilities, although these positive contributions were almost uniformly ignored by researchers. They noted that many parents were effectively rearing children with intellectual disabilities in the context of healthy, well-functioning families. In 1982, Stoneman and Brody called for a similar focus on the strengths of siblings of children with intellectual disabilities. Describing a ‘‘functional role theory’’ approach (p. 115) to sibling relationships, they posited that the presence of a child with an intellectual disability in the family would hold benefits for siblings, including the opportunity for expanded role enactments and opportunities for teaching and helping which would be expected to result in increased sibling competencies and self-esteem (Stoneman & Brody, 1982). Recently, Dykens (2005) drew upon the tenets of positive psychology (e.g., Seligman, 2002) to posit a framework for conceptualizing the positive impacts of children with intellectual disabilities on their siblings. As is the case with typically developing siblings, siblings of children with disabilities spend large amounts of time together. Studies employing naturalistic observational methods have documented that both older and younger siblings of children with intellectual disabilities have high levels of daily interactions across a wide range of routine daily activities (Stoneman & Brody, 1993; Stoneman et al., 1987; Weisner, 1993), although this may be less true for children with more substantial intellectual disabilities. Stoneman and Brody (1984) observed children interacting with their siblings with substantial intellectual disabilities while engaged in naturally occurring activities at home. The children with disabilities, very limited in their ability to contribute to social interactions, spent most of their time unoccupied. Even though the occurrence of sibling interactions was quite low, the children with disabilities frequently were moved around the house to be with their siblings and watched their brothers and sisters as they played and went about their daily activities.
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2.2. Research questions and guiding theory Why would it be expected that children with intellectual disabilities would affect their siblings in ways that differed from typically developing siblings? I (Stoneman, 1990) have suggested that it might seem like calling into question the obvious to ask why intellectual disability would be expected to have a significant impact on families. To answer this question, however, we need guiding theory that unbundles the construct of intellectual disability and clearly conceptualizes the processes through which siblings influence each other, and through which families influence siblings in the context of disability. This task is made more difficult by the lack of consensus in the field about how to conceptualize intellectual disability (Switzky & Greenspan, 2006). As scholars debate the criteria for determining that a child has an intellectual disability and the degree to which this disability is a socially determined phenomenon, sibling researchers have generally avoided these debates. This is perhaps unfortunate in that the conceptualization of what constitutes an intellectual disability is central to understanding the effect that intellectual disability might be expected to have on siblings. Researchers who have tried to explain the interactional processes that are altered in families of children with intellectual disabilities have often drawn upon the classic work of Farber (Farber, 1959, 1960; Farber & Jenne´, 1963), who articulated a family systems approach to families of children with intellectual disabilities. Family systems theory (Broderick & Smith, 1979) emphasizes the interconnectedness of family members, positing that when events impact one family member, all members are changed in some way. Farber suggested that mothers pay disproportionate attention to their offspring with intellectual disabilities, at the expense of other children in the family (Farber & Jenne´, 1963). He believed that mothers accommodated heavy care demands placed on them by obtaining the assistance of their nondisabled daughters in housework and in childcare, thus creating an expanded set of roles for these girls. Farber expected that this would prove confining to the daughters, limiting their ability to spend time with peers and to be actively involved in activities outside of the home. A different pattern was expected for brothers (Farber & Jenne´, 1963). Unlike daughters, sons were not expected to be recruited by mothers as helpers or as surrogate parents. In response to the tension and anxiety that Farber believed would characterize family interactions because of the presence of the child with an intellectual disability, he predicted that brothers would try to escape the home environment. With the child with intellectual disability as the center of attention in the home, he posited that brothers would seek companionship in the school and neighborhood. Farber (1960) further posited that the presence of a child with intellectual disability would result in an arrest in the family lifecycle. As siblings without disabilities matured, the child with intellectual disability would
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develop more slowly, gradually assuming the status of a younger sibling, even if he/she were actually chronologically older than the other children in the family. This conceptualization implies that as younger siblings mature, they will at some point developmentally ‘‘catch up’’ to and eventually surpass their older siblings with intellectual disabilities. Farber (1960) posited that this period of role crossover would be accompanied by sibling conflict and anxiety, as new role relationships are formed and the older child with intellectual disability is forced to relinquish his/her position of dominance. Farber’s themes, including an increased burden of child care on sisters, restricted social activities and time with friends, anxiety, decreased parent attention, arrested family life cycle, and sibling conflict, have been repeated in the disability sibling research literature across the past 50 years. Although the themes have been relatively consistent, the research literature has not yielded clear findings. Numerous disability sibling researchers have all or in part justified the need for their research because the literature is characterized by a lack of consensus (Cuskelly & Gunn, 1993), conflicting and contradictory results (Dyson, 1989; Hannah & Midlarsky, 1999; Verte, Roeyers, & Busse, 2003), confusion (Dyson, 1989), and inconsistencies in research findings (Cuskelly & Gunn, 1993; Hannah & Midlarsky, 1999; Levy-Wasser & Katz, 2004; Macks & Reeve, 2007). In her 1999 methodological paper on sibling disability research, Cuskelly wrote that the literature on the psychological adjustment of siblings of individuals with disabilities was filled with ‘‘contradiction and confusion’’ (p. 111). She cited methodological differences and deficiencies as the most frequent explanations for these inconsistencies. One of the most important methodological issues is the choice of which population of typically developing siblings to draw from to constitute a comparison sample (Cuskelly, 1999; Stoneman, 1989). To ask whether or not siblings of children with intellectual disabilities differ from other siblings, the researcher must either employ a comparison group of siblings in the research design or compare data from the target siblings to normative data on selected outcome measures. Neither of these approaches is as straightforward as it might appear on first glance.
3. Use of Comparison Groups in Sibling Disability Research 3.1. Comparing siblings of children with and without disabilities In order for researchers utilizing sibling comparison groups to achieve clearly interpretable, replicable findings, it is important that the group of siblings of children with intellectual disabilities and the group of typically developing siblings are similar on important demographic characteristics.
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Because the development of individual children and socialization of sibling relationships occur in and are influenced by the family context, it also is important that the two groups of families are comparable. Although precise control can never be achieved in family research, the notion of reducing alternate explanations for group differences on study outcomes remains sound. This idea harkens back to the basic tenets of experimental design, namely that it is impossible to attribute sibling group differences to one factor (e.g., intellectual disability) when the groups also differ on other, potentially important, characteristics. When groups are dissimilar, confounding variables, rather than the researcher’s stated hypotheses, may hold the key to explaining significant group differences. In an article published 20 years ago (Stoneman, 1989), I examined the strategies that researchers were using to empirically compare families of individuals with intellectual disabilities to comparison families not affected by disability. That paper covered the period from 1965 to 1988. Sibling research constituted only a minor portion of the article because in the time period covered only a few empirical journal articles were published that compared siblings of children with intellectual disabilities to comparison siblings (Abramovitch, Stanhope, Pepler, & Corter, 1987; Gath, 1972, 1973; Gath & Gumley, 1987; Lobato, Barbour, Hall, & Miller, 1987; McHale, Sloan, & Simeonsson, 1986; Stoneman et al., 1987; Stoneman, Brody, Davis, & Crapps, 1988). My analysis revealed that there was a large amount of unreported information about the demographic characteristics of most of the study samples. This lack of information made it impossible to determine whether confounding variables could have accounted for study findings. In this regard, sibling research was similar to the overall body of disability family research examined in the paper. Tables 8.1 and 8.2 provide an updated overview of how disability sibling researchers have constituted comparison groups from 1989 (the end of the period covered by the Stoneman, 1989 article) to the present. As with the original article, only journal articles are tabled (excluding books, book chapters, conference papers, dissertations, and in press articles). Manuscripts are included if they contained a group of siblings of children with intellectual disabilities or an ASD (or a mixed group including children with intellectual disabilities) and a comparison group of typically developing siblings. Research examining family-level genetic effects of syndromes such as autism are not included. Clusters of studies are divided by whether the article focused on outcomes for the nondisabled sibling, the sibling relationship, or both. Table 8.1 includes studies which included only a comparison group of typically developing siblings. Table 8.2 includes studies that included both a comparison group of typically developing siblings and a cross-disability comparison group. Studies were not tabled if they included multiple disability groups without a group of typically developing siblings.
Table 8.1
Matching variables in studies with nondisability comparison groups Matching variables
Type of study/ author(s)
MD
#D
#C
D CA
Effects on nondisabled siblings—ND comparison groups ID 70 70 NR Auletta and DeRosa (1991) Burton and MD 30 30 NR Parks (1994) Coleby (1995) ID 41 41 NR Cuskelly and DS 70 67 NR Gunn (1993) Cuskelly et al. (1998)
DS
Dyson and MD Fewell (1989) Dyson (1989) MD and Dyson, Edgar, and Crnic (1989) Gold (1993) AUT Grissom and MD Borkowski (2002) ID Hannah and Midlarsky (1999) Levy-Wasser ID and Katz (2004)
D Sex
Sib CA
Sib Sex
Comb Sex
B.O.
Age space
Which Sib
MA
Race
PEd
SES
# Par
# Sibs
PAge
NR
þ
NR
NR
NR
NR
Sib-R
N/A
NR
NR
NR
NR
NR
NR
NR
S
NR
NR
NR
NR
Sib-R
N/A
NR
NR
NR
NR
NR
NR
NR NR-D
NR-G-M NR-G-M NR þ þ NR-D
NR NR
NR-M S-M NR þ
NR
þ
NR
NR
NR-M NR-M Random N/A þ S Within N/A 4 years of DS NR NR All N/A
NR
NR
NR
NR-M S-M S þ
NR-M NR
þ
þ
NR
NR
NR
þ
NR
NR
NR
DS 45 (Sibs 154) 37
T 88 (Sibs 273) 37
NR
NR-G NR
þ
þ
NR
No
NR
55
55
þ
þ
þ
þ
No
þ
NR-D Oldest N/A <14 years
þ
No
NS-No
þ
þ
NR
22 27
34 27
NR þ
þ NR
NS-No þ
þ þ
NR NR
No þ
NR þ
NR NR
N/A N/A
þ þ
No-St þ
þ NR
NR þ
þ NR
NR þ
50
50
þ
þ
þ
þ
þ
þ
S
Random
N/A
NR
NR
No
S
þ
NR
25
27
NR-D NR
þ
No
NR
S
NR
NR
N/A
NR
No
S
þ
NR-G
NR
NR
N/A
Lynch et al. (1993)
ID
Macks and AUT Reeve (2007) Mandleco et al. MD (2003) McMahon et al. ABI (2001) Nixon and D Cummings (1999) Senel and Akkok MD (1996) Stores et al. DS (1998) Verte et al. AUT (2003)
ID 9 (Sibs T 10 12) (Sibs 13) 51 36
þ
NR
þ
þ
NR
NR
NR
All 8–16 years N/A
No
NR
þ
NR
þ
NR
NR
NR
NR
S
NR
S
NR
Closest in age N/A
NR
NR
þ
NR
þ
NR
39
39
NR-D NR
NR-G-M NR-G-M NR
NR
NR
Close in age
N/A
þ
NR-NS No-St
þ
12
11
NR-D NR-D
þ
þ
NR
NR
NR
Closest in age N/A
þ
NR-NS NR-NS þ
NR-G- NR-NS NS NR NR
30
30
NR
NR
þ
þ
NR
þ
S
NR
N/A
þ
NR
No-St
þ
NR
NR
30
30
NR
NR
þ
NR-D
NR
NR-D
NR
NR
N/A
NR
NR
NR
NR
S
NR
54
78
NR-D NR-D
No
þ
NR
NR
NR
NR
N/A
NR
NR
NR-NS NR
NR
NR
29
29
þ
þ
þ
þ
NR
þ
þ
NR
N/A
NR
NR
NR
NR
þ
NR
NR þ
þ þ
NR-M þ
NR þ
NR þ
NR þ
NR N/A N/A Younger, same-sex closest in age
NR þ
NR þ
NR S
þ þ
NR-M NR þ þ
NR-G
NR
NR-G
NR
NR
NR
All 2–18 years N/A
S
No-St
þ
þ
NR
NR
þ
þ
NR
þ
S
NR
N/A
No-St
NR-G NR-NS NR
þ
þ
þ
NR
þ
NR-M NR
N/A
NR- NR GNS NR NR
þ
þ
Effects on sibling relationship—ND comparison groups Anderson (1997) ID 16 16 NR ID 16 16 þ Brody, Stoneman, Davis, and Crapps (1991) and Stoneman et al. (1991) Costigan, Floyd, ID ID 165 T 52 þ Harter, and (Sibs (Sibs McClintock 229) 58) a (1997) ID 50 50 þ Hannah and Midlarsky (2005) Lobato et al. MD 20 20 þ (1991)
þ
þ
NR
(continued)
Table 8.1 (continued) Matching variables Type of study/ author(s)
MD
Stoneman et al. ID (1989)
#D
#C
D CA
D Sex
Sib CA
Sib Sex
Comb Sex
B.O.
Age space
16
16
þ
þ
þ
þ
þ
þ
þ
Older same- N/A sex closest in age
NR- NR-G- NR-GGM M M
NR- þ GM
NR
NR-G
NR
þ
þ
All older sibs N/A
þ
NR
NR-G
þ
NR
NR
Effects on nondisabled siblings and sibling relationship—ND MD 12 (16 T 12 (Sibs þ Bischoff and Tingstrom Sibs) 16) (1991) Cuskelly and DS 54 53 þ Gunn (2003, 2006) Ishizaki et al. MD 50 128 NR (2005) ID 31 31 þ Gamble and McHale (1989), McHale and Gamble (1989), and McHale and Pawletko (1992) a
comparison groups þ þ
Which Sib
MA
Race
PEd
SES
# Par
# Sibs
PAge
þ
þ
þ
No
þ
NR
Closest in age N/A
NR
NR
þ
þ
þ
NR
NR
No
NS-No
No
NR
NR
NR
NR
No
No
NR
NR
S
þ
þ
þ
þ
þ
þ
Older closest N/A to 11 years
þ
NR
þ
þ
þ
NR
N/A
Sample sizes are reported for participating families, but not for the families that included siblings. ABI, acquired brain injury; AUT, autism; MD, mixed disabilities; DS, Down syndrome; ID, intellectual disability; T, target child; D, type of disability; # D, number of disability sibling pairs; # C, number of comparison sibling pairs; CA, chronological age; Sib, sibling; Comb Sex, sex combination of sibling pair; B.O., relative birth order of the siblings participating in the study; PEd, parent education; # Par, number of parents, family form; # Sibs, number of siblings, family size; PAge, parent age; NR, information not reported; NR-G, data reported for total sample or combined groups, but not reported individually by group; NR-D, data reported for disability group but not for comparison group; NS, no significantly differences between groups; No, groups not matched or similar, significant differences between groups; NS-No, groups are quite different, but described as statistically nonsignificant; St, variable is statistically controlled in some/all analyses; M, groups described as matched; S, groups are generally similar, not formally matched; þ, groups successfully matched, very similar; Sib-R, sibling was recruited from population pool (college); x/y, sample size of x in year 1, y in year 2 of longitudinal study.
Table 8.2
Matching variables in studies with both nondisability and cross-disability comparison groups Matching variables
Type of study/ author(s)
MD
#D
#C
D CA
D Sex
Sib CA
Effects on nondisabled siblings—both ND and cross-disability comparison groups Rodrigue AUT 19 20 No NR-M- þ et al. (1993) DS 20 NS Singhi CP et al. (2002) ID
75 25
76
NR
NR
S
Effects on sibling relationship—both ND and cross-disability comparison groups Floyd ID 67-NR 50-NR NR-GNR NR a et al. (2004) CI 45-NR No Roeyers and Mycke (1995) Summers et al. (1997)
Sib Sex
Comb Sex
S
NR
S
Age space
Which Sib
MA
Race
NR-M- NR NS
NR
þ
NR
NR
NR
Closest in age N/A
NR- NR GNS þ S
NR
NR
NR
NR
All 2–18 years N/A
PEd
SES
# Par
NR-M- þ NS S
# Sibs
PAge
NR-M- NR NS
þ
NR
þ NR
NR-G- NR-GNSNo St S NR
NR
AUT ID
20 20
20
þ
þ
þ
þ
NR
þ
S
NR
N/A
NR- NR-G- NR-GGNS NS NS NR NR NR
DS H DD
14 10 13
26
þ
NS-No
þ
NS-No
NR
þ
NR
Older
N/A
NR
No
NS-No
NR
NR
NR
þ
þ
NR
NR
N/A
No
NR
þ
No
No
NR
NR
No
þ
Random
N/A
No
þ
þ
S
þ
No
NR-G
NR-G- S M
Closest in age N/A
NR-M þ
No
þ
S
NR
NR
þ
NR
S
þ
þ
þ
þ
þ
NR
NR-G
NR
Chosen by N/A researcher Closest in age N/A
NR
NRþ NoSt
Effects on nondisabled siblings and sibling relationship—ND and cross-disability comparison groups Bagenholm AUT 20 20 NR NR-M S þ and Gillberg ID 20 (1991) ID-H 25 28 þ No þ No Eisenberg, IH-P 20 Baker, and Blacher (1998) PDD 46/42/ 46/43 NR No NR þ Fisman et al. 41 (1996, 2000) DS 45/42 and Wolf et al. (1998) Gargiulo MD 51 48 þ þ þ þ et al. (1992) Kaminsky and AUT 30 30 þ NR-D- þ þ Dewey No DS 30 (2001, 2002) a
B.O.
NR- þ NS
NR
Sample sizes are reported for participating families, but not for the families that included siblings. AUT, autism; CI, mixed chronic illnesses; CP, cerebral palsy; MD, mixed disabilities; DD, developmentally delayed; DS, Down syndrome; H, hearing impairment; ID, intellectual disability; ID-H, children with ID living at home; IH-P, children with ID in residential placement; PDD, pervasive developmental disorder; D, type of disability; # D, number of disability sibling pairs; # C, number of comparison sibling pairs; CA, chronological age; Sib, sibling; Comb Sex, sex combination of sibling pair; B.O., relative birth order of the siblings participating in the study; PEd, parent education; # Par, number of parents, family form; # Sibs, number of siblings, family size; PAge, parent age; NR, information not reported; NR-G, data reported for total sample or combined groups, but not reported individually by group; NR-D, data reported for disability group but not for comparison group; NS, no significantly differences between groups; No, groups not matched or similar, significant differences between groups; NS-No, groups are quite different, but described as statistically nonsignificant; St, variable is statistically controlled in some/all analyses; M, groups described as matched; S, groups are generally similar, not formally matched; þ, groups successfully matched, very similar; x/y, sample size of x in year 1, y in year 2 of longitudinal study.
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Terminology used in sibling research is often cumbersome, confusing, and used inconsistently across studies. In this chapter, the child in the comparison sibling pair who is matched to the child with a disability is referred to as the target child. The sibling of the child with a disability and the child matched to this child in the typically developing sibling pair are referred to as siblings. Relative birth order is used to indicate whether a child is the older or younger child in a sibling pair. Family birth order is the order of birth of the child as compared to all other children in the family, sometimes referred to as ordinal position. A child, for example, might be the older child in the pair (relative birth order), but the third born of four children in the family (family birth order). Because it is so seldom reported in sibling disability research, family birth order is not included in Tables 8.1 and 8.2. The developmental literature on typically developing siblings provides a wealth of insight into factors which can affect sibling outcomes and the sibling relationship (and thus provide potential confounding variables in disability sibling research). These variables include the sex of both siblings, the sex combination of the sibling pair, the ages of both siblings, the relative birth order and age spacing of the two children, race, social class, family form (the number of parents in the home), family size (the number of children), and parent age (see McHale et al., 2006 for a review of this literature). Each of these variables is included in Tables 8.1 and 8.2. Social class is often considered to be comprised of three components: income, parent education, and occupation/employment status (DeGarmo, Forgatch, & Martinex, 1999). Parent education and SES are both tabled; SES is coded if the article provided information on either income or parent occupation. Tabled entries for each variable indicate whether the author(s) provided data supporting the equivalence of groups on that variable (coded with a þ), provided data that the groups were not equivalent on the variable (No), provided data indicating that groups were relatively similar on the variable but not equivalent or formally matched (S), or failed to report data concerning the variable in the description of subjects or elsewhere in the manuscript (NR). A study variable is coded as NR-G if the author(s) provided information about the variable for the total sample but did not report information separately for the groups which were subsequently compared to each other. M was coded if the author(s) made a statement that the groups were matched on a variable, even if no supporting information (e.g., means, frequencies) was provided. D was entered if data about the variable were provided for the disability group but not for the comparison group. When group differences were acknowledged by the author(s), many researchers utilized statistical procedures in their data analyses in an effort to control for these variables. When a previously published paper contained additional sample information not included in the tabled publication, data from the original article was utilized in completing the tabled entry for the study. Multiple studies published from the same data are tabled on the same line and information is
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coded as being present if it appeared in at least one article. When studies included multiple groups of siblings of children with disabilities (e.g., Down syndrome and autism), Table 8.2 designates whether each disability group had a separate comparison group or whether multiple disability groups shared one comparison group. Group comparability was examined between the disability groups and the comparison group(s) of typically developing siblings, but not between disability groups. Tables 8.1 and 8.2 also contain information about how the researcher(s) selected the siblings who participated in the study when families had more than two children. For families of children with disabilities, a common practice was to select the sibling closest in age to the child with a disability. Other researchers randomly selected the participating sibling (e.g., Coleby, 1995) or used multiple selection criteria, such as the same-sex older sibling closest in age to the child with a disability (e.g., Stoneman, Brody, Davis, & Crapps, 1989). A few studies collected data from all siblings in the family (e.g., Cuskelly, Chant, & Hayes, 1998) or from all siblings in a selected age range (e.g., Lynch, Fay, Funk, & Nagel, 1993). Approximately 40% of the articles did not provide information on the criteria used to select participating siblings. Two studies, McMahon, Noll, Michaud, and Johnson (2001) and Stores, Stores, Fellows, and Buckley (1998), appeared to recruit comparison children regardless of whether or not they had siblings.
3.2. Comparability of sibling groups In a number of studies, comparison siblings and/or their families clearly differed from the siblings/families of children with disabilities on multiple dimensions in addition to the presence of a child with a disability. As was the case in the Stoneman (1989) article, one of the most striking aspects of Tables 8.1 and 8.2 is the large number of NR entries, representing information about the sample that was not provided in the article. The large amount of missing information across studies makes it more difficult to evaluate the results of a given study and to compare findings across studies. It is not always possible to equate groups on important demographic factors, but it is under the researcher’s control to provide sufficient data on the sample for the reader to ascertain whether the groups differed on important dimensions that could affect study findings. Researchers frequently examined the comparability of their study groups by using t-tests or similar statistics to determine if groups differed on potentially confounding variables. Coleby (1995), for example, wrote: ‘‘Our comparison group was not perfectly matched but the differences. . .were small, and insignificant on analysis’’ (p. 423). In the tables, a NS is entered if the researcher(s) conducted statistical tests to examine whether or not their groups differed and these tests resulted in nonsignificant p-values. Executing statistical analyses to verify post hoc that groups are equated on important parameters is akin to trying
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to prove the null hypothesis. The researcher has a 95% or better chance of finding that groups do not differ. As discussed below, using such tests as sole support for claims of group equivalence is potentially misleading, particularly when combined with small sample sizes, and can create false confidence in the comparability of sibling groups. A code of NS-No is assigned when nonsignificant statistical tests are reported but data included in the paper indicate that the groups are quite different on the analyzed variable. For example, several sibling researchers reported nonsignificant differences between disability and comparison groups on income. Gold (1993) reported that families of children with autism and comparison families did not differ on income and therefore the groups were treated as being equivalent on this factor. Her data indicate that 42% of the families of children with autism had incomes less than $39,000 while only 16% of the comparison families had incomes in that range. Similarly, Dyson (1989) reported nonsignificant income differences between families of children with disabilities and comparison families, although 26% of families in the disability group and only 7% of comparison families were categorized as lower SES. Summers, Hahs, and Summers (1997) had groups that appeared to be quite different on income. Income was described as not being different between sibling groups based on a statistical test with a p-value of 0.07. Gold (1993) found that siblings of boys with autism reported more depressive symptoms than comparison siblings. She noted that although sibling age was not significantly different between sibling groups based on Chi square analyses, more siblings of boys with autism were adolescents (77% of siblings of boys with autism; 50% of comparison siblings). The age difference between groups was acknowledged by the authors to be a potential confound since adolescents, in general, are more likely to report depressive symptoms. Including this information in the discussion assists the reader in interpreting the findings of the study. In longitudinal studies, differential attrition can create unbalanced groups over time, even if groups are similar during the first phase of the research. For this reason, it is important to provide sample information for the longitudinal time point providing the data that are analyzed in the study. Fisman, Wolf, Ellison, and Freeman (2000), Fisman, Wolf, Ellison, Gillis, Freeman, et al. (1996), and Wolf, Fisman, Ellison, and Freeman (1998) lost subjects in their longitudinal follow-up, as would be expected, but did not provide new demographic information for their reduced longitudinal sample. It is also important to provide information on sibling subsamples analyzed in the study. Dyson (1989) initially matched groups of siblings of children with and without disabilities on demographic variables. Additional analyses were executed to examine differences among disability subgroups, with no information about the characteristics of the families constituting the subgroups. Similarly, Dyson and Fewell (1989) reported analyses executed
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by disability subgroups without reporting sample information at the subgroup level. Gargiulo, O’Sullivan, and Wesley (1992) matched their disability and comparison groups, but analyzed their data by subdividing the disability group into children with acquired and congenital disabilities, and children with visible and invisible disabilities. Information on these subgroups was not provided. Other researchers (e.g., Floyd, Harter, & Costigan, 2004) provided data for a sample recruited for a large family study but did not provide information about the smaller sample of siblings whose data also are analyzed. Only one sibling study matched children on competency. Rodrigue, Geffken, and Morgan (1993) matched children with autism, Down syndrome, and comparison children based on their age equivalent scores on the Vineland adaptive behavior scale (Sparrow, Balla, & Cicchetti, 1984). All children had age equivalents of approximately 3 years. To execute this match, children with disabilities and their comparison matches had to be of quite different chronological ages. Children with Down syndrome and autism averaged 11–12 years of age; comparison children averaged less than 3 years of age. Almost all of the comparison siblings (aged 9–11 years) were older siblings—this was not the case for the siblings of children with Down syndrome and autism. Age spacing of the groups of siblings, although not reported in the article, had to differ substantially. Although the authors sought to clarify inconsistent findings in the literature, the confounding of relative birth order and age spacing of the sibling pairs appreciably entangles the interpretation of study findings. Numerous problems inherent in using competency matching strategies in sibling research probably account for its lack of popularity, the most serious of which are alterations in sibling age relationships and birth orders. Only a few of the sibling comparison studies employed mixed groups of children with disabilities (e.g., Dyson, 1989; Nixon & Cummings, 1999). Nixon and Cummings argued that a mixed disability group was a sound methodological choice because ‘‘type of disability is reported to be unrelated to the sibling’s psychological functioning or adjustment.’’ This approach is in contrast to more recent research and scholarship arguing for the importance of etiological specificity in family research (e.g., Dykens & Hodapp, 2001; Hodapp, 1997) and for the importance of etiology to understanding sibling relationship outcomes (Stoneman, 1998).
3.3. Are child and sibling social address variables important when comparing sibling groups? 3.3.1. Group differences in sibling gender Tables 8.1 and 8.2 reveal substantial missing data and group differences on child and sibling social address variables, including sex of the siblings and the sex combination of the sibling pairs. To examine the state of our knowledge
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about siblings of children with intellectual disabilities, it is important to ascertain whether this inattention to sibling gender is innocuous or whether it potentially compromises what can be learned from this literature. Across cultures, one of the most salient aspects of a person is whether the person is male or female. The importance of gender begins at birth and lasts for a lifetime. During childhood, girls and boys are socialized differently by their parents and by society (Leaper, 2006). In families, men and women, and girls and boys, usually assume different roles and responsibilities. Few children are socialized in a manner that is gender neutral. Even when parents attempt to socialize boys and girls without regard to traditional gender roles in their society, children are exposed to numerous influences outside the home (and even inside the home through television, magazines, books, etc.) that reinforce traditional gender roles and behavior patterns. The field of women’s studies has developed as a cross-cultural area of scholarship based on strong societal mores that create gender differentiated realities for men and women, and for boys and girls. As such, it is striking that Tables 8.1 and 8.2 include many published sibling papers where the sex of one or both members of the sibling pair is not reported. The absence of information about child gender is especially evident for the children with disabilities and the children who are recruited as their comparison matches. Children with intellectual disabilities and autism are more likely than typically developing children to be male (Chapman, Scott, & StantonChapman, 2008; Leonard & Wen, 2002; Oswald, Coutinho, Best, & Nguyen, 2001; Yeargin-Allsopp, Drews, Decoufle´, & Murphy, 1995). Chapman et al. found that males had higher rates of intellectual disabilities than did females at all levels of impairment. Autism rates are estimated to be approximately four boys for each girl (Yeargin-Allsopp, Rice, Karapurkar, Doernberg, Boyle, et al., 2003). Given this imbalance, unless researchers select comparison target children matched on gender, there is a high probability that disability groups will contain proportionally more boys than comparison groups. This was true for several of the tabled studies (e.g., Fisman et al., 1996; Kaminsky & Dewey, 2001, 2002). Kaminsky and Dewey (2001, 2002) reported that the children with autism in their study were more likely to be boys (the ratio of boys to girls for the children with autism was 6:1) than were comparison target children, but they did not reveal the magnitude of the group difference; the number of boys and girls in each group was not reported. Fisman et al. (1996) reported that 83% of the children with autism in their study were male. The number of boys and girls in the comparison group of typically developing children was not reported. Researchers were more likely to attend to and attempt to equate the sex of nondisabled siblings as compared to the children with disabilities. Nonetheless, missing data and unbalanced groups were problems for these
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siblings as well. To assess the importance of gender differences between sibling groups, it is instructive to look at two common outcomes in sibling studies: depressive symptoms and externalizing behavior problems (Stoneman, 2004). In normative samples, around age 13, girls begin to report more depressive symptoms and to experience more clinical depression than do boys of the same age (Allgood-Merten, Lewinsohn, & Hops, 1990; Ge, Lorenz, Conger, Elder, & Simons, 1994; Hankin, Abramson, Moffitt, Silva, McGee, et al., 1998). This gender-related trend intensifies through the teenage years into adulthood, when women are twice as likely to experience depression as are men (Hankin et al., 1998). Boys, on the other hand, are more likely than girls to demonstrate externalizing problem behaviors across the childhood and adolescent years (Bongers, Koot, van der Ende, & Verhulst, 2003). Thus, if sibling groups differ on gender, it is plausible that differences in depressive symptoms or behavior problems between siblings of children with and without disabilities are the result of normative gender-related patterns rather than the presence of a child with a disability in the family. At the very least, this alternative explanation cannot be ruled out. The family processes leading to child and sibling outcomes can differ for girls and boys. Gold (1993), for example, found that although there were no differences in depressive symptoms between brothers and sisters of boys with autism, the factors contributing to depressive symptoms differed for girls and boys. Similarly, Cuskelly and Gunn (2006) did not find sibling sex differences in household or childcare tasks, but did find different correlates. For girls, chores were related to maternal reports of higher levels of externalizing behaviors. For boys, childcare responsibilities were related to higher maternal ratings of internalizing behaviors. Grissom and Borkowski (2002) found that the association between maternal attitudes/actions and sibling self-efficacy was stronger for girls than for boys. Similarly, Mandleco, Olsen, Dyches, and Marshall (2003) found that the family predictors of sibling psychosocial outcomes differed for male and female siblings. In dyadic sibling research there are four possible gender combinations: two sisters, two brothers, an older sister with a younger brother, and an older brother with a younger sister. The number expands geometrically when more than two siblings are considered. Research suggests that the four sibling gender combinations are associated with different relationship patterns (e.g., Stoneman, Brody, & MacKinnon, 1986). In intellectual disability research, sibling constellation factors become even more complex, since the child with a disability can be the older or younger sibling. The four gender combinations increase to eight when the relative birth order of the child with an intellectual disability is considered (e.g., boy with a disability with an older sister, boy with a disability with a younger sister). The developmental literature (McHale et al., 2006) suggests that sex-related
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biological characteristics brought into the sibling relationship and gender role socialization experienced by the child in the family/community interact with numerous other individual difference and family factors to create child and sibling outcomes. Without knowing the sex composition of sibling study groups, the reader cannot adequately interpret research findings concerning sibling outcomes that show clear gender-related developmental patterns or begin to understand gender-associated differences in family processes. 3.3.2. Group differences in sibling age and birth order As noted earlier in this chapter, sibling relationships change developmentally (McHale et al., 2006). McHale et al. argued that in addition to the direct effects of sibling age, important family processes that affect siblings may have different outcomes at different ages. They used the example of parent intervention in sibling conflict which has positive outcomes at early ages but negative outcomes during adolescence. Similarly, in their longitudinal study of sibling relationships from childhood into adolescence, Kim et al. (2006) found that the effects of sibling dyad sex constellation were more apparent at some ages than at others. Developmental pathways identified in their study differed based on the sex of the younger and older siblings, the sex combination of the two siblings, and birth order. To further complicate matters, as noted by Furman and Lanthier (2006), sibling age and birth order are confounded. They described the dilemma often confronted by sibling researchers who examine sex and birth order constellations, ‘‘Some work suggests that constellation effects may interact with other variables in meaningful ways. . .studies that have considered all the combinations of constellation variables have not yielded stronger or clearer effects. Often, in fact, the results of such studies are so complex that they baffle the most clever post hoc theorist’’ (p. 174). These complex effects are inconsistent across studies and are not clear in interpretation, but that does not equate with saying that they should be ignored. Yet, only a few researchers have examined relative birth order older sibling sex younger sibling sex combinations (e.g., Cuskelly & Gunn, 1993). Age spacing is also frequently ignored, even though mothers of children with disabilities are more likely to postpone subsequent births (MacInnes, 2008), creating potential group differences in sibling age spacing. Kim et al. (2006), in their discussion of the longitudinal course of childhood sibling relationships, reached an important conclusion: ‘‘. . .the study of relationship development involves the study of a dyad whose properties are not reducible to the characteristics of individual relationship partners’’ (p. 1758). This realization adds complexity to research, but the alternative of ignoring these potentially important variables distorts study findings and contributes to inconsistencies and contradictions in research findings.
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3.4. Are demographic confounds important in disability sibling research? The case of SES 3.4.1. Economic disadvantage experienced by families affected by disability In addition to informing researchers about the importance of sibling constellation variables, such as those discussed in the previous sections, research on typically developing siblings also provides a wealth of insight into family demographic factors that impact outcomes for individual siblings and for the sibling relationship, including income, parent age and education, race/ethnicity, family size, and family form (see McHale et al., 2006 for a review of this literature). It can be asked whether demographic differences between families are really important enough in sibling disability research to devote the funds and extensive time and effort needed to adequately incorporate these factors into research designs. To address this question, it is informative to examine what we know about the effects of one such variable, economic disadvantage, on child and sibling outcomes. Families of children with intellectual disabilities are more likely than other families to be economically disadvantaged and to live in poverty (Chapman et al., 2008; Emerson, 2003; Fujiura, 1998; Fujiura & Yamaki, 1997, 2000; MacInnes, 2008; Yeargin-Allsopp et al., 1995). Being born into a low-income family increases the probability that a child will acquire a disability because of numerous toxic factors associated with poverty, including exposure to environmental hazards such as lead, absence of prenatal and other health care, heightened injury risk, and poor nutrition (Emerson & Hatton, 2007). Haggerty, Roughman, and Pless (1975) coined the term ‘‘new morbidity’’ to refer to negative child outcomes associated with poverty. Baumeister, Kupstas, and Klindworth (1992) expanded on this concept to provide a framework for understanding the interface between poverty and disability. The new morbidity (which more than 30 years after Haggerty et al. introduced the term is no longer new) encompasses a transaction of environmental, behavioral, and biological forces which produce long-lasting deleterious effects for children (Baumeister et al., 1992). Families rearing a child with a disability often encounter numerous disability-related expenses which are in addition to the costs associated with a typically developing child. These extra expenses can deplete family financial resources and create major economic stress (Emerson & Hatton, 2007; Lukemeyer, Meyers, & Smeeding, 2000; Parish, Rose, GrinsteinWeiss, Richman, & Andrews, 2008). In addition, because of lack of childcare and other factors, the labor force participation of mothers of children with disabilities is significantly lower than that of mothers of children without disabilities (Brandon, 2000; Gallimore, Coots, Weisner, Garnier, & Guthrie, 1996; Porterfield, 2002). The difficulty experienced by mothers in returning to (or in entering) the workforce increases the probability that
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the economic distress experienced by families of children with intellectual disabilities will be long term (Emerson & Hatton, 2007). In the general population, economic disadvantage is associated with lower levels of parent education. Less educated workers have a reduced ability to secure higher-paying employment. The same is true for families of children with intellectual disabilities (Chapman et al., 2008; Yeargin-Allsopp et al., 1995). It is clear that there are multiple pathways through which economic disadvantage and childhood intellectual disability become associated. The increased economic disadvantage of families of children with intellectual disabilities creates the likelihood that typically developing comparison siblings will live in families that are more affluent, with better educated parents, than the families of the siblings of children with intellectual disabilities. This is especially true for children with intellectual disabilities that do not stem from identified genetic conditions. In fact, numerous sibling studies (e.g., Fisman et al., 1996; Hannah & Midlarsky, 1999; Nixon & Cummings, 1999) reported differences in income and/or parent education between sibling groups. 3.4.2. The effects of economic disadvantage on children and families Gershoff, Aber, Raver, and Lennon (2007) opened their recent article on material hardship with the following statement: ‘‘Several decades of research leave little doubt that family income matters for children’’ (p. 70). There is a large literature documenting that economic strain and disadvantage negatively affect the well-being of children (McLoyd, 1998). Raver and Leadbeater (1999) summarized 20 years of research by stating that poverty ‘‘takes a harsh toll’’ (p. 523) on children’s social and emotional development, placing them at risk for both internalizing and externalizing problems. Similarly, McLoyd (1998) concluded from her research review that children living in poverty and in conditions of economic stress are at risk for socioemotional maladjustment, including depression and behavior problems. These poverty-related outcomes are strikingly similar to those often reported for siblings of children with disabilities (Stoneman, 2005). Bronfenbrenner (1986) argued that constructs such as poverty and social class do not directly affect children’s development. These constructs are more appropriately regarded as proxies for social and interpersonal processes that operate in families. The well-being of parents is compromised by economic deprivation (Belle, 1990; Kotchick & Forehand, 2002). Most of the negative effects of economic deprivation on children are mediated through the behavior of parents (Gershoff et al., 2007). The research literature linking low income and compromised parenting dates back to the work of Hess and Shipman in the 1960s (Hess & Shipman, 1965; Kotchick & Forehand, 2002). Lower levels of parent education and fewer financial resources operate by different family process pathways, but each
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predicts lower quality parenting practices which, in turn, predict lower child achievement (DeGarmo et al., 1999). Recent work has documented similar associations among financial distress, parent mental health, and parenting among families of children with disabilities (e.g., Emerson, 2003; Giallo & Gavidia-Payne, 2006; Wang et al., 2004). For example, lower-income mothers of children with autism and intellectual disabilities reported more depressive symptoms and poorer psychological outcomes than did more affluent mothers of children with these disabilities (Abbeduto, Seltzer, Shattuk, Krauss, Orsmond, et al., 2004; Emerson, 2003; Orsmond, Lin, & Seltzer, 2007; Park, Turnbull, & Turnbull, 2002). Families of children with mild intellectual disabilities are more likely to live in neighborhoods with a lower median family income (Yeargin-Allsopp et al., 1995). In these areas, neighbors are financially stressed and social services and social support are scarce. Economically stressed parents have fewer personal resources to draw on to implement in-home interventions, are less likely to access parent meetings and support resources, and are more likely to face barriers such as transportation and childcare (Bhagwanji & McCollum, 1998; Breiner & Beck, 1984; GavidiaPayne & Stoneman, 1997; Sanders, 1992; Shriver & Kramer, 1993; Stoneman & Gavidia-Payne, 1998; Weber & Stoneman, 1986). Similarly, parents with less education have lower rates of participation in parent support and youth-related prevention programs (Spoth, Redmond, & Shin, 2000; Stoneman & Gavidia-Payne, 1998). For these reasons, economically stressed families receive less benefit from school and community services and supports. Many of the effects of economic deprivation on children with intellectual disabilities and their families are not direct effects, but complex interactions (Emerson & Hatton, 2007). Tschann, Kaiser, Chesney, Alkon, and Boyce (1996) noted that the effects of a specific family stressor may be stronger or weaker for children living in low-income homes, where numerous other stressors exist. In the midst of significant economic stress, certain stressors can be magnified in their impact. The same may be true for siblings. Macks and Reeve (2007) found that demographic factors were more likely to be associated with positive and negative outcomes for siblings of children with disabilities, as compared to siblings of typically developing children. Macks and Reeve concluded that the presence of a sibling with autism had an increasingly negative impact on nondisabled children as the number of demographic risk factors increased. This is reminiscent of the cumulative risk index utilized by Sameroff and Seifer (1995). Many of the studies linking economic deprivation to compromised child development have focused on families living in poverty. The work of Gershoff et al. (2007) cautions that families can experience material hardship at higher-income levels when expenses are high. Traditional SES markers such as income or occupational status may not capture the material hardship
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experienced by a family with an apparently adequate income combined with large out-of-pocket disability-related expenses. For these families, the negative effects of economic hardship on child outcomes may be evidenced for families who might otherwise be viewed as middle class and economically stable. Parish et al. (2008) documented that a substantial number of middle class families of children with disabilities experience material hardship. The association between economic disadvantage and ASDs is less clear than it is for intellectual disabilities. Newschaffer et al. (2007), in their review of the epidemiology of ASD, reported that a positive relationship between autism prevalence and higher-income status has been reported in the literature. They suggested that this association was probably the result of increased ascertainment in more affluent families. Economic stresses, however, still impact these families since the cost of interventions related to ASDs can create financial hardship. 3.4.3. The effects of economic disadvantage on siblings In addition to the research linking economic deprivation to negative outcomes for individual children, there is a growing, but more ambiguous, literature examining the effects of economic and other stressors on the relationship between siblings. There is evidence that older siblings in economically deprived homes can provide important protective support during times of stress for their younger brothers and sisters (Sandler, 1980), but also some suggestion that financial distress may exacerbate sibling conflict (Dunn, 1996; Updegraff, McHale, Whiteman, Thayer, & Delgado, 2006). Some family adversities, such as maternal illness, accidents, or children’s peer problems, seem to bring siblings closer together (Bank & Kahn, 1982; Dunn, Slomkowski, & Beardsall, 1994; Jenkins, 1992; Lanthier & Furman, 1992). On the other hand, certain family stresses, such as marital disruption, family conflict, and residential instability, have been associated with negative sibling relationship outcomes (Brody, Stoneman, & Burke, 1987; Brody et al., 1994; Jenkins, 1992; Stoneman, Brody, Churchill, & Winn, 1999). It appears that specific child and family stresses result in different sibling relationship outcomes (Dunn et al., 1994; Lanthier & Furman, 1992), depending on the source of the stress and the family context. 3.4.4. SES group differences and sibling disability research Returning to the question posed earlier, is economic hardship important when conducting or interpreting research on siblings of children with intellectual disabilities? Perhaps we really should be asking why economic hardship would not be important for these siblings when the developmental
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literature has demonstrated that factors associated with family economic status are so important for children’s development. The most parsimonious answer is that children who have siblings with disabilities are children first and are therefore subject to the same family and developmental processes that affect all children. As such, if two groups of siblings differ in the economic situation of their families, one might expect the children in lower SES, economically disadvantaged homes to have more psychosocial, behavioral, and academic problems than the children in more affluent homes. If we learn that the children from lower-income homes have siblings with intellectual disabilities, it is unlikely that we would conclude that the group differences were due to the disability status of one sibling rather than to economic hardship. Yet, reaching the later conclusion is the risk inherent in studying sibling groups drawn from populations that have been demonstrated to consistently differ in economic advantage.
3.5. Family form, race, and ethnicity 3.5.1. Group differences in family form In addition to being more likely than other children to live in families that are economically disadvantaged, children with intellectual disabilities are more likely than children without disabilities to live with single parents, especially in mother-headed households (Cohen & Petrescu-Prahova, 2006; Fujiura & Yamaki, 1997, 2000; MacInnes, 2008). Family status has a close relationship to poverty; single parent, mother-headed households of children with disabilities are disproportionally poor (Emerson, 2003; Fujiura & Yamaki, 2000). Additionally, less educated parents of children with disabilities have higher rates of divorce (Urbano & Hodapp, 2007). In the United States, less than half of children with disabilities live with two married biological parents (45.8% as compared with 62.3% of typically developing children; Cohen & Petrescu-Prahova, 2006). Recruiting comparison families from the general population is likely to result in a sample that contains proportionally more traditional two-parent families. McHale et al. (2006) suggested that it is important to examine the ways in which different family forms provide a context for sibling relationships. In single parent and divorced households, older sisters may take on additional responsibilities including caring for younger siblings (Hetherington, 1989; Weiss, 1979). Kier and Lewis (1998) found that variations in young children’s sibling interactions in different family forms were associated with the gender combination of the sibling pair, with sister-sister pairs evidencing greater amounts of play and social engagement under the stress of parent separation. In divorced families, brothers’ relationships have been found to be more hostile and aggressive than those in two-parent homes. Conversely, sisters in divorced homes were characterized as caring and warm.
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Deater-Deckard et al. (2002) studied sibling relationships in five different family forms (single mother, two biological parents, and three forms of blended families) and found variations in sibling positivity and negativity that were associated with family form, as well as differences between siblings who were and were not biologically related. Associations between sibling relationship quality and individual child outcomes differed depending on the family form in which the children lived. 3.5.2. Group differences in race and ethnicity Across Western countries, children with intellectual disabilities are more likely to be from minority families (Fujiura & Yamaki, 1997, 2000; Leonard & Wen, 2002; Oswald et al., 2001; Yeargin-Allsopp et al., 1995). Minority status does not cause disability, but minority children are more likely to have an intellectual disability because they are more likely to be poor (Fujiura & Yamaki, 1997, 2000). Racial/ethnic differences also have been found for children with an ASD although findings have not been consistent across studies and vary depending on ASD subtype (Newschaffer et al., 2007). The variability in disability prevalence that occurs across ethnic/racial groups makes it probable that the disability sibling groups recruited by researchers will differ from comparison siblings in race and ethnicity. This is important because sibling roles and relationships often differ by race, culture, and ethnicity (Weisner, 1993; Zukow, 1989). Mexican-American children often spend more time with siblings than do Euro-American siblings (Updegraff et al., 2006). African American and Latino siblings, living in families where mutual kin support is emphasized, are more likely than Euro-American siblings to assume care responsibilities for their brothers and sisters, although these patterns differ by sibling gender (e.g., Brody, Stoneman, Smith, & Gibson, 1999; Lobato, Kao, & Plante, 2005; McHale, Whiteman, Kim, & Crouter, 2007; Updegraff et al., 2006). It is also possible that the effects on siblings of stresses, such as financial hardship, may differ by race/ethnicity (McHale et al., 2007; Updegraff et al., 2006). The relevant racial or ethnic groups for sibling disability researchers will differ by geographic location and are arguably more important in heterogeneous societies. Gold (1993), in her Canadian sample, equated groups on ethnicity: Canadian, British Isles, Eastern European, mixed, or other. Singhi, Malhi, and Dwarka (2002), working in India, reported sibling group membership by religion: Hindu or Sikh. In the United States, African-American families and recent immigrants often live in multigenerational households, or live with extended family or in households with fluid boundaries (Hunter & Ensminger, 1992). Ishizaki et al. (2005), in their Japanese sample, noted that households in which multiple generations live in the same home create distinctive contexts for sibling relationships, the effects of which are unexplored.
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4. Methodological Considerations in Conducting Comparison Group Sibling Research 4.1. Statistical controls as a ‘‘solution’’ to dissimilar sibling groups When sampling and matching strategies fail to produce similar groups, researchers often use statistical remedies to artificially equate groups on important uncontrolled variables. In group comparisons, this is usually accomplished by executing an analysis of covariance (ANCOVA). Although these procedures are in common use, there is substantial concern about their appropriateness and effectiveness in addressing group inequalities. Miller and Chapman (2001) argued that the statistical literature ‘‘overwhelmingly condemns’’ (p. 47) the use of ANCOVA to control for group confounds that may reflect ‘‘meaningful substantive differences that are attributable to group membership’’ (p. 40). They argued that when researchers use ANCOVA to compare naturally occurring groups, such as children with and without siblings with disabilities, spurious statistically significant findings can result. When the variance of the covariate is removed from the grouping variable, in this instance the presence of a sibling with a disability, this variable is altered in such a substantial way that it no longer retains its original meaning. The residual variable analyzed by the researcher has an ‘‘uncertain relationship’’ (Miller & Chapman, 2001, p. 45) to the original grouping construct. It is argued that the meaning of the new variable cannot be ascertained or meaningfully articulated (Lynam, Hoyle, & Newman, 2006; Miller & Chapman, 2001). Lord (1967) was one of the first psychometricians to caution against the distortions that can result, which have been referred to as ‘‘Lord’s paradox’’ (e.g., Wainer, 1991). Cook and Campbell (1979) cautioned that statistical adjustments to compensate for nonequivalent groups were strongest when researchers know all meaningful ways in which study groups differ, as well as ways in which multiple confounding variables interact to create specific outcomes. Obviously, this is almost never the case. Furman and Lanthier (2006) noted that in sibling research the confounding variables to be statistically controlled are correlated with numerous other variables, known and not known; measured and not measured. They cited associations among family size, parent education, maternal IQ, divorce risk, SES, and religiosity as examples. Attempting to control for one of these variables has implications for the others. They cautioned that even if researchers knew all of the confounding variables, statistical control procedures in sibling research would not lead to accurate inferences (Furman & Lanthier, 2006).
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Using post hoc statistical controls as the primary strategy for dealing with differences between sibling groups can result in analyses with a very large number of covariates. Miller and Chapman (2001) gave an example of covarying poverty, parental education, and class size in a study of differences between black and white school districts, examining the effects of teacher quality: ‘‘. . .by the time that all of those covariates that are surely meaningfully correlated with it (teacher quality) have been partialed out. . . One could not conclude anything about the original variable’’ (p. 46). This is a clear articulation of the multiple covariate issue that I once described in a less sophisticated manner as a ‘‘blind leap into the realm of mystical thought’’ (Stoneman, 1989). In their study of sibling sensitivity to family conflict, Nixon and Cummings (1999) included three covariates in their sibling study. Following the above logic, it is difficult to determine the meaning of the residual variables that were actually analyzed in this study. Covariance strategies are best used in random experiments. Unfortunately for research clarity, siblings cannot be randomly assigned to disability groups. Rather than using ANCOVA, Miller and Chapman (2001) recommended incorporating confounding variables into study analyses as additional substantive variables. When naturally occurring variables are confounded (gender and body weight in Lord’s example), it is argued that there is no statistical means to unconfound the variables. Lord (1967, p. 305) summed up the problem as follows: ‘‘. . .there simply is no logical or statistical procedure that can be counted on to make proper allowances for uncontrolled preexisting differences between groups. . . The usual research study of this type is attempting to answer a question that simply cannot be answered in any rigorous way on the basis of available data.’’ Disability status is hopelessly confounded with multiple important child and family demographic variables. Family income, parent education, parent employment status, family form, race/ethnicity, and child sex, for example, are meaningfully associated with child intellectual disability status. When disability sibling groups differ on these variables, numerous statisticians have warned that it is not possible for researchers to covary the effects away. For researchers whose research questions require comparison groups of typically developing siblings, several strategies exist to decrease demographic difference between disability and comparison groups.
4.2. Strategies for matching comparison samples Levy-Wasser and Katz (2004) wrote, ‘‘. . .the need to achieve conformity between the experimental and control groups created many problems for the investigators and is one of the main reasons for the small sample’’ (p. 93). This lament is common because equating sibling groups can be very difficult. Three primary strategies have been used by disability sibling researchers to equate groups of siblings: (1) case-by-case matching, (2) group matching,
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and (3) restricted sampling. Case-by-case matching is the most precise and difficult strategy to implement. Each sibling pair is individually matched to comparison siblings on a set of predefined variables (e.g., child age, sex, race). In group matching, the means (and sometimes the ranges) of a set of variables in the disability sibling group are matched to the comparison group, but individual sibling dyads are not matched. The third strategy, restricting the sampling frame, reduces differences between sibling groups by limiting the population from which siblings are recruited, resulting in a sample that is homogeneous on specific preselected variables. Each matching strategy has its strengths and weaknesses. Case-by-case matching of sibling dyads provides a precise remedy to a limited number of potentially important confounding variables, but is extremely tedious and time consuming to implement. Instituting case-bycase matching on all relevant variables is seldom practical (even if it were desirable). Coleby (1995), for example, attempted to match each sibling of a child with a disability to a comparison child using community health records with a series of 12 ordered matching priorities: age, school, sex, family size, birth order, age spacing, neighborhood, father occupation, maternal education, unemployment, marital status, and maternal age. This would seem to be an impossible task. Coleby does not report data indicating how successful this matching strategy was in creating comparable groups in her study. For some researchers, even after exhaustive search, case matches cannot be found for all siblings. Lobato, Miller, Barbour, Hall, and Pezzullo (1991) executed case-by-case matching on the number of children in the family, relative birth order, age and sex of both siblings, age spacing, and parent marital status. Two siblings of children with disabilities were lost to the sample because appropriate comparison siblings could not be found. Similarly, Cuskelly and Gunn (2003) were unable to find a case-by-case match for one sister of a child with Down syndrome. Kaminsky and Dewey (2001) had 21 siblings who were excluded from their study because of inadequate matching. Group matching is less taxing to implement than case-by-case matching. Stores et al. (1998, p. 230) described this strategy: ‘‘children in the four groups were not matched individually, but an attempt was made to obtain groups with similar age ranges, sex distributions, and socioeconomic backgrounds.’’ Group matching carries an implicit assumption that groupmatched variables function as main effects, rather than in interaction with other variables. An example provided in Stoneman (1989) can be modified to illustrate this point. Work such as that of Hetherington (1989) has documented that divorce interacts with child gender to create increased risk for sons. Consider a hypothetical study in which the intellectual disability sibling group is constituted of 10 male siblings who have divorced mothers and 10 female siblings from two-parent families. A group-matched comparison sample is recruited consisting of 10 boys from intact families
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and 10 girls with divorced mothers. The groups are equated for child gender and marital status. In this example, negative outcomes for the brothers of children with intellectual disabilities would probably be attributed to the effects of ‘‘intellectual disability’’ on male siblings, but could plausibly be caused by the effects of divorce on sons instead. The final strategy, limiting the sampling frame, avoids the complexities of matching sibling groups on specified variables, but sacrifices generalizability of findings to all but the specific subgroups studied. Finding families which fit the requirements of a limited sampling frame can also be difficult. A frequent approach is only to recruit siblings who are older than the child with a disability (e.g., Bischoff & Tingstrom, 1991; Dyson, 1989; Gamble & McHale, 1989; Mandleco et al., 2003; McHale & Gamble, 1989; Stoneman et al., 1989; Summers et al., 1997). Other researches have limited their samples to younger siblings (e.g., Stoneman, Brody, Davis, Crapps, & Malone, 1991), same-sex sibling pairs (Stoneman et al., 1989, 1991), twoparent families (e.g., Cuskelly & Gunn, 2006), or only male children with disabilities (e.g., Gold, 1993). One compromise is to use a combination of strategies. Researchers can match dyads on a case-by-case basis on variables considered to be most important, use group matching on other, secondary variables, and limit the sampling frame to a specific subgroup of families. Cuskelly and Gunn (2006) recruited case-by-case matches based on sibling gender, age and birth order in the family. Families were group matched on approximations of family size and father’s occupation. This strategy also was used by Stoneman et al. (1991), who recruited same-sex sibling pairs in which the older sibling had an intellectual disability (a limited sampling frame). Comparison siblings were matched case by case on sex, ages of both siblings, race, income, and parent education. Group matching was executed on marital status, family size, sibling spacing, and family birth order. There is no perfect matching strategy and no simple ‘‘cookie cutter’’ approach to constituting comparison groups. At the very least, it is imperative that the researcher clearly describe the strategy or strategies that were used and provide detailed information on the demographic composition of each study group. In an imperfect world, this allows the reader to judge the appropriateness of the comparison group and to interpret findings accordingly.
5. Same or Not Too Different from Average? 5.1. Small differences? To borrow a question posed about intellectual disability research by Brooks and Baumeister over a quarter century ago (1977), ‘‘How much greater is our understanding. . .as a result of all this research activity?’’ (p. 407).
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Tables 8.1 and 8.2 represent almost 50 research papers that have compared siblings of children with intellectual disabilities to typically developing siblings. What have we learned? Rossiter and Sharpe (2001) conducted a meta-analysis of 25 studies published between 1972 and 1999 that compared siblings of children with intellectual disabilities/autism to siblings of typically developing children. They concluded that the difference between siblings of individuals with intellectual disabilities/autism and comparison siblings, both related to individual sibling outcomes and to qualities of the sibling relationship, is ‘‘small at best’’ (p. 71). The small differences that emerged favored the comparison siblings. Rossiter and Sharpe cautioned that meta-analysis strategies can never rule out the possibility that a third variable is responsible for the pattern of findings across studies. Tables 8.1 and 8.2 suggest that variables such as family income, marital status, race/ethnicity, and parent education, among others, often have not been addressed in disability sibling research. Because the populations of families with and without children with intellectual disabilities are known to vary on these demographic factors, and these factors are known to affect the psychosocial development of children, it is plausible that even the small differences in sibling outcomes detected by Rossiter and Sharpe were caused by a third variable, or a combination of several of these demographic third variables which tend to covary in families. Given the large quantity of missing information reflected in the tables, one must make the cautious assumption that the population differences between families of children with and without intellectual disabilities (i.e., income, family form) were probably present in the samples comprising the majority of disability sibling studies where key demographic data were not fully reported. At the very least, it is not possible to attribute the sibling group differences identified in individual studies, or in Rossiter and Sharpe’s meta-analysis, to the presence of a child with an disability when the sibling groups also plausibly differed on other important variables (in addition to disability status of one of the siblings).
5.2. ‘‘Average’’ siblings are a statistical creation and probably exist only on computer printouts Even if studies achieve methodological rigor, and sibling samples are demographically similar, what does it mean (or what does it matter) that siblings of children with and without intellectual disabilities differ from each other? Disability sibling researchers who execute comparison group studies that include a sample of typically developing siblings are in essence trying to determine whether siblings of children with disabilities differ from a population average. The average sibling and the average sibling relationship in the general population are not real constructs, in that there is no identified set of sibling behaviors or characteristics defined a priori as belonging to average
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siblings. Is the average sibling the child living in an upper middle class suburban neighborhood, spending after school time in music lessons, sports, and other enriching activities? Or is it the child living in an urban housing project whose mother keeps her children in the apartment after school to keep them safe from crime and danger? Or, consider the rural child who has numerous farm tasks to complete after school, working until dark to help the family farm succeed. Is this child the average sibling? The average sibling and the average sibling relationship are statistical constructions, defined by the mean and standard deviation of siblings in a given sample, recruited to represent a certain population. A statistical average might include all three of the siblings described above, along with a sibling who recently experienced divorce and a child who stays home with a younger sibling after school while her or his mother works. For researchers who compare sibling outcomes to normative data (e.g., Giallo & Gavidia-Payne, 2006; Hastings, 2003a,b, 2007; Orsillo, McCaffrey, & Fisher, 1993), children providing data for the test norms become the average siblings (even if they are only children and do not have siblings). For most researchers, the first sibling described above, whose upper middle class parents have arranged for many enriching after school activities, is closest to the idea of an average sibling, since these children are more similar to the children of university faculty and to the children in the neighborhoods in which most faculty live. These siblings also more closely fit the concerns raised by Farber (1959, 1960, Farber & Jenne´, 1963) described earlier in this chapter, who cautioned that the presence of a child with a disability in the family would create caregiving burdens for siblings, restricting their ability to participate in enriching activities with friends. These concerns have different relevance for the average sibling sequestered in an apartment in an urban housing project or the average sibling working nights and weekends on the family farm. Returning to the question posed earlier, what does it mean if siblings of children with disabilities are found to differ from average children? If for the moment one accepts the small differences identified in the Rossiter and Sharpe (2001) meta-analysis, these modest differences suggest that for siblings of children with and without disabilities, there are two distributions of outcomes with means offset by differing degrees depending on the study, with very large areas of overlap. Therefore, although the statistical means for the disability and comparison samples may shift significantly in one direction or the other, most siblings of children with disabilities are indistinguishable from children in the comparison group. Similarly, most sibling relationships involving children with disabilities lie within the overlap of distributions, making their relationships impossible to differentiate from those of typically developing children on many parameters. Overlapping distributions with small mean differences lead to an interpretation that children with and without siblings with disabilities are more similar than they are different.
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6. The Case (or the Lack Thereof) for Sibling Interventions Researchers often offer recommendations for practice when they discuss the findings of their sibling studies. A reader examining the discussion sections of the comparison group research literature could reach almost any conclusion about the intervention needs of siblings of children with intellectual disabilities and ASDs. Coleby (1995, p. 424) concluded that for siblings: ‘‘Their distress may be underestimated and they should be included in counseling from an early stage. . .’’ Verte et al. (2003, p. 202) reached a different conclusion: ‘‘. . .we can trust that they will find their own way without the burden of all kinds of interventions.’’ Coleby (1995, p. 424) warned that: ‘‘Proposals to involve siblings in plans of care for children with disabilities should proceed with caution.’’ Fisman et al. (2000, p. 374) made the opposite recommendation: ‘‘This study underlines the importance of including brothers and sisters of disabled children in the family and in treatment planning.’’ Clearly, there is no consensus in the comparison group research literature concerning siblings’ needs for intervention or treatment participation. There is no strong argument to be made supporting the notion that all siblings of children with intellectual and related disabilities need interventions or therapies. This does not mean, of course, that individual children or individual sibling pairs might not need and/or benefit from individually tailored interventions. Dyson (1989) reached a similar conclusion, recommending that interventions should be focused on children experiencing adjustment difficulties, regardless of whether or not those children have siblings with disabilities. Emerson (2003) presented a strong case for interventions to reduce poverty in families of children with intellectual disabilities. Although his recommendation was targeted at supporting the family as a whole, it has important relevance for siblings. Sibling relationships are socialized in the context of the family (Stoneman, 1998; Stoneman & Brody, 1993). Strong marriages, cohesive families, and low family conflict forecast positive sibling relationships, high self-concepts, and the absence of behavior problems in siblings of children with a range of disabilities (e.g., Benson, Gross, & Kellulm, 1999; Cuskelly & Dadds, 1992; Giallo & Gavidia-Payne, 2006; Lynch et al., 1993; Mandleco et al., 2003; McHale & Gamble, 1989; Rivers & Stoneman, 2003; Rodrigue et al., 1993; VanRiper, 2000). Relieving financial stress and supporting strong families through family support programs and other mechanisms promise substantial benefits for siblings. Researchers (Baker, McIntyre, Blacher, Crnic, Edelbrock, et al., 2003; Cuskelly et al., 1998; Hastings, 2007; Lecavalier, Leone, & Wiltz, 2006)
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have stressed the negative effects of challenging behaviors on families of children with disabilities, and on siblings. Family chaos impinging on sibling well-being can develop when a child destroys property, attacks family members, incessantly cries or screams, and/or tantrums at home and in public. These disruptive behaviors over time can create fatigue, social isolation, and frustration, negatively affecting the ability of the family to support its members (Fox, Vaughn, Wyatte, & Dunlap, 2002; Worchester, Nesman, Mendez, & Keller, 2008). One of the most powerful interventions for the benefit of siblings may be the implementation of positive behavior supports focused on reducing the challenging behaviors of the child with a disability (Lucyshyn, Dunlap, Horner, Albin, & Ben, 2002). Investing resources in in-home behavioral interventions may be a less obvious sibling intervention than sibling counseling or support groups, but the potential impact of family-based positive behavior supports may surpass the impact of these more traditional sibling interventions. An important factor in considering the need for sibling interventions and in determining the nature of interventions is the conceptualization of desired sibling outcomes. Ideal outcomes for the sibling relationship and for individual siblings are culturally determined (Weisner, 1993). There is not one ideal sibling relationship. Desired sibling outcomes are defined by families, consistent with cultural and religious mores and with community norms. As such, the need for sibling interventions depends on the perspectives of parents about whether or not their children are developing and behaving in ways that are consistent with family expectations and desires, rather than on whether their children differ from average siblings.
7. Concluding Thoughts The past 20 years of research comparing siblings of children with and without intellectual disabilities have yielded only modest advances in our knowledge base. One factor diminishing the contribution of this body of research is the popularity of comparison group research combined with a failure of many researchers to adequately address important population differences between families of children with and without disabilities. Children with intellectual disabilities are more likely to be male, and their parents are more likely than parents in the general population to be financially stressed, single parents, from minority groups, with lower levels of parent education. Unless these population differences are purposely addressed by the researcher, the resulting sibling groups will probably not be equivalent on numerous characteristics in addition to the disability status of a child. These oversights are magnified by inattention by many researchers to variables demonstrated to be important in the general sibling
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literature, such as sibling age, sibling sex, sex combinations, relative birth order, and age spacing. Furman and Lanthier (2006) note that the effects of sibling constellation variables are only modest in size, but so are the effects of the presence in the family of a child with a disability. Cuskelly et al. (1998), following the lead of Longo and Bond (1984), suggested that the greater the care that disability sibling researchers take in constituting comparison groups, the less likely they are to find differences between groups. The disability sibling literature seems to reflect a confidence on the part of at least some researchers that intellectual disability and ASDs are such powerful constructs that their influence on siblings overshadows other potential sources of influence. To paraphrase a question posed earlier, why would we believe that children who are siblings of children with intellectual disabilities are so different from other children that the findings of the developmental literature would not apply to these children? There is, of course, no reason to accept this belief. It is probable that the tendency of researchers to ignore confounding variables is not based on a conscious belief that these variables are unimportant, but is rather a product of expediency. Conducting comparison group sibling studies is difficult and resource intensive. Even the most perfectly designed study is subject to multiple interpretations because of the inability to control, or even to be aware of, all extraneous variables that can contribute to sibling outcomes (Furman & Lanthier, 2006). Comparison group designs are probably over-used in disability sibling research. Examining group differences is less enlightening than understanding family processes. The experience of having a sibling with a disability is highly variable across families. Similarly, there is wide variability in psychosocial outcomes for siblings of children with disabilities (e.g., Hannah & Midlarsky, 1999; McHale et al., 1986). Many of the most interesting and informative research questions are focused on understanding this variability, both across families and across time, by examining within-group processes and outcomes (Cuskelly, 1999; Hastings, 2007; Stoneman, 2007). These important research questions do not require comparison groups. In comparison group research, the sibling relationship is often studied apart from the families in which the children live. It is only by examining the development of individual children and the socialization of sibling relations in the family context that we can begin to understand the complexity and richness of the social forces that shape this relationship. It is through this process-oriented research that we will truly begin to understand the effects that intellectual disability, and different etiologies of intellectual disability, have on children and families. For siblings of children with a disability, explanatory models must include recognition of the pervasive impact of child characteristics associated with these conditions on the entire family system. These influences, which often differ depending on the etiology of the child’s intellectual disability, create a complex network of
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direct and indirect effects which shape and mold the sibling relationship and which determine outcomes for individual children (see Stoneman, 1998 for a discussion of the effects of disability etiology on siblings). In Stoneman and Brody (1993), we offered a family process model to attempt to explain the socialization of sibling relationships of children with intellectual disabilities in the family context. Our model posited that the sibling relationship is directly affected by specific characteristics of each of the individual siblings, characteristics of the family in which the children live, and childrearing strategies utilized by the children’s parents/primary caregivers. The childrearing strategies used by parents, in turn, are influenced by several factors, including characteristics of the parents, the family emotional climate, and characteristics of the individual siblings. In addition to the components included in the model, factors originating outside the family (i.e., social support, school) exert undeniably important influences on family functioning, including the relationship between siblings. Important information will be gained as we as researchers continue to move away from the simplistic (but very difficult to answer) questions about whether siblings of children with disabilities differ from siblings of typically developing children, and instead focus our energies on understanding family and societal processes that shape individual child and sibling relationship outcomes. Every child and every sibling pair experiences unique family circumstances. Some are of major import, such as the serious injury of a parent in a traffic accident, multiple relocations as parents achieve career advancement, or an elderly grandparent who moves into the child’s home. The presence of one or more siblings with a disability in the family is a circumstance experienced by only a small proportion of children. Similar to other life circumstances, some families of children with disabilities grow stronger and support the positive development of all of family members, including siblings. Other families struggle with the realities of parenting a child with a disability and are not able to provide siblings with what they need to thrive. Within the same family, some children may adjust well and others not so well. As we better understand the family processes that lead to positive and negative sibling outcomes, we will be better able to support families in the essential tasks of effectively nurturing all of their children and in supporting positive, loving sibling relationships.
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Verte, S., Roeyers, H., & Busse, A. (2003). Behavioural problems, social competence and self-concept in siblings of children with autism. Child: Care, Health & Development, 29, 193–205. Volling, B. L., Herrera, C., & Poris, M. P. (2004). Situational affect and temperament: Implications for sibling caregiving. Infant and Child Development, 13, 173–183. Wainer, H. (1991). Adjusting for differential base rates: Lord’s paradox again. Psychological Bulletin, 109, 147–151. Wang, M., Turnbull, A. P., Summers, J. A., Little, T. D., Poston, D. J., Mannan, H., et al. (2004). Severity of disability and income as predictors of parents’ satisfaction with their family quality of life during early childhood years. Research and Practice for Persons with Severe Disabilities, 29, 82–94. Weber, J. L., & Stoneman, Z. (1986). Parental nonparticipation in program planning for mentally retarded children: An empirical investigation. Journal of Applied Research in Mental Retardation, 7, 359–369. Weisner, T. S. (1993). Ethnographic and ecocultural perspectives on sibling relationships. In Z. Stoneman, & P.W. Berman (Eds.), The effects of mental retardation, disability, and illness on sibling relationships (pp. 51–83). Baltimore, MD: Paul H. Brookes. Weiss, R. S. (1979). Growing up a little faster: The experience of growing up in a single-parent household. Journal of Social Issues, 35, 97–111. Wolf, L., Fisman, S., Ellison, D., & Freeman, T. (1998). Effect of sibling perception of differential parental treatment in sibling dyads with one disabled child. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 1317–1325. Worchester, J. A., Nesman, T. M., Mendez, L. M. R., & Keller, H. R. (2008). Giving voice to parents of young children with challenging behavior. Exceptional Children, 74, 509–525. Yeargin-Allsopp, M., Drews, C. D., Decoufle´, P, & Murphy, C.C (1995). Mild mental retardation in black and white children in metropolitan Atlanta: A case-control study. American Journal of Public Health, 85, 324–328. Yeargin-Allsopp, M., Rice, C., Karapurkar, T., Doernberg, N., Boyle, C., & Murphy, C. C. (2003). Prevalence of autism in a US metropolitan area. Journal of the American Medical Association, 289, 49–55. Zukow, P. (Ed.) (1989). Sibling interactions across cultures: Theoretical and methodological issues New York, NY: Springer-Verlag.
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Family Support Interventions for Families of Adults with Intellectual and Developmental Disabilities Tamar Heller and Abigail Schindler Contents 1. Introduction 2. Impact of Having a Family Member with I/DD 3. Family Support Public Policies and Programs 3.1. Family support movement 3.2. Financial support 3.3. Impact of consumer direction on persons with disabilities and families 3.4. Programs targeted to aging caregivers 3.5. Family support 360 4. Family Support Psychosocial Interventions 4.1. Future planning 4.2. Support groups 4.3. Support coordination and direct service program interventions for older caregivers 4.4. Sibling support interventions 5. Conclusion Acknowledgments References
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Abstract Though families are considered the primary provider of support to people with intellectual and developmental disabilities (I/DD), only a small amount of I/DD funding in the United States goes toward offering assistance to these families. In addition, formal interventions typically target families of children with I/DD, which are no longer available when the individual enters adulthood. This
Department of Disability and Human Development, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois 60608-6904, USA International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37009-3
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2009 Elsevier Inc. All rights reserved.
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chapter reviews the literature on family support interventions for families caring for adults with I/DD. It first examines the impact of lifelong caregiving and the support needs of these families. It then draws attention to various interventions currently available for these families, including systemic federal and state family support public policies (such as cash subsidies, and consumer-directed supports), as well as group level psychosocial interventions (such as support groups, future planning interventions, and support coordination). The review calls attention to the need for more intervention research that is methodologically sound and that addresses not only the perspective of parents but also that of other family members (such as siblings) and the person with disabilities.
1. Introduction Families are typically considered the primary provider of support to people with intellectual and developmental disabilities (I/DD) (Fujiura, 1998; Fujiura & Braddock, 1992; Turnbull & Turnbull, 2000). In 2006, approximately 60% of individuals with I/DD in the United States lived with family caregivers, comprising an informal system of residential care that was five times greater than the formal out-of-home residential care system (Braddock, Hemp, & Rizzolo, 2008a). Studies have shown that most individuals with disabilities prefer to remain at home, a preference family members typically share ( Johnson, Kastner, & the Committee/Section on Children with Disabilities, 2005). However, as people with I/DD age, support from family members tends to decline as parents age and the need for formal services increases (Bigby, 2003). Life expectancy for adults with developmental disabilities has risen dramatically over the last 80 years. Reports show that mean age at death now ranges from the late 50’s (for those with more severe disabilities or Down syndrome) to 71 years for adults with mild to moderate intellectual disabilities (Bittles, Petterson, Sullivan, Hussain, Glasson, et al., 2002; Patja, Iivanainen, Vesala, Oksanen, & Ruoppila, 2000). This compares with an average life expectancy of 15 years for males and 22 years for females with intellectual disabilities in 1931 (Carter & Jancar, 1983). In 2006, women aged 40–44 ended their childbearing years with an average of 1.9 children, as compared to 3.6 children in the 1950s (Dye, 2008). This aging trend in combination with the low rate of childbirth results in both an extended period of caregiving for adults with I/DD and fewer family members from which to draw support. In the United States, over 25% of family caregivers of individuals with I/DD are over the age of 60 years and another 35% are ages 41–59 years (Braddock et al., 2008a). With the large number of people on waiting lists for residential services and with the current fiscal crisis preventing further expansion of residential services, the number of adults with I/DD living at
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home is likely to continue to increase. This increased demand for services will directly impact the capacity of state service delivery systems, which already are struggling to address the needs of 70,000 persons with I/DD awaiting residential services (Prouty, Smith, & Lakin, 2006). Whether or not individuals with I/DD live in the family home, their family members often provide informal support including both social– emotional and instrumental support that complements or even supplements the formal supports available. These informal supports are invaluable to these individuals, since they are related to higher morale, decreased loneliness and worry, feelings of usefulness, lower mortality, better survival and recovery rates from acute conditions, and reduced institutionalization (Hooyman, 1983; Mendes de Leon, Glass, Beckett, Seeman, Evans, et al., 1999; Mendes de Leon, Gold, Glass, Kaplan, & George, 2001). The comprehensive commitment, affective support, and individual oversight that informal social supports provide cannot be truly replicated with formal social supports (Bigby, 2000). Thompson (2004) found that 78% of adults with all types of disabilities age 18 years and older in the United States who receive long-term care at home get all their care exclusively from unpaid family and friends. Despite this, only a fraction of the funding allotted for individuals with I/DD in the United States goes toward offering assistance for those who provide this essential informal support (Rizzolo, Hemp, Braddock, & Schindler, 2009). This chapter reviews the literature on interventions to support families caring for adults with I/DD. First, it examines the impact of lifelong caregiving on families and support needs of families. Secondly, it focuses on interventions aimed at different levels ranging from systemic federal and state family support public policies (such as cash subsidies, consumerdirected supports) to group level psychosocial interventions (such as support groups, future planning interventions, support coordination) targeted to specific subpopulations addressing various life transitions. The subpopulations include aging parents, adult siblings, and the adults with I/DD themselves. Table 9.1 summarizes peer-reviewed empirically tested interventions that primarily targeted families of adults with I/DD and includes the methods and results.
2. Impact of Having a Family Member with I/DD While most families adapt well to having a family member with I/DD, the lifelong impact of providing care to a family member with I/DD can affect the economic, health, and psychosocial well-being of family members. The well-being of mothers was explored in two large population-based samples, the Midlife Development in the United States (MIDUS) and the Wisconsin Longitudinal Study. Findings indicated that
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Table 9.1 Authors
Family support interventions for adults with intellectual and developmental disabilities Intervention
Consumer direction Caldwell Home-Based Support (2007) Services Program (HBSSP); selfdirected; service facilitation; benefits up to three times social security (SS)
Caldwell (2006)
HBSSP; self-directed services; service facilitation; amount of benefits up to three times SS
Subjects
Research design
Measures
Findings
Nine intervention families of adults with intellectual and developmental disabilities (I/DD) in a consumerdirected program
Qualitative exploration of experiences of families participating in a consumerdirected support program
Semistructured inhome interviews
209 intervention; þ 85 control families of adults with I/DD who applied for the HBSSP; randomly assigned by lottery
Cross-sectional comparison of economic, health, and social outcomes between families of adults with I/DD in the HBSSP and families on waiting list
Surveys: (a) household income, (b) functioning of people with I/DD, (c) outof-pocket disability expenses, (d) employment, (e) physical/mental health, (f ) healthcare access, (g) social activities, and (h) leisure satisfaction
Benefits expressed by families fit within three central themes: (1) family financial benefits, (2) benefits from respite and personal assistance services, and (3) prevention of institutional placements (1) Caregivers of adults in the program reported: (a) fewer out-ofpocket disability expenses, (b) greater access to health care, (c) engagement in more social activities, and (d) greater leisure satisfaction (2) Lower-income families reported better mental
Caldwell and Heller (2007)
HBSSP; self-directed services; service facilitation; benefits up to three times SS
38 intervention; þ 49 control families (at Time 3) of adults with I/DD who applied for the HBSSP; randomly assigned by lottery
Longitudinal study of impact of a HBSSP at three points over a 9year period: Time 1 (1991), Time 2 (1995), and Time 3 (2000). Cross-sectional comparison of groups at Time 3
Surveys: (a) unmet service needs, (b) service satisfaction, (c) community participation, and (d) caregiving burden
Caldwell and Heller (2003)
HBSSP; self-directed services; service facilitation;
97 families who had applied to the HBSSP and who received paid
Cross-sectional survey of families using paid respite or personal
Surveys: (a) caregiving burden, satisfaction, and
health and access to health care than controls (1) Over time, families in the program experienced (a) decreased unmet service needs, (b) higher service satisfaction, increased community participation of individuals with disabilities, and (c) decreased caregiver burden (2) At Time 3, families in the program had fewer unmet needs and higher service satisfaction than did families on the waiting list (1) More control by families of their respite/personal assistance services
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(continued)
Table 9.1
(continued)
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Authors
Heller and Caldwell (2005)
Intervention
Subjects
Research design
Measures
benefits up to three times SS
respite or personal assistance services
assistance services, measured impact of (1) level of control of services and (2) hiring relatives versus others to provide services
self-efficacy, (b) service satisfaction, (c) community involvement, maladaptive behavior, and health status of adult with I/DD, (d) maternal employment, (e) staff turnover, (f ) control of respite/ PA services, and (g) unmet service needs
HBSSP; self-directed services; service facilitation; benefits up to three times SS
301 families; þ 835 controls who applied for the HBSSP; randomly assigned by a lottery
Impact of HBSSP on out-of-home placement over an 8-year period using placement date provided by the state Department of Human Services
Placement data: (a) at home with family, (b) out of home in any type of residential setting, and (c) institutional placement
Findings
was associated with (a) increased service satisfaction, (b) increased community involvement of individuals with I/DD, and (c) increased employment of mothers (2) Hiring relatives to provide services was associated with the increased community involvement of individuals with I/DD Individuals with I/DD enrolled in HBSSP were less likely than controls to move into an out-ofhome placement, particularly to an institution
Heller, Miller, and Hsieh (1999)
HBSSP; self-directed services; service facilitation; benefits up to three times SS
Future planning Botsford Workshop sessions and Rule for mothers (2004) 305
78 intervention; þ 146 controls who applied for the HBSSP; randomly assigned by a lottery
Impact of HBSSP on family caregivers and adults with I/DD used surveys þ phone interviews: (a) pretest, posttest design compared participants’ outcomes over 4 years and (b) posttest design compared groups at Time 2
Survey: (a) family Support Index, (b) service satisfaction, (c) caregiving self-efficacy, (d) caregiver burden, (e) out-of-home placement plans, (f ) community integration, (g) monthly wage, and (h) phone interviews
(1) Participants had fewer unmet needs and used more services than controls (2) Participant caregivers were more satisfied with the services their relative received, experienced greater selfefficacy, and were less likely to desire an out-of-home placement than the control group (3) Participants with I/DD experienced increases in community integration and monthly wage
13 intervention; þ 14 control mothers of adults with I/DD; applicants to
Pre- and posttest group comparison
Pre- and posttest telephone interviews: (a) age-related changes; (b)
(1) Increase in knowledge and awareness of resources for planning (continued)
Table 9.1
(continued)
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Authors
Intervention
Subjects
Research design
support group matched on age and marital status
Heller and Caldwell (2006)
1-day legal and financial training for both groups, 5, 2-h peer coled monthly sessions for intervention families and adult with I/DD using ‘‘The future is now’’ curriculum
Support coordination Bigby et al. Two programs (2002) ‘‘options for older
29 intervention; þ 19 control families of adults with I/DD; program applicants randomly assigned by lottery
Pre- and 1-year follow-up posttest with intervention and control groups
44 parent caregivers over age 50 years
Postintervention process-outcome
Measures
Findings
function, health, and behaviors of adult offspring; and (c) knowledge of resources, awareness of planning resources, and identification of service needs Pretest and 1-year follow-up surveys of caregivers: (a) future planning activities; (b) caregiving burden, satisfaction, selfefficacy; (c) discussion with individuals with I/DD; (d) choicemaking of individuals with I/DD; and (e) barriers to future planning
(2) Stronger sense of confidence and competence in the future plan (3) Advance in their own future planning process
Interviews: (a) clients, (b) service
(1) 59% of families reported that they
(1) Increased family completion of a letter of intent (2) Increased actiontaking on residential planning (3) Increased actiontaking on the development of a special needs trust (4) Decreased caregiving burden (5) Increased daily choice-making of individuals with I/DD
families,’’ Case management Discretionary funds for older caregivers on immediate needs and future planning; targeted caregivers and adult with I/DD; proactive intervention and crisis prevention; support workers; community education
Bigby and Ozanne (2005)
Compared a specialist programs for older caregivers to mainstream disability case coordination programs
(44-file audit; 20-interviews randomly selected) in two sites
evaluation; quantitative and qualitative data
10 educational session attendees (randomly selected from 99 for phone survey) 2 case managers
307
4 key DHS personnel 64 older family caregivers (age over 55 years) in case coordination programs (44 in specialist and 20 in mainstream program) for parents of adults with I/DD
coordinators, (c) case managers, and (d) key DHS personnel
File audits
Phone survey: (a) clients and (b) service providers
Two group processoutcome comparisons evaluating the programs; qualitative and quantitative data
Focus groups: agencies Interviews and file audits
were better able to make plans and decisions about the future, including the process of separation and letting go (2) 48% of families reported that their trust or access to formal services increased (3) 66% of people with ID had increased access to out-of-home day and recreational activities
(1) Few significant differences exist between the two types of programs (2) The older caregiver programs provided community education (continued)
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Table 9.1
(continued)
Authors
Intervention
Subjects
Research design
Measures
Findings
functions which the mainstream programs did not (3) Case managers in the specialist programs were more likely to organize/facilitate activity outside the home Support groups Mengel Needs assessment of et al. parents of adults (1996) with I/DD and/or mental illness used to design 5, 2-h weekly support and educational meetings
Smith et al. (1996)
Focus group determined the
33 family members from 24 families from a community agency
30 parents of adults with I/DD (17
Postintervention evaluation of intervention
Process-outcome evaluation with
Questionnaires: (a) family characteristics and (b) informal resource needs Feedback from group members
Survey questionnaire
(1) Participants found the group as a whole helpful
(2) Participants reflected that the group gave them new perspectives (3) Many found that caregiving parents of children with I/DD and mental illness had more in common than they originally thought (1) Parents found most helpful:
intervention psychoeducational support group that met for six sessions for 1.5 h. Didactic presentation and parent discussion
lived with their child, 13 had children who lived elsewhere)
quantitative and qualitative data
Only those interventions formally evaluated and reported in journals with outcome measures were included.
(a) information about future planning, (b) developing awareness of formal services, (c) hearing the concerns of other parents, and (d) sense of camaraderie (2) Parents found less helpful: (a) preparing them to cope with age-related changes and (b) enabling them to call on support network for assistance
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while mothers show increased negative affect after receiving their child’s diagnosis of I/DD, over time families adapt well to having a child with I/DD. Still, mothers are likely to experience fewer visits with friends and an economic impact reflected in lower maternal rates of employment, lower family savings, and greater family-related work role strain (Ha, Hong, Seltzer, & Greenberg, 2008; Seltzer, Greenberg, Floyd, Pettee, & Hong, 2001). The research on health effects of caregiving for adults with I/DD is mixed. While some studies have shown little impact on their health (Chen, Ryan-Henry, Heller, & Chen, 2001; Seltzer et al., 2001), several recent studies have noted higher rates of certain health conditions and poorer access to health care for subgroups of mothers (Caldwell, 2008; Magana & Smith, 2006, 2008). Data from the National Health Interview Survey showed higher rates of depressive symptoms, heart problems, and arthritis in Latina mothers who were caregivers of adults with I/DD versus other Latina mothers in the same age group (Magana & Smith, 2006, 2008). The mothers caring for an adult with I/DD were also less likely to see a general practitioner, see or afford a mental health professional, or afford prescription medicines. Similar findings existed for Black American mothers caring for adults with I/DD, as these mothers were more likely than other Black American mothers to have arthritis and diabetes and also reported more difficulty in affording medication and mental health professionals. In a study of mothers coresiding with their adult child with I/DD who had applied for a consumer-directed program, no differences existed in physical health between these mothers and the general population of mothers (Caldwell, 2008). However, the mental health of midlife caregivers (45–54 years of age) and older caregivers (older than 65 years) was worse than national norms. Caldwell (2005) notes that this may be associated with two key periods: transitions to adulthood of individuals with disabilities and transitions when aging caregivers are no longer able to provide care. However, one alternative explanation is that the mothers who applied for the program had worse mental health than mothers who did not apply for the program. A range of contextual factors influence the health and well-being of families of adults with I/DD, including child characteristics, socioeconomic status, minority cultural context, and extent of social support networks (Greenberg, Seltzer, Krauss, & Kim, 1997; Heller, Hsieh, & Rowitz, 2000; Hong, Seltzer, & Krauss, 2001; Magana, Seltzer, & Krauss, 2004; Orsmond, Seltzer, Greenberg, & Krauss, 2006; Orsmond, Seltzer, Krauss, & Hong, 2003). Greater unmet needs for services have contributed to poorer mental health (Caldwell, 2008), caregiving burden (Heller & Factor, 1993), and to desire for an out-of-home placement (Heller & Factor, 1993). Caldwell (2008) found that poorer access to health care was associated with poorer mental and physical health among mothers caring for an adult
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with I/DD. Unmet needs for services and out-of-pocket disability-related expenses appeared to pose difficulties for working age caregivers in affording the financial costs of health care for themselves. Key service needs reported by families include respite services; case coordination; transportation; recreation services; and information regarding housing, financial plans, and guardianship (Heller & Factor, 1993; Heller, Miller, & Factor, 1999; Pruchno & McMullen, 2004). Despite these findings, many families affirmatively choose to have their adult son or daughter live at home into adulthood (Seltzer, Larson, Makuch, & Krauss, 2000). Additionally, many families also report positive benefits of having a family member with I/DD living with them, including receiving companionship and help with household chores (Heller, Miller, & Factor, 1997).
3. Family Support Public Policies and Programs 3.1. Family support movement The family support movement emerged in the 1970s, emphasizing the provision of information, emotional support, and instrumental support to families in order to build on existing strengths (Dunlap, 2000; Kagan, 1996; Zigler & Black, 1989). This movement reflects a theoretical shift from providing treatment for individuals with some perceived deficiency to empowering an entire family within their own social context as a form of prevention (Kagan, 1996). The term family support is conceptually ambiguous due to the wide range of programs which employ this terminology (Dunst & Trivette, 1994). However, a review of family support literature revealed that the guiding principles for family support can be organized into approximately six categories: (1) enhancing a sense of community, (2) mobilizing resources and supports, (3) sharing responsibility and collaboration, (4) protecting family integrity, (5) strengthening family functioning, and (6) adopting proactive program practices (Dunst, 1995). Family supports for families of adults and children with I/DD are services provided with the purpose of enabling the individual to continue living at home. Specific supports may include financial support, respite services, home health care, family education and training, family counseling, support groups, and flexible financial assistance (Freedman & Boyer, 2000). In the United States, only a small amount of spending on I/DD services is typically directed toward individuals living in the family home. In 2006, family support spending accounted for only 5% of total I/DD spending (Rizzolo et al., 2009). Many of these programs primarily focus on families of children versus adults with disabilities (Freedman & Boyer, 2000).
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3.2. Financial support Families of children with I/DD, work fewer hours, quit working, have more severe financial problems, and are less likely to take a job than families of other children with disabilities and families of nondisabled children (Anderson, Larson, Lakin, & Kwak, 2002; Parish, Seltzer, Greenberg, & Floyd, 2004). Out-of-pocket costs for the care of an adult with I/DD can be substantial (Caldwell, 2006; Fujiura, Roccoforte, & Braddock, 1994). Hence, support for families of an adult with a disability often comes in the form of financial assistance including cash subsidies, vouchers, reimbursement, or direct payments to providers (Turnbull, Stowe, Agosta, Turnbull, Schrandt, et al., 2007). Two types of financial support are essential components of the family support system in the United States: cash subsidies and the Medicaid Home and Community-Based Support Waiver. Cash subsidies are direct payments to families which give them increased control over services and supports most suitable for their particular family member. Nationally, 24 states offer cash subsidies or vouchers to families and 18 states have Supported Living waivers. Forty eight states and DC provide state or Medicaid-funded supported living or personal assistance services (PAS) for people with I/DD living in their own or family home (Braddock et al., 2008a). Community-based services from Medicaid include the Home and Community-Based Support (HCBS) Waiver, PAS, and case management. The Medicaid Home and Community-Based Services Waiver (HCBS), enacted in 1981 (Pub. L. 97-35), permits states to waive certain Medicaid requirements in order to receive federal Medicaid cost share for ‘‘noninstitutional’’ services (Lakin, Prouty, Alba, & Scott, 2008). The first year this program was enacted, only two states provided the waiver as an option, but it has since expanded to become the principal funding source for services that support individuals living in the family home (Lakin et al., 2008; Rizzolo, Hemp, & Braddock, 2006). In 2006, the HCBS Waiver financed 70% of all family support services in the United States, with over 45% of recipients of the waiver living with family members (Braddock, Hemp, & Rizzolo, 2008b; Lakin, Prouty, & Coucouvanis, 2007). HCBS Waiver services vary by state, and may include individualized funding for case management, homemaker assistance, home health aides, personal care, residential and day habilitation, transportation, supported employment, home modification, respite care, and therapies (Rizzolo et al., 2009). Use of this waiver has played a significant role in financing the supports necessary for community living as an alternative to institutionalization (Lakin et al., 2008). They have provided more options for families who would like to keep their adult with I/DD in the family home. In fact, 21 states have restructured their HCBS waivers into distinct ‘‘supports’’ and ‘‘comprehensive’’ programs. While ‘‘comprehensive’’ programs allow for 24-h community residential care for individuals with I/DD,
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‘‘supports’’ waivers are geared toward preventing out-of-home placement. These waivers operate at around 20–50% of the cost of a comprehensive waiver and encourage families to act as nontraditional providers of care. Seven of these programs target adults with I/DD, 11 target both children and adults with I/DD, and just three target only children (Smith, Fortune, & Agosta, 2006). Over the past decade many of these programs both in the United States and internationally are based on consumer-directed models, in which persons with disabilities and their families define, choose and direct their own supports (Lundsgaard, 2005; Tilly, Wiener, & Cuellar, 2000; Tritz, 2005). Recent developments, such the Robert Wood Johnson Cash and Counseling demonstration projects (Phillips et al., 2003) and the Independence Plus initiative (Crowley, 2003), have catalyzed the development of new consumer-directed programs across disability and age groups. For people with physical disabilities, consumer direction in PAS has existed for over 30 years. Consumer direction for the elderly and persons with I/DD, however, is a more recent development.
3.3. Impact of consumer direction on persons with disabilities and families Research has shown a positive association between perception of control and health and disability among elders (Hofland, 1988; Rodin, 1986) and those with I/DD (Neely-Barnes, Marcenko, & Weber, 2008). The shift from social benevolence to individual capabilities and autonomy, and human rights (Powers, Sowers, & Singer, 2006) has resulted in less focus on health and safety and more on independence and individual control of supports. This change is more subtle for people with I/DD, who are often perceived as passive recipients of help and in need of protection from abuse. However, their access to person-directed approaches is increasing, including use of delegated decision making in which family members provide supported decision making. Studies comparing consumer-directed and agency-directed services found consumer-directed services resulted in greater service satisfaction and fewer unmet service needs among individuals with physical disabilities (Beatty, Richmond, Tepper, & DeJong, 1998; Benjamin, Franke, Matthias, & Park, 1999; Benjamin & Matthias, 2001; Benjamin, Matthias, & Franke, 2000; Doty, Kasper, & Litvak, 1996); and no significant differences in health status or safety (Beatty et al., 1998; Foster, Brown, Phillips, Schore, & Carlson, 2003). However, some have reported psychological benefits concerning feelings of empowerment (Beatty et al., 1998) and perceived quality of life of individuals with disabilities (Foster et al., 2003). However, relatively few empirical studies have examined consumer-directed supports for adults with
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I/DD; instead, studies have focused on consumer-directed supports for individuals with physical disabilities. The research on consumer-directed supports for people with I/DD has primarily focused on the impact of support on families, though a few studies also included the impact on individuals with I/DD. Since the majority of persons with I/DD live with family members, in practice, consumer direction is often linked with supporting families (Simon-Rusinowitz, Mahoney, Loughlin, & Sadler, 2005). Some programs have specifically targeted families, such as the existing cash subsidy family support programs within the developmental disabilities system (Braddock et al., 2008b) and many family support programs within the aging service systems (Feinburg & Newman, 2005). Among families of persons with I/DD, outcomes of consumer-directed programs have included studies of cash subsidies for families of children with I/DD in Michigan and Minnesota (Herman, 1991, 1994; Meyers & Marcenko, 1989; Zimmerman, 1984) and studies of the Illinois HomeBased Support Services Program (HBSSP), an HCBS Waiver program, which offers funding of up to three times Social Security Income (currently $1274). This program allows adults with I/DD and/or their families to direct their supports with the aid of support brokers and fiscal intermediaries that reimburse personal assistants (PAs). It also allows the individuals to hire family members, excluding spouses. Families in the Michigan cash subsidy program for families of children experienced decreased family stress and increased ability to meet their relative’s needs (Herman, 1991, 1994; Meyers & Marcenko, 1989). Minnesota’s cash subsidy program for families of children with I/DD showed similar results, with parents reporting improved caregiving conditions as a result of direct cash subsidies (Zimmerman, 1984). The series of studies of the Illinois HBSSP included longitudinal data over a 9-year period (1991–2000) on families receiving the consumerdirected program and those on the waiting list. During this period, the program used a lottery to draw eligible participants from the applicant pool, enabling a random design. Using data provided from the Illinois Department of Human Services, findings indicated decreased out-of-home placement, particularly institutional placements over a period of 8 years among 1136 families (Heller & Caldwell, 2005). In a longitudinal study of the program’s first 4 years including 224 subjects, participants had fewer unmet needs and used more services than the waiting list applicants. Participant caregivers also were more satisfied with the services their relative received, experienced greater self-efficacy, and were less likely to desire an outof-home placement than the control group. Participants with I/DD experienced increases in community integration and monthly wages. In a further follow-up over a 9-year period of 38 HBSSP participants, Caldwell and Heller (2007) found that over time, families in the program experienced decreased unmet service needs, higher service satisfaction, decreased
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caregiver burden, and increased community participation of individuals with disabilities. Families in the program had fewer unmet needs and higher service satisfaction than did families on the waiting list. In a cross-sectional analyses comparing the economic, health, and social impacts of the HBSSP program on 209 randomly selected families in the program with 85 families on the waiting list for the program, program participants reported fewer out-of-pocket disability expenses, greater access to health care, engagement in more social activities, and greater leisure satisfaction. There also appeared to be greater impacts on lower-income families; these caregivers reported better mental health and access to health care than did similar caregivers on the waiting list. Experiences of families with relatives with I/DD participating in a consumer-directed support program were also explored qualitatively. Financial benefits, benefits from respite and personal assistance services, and prevention of undesirable institutional placements were major themes that emerged and triangulated with the quantitative research (Caldwell, 2008). In the United Kingdom, an evaluation of the way in which families of persons with various disabilities use the direct payment program, which allows families of various disabilities to receive a direct cash payment instead of using community services, revealed that most families used this money to help pay for personal assistant services and related expenses (Stainton, 2002). Interviews with participants in this program were overwhelmingly positive. Participants felt that the direct payments gave them increased choice and empowerment, increased flexibility in scheduling services, a greater sense of trust for personal assistant workers (since they were able to choose and train them themselves), and feelings of confidence and optimism (Stainton & Boyce, 2004). Family members felt that the direct payments relieved their anxiety about going out or working because they were more confident in the care their family member was receiving using the direct payments. Flexibility in hiring, including the ability to hire family and friends, is a key determinant of interest in consumer direction (Mahoney, Desmond, SimonRusinowitz, Loughlin, & Squillace, 2002; Simon-Rusinowitz, Mahoney, & Benjamin, 2001; Simon-Rusinowitz, Mahoney, Desmond, Shoop, Squillace, et al., 1997). Among 139 programs in the United States surveyed, 80% allowed hiring family (Doty & Flanagan, 2002). At least half of all paid employees in consumer-directed programs in California, Florida, New Jersey, and Arkansas are family members (Stainton & Boyce, 2004). When consumers are able to hire their own PAs, they often hire those they already know, including friends and family members. Hence, PAs are more likely to give emotional as well as physical support, leading to higher life satisfaction (Stainton & Boyce, 2004). In the California program for people with various disabilities, consumers who hired families and friends experienced more satisfaction and stability with their personal assistants and less abuse than did the consumers who hired strangers (Matthias & Benjamin, 2008).
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Among families of people with I/DD in the Illinois consumer-directed support program, those participants who hired families and friends had significantly higher leisure satisfaction than families who used agency direct support workers (Caldwell & Heller, 2003). Hiring friends and relatives to provide services was also associated with increased community involvement of individuals with I/DD (Caldwell & Heller, 2003). For adults with I/DD, hiring of parents could result in less self-determination since they may desire more independence from parents in adulthood. Additional research is needed to address the influence of hiring parents, other family members, and friends on the outcomes of consumer-directed support. Also, none of the research has included the perspectives of people with I/DD, which are critical to understanding the impact of consumer direction on their lives.
3.4. Programs targeted to aging caregivers For some family members of adults with I/DD, care has primarily been considered a family responsibility, and they remain out-of-touch with formal disability services (Knox & Bigby, 2007). While the use of formal disability services predicts lower caregiving time demands and lower perceived burden of parents, families of adults with disabilities are less likely to use these services than families of children (Haveman, Van Berkum, Reijnders, & Heller, 1997; Hayden & Heller, 1997; Smith, 2007). This may be because community services were not as readily available during the earlier years of some older families. These parents would have had very different experiences with the service system, with fewer services being available and the expectations for services likely to be lower (Haveman et al., 1997). Older family caregivers are often reluctant to ask for assistance due to a history of mistrusting services, previous bad experiences or rejection of services, and fear that their family member will be ‘‘taken away’’ (Walker & Walker, 1998). Several programs have been designed as outreach to this population of family caregivers. In the United States, the 1973 amendments to the Older Americans Act required the establishment of Area Agencies on Aging (AAA) in each state. AAAs are funded through a combination of federal funds through the Older Americans Act, state funds, and private grants. These organizations are responsible for coordinating and providing a wide range of services and support to older Americans. Its family support program, The National Family Caregiver Support Program (NFCSP), enacted under Title III-E of the Older Americans Act Amendments of 2000 and in its reauthorization in 2005, has funded states to serve caregivers of individuals age 60 years and older and grandparent caregivers of minor children. Language was included in the 2005 reauthorization that was intended to expand coverage to older caregivers of family members of any age with I/DD, but the language still remains unclear about the applicability to caregivers of adults with I/DD.
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Supports for older caregivers may include information on future planning, referrals to agencies for respite care and community services, mailing lists, home modifications, and financial assistance ( Janicki et al., 1996/2003). Another program that bridges the aging and disability service systems is the Aging and Disabilities Resource Center (ADRCs) programs jointly developed in 2003 by the Administration on Aging (AoA) and the Centers for Medicare and Medicaid (CMS). These centers are designed as coordinated, ‘‘one-stop’’ informational centers. As of 2006, at least 14 of the 43 centers targeted families and individuals with I/DD. Little research exists on the impact of these programs on adults with I/DD or on their families.
3.5. Family support 360 The family support 360 (FS 360) initiative, sponsored by the U.S. Department of Health and Human Services’ Administration on Developmental Disabilities (ADD), focus on the needs of families of both children and adults with I/DD. ADD is presently providing 21 ‘‘implementation’’ grants along with 9 ‘‘planning’’ grants. The implementation grants are awarded to organizations that serve as ‘‘one-stop centers’’ for families of individuals with I/DD. These centers work directly with targeted families to assist them in locating and navigating public human service agencies, as well as to connect them with private community organizations. Centers may assist families with a wide range of needs, including accessing health care, childcare, early intervention, education, employment, marriage education, transportation, housing, respite care, and assistance in maintaining parental rights (Administration on Developmental Disabilities, 2005). Many of these centers address underserved families, such as those from minority backgrounds, those living in poverty, and military families. Most of the grants serve families of children and youth, though a few cover all ages. Little research is available on the impact of these programs on families of adults with I/DD.
4. Family Support Psychosocial Interventions Beyond federal and state public programs, interventions for families of adults with I/DD include education and training, counseling, and support groups. These interventions may be targeted at specific groups like aging family caregivers or adult siblings of individuals with I/DD. The following section explores interventions targeting family members of adults with I/DD, including future planning, support groups, and support coordination and direct services.
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4.1. Future planning A primary concern for aging family caregivers is the future safety and security of their relative with I/DD after their death. More than half of these families neglect to make concrete future plans (Freedman, Krauss, & Seltzer, 1997; Heller & Factor, 1994), which should include legal and financial planning, guardianship, and future living arrangements. Without adequate plans and supports in place, individuals with I/DD may be given emergency placements in inappropriate settings, and inadequate financial and legal safeguards when primary caregivers can no longer provide care. Future planning initiatives target this need by helping aging families and adults with I/DD plan for the future to assure quality care and avoid crises for their relative after their death. A number of future planning projects targeted families of adults with I/DD. These include the Family Futures Planning Project (Susa & Clark, 1996), the Planned Lifetime Advocacy Network (PLAN) (Etmanski, 1997), the Family-to-Family project (Griffiths, 1997), the Psychoeducational Group Intervention for Aging Parents (Botsford & Rule, 2004) and the Rehabilitation Research and Training Center (RRTC) and Aging with Developmental Disabilities Family Future Planning Project (Heller & Caldwell, 2006). The Family Futures Planning Project (Susa & Clark, 1996) out of Rhode Island was a 10-session program for older family caregivers. Families were given information on future planning and a facilitator assisted families with developing a plan and building a support network. The 18 participating families were able to make change and progress in the process of future planning. In British Columbia, PLAN (Etmanski, 1997) is a nonprofit organization devoted to helping families of individuals with I/DD in future planning and in caring for their relative with a disability. Their six-step guide for developing a future plan includes clarifying your vision, building relationships, controlling the home environment, preparing for decision making, developing your will and estate plan, and securing your plan. This intervention combines workshops, technical assistance, and interaction with mentor families and paid facilitators to develop future plans. In addition to in-person workshops, PLAN has introduced online and telelearning workshops on registered disability savings plans, and wills, trusts, and estates. Using these mediums, parents are able to get critical information their own homes (Planned Lifetime Advocacy Network, 2008). The Family-to-Family project in Massachusetts (Griffiths, 1997) involved the development of eight family-to-family centers across the state. Each center varied in the supports they provided as part of this intervention. Presentations, resource manuals, and parent support groups were developed and enacted regarding future planning issues. These issues
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included special needs trusts and wills, funding sources, housing options, home ownership, consumer-controlled housing, circles of support, and self-advocacy. The Psychoeducational Group Intervention for Aging Parents (Botsford & Rule, 2004) was a professionally led psychoeducational group intervention for older parents caring for an adult with I/DD at home. The intervention provided caregivers the opportunity to express concerns about the future for their offspring. Three sessions were devoted exclusively to parents expressing concerns and interacting, while the remaining three sessions included speakers on legal, financial, and other future planning issues. The effectiveness of the intervention was assessed using a randomized experimental design with a fairly small sample (N ¼ 27, of which 13 received the intervention). Two weeks after the training, parents participating in the program showed increases in knowledge and awareness of resources for planning, a stronger sense of confidence and competence in their ability to make future plans, and progress in making residential and legal plans for their family member with I/DD. In a study that included a longer-term longitudinal randomized design with a larger sample, the Rehabilitation Research and Training Center on Aging with Developmental Disabilities Family Future Planning Project, examined the impact of its ‘‘Future is Now’’ curriculum. The curriculum involves training of both family members and the person with I/DD. It is based on a person-centered planning approach and a peer support model which includes adults with I/DD and families as coleaders in the training. The intervention studied consisted of a legal/financial training session followed by five additional small-group workshops. Pretest and 1-year follow-up surveys to 49 families (29 in the intervention and 19 control) indicated that the intervention families were more likely to complete letters of intent, take actions on residential planning, and develop special needs trusts (Heller & Caldwell, 2006). In addition to these concrete future plans, the intervention also led to decreased caregiving burden and increased opportunities for daily choice-making of individuals with I/DD. The major limitation noted was that families did not involve siblings of the adults with I/DD in the planning process. Also, there were no data reported on the perspectives of the adults with I/DD.
4.2. Support groups Parent or professionally led support groups are common for parents of children with I/DD. Studies have found that parents in these support groups are highly satisfied with the sense of agency and belonging the groups provide (Solomon, Pistrang, & Barker, 2001). Participants have reported improved parenting skills, a reduced sense of isolation, and a stronger sense of emotional support (Kerr & McIntosh, 2000; Law, King, Stewart, & King, 2001).
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With the exception of a few studies on support groups for aging caregivers (Mengel, Marcus, & Dunkle, 1996; Smith, Majeski, & McClenny, 1996), little data are available on support groups for parents of adults with I/DD. One study revealed that parents of adults with mental illness were more likely to participate in support groups than were parents of adults with I/DD (Greenberg et al., 1997). The authors hypothesized that this may be because mothers of adults with I/DD are more likely to have more extensive social supports already through family and friends than do parents of adults with mental illness. The parents of adult children with developmental disabilities (PACDD) group, part of the parents helping parents (PHP) network is designed to support parents and adult siblings of people with I/DD. This group holds monthly seminars on topics such as in-home support services, challenging behaviors, and social security. In addition to these more formal seminars, the group meets for potluck dinners every few months. These informal times offer a chance for parents to fellowship and create a network of support (Parents Helping Parents, 2008). Many parent support groups employ an online format, utilizing message boards and listservs to help parents make connections with others in similar situations. Many of these support groups are disability-specific, and connect parents of children with I/DD, Down syndrome, Autism, and a variety of other disorders. Very few of the in-person or online support groups have been evaluated for their impact on participants. Two studies examining support groups for aging caregivers of adults with I/DD provide some limited data that show promise, but do not include much empirical data (Mengel et al., 1996; Smith et al., 1996). Smith et al. (1996) describe a psychoeducational support group program attended by 30 aging parents of adult offspring with I/DD established with assistance from a focus group of practitioners and parents. The six sessions, which were led by professionals, aimed to provide information on future planning and to help families cope with their caregiving demands. Participants appraised the sessions very positively and were most satisfied with the opportunities provided them for networking and sharing experiences with other families. Parents who coresided with the adult with I/DD were more interested in information on future planning; whereas parents whose adult child lived out of the family home were most interested in information on quality of residential care. Mengel et al. (1996) evaluated a support and education group targeting 33 aging caregivers of individuals with I/DD and mental illness. The group was held in a senior service center, so the population targeted did not necessarily reflect those families that are connected to the disability services network. The group held three meetings that provided educational support from experts in permanency planning, residential options, and community services. The majority of parents attending the group had a son or daughter
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with I/DD, with only about a quarter of offspring having mental illness, and one having a traumatic brain injury. The remaining two meetings were designed for parents to get acquainted with one another and offer emotional support. While no formal measures were used to assess the efficacy of this group, anecdotal reports indicate that this support group contributed to shared coping strategies between parents, dispelled myths about mental illness and I/DD, and provided insight and self-understanding for group members. An indication that the group may have been successful in meeting needs of families was that 15 members of the support group continued to meet once a month after the first five sessions held at the senior center. While psychoeducational support groups for aging caregivers hold promise as effective means of helping aging caregivers acquire information and network with other families, the empirical research to date is very scant regarding their outcomes.
4.3. Support coordination and direct service program interventions for older caregivers Several projects in the United Kingdom and Australia provide models for support coordination and direct family support services for aging caregivers of adults with I/DD (Bigby, Ozanne, & Gordon, 2002; Carers FIRST, 2008; Sharing Caring Project, 2008). The Sharing Caring Project (SCP) in the United Kingdom is an organization that supports family caregivers over 55 years of age. It has produced information packets for caregivers, ‘‘lifebooks’’ for people with I/DD, and partnered with the Sheffield National Health Service (NHS) Trust to provide direct preventative support for older carers. They have also partnered with the Asian Disability Project to help ensure culturally competent supports (Sharing Caring Project, 2008). Carers FIRST in the United Kingdom is an organization dedicated to comprehensive help and support to caregivers of all types through information and resources, discussion, advocacy, one-to-one support, and groups where caregivers can meet others in similar situations. One of their projects, ‘‘Older Carers of People with Learning Disabilities,’’ targets aging caregivers of people with I/DD (Carers FIRST, 2008). A pilot program from 1995–1999 in two regions of Australia titled ‘‘Options for Older Families’’ provided intensive support coordination on immediate needs and future planning and access to discretionary funds to older caregivers of adults with I/DD. The support coordination model was proactive intervention and crisis prevention. In addition, the program provided support workers and community educational sessions for the families and support coordinators. Interviews with consumers and social workers, file audits, focus groups, and a telephone survey after the intervention revealed that the strong relationship between case workers and families had many benefits. A major benefit reported by 66% of families
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was increased access to out-of-home activities and services for people with ID. Also, 59% of families reported that they were better able to make plans and decisions about the future, including the process of separation and letting go, and 48% of families reported that their trust or access to formal services increased (Bigby et al., 2002). Further study on this initiative revealed that there were few differences between the program targeted at older caregivers and ‘‘mainstream’’ programs that had older caregivers as clients (Bigby & Ozanne, 2005). While there have been a couple of reports of various projects comprehensively addressing aging caregivers as noted above, this study is one of few to report on an extensive evaluation of the program’s effectiveness. It highlights the need for effective brokering of services that can enable families to bridge both the aging and disability networks, determine support needs, and find providers and services.
4.4. Sibling support interventions Although siblings provide the most long-lasting relationships for adults with I/DD and provide considerable social support to them (Krauss, Seltzer, & Goodman, 1992), little data exist on interventions aimed at helping siblings in these roles. Research on the impact of having a sibling with I/DD has found mixed results, with some noting that having a sibling with I/DD may contribute to depression, loneliness, behavioral problems and low self-esteem (Bagenholm & Gillberg, 1991; Bischoff & Tingstrom, 1991; Cuskelly & Gunn, 1993; McHale & Gamble, 1989; San Martino & Newman, 1974). However, a meta-analysis of 25 studies relating to siblings of individuals with I/DD revealed that these siblings have experienced only modest negative effects, and the magnitude of these effects has traditionally been overstated (Rossiter & Sharp, 2001). Sibling relationships are considered unique in that they typically last longer than any other relationship in a person’s lifetime (Cicirelli, 1995). Adult siblings usually maintain high levels of involvement with their sibling with disabilities across the life course (Seltzer, Begun, Seltzer, & Krauss, 1991; Zetlin, 1986). Since individuals with I/DD often require lifelong care (Barron, McConkey, & Mulvany, 2006), their siblings are likely to take on caregiving roles in their later lives (Bigby, 1997, 2000; Freedman et al., 1997; Heller & Factor, 1994; Orsmond & Seltzer, 2000; Smith & Tobin, 1989). Though siblings are likely to become primary caregivers when parents can no longer provide care, most are not included in family discussions of future plans for their siblings with disabilities (Heller & Kramer, 2009; Krauss et al., 1992). A survey of 139 siblings of individuals with I/DD revealed that siblings who were most involved in future planning were older, provided more support to their siblings with disabilities and were more involved in disability activities. These siblings expressed concerns about the availability of services for their sibling with I/DD, helping their
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sibling’s voice to be heard, and their sibling’s health, safety, and happiness (Heller & Kramer, 2006). Major support needs of siblings were for support groups, workshops/training on how to assume caregiving responsibility, financial support, and printed material on making future plans. Interventions for adult siblings of people with I/DD have taken several forms, including conferences, support groups (both in-person and online), and information provision. Organizations for child and adult siblings currently exist in Australia, Belgium, Croatia, Guatemala, Greece, Iceland, Ireland, Italy, Japan, New Zealand, the United Kingdom, and the United States. These organizations sponsor various interventions for training, supporting, and providing information to adult siblings. Conferences offer adult siblings the opportunity to network with peers and to learn more about specific issues of concern like future planning, service provision, and balancing care responsibilities with the role of a sibling. Sibs, an organization in the United Kingdom designed to enhance the lives of child and adult siblings of individuals with I/DD, sponsors the ‘‘Working with Adult Siblings of Disabled People’’ conference, targeted for adult siblings and their supporters in London (Sibs, 2008). Beginning in 2007, the US national Sibling Leadership Network initiated an annual conference for adult siblings. Their first annual conference was held in Washington, DC, during which attendees heard from a wide range of experts about sibling issues across the lifespan, future planning, and policy (Heller & Kramer, 2007). The second conference was held in Ohio the following year. The goal of the Sibling Leadership Network is to provide opportunities for siblings of Americans with I/DD to increase their involvement in disability advocacy, policy-making and services concerning their siblings with disabilities. Its mission is ‘‘to provide siblings of individuals with disabilities the information, support, and tools to advocate with their brothers and sisters and to promote the issues important to them and their entire families’’ (Heller, Kaiser, Meyer, Fish, Kramer, et al., 2008). In addition to support groups, many organizations provide information for adult siblings on their web sites on issues of importance to siblings. All of the organizations mentioned in the previous section provide information for adult siblings, including the UK Sibs group, Supporting Illinois Brothers and Sisters, The Arc of the Greater Twin Cities, AHRC New York, Ohio Sibs, and the Fox Valley Sibling Support Network (AHRC, 2008; Sibling Support Project, 2008). Some organizations also provide workshops and training sessions for adult siblings. The Sibling Support network sponsors workshops for adult siblings that employ a large-group discussion format in which adult sibling participants learn from researchers, clinicians, and other siblings about topics of interest (Meyer, 2007). While siblings voice a need for supports in providing care and advocacy for their siblings with I/DD and some emerging promising practices exist to address these need, no studies to date have examined the effectiveness of
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these interventions. Furthermore, the research on these siblings has not included the perspectives of the adults with disabilities regarding their relationships with their siblings and the types of interventions that would be most useful to their family.
5. Conclusion While a large body of research exists on supportive intervention for families of children with I/DD, the literature on families of adults with I/DD is sparse. Literature examining the public support policies has mostly examined the effectiveness of consumer-directed programs. However, the empirical studies pertaining to families of adults with I/DD have mostly focused on one state: Illinois. This was a good state to study in the earlier years of its program since admission into the program was originally based on a lottery system. This research needs to expand to other states, and include the perspectives of adults with I/DD. One key issue is the impact of having families as paid caregivers on the self-determination and wellbeing of the adult with I/DD. The impact of training of families and individuals in directing their own supports has also not yet been investigated in this population. While there are various programs that provide support for families of adults with I/DD such as the HCBS Waiver, the National Caregiver Support Program, the family support 360 programs, and the Aging and Disability Resource Centers, the effectiveness of these programs for this population has not been studied or documented. For example, we know very little about the effectiveness of the Aging and Disability Resource Centers in providing ‘‘one-stop’’ support coordination for families of adults with I/DD. The psychosocial interventions that have received the most attention for families of adults with I/DD are those that address future planning. Some evidence exists that training of families can result in more plans being made and in increasing the choice-making of adults with I/DD. However, the research needs to be expanded to larger samples and to inclusion of the perspectives of the adult with I/DD. One of the biggest issues in future planning is the unavailability of suitable services, with the large waiting lists for residential services and with the growing deficits in state budgets. Given the health and economic impact that lifelong caregiving can have on mothers of adults with I/DD, particularly those from minority backgrounds or those living in poverty, we need to have programs that assist these mothers through financial supports and availability of adequate health care. In addition, we need to develop and test models of health promotion that can help mitigate depression and preventable health conditions.
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In addition to parents, siblings are starting to gain the attention of researchers and policy makers as they are likely to take over caregiving when parents can no longer take care and as people with I/DD are living longer. While various supports exist for siblings of adults with I/DD such as support groups, training, and web sites, research examining the outcomes of these efforts does not exist and is needed. Further few programs exist that are intended to directly benefit the skills and abilities of adults with I/DD. In the general population, there is the recognition that learning and development are lifelong processes, but this perspective does not seem to have influenced family support interventions. Rather, many of the family support interventions seem to have different goals such as assisting parents of adults with I/DDs with caregiving and future planning. One area of skill development and support that has been neglected is that of interventions that support persons with I/DD in caring for their elderly parents. Overall, the research presented has shown some evidence of the value of public policies that include consumer-directed family support, the benefits of helping families make future plans, and positive outcomes of psychoeducational support group and targeted case coordination strategies for older family caregivers. However, the research base is weak, often lacking in controlled studies and longitudinal designs. Much of the data reported only include outcome data following the interventions. The psychosocial interventions tend to include small samples and a fairly homogeneous population. Across the different type of interventions a need also exists for further research to increase our understanding of sociocultural differences among families. Such factors as poverty, immigrant status, race and ethnicity, and religion can influence families’ needs and the effectiveness of various interventions.
ACKNOWLEDGMENTS Support for this research was provided through the Rehabilitation Research and Training Center on Aging with Developmental Disabilities, National Institute on Disability and Rehabilitation Research (Grant No. H133B080009).
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Interventions Aimed at Improving Child Language by Improving Maternal Responsivity Nancy Brady,* Steven F. Warren,† and Audra Sterling* Contents 1. Responsivity is a Multilevel Construct 1.1. Molar responsivity 1.2. Molecular responsivity 2. Responsivity Relates to Child Outcomes 2.1. Language and communication outcomes 2.2. Responsivity in families who have a child with a disability 3. Interventions Aimed at Improving Responsivity 3.1. Interventions based on materials from the Hanen Center 3.2. Relationship focused intervention (RFI) 3.3. The playing and learning strategies (PALS) program 3.4. Responsivity components in language intervention studies 4. Summary and Conclusions Acknowledgments References
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Abstract Maternal responsivity, or the ways in which mothers provide for, interact with, and respond to their children, helps to shape their children’s development, including language development. In this chapter, we describe maternal responsivity as a multilevel construct with different measures appropriate for each level. Molar responsivity refers to aspects of interaction style such as affect that can best be measured with rating scales. Molecular responsivity refers to contingent maternal behaviors that occur in response to child behaviors; and are best reflected by the frequencies of occurrence of these contingent behaviors. Results of many studies have demonstrated that both molar and molecular responsivity are related to important child outcomes such as language development. Children of more responsive mothers tend to have better * {
Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, Kansas 66045, USA Director, Schiefelbusch Institute for Life Span Studies, University of Kansas, Lawrence, Kansas 66045, USA
International Review of Research in Mental Retardation, Volume 37 ISSN 0074-7750, DOI: 10.1016/S0074-7750(09)37010-X
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2009 Elsevier Inc. All rights reserved.
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outcomes. Based on these findings, interventions aimed at improving maternal responsivity and thereby child language outcomes have been developed and investigated through a number of studies. Results have shown positive outcomes for maternal responsivity and lesser secondary benefits to child language outcomes. Some of the qualities that appear associated with better outcomes include timing the interventions to co-occur with specific developments in child behaviors, teaching over a span of approximately 10–12 sessions, and designing lessons to be culturally sensitive to individual families.
A highly responsive mother reacts to her infant’s crying by offering soothing vocalizations, warmth, and affection. The infant soon stops crying and begins making cooing sounds, which in turn elicit soft vocalizations by the mother. So goes one of countless episodes in the all-important relationship between a young child and a responsive caregiver. The interactions that characterize this type of highly responsive relationship change over time in accordance with developments in the child’s behavioral repertoires. For example, as the infant begins to smile and produce a greater variety of sounds, the responsive mother is likely to react contingently and differentially to these behaviors. Such interactions between infant and primary caregiver play a foundational role in optimal communication and language development. In this chapter, we use the term responsivity to refer to how a parent responds to and provides for a child (most often mothers in our examples). The quantity and quality of maternal interactions with infants and young children has been shown to impact children’s communication and language development, as well as aspects of cognition and emotional development (Landry, Smith, Swank, Assel, & Vellet, 2001). Mothers who talk more have children who also talk more (Hart, 1991; Hart & Risley, 1995; Paavola, Kunnari, Moilanen, & Lehtihalmes, 2005). In contrast, children who experience long periods of relatively low maternal responsivity tend to show lower language development (Landry et al., 2001). In fact, the (thankfully) few cases of extreme language impoverishment have shown that very low levels of responsivity during early sensitive periods of development may permanently arrest some aspects of language development (Curtiss, 1977; Farran, 2001). Similarly, the quality of mother’s speech as well as nonspeech behaviors has been linked to some aspects of child communication development. For example, responding more often to a child’s initiations as opposed to redirecting the child to the adults’ focus of interest has been reported to facilitate early language development (McCathren, Yoder, & Warren, 1995). Other examples of language enhancing parent behaviors (such as ‘‘motherese’’ or ‘‘parentese’’) are at the heart of social interactionist accounts of early language development (Bates, O’Connell, & Shore, 1987; Bruner, 1977; Hoff-Ginsberg, 1990; Snow, 1991). These language enhancing parent behaviors have been documented across numerous cultures (Bornstein et al., 2008; Kartner et al., 2008). However, there is cultural variability
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in these behaviors and the variability reflects differences in underlying values and beliefs such as the value of child talkativeness or initiations (van Kleek, 1994). Relative use of language enhancing behaviors also reflects socioeconomic status, frequently indicated by parent (especially mother) educational attainment (Hoff, Laursen, & Tardif, 2008). That is, higher levels of educational attainment are linked to high levels of parent responsiveness. Similar observations had been made in terms of the impact of parental responsivity on children ‘‘at risk’’ for developmental disabilities (Warren & Brady, 2007). It can be admittedly difficult to disentangle the directionality of effect between maternal and child behaviors given the evidence of bidirectional effects within the dyad. Nevertheless, in this chapter we have chosen to focus on the maternal contribution to the dyadic equation because this serves as the vehicle for interventions intended to optimize responsivity. In this chapter, we discuss various key components of maternal responsivity drawing in part on our research on the effects of maternal responsivity on the development of children with fragile X syndrome (FXS). We then focus the remainder of the chapter on interventions aimed at enhancing responsivity to facilitate child development. We conclude by summarizing the common aspects of effective interventions and offer suggestions for further research on improving child communication development through improved maternal–child interactions.
1. Responsivity is a Multilevel Construct Responsivity refers to how a parent responds to and provides for a child. Throughout the remainder of this chapter we will refer specifically to maternal responsivity because the bulk of research and intervention has been focused on maternal–child interactions. However, we can think of no reason why this literature would not apply to fathers, other relatives, and caregivers in general who spend time interacting with young language learning children. Maternal responsivity can operate at different levels of analysis. Warren and Brady (2007) described three levels: general responsivity, molar responsivity, and molecular responsivity. General responsivity refers to basic caregiving. Mothers may be viewed as generally responsive if they provide for the basic needs of a child. For example, if the child is well fed, kept safe, and comfortable, the mother is being responsive to basic biological needs. In addition, at this most general level, the mother may seek out appropriate services for her child and advocate for her child’s needs. Although general responsivity is clearly important for child welfare, much of the research about the links between responsivity and child language attainments has
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focused on more specific aspects of caregiver–child interaction. We have used the terms molar and molecular responsivity to describe these levels of caregiver–child interaction. These levels are defined and discussed in the following sections.
1.1. Molar responsivity Molar responsivity describes the affective aspects and verbal interaction style components of mother–child interactions. For example, a mother may be viewed as responsive when she displays qualities such as ‘‘warmth’’ or ‘‘positive affect’’ toward her child (cf. Landry, Smith, Swank, & MillerLonear, 2000). These qualities of interaction can be described and measured through the use of rating scales. For example, rating scales were developed and used by Mahoney and colleagues to describe maternal responsiveness/ sensitivity, affect, achievement orientation, and directiveness (Kim & Mahoney, 2004, 2005). Studies have reported a positive relationship between these qualities of maternal interaction and child outcomes. Using a Likert-type scale called the Maternal Behavior Rating Scale, mothers of children with disabilities were found to be less responsive, have lower affect scores and to be more directive than mothers of the typically developing children (Kim & Mahoney, 2004). In addition, these authors reported significantly less engagement in young children with developmental disabilities, compared to typically developing peers. The researchers performed both correlations and regression analyses to test for significant relationships between maternal responsivity and child engagement. Their results indicated that more responsive and affective mothers had children with higher engagement scores. Directiveness was not significantly related to child engagement. Earlier research by Mahoney, conducted with mothers of children with Down syndrome, had reported that directive maternal behaviors actually had positive effects on children’s behaviors, if the directiveness was related to a topic of interest and engagement by the child (Mahoney & Neville-Smith, 1996). Additional examples of molar responsivity are demonstrated by sensitivity to specific changes in child development. Maternal adjustments in reaction to child behaviors are examples of responsivity because they demonstrate sensitivity to and adjustment toward the child’s perceived level of development. For example, the terms ‘‘motherese’’ or ‘‘infant/ child-directed speech’’ describe use of exaggerated prosody, higher pitch, slower rate, and repetitious speech toward infants (Fernald, 1993), as well as older individuals perceived as having cognitive disabilities (Nind, Kellet, & Hopkins, 2001). However, these distinctive speech patterns typically dissipate as the child grows older (D’Odorico, Salerni, Cassibba, & Jacob, 1999). That is, mothers appear to adjust to developmental changes in the child. D’Odorico et al. (1999) found that mothers decreased their use of
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conversational devices, or utterances without referents, used to maintain a child’s attention (e.g., ‘‘no’’?) and increased their use of object-referenced speech (e.g., ‘‘that’s a telephone.’’) between the ages of 11 and 16 months. This is the age span during which most babies transition from babbling to first words. Mothers’ utterances were relatively stable before and after this age period, suggesting that mothers may have been fine-tuning their speech to reflect child changes. Highly negative correlations between child vocabularies and mothers use of conversational devices at 21 months suggests that poor maternal adjustments to child developments may be detrimental to vocabulary production. Use of infant-directed speech is often not a conscious adjustment on the part of the mother, but it may be part of a style that promotes language development by increasing interest in speech itself. Singh (2008), for example, reported improved infant word recognition when mothers spoke with infant-directed speech (compared to a more adult-directed speech pattern). Another example of maternal responsivity is the fact that mothers are much more observant of developmental progressions such as sounds and words during the first year of life, than they are to changes that occur later in development (Warren & Brady, 2007). In addition to use of different speech patterns, responsive parents adjust attention to child behaviors. Legerstee, Varghese, and van Beek (2002) found that mothers of typically developing children and children with Down syndrome redirected younger infants (mean CA 8.6 months) more often than older infants (mean CA 16.5 months), whereas the mothers of the older infants maintained the child’s focus of attention more often. It is possible that mothers of the younger infants redirected more because their infants were less skilled in maintaining attention on their own.
1.2. Molecular responsivity We have used the term molecular responsivity to refer to contingent maternal actions that can be directly linked to changes in child behaviors (Warren & Brady, 2007). For example, if the child vocalizes and the mother immediately responds by speaking to the child, this would be considered a contingent response by the mother. Or if a young child attempts to say a word and their mother recasts the child’s attempt by saying the word more clearly, this would also be considered a molecular example of responsivity because the mother’s action is in direct response to a notable change in the child’s behavior. Researchers such as Bornstein, Tamis-LaMonda, Hahn, and Haynes (2008) and Spiker, Boyce, and Boyce (2002) have pointed to contingent maternal responsivity as particularly important for child developmental outcomes including emotional security, social relationships, cognitive development, and language outcomes. Contingency leads to predictability and this predictability is thought to enable the child’s
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development of self-regulation and emotional well-being (Landry, Smith, & Swank, 2006). These types of responses support and encourage the child’s vocalizations and verbal development. Molecular responses may be contingent upon changes in child attention or play behaviors. For example, maternal responses to shifts in a child’s attention (demonstrated by looking in a particular direction) or initiating play with a particular object are often analyzed (Legerstee et al., 2002; Paavola et al., 2005). One of the key factors in determining contingency is often the lag in time between child behavior and maternal responses (Bornstein & Tamis-LeMonda, 1989; Kartner et al., 2008). Maternal responses that occur within several seconds of the child’s change in behavior are typically considered contingent and would follow under our description of a molecular analysis of maternal responsivity. The following example, drawn from the authors’ research on maternal interactions in families that have a child with FXS, will provide an illustrative summary of the different levels of responsivity research. 1.2.1. Research example In our work with families who have a child with FXS, all children live in what we would describe as a generally responsive interaction. That is, all participants were adequately fed, clothed and basic child needs have been met. (Note that this may not be the case in studies that include children who live in extreme poverty or in neglectful situations.) We have employed both molar and molecular measures to further describe maternal responsivity and to the potential relationships between responsivity and child developments (Warren, Brady, Sterling, Fleming, & Marquis, 2009). Global ratings have been employed by watching samples of videotaped mother–child interactions and then assigning a value between 1 and 5 for molar qualities of maternal interaction. These ratings were modeled after those used by Landry and colleagues (Landry et al., 2001, 2006). A 30-min observation of mother–child interaction is divided into 10-min segments. The three 10-min segments are scored separately on each of the following components using a five-point rating scale: positive affect, warmth, flexibility/responsiveness, physical control, verbal discipline, and punitive tone. Scores for each 10-min segment are averaged for one single score per component, per dyad, per observation. This procedure yields an indication of maternal responsivity, relative to other mothers in our sample and relative to participants in other studies that have used this scale. In addition to this molar level of coding, we have coded molecular responsivity. Molecular coding is measured by coding each maternal behavior toward the child to determine, for example, how often the mothers respond contingently to the child’s changes in behavior, and how often mothers use language to interpret their child’s communication attempts.
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For this level of coding, research assistants observe the videotaped interactions along with a transcript of all child communication behaviors. We are interested in specific types of maternal responses; therefore, observers record redirects, recodes, requests for verbal complies, comments, and admonishments directed to the child. Data derived from these molecular scales enable us to analyze the degree to which frequencies and proportions of specific maternal responses following child behaviors are related to child outcomes. Not surprisingly, several aspects of the molar and molecular ratings are correlated with each other. Nevertheless, we have found that the molecular ratings that capture the contingent nature of maternal responsivity are most closely aligned with child cognitive and communication outcomes (Sterling, Brady, Warren, Fleming, & Marquis, 2006). One reason for this difference is probably due to the greater variability in the molecular scores, compared to the molar scores. When considered together, data from the two scales provide complimentary information about overall maternal interaction style and specific behaviors that have been linked to child language developments. A mother who scored high on the flexibility/ responsiveness scale would routinely follow the child’s lead in interactions. If this same mother also provided vocabulary input while following the child’s lead, her child would likely show gains in vocabulary development. For example, saying ‘‘night night bear’’ as the child is covering a bear with a blanket is an example of combined flexibility/responsiveness and contingent comments. Interactions such as these are often suggested for promoting language development (Tamis-LeMonda, Cristofaro, Rodriguez, & Bornstein, 2006).
2. Responsivity Relates to Child Outcomes Responsivity correlates significantly with, and in many cases predicts, certain child outcomes, in typically developing children, in children at risk for developmental delays and in children with identified disabilities such as Down syndrome, autism, and FXS. Differences in maternal responses to child behaviors have been observed within just a few hours of birth. For example, babies who experienced increased maternal talk when being picked up were found to be less fussy and to spend more time in a quiet awake state compared to infants in a control group who did not have extra exposure to maternal talk (Thoman, Korner, & Beason-Williams, 1977). Thus, differences in child behaviors can be observed to follow responsive caregiving right from birth. Changes in fussiness or attentiveness may show up at these very early stages, setting the stage for later changes in communication and language that appear attributable to responsivity.
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2.1. Language and communication outcomes In terms of language outcomes, maternal responsivity has been linked to several important aspects of early language development, such as productive and receptive vocabulary sizes (Bornstein & Tamis-LeMonda, 1989; Tamis-LeMonda, Bornstein, Baumwell, & Melstein Damast, 1996). Children with more responsive mothers during their first year of life had higher vocabulary scores once they began to talk (around 13 months in one study, and later in toddlerhood in another). In these studies with typically developing children and their mothers, responsivity not only relates to cumulative vocabulary size, but also to important milestones such as first words and the onset of the vocabulary burst (first 50 words) (TamisLeMonda et al., 2006). That is, children with more responsive mothers said their first words and hit the 50-word marker at significantly younger ages than children with less responsive mothers. The importance of the vocabulary spurt is that it signals not only increased vocabulary size, but also coincides with the onset of beginning sentence productions. Responsivity has also been found to be an important variable for families who have children at risk of developmental delays. Risk may be associated with poverty or other adverse environmental circumstances and also with prematurity. In a series of studies, Landry and colleagues investigated the role of responsivity in mothers of children who were born preterm. Some children also had very low-birth weight, and additional medical risks. Sustained responsive caregiving was found to be positively associated with a number of child outcomes in these children, including vocabulary development. Responsivity remains important throughout the preschool years. In a study with over 500 low-birth weight children, responsivity at 30 months predicted verbal IQ measures obtained when children were 5 years old (Fewell & Deutscher, 2002). Responsivity was a significant factor even after differences in initial vocabulary comprehension were considered. Although research has often indicated that early maternal responsivity is particularly important for child development, Landry and colleagues reported that the amount of responsivity sustained over time, that is over many years, is an important factor in child language outcomes as well as important social, emotional, and cognitive outcomes (Landry et al., 2001; Landry, Smith, Swank, & Guttentag, 2008). Landry and colleagues measured maternal responsivity with global rating scales, and concurrent child language development at child ages of 6, 12, 24, 36, and 48 months of age. Children who experienced highly responsive parenting early in development, but not later, or later but not earlier, scored significantly lower on measures of language, cognitive and social development than children who experienced sustained, consistently high levels of responsiveness.
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Additional evidence for the importance of sustained responsivity is provided by the work of Hart and Risley (1995). This frequently cited study reported on the cumulative effects of variations in children’s language experiences between 1 and 3 years of age. The authors calculated differences in language input over multiple observations across children who eventually had relatively low versus high vocabularies. Children who ended up with higher productive vocabularies had experienced vastly more utterances spoken to them over time, compared to children with relatively lower vocabularies. In addition, the authors point to differences in types of utterances such as responses to child initiations and parent utterances containing nouns as further contributing to positive child language outcomes.
2.2. Responsivity in families who have a child with a disability Children who have various disabilities are likely to have delayed language development and for these children it may be beneficial to provide a responsive learning environment. Research by Warren, Yoder, and colleagues has found significant relationships between maternal responsivity and language outcomes in children with developmental disabilities. Yoder and Warren (1999b) analyzed relationships between early child communication attempts, maternal responsiveness to these attempts and later expressive and receptive language scores. Early child communication significantly correlated with these language outcomes, but the effects were mediated by maternal responsivity. Children who communicated more and whose mothers responded more to these attempts had better outcomes. In addition, these authors reported that effects of an intervention package, prelinguistic milieu teaching (PMT), were dependent on initial levels of maternal responsivity (Yoder & Warren, 1999a). Children who had highly responsive mothers at the outset of intervention showed better effects of the PMT intervention than did children who had less responsive mothers. In subsequent research Yoder and Warren added parent responsivity training to their intervention studies to complement direct practitioner provided PMT. They termed this approach responsivity education/prelinguistic milieu teaching (RE/PMT). Fey, Warren, Brady, and colleagues have reported the effects of a randomized clinical trial of this approach (Fey, Warren, Brady, Finestack, Bredin-Oja, et al., 2006; Warren, Fey, Finestack, Brady, Bredin-Oja, et al., 2008) and it is described later in this chapter. Children with disabilities such as Down syndrome, autism, or fragile X may experience lower levels of maternal responsivity due to low rates of child initiations and/or difficulty sustaining interactional routine compared to children without disabilities. Delayed onsets of important prelinguistic and early linguistic skills are generally associated with these disabilities (Chapman, 2003; Franco & Wishart, 1995; Roberts et al., 2005;
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Rondal, 2003). Delayed onset of certain communicative behaviors such as pointing may delay and decrease the amount of maternal responsivity because the lack of intentional communication gives parents few child behaviors to contingently respond to. For example, Tomasello and colleagues have shown that mothers often respond to infant pointing gestures by providing the verbal labels for the objects pointed to by the infant (Tomasello, 1995, 1999). Thus, when a child is delayed in onset of pointing, they may experience cumulatively less vocabulary input, particularly during bouts of joint attention. This type of vocabulary input has been found to predict child vocabulary acquisition over time. There is evidence that many children with developmental disabilities experience potentially important differences in responsivity from early infancy onward. For example, Slonims and McConachie (2006) reported very early differences in maternal responsivity between mothers of infants with Down syndrome compared to mothers with typically developing infants. Maternal responsivity and child social and communication behaviors were measured when children were 8 weeks old and again at 20 weeks old. The 8-week measures were not significantly different, but by 20 weeks of age the mothers of children with Down syndrome were judged as being more remote and less sensitive than the mothers of the typically developing children. Correlations between infant and mother behaviors at the two time points suggested that maternal responsivity for the Down syndrome group were related to child behaviors, whereas behaviors of mothers of typically developing children were primarily associated with nonchild variables such as maternal mental health. Some interactional characteristics associated with developmental disabilities may be disruptive to maternal responsivity. These include low child initiation rates, slower response times, gaze avoidance or atypical eye gaze patterns, hypersensitivity to environmental stimuli, social anxiety or shyness, and poor speech intelligibility (Warren & Brady, 2007). Put another way, children with disabilities may have difficulty providing clear signals about their needs (Landry et al., 2008). A mother may respond to these child behaviors by directing their child to interact in particular ways. For example, mothers may become less likely to wait for their child to respond over time if the child’s response latency is excessively long. In the case of children with ASD or FXS, it may be that problem behaviors including impaired social and cognitive engagement could suppress parental responsiveness that affects parental engagement and responsiveness over time. The resulting interaction pattern is one of low child engagement and high parent directiveness. To summarize, the interaction patterns observed in dyads that include a child with disabilities may develop some characteristic features such as maternal directiveness, but these characteristics are likely to be associated with specific child behaviors that may make it difficult for some mothers to be highly responsive.
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FXS provides an interesting context for studying maternal responsivity. Children with FXS display a social, cognitive, and linguistic profile similar to that of autism, including the aforementioned behaviors that are disruptive to maternal responsivity. In addition, women who are carriers of FXS are more susceptible to depression and anxiety, which can also impact responsivity. Warren et al. (in press) examined the relationship between maternal responsivity and later communication and language development in a cohort of young children with FXS. Responsivity was measured at the molecular level, and both maternal and child communicative behaviors were coded. The results indicated that maternal responsivity predicted child language variables at 36 months of age, including number of different words, rate of child communication, as well as scores on expressive and receptive language subscales on the Mullen Early Learning Scales (Mullen, 1995). In other words, children with FXS who were exposed to a highly responsive style of parenting scored higher on language outcomes than children who received less responsive interactions. This finding complements the literature on responsivity within typical development; both children with developmental disabilities and children with typical development demonstrate a measurable advantage when exposed to high levels of maternal responsivity early in life (Landry, Smith, Miller-Lonear, & Swank, 1998; Landry et al., 2001; Tamis-LaMonda, Bornstein, & Baumwell, 2001; Warren et al., in press). In addition to varying responsivity in accordance with child developments, mothers may be more or less responsive depending on whether the child is first born or latter born (Furman & Lanthier, 2002). There are many possible explanations for possible differences in responsivity within a family. It could be that mothers of latter-born children are more responsive because they are experienced, more assured in caregiving, and better at reading their child’s behavioral and emotional signals. Alternatively, mothers of latterborn children may be more influenced by the competing demands of caring for multiple children. Although there have been many studies conducted on the influences of these family dynamics on parenting style, it is difficult to disentangle the effects of birth order, age of children, spacing of children, size of family, family support variable, and so on. Nevertheless, it is important to remain mindful of parenting within the complex family structure when trying to evaluate maternal responsivity and its role on child outcomes. The literature reviewed above provides examples of different responsive techniques repeatedly observed in typical mother–child interaction that may play important roles in early language development. This literature has been steadily accumulating for nearly a half century and is central to social-interactional theories of language development. We have provided only selected examples above. Taken as a whole, whether one is focused on typical child development or atypical development, the research supports
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the contention that a consistent, contingent, and adaptive interaction style is the most facilitative of early language development. Not surprisingly then, a number of early intervention programs have been developed with the goal of enhancing various pivotal aspects of maternal responsivity that may have a cumulative impact on development. In the following section, we briefly describe several interventions aimed at primarily improving maternal responsivity, with a primary goal of thus improving children’s language outcomes.
3. Interventions Aimed at Improving Responsivity Thus far we have made a case for the important contribution that cumulative exposure to highly responsive maternal interactions can provide for child development in general and language development in particular. One of the most salient and promising outcomes of the research on maternal responsivity is the recognition that intervention might attempt to establish and enhance this parenting style as a means of facilitating young children’s language development. The goal for the intervention approaches we review next is to teach mothers an interaction style that the descriptive literature indicates to be closely associated with optimal child development. Central to this style is the notion that it should be responsive to the child’s interests, not the adults, and to the extent possible be responsive to child initiations. Questions, models, and imitation prompts may be used, but only within conversational routines based on the child’s interests. Furthermore, the aim is to utilize this style throughout the day whenever opportunities naturally arise. This style may be especially effective in the context of structured routines such as dialogic book reading (Whitehurst, Falco, Lonigan, & Fischel, 1988; Zevenberger & Whitehurst, 2003). The overall aim is to emulate the consistent ubiquitous responsivity that has been associated with relatively advanced child language outcomes. Relative to other behavioral interventions, a substantial amount of research supports the conclusion that a highly responsive child-focused interaction style can be taught to a parent or practitioner with a relatively modest effort. Bakermans-Kranenburg, van IJzendoorn, and Juffer (2003) examined the effectiveness of various parental interventions on parental sensitivity, attachment, and responsivity by reviewing a large number of studies and using meta-analytical procedures to analyze cumulative results. Effects across 70 different parental intervention studies that were aimed at improving infant attachment and security were compared. Although this child outcome (sensitivity/attachment) is not the same as the language
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outcomes focused on in the current chapter, the literature is relevant because many of the interventions were aimed at improving maternal responsivity. Results of this meta-analysis indicated that relatively short interventions that lasted less than 16 sessions were found to be more effective than longer interventions in establishing more responsive interaction styles. An additional finding was that mothers increased their responsivity significantly more in studies that used nonprofessional (e.g., experienced mothers) interveners, compared to professional (e.g., graduate student) interveners. Based on this large set of data, Bakermans-Kranenburg and colleagues concluded that interventions that began at around 6 months after birth or later were slightly more effective than those that began prenatally or at birth. Further, well-timed, focused interventions that lasted ‘‘long enough to lead to sustained changes in mother–child interactions, but not so long as to become burdensome’’ were optimal. The issue of timing of intervention is important and in need of further research. It may be that there is something specific about child development at the age of 6 months that provide an optimum social context for interventions. Or, it may be that by the time her child is 6 months of age, mothers are comfortable with being a mother, and are ready to learn new interaction strategies. Recent research by Landry and colleagues investigated the timing of interventions. Mother–child dyads who experienced the PALS intervention (described below) during both infancy and the toddler period were compared to dyads that experienced the intervention only in infancy. They found that mothers who experienced both phases of intervention had higher levels of contingent responsiveness. Increases in maternal warmth were associated with early interventions, and changes in mothers’ language input were associated with interventions during the toddler stage. Similar timing differences were found for child language outcomes. Greater effects on receptive and expressive language scores were seen following the toddler intervention. Thus, optimal timing of interventions differed depending on the outcome variable and ‘‘the degree to which the behaviors were linked to a child’s changing developmental needs’’ (Landry et al., 2008, p. 1350). Changes in maternal responsivity have been documented following as little intervention as a single viewing of a developmental assessment session (Anderson & Sawin, 1983), but sustained changes in maternal interactions may require participation in an ongoing intervention that provides weeks or months of regular learning opportunities. Such is the nature of the programs briefly described below. These intervention approaches are generally based on the same underlying principles and many of the same general set of adult behaviors and child skills although sometimes different terms are used for the same underlying concept. A number of interventions have been developed that address parent responsivity within everyday interactions. Interventions such as It Takes
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Two to Talk and RFI (each described in following sections) encourage parents to implement strategies throughout the day, by embedding strategies within everyday routines. Other interventions have created routines that provide a context for learning new skills (Snyder-McLean, Solomonson, McLean, & Sack, 1984). Research by Woods and colleagues has emphasized the importance of parent input into the selection of teaching routines (Kashinath, Woods, & Goldstein, 2006; Woods-Cripe & Venn, 1997). Kashinath, Woods, and Goldstein taught mothers to interact in specific ways during individually selected everyday contexts, such as dressing or mealtimes. A unique feature of this intervention was that teaching contexts were identified by first querying families about the routines they already engaged in, such as dressing, music, and play. Next, the different routines were evaluated by each mother and the interventionist to identify the routines that were most representative, occurred most frequently, and were most preferred by the mothers. Mothers learned interaction strategies such as waiting for their child to initiate and contingently imitating their child’s communication, within the contexts of the selected routines. A potential benefit of this approach is that individualization is likely to increase parent implementation of the intervention. In addition, generalization of these strategies to nontraining contexts was also observed. Results from the routine-based intervention implemented by Kashinath et al. (2006) were evaluated using a single-subject design. Five mothers each showed increases in various aspects of responsivity including waiting for child communication and contingent imitation of child responses. The five children of the mothers who participated also showed improved communication. Increases were observed in children’s use of gestures, single words, and multiword utterances.
3.1. Interventions based on materials from the Hanen Center One of the most developed and marketed interventions aimed at improving parental responsivity and child language outcomes was developed at the Hanen Center. A number of intervention programs are now available that promote language learning opportunities for children with a range of language disorders including Autism and Late Talkers. ‘‘It Takes Two to Talk’’ (Girolametto & Wieitzman, 2006) was developed to teach parents of young children to apply language facilitation strategies across everyday contexts. The curriculum for ‘‘It Takes Two to Talk’’ is intended to be delivered by a certified speech-language pathologist (SLP). It includes information on the development of nonverbal and early verbal communication, how to recognize, respond to, and provide opportunities for children’s early communication attempts, and how to incorporate these communication opportunities throughout the day. One of the theoretical underpinnings of the Hanen Center approach is based on Vygotsky’s
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concept of a zone of proximal development. Parents are encouraged to provide input that matches the child’s input. For example if the child is producing mostly one-word responses, parents are told to reduce the length of their utterances to single words or short phrases. The Hanen Center approach is ‘‘family centered’’ in that it recognizes the family as the most important element in a young child’s life (Girolametto & Wieitzman, 2006). Parents help each other through group interactions and each parent actively participates in selecting appropriate intervention goals for their child. The curriculum is delivered primarily through 11 weekly sessions between a trained SLP and small groups of parents. Parents are provided feedback on their interactions through the use of videotaping and counseling. It is worth noting that BakermansKranenburg et al. (2003) reported the use of videotaping as a significantly effective intervention strategy. A number of research studies have found that parents participating in ‘‘It Takes Two to Talk’’ have changed their interaction styles and became more responsive to their child’s communication after participating in the intervention. Girolametto (1988) found that, compared to a control group, mothers who participated in ‘‘It Takes Two to Talk’’ used fewer turns, and maintained longer conversational exchanges. A follow-up study by Tannock, Girolametto, and Siegel (1992) showed similarly positive results in terms of mothers’ responsivity. Unfortunately, across these two studies, no significant effects were found for children’s language development. Based on these outcomes, the authors added additional material to the curriculum of ‘‘It Takes Two to Talk’’ that focused more on strategies aimed at stimulating word production (Girolametto, Perarce, & Weitzman, 1996). Results from the version of the intervention that included focused word stimulation indicated positive results for both parents and children. In focused stimulation, targeted words are spoken more often during the intervention, and opportunities for the child to use these words may be provided (Ellis Weismer & Robertson, 2006). Children in the intervention group had a significant increase in their number of target words learned and had significantly larger vocabularies according to parent report. Another program developed at the Hanen Center, ‘‘More than Words’’ is an offshoot of the program ‘‘It Takes Two to Talk’’ and was developed specifically for children with ASD and their mothers. This intervention emphasizes many of the same principles of reciprocity as ‘‘It Takes Two to Talk,’’ but also includes information on the importance of affect, predictability, structure and the use of visual supports to facilitate language learning in children with ASD. Like the ‘‘It Takes Two’’ program, intervention is provided through individual sessions and parent groups over an 11-week time period. Girolametto, Sussman, and Weitzman (2007) found that three mothers of children with ASD increased in the following ways after
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participating: following their child’s lead, promoting children’s participation in routines and modeling language at the children’s level (matching). The participating mothers’ children also showed increased vocabulary size and numbers of different words after intervention. Larger studies with a control group will allow a more definitive evaluation of the role of ‘‘More than Words’’ in promoting maternal responsivity and child language outcomes. An intervention based on ‘‘More than Words’’ was implemented in a pilot study of responsivity in mothers of children with FXS conducted by the current authors (Brady, Sterling, & Warren, 2008). Four mothers participated in ten weekly intervention sessions that utilized the teaching materials provided by the Hanen Center. It should be noted, however, that, although the intervention was implemented by a Hanen certified clinician, it did not include a group component. That is, all aspects of the intervention were provided in 1:1 intervention sessions. As in other applications of this program, participating mothers were taught to wait for their child to initiate interactions, recognize communication attempts, follow the child’s lead, and provide simplified input to their child. A multiple baseline design was used to evaluate responses by each participating dyad. Videotaped interactions were collected before, during and after interventions and maternal and child behaviors scored from these videotapes served as primary data sources. Three of the four mothers increased their proportion of responsive interactions and decreased proportions of directive-style behaviors during the intervention sessions. The fourth mother did not show any changes in her behavior. It may be noteworthy that this fourth mother also had the full mutation of FXS; hence, the instructional materials may not have been explicit enough for this mother. The children of the three mothers who responded to the intervention also showed positive changes in language outcomes during intervention. Specifically, increased vocabulary size and rates of intentional communication were observed. Positive language changes were not observed in the fourth child.
3.2. Relationship focused intervention (RFI) This intervention, developed by Mahoney and colleagues, is designed to help parents learn and incorporate responsive interactions in their daily routines with their children and is conceptually similar to the Hanen approach. Topics addressed by RFI include interacting with children in play, turn taking, following the child’s lead, increasing the number of responses, and decreasing the number of redirectives issued to the child. As described in two recent studies by Kim and Mahoney (2004, 2005) intervention includes four components: classroom-based instruction;
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home-based instruction; feedback; and evaluation. Children were between 3 and 8 years of age, with developmental age equivalents around 2–4 years, based on the Vineland Adaptive Behavior Scale. Intervention is typically provided in weekly sessions lasting from 1 to 2 h over the course of 3 months. The majority of instruction (e.g., eight sessions) is provided in a classroom setting and then home-based instruction sessions (e.g., two sessions) offer opportunities for interventionists to observe and provide feedback to mothers during daily routines. Videotaped observations of mother–child interactions provide an additional source of feedback. Results from the Kim and Mahoney studies were similar to those reported for earlier versions of the Hanen programs—mothers changed but only modest changes in child behaviors were observed. Effects on mothers’ responsiveness, affect and achievement orientation were significant, but only child affect significantly increased in the intervention group. However, small sample sizes may again limit the significance of their findings because only 18 dyads participated in this study, 10 in intervention and 8 as control dyads. Participants were not randomly assigned to groups; rather participants were matched according to maternal age, years of education and level of stress of the mothers, age of the child and functioning level of the child. Post hoc analyses indicated that children whose mothers made larger gains in responsiveness did show substantial changes in their interactive behaviors.
3.3. The playing and learning strategies (PALS) program The PALS program was developed by Landry and colleagues (Landry et al., 2006, 2008) to address maternal responsivity in families at risk of low social engagement due to biological risk associated with prematurity and very low-birth weight. PALS is a home visiting program designed to teach mothers to engage in a highly responsive style that is similar to those targeted by It Takes Two to Talk and RFI. The goal of PALS is to establish a style of interaction that includes four different aspects of responsiveness: contingent responding, emotional-affective support, support for infant foci of attention, and language input matched to infant’s developmental level. Ten weekly 90-min home visits provide maternal instruction. The format for the visits includes (a) asking mothers to review their experiences across the last week; (b) describing the current visit’s targeted behavior; (c) watching and discussing videos of other mothers modeling targeted behaviors with coaching; (d) videotaping mothers with their infants engaged in toy play, feeding, bathing, and so forth with coaching; (e) allowing mothers to critique their behaviors and infant responses while viewing the videotape; and (f) planning for practice during the coming week. Landry et al. (2006) evaluated the effectiveness of PALS by comparing performance of a group of mothers who participated in PALS to another
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group of mothers who participated in a control group condition. The control group experienced the same number of visits as did mothers in the PALS group, but the focus of the control group was developmental milestones, rather than responsivity. A strength of this study was the large number of participants—264 mother–infant pairs in total. Measures were obtained longitudinally during four assessments conducted when infants were between 6 and 13 months of age. Positive outcomes were obtained for both mothers and infants. Increased maternal responsiveness facilitated greater growth in infants’ social and emotional skills and early communication development including vocabulary. Additional assessments of infant interactions with an experimenter also showed growth in infant skills. That is, the infants generalized their interaction and communication skills to interactions outside of mother–child interactions. Results from Landry and colleagues’ studies also feature changes in more distal measures of child outcomes, including standardized language measures. Improvements in receptive and expressive scores on the Preschool Language Scale (Zimmerman, Steiner, & Evatt Pond, 2003) and the Peabody Picture Vocabulary Test (Dunn & Dunn, 1997) demonstrated that changes in child language behaviors over time were also associated with changes in mothers responsivity following PALS interventions.
3.4. Responsivity components in language intervention studies A focus on maternal responsivity is often one component of a complex intervention than includes child goals in addition to maternal interaction goals. An example of such a complex approach is responsivity education/ prelinguistic milieu teaching (Warren, Bredin-Oja, Fairchild Escalante, Finestack, Fey, et al., 2006). RE/PMT evolved over many years of research (Fey et al., 2006; Warren et al., 2008; Yoder & Stone, 2006; Yoder & Warren, 2001, 2002). The child-focused component of the intervention is aimed at improving prelinguistic gestures and vocalizations in children who have significant delays in language development and who are currently infrequent communicators. The parent-focused component follows many of the same themes addressed by It Takes Two to Talk, such as following the child’s lead, observing child communication and waiting for child initiations. Yoder and Warren (2002) included parent responsivity education as part of their comprehensive early language intervention program. Parents were provided individualized treatment focused on increasing responsivity and providing ideal language models and feedback, in a series of 11 weekly sessions. The authors found significant increases in parents’ use of optimal contingent responses for parents in the intervention group, compared to children in a control group. Optimal responses included responding to child
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initiations and linguistic mapping of child communication attempts. For example, if a child pointed to a spinning top and said ‘‘that’’ the parent might linguistically map the child’s communication by saying ‘‘yes, that’s a top.’’ In a study that replicated many of the components of Yoder and Warren’s (2002) study, Fey et al. (2006) also reported an increase in linguistic mapping following RE/PMT intervention. In contrast, parents who did not receive RE/PMT (because they were in the control group) did not show increases in linguistic mapping. These increases in linguistic mapping are encouraging because they reflect learning of one of the key contingent responses targeted in the intervention, and because linguistic mapping is part of a general approach called language stimulation that has been shown to be effective in improving child language outcomes (Ellis Weismer & Robertson, 2006). One concern regarding parent-focused interventions is that the intervention may increase parental stress levels—levels that may already be high due to having a child with a disability (Kim & Mahoney, 2004). The study by Fey et al. (2006) monitored stress levels of the mothers who participated. Mothers completed the parental stress index (PSI) (Abidin, 1995) before and after intervention. Potential differences in stress that could be attributed to participating in the intervention were evaluated with an ANOVA. There were no significant differences for treatment versus nontreatment groups, and the PSI scores were within normal limits. The authors concluded that RE/PMT did not increase parental stress as measured by the PSI.
4. Summary and Conclusions Responsive interactions between infants and young children and their primary caregivers are essential for optimal language development and this basic finding has been well established in the literature. Importantly, a growing body of research is becoming available regarding interventions aimed at improving maternal responsivity and thereby also impacting child language attainments. A number of effective aspects of intervention such as length and timing can be identified that are common to the interventions reported in the literature and summarized in the previous sections. The intervention programs that were described in previous paragraphs were generally effective following 10–12 weekly sessions. This amount of time appears sufficient to achieve sustained change in maternal responsivity and modest changes in child language outcomes associated with these maternal attainments. Interventions appear most effective when they are timed to co-occur with expected child developments. For example, the studies by Landry
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et al. (2008) reported optimal child outcomes when intervention was provided during both infant and toddler years, but specific gains in distal language outcomes were tied to the toddler phase of intervention. For example, greater use of multiword utterances was observed in children following responsivity intervention delivered during the toddler years. The authors concluded that optimal timing of intervention depended on skill complexity and the age at which the targeted skill would naturally be observed. However, most of the children in the Landry et al. studies did not have identified developmental disabilities, and further research regarding these timing issues in children with varying degrees of delayed development are needed. To date, most of the research studies have provided outcomes based on using a curriculum that teaches multiple aspects of responsivity, such as following the child’s lead, being contingent, waiting for child communication, and providing linguistic input. These components are based on studies documenting their relationships to child language outcomes. Use of videotaped feedback was also frequently identified as a significant feedback component. Although the research summarized in this chapter indicates that interventions can be effective in increasing maternal responsivity, potential interventionists and researchers must remain mindful of the sensitive, complex nature of family interactions when planning and conducting interventions. In previous sections, we noted the need to monitor stress levels that could be elevated by intervention. Families who are likely to participate in these interventions are at risk for increased stress due to the challenges faced in raising a child with a disability, financial burdens associated with disability, and potential cognitive limitations by the mother or other members of the family. Interventions aimed at improving maternal responsivity may often be improved, therefore, by individualizing curriculum and goals to reflect individual family concerns. In addition to individualizing interventions to reflect family dynamics, concern for a family’s culture should also be maintained. As mentioned in the introduction of this chapter, responsivity may indeed vary across cultures, in accordance with different values toward child communication. Interventionists are faced with the challenge of how to address interaction styles and practices that may sometimes be at odds with a family’s cultural background. van Kleek (1994) suggests that interventionists may alter existing programs to fit a particular family or develop different materials based on a study of successful and unsuccessful interactions within the target family. In terms of affecting both maternal responsivity and child language outcomes, interventions that combine both responsivity education and language interventions, such as the RE/PMT approach may be most likely to generate positive results. The combined approach has several advantages.
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Mothers learn a facilitative interaction style that is likely to foster child language at current and future levels of child language development. Children will benefit from individualized intervention aimed at promoting growth toward an advanced level of language and communication. In addition, parents place extreme value on the child language component and may be more likely to ‘‘buy-in’’ to an intervention that includes child goals, as opposed to an intervention that is exclusively focused on maternal responsivity. Although the research to date generally supports interventions aimed at improving child language by increasing responsivity, further research is needed in this area. Specifically, further studies are needed to help identify components within treatment packages that are optimal and to identify the optimal timing of intervention components (relative to both child chronological and developmental ages).
ACKNOWLEDGMENTS We wish to gratefully acknowledge the support of NIH grants P30 HD003110 and P30 HD002528.
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Index
A Adaptation, cross-cultural model care givers effect, 205–206 limitation, 206 psychological distress, 205 social functioning, morale and somatic health, 204 Adulthood transition, ID individuals adolescence and, 33 adoptive and birth parents, 78–79 challenges, 33–34 childhood behavior problems family contact and involvement, 49 health and stress, 49–50 independent living, 48–49 criteria, 34 critical role, 55–56 emerging strength, 54–55 family interaction project, 37–38 gender family contact, health and stress, 51 independent living, 50–51 independence and self-sufficiency, 54 limitations, 32 measures time 4 family contact, health and stress, 41 time 4 independent living, 40 moderate vs. mild ID family contact and involvement, 47 health and stress, 47–48 independent living, 42–47 launching and financial independence, 48 negative consequences, 57 parents, 32–33 participants disability level and child behavior problem, 39–40 sample characteristics, 38–39 perceptions chi-squared tests, 53–54 independent living, 51–52 indicators, 52–53 procedures, 40 relational competence, 57–58 research children cohort study, 34–35 functioning, 35–36 normative expectation, 36–37
role functioning, 56 study purpose, 37 transitional nature, 55 Aging and Disabilities Resource Center (ADRCs), 317 Aging caregivers AAA, 316–317 ADRCs, 317 future planning, I/DD person, 318–319 support coordination and direct service program, 321–322 Allostatic load approach, stress, 240–241 Area Agencies on Aging (AAA), 316 ASD. See Autism spectrum disorders Asian families research cross-cultural model adaptation, 204–206 appraisal, 187–194 coping, 194–197 cultural and religion factor, 185–187 environmental factor, 182–185 family functioning, 181–182 social support, 197–204 immigrants, 180 Autism spectrum disorders (ASD) epidemiology, 274 ID children sibling, 253, 259, 283, 285 ‘‘It Takes Two to Talk’’, 347 parental responsiveness, 342 racial/ethnic difference, 276 B Behavioral impressions of parents-coder inventory (BIP–CI), 86 Biomarkers, families of children study allostatic load, 240–241 cellular aging individual variability, 240 telomere length, 239–240 cortisol profile, parents daily stress, 234–236 disabilities children vs. comparison group, 233–234, 236–238 diurnal rhythm and daily stress measurement, 232–233 HPA axis and role, 229–230 stress and, 230–231 definition, 215
359
360
Index
Biomarkers, families of children study (cont.) FXS causes and effects, 216 FMR1 gene, 217–221 limitations, FMR1 biomarkers, 227–229 stress and well-being, 221–227 stressors vs. stress syndrome, 214 Buddhism. See Religious belief C Caregiver–child interaction. See Molar responsivity; Molecular responsivity CDC. See Centers for Disease Control and Prevention CDERS. See Client Development Evaluation Report Cellular aging individual variability, 240 telomere length, 239–240 Centers for Disease Control and Prevention (CDC), 132, 147 Childhood behavior problems family contact and involvement, 49 health and stress, 49–50 independent living, 48–49 Chi-squared tests, 53–54 Chronic sorrow, adoptive and birth parents. See also Hypothesis testing, adoptive and birth parents comparison, 79–80 mothers, 80–81 Client Development Evaluation Report (CDERS), 156, 164 Collaborative family study (CFS). See also Parenting, preschool to early school age data fathering behavior, 20 parental stress, 13 goal, 10 parenting behavioral trajectories dimensions, 20–21 growth curves, 17, 21–22 individual t-test comparison, 15, 21 Collectivism in Asian society, 198 vs. individualism, 186–187 Comparison group, siblings research comparability age difference and disability subgroups, 266–267 competency, 267 on income, 266 t-test, 265–266 social address age and birth order, 270 gender, 267–270 with vs. without disabilities
family context, 259 matching variables, nondisability, 259–262 nondisability and cross-disability variables, 263–264 relative and family birth order, 264 Confucianism. See Religious belief Consumer directed services, I/DD agency-directed, 313–314 direct payment program, 315 family and friends hiring, 315–316 HBSSP, 314–315 Cortisol, children study family daily stress, parents, 234–236 disabilities children vs. comparison group parents, 233–234, 236–238 diurnal rhythm, 232–233, 237 stress and acute stressful life events, 231 daily stressor, 230–231 morning and evening level, 230 Cross-cultural model, research on Asian families adaptation caregivers effect, 205–206 limitation, 206 psychological distress, 205 social functioning, morale and somatic health, 204 appraisal belief and explanation, 187–189 immigrant families, acculturation and beliefs, 189–194 coping strategies, 195–197 Western vs. Eastern conception, 194–195 cultural and religion factor collectivism vs. individualism, 186–187 religious belief, 186 environmental factor availability and accessibility, service, 184–185 disabilities, 183–184 family functioning permeation, 181 structure, 181–182 social support formal, 199–204 informal, 197–199 Cultural belief disability cause, 196 and explanatory model, 187–189 reliance on, 192 D Data collection, adoptive and birth parents criteria, 66–67 initial, 67–69 subsequent, 69–70
361
Index
DDIS. See Developmental Disabilities Information System Department of Education (DOE), 137, 142, 147 Department of Health and Human Services (DHHS), 137, 147 Depression, adoptive and birth parents DEP5, 76 Escape-Avoidance strategy, 89 resilience, 73 trajectory, 72–73 Developmental Disabilities Information System (DDIS), 156, 157, 164 DHHS. See Department of Health and Human Services Disability research, siblings foundation family strength and interactions, 256 negative mental health outcome, 255–256 questions and guiding theory family system theory, 257 Farber’s theme, 258 DOE. See Department of Education E Economic disadvantage, siblings research effect, children and families material hardship, 273–274 poverty, 272–273 relationship outcome, 274 families disability-related expense, 271 parent education, 272 SES group difference, 274–275 Environmental factor, cross-cultural model availability and accessibility, service, 184–185 disabilities chemical warfare, 183–184 nutritional deficiency and malnutrition, 183 Escape-avoidance strategy, 89 F Familial mental retardation protein (FMRP) cognition and brain activation, 220 description, 217 FMR1 mutation, 219 function, 217–218 FXS, 215 lymphocytes, 227 Family caregiver support program (NFCSP), 316 Family interaction project, 37–38 Family-related outcome, large scale approach divorce, Down syndrome, 166–167 ethnic–racial background, African American, 167–168 Family, socioeconomic position and child well-being functioning and parenting practices, 105
material and psychosocial hazards, 105–106 poverty trajectories, 104 resilient functioning, 106 IDD child between-group differences, 108–110 emotional and conduct disorder, 107 immunity, 107–108 moderating variable, 110–111 within-group differences, 110 research, methodological and conceptual analytic strategies, 118 mediating pathways, 112 models, 113–115 and poverty measures, 115–118 public health, 112–113 sampling, 119 Family stress model, 113–114 Family support 360 (FS 360), 317 Family support interventions I/DD member impact adults, 302–309 health effects, 310–311 mother’s well-being, 301, 310 psychosocial future planning, 318–319 old caregivers, 321–322 siblings, 322–324 support groups, 319–321 public policies and programs aging caregivers, 316–317 consumer impact, 313–316 finance, 312–313 FS 360, 317 movement, 311 Family support movement, 311 Five-item inventory of depression (DEP5) adoptive/birth mother depression, 82–83 description, 76 and Holroyd factors, 75 maternal and parental adjustment, 82 FMR1. See Fragile X mental retardation 1 FMRP. See Familial mental retardation protein Fragile X-associated tremor–ataxia syndrome (FXTAS) characterization, 220 and POI, 228 Fragile X mental retardation 1 (FMR1) full mutation FMRP function and deficiency, 217–218 level, FMRP, 218 sex difference, affectedness, 219 premutation FXTAS, 220 vs. individuals, allele, 220–221 mRNA level, 219 Fragile X syndrome (FXS) biomarkers identification, 217 causes and effects, 216
362
Index
Fragile X syndrome (FXS) (cont.) FMR1 full mutation, 217–219 limitations, 227–228 premutation, 219–221 stress and well-being characteristics, mothers, children and families, 223 child challenging behavior, 226 Down syndrome and autistic disorder, 222 FMR1, 226–227 mental health symptoms, 222–223 premutation size, 225 psychopathology and lifetime rate, 221 SCL-90-R depression scores, 224–225 Future planning, I/DD person Family Futures Planning Project, 318 Family-to-Family project, 318–319 Psychoeducational Group Intervention for Aging Parents, 318, 319 FXS. See Fragile X syndrome FXTAS. See Fragile X-associated tremor–ataxia syndrome G Gender family contact, health and stress, 51 independent living, 50–51 Group differences, siblings research age and birth order, 270 family form, 275–276 gender combinations, 269–270 depressive symptom, 269 male vs. female, ID, 268 racial and ethnicity, 276 SES, 274–275 H Hanen Center approach curriculum, ‘‘It Takes Two to Talk’’, 346–347 ‘‘More than Words’’ program, 347–348 videotape interactions, 348 Head Start program, 191 Hinduism. See Religious belief Home Based Support Services Program (HBSSP), 314–315 Hypothalamic–pituitary–adrenocortical (HPA) axis, 229 Hypothesis testing, adoptive and birth parents depression birth mothers, 73 trajectory, 72–73 lifespan trajectory models, 71–72
I Immigrant families acculturation, USA and UK belief difference, 194 cultural values retention, 192–193 demographic characteristics, 191 folk beliefs, 190 Head Start program, 191 mental retardation, 193 Independent living adulthood perceptions, 51–52 childhood behavior problems, 48–49 gender, 50–51 moderate vs. mild ID employment and family formation, 46 residence, 42 schooling, 42–46 support services use, 47 time 4, 40 L Large-scale approach, family research birth records, 135–136 marital status, 136 National surveys data, 136–147 disability status, 147–148 feature, 147 use, 148 National Vital Statistics System birth defects, 149 data sets, 149–154 Down syndrome rate, 155 goal, 148–149 individual identifiers, 156 state–city–region database, 156–163 individual information, 165 nondisability survey, 164 Large-scale databases approach, family research National surveys, 136–148 National Vital Statistics System, 148–156 state–city–region, 156–165 comparison data quality, 171–172 national data sets vs. data sets, 169–170 sample vs. population, 170 families of persons, disabilities in Down syndrome and ASD, 134 by generation, 132–133 parent–family functioning, 135 family-related outcome divorce, 166–167 ethnic–racial background, 167–168
363
Index
M MADDS. See Metropolitan Atlanta Developmental Disabilities Study Maternal behavior rating scale, 336 Maternal responsivity analysis, levels, 335–336 behavioral intervention approach aim, 344 components, language study, 350–351 features, 346 Hanen Center approach, 346–348 mother–child dyads, 345 nonprofessional vs. professional interveners, 345 PALS program, 349–350 RFI, 348–349 communication and language outcome sustained responsivity importance, 341 vocabulary comprehension, 340 in families, disability child communication attempt, 341 first born/latter born, 343 interactional characteristics, 341–342 infants, interactions, 334 language enhancing parent behavior, 334–335 molar directiveness, 336 infant-directed speech, 337 speech patterns, 336–337 molecular child’s vocalization, 337–338 coding, 338–339 global ratings, 338 vocabulary development, 339 Metropolitan Atlanta Developmental Disabilities Study (MADDS), 135, 156, 164 Molar responsivity directiveness, 336 infant-directed speech, use, 337 speech patterns, 336–337 Molecular responsivity child’s vocalization, 337–338 coding, 338–339 global ratings, 338 vocabulary development, 339 ‘‘More than Words’’ program, 347–348 N National Center for Health Statistics (NCHS), 136, 147 National Family Caregiver Support Program (NFCSP), 316 National Institutes of Child Health and Human Development (NICHD), 147 National Institutes of Health (NIH), 132
National Survey of Children with Special Health Care Needs (NS-CSHCN), 136, 147, 148, 170 National Survey of Midlife in the United States (MIDUS), 232 National surveys, family research data, 136–147 disability status, 147–148 feature, 147 use, 148 National Vital Statistics System, family research birth defects, 149 data sets, 149–154 Down syndrome rate, 155 goal, 148–149 individual identifiers, 156 NCHS. See National Center for Health Statistics NICHD. See National Institutes of Child Health and Human Development NIH. See National Institutes of Health Novelty shock crisis, 5 NS-CSHCN. See National Survey of Children with Special Health Care Needs P Parental long-term adjustment adulthood transition, 78–79 personality, resilience adoptive/birth comparison, 86 behavioral ratings, 83 characteristics, 81–82 coder impression, 83–86 disability/no disability, 86 individual traits, 82 mother and father status, adjustment, 82–83 variables, multiple times DEP5, 76 family strengths, 76–77 QRS, 74–75 subjective well-being (SWB), 77–78 Parental stress index (PSI), 351 Parenting, preschool to early school age behavior with ID children father interactive behavior, 22 mothering, 20 trajectories, CFS, 20–22 CFS goal, 10 mothers and fathers data comparison, 11 strengths, 10–11 complexity equifinality and multifinality, 6 maladaptation, 6–7 model, family process, 7–8 self-regulatory processes, 8 father, family complexity, 23 growing attention, 9
364
Index
Parenting, preschool to early school age (cont.) and mother comparison, 23–24 role, 8 historical perspective chronic sorrow, 5 family stresses and strengths, 5–6 mediational and moderational mechanisms, 24–25 psychological well-being data, psychological well-being, 18–19 depression, anxiety and distress, 17–18 marital relationship, 18 stress CFS data, 13 date contrasting, 12–13 factors complexity, 16 family response, 11–12 growth models, 16–17 ID vs. typically developing children, 12 individual t-test comparison, 14, 15 well-being, stress and, 9–10 Parents helping parents (PHP) network, 320 Parents of adult children with developmental disabilities (PACDD), 320 Planful problem solving, 89 Playing and learning strategies (PALS) program evaluation and strength, 349–350 goal, 349 POI. See Primary ovarian insufficiency Poverty. See also Family, socioeconomic position and IDD prevalence data, children age 4–15, 100 direct and indirect cost, 102 gradients, socioeconomic, 101–102 maternal report, 100–101 parents intellectual function, 103 social patterning, 102–103 measuring approaches, 99 and socioeconomic position measures cumulative/repeated exposure, 116–117 description, 98–99 hardship/financial strain, 116 key components, 115–116 social deprivation and capital, 117–118 Pregnancy to Early Life Longitudinal (PELL) Data System, 156 Primary ovarian insufficiency (POI). See also Fragile X-associated tremor–ataxia syndrome (FXTAS) description, 219 premutation, 216 PSI. See Parental stress index Psychoeducational group intervention for aging parents, 318, 319 Q Questionnaire on resources and stress (QRS) adoptive and birth mothers and fathers, 74–75 and DEP5, 76
R Reality crisis, 5 Relationship focused intervention (RFI) components, 348–349 post hoc analysis, 349 Religious belief, 186 Resilience and vulnerability, adoptive and birth parents adaptation and adjustment, 88–89 adulthood transition TDRWQ factors, 79, 80 time 4 measurement, 78–79 characteristics, 62–63 chronic sorrow/crisis and recovery depression, 72–73 description, 71 lifespan trajectory models, 71–72 mean-level differences, 79–81 comparison family strengths, 77 Holroyd factors and DEP5, 75 subjective well-being (SWB), 78 transition daily rewards and worry questionnaire, 80 data collection child diagnoses/characteristics, 66–67 initial, 67–69 subsequent, 69–70 methodological considerations, 87–88 multiple variables data collection, 73–74 DEP5, 75, 76 family strengths, 76–77 QRS, 74–75 subjective well-being (SWB), 77–78 personality behavioral ratings, 83, 84 characteristics, 81–82 coder impressions, 83–86 and disability vs. no disability, 86 individual differences and, 88 mother and father status and adjustment, 82–83 project overview, 66 rationale and methodology family comparison, 63–65 features, 63 upper pathway, 65–66 strategies and personality, 89 Responsivity education/prelinguistic milieu teaching (RE/PMT) approach, 350–351 RFI. See Relationship focused intervention S SCL-90-R. See Symptom checklist-90-R Sharing Caring Project (SCP), 321 Sibling, I/DD adult
365
Index
interventions, 323 relationship description, 322 support network, 323–324 Siblings, ID children average relationship, 281–282 comparison group, research comparability, 265–267 social address, 267–270 with vs. without disabilities, 258–265 description, 252 developmental effects, being, 255 differentiation, 280–281 disability research foundation, 255–256 questions and guiding theory, 257–258 economic disadvantage effect, children and families, 272–274 families, disability, 271–272 SES group difference, 274–275 group differences family form, 275–276 racial and ethnicity, 276 intervention disruptive behavior, 283–284 factor, 284 matching comparison sample case-by-case, 279 group, 279–280 restricted sampling, 280 relationships characteristics, 253–254 conflict, 254 infant and older, 254–255 statistical control, dissimilar sibling groups analysis of covariance (ANCOVA), 277 disability status, 278 Social address, sibling group difference age and birth order, 270 gender, 267–270 Social support, cross-cultural model formal Asia, service access and use, 199–202 service access and use, immigrant families, 202–204 informal family relationship, 197–198
local vs. immigrant mothers, 198–199 Socioeconomic position definition, 98 family functioning and child well-being, 104–106 methodological and conceptual issues, 112–119 support, IDD chid, 106–111 and poverty IDD prevalence, 100–103 key resources, 98–99 measurement, 99 State–city–regional area, family research database, 156–163 individual information, 165 nondisability survey, 164 Stress. See also Adulthood transition, ID individuals allostatic load approach, 240–241 and psychological well-being, FXS characteristics, mothers, children and families, 223 child challenging behavior, 226 Down syndrome and autistic disorder, 222 FMR1, 226–227 mental health symptoms, 222–223 premutation size, 225 psychopathology and lifetime rate, 221 SCL-90-R depression scores, 224–225 Symptom checklist-90-R (SCL-90-R), 221 T Taoism. See Religious belief Telomere length, 239–240 Transition daily rewards and worries questionnaire (TDRWQ), 79, 80 V Value crisis, 5 W Wisconsin Longitudinal Study (WLS), 156, 164
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Contents of Previous Volumes
Volume 1
Volume 2
A Functional Analysis of Retarded Development SIDNEY W. BIJOU
A Theoretical Analysis and Its Application to Training the Mentally Retarded M. RAY DENNY
Classical Conditioning and Discrimination Learning Research with the Mentally Retarded LEONARD E. ROSS
The Role of Input Organization in the Learning and Memory of Mental Retardates HERMAN H. SPITZ Autonomic Nervous System Functions and Behavior: A Review of Experimental Studies with Mental Defectives RATHE KARRER
The Structure of Intellect in the Mental Retardate HARVEY F. DINGMAN AND C. EDWARD MEYERS Research on Personality Structure in the Retardate EDWARD ZIGLER
Learning and Transfer of Mediating Responses in Discriminating Learning BRYAN E. SHEPP AND FRANK D. TURRISI
Experience and the Development of Adaptive Behavior H. CARL HAYWOOD AND JACK T. TAPP
A Review of Research on Learning Sets and Transfer or Training in Mental Defectives MELVIN E. KAUFMAN AND HERBERT J. PREHM
A Research Program on the Psychological Effects of Brain Lesions in Human Beings RALPH M. REITAN
Programming Perception and Learning for Retarded Children MURRAY SIDMAN AND LAWRENCE T. STODDARD
Long-Term Memory in Mental Retardation JOHN M. BELMONT
Programming Instruction Techniques for the Mentally Retarded FRANCES M. GREENE
The Behavior of Moderately and Severely Retarded Persons JOSEPH E. SPRADLIN AND FREDERIC L. GIRARDEAU
Some Aspects of the Research on Mental Retardation in Norway IVAR ARNIJOT BJORGEN
Author Index-Subject Index
367
368
contents of previous volumes
Research on Mental Deficiency During the Last Decade in France R. LAFON AND J. CHABANIER
A Theory of Primary and Secondary Familial Mental Retardation ARTHUR R. JENSEN
Psychotherapeutic Procedures with the Retarded MANNY STERNLIGHT
Inhibition Deficits in Retardate Learning and Attention LAIRD W. HEAL AND JOHN T. JOHNSON, JR.
Author Index-Subject Index
Volume 3 Incentive Motivation in the Mental Retardate PAUL S. SIEGEL Development of Lateral and Choice-Sequence Preferences IRMA R. GERJUOY AND JOHN J. WINTERS, JR. Studies in the Experimental Development of Left-Right Concepts in Retarded Children Using Fading Techniques SIDNEY W. BIJOU Verbal Learning and Memory Research with Retardates: An Attempt to Assess Developmental Trends L. R. GOULET Research and Theory in Short-Term Memory KEITH G. SCOTT AND MARCIA STRONG SCOTT
Growth and Decline of Retardate Intelligence MARY ANN FISHER AND DAVID ZEAMAN The Measurements of Intelligence A. B. SILVERSTEIN Social Psychology and Mental Retardation WARNER WILSON Mental Retardation in Animals GILBERT W. MEIER Audiologic Aspects of Mental Retardation LYLE L. LLOYD Author Index-Subject Index
Volume 5 Medical-Behavioral Research in Retardation JOHN M. BELMONT Recognition Memory: A Research Strategy and a Summary of Initial Findings KEITH G. SCOTT
Reaction Time and Mental Retardation ALFRED A. BAUMEISTER AND GEORGE KELLAS
Operant Procedures with the Retardate: An Overview of Laboratory Research PAUL WEISBERG
Mental Retardation in India: A Review of Care, Training, Research, and Rehabilitation Programs J. P. DAS
Methodology of Psychopharmacological Studies with the Retarded ROBERT L. SPRAGUE AND JOHN S. WERRY
Educational Research in Mental Retardation SAMUEL L. GUSKIN AND HOWARD H. SPICKER
Process Variables in the Paired-Associate Learning of Retardates ALFRED A. BAUMEISTER AND GEORGE KELLAS
Author Index-Subject Index
Volume 4
Sequential Dot Presentation Measures of Stimulus Trace in Retardates and Normals EDWARD A. HOLDEN, JR.
Memory Processes in Retardates and Normals NORMAN R. ELLIS
Cultural-Familial Retardation FREDERIC L. GIRARDEAU
contents of previous volumes
369
German Theory and Research on Mental Retardation: Emphasis on Structure LOTHAR R. SCHMIDT AND PAUL B. BALTES
Placement of the Retarded in the Community: Prognosis and Outcome RONALD B. MCCARVER AND ELLIS M. CRAIG
Author Index-Subject Index
Physical and Motor Development of Retarded Persons ROBERT H. BRUININKS
Volume 6 Cultural Deprivation and Cognitive Competence J. P. DAS Stereotyped Acts ALFRED A. BAUMEISTER AND REX FOREHAND Research on the Vocational Habilitation of the Retarded: The Present, the Future MARC W. GOLD Consolidating Facts into the Schematized Learning and Memory System of Educable Retardates HERMAN H. SPITZ An Attentional-Retention Theory of Retardate Discrimination Learning MARY ANN FISHER AND DAVID ZEAMAN Studying the Relationship of Task Performance to the Variables of Chronological Age, Mental Age, and IQ WILLIAM E. KAPPAUF Author Index-Subject Index Volume 7 Mediational Processes in the Retarded JOHN G. BORKOWSKI AND PATRICIA B. WANSCHURA The Role of Strategic Behavior in Retardate Memory ANN L. BROWN Conservation Research with the Mentally Retarded KERI M. WILTON AND FREDERIC J. BOERSMA
Subject Index
Volume 8 Self-Injurious Behavior ALFRED A. BAUMEISTER AND JOHN PAUL ROLLINGS Toward a Relative Psychology of Mental Retardation with Special Emphasis on Evolution HERMAN H. SPITZ The Role of the Social Agent in Language Acquisition: Implications for Language Intervention GERALD J. MAHONEY AND PAMELA B. SEELY Cognitive Theory and Mental Development EARL C. BUTTERFIELD AND DONALD J. DICKERSON A Decade of Experimental Research in Mental Retardation in India ARUN K. SEN The Conditioning of Skeletal and Autonomic Responses: Normal-Retardate Stimulus Trace Differences SUSAN M. ROSS AND LEONARD E. ROSS Malnutrition and Cognitive Functioning J. P. DAS AND EMMA PIVATO Research on Efficacy of Special Education for the Mentally Retarded MELVINE E. KAUFMAN AND PAUL A. ALBERTO Subject Index
370 Volume 9 The Processing of Information from Short-Term Visual Store: Developmental and Intellectual Differences LEONARD E. ROSS AND THOMAS B. WARD Information Processing in Mentally Retarded Individuals KEITH E. STANOVICH Mediational Process in the Retarded: Implications for Teaching Reading CLESSEN J. MARTIN Psychophysiology in Mental Retardation J. CLAUSEN Theoretical and Empirical Strategies for the Study of the Labeling of Mentally Retarded Persons SAMUEL L. GUSKIN The Biological Basis of an Ethic in Mental Retardation ROBERT L. ISAACSON AND CAROL VAN HARTESVELDT Public Residential Services for the Mentally Retarded R. C. SCHEERENBERGER Research on Community Residential Alternatives for the Mentally Retarded LAIRD W. HEAL, CAROL K. SIGELMAN, AND HARVEY N. SWITZKY Mainstreaming Mentally Retarded Children: Review of Research LOUIS CORMAN AND JAY GOTTLIEB Savants: Mentally Retarded Individuals with Special Skills A. LEWIS HILL
contents of previous volumes Visual Pattern Detection and Recognition Memory in Children with Profound Mental Retardation PATRICIA ANN SHEPHERD AND JOSEPH F. FAGAN III Studies of Mild Mental Retardation and Timed Performance T. NETTELBECK AND N. BREWER Motor Function in Down’s Syndrome FERIHA ANWAR Rumination NIRBHAY N. SINGH Subject Index
Volume 11 Cognitive Development of the Learning-Disabled Child JOHN W. HAGEN, CRAIG R. BARCLAY, AND BETTINA SCHWETHELM Individual Differences in Short-Term Memory RONALD L. COHEN Inhibition and Individual Differences in Inhibitory Processes in Retarded Children PETER L. C. EVANS Stereotyped Mannerisms in Mentally Retarded Persons: Animal Models and Theoretical Analyses MARK H. LEWIS AND ALFRED A. BAUMEISTER An Investigation of Automated Methods for Teaching Severely Retarded Individuals LAWRENCE T. STODDARD
Volume 10
Social Reinforcement of the Work Behavior of Retarded and Nonretarded Persons LEONIA K. WATERS
The Visual Scanning and Fixation Behavior of the Retarded LEONARD E. ROSS AND SUSAM M. ROSS
Social Competence and Interpersonal Relations between Retarded and Nonretarded Children ANGELA R. TAYLOR
Subject Index
contents of previous volumes The Functional Analysis of Imitation WILLIAM R. MCCULLER AND CHARLES L. SALZBERG Index
371 Autonomy and Adaptability in Work Behavior of Retarded Clients JOHN L. GIFFORD, FRANK R. RUSCH, JAMES E. MARTIN, AND DAVID J. WHITE Index
Volume 12 An Overview of the Social Policy of Deinstitutionalization BARRY WILLER AND JAMES INTAGLIATA Community Attitudes toward Community Placement of Mentally Retarded Persons CYNTHIA OKOLO AND SAMUEL GUSKIN Family Attitudes toward Deinstitutionalization AYSHA LATIB, JAMES CONROY, AND CARLA M. HESS Community Placement and Adjustment of Deinstitutionalized Clients: Issues and Findings ELLIS M. CRAIG AND RONALD B. MCCARVER
Volume 13 Sustained Attention in the Mentally Retarded: The Vigilance Paradigm JOEL B. WARM AND DANIEL B. BERCH Communication and Cues in the Functional Cognition of the Mentally Retarded JAMES E. TURNURE Metamemory: An Aspect of Metacognition in the Mentally Retarded ELAINE M. JUSTICE Inspection Time and Mild Mental Retardation T. NETTELBECK
Issues in Adjustment of Mentally Retarded Individuals to Residential Relocation TAMAR HELLER
Mild Mental Retardation and Memory Scanning C. J. PHILLIPS AND T. NETTELBECK
Salient Dimensions of Home Environment Relevant to Child Development KAZUO NIHIRA, IRIS TAN MINK, AND C. EDWARD MEYERS
Cognitive Determinants of Reading in Mentally Retarded Individuals KEITH E. STANOVICH
Current Trends and Changes in Institutions for the Mentally Retarded R. K. EYMAN, S. A. BORTHWICK, AND G. TARJAN Methodological Considerations in Research on Residential Alternatives for Developmentally Disabled Persons LAIRD W. HEAL AND GLENN T. FUJIURA A Systems Theory Approach to Deinstitutionalization Policies and Research ANGELA A. NOVAK AND TERRY R. BERKELEY
Comprehension and Mental Retardation LINDA HICKSON BILSKY Semantic Processing, Semantic Memory, and Recall LARAINE MASTERS GLIDDEN Proactive Inhibition in Retarded Persons: Some Clues to Short-Term Memory Processing JOHN J. WINTERS, JR. A Triarchic Theory of Mental Retardation ROBERT J. STERNBERG AND LOUIS C. SPEAR Index
372
contents of previous volumes
Volume 14
Volume 15
Intrinsic Motivation and Behavior Effectiveness in Retarded Persons H. CARL HAYWOOD AND HARVEY N. SWITZKY
Mental Retardation as Thinking Disorder: The Rationalist Alternative to Empiricism HERMAN H. SPITZ
The Rehearsal Deficit Hypothesis NORMAN W. BRAY AND LISA A. TURNER Molar Variability and the Mentally Retarded STUART A. SMITH AND PAUL S. SIEGEL Computer-Assisted Instruction for the Mentally Retarded FRANCES A CONNERS, DAVID R. CARUSO, AND DOUGLAS K. DETTERMAN
Developmental Impact of Nutrition on Pregnancy, Infancy, and Childhood: Public Health Issues in the United States ERNESTO POLLITT The Cognitive Approach to Motivation in Retarded Individuals SHYLAMITH KREITLER AND HANS KREITLER Mental Retardation, Analogical Reasoning, and the Componential Method J. MCCONAGHY
Procedures and Parameters of Errorless Discrimination Training with Developmentally Impaired Individuals GIULO E. LANCIONI AND PAUL M. SMEETS
Application of Self-Control Strategies to Facilitate Independence in Vocational and Instructional Settings JAMES E. MARTIN, DONALD L. BURGER, SUSAN ELIAS-BURGER, AND DENNIS E. MITHAUG
Reading Acquisition and Remediation in the Mentally Retarded NIRBHAY N. SINGH AND JUDY SINGH
Family Stress Associated with a Developmentally Handicapped Child PATRICIA M. MINNES
Families with a Mentally Retarded Child BERNARD FARBER AND LOUIS ROWITZ
Physical Fitness of Mentally Retarded Individuals E. KATHRYN MCCONAUGHY AND CHARLES L. SALZBERG
Social Competence and Employment of Retarded Persons CHARLES L. SALZBERG, MARILYN LIKINS, E. KATHRYN MCCONAUGHY, AND BENJAMIN LINGUGARIS/KRAFT Toward a Taxonomy of Home Environments SHARON LANDESMAN Behavioral Treatment of the Sexually Deviant Behavior of Mentally Retarded Individuals R. M. FOXX, R. G. BITTLE, D. R. BECHTEL, AND J. R. LIVESAY Behavior Approaches to Toilet Training for Retarded Persons S. BETTISON Index
Index
Volume 16 Methodological Issues in Specifying Neurotoxic Risk Factors for Developmental Delay: Lead and Cadmium as Prototypes STEPHEN R. SCHROEDER The Role of Methylmercury Toxicity in Mental Retardation GARY J. MYERS AND DAVID O. MARSH Attentional Resource Allocation and Mental Retardation EDWARD C. MERRILL
contents of previous volumes Individual Differences in Cognitive and Social Problem-Solving Skills as a Function of Intelligence ELIZABETH J. SHORT AND STEVEN W. EVANS Social Intelligence, Social Competence, and Interpersonal Competence JANE L. MATHIAS Conceptual Relationships Between Family Research and Mental Retardation ZOLINDA STONEMAN Index Volume 17 The Structure and Development of Adaptive Behaviors KEITH F. WIDAMAN, SHARON A. BORTHWICK-DUFFY, AND TODD D. LITTLE Perspectives on Early Language from Typical Development and Down Syndrome MICHAEL P. LYNCH AND REBECCA E. EILERS The Development of Verbal Communication in Persons with Moderate to Mild Mental Retardation LEONARD ABBEDUTO Assessment and Evaluation of Exceptional Children in the Soviet Union MICHAEL M. GERBER, VALERY PERELMAN, AND NORMA LOPEZ-REYNA Constraints on the Problem Solving of Persons with Mental Retardation RALPH P. FERRETTI AND AL R. CAVALIER Long-Term Memory and Mental Retardation JAMES E. TURNURE Index Volume 18 Perceptual Deficits in Mildly Mentally Retarded Adults ROBERT FOX AND STEPHEN OROSS, III
373 Stimulus Organization and Relational Learning SAL A. SORACI, JR. AND MICHAEL T. CARLIN Stimulus Control Analysis and Nonverbal Instructional Methods for People with Intellectual Disabilities WILLIAM J. MCILVANE Sustained Attention in Mentally Retarded Individuals PHILLIP D. TOMPOROWSKI AND LISA D. HAGER How Modifiable Is the Human Life Path? ANN M. CLARKE AND ALAN D. B. CLARKE Unraveling the ‘‘New Morbidity’’: Adolescent Parenting and Developmental Delays JOHN G. BORKOWSKI, THOMAS L. WHITMAN, ANNE WURTZ PASSINO, ELIZABETH A. RELLINGER, KRISTEN SOMMER, DEBORAH KEOUGH, AND KERI WEED Longitudinal Research in Down Syndrome JANET CARR Staff Training and Management for Intellectual Disability Services CHRIS CULLEN Quality of Life of People with Developmental Disabilities TREVOR R. PARMENTER Index
Volume 19 Mental Retardation in African Countries: Conceptualization, Services, and Research ROBERT SERPELL, LILIAN MARIGA, AND KARYN HARVEY Aging and Alzheimer Disease in People with Mental Retardation WARREN B. ZIGMAN, NICOLE SCHUPF, APRIL ZIGMAN, AND WAYNE SILVERMAN
374 Characteristics of Older People with Intellectual Disabilities in England JAMES HOGG AND STEVE MOSS Epidemiological Thinking in Mental Retardation: Issues in Taxonomy and Population Frequency TOM FRYERS Use of Data Base Linkage Methodology in Epidemiological Studies of Mental Retardation CAROL A. BOUSSY AND KEITH G. SCOTT Ways of Analyzing the Spontaneous Speech of Children with Mental Retardation: The Value of Cross-Domain Analyses CATHERINE E. SNOW AND BARBARA ALEXANDER PAN Behavioral Experimentation in Field Settings: Threats to Validity and Interpretation Problems WILLY-TORE MRCH Index
Volume 20 Parenting Children with Mental Retardation BRUCE L. BAKER, JAN BLACHER, CLAIRE B. KOPP, AND BONNIE KRAEMER Family Interactions and Family Adaptation FRANK J. FLOYD AND CATHERINE L. COSTIGAN Studying Culturally Diverse Families of Children with Mental Retardation IRIS TAN MINK Older Adults with Mental Retardation and Their Families TAMAR HELLER A Review of Psychiatric and Family Research in Mental Retardation ANN GATH
contents of previous volumes A Cognitive Portrait of Grade School Students with Mild Mental Retardation MARCIA STRONG SCOTT, RUTH PEROU, ANGELIKA HARTL CLAUSSEN, AND LOIS-LYNN STOYKO DEUEL Employment and Mental Retardation NEIL KIRBY Index
Volume 21 An Outsider Looks at Mental Retardation: A Moral, a Model, and a Metaprincipal RICHARD P. HONECK Understanding Aggression in People with Intellectual Disabilities: Lessons from Other Populations GLYNIS MURPHY A Review of Self-Injurious Behavior and Pain in Persons with Developmental Disabilities FRANK J. SYMONS AND TRAVIS THOMPSON Recent Studies in Psychopharmacology in Mental Retardation MICHAEL G. AMAN Methodological Issues in the Study of Drug Effects on Cognitive Skills in Mental Retardation DEAN C. WILLIAMS AND KATHRYN J. SAUNDERS The Behavior and Neurochemistry of the Methylazoxymethanol-Induced Microencephalic Rat PIPPA S. LOUPE, STEPHEN R. SCHROEDER, AND RICHARD E.TESSEL Longitudinal Assessment of Cognitive-Behavioral Deficits Produced by the Fragile-X Syndrome GENE S. FISCH Index
contents of previous volumes Volume 22 Direct Effects of Genetic Mental Retardation Syndromes: Maladaptive Behavior and Psychopathology ELISABETH M. DYKENS Indirect Effects of Genetic Mental Retardation Disorders: Theoretical and Methodological Issues ROBERT M. HODAPP The Development of Basic Counting, Number, and Arithmetic Knowledge among Children Classified as Mentally Handicapped ARTHUR J. BAROODY The Nature and Long-Term Implications of Early Developmental Delays: A Summary of Evidence from Two Longitudinal Studies RONALD GALLIMORE, BARBARA K. KEOGH, AND LUCINDA P. BERNHEIMER Savant Syndrome TED NETTELBECK AND ROBYN YOUNG The Cost-Efficiency of Supported Employment Programs: A Review of the Literature ROBERT E. CIMERA AND FRANK R. RUSCH Decision Making and Mental Retardation LINDA HICKSON AND ISHITA KHEMKA ‘‘The Child That Was Meant?’’ or ‘‘Punishment for Sin?’’: Religion, Ethnicity, and Families with Children with Disabilities LARAINE MASTERS GLIDDEN, JEANNETTE ROGERS-DULAN, AND AMY E. HILL Index Volume 23 Diagnosis of Autism before the Age of 3 SALLY J. ROGERS The Role of Secretin in Autistic Spectrum Disorders AROLY HORVATH AND J. TYSON TILDON
375 The Role of Candidate Genes in Unraveling the Genetics of Autism CHRISTOPHER J. STODGELL, JENNIFER L. INGRAM, AND SUSAN L. HYMAN Asperger’s Disorder and Higher Functioning Autism: Same or Different? FRED R. VOLKMAR AND AMI KLIN The Cognitive and Neural Basis of Autism: A Disorder of Complex Information Processing and Dysfunction of Neocortical Systems NANCY J. MINSHEW, CYNTHIA JOHNSON, AND BEATRIZ LUNA Neural Plasticity, Joint Attention, and a Transactional Social-Orienting Model of Autism PETER MUNDY AND A. REBECCA NEAL Theory of Mind and Autism: A Review SIMON BARON-COHEN Understanding the Language and Communicative Impairments in Autism HELEN TAGER-FLUSBERG Early Intervention in Autism: Joint Attention and Symbolic Play CONNIE KASARI, STEPHANNY F. N. FREEMAN, AND TANYA PAPARELLA Attachment and Emotional Responsiveness in Children with Autism CHERYL DISSANAYAKE AND MARIAN SIGMAN Families of Adolescents and Adults with Autism: Uncharted Territory MARSHA MAILICK SELTZER, MARTY WYNGAARDEN KRAUSS, GAEL I. ORSMOND, AND CARRIE VESTAL Index
Volume 24 Self-Determination and Mental Retardation MICHAEL L. WEHMEYER
376 International Quality of Life: Current Conceptual, Measurement, and Implementation Issues KENNETH D. KEITH Measuring Quality of Life and Quality of Services through Personal Outcome Measures: Implications for Public Policy JAMES GARDNER, DEBORAH T. CARRAN, AND SYLVIA NUDLER Credulity and Gullibility in People with Developmental Disorders: A Framework for Future Research STEPHEN GREENSPAN, GAIL LOUGHLIN, AND RHONDA S. BLACK Criminal Victimization of Persons with Mental Retardation: The Influence of Interpersonal Competence on Risk T. NETTELBECK AND C. WILSON The Parent with Mental Retardation STEVE HOLBURN, TIFFANY PERKINS, AND PETER VIETZE Psychiatric Disorders in Adults with Mental Retardation STEVE MOSS Development and Evaluation of Innovative Residential Services for People with Severe Intellectual Disability and Serious Challenging Behavior JIM MANSELL, PETER MCGILL, AND ERIC EMERSON The Mysterious Myth of Attention Deficits and Other Defect Stories: Contemporary Issues in the Developmental Approach to Mental Retardation JACOB A. BURACK, DAVID W. EVANS, CHERYL KLAIMAN, AND GRACE IAROCCI Guiding Visual Attention in Individuals with Mental Retardation RICHARD W. SERNA AND MICHAEL T. CARLIN Index
contents of previous volumes Volume 25 Characterizations of the Competence of Parents of Young Children with Disabilities CARL J. DUNST, TRACY HUMPHRIES, AND CAROL M. TRIVETTE Parent–Child Interactions When Young Children Have Disabilities DONNA SPIKER, GLENNA C. BOYCE, AND LISA K. BOYCE The Early Child Care Study of Children with Special Needs JEAN F. KELLY AND CATHRYN L. BOOTH Diagnosis of Autistic Disorder: Problems and New Directions ROBYN YOUNG AND NEIL BREWER Social Cognition: A Key to Understanding Adaptive Behavior in Individuals with Mild Mental Retardation JAMES S. LEFFERT AND GARY N. SIPERSTEIN Proxy Responding for Subjective Well-Being: A Review ROBERT A. CUMMINS People with Intellectual Disabilities from Ethnic Minority Communities in the United States and the United Kingdom CHRIS HATTON Perception and Action in Mental Retardation W. A. SPARROW AND ROSS H. DAY Volume 26 A History of Psychological Theory and Research in Mental Retardation since World War II DONALD K. ROUTH AND STEPHEN R. SCHROEDER Psychopathology and Intellectual Disability: The Australian Child to Adult Longitudinal Study BRUCE J. TONGE AND STEWART L. EINFELD
contents of previous volumes Psychopathology in Children and Adolescents with Intellectual Disability: Measurement, Prevalence, Course, and Risk JAN L. WALLANDER, MARIELLE C. DEKKER, AND HANS KOOT Resilience, Family Care, and People with Intellectual Disabilities GORDONGRANT, PAULRAMCHARAN, AND PETER GOWARD Prevalence and Correlates of Psychotropic Medication Use among Adults with Developmental Disabilities: 1970–2000 MARIA G. VALDOVINOS, STEPHEN R. SCHROEDER, AND GEUNYOUNG KIM Integration as Acculturation: Developmental Disability, Deinstitutionalization, and Service Delivery Implications M. KATHERINE BUELL Cognitive Aging and Down Syndrome: An Interpretation J. P. DAS Index
377 CARMICHAEL OLSON, AND GERALYN R. TIMLER Memory, Language Comprehension, and Mental Retardation EDWARD C. MERRILL, REGAN LOOKADOO, AND STACY RILEA Reading Skills and Cognitive Abilities of Individuals with Mental Retardation FRANCES A. CONNERS Language Interventions for Children with Mental Retardation NANCY C. BRADY AND STEVEN F. WARREN Augmentative and Alternative Communication for Persons with Mental Retardation MARYANN ROMSKI, ROSE A. SEVCIK, AND AMY HYATT FONSECA Atypical Language Development in Individuals with Mental Retardation: Theoretical Implications JEAN A. RONDAL Index
Volume 27
Volume 28
Language and Communication in Individuals with Down Syndrome ROBIN S. CHAPMAN
Promoting Intrinsic Motivation and Self-Determination in People with Mental Retardation EDWARD L. DECI
Language Abilities of Individuals with Williams Syndrome CAROLYN B. MERVIS, BYRON F. ROBINSON, MELISSA L. ROWE, ANGELA M. BECERRA, AND BONITA P. KLEIN-TASMAN Language and Communication in Fragile X Syndrome MELISSA M. MURPHY AND LEONARD ABBEDUTO On Becoming Socially Competent Communicators: The Challenge for Children with Fetal Alcohol Exposure TRUMAN E. COGGINS, LESLEY B. OLSWANG, HEATHER
Applications of a Model of Goal Orientation and Self-Regulated Learning to Individuals with Learning Problems PAUL R. PINTRICH AND JULIANE L. BLAZEVSKI Learner-Centered Principles and Practices: Enhancing Motivation and Achievement for Children with Learning Challenges and Disabilities BARBARA L. MCCOMBS Why Pinocchio Was Victimized: Factors Contributing to Social Failure in People with Mental Retardation STEPHEN GREENSPAN
378 Understanding the Development of Subnormal Performance in Children from a Motivational-Interactionist Perspective JANNE LEPOLA, PEKKA SALONEN, MARJA VAURAS, AND ELISA POSKIPARTA Toward Inclusion Across Disciplines: Understanding Motivation of Exceptional Students HELEN PATRICK, ALLISON M. RYAN, ERIC M. ANDERMAN, AND JOHN KOVACH Loneliness and Developmental Disabilities: Cognitive and Affective Processing Perspectives MALKA MARGALIT The Motivation to Maintain Subjective Well-Being: A Homeostatic Model ROBERT A. CUMMINS AND ANNA L. D. LAU Quality of Life from a Motivational Perspective ROBERT L. SCHALOCK Index Volume 29 Behavioral Phenotypes: Going Beyond the Two-Group Approach ROBERT M. HODAPP Prenatal Drug Exposure and Mental Retardation ROBERT E. ARENDT, JULIA S. NOLAND, ELIZABETH J. SHORT, AND LYNN T. SINGER Spina Bifida: Genes, Brain, and Development JACK M. FLETCHER, MAUREEN DENNIS, HOPE NORTHRUP, MARCIA A. BARNES, H. JULIA HANNAY, SUSAN H. LANDRY, KIM COPELAND, SUSAN E. BLASER, LARRY A. KRAMER, MICHAEL E. BRANDT, AND DAVID J. FRANCIS The Role of the Basal Ganglia in the Expression of Stereotyped, Self-Injurious Behaviors in Developmental Disorders HOWARD C. CROMWELL AND BRYAN H. KING
contents of previous volumes Risk Factors for Alzheimer’s Disease in Down Syndrome LYNN WARD Precursors of Mild Mental Retardation in Children with Adolescent Mothers JOHN G. BORKOWSKI, JULIE J. LOUNDS, CHRISTINE WILLARD NORIA, JENNIFER BURKE LEFEVER, KERI WEED, DEBORAH A. KEOGH, AND THOMAS L. WHITMAN The Ecological Context of Challenging Behavior in Young Children with Developmental Disabilities ANITA A. SCARBOROUGH AND KENNETH K. POON Employment and Intellectual Disability: Achieving Successful Employment Outcomes KAYE SMITH, LYNNE WEBBER, JOSEPH GRAFFAM, AND CARLENE WILSON Technology Use and People with Mental Retardation MICHAEL L. WEHMEYER, SEAN J. SMITH, SUSAN B. PALMER, DANIEL K. DAVIES, AND STEVEN E. STOCK Index
Volume 30 Neurodevelopmental Effects of Alcohol THOMAS M. BURBACHER AND KIMBERLY S. GRANT PCBs and Dioxins HESTIEN J. I. VREUGDENHIL AND NYNKE WEISGLAS-KUPERUS Interactions of Lead Exposure and Stress: Implications for Cognitive Dysfunction DEBORAH A. CORY-SLECHTA
contents of previous volumes Developmental Disabilities Following Prenatal Exposure to Methyl Mercury from Maternal Fish Consumption: A Review of the Evidence GARY J. MYERS, PHILIP W. DAVIDSON, AND CONRAD F. SHAMLAYE Environmental Agents and Autism: Once and Future Associations SUSAN L. HYMAN, TARA L. ARNDT, AND PATRICIA M. RODIER Endocrine Disruptors as a Factor in Mental Retardation BERNARD WEISS The Neurotoxic Properties of Pesticides HERBERT L. NEEDLEMAN Parental Smoking and Children’s Behavioral and Cognitive Functioning MICHAEL WEITZMAN, MEGAN KAVANAUGH, AND TODD A. FLORIN Neurobehavioral Assessment in Studies of Exposures to Neurotoxicants DAVID C. BELLINGER From Animals to Humans: Models and Constructs DEBORAH C. RICE
379 Individual Differences in Interpersonal Relationships for Persons with Mental Retardation YONA LUNSKY Understanding Low Achievement and Depression in Children with Learning Disabilities: A Goal Orientation Approach GEORGIOS D. SIDERIDIS Motivation and Etiology-Specific Cognitive–Linguistic Profiles DEBORAH J. FIDLER The Role of Motivation and Psychopathology in Understanding the IQ–Adaptive Behavior Discrepancy ´ AND MARC J. TASSE SUSAN M. HAVERCAMP Behavior-Analytic Experimental Strategies and Motivational Processes in Persons with Mental Retardation WILLIAM V. DUBE AND WILLIAM J. MCILVANE A Transactional Perspective on Mental Retardation H. CARL HAYWOOD Index
Index
Volume 32
Volume 31
Research on Language Development and Mental Retardation: History, Theories, Findings, and Future Directions LEONARD ABBEDUTO, YOLANDA KELLER-BELL, ERICA KESIN RICHMOND, AND MELISSA M. MURPHY
The Importance of Cognitive–Motivational Variables in Understanding the Outcome Performance of Persons with Mental Retardation: A Personal View from the Early Twenty-First Century HARVEY N. SWITZKY Self-Determination, Causal Agency, and Mental Retardation MICHAEL L. WEHMEYER AND DENNIS E. MITHAUG The Role of Motivation in the Decision Making of Adolescents with Mental Retardation ISHITA KHEMKA AND LINDA HICKSON
Residential Services Research in the Developmental Disabilities Sector STEVE HOLBURN AND JOHN W. JACOBSON The Measurement of Poverty and Socioeconomic Position in Research Involving People with Intellectual Disability ERIC EMERSON, HILARY GRAHAM, AND CHRIS HATTON
380 The Influence of Prenatal Stress and Adverse Birth Outcome on Human Cognitive and Neurological Development LAURA M. GLYNN AND CURT A. SANDMAN Fluid Cognition: A Neglected Aspect of Cognition in Research on Mental Retardation CLANCY BLAIR AND MEGAN PATRICK Dietary Supplementation with Highly Unsaturated Fatty Acids: Implications for Interventions with Persons with Mental Retardation from Research on Infant Cognitive Development, ADHD, and Other Developmental Disabilities NATALIE SINN AND CARLENE WILSON Screening for Autism in Infants, Children, and Adolescents KYLIE M. GRAY, BRUCE J. TONGE, AND AVRIL V. BRERETON People with Mental Retardation and Psychopathology: Stress, Affect Regulation and Attachment: A Review CARLO SCHUENGEL AND CEES G. C. JANSSEN Diagnosis of Depression in People with Developmental Disabilities: Progress and Problems ANN R. POINDEXTER Index Volume 33 Developmental Epidemiology of Mental Retardation/Developmental Disabilities: An Emerging Discipline ROBERT M. HODAPP AND RICHARD C. URBANO Record Linkage: A Research Strategy for Developmental Epidemiology RICHARD C. URBANO Second-Order Linkage and Family Datasets SHIHFEN TU, CRAIG A. MASON, AND QUANSHENG SONG
contents of previous volumes Incorporating Geographical Analysis into the Study of Mental Retardation and Developmental Disabilities RUSSELL S. KIRBY Statistical Issues in Developmental Epidemiology and Developmental Disabilities Research: Confounding Variables, Small Sample Size, and Numerous Outcome Variables JENNIFER URBANO BLACKFORD Economic Perspectives on Service Choice and Optimal Policy: Understanding the Effects of Family Heterogeneity on MR/DD Outcomes STEPHANIE A. SO Public Health Impact: Metropolitan Atlanta Developmental Disabilities Surveillance Program RACHEL NONKIN AVCHEN, TANYA KARAPURKAR BHASIN, KIM VAN NAARDEN BRAUN, AND MARSHALYN YEARGIN-ALLSOPP Using GIS to Investigate the Role of Recreation and Leisure Activities in the Prevention of Emotional and Behavioral Disorders TINA L. STANTON-CHAPMAN AND DEREK A. CHAPMAN The Developmental Epidemiology of Mental Retardation and Developmental Disabilities DENNIS P. HOGAN, MICHAEL E. MSALL, AND JULIA A. RIVERA DREW Evolution of Symptoms and Syndromes of Psychopathology in Young People with Mental Retardation STEWART L. EINFELD, BRUCE J. TONGE, KYLIE GRAY, AND JOHN TAFFE Index Volume 34 Historical Overview of Assessment in Intellectual Disability STEPHEN R. SCHROEDER AND R. MATTHEW REESE Assessing Mental Retardation Using Standardized Intelligence Tests
contents of previous volumes
381
BARBARA TYLENDA, JACQUELINE BECKETT, AND ROWLAND P. BARRETT
Pain Assessment FRANK ANDRASIK AND CARLA RIME
Adaptive Behavior Scales DENNIS R. DIXON
Index
Educational Assessment MARK F. O’REILLY, BONNIE O’REILLY, JEFF SIGAFOOS, GIULIO LANCIONI, VANESSA GREEN, AND WENDY MACHALICEK Autism and Pervasive Developmental Disorders BART M. SEVIN, CHERYL L. KNIGHT, AND SCOTT A. BRAUD Psychopathology: Depression, Anxiety, and Related Disorders PETER STURMEY Psychotropic Medication Effect and Side Effects ERIK A. MAYVILLE Memory Disorders HEATHER ANNE STEWART AND HOLLY GARCIE-MERRITT Assessment of Self-Injurious and Aggressive Behavior JOHANNES ROJAHN, THEODORE A. HOCH, KATIE WHITTAKER, ´ LEZ AND MELISSA L. GONZA Social Skills JONATHAN WILKINS AND JOHNNY L. MATSON Self-Care Skills REBECCA L. MANDAL, BRANDI SMIROLDO, AND JOANN HAYNES-POWELL Feeding Disorders DAVID E. KUHN, PETER A. GIROLAMI, AND CHARLES S. GULOTTA
Volume 35 Theory and Research on Autism: Do We Need a New Approach to Thinking About and Studying This Disorder? THOMAS L. WHITMAN AND NAOMI EKAS Social Cognition in Children with Down Syndrome KATIE R. CEBULA AND JENNIFER G. WISHART The Development of Social Competence Among Persons with Down Syndrome: From Survival to Social Inclusion GRACE IAROCCI, JODI YAGER, ADRIENNE ROMBOUGH, AND JESSICA MCLAUGHLIN The Flynn Effect and the Shadow of the Past: Mental Retardation and the Indefensible and Indispensable Role of IQ JAMES R. FLYNN AND KEITH F. WIDAMAN Remaining Open to Quantitative, Qualitative, and Mixed-Method Designs: An Unscientific Compromise, or Good Research Practice? KEITH R. MCVILLY, ROGER J. STANCLIFFE, TREVOR R. PARMENTER, AND ROSANNE M. BURTON-SMITH Active Support: Development, Evidence Base, and Future Directions VASO TOTSIKA, SANDY TOOGOOD, AND RICHARD P. HASTINGS
382 Child Abuse Among Children with Disabilities: What We Know and What We Need to Know MARISA H. FISHER, ROBERT M. HODAPP, AND ELISABETH M. DYKENS Siblings of Children with Mental Retardation: The Role of Helping ELIZABETH MIDLARSKY, MARY ELIZABETH HANNAH, EREL SHVIL, AND AMANDA JOHNSON Index Volume 36 Newborn Screening for Intellectual Disability: Past, Present, and Future DON BAILEY Responsive Parenting: Closing the Learning Gap for Children with Early Developmental Problems SUSAN H. LANDRY, HEATHER B. TAYLOR, CATHY GUTTENTAG, AND KAREN E. SMITH Trisomy 21: Causes and Consequences JEANNIE VISOOTSAK AND STEPHANIE L. SHERMAN Alzheimer’s Disease in Adults with Down Syndrome WARREN B. ZIGMAN, DARLYNNE A. DEVENNY, SHARON J. KRINSKY-
contents of previous volumes MCHALE, EDMUND C. JENKINS, TIINA K. URV, JERZY WEGIEL, NICOLE SCHUPF, AND WAYNE SILVERMAN Foolish Action in Adults with Intellectual Disabilities: The Forgotten Problem of Risk-Unawareness STEPHEN GREENSPAN Animal Models of Self-Injurious Behavior: Induction, Prevention, and Recovery STEPHEN R. SCHROEDER, PIPPA S. LOUPE, AND RICHARD E. TESSEL Theoretical and Methodological Issues in Sibling Research J. CAROLYN GRAFF, SUSAN NEELYBARNES, AND HEATHER SMITH Understanding Individual Differences in Adaptation in Parents of Children with Intellectual Disabilities: A Risk and Resilience Perspective MALIN B. OLSSON ‘‘What do you Think if . . .’’: Using Vignettes to Study Attitudes Toward Adult Sibling Caregiving and Competence of Parents of Children with Disabilities BRIAN M. JOBE AND LARAINE M. GLIDDEN Index
