V O LU M E
T H I RT Y
F I V E
INTERNATIONAL REVIEW OF
RESEARCH IN MENTAL RETARDATION
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 M. SELTZER University of Wisconsin-Madison
JAN WALLANDER Sociometrics Corporation
V O LU M E
T H I RT Y
F I V E
INTERNATIONAL REVIEW OF
RESEARCH IN MENTAL RETARDATION Edited by
LARAINE MASTERS GLIDDEN Department of Psychology St. Mary’s College of Maryland St. Mary’s City, Maryland
AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier
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CONTENTS
Contributors Preface
ix xi
1. Theory and Research on Autism: Do We Need a New Approach to Thinking About and Studying This Disorder?
1
Thomas L. Whitman and Naomi Ekas 1. Introduction 2. Toward a Developmental Theory of Autism 3. Characteristics Associated with Autism 4. Future Research Directions 5. Final Thoughts References
2. Social Cognition in Children with Down Syndrome
2 4 7 28 31 34
43
Katie R. Cebula and Jennifer G. Wishart 1. Introduction 2. Early Indicators of Emerging Sociocognitive Understanding 3. Later Developments in Social Cognition: Understanding and Relating to Others 4. Linking Sociocognitive and Cognitive Development: Learning from and with Others 5. Conclusions References
44 49
68 72 76
3. The Development of Social Competence Among Persons with Down Syndrome: From Survival to Social Inclusion
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Grace Iarocci, Jodi Yager, Adrienne Rombough, and Jessica McLaughlin 1. Introduction 2. The Case for Social Competence Research on DS 3. Defining the Construct of Social Competence
88 89 89
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4. Status of Evidence on Social Competence in DS 5. Conclusion References
4. The Flynn Effect and the Shadow of the Past: Mental Retardation and the Indefensible and Indispensable Role of IQ
92 109 110
121
James R. Flynn and Keith F. Widaman 1. Introduction 2. The Flynn Effect and MR Diagnosis 3. Possible Solutions 4. Concluding Remarks References
5. Remaining Open to Quantitative, Qualitative, and Mixed-Method Designs: An Unscientific Compromise, or Good Research Practice?
122 122 137 142 148
151
Keith R. Mcvilly, Roger J. Stancliffe, Trevor R. Parmenter, and Rosanne M. Burton-Smith 1. Introduction 2. Selecting Appropriate Research Method(s) 3. Quantitative, Qualitative, and Mixed-Method Designs 4. Collecting Data Using Different Research Designs 5. Summary and Concluding Remarks References
6. Active Support: Development, Evidence Base, and Future Directions
152 153 159 182 194 195
205
Vaso Totsika, Sandy Toogood, and Richard P. Hastings 1. 2. 3. 4. 5. 6.
Introduction What is Active Support? Staff Training in Active Support Recent Developments in Active Support and the Training Model Conceptual Issues Setting the Context for Evaluating the Effects of Active Support Implementation 7. Evidence Base for Active Support 8. Discussion and Future Directions References
206 207 214 215 217 225 227 238 242
Contents
7. Child Abuse Among Children with Disabilities: What We Know and What We Need to Know
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Marisa H. Fisher, Robert M. Hodapp, and Elisabeth M. Dykens 1. Introduction 2. Definitional and Methodological Issues 3. Demographics of Child Abuse in Children with Disabilities 4. Going beyond more or less Abuse 5. Remaining Issues for Research 6. Conclusion References
8. Siblings of Children with Mental Retardation: The Role of Helping
252 253 263 269 278 282 283
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Elizabeth Midlarsky, Mary Elizabeth Hannah, Erel Shvil, and Amanda Johnson 1. Introduction 2. Impact of Having a Sibling with Mental Retardation 3. Factors Associated with Adjustment 4. Methodological Considerations 5. Helping by Siblings of Children with Mental Retardation 6. Conclusions and Future Directions References Index Contents of Previous Volumes
292 293 295 301 304 312 313 319 327
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CONTRIBUTORS
Numbers in parentheses indicate the pages on which the authors’ contributions begin.
Rosanne M. Burton-Smith (151) School of Psychology, University of Tasmania, Hobart Campus, Humanities Building 118, Hobart, Tasmania 7001, Australia Katie R. Cebula (43) Moray House School of Education, University of Edinburgh, Holyrood Road, Edinburgh, EH8 8AQ, Scotland, UK Elisabeth M. Dykens (251) Vanderbilt Kennedy Center and Department of Special Education, Peabody College at Vanderbilt University, Nashville, Tennessee 37203, USA Naomi Ekas (1) Department of Psychology, University of Notre Dame, 118 Haggar Hall, Notre Dame, IN 46556, USA Mary Elizabeth Hannah (291) Department of Psychology, University of Detroit, Mercy, 4001 W. McNichols Road, Detroit, MI 48219, USA Marisa H. Fisher (251) Vanderbilt Kennedy Center and Department of Special Education, Peabody College at Vanderbilt University, Nashville, Tennessee 37203, USA James R. Flynn (121) Department of Political Studies, University of Otago, PO Box 56, Dunedin, New Zealand Richard P. Hastings (205) School of Psychology, Bangor University, Adeilad Brigantia, Bangor, Gwynedd, LL58 2AS, UK Robert M. Hodapp (251) Vanderbilt Kennedy Center and Department of Special Education, Peabody College at Vanderbilt University, Nashville, Tennessee 37203, USA Grace Iarocci (87) Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada Amanda Johnson (291) Department of Counseling & Clinical Psychology, Teachers College, Columbia, 525 West 120th Street, New York, NY 10027, USA ix
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Contributors
Jessica McLaughlin (87) Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada Keith R. McVilly (151) Division of Disability Studies, School of Health Sciences, RMIT University, P.O. Box 71, Bundoora, Victoria 3083, Australia Elizabeth Midlarsky (291) Department of Counseling & Clinical Psychology, Teachers College, P. O. Box 148, Columbia, 525 West 120th Street, New York, NY 10027, USA Trevor R. Parmenter (151) Centre for Developmental Disability Studies, University of Sydney, P.O. Box 6, RYDE, New South Wales 1680, Australia Adrienne Rombough (87) Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada Erel Shvil (291) Department of Counseling & Clinical Psychology, Teachers College, Columbia, 525 West 120th Street, New York, NY 10027, USA Roger J. Stancliffe (151) Centre for Developmental Disability Studies, University of Sydney, P.O. Box 6, RYDE, New South Wales 1680, Australia Sandy Toogood (205) School of Psychology, Bangor University, Adeilad Brigantia, Bangor, Gwynedd, LL58 2AS, UK Vaso Totsika (205) School of Psychology, Bangor University, Adeilad Brigantia, Bangor, Gwynedd, LL58 2AS, UK Thomas L. Whitman (1) Department of Psychology, University of Notre Dane, 127 Haggar Hall, Notre Dame, IN 46556, USA Keith F. Widaman (121) Department of Psychology, University of California at Davis, 265 Young Hall, Davis, CA 95616, USA Jennifer G. Wishart (43) Moray House School of Education, University of Edinburgh, Holyrood Road, Edinburgh, EH8 8AQ, Scotland, UK Jodi Yager (87) Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
PREFACE
This current volume of the International Review of Research in Mental Retardation includes chapters that cover a broad array of topics in the mental retardation/developmental disabilities field. They range from ones that focus on theoretical and methodological concerns such as Chapter 4 by James Flynn and Keith Widaman, and Chapter 5 by Keith McVilly, Roger Stancliffe, Trevor Parmenter, and Rosanne Burton-Smith and those that, like Chapter 2 by Katie Cebula and Jennifer Wishart, although not neglecting theory, are also data laden. The breadth of the chapters is also exemplified in the diversity of the developmental disabilities that are the focus, as well as the ages and stages of life that are of interest. Clearly, this breadth demands many reviewers whose expertise is wide ranging. I am pleased to acknowledge the service that more than a dozen individuals selflessly provided to the field. For her work on this volume, I particularly appreciate the efforts of associate editor Connie Kasari, who both reviewed and brought others into the reviewing process. In addition to Connie, I thank the following individuals, listed alphabetically: Nurit Bauminger, Julie Beadle-Brown, Steve Ceci, Victor Cicirelli, Debbie Fidler, Steve Greenspan, Amanda Gulsrud, Mike Guralnick, Bob Hodapp, Laudan Jahromi, Derek Moore, Bob Schalock, Matt Scullin, Dick Sobsey, Roger Stancliffe, Zo Stoneman, and Harvey Switzky. Each provided insightful and timely reviews that helped to strengthen manuscripts, providing authors with commentary that offered additional perspectives on the topics. We owe them gratitude and respect. Although this volume is eclectic, the eight chapters have varied connections with each other. The first three are interrelated in their attention to two prevalent conditions associated with mental retardation and developmental disabilities. In Chapter 1, Thomas Whitman and Naomi Ekas propose a theory of autism that more fully accounts for the dynamic interrelations of the various characteristics of autism than do more unidimensional theories. As with all theories, the interplay between proposition and confirmation must be resolved empirically, and I predict that this chapter will have substantial heuristic value, as investigators pursue verification. Chapters 2 and 3 both focus on children with Down syndrome, and indeed, in each chapter the work of the other authors is cited. In their focus on social cognition, Katie Cebula and Jennifer Wishart review much of xi
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their own programmatic research and conclude that in order to move forward, future research should compare across syndromes and ages, use longitudinal methodology, and demonstrate the role that social-cognitive deficits have in day-to-day functioning. Grace Iarocci, Jodi Yager, Adrienne Rombough, and Jessica McLaughlin would not be likely to disagree with these recommendations. Indeed, their emphasis is on socially competent behavior as part of day-to-day functioning. They conclude that although social-cognitive deficits certainly contribute to difficulties in attaining social competence, inadequate contextual supports are also responsible. Iarocci et al. organized their review by both age and type of social interaction, helping to ensure that this chapter will be accessible and of interest to a relatively large number of investigators. Chapters 4 and 5 are methodological in their emphasis. James Flynn and Keith Widaman review and summarize the evidence for the ‘‘Flynn effect,’’ i.e., that gains in IQ over time render test norms increasingly inaccurate as the time since intelligence test publication increases. They review the implications of this effect and question the continued use of testing and classification practice. In the United States, the Flynn effect has serious implications for capital offenders who function at the upper border of mild mental retardation. Thus, this chapter is genuinely dealing with a life or death issue. Keith McVilly, Roger Stancliffe, Trevor Parmenter, and Rosanne Burton-Smith are masterful teachers in Chapter 5 of this volume. It is based on the award-winning dissertation research of Dr. McVilly, and he and his co-authors focus on evaluating the merits and pitfalls of qualitative and quantitative designs, concluding that mixed-method approaches are frequently the solution in research with persons with intellectual disability. One strength of this review is that it addresses both philosophical and pragmatic aspects of the choice of methodology. Whereas the earlier chapters by Cebula and Wishart and Iarocci et al. focus almost exclusively on children and adolescents, Vaso Totsika, Sandy Toogood, and Richard Hastings propose a person-focused model of care for adults with intellectual disability living in community-based small homes. Their active support model aims to maximize participation of persons with ID in activities of daily life and the authors review the model comprehensively, including the evidence base for the effectiveness of its interventions, and the challenges that real-world settings pose for its implementation. For several decades, there has been recognition that children with disabilities are at greater risk for child abuse than children without disabilities. In their chapter, Marisa Fisher, Robert Hodapp, and Elisabeth Dykens review the research evidence and conclude that even though methodological and definitional problems with the research must qualify the findings, there is little doubt that this greater risk is substantial, likely a combination of characteristics of the children, of the families, and of the ecological context.
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It is essential, they point out, to design research protocols that will determine whether these risk factors operate similarly regardless of whether the child has disabilities or not. Although children with disabilities may be at greater risk of abuse and neglect, they also may experience more helping behavior. In the final chapter of volume 35, Elizabeth Midlarsky, Mary Elizabeth Hannah, Erel Shvil, and Amanda Johnson examine the helping behavior of typical siblings of children with mental retardation. They propose that engaging in helping behavior promotes positive adaptation of the typically developing brothers and sisters, and they examine both conceptual and empirical evidence supporting their view. These eight chapters, then, represent an amazing breadth of issues. There is certainly something for everyone, and, in most cases, there is a lot for each of us. It is a testimony to the vigor of the field, and the complexity and multidimensionality of the condition. Mental retardation and developmental disabilities must be approached from the most basic biological and neurogenetic functioning to the variables of family and culture and how the macroenvironment influences functioning. They are all crucial to the ultimate understanding of mental retardation and how to prevent and treat it. LARAINE MASTERS GLIDDEN
C H A P T E R
O N E
Theory and Research on Autism: Do We Need a New Approach to Thinking About and Studying This Disorder? Thomas L. Whitman* and Naomi Ekas† Contents 2 4 7 7 12 14 16 19 23
1. Introduction 2. Toward a Developmental Theory of Autism 3. Characteristics Associated with Autism 3.1. Arousal/activation and emotion processes 3.2. Sensory processing 3.3. Motor characteristics 3.4. Cognitive characteristics 3.5. Social interaction deficiencies 3.6. Communication and language 3.7. Repetitive, restricted, and stereotyped behavior: A self-regulatory perspective 4. Future Research Directions 5. Final Thoughts Acknowledgments References
25 28 31 34 34
Abstract Most theories of autism have tended to be static and unidimensional, often focusing on one process that is purported to be defective, while ignoring other potentially important emergent processes. In this chapter, a comprehensive and developmental theory of autism is proposed, describing the interrelationship between symptoms/processes diagnostically associated with autism and other features that commonly co-occur with this disorder. Past research relating to specific symptoms associated with autism is then described, with a special emphasis placed on examining how these symptoms may influence one another. Finally, future research directions along with research methodologies that can be
* {
Department of Psychology, University of Notre Dame, 127 Haggar Hall, Notre Dame, IN 46556, USA Department of Psychology, University of Notre Dame, 118 Haggar Hall, Notre Dame, IN 46556, USA
International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35001-5
#
2008 Elsevier Inc. All rights reserved.
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employed to evaluate the structure of complex systems and how they change over time are discussed.
1. Introduction Autism is a developmental disorder that is characterized by social interaction and language/communication deficiencies as well as by the presence of stereotyped and restricted behavior patterns. Within the DSM-IV classification system, Autistic disorder is one of several disorders within a larger category of pervasive developmental disorders (PDD), which also includes Rett’s disorder, Childhood Disintegrative Disorder, Asperger’s Syndrome (AS), and Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS). All of these latter disorders share core characteristics in common with Autistic Disorder and are sometimes given the label nonautistic PDDs (American Psychiatric Association, 2000). Autism is often referred to as a spectrum disorder because of the marked individual differences that exist among persons diagnosed as autistic. This variation is reflected in many domains, including social, language/communication, and cognitive functioning. For example, many individuals with autism are characterized as having mental retardation; however, some function in the average and above average range of intelligence. Individuals who meet the criteria of mental retardation are estimated to be around 75% (American Psychiatric Association, 2000). This figure may be inflated, however, because individuals with autism are at a disadvantage in IQ testing situations because of their social and communication impairments. Autism is commonly acknowledged to have a genetic basis. Evidence for this assertion comes from various types of research, including twin, family, and genetic linkage studies (Rutter, 2005; Whitman, 2004, pp. 119–122). However, the pattern of inheritance and the factors affecting genetic expression appear to be complicated. Genetic linkage studies suggest that a number of genes, perhaps from 15 to 20, are needed to produce the characteristics associated with autism. Research also has suggested that what is inherited is a genetic susceptibility, with extrinsic agents, such as an infection or toxin, possibly serving as a trigger for vulnerable individuals. The complexity of autism at the genetic level is mirrored at both a structural and a neurochemical level, with numerous parts of the brain and a variety of neurotransmitters and neurohormones being proposed as playing a role in this disorder (Whitman, 2004, pp. 124–132). Despite its biological roots, autism appears to be a plastic disorder, capable of being influenced by early intervention programs. Although genetic and biological markers are being sought, the diagnosis of autism is currently based on the examination of behavioral signs.
Theory and Research on Autism
3
Historically, autism was not diagnosed until age three or later; however, recent research indicates that screening for autism and earlier diagnosis, during the second and even first year of life, is possible (Coonrod & Stone, 2005). Estimates of the incidence of autism have varied considerably over time, ranging from 2 to 72 children per 10,000 births (Fombonne, 2005). Recent estimates have suggested that the incidence of autism is increasing and that it may occur in 1 out of every 150 births. Some researchers have maintained that this apparent increase is an artifact, related to the emergence of clearer diagnostic criteria, better assessment instruments, and greater professional and parent awareness. Other individuals have asserted, however, that the increase is real and related to factors such as immunization procedures and increases in environmental toxins in the earth, air, and water (Whitman, 2004, pp. 43–45). From a demographic perspective, it is known that autism occurs more frequently in males than females, with a ratio of somewhere between 3:1 and 4:1; however, autism in females is generally associated with greater developmental delays than in males. Furthermore, research suggests no difference in incidence in autism across social classes; however, it may be diagnosed more frequently in higher socioeconomic status individuals because parents are more proactive in seeking out services for their children when developmental problems occur (Fombonne, 2005). At present, there is no known medical cure for autism. However, there is evidence that some medications may be used to control specific autistic or comorbid symptoms. Moreover, research has repeatedly shown the importance of early educational interventions that are individualized and intensive in nature. A range of studies have suggested that, when begun early, such interventions can have a dramatic effect on the trajectory of this disorder, with individuals occasionally achieving developmental levels approximating those of neurotypical individuals (Whitman, 2004, pp. 176–232). In this chapter, we will describe current theory and research focusing on symptoms/processes diagnostically associated with autism and other features that commonly co-occur with this disorder. These symptoms/processes include arousal/emotion, sensory, motor, cognitive, social, language/communication, and restricted, repetitive, and stereotyped behaviors. Although a variety of theories have been proposed to explain autism, these theories have tended to be static and unidimensional, often focusing on one process that is purported to be defective, while ignoring other potentially important emergent processes. In contrast, in this chapter, a comprehensive and developmental theory of autism is proposed, describing different ways that the various characteristics of autism may be dynamically interrelated. After presenting this theory, past research and theory relating to specific symptoms associated with autism are described, with a special emphasis placed on examining how these symptoms may influence one another. At the end of the chapter, we discuss future research directions along with research
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methodologies that can be employed to evaluate the structure of complex systems and how they change over time.
2. Toward a Developmental Theory of Autism Despite the increasing theoretical and empirical attention being given to the study of autism, there remains a considerable difference of opinion about how this disorder develops. Theory formulation is particularly difficult because of the number and heterogeneous nature of the symptoms associated with autism. Both theory and research have typically focused on only one or two of the characteristics of autism, most commonly a particular cognitive, or social process. At present, however, it is not clear which symptoms of autism are primary, that is, critical components of a process leading to other symptoms. In this section, a broader and more dynamic theoretical perspective regarding its origins is presented that considers not only symptoms diagnostically associated with autism but also other characteristics commonly connected to this disorder. We believe that a comprehensive theory of autism should
Describe the processes underlying both its initial emergence and later development. Account for the considerable individual differences in persons labeled autistic. Ideally, a comprehensive theory should provide insights not only into the reasons for differences in individuals diagnosed with autistic disorder but also differences between individuals with this diagnosis and other individuals on the autism spectrum, including AS and PDD-NOS. From a theoretical perspective, it is reasonable to assume that different causal pathways may be needed to explain these individual differences. View autism as emerging through an interaction of a variety of individual processes, with the pattern of relations between and among these processes likely changing over time. To study these changing patterns, longitudinal designs need to be employed. As Smith and Thelen (1993) have pointed out, emergent behaviors show patterns over time that are not contained in any of their components when evaluated in a cross-sectional fashion. Make sense at both a biological and a psychobehavioral level. It is assumed at one level that autism is a genetic disorder that affects development and functioning at an anatomical and neurophysiological level, and, in turn, behavior. Conversely, biological development is affected by behavior development and both types of development are influenced by environmental factors. Biological and/or environmental stressors may change the microstructure of the brain, resulting in impaired sensitivity and a cascade of events that lead to a cycle of increasing impairments at both a biological and a behavioral level.
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Constructing a theory that incorporates the aforementioned characteristics is a demanding task. The theory, presented in Fig. 1.1, represents one approximation of how it might be constructed. This theory postulates that a number of factors need to be considered in order to understand the development of autism in its diverse manifestations. Three of the constructs in the theory relate to symptoms/processes referred to in the DSM-IV (American Psychiatric Association, 2000) definition of autism—social interaction deficiencies, communication/language deficiencies, and repetitive, restricted, and stereotyped responses. Four other constructs in the theory consist of symptoms/processes— arousal/emotion, sensory, motor, and cognitive—that are not a formal part of this definition. The self-regulatory construct in Fig. 1.1 refers to the processes employed by individuals with autism to cope with their environment. The stereotyped, restrictive, and repetitive behaviors displayed by individuals with autism are reflective of a poorly developed self-regulatory system that evolves because more sophisticated forms of self-regulation are not learned. The six processes, depicted to the left of the self-regulatory construct in Fig. 1.1, are hypothesized to influence the development of the self-regulatory system, which in turn influences in a reciprocal fashion the development of these other processes. More specifically, as Whitman (2004) has suggested, their unique selfregulatory style is shaped by their cognitive, language, and social deficiencies as well as their emotional, sensory, and motor problems. Effective self-regulation requires an optimal level of arousal, with both hyperarousal and hypoarousal associated with diminished functioning. The sensory system is critical for self-regulation because it provides information to the individuals about the environment and their behavior. The motor
Language/ communication processes
Sensory processes Arousal activation emotion processes
Cognitive processes Motor processes
Social interaction processes
Selfregulation processes
Figure 1.1 A developmental theory of autism: The role of arousal/activation, sensory, motor, cognitive, language/communication, and social interaction processes in the emergence of self-regulation.
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system enables individuals to engage in rudimentary self-regulation acts when distressed, such as sucking and cuddling, as well as provides a structural foundation for the development of more complex, cognitive, linguistic, and social forms of self-regulation. The cognitive, language, and social interaction systems provide individuals the advanced tools (e.g., executive functioning, self-instruction, and information-seeking) that they need to strategically guide their behavior. Because each of these systems is frequently compromised in children with autism, an immature selfregulatory system emerges. This immature self-regulatory system is not only influenced by the emotional, sensorimotor, cognitive, language, and social processes but in turn also influences these processes, with selfregulation deficiencies resulting in problems and deficiencies in motor planning, rule-governed behavior, problem solving, self-monitoring, following social protocols and emotion management. All of the theoretical constructs in Fig. 1.1 can be considered, either directly or indirectly, as ‘‘causes’’ that exert influence across time on the other constructs; thus, constituting a complex chain of ‘‘causality’’ that results in the emergence of the symptoms of autism. The theory assumes that the characteristics referred to in the seven constructs change over time and, thus, the system as a whole is in a constant state of reorganization. Moreover, all of the constructs can be considered at either a psychobehavioral or a neurobiological level. The theory, therefore, can be considered, at least implicitly, as psychobiological in nature. Although all of the processes referred to in the theory described in Fig. 1.1 exert influence, either directly or indirectly, on the other processes, the three processes on the left side of Fig. 1.1 (arousal/activation/emotion, sensory, and motor processes) mature earlier developmentally than the other processes (cognition, language/communication, and social interaction) and for that reason may play a particularly critical role during the initial stages of emergence of autism. For example, children with autism appear to be especially vulnerable to stress because their early environment is chaotic and challenging. If early stress is not managed, the development of their sensory and motor as well as their cognitive, language, and social interaction systems is likely placed at risk for delays. Such delays in turn make it difficult for individuals with autism to develop more mature forms of regulating their emotions and behaviors and to engage in independent, intentional, and goal-directed action (Ruble, 2001). Similarly, the theory also suggests that individuals who have early motor or sensory problems may have a different trajectory of cognitive, language, and social development than individuals without these early problems (see Fig. 1.1). Thus, the theory allows for the possibility that these early occurring processes may play a major role in the development of different symptom patterns for some children on the autism spectrum, with the role of these early emerging processes diminishing as the cognitive and communication systems mature.
Theory and Research on Autism
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The theory presented in Fig. 1.1 is likely to be refined and perhaps even radically modified by future research. A major advantage of this theory is, however, that it does not exclude potentially important processes and interactions among the processes that may be important for understanding how autism unfolds. In Section 3, research and theory examining each of the characteristics/constructs outlined in this theory and their possible interrelationships are described.
3. Characteristics Associated with Autism Whereas researchers have actively studied the social, cognitive, and language/communication features associated with autism, less attention has been given to the investigation of other processes, specifically affective, sensory, and motor, that may play a dynamic role in the early development of this disorder. For this reason, these latter processes are discussed first in this section. After examining each of the aforementioned features of autism, self-regulation processes in children with autism will be described along with their connections to stereotyped and restrictive behavior patterns. We begin by examining arousal/activation and emotion processes in autism.
3.1. Arousal/activation and emotion processes There has been considerable discussion about the emotional life of individuals with autism; however, much of the literature in this area is descriptive in nature. A number of clinical studies have indicated that children and adults on the autism spectrum are at great risk for mood and anxiety disorders (Bradley, Summers, Wood, & Bryson, 2004; Ghaziuddin, Ghaziuddin, & Greden, 2002; Kim, Szatmari, Bryson, Streiner, & Wilson, 2000; Muris, Steerneman, Merckelbach, Holdrinet, & Meesters, 1998). For example, Muris et al. (1998) found in their study that 84% of individuals with a PDD met the full criteria for an anxiety disorder. Other research has pointed to the problems individuals with autism have in emotion expression, emotion recognition, and emotion interpretation (Hobson, 2005). Although there is evidence that older children and adults with autism may be at greater risk for certain types of emotional problems, little is known about early affective processes in young children with autism or how they influence development in other domains. In order to function effectively, a calm–alert state is necessary. Paris (2000) suggested that children with autism demonstrate levels of arousal that tend to the extremes, either lower than desirable or so high that decompensation results. Reviewing evidence from experimental studies
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on children with autism, Toichi and Kamio (2003) pointed out that there is support for both a hypoarousal and a hyperarousal hypothesis, either of which they speculate could result from an impairment in the reticular activating system. Hypoarousal is frequently connected with lethargy, indifference, and sleep, whereas hyperarousal is associated with intense, often uncomfortable feelings, avoidance, or immobility (Dunn, 1997). Related research examining temperament in children with autism has found that they show greater variability in affect regulation, less effective affect-regulation strategies, poorer inhibitory control, and difficulties in being soothed (Konstantareas & Stewart, 2006). They have also been reported to be less adaptable and require more intense stimulation from the environment in order to respond (Hepburn & Stone, 2006). Research by Shalom et al. (2006) suggests that children with autism are not impaired in their emotional response at a physiological level but rather in the manner in which they interpret, express, and react to the emotions they are experiencing at a physiological level. Problems in the arousal/activation and affect-regulation system have been theorized to have a major influence on both the early and the later development of the sensory, motor, cognitive, language, social, and selfregulatory systems. At a sensory level, children with autism who are experiencing a high state of arousal might be expected to show a pattern of hypersensitivity, particularly in environments that are changing, novel, and/or more intense. In contrast to more typically developing children, they would be expected to show slower habituation responses to sensory input. Conversely, problems of hyposensitivity and the absence of an orienting response toward stimulus inputs, such as pain, hot, and/or cold, could be explained by a state of low arousal (Whitman, 2004, pp. 61–63). Paris (2000) suggested that a state of hyperarousal could also explain many of the motor symptoms associated with autism, including muscular tension and problems related to the development of gross and fine motor skills, coordination, balance, and motor planning. Hyperarousal would also be expected to be associated with hyperactivity, behavioral disorganization, and avoidance. In contrast, low arousal would be compatible with a state of low muscle tone, lethargy, and inactivity. Cognitively, individuals with autism in a state of hyperarousal would likely be distractible and impulsive, as a result of problems in attentional focusing, attention-span, changing attentional focus, and information processing as well as in short-term and long-term memory (Dawson & Levy, 1989). As a consequence, learning would be slower and more complex cognitive and metacognitive processes, such as abstract thinking, problem solving, executive functioning, social comprehension, self-monitoring, and self-understanding, would show particularly adverse effects. Although the process would be somewhat different, low arousal would likely lead to a similar pattern of problems due to inattention rather than distractibility.
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Increasingly, arousal and cognition are viewed from a cognitive neuroscience perspective as intricately bound developmental processes (Bell & Wolfe, 2004). Gardner and Karmel (1983) suggested that during early infancy, maladaptive arousal patterns may alter central nervous system organization in permanent ways. In discussing research that showed highly aroused infants to prefer less complex and informative stimuli, they pointed out that, under conditions of prolonged stress, such preferences may be permanently established as functional and structural connections in the brain, thus having a detrimental effect on cognitive development. This preference for noncomplexity displayed by distressed infants bears close similarity to the attention fixations and stereotyped routines engaged in by children with autism who are under stress. In an intriguing proposal, Baron-Cohen, Ring et al. (2000) suggested that autism may be caused by a defect in the amygdala. The amygdala, which is interconnected with many regions of the brain, including the limbic system and the neocortex, receives many types of sensory input and plays a critical role in attentional behavior, threat detection, fear, and fight or flight responses. Baron-Cohen, Ring et al. (2000) presented evidence indicating that amygdala activity is abnormal in people with autism and may be related to their deficits in social intelligence. Moreover, a variety of studies, both human and animal, have suggested that a pathological amygdala contributes to abnormal fears and anxiety and may be related to social-cognitive deficits, including problems in facial identity and interpreting facial expressions (Amaral, Bauman, & Schumann, 2003; Schultz, 2005), as well as higher levels of repetitive/restricted behaviors (Dziobek, Fleck, Rogers, Wolf, & Convit, 2006). Schultz (2005) pointed out that early problems involving the amygdala have a cascading effect on the development of cortical areas that mediate social perception and the acquisition of social knowledge. Ledoux (1998) suggested that information about external stimuli reaches the amygdala by two pathways, directly from the sensory thalamus (the low road) and also from the sensory thalamus to the sensory cortex to the amygdala (the high road). What Ledoux’s characterization perhaps implies, but does not include, is a feedback loop back from amygdala to the sensory cortex (Ledoux, 1998). If the amygdala is defective in individuals with autism, as Brothers (1990) and Baron-Cohen, Ring et al. (2000) indicated, it is likely that all these pathways will not function normally. Teichner (2002) suggested that early stress and dysfunctions in the limbic system can lead to abnormalities in the left hemisphere, and reduced integration between right- and left-hemisphere processes and possibly a shift from left- to right-dominated states, resulting in problems in emotion perceptions. Although Teichner’s research focused on individuals with a history of abuse, it is plausible to assume that similar effects might be produced by other types of trauma, including the early social and physical
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stressors that lead children with autism, who are already biologically compromised, to display intense fear reactions, social avoidance, and social withdrawal. Because the limbic system is implicated in emotional functioning and influences the functions of the hypothalamus and the pituitary gland, a variety of research has examined hormones associated with these organs. Research with typically developing children has indicated that hypothalamic-pituitary-adrenal (HPA) reactivity to stress is adaptive in this population. For example, Blair, Granger, and Razza (2005) found a positive relation between HPA reactivity and measures of executive function and self-regulation. In a study by Curin, Terzic´, Petovic´, Zekan, Terzic´, and Sˆusˆnjara (2003), children with autism were found to have significantly lower serum concentrations of cortisol and higher concentrations of adrenocorticotropin hormone compared to control age- and sex-matched subjects, thus indicating a possible dysfunction in the HPA axis in individuals with autism, which might in turn lead to a disruption at a cortical level and cognitive problems. The relationship between arousal and emotion processes in individuals with autism and performance in perceptual and cognitive task situations is just beginning to be examined. For example, Schwartz et al. (2005) found that error rate on a speeded reaction task requiring subjects to make a discrimination was directly related to self-reported anxiety in highfunctioning individuals with autism. In an intriguing study by Toichi and Kamio (2003), autonomic responses to mental tasks requiring attention were examined in adolescents with autism and age- and ability-matched controls. Autonomic function was evaluated using an index of heart rate variability. Whereas the control group showed a significant decrease in parasympathetic function during mental tasks, the group with autism showed no significant change, suggesting perhaps that they were not orienting toward the task. In contrast, some individuals with autism appeared more emotionally aroused in a resting condition than in the mental task condition, possibly indicating that the lack of structure or the complexity and unpredictability of this condition was more stressful for them. Arousal/activation and emotion processes may also play a critical role in the development of the language/communication system in individuals with autism. Language development is likely influenced through the impact that hyperarousal and hypoarousal have on language acquisition and communication processes, such as those which are a part of the cognitive (e.g., attention and monitoring) and motor (speech) systems. Bloom (1993) linked affective expression with the development of language. She pointed out that emotional expression competes with language learning for an infant’s attention, and suggested that a neutral emotional state allows infants to use their limited cognitive resources for early language learning.
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Her research indicated that one-year-old infants who spent more time in neutral emotional states achieve language milestones, such as first words and multiword speech, earlier than infants who are more emotionally expressive (Bloom & Capatides, 1987). If infants with autism are experiencing more intense and unregulated emotions, this could explain at least in part their early delays in language development. Social development is also likely affected by states of hyperarousal and hypoarousal. Paris (2000) suggested that because the level of arousal of individuals with autism is less than optimal, their ability to learn and perform in social situations will be adversely affected. This impact on social learning and performance is likely mediated in part through the attentional problems that result from overarousal and/or underarousal, with inattention or selective attention leading to problems in encoding, processing, and recalling social information. Children who are extremely anxious are less likely to be aware of their social environment, less strategic in their social decisionmaking, and less able to carry through an orderly plan of social action. Results of a correlational study by Bellini (2004) indicated that adolescents diagnosed with autism, AS, and PDD-NOS were more likely to report higher levels of anxiety than would be expected in a general population; in turn higher anxiety was associated with lower social assertion. Further insight into how emotional arousal might affect social functioning is provided by research examining face processing in children with autism. A variety of studies indicate that individuals with autism demonstrate marked abnormalities, compared to non-autism spectrum disorder (non-ASD) controls, in the processing of faces, including reduced attention to faces, reduced attention to eyes, increased focus on mouths, poor memory for faces, and impaired recognition of familiar faces. More generally, they tend to use a feature-based rather than a configural approach to processing. In turn, this mode of facial processing has been purported to be associated with a variety of social and communication problems, including joint attention deficiencies, reduced social imitation, poor emotion recognition, and lower social-referencing (Sasson, 2006). The amygdala hypothesis of autism proposed by Baron-Cohen, Ring et al. (2000) suggests a relation between threat detection and social functioning as well as a possible reason why facial processing in individuals is impaired. Indirect support for this hypothesis is provided by recent research. In a study by Joseph, Ehrman, McNally, Keehn, and Tager-Flusberg (2005), two groups of children (with and without autism) viewed faces on a computer. Children were asked to look at the faces and remember them. Physiological reactivity to the faces was measured, using skin conductance as a measure of autonomic arousal. Children with autism performed as well as control participants when face recognition depended on differences in the mouth region, but not when face recognition depended on differences in
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the eye region. Children with autism exhibited increased arousal to faces with eyes fixed in a direct gaze (in contrast to eyes gaze-averted to one side); in turn, arousal was inversely related to their face-recognition accuracy. In contrast, there was no association between face-recognition performance and autonomic reactivity in the control group. Thus, it appeared that faces with eyes focused directly increased arousal in children with autism which in turn inhibited face recognition. Similarly, Kyllia¨inen and Hietanen (2006) found that physiological arousal responses to straight gaze responses were stronger than responses to averted gaze in children with autism. In a related study of individuals with autism, Dalton et al. (2005) found that variation in gaze fixation was strongly and positively associated with amygdala activation, again suggesting that gaze fixation is associated with heightened emotional arousal in autism. In summary, the majority of the research on affective processes in individuals on the autism spectrum has been directed to the study of emotional problems occurring in later childhood and adulthood. Considerably less is known about the affective states of young children with autism or how emotional reactivity and arousal affect functioning in other domains during this period. Research with younger age groups could prove to be extremely important because of the possibility that arousal processes may play a formative role in the psychological, behavioral, and neurological development of children with autism.
3.2. Sensory processing Although formal definitions of autism do not include sensory processing problems as a key defining characteristic of this disorder, the presence of sensory disturbances in children with autism has been widely acknowledged (Baranek, Parham, & Bodfish, 2005). Individuals with autism appear to experience the sensory world at the extremes, showing either hypersensitivity or hyposensitivity. Sensory problems have often been reported in terms of a specific modality; however, problems in one sensory modality may influence functioning in other sensory modalities, thus creating sensory integration problems (Anzalone & Williamson, 2000). Other sensory problems associated with autism include sensory distortions, sensory overload, and synesthesia, (Baranek et al., 2005; Harrison & Hare, 2004). Gillberg and Coleman (1992) suggested that abnormal sensory responses to stimuli may constitute the most characteristic symptom of autism not currently contained in the diagnostic criteria for this disorder. O’Neill and Jones (1997), reviewing evidence from clinical and empirical studies, indicated that unusual sensory responses are present in the majority of children with autism during early development and are linked to other aspects of autistic behavior. Existing research has also indicated that sensory symptoms are not unique features of autism but are also associated with other clinical
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diagnoses (Baranek et al., 2005; Ermer & Dunn, 1998; Rogers, Hepburn, & Wehner, 2003). Baranek et al. (2005) summarized evidence suggesting that unusual sensory features exist at a young age in children with autism, including during infancy, but often decrease over time. Given the fact that sensory symptoms appear to occur early, an argument can be made that sensory symptoms may play an important role in the early stages of development of autism. Support for this position is provided by Rogers et al. (2003) who found that sensory symptoms were significantly related to overall adaptive behavior. Little is known, however, about the etiology and development of sensory problems in children with autism or their possible relationships to the sequelae and symptoms associated with autism. Despite the fact that little research has investigated these questions, there has been considerable theoretical speculation about interprocess relationships. Ornitz (1983) suggested that the behavior of children with autism becomes disorganized because of their inability to modulate sensory input. Disorganization might occur for a variety of reasons, including an inability to focus on incoming stimuli, a failure to filter out irrelevant aspects of the stimuli, and/or a failure to process completely information contained in the stimuli. These problems may in turn produce disruptions at an emotional level that further inhibit effective sensory processing, and even perhaps elicit a fight or flight response, thus preventing coordinated and strategic action. Dunn (1997) pointed out that for some children hypersensitivity results in a high level of arousal and activity; for other children, however, hypersensitivity results in sensory overload and an ensuing behavioral lethargy and flatness of affect. The influence of sensory problems on the motor system may also be farreaching and profound. For example, Paris (2000) suggested that problems in processing tactile information can result in impairments in gross motor control (e.g., impaired balance reactions, postural insecurity, and motor clumsiness), hand control (e.g., impairments in grasp and manipulation skills), oral motor control (e.g., decreased isolated tongue movements and articulation problems), physical problems, such as shortening of the hand, as well as general disruptions in motor development (e.g., feeding, walking, and speech). Research by Gepner and Mestre (2002) indicated that children with autism are less reactive posturally to visually perceived environmental motion than typically developing children, and that hyporeactivity to such visual input is associated with motor impairments. This type of relation between the visual and motor sensory system may account for the delays some children with autism experience in achieving major motor milestones, as well as motor problems such as rigid gait and writing problems. Sensory problems also seem to influence cognitive, language, and social development. Cognitively, hypersensitive children often appear distractible or narrowly focused on one aspect of their environment. In contrast,
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hyposensitivity, which can be viewed as an attempt on the part of children to deal with the problem of overstimulation by shutting out a physical and social world that is too intense and chaotic, has been associated with low levels of attention to incoming stimuli. Huebner (2001) suggested that sensory problems adversely affect social and language development through their impact on arousal, motor, and cognitive learning processes. Available information indicates that the sensory problems of children with autism may be secondary to their problems in other areas, such as in the arousal/activation or self-regulatory systems, rather than due to basic defects in the sensory system. In particular, there is no compelling evidence that their sensory problems are related to problems in the peripheral sensory structures; however, there are reports in the literature of children with autism having different types of visual and hearing difficulties (Baranek et al., 2005; Carmody, Kaplan, & Gaydos, 2001; Klin, 1993; Rosenhall, Nordin, Sandstrom, Ahlsen, & Gilberg, 1999).
3.3. Motor characteristics Motor problems have been mentioned as one of the key characteristics of individuals with AS. For example, Gillberg (1989) found that 83% of the individuals with this disorder have relatively poor motor skills; in particular, he noted that they were generally clumsy and had an awkward way of walking that has been described as rapid and arrhythmic. Other motor problems that have been noted include: difficulties in throwing and catching a ball, problems with balance, and a lack of manual dexterity (e.g., difficulties in tying shoelaces, and handwriting) (Attwood, 1998). Whereas motor problems are viewed as an important feature of AS, children with autism have sometimes been portrayed as displaying normal motor development and even possessing special competencies in this domain. However, a variety of research challenges this perspective and suggests that children with autism may have at least as high of incidence of motor problems as children with AS ( Jansiewicz et al., 2006; Manjiviona & Prior, 1995; Rinehardt, Bradshaw, Brereton, & Tonge, 2001). In a review of research, Smith (2004) evaluated the claim that motor problems are characteristics of specific subgroups within the autism spectrum. Examining motor skills in individuals with high-functioning autism (HFA) and AS, she concluded that an AS–HFA distinction does not hold up in the motor domain. It is still possible that motor abilities may vary across other portions of the autism spectrum, for example, between individuals with HFA and lower functioning autism. Support for such a relationship is provided by Baranek et al. (2005) who summarized evidence suggesting that individuals who are more cognitively advantaged are more motorically competent than less cognitively advantaged individuals.
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Although motor problems frequently have been observed in populations with ASDs, they are certainly not unique to these disorders. Children with a variety of other developmental disorders, such as mental retardation and attention deficit disorder, also exhibit an array of motor symptoms. There is, however, increasing evidence that there may be specific motor difficulties distinctively associated with autism, including imitation deficits (Baranek et al., 2005; Williams, Whiten, & Singh, 2004). Imitation deficits and their relationship to other processes will be discussed at length in Section 3.5.3. From a developmental perspective, parents, clinicians, and researchers have noted that infants and toddlers, later diagnosed with autism, often display early problems in self-feeding, dressing, and general manual dexterity, as well as delays in meeting the major motor milestones (Teitelbaum, Teitelbaum, Nye, Fryman, & Mauer, 1998). Results of a study by Baranek (1999) are intriguing in that they suggest that motor as well as sensory problems are present in children with autism when they are 9–12 months old, and that these symptoms might be used, in conjunction with social deficiencies, to distinguish children with autism from typically developing children. Motor symptoms can be conceptualized as falling into two categories, voluntary and involuntary. Voluntary motor behaviors involve a cognitive component (praxis) that involves understanding/visualizing what needs to be done, planning to execute, and then actually executing an action. In contrast, involuntary motor behaviors are nonintentional, but nevertheless may serve an adaptive function. Although little is known about the developmental course of involuntary movement problems in children with ASD, there is evidence that they are negatively related to IQ and comorbid with mental retardation (Baranek et al., 2005). Reviewing research on voluntary movements, Baranek et al. (2005) suggested that children with autism have particular problems on nonrepetitive gross and fine motor tasks that involve complex and novel features. They indicated, however, little is known about the specific processes that influence these types of performance. It is not clear whether the early occurring motor problems that are associated with autism are a function of defects in the motor system, the arousal/activation system, the sensory system, or a combination of these and other defects. For example, it is possible that during infancy early stress and associated sensory problems lead to disorganized motor behavior. In turn, the motor problems may restrict the availability of motor coping resources available for dealing with stress, which then further exacerbates the infant’s emotional and sensory problems (Als, 1982). Although the relations among motor functioning and cognitive functioning, speech acquisition, socioemotional development as well as stereotyped behavior have been of interest to autism researchers, the importance of these relations is only beginning to be appreciated (Baranek et al., 2005).
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Motor development has been proposed as playing a critical early role in the development of the cognitive system (Piaget, 1970). From a sensory and cognitive perspective, a more motorically advanced child not only comes into contact with more of the environment but is also able to explore more fully and competently that environment through active manipulation. Children’s perception of the world changes dramatically as locomotion increases (Smith & Thelen, 1993). The motor system also likely plays a critical role in social development, through its influence on the acquisition of motorically based communication skills and social behaviors. Delays in the motor arena not only hamper social interaction but also mark children as different, sometimes stigmatizing them. Most of the aforementioned relationships between motor development and functioning in other domains have not yet been systematically examined in populations with autism. Some research has suggested that motor dysfunction in autism is related to motor-planning problems including dyspraxia (Rinehardt et al., 2001). Motor planning is a process which requires conscious attention and effort (Paris, 2000). Dyspraxia, a common problem in children with autism, refers to difficulties in formulating a goal, figuring out how to accomplish a goal, and executing an action, steps that obviously have a strong cognitive as well as a motor component. Children with dyspraxia find it difficult to learn new tasks (Huebner, 2001).
3.4. Cognitive characteristics The range of cognitive deficiencies that have been associated with autism is considerable. For example, theory and research have suggested that individuals with autism display deficits in attention, executive functioning, and theory of mind processes. In this section, these processes are discussed along with how they are related to each other and functioning in other domains. 3.4.1. Attention and information-processing difficulties It is quite common for persons with autism to have attention difficulties, with estimates of this type of problem being as high as 64% (Tsai, 1998). Deficiencies in attention have been linked to later language problems and language competence (Im-Bolter, Johnson, & Pascual-Leone, 2006), difficulties in understanding the state of mind of other people, thus in turn possibly explaining why individuals with autism have difficulties in social as well as educational situations (Phillips, Baron-Cohen, & Rutter, 1992; Uvland & Smith, 1996). Speculations regarding the precise nature of the attention problems of children with autism suggest a range of potential deficits, including an inability to orient to a stimulus, to sustain attention to a stimulus, and to shift attention from one stimulus to another. Research has suggested, however, that many of the aforementioned attention characteristics are
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not necessarily reflective of a basic underlying defect and that children with autism can and do attend appropriately in certain situations (Mesibov, Adams, & Klinger, 1997). Nevertheless, persons with ASDs often display stimulus overselectivity in which behavior/attention is controlled by a limited subset of stimuli within a complex stimulus array. This tendency toward overselectivity may inhibit learning in academic situations and result in inappropriate behavior in social situations. The challenge faced by researchers is to understand the circumstances that produce attentional problems and what underlying mechanisms may be responsible. One explanation is that their unique attentional style may evolve as a way of regulating unpleasant emotions and dealing with situations that are overdemanding (Reed & Gibson, 2005). From this perspective, attention characteristics, such as eye-gaze avoidance, a tendency to look at objects using peripheral perception, and ‘‘unwillingness’’ to share attention with other people, can be viewed as coping mechanisms. Another explanation for the attentional problems of individuals with autism is that they have difficulty perceptually integrating or deriving meaning from ‘‘complicated’’ stimulus patterns; instead they restrict their focus and attend to stimuli that are simpler in nature (Mesibov et al., 1997). Some researchers have also suggested that children with autism have a problem using cues to direct their actions, particularly if the cues contain complex social information that must be interpreted (Leekam & Moore, 2001). Frith and Happe´ (1994) hypothesized that persons with autism display an abnormality in information processing, more specifically a failure of holistic processing or what they referred to as ‘‘weak central coherence.’’ Individuals with weak central coherence tend to concentrate on one or a few aspects of a task or an environment, that is they process at a local level, rather than on the task/environment as a whole and fail to integrate the local details of the task into a global percept. Although research support for this theoretical position has been mixed ( Jordan, 1999), a variety of research has emphasized the difficulties that individuals with autism have in processing complex material and how these difficulties influence social performance. For example, Gross (2005) found a significant relation between global information processing and recognition of human emotions. Children with autism made fewer global responses and more errors in recognizing human emotions than children without autism. The results of this study are interesting, given a finding by Basso, Schefft, Ris, and Dember (1996), in which they found that positive mood was directly associated with global processing and inversely related to a local bias. It may be that the emotionally laden stimuli in the Gross study elicited a state of high arousal in the subjects with autism, leading them to process information at a local level (Gross, 2005). A study by Hill, Berthoz, and Frith (2004) suggests that individuals on the
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autism spectrum also have more difficulty processing their own emotions. Moreover, Burnette et al. (2005) found relations between weak central coherence and theory of mind measures. The attention and informationprocessing style of individuals with autism could also explain some of their executive functioning deficiencies. 3.4.2. Executive function deficiency A variety of research conducted on children with autism has suggested that they display an executive dysfunction (e.g., Hala, Rasmussen, & Henderson, 2005; Goldberg et al., 2005). Russell (1997) referred to executive functioning as ‘‘a set of mental processes necessary for the control of action’’ (p. 258). Executive functioning involves processes such as planning, searching, strategy selection, impulse control, and attention-shifting, as well as working memory and monitoring, all processes that facilitate flexibility of thought and action. These processes are more conscious in nature, guided by knowledge, goals, ideas, plans, and scripts ( Jordan, 1999). Research has suggested that children with autism have a variety of problems because of a deficit in their executive control system. For example, Jarrold (1997) indicated that children with autism have problems with pretend play because of an executive dysfunction. Relatedly, Turner (1997) hypothesized that they engage in repetitive behaviors in play situations because they are unable to generate alternative ways of acting. Landa and Goldberg (2005) also suggested that executive functioning influences social functioning and language development, including the formulation and implementation of plans in social situations, shifting social behavior in response to changing contextual demands, and holding social information in mind during dynamic social exchanges. Empirical support for these hypothesized relations is weak to nonexistent, although little research has been focused in this direction ( Joseph, McGrath, & Tager-Flusberg, 2005; Landa & Goldberg, 2005). Similarly, the relation between executive functioning and the least studied autistic characteristics, restricted and repetitive symptoms, has been underinvestigated. However, Lopez, Lincoln, Ozonoff, and Lai (2005) found that three executive processes—cognitive flexibility, working memory, and response inhibition—were significantly related to this symptom category. Ozonoff, South, and Provencal (2005) indicated that executive dysfunction may be secondary to and influenced by earlier emerging core symptoms, including lack of social awareness, imitation problems, and failure to use language to control thoughts and behavior. Russell (1997) speculated that the development of awareness in children with autism may be disrupted because of action-monitoring deficiencies, and that as a consequence they have problems such as developing a sense of agency or intentionality, obtaining knowledge regarding their own actions, imitating the actions of others, and regulating their actions through inner speech.
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3.4.3. Social cognition, theory of mind, and empathy The area of social cognition involves the study of how a person’s thought processes are related to their social context. Research in this area has focused on how persons come to understand both their own thought processes as well as the thought processes of other people. Some researchers have proposed that individuals with autism have a primary deficit in understanding the minds of other people (mind-blindness) and how mental states (e.g., beliefs and knowledge) influence behavior in social situations (Baron-Cohen, Tager-Flusberg, & Cohen, 2000). Baron-Cohen et al. (2005) hypothesized that mind-blindness and empathy are dynamically interrelated. Empathizing involves understanding the mental states of self and others and their relationships to behavior and emotions. Whereas individuals with autism often have difficulty expressing empathy, Baron-Cohen et al. (2005) suggested that they may have intact and even superior systematizing skills that allow them to understand, manipulate, and make predictions about the physical/nonsocial world. They also pointed out that a strong drive to systematize in individuals on the autism spectrum may be responsible for their repetitive, obsessional, and narrowly focused interests, as well as their special abilities, and in combination with their poor empathizing skills explain the mechanical ways they socially interact with others. Some researchers have suggested that children with autism do not understand others’ minds because they do not know that they themselves have a mind, or if they do possess this general knowledge, they do not understand or appreciate the contents of their own mind; that is, they have a metacognitive deficit. Other theories and research have indicated a relation between theory of mind deficiencies and weak central coherence (Burnette et al., 2005). Russell (1997) hypothesized that executive-processing dysfunctions lead to theory of mind problems, although empirical support for this relation is mixed (Landa & Goldberg, 2005; Russell, Saltmarsh, & Hill, 1999). Still other theories focus on social processes to explain theory of mind problems. Peterson (2005) suggested that children with autism may be deprived of critical social experiences (e.g., play and conversation with others) that provide a forum for learning about the mental states of other people.
3.5. Social interaction deficiencies From a diagnostic perspective, social deficits are considered a core characteristic of autism. Deficiencies in the social development of children with autism are not always easy to detect during infancy; however, they become increasingly apparent during the second year of life. Although children with autism often become attached to their parents, use gestures to make requests, and show turn-taking skills during play, they typically display
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limitations in these as well as other areas of social interaction, especially in situations requiring joint attention, social initiation, and dynamic social reciprocity. For example, children with autism manifest a variety of difficulties in social situations, such as using adults as a social reference to interpret ambiguous social contacts, following social protocols, engaging in social play with peers, and developing friendships. Wing and Gould (1979) suggested that the social interaction styles of individuals with ASDs can be grouped into three types: (1) aloof, (2) passive, and (3) active, but odd. Like individuals with autistic disorder, individuals with AS show impaired social behavior despite their more normal language and intellectual development (Gillberg & Gillberg, 1989). As indicated earlier, many theoretical perspectives have emphasized the major influence that the cognitive system and deficits in this system have on the social development of individuals with autism. A different perspective, referred to as enactive mind, shifts the focus from ‘‘disembodied cognition’’ to the interaction of the mind with the social environment and how experience changes the mind (Klin, Jones, Schultz, & Volkmar, 2005). Klin et al. (2005) pointed out that the affective and motivational predispositions that are brought by children with autism into social situations and that shape the social mind/brain are different from those of typically developing children. Similarly, Hobson (1993, 2005) has viewed the difficulties that children with autism display in peer and adult interactions—including those relating to social gesturing, sharing experiences, joint attention, affect coordination, emotion perception and expression, imitation, attachment behavior, and self-development—as evidence of their broader difficulty in intersubjective engagement. As a consequence of this intersubjective difficulty, children with autism are constrained in their ability to acquire knowledge about other people’s mental and emotional states, their own selves, language, and communication. 3.5.1. Play Research examining the social difficulties of children with autism has often used play as a forum. Play with others provides a social vehicle for exploration and learning and for the development of social, language/communicative, and cognitive skills. It is well established that children with autism are impaired in their play skills. Their play not only appears to be delayed but is also different in its level of complexity, frequency, social orientation, functionality, and symbolic nature (Rogers, Cook, & Meryl, 2005). For example, children with autism have been found to be less socially engaged than typically developing children, as well as children with other developmental delays, because they less frequently initiate or accept requests for play (Rogers et al., 2005; Sigman & Ruskin, 1999).
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Functional play skills, along with responsiveness to bids for attention and imitation of requesting behaviors, have been found to be early childhood predictors of gains in language skills in adolescents with autism (Sigman & McGovern, 2005). Conversely, it seems likely that a child’s language skills also affect their play skills. Lewis (2003), however, has suggested that although there is general support for a play–language correlation in typically developing children, the nature of this relation in children with autism is likely more complex, specifically because children with autism show play deficits when compared to children who have a similar language ability, but do not have autism. The results of a study by Blanc, Adrien, Roux, and Barthe´le´my (2005) pointed out that both level of play and communication skills in children with autism are associated with their ability to self-regulate. The findings of Blanc et al. (2005) are consistent with the suggestion of Russell (1997) that the language of children with autism does not regulate as effectively their social behavior as that of typically developing children. The social-cognitive perspective and research just described suggests that children with autism develop differently because of the predispositions they bring into social situations and that in turn their interactions in these social situations shape both their social-cognitive and language development. Two of these predispositions, joint attention and imitation, are briefly discussed here. 3.5.2. Joint attention Joint attention involves both responding to the bids for attention by others and soliciting the attention of others. Mundy and Burnette (2005) propose that these skills are impaired in infants with autism and inhibit proper attention deployment, social information processing, and social learning, thus isolating them from the typical pattern of social exchange, resulting not only in social impairment but also in neurobehavioral disorganization and neurodevelopmental pathology. Sigman and Ruskin (1999) found that children with autism have a deficit in joint attention compared to children with Down syndrome. Moreover, joint attention skills in this study predicted both concurrent language abilities and long-term gains in expressive language. Similarly, Bono, Daley, and Sigman (2004) found that better joint attention skills were associated with greater language development. Most interestingly, they also found that a relationship between amount of intervention and language development was conditional, depending upon the children’s ability to respond to the bids for joint attention from others as well as their initial language skills. Relatedly, Whalen, Schreibman, and Ingersoll (2006) found that teaching joint attention skills to children with autism was related to improvement in social initiations, positive affect, imitation, play, and spontaneous speech.
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3.5.3. Imitation Like joint attention, imitation appears to be a key process that shapes learning during infancy and early childhood, influencing early motor development, play, social interaction, communication skills, and knowledge acquisition as well as socioemotional understanding. The difficulties children as well as adults with autism have in imitating the actions of others is well documented. Furthermore, imitation defects seem to be universal in this population. Although individuals with autism appear to manifest a general imitative deficit, their ability to imitate simple actions on objects seems less impaired than their imitation of body movements, such as oral– facial movements. Relatedly, imitation of body movements having social significance and/or involving sequential action is more difficult for them (Rogers et al., 2005). Although imitation deficits are not unique to autism, given they also occur in individuals with a range of other developmental delays, this deficit seems to be greater in individuals with autism (Rogers, Bennetto, McEvoy, & Pennington, 1996). In a meta-analysis of action imitation research in individuals with ASD, Williams et al. (2004) concluded that children with ASD show a marked and highly significant delay in normal imitative development, but not an absolute deficit. Several different processes have been suggested to produce this imitation deficit, including representational and executive functioning deficits, motivational problems, sensory integration and motor problems, social interaction deficits, low verbal ability, dysphasic and action representation disorders, and deficits in self–other mapping (Rogers et al., 2005). At present, little is known about how imitation defects are related to delays in motor, social, cognitive, and language development or whether imitation in individuals with ASD is not only delayed but also develops in a deviant fashion. Intervention research has, however, established that imitative skills can be learned and generalized to novel environments. Moreover, an increase in reciprocal imitation skills in young children with autism has been associated with increases in social communicative behaviors, including language, pretend play, and joint attention (Ingersoll & Schreibman, 2006). In addition, imitation, along with joint attention and toy play, have been found to be early predictors of communication development in this age group (Toth, Munson, Meltzoff, & Dawson, 2006). From a biological perspective, considerable attention has been given to mirror neurons and the role they play in imitation. Mirror neurons have been thought to be involved in both the perception and the comprehension of motor actions. Because deficits in each of these processes occur in individuals with ASD, there has been speculation that the mirror neuron system is dysfunctional in this population. Past research has indicated that when typically developing humans, as well as monkeys, watch an action
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performed by another that is also in their own motor repertoire, mirror neurons fire in the prefrontal cortex. There is speculation that this pattern of firing of the mirror neurons means that they play a role in linking the visual representation of an observed action to the motor representation of that action, thus providing a foundation for the development of both lower- and higher-order processes, such as imitation, language, empathy, and theory of mind (Gallese & Goldman, 1998; Oberman et al., 2005; Rizzolatti & Arbib, 1998; Rizzolatti, Fogassi, & Gallese, 2002). Once another individual’s actions can be related to one’s own actions, then it is a short step to being able to understand and predict another’s actions. Although there is an emerging interest in the functioning of the mirror neuron system in individuals with ASD, research in this area is only beginning to be conducted. One major tool for evaluating the mirror neuron system involves monitoring mu-neuron suppression. Using this methodology, Oberman et al. (2005) investigated whether individuals with ASD showed a dysfunction in the mirror neuron system when compared with age- and gender-matched control subjects. Whereas control subjects manifested significant mu-neuron suppression both while moving their own hand and observing hand movements, the ASD group showed significant mu-neuron suppression only to self-performed movements. The authors suggested that their results support the hypothesis that highfunctioning individuals with ASD have a dysfunctional mirror system, specifically because they do not appear to recognize the similarity between actions performed by others and their own actions. The developmental implications of this finding for areas such as language have not yet been empirically explored.
3.6. Communication and language Communication and language deficiencies are also a core diagnostic characteristic of autism. As Tager-Flusberg, Paul, and Lord (2005) have pointed out, there is considerable variation in the timing and patterns of language acquisition in children with autism. Estimates suggest that around 50% of them do not acquire speech as a primary mode of communication (Prizant, 1996). Early speech characteristics include echolalia, pronoun reversal, and peculiar word use. Once children with autism acquire speech, they manifest a variety of problems relating to articulation, syntax, morphology, prosody, and pragmatics. As a consequence, they have difficulty engaging in dynamic discourse with others and comprehending the intricacies of social communications. They also frequently display peculiar paralinquistic features relating to vocal quality, intonation, and stress patterns (Paul & Sutherland, 2005). Many of the aforementioned characteristics are also displayed by children with AS (Attwood, 1998; Gillberg & Gillberg, 1989).
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The fact that children with autism have communication deficiencies is not surprising given their problems in preverbal communication (e.g., limited use of social gestures) and deficiencies in maintaining eye contact, social referencing, and imitation. Several core problems have been proposed as being responsible for the communicative deficits of children with autism including a failure to attend to speech, joint attention deficiencies, symbol use limitations, and emotion-regulation problems (Marans, Rubin, & Laurent, 2005; Paul & Sutherland, 2005; Tager-Flusberg et al., 2005; Wetherby & Prizant, 2005). From a cognitive perspective, Tager-Flusberg (1996) hypothesized that children with autism seldom use language to share or seek information from others because they fail to understand that other people’s viewpoints are not the same as theirs; that is, they do not have a theory of mind. In contrast, Russell (1997) suggests that children with autism have difficulty both retaining and utilizing information to guide their social behavior because of an inability to use inner speech, a process that has been conceptualized as having its roots in social interaction. Some theorists emphasize that inner speech or self-verbalization is part of a developmental process in which the interpersonal nature of thought is transferred into an intrapersonal process, that is internalized (Luria, 1961; Vygotsky, 1978). Because of the problems children with autism have in their interpersonal relationships, it seems likely that this internalization process will not proceed in a typical fashion and that the language and cognitive processes that assist them in self-regulating their behavior will not develop normally. A more recent theory of language acquisition, espoused by Bloom and Tinker (2001), views the child as an active agent in her/his language development. Although their theory of language acquisition was not developed to explain language development in children with delays, their theory implies that to understand the language acquisition process in children with autism, the unusual cognitive, emotional, and social characteristics of this population would all need to be considered. In contrast to this perspective, Prizant (1996) pointed out that there is increasing evidence that speech problems in individuals with autism may be caused by factors other than or in addition to their social-cognitive impairments. More specifically, he suggested that their general motor difficulties, including oral motor impairments and motor-planning problems, may be responsible for their speech and communication delays. Similarly, MurraySlutsky (2000) indicated that effective speech and communication require that a child registers sensory information, formulates an idea, plans and sequences thoughts, and then speaks. She pointed out that this is the same process that occurs in motor planning and executing total body activities and hypothesized that motor planning and language share overlapping neural structures.
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Research examining the connections between language and communication deficiencies and other autistic symptomatology has been quite limited. Hale and Tager-Flusberg (2005) investigated and found a relationship between discourse deficits, specifically utterances that do not relate to a prior speaker’s utterance, and a broader range of autistic symptoms as measured by the Autism Diagnostic Observation Schedule. Paul et al. (2005) examined and found a connection between prosodic performance and ratings of social and communicative competence in individuals with autism. Prosody refers to those aspects of speech that modulate the meaning of a speech signal such as intonation, rate, pitch, rhythm, and timing. In a study of young children with language impairments, these impairments were associated with theory of both mind and visual perspective taking problems (Farrant, Fletcher, & Maybery, 2006).
3.7. Repetitive, restricted, and stereotyped behavior: A self-regulatory perspective In addition to the social and communication/language deficiencies associated with autism, there is an intriguing third set of diagnostic characteristics, consisting of repetitive, restricted, and stereotyped interests, activities, and behaviors. Turner (1999) suggested that the broad range of behaviors in this symptom category can be subdivided into two subcategories: lowerlevel behaviors in which there is repetition of movement (e.g., stereotyped behavior and repetitive manipulation of object) and higher-level, more complex responses (e.g., object attachments, repetitive language, narrow interests, and insistence on maintaining sameness). Stereotyped and repetitive behaviors also occur in typically developing children as well as in other disorders such as mental retardation and obsessive compulsive disorder. Research in the area of autism has focused on whether there are certain classes of repetitive behavior that are unique to autism (Bodfish, Symons, Parker, & Lewis, 2000) as well as the relationship of repetitive behaviors to age and IQ. The answers to these questions are inconclusive and complex (Turner, 1999). It is clear, however, that individuals with autism display a relatively high frequency of repetitive and stereotyped behaviors. South, Ozonoff, and McMahon (2005) found that the incidence of four repetitive behavior categories (object use, motor movements, rigid routines, and circumscribed interests) was more pronounced in persons with ASD than in typically developing individuals. Individuals with autistic disorder also displayed a higher incidence of certain types of repetitive behaviors (object use and rigid routines) than those with AS. Relatedly, Bodfish, Symons, Parker, and Lewis (2000) found that subjects with autism and mental retardation had significantly higher severity ratings for compulsions, stereotypy, and self-injury than individuals with only mental retardation. Most importantly, repetitive behavior severity predicted severity of autism
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in this study. This latter finding raises interesting questions about the inhibitory role that repetitive behaviors play in the cognitive and social development of children with autism. There has also been considerable speculation about the origins of repetitive behavior that focus variously on operant learning, drive-reduction, sensory reinforcement, cognitive, and homeostatic explanations. In particular, there has been speculation about the role of arousal in repetitive and stereotyped behavior as well as other unusual responses in children with autism. 3.7.1. The role of arousal One thing that differentiates children with autism from typically developing children is their difficulty, when they become upset, in regaining a sense of calmness, alertness, and focused attention. When children with autism are put in novel and complex situations, they often appear confused, helpless, and distractible; act in an impulsive and seemingly mindless fashion; and perseverate using ineffective strategies (Adrien et al., 1995). Many of the unusual behaviors that children with autism display in new and challenging situations, such as stereotypy as well as hyperactivity, inattention, gaze aversion, restricted attentional focus, withdrawal, social aloofness, and physical escape, can be viewed as functional in the sense that they serve to reduce unpleasant states of high arousal (Dunn, 1997). A related explanation for such behaviors suggests that there is an optimal level of stimulation necessary for adaptive human functioning. In order to maintain homeostasis, individuals self-activate or seek stimulation when their level of arousal is low or conversely act to decrease stimulation when their overall level of arousal is high. From this perspective, behaviors such as stereotypy can be viewed as serving either a self-stimulatory function, directed at increasing stimulation, or a filtering mechanism, directed at reducing external stimulation. In explaining stereotyped behaviors, both the tension-reduction and homeostatic hypotheses suggest that although the external environment plays a role, the critical factor is not what is happening in the environment per se. Instead, it is what impact the environment has on the state of arousal/activation within the individual, with levels of arousal/ activation mediating the effects that the external environment has on behavior. 3.7.2. The role of self-regulation The aforementioned perspective suggests that the defect that produces stereotyped and repetitive behaviors in individuals with autism is a dysfunctional arousal/activation system. This hypothesis is generally consistent with the amygdala theory of autism discussed in an earlier section. In contrast, another hypothesis invokes a concept of an immature self-regulatory system to explain autistic behaviors, including stereotypy and repetitive behavior.
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Self-regulation is considered to be an essential skill that lays a foundation for a child’s development. Self-regulation develops during early infancy, progressing from primitive attentional and motor responses that regulate arousal and sensory input, and gradually evolving into more complex capacities that direct cognitive activity and social interaction (Whitman, 2004). Although children come equipped with a few innate responses for controlling arousal, the development of self-regulation occurs in conjunction with and is closely related to a child’s overall development. Structurally, self-regulation is commonly conceptualized as involving cognitive as well as language and motor components. More specifically, selfregulation involves skills such as attention deployment, inhibitory processes, problem-solving skills, and more generally, executive functioning skills. Regulatory skills improve dramatically as language becomes more advanced. Self-regulation allows an individual to direct and share attention, process and store information in memory, retrieve information, and use it to guide responding. Brain development, particularly in the frontal lobes, support the child’s cognitive growth of processes, such as attention, working memory, metacognition, and executive functioning (Bronson, 2000). Until recently, little research has been directed at studying the selfregulatory system of children with autism. Research by Gomez and Baird (2005) suggested that children with autism display difficulties in selfregulation during infancy; specifically, they were reported as having more self-regulatory problems at one year than children without disabilities, at a level that was consistent with a diagnosis of regulatory disorder. In a study of older children, at 8 and 10 years, Bieberich and Morgan (2004) found children with autism to have more self-regulation problems than children with Down syndrome. More specifically, children with autism showed greater deficits in measures of attention, flexibility, engagement, and goal directedness during play activity. Although the infant–caregiver relationship is critical for the development of self-regulation in children without disabilities, this process in children with autism appears to be heavily influenced by their pattern of motor, cognitive, social, and language deficiencies and prolonged periods of distress. For example, Russell (1997) suggests that children with autism have difficulty using language/inner speech to direct their actions. Individuals with autism have also been characterized as not understanding their own capabilities and how they can be utilized in action situations (Whitman, 1990). As a consequence, they often perseverate in using ineffective strategies, thus appearing inflexible. Moreover, they do not appear to selfmonitor or self-evaluate their actions; and even when they are successful, they do not seem to understand the reasons for their success or experience a sense of self-accomplishment (Millward, Powell, Messer, & Jordan, 2000). If autism is viewed as a self-regulatory disorder, children with autism can be paradoxically characterized as both undercontrolling and overcontrolling
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in their self-regulatory style when confronted with emotional and cognitive challenges. They are undercontrolled because they often do not develop more complex forms of self-regulation, such as executive control processes (e.g., planning and monitoring), or sometimes even simpler forms of selfregulation, such as soliciting social support. Children with autism share a number of other characteristics in common with undercontrolled children who are often described as impulsive and distractible, seek immediate gratification, and are easily influenced by shifting environmental contingencies (Kremen & Block, 1998). Conversely, they appear overcontrolled in that they use the primitive self-regulatory techniques they possess to restrict and compulsively order their environment. Children with autism share several other features in common with overcontrolled children. They are often described as obsessive, perseverative, uncomfortable with ambiguities, reactive to novel situations, temperamentally wary, difficult to soothe, and socially withdrawn (Kremen & Block, 1998; Rubin, Coplan, Fox, & Calkins, 1995).
4. Future Research Directions Both the theory described earlier (see Fig. 1.1) and the research summarized in previous sections suggest the need for a more multivariate perspective for understanding the development of autism. This perspective includes not only characteristics/processes directly associated with the diagnosis of autism (social, language/communication, stereotyped, repetitive, and restricted behaviors) but also other commonly occurring characteristics/ processes. Moreover, this perspective emphasizes the need to examine how the relations among these characteristics/processes change over time and combine to create a unique self-regulatory system. Past research examining the characteristics associated with autism has most often fallen into one of three categories: descriptive, comparative, and process-oriented. Descriptive research has focused on examining the frequency with which a specific characteristic or characteristics occur in populations with autism (Muris et al., 1998). Comparative research has examined the relative frequency of these characteristics in populations with autism and other populations without autism, for example, individuals with mental retardation, other developmental disabilities, and/or without any delays (Kim et al., 2000). Often the question posed in such research is whether characteristics associated with autism are unique to this disorder or different in their configuration from those that occur in other populations. A third category of research has examined the concurrent linkages between one or more processes/characteristics associated with autism. Frequently, this type of research has been directed at exploring intradomain questions. An example within the cognitive domain is whether weak central
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coherence is related to emotion recognition (Gross, 2005). Much less frequently, research has addressed interdomain questions such as how joint attention influences language processes (Sigman & Ruskin, 1999). Relatedly, other studies have examined how physical or social environmental factors affect these various developmental processes (e.g., Reed & Gibson, 2005). In contrast, research has seldom examined intraprocess and interprocess dynamics across time. As pointed out in previous sections, considerable speculation exists concerning about how autism unfolds, how specific processes change over time, and how functioning/symptomatology in one domain influences subsequent functioning in other domains. By studying these relationships across time, more precise information about the development of autism can be obtained. A variety of research questions, suggested both by the previous literature review and by the developmental theory presented in Fig. 1.1, can be addressed within this framework. We describe five categories of questions below that we believe are salient and feasible at this stage of the research endeavor. Developmental process trajectories: At a descriptive level, the developmental trajectories of different processes (arousal/emotion, sensory, motor, cognitive, language, and social interaction) can be examined. For example, within the sensory realm what is the trajectory of individuals who are hypersensitive early in life? Does this hypersensitivity reduce over time and if so how rapidly? How variable are these trajectories across individuals with autism? Within the motor realm, it appears that some individuals with autism show early motor delays and these delays continue over time whereas other individuals seem to function well motorically during early development but manifest increasing problems over time. Developmental process interrelationships: How do different domains of development interrelate? For example, how are individuals’ trajectories of hypersensitivity over time related to their trajectories of motor development or how are individuals’ motor development trajectories related to their language development trajectories? A related but more complex question can also be examined. What is the relative influence of different domains of development on a particular process? For example, what is the relative influence of the trajectories of arousal/emotion, sensory, motor, cognitive, language, and social processes over time on the development of and changes in stereotyped, repetitive, and restrictive behaviors? Critical periods of influence: Are there critical time periods in which a particular process or processes have greater influence on the development of autistic symptomatology? For example, it may be that early delays in motor development are associated with greater subsequent autistic
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symptomatology than later delays in motor development. Examining the antecedents relating to the emergence of symptoms associated with autism, as well as symptom severity, may provide critical insights into not only the early but also the later development of autism; for example, why some children with autism develop significant language delays while others do not or what the developmental consequences are for children with autism who have an early history of regression. In discussing the developmental model in Fig. 1.1, we suggested that the influences of three early emerging processes (emotional arousal, motor, and sensory) may diminish over time in their influence on cognitive, language, and social processes. In contrast, these latter processes may increase over time in their influence on the early emerging processes, as well as on each other, and more generally on the development of various autistic symptoms. For example, it might be hypothesized that early gross motor functioning will have greater influence, compared to later developing fine motor functioning, on cognitive language and social development; in contrast, development in these latter three areas will have greater influence on the development of fine motor skills than gross motor skills. Mediational and moderational relationships: Mediational as well as moderational questions can also be addressed within a longitudinal framework. For example, does cognitive and/or language/communication competency mediate a relationship between emotional reactivity and stereotypy or does language/communication and/or cognitive competency serve to moderate, as either a risk or a protective factor, a relation between motor development and stereotypy? Autism subtypes and their etiology: At a complex multivariate level, questions can be asked concerning whether there are different subtypes of autism. For example, it may be that some individuals fall into a cluster without sensory or motor symptoms, whereas other individuals are in a cluster with these symptoms. Is membership in these clusters stable over time? How is early group membership related to later autistic symptomatology and overall development? Finally, questions can be asked about whether there are uniform or different pathways involved in the development of different autism subtypes/clusters as well as about whether similar autism outcomes are sometimes produced through different pathways (See Fig. 1.1). Previous and current research in the area of autism has utilized crosssectional designs. However, in order to study the types of process connections just outlined in individuals with autism, longitudinal designs must be employed. Although studies using cross-sectional designs can be conducted more quickly, inferences about causality are quite limited. In contrast,
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longitudinal designs allow for the examination of a variety of relations: (1) intraindividual as well as interindividual patterns of changes, (2) the interrelation between the trajectories of different developmental processes, (3) the causes of different patterns of intraindividual change, (4) the direction and magnitude of causal connections between and among different process variables, (5) critical periods when specific processes exert their maximum influence, and (6) factors that may mediate or moderate relationships between processes. To examine patterns of change and relations between processes across time, appropriate statistical techniques must be used. Fortunately, a variety of techniques are available to autism researchers using longitudinal designs, including latent growth curve, autoregressive, and dynamical systems approaches. A major advantage of these approaches is that they utilize advanced techniques for handling missing data (Carothers, Farris, & Maxwell, 2007; McCartney, Burchinal, & Bub, 2006). It should be noted that when employed, multivariate longitudinal designs place considerable demands on researchers because they are measurement intensive and require larger sample sizes. In order to obtain an adequate number of subjects, large autism research registries have to be established and/or active collaboration among researchers in different geographic areas is required. Moreover, a variety of measurement challenges confront investigators evaluating psychological and behavioral processes (e.g., cognitive, motor, and language) that undergo rapid change over time. Another challenge confronting researchers who use longitudinal as well as cross-sectional designs is to obtain more complete developmental information on the subjects (e.g., medical history, major environmental stressors, and parenting history) so as to allow them to make more precise statements about the generalizability of their findings. Although longitudinal research is more demanding, it seems likely that the insights it will provide into the development of autism will more than justify the difficulties that must be confronted.
5. Final Thoughts Because the developmental theory described previously does not explicitly include a social environmental construct (see Fig. 1.1), a few words regarding its role are in order. Historically, it was proposed that autism is caused by poor parenting. Kanner (1943) described the parents of children with autism as often appearing cold and aloof, more preoccupied with their occupational and personal pursuits than their children. Currently, there is no empirical evidence to suggest that parents are responsible for their children’s autism, and considerable evidence to the contrary; rather
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research strongly indicates that autism is a genetically based disorder. Nevertheless, there is growing evidence that environment may play a critical role in how this disorder emerges. This interplay between genes and environments and their influence on brain and behavior has long fascinated researchers. As Moffitt, Caspi, and Rutter (2006) pointed out, psychologists have come to appreciate the multiplicity of ways genetic and environmental risk factors interact. For example, early experience can alter gene expression, which in turn influences behavior development. Alternatively, a person’s genotype can make a person vulnerable to insults from certain types of environments. Relatedly, genetically determined characteristics can limit the ways a person responds to an environment. Although it is clear on the one hand that genes can ultimately influence an organism’s adaptation to the environment, it is also clear that biological development is influenced by an individual’s behavior and adaptation to the environment. At present behavioral researchers are only beginning to understand the multiplicity of ways that environments can place individuals who are already at risk for genetic reasons, like children with autism, at further increased risk for developmental delays or conversely, how such environments can protect and facilitate development in such at-risk populations. The results of various investigations have emphasized the dramatic inhibitory effects that environmental restriction/deprivation can have on early brain and behavior development and conversely how environmental enrichment can greatly facilitate such development. For example, Lewis (2004) summarized research that points out how environmental complexity prevents the development of stereotyped behavior as well as alters neuronal metabolic activity. Moreover, Dong and Greenough (2004) described the impact that environmental factors can have on brain plasticity, at both the neuronal and the nonneuronal level, along with an emerging body of research suggesting how the structural and functional plasticity of neurons in developmental disorders, including autism, may be impacted by environmental and experiential factors. Although considerable research is needed to clarify the types of environmental factors that enhance or inhibit plasticity at the neurological level in individuals with autism and how these neurological changes mediate change at the behavioral level, existing research has suggested a range of prenatal and postnatal environmental factors that may be related to autism and autistic characteristics. For example, greater prenatal stress during the 21- to 32-week gestation period has been reported by mothers of children with autism in comparison to mothers of children with Down syndrome and mothers of children without a neurodevelopmental diagnosis (Beversdorf et al., 2005). In another study pointing to the importance of prenatal factors, twin status was associated with subthreshold autistic symptomatology in males. Other research has suggested the influence of social
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environmental factors on the development of theory of mind (Hughes et al., 2005) and the ability to discriminate facial expressions of emotion (Parker, Nelson, & The Bucharest Early Intervention Project Core Group, 2005). In addition to investigating the influence of these types of environmental factors, attention also needs to be given to evaluating the impact of the environments that children with autism create for themselves as well as how changing these environments through early interventions influences development. The environments that children with autism create in their homes through their restrictive behaviors are typically quite different from those put in place by parents with professional assistance. Because children lack social skills, they are often deprived of critical social experiences that provide a forum for learning adaptive behavior (Peterson, 2005). Even though autism has genetic origins, perhaps with some early bioenvironmental triggers, it is not unreasonable to assume that parents of children with autism, like parents of all children, exert considerable influence on the general development of their children. As autism emerges, parents are confronted with children whose characteristics are peculiar and perplexing. At least initially, they have little insight into why their children act as they do and what they as parents should do to help their children. For example, they may be bewildered by their children who are hypersensitive, motorically challenged, fearful, socially avoidant, linguistically and cognitively delayed, and prone to engage in unusual stereotyped and ritualistic behaviors. Moreover, because the social signaling system of children with autism is compromised, parents have difficulty responding to the needs of their children. The children are not able to elicit the instrumental and emotional supports from their parents (and teachers) that they need to develop normally. Parents experience increasing stress, and not infrequently a sense of helplessness, as their children manifest increasing delays and selfregulation problems. Although any parent would find the symptoms of autism challenging, the parents of children with autism may possibly find their behaviors more challenging because they share for genetic/familial reasons certain characteristics in common. Nevertheless, evidence is accumulating which indicates that this parental and child trajectory can be at least partially ameliorated through intervention programs. Although more and better research needs to be conducted, both anecdotal report and research have suggested that intervention programs can have positive, and sometimes dramatic, effects on children with autism, particularly if they are intensive, begun early, and are multidimensional in nature (Whitman, 2004). The theory, presented in Fig. 1.1, not only describes the processes that appear to be involved in the development of autism but also provides a general blueprint for designing multidimensional interventions to alter the trajectory of this disorder.
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ACKNOWLEDGMENTS This study of this chapter was supported in part by grants from NICHD (HD-007184 and HD-26456).
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C H A P T E R
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Social Cognition in Children with Down Syndrome Katie R. Cebula and Jennifer G. Wishart Contents 1. Introduction 1.1. The focus of this chapter 1.2. Social Cognition: What is it and why is it important? 2. Early Indicators of Emerging Sociocognitive Understanding 2.1. Attending to people, objects, and the wider environment 2.2. Nonverbal gestures 2.3. Imitation 2.4. Expressing emotion 2.5. Possible links between early sociocognitive behavior and caregiver styles of interaction 3. Later Developments in Social Cognition: Understanding and Relating to Others 3.1. Emotional understanding 3.2. Theory of mind 3.3. Empathy and prosocial behavior 4. Linking Sociocognitive and Cognitive Development: Learning from and with Others 4.1. Learning with others 4.2. Learning from others 5. Conclusions Acknowledgments References
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Abstract Children with Down syndrome face considerable intellectual challenges. Despite the widespread belief that their social understanding is relatively ‘‘spared,’’ many also experience significant difficulties at an interpersonal level. This chapter assesses the literature on sociocognitive development in Down syndrome and Moray House School of Education, University of Edinburgh, Holyrood Road, Edinburgh, EH8 8AQ, Scotland, UK International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35002-7
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the evidence for strengths or weaknesses in understanding the social behaviors, emotions, and intentions of others. It highlights the predominant focus to date on infants and preschool children and the consequent need for more research at older ages, ideally through larger-scale, cross-syndromic, and longitudinal studies. It also underlines the need to tie knowledge of developmental trajectories not only to the underlying neurobiology of Down syndrome but also to aspects of the children’s social environment. Investigating how interpersonal understanding is used in learning contexts and translating this knowledge into more focused support programs should also be a priority.
1. Introduction Social cognition, broadly defined as the ability to process and respond appropriately to the behavior, emotions, and intentions of others, is widely recognized as a major driver of development in children without intellectual disabilities (see e.g., Bukowski, Newcomb, & Hartup, 1996; Carpendale & Lewis, 2006; Flavell, Miller, & Miller, 2002). This is no less true for children with intellectual disabilities. To date, however, with the notable exception of research into autism, investigation of social understanding in children with intellectual disabilities has tended to focus either on the nature of early parent–child interactions or on the acquisition of specific socioadaptive skills at later ages. The latter are routinely assessed in research studies and in professional practice but the core sociocognitive processes underlying them are seldom directly investigated, nor are these processes linked within investigations either to difficulties in more general aspects of psychological functioning (e.g., memory, attention, and information-processing ability) or to any more fundamental communication difficulties. This chapter focuses on the development and use of social cognition in children with Down syndrome. This genetic syndrome remains the single largest cause of significant intellectual disability in childhood and the most common birth disorder. IQ levels range from profound to mild, and yet, despite more than a century of research, there is still a surprising lack of detailed understanding of how social understanding develops within this wide IQ range. Although children with Down syndrome frequently serve as controls in studies of typical development or of other intellectual disabilities, relatively few developmental psychologists study Down syndrome in its own right beyond infancy and the early years; studies which specifically address sociocognitive understanding are particularly rare at later ages. This may well reflect the difficulties of carrying out empirical research in school settings as opposed to university-based child development centers. It may also, however, reflect a common assumption in mainstream psychology that (a) most of what there is to be known about Down syndrome is already
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known, (b) little can be done to alleviate its adverse developmental effects, and (c) it affects all cognitive domains equally and is therefore less informative than other syndromes in constructing theories of typical and atypical development. As we hope to demonstrate in this chapter, none of these assumptions is necessarily sound. Despite the fact that most theories of child development consider social understanding to be central to intellectual development, work on social cognition in children with Down syndrome has received even less attention than have other areas of their functioning. This may be because social understanding is often thought to be relatively ‘‘protected’’ in Down syndrome in comparison to other syndromes. The benign stereotype––of children who never seem to learn much but are nevertheless happy, affectionate, and sociable (Down, 1866; Hines & Bennett, 1996)––is deeply entrenched in the minds of the general public and indeed some of the many professionals who work with this group of children (Gilmore, Campbell, & Cuskelly, 2003; Rogers, 1987; Wishart & Johnston, 1990; Wishart & Manning, 1996). Given that socially based learning is believed to drive development, however, it is difficult to reconcile this apparently outgoing personality and predisposition to engage with others with the decline in developmental rate which seems to characterize developmental progress in children with Down syndrome (Carr, 1995; Dunst, 1990; Hodapp, Evans, & Gray, 1999; Hodapp & Zigler, 1990; Sigman & Ruskin, 1999; Wishart & Duffy, 1990). This raises concerns that social cognition may not be playing the same supporting role in the children’s overall development as it does for their typically developing peers. This concern is addressed in greater detail at various points below. There is also now growing evidence to suggest that children with Down syndrome may show specific patterns of similarities and differences in sociocognitive functioning both in comparison to their typically developing peers and to children with intellectual disabilities of similar severity but differing etiology. A review of findings in this field may therefore help to indicate those areas of social cognition that might benefit from an intervention focus as well as those, which as relative strengths, could be used to support tailor-made intervention programs for this particular group of children.
1.1. The focus of this chapter To allow some evaluation of what is known about social cognition in children with Down syndrome, we have attempted to both review and integrate relevant findings from the European, US, and wider literature. Our aims were threefold:
to explain whether the development of sociocognitive understanding in Down syndrome differs from that seen in typical development and in other developmental disabilities
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to examine how sociocognitive skills are put to use in learning contexts by children with Down syndrome to outline some of the methodological concerns for research in this field. The focus will be on some of the key components of social cognition and on how these might influence broader cognitive outcomes. As an organizing structure, we have reviewed the literature under three main headings: early indicators of emerging sociocognitive understanding, later developments in social cognition (understanding and relating to others), and linking sociocognitive and cognitive development (learning from and with others). Inevitably the review has had to be somewhat selective in its coverage. In general we have concentrated on areas in which we have ourselves carried out some work, attempting to link our own findings either to work by others on similar or clearly related aspects of sociocognitive understanding, or to research which seems to us to have potential relevance to social cognition and its development. Social interactions are by definition bidirectional processes and this chapter will therefore also include consideration of the role of others in the sociocognitive development of children with Down syndrome. ‘‘Others’’ obviously includes parents, siblings, and peers but also covers the wider social and educational community in which the children grow up. It is worth bearing in mind that Down syndrome has the rather dubious advantage of being very easily identifiable. This is not an unimportant consideration, as the preconceptions of high sociability but low cognitive ability referred to earlier clearly have the potential to influence the nature and content of interpersonal interactions at many levels, both positively and negatively. This issue is touched on later in this chapter, although few studies have directly addressed these areas of concern as yet. In this chapter we do not attempt to cover two related, but distinct, aspects of interpersonal functioning: the development of specific socioadaptive skills and the development of language skills. Social cognition as it is reflected in socioadaptive skills is not directly addressed here as this ground is admirably covered elsewhere in this volume, from a different but complementary developmental perspective (see this volume, Iarocci, Yager, Rombough, & McLaughlin, 2008). Clearly some level of sociocognitive understanding is a prerequisite for the emergence of even the most basic of socioadaptive skills but the emphasis here is rather on the underlying ability to respond to and process the kinds of information generally agreed to be fundamental to interacting successfully with others and to understanding the social world––that is, on processes rather than on specific outcomes. Likewise, although language and communication are recognized as central to the development of interpersonal understanding, especially at higher levels (see e.g., Homer & Tamis-Lemonda, 2005), this area of
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development, although treated briefly, is not reviewed in any great depth here. Again, a number of excellent and comprehensive reviews are already available (see e.g., Chapman, 2003; Miller, 1999; Roberts, Price, & Malkin, 2007). From these, it is evident that language is usually significantly more impaired in children with Down syndrome than would be expected on the basis of overall levels of cognitive functioning, with recent work in fact suggesting that the kinds of language difficulties experienced bear close similarities to those seen in children with specific language impairment (Laws & Bishop, 2003). Expressive language is especially slow to develop in children with Down syndrome (Klein & Mervis, 1999; Miller, 1987) and while vocabulary size continues to grow with increasing age, few children develop grammatical skills much beyond the level of the typically developing 3 year old (Fowler, 1990). This must place significant obstacles in the way of communication with others, as well as posing particular difficulties in contexts where the accurate exchange of information is central to the interaction (see e.g., Abbeduto et al., 2006). Articulation is an additional major problem for many children with Down syndrome, and deciphering their speech can often be very difficult, even for close family members (Kumin, 1994, 2006). Again, this has the potential to impede the process of learning about the social world from other children and adults, as will be evident from some of the findings reviewed here. As we shall also see later in this chapter, ensuring that the children make effective use of whatever levels of language skills they do acquire may require much more direct, adult-led intervention in educational contexts. Parental reports and clinical impressions suggest that as the children grow older, some choose to speak increasingly infrequently in social or learning contexts, with spontaneous speech restricted to when they are with family or friends (see e.g., Dykens, Shah, Beck, & King, 2002). This is an understandable response to the everyday difficulties they must experience in making themselves understood but given the fundamental role of language in social cognition, and in learning more broadly, it may well have unfortunate—and unnecessary—developmental consequences.
1.2. Social Cognition: What is it and why is it important? Within this chapter, a rather basic but pragmatic definition of social cognition is used, albeit one which recognizes the wide-ranging hierarchy of skills involved in sociocognitive development. These range from the core behaviors usually seen in the very early stages of development (such as joint attention, imitation, and social referencing) to the skills required to respond appropriately in contexts where sociocognitive and meta-cognitive demands are much higher (such as in theory of mind tasks or joint problemsolving contexts). Social cognition is therefore regarded as encompassing
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all of those skills that are required to allow a child to understand the behavior, the emotions, and the intentions of other children and adults: in sum, the ability to make sense of other people (Kunda, 1999). It is widely viewed as the bedrock of development, with implications for learning, for making friendships, and ultimately for socioemotional well-being and quality of life. As will be seen, there is surprisingly little information beyond the early years on the development of core sociocognitive skills in children with Down syndrome. Much of the classic work on social understanding in Down syndrome was carried out predominantly with infants and toddlers in the 1970s and 1980s, a period which saw an unprecedented growth in developmental psychology and in studies of both typically and atypically developing children. Ingenious paradigms for investigating early psychological functioning emerged and the availability of video recording revolutionalized the detail in which child behaviors could be analyzed. Many of these studies are still considered to be benchmark ones (for overview, see Cicchetti & Beeghly, 1990a), and findings from the most important of these are reviewed below. Research on social cognition in Down syndrome has been somewhat moribund in the intervening 15 years, although there has been an encouraging resurgence in more recent years. To some extent, this may stem from the Human Genome Project leading to a renewed interest in investigating neuropsychological profiles of strengths and weaknesses in specific genetic syndromes such as Down syndrome (for overview, see Chapman & Hesketh, 2000; Chertkoff Walz & Benson, 2002; Fidler, 2005; Nadel, 2003; Roizen & Patterson, 2003). Research carried out within this behavioral phenotype framework typically focuses on contrasting etiological subgroups of children with intellectual disabilities in order to gain a better understanding of any differences or similarities in underlying developmental processes which might help to explain differential developmental outcomes, both at the individual and group levels. There is as yet little genetic research focusing directly on children with Down syndrome, but there is a growing body of psychological research directed at exploring whether there are changes in ability profiles and developmental trajectories over time; identifying more effective and developmentally sensitive intervention methods is a major objective of this kind of research (see e.g., Burack, Evans, Klaiman, & Iarocci, 2001; Cicchetti & Beeghly, 1990a; Dykens & Hodapp, 2001; Fidler, 2005, 2006; Fidler, Philofsky, & Hepburn, 2007; Freeman & Hodapp, 2000; Hodapp, DesJardin, & Ricci, 2003; Karmiloff-Smith, 1997, 2007; Paterson, Brown, Gsoedl, Johnson, & Karmiloff-Smith, 1999; Wishart, 1996). The recent resurgence of interest in Down syndrome is a welcome development, although empirical investigations of social cognition are still relatively rare, especially in children beyond preschool age. This comparative
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lack of attention to development at older age levels is unfortunate. Interpersonal interactions underpin intellectual growth but they can also play a major role in determining quality of life. There is evidence that although the friendships enjoyed in preschool years by children with Down syndrome are not very different in nature and stability from those formed by typically developing toddlers (Freeman & Kasari, 2002), these tend to reduce in number as the children grow older and are not always reciprocated. Social activities also tend to become more restricted in range as age increases and ability levels and interests diverge from those of nonintellectually disabled peers. As a result, the personal life of many teenagers with Down syndrome revolves primarily around family members and organized community activities rather than school friends (Cuckle & Wilson, 2002; Sloper, Turner, Knussen, & Cunningham, 1990). Behavior seems to become less engaged and less socially motivated with age, with social isolation not uncommon in later years (Buckley, Bird, Sacks, & Archer, 2002; Carr, 1995; Dykens et al., 2002; Fidler, Barrett, & Most, 2005; Freeman & Kasari, 2002; Guralnick, 1995; Sloper et al. 1990). This in turn places significant restrictions on the many opportunities which interacting with others provides for informal learning. More importantly though, unsatisfactory or restricted peer interactions may impact negatively on later mental health (Collacott, Cooper, Branford, & McGrother, 1998), a topic which has received relatively little attention in Down syndrome research to date.
2. Early Indicators of Emerging Sociocognitive Understanding In this section, we briefly overview key findings relating to early components in the development of social understanding in children with Down syndrome. The aim here is not to provide an exhaustive review of the social skills themselves, as much of this has already been well covered elsewhere (see e.g., Cicchetti & Beeghly, 1990a). The purpose is rather to highlight that while there are many similarities to typical development in the sequence in which these early abilities unfold in Down syndrome, they generally take longer to develop, often show subtle qualitative differences, and may be used to different effect, potentially impacting on the later development of more complex sociocognitive skills. These developmental and functional differences at early stages, even though subtle, may also change the learning environment of children with Down syndrome by influencing how adults interact with them, with this in turn possibly having implications for subsequent developmental progress.
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2.1. Attending to people, objects, and the wider environment It is now widely accepted that human infants come into the world predisposed to interact with others in their environments and apparently ‘‘prewired’’ to initiate and respond to social interactions (Stern, 1998; Trevarthen, 1977, 1979). Although the first dyadic interactions between infant and adult may be relatively basic, they are nonetheless elegant in their simplicity, with both partners often showing a highly tuned receptiveness to even very subtle social and communicative signals and a remarkable synchronicity. Even in these first stages, adult–infant interactions are two-way processes, with each partner influencing the response of the other. These early nonverbal, but conversation-like, interactions set the stage for the development of more complex interactions, ones in which infants can follow, share, and even direct the caregiver’s attention to objects of interest in the immediate environment. In typically developing children important skills such as joint attention, pointing and requesting behaviors, and imitation all develop within the first year of life. Although there is disagreement over the extent to which these abilities truly represent an early understanding of others as intentional agents, it does seem clear that these interactive contexts serve as the foundation for acquiring higher level sociocognitive skills, such as emotion recognition, theory of mind, and empathy (Carpendale & Lewis, 2006; Flavell, 1999; Tomasello, 1995). A fundamental component of early communicative exchanges between infant and caregiver is mutual gaze. The ability to look at the caregiver’s face and to make eye contact is initially slow to emerge in infants with Down syndrome, but is then maintained at a high level in the middle of the first year, a time at which it normally begins to decline in typical development, as the infant begins to pay more attention to the wider social and physical world (Berger & Cunningham, 1981; Carvajal & Iglesias, 2000). The reasons for longer looking time in children with Down syndrome are not clear, but may relate to hypotonia or a need for more looking time in order to obtain the same amount of information as typically developing children (MacTurk, Vietze, McCarthy, McQuison, & Yarrow, 1985; Sigman, 1999). Despite this longer looking time, these looks may be difficult to interpret. Walden, Blackford, and Carpenter (1997), for example, reported that, when length of look was balanced across child groups, unfamiliar adults were less accurate and less confident in their ability to distinguish the socially directed looking behaviors of young children with Down syndrome than those of children with nonspecific intellectual disability or typically developing children. Although such difficulties may be less likely to exist to the same degree in caregivers more familiar with the child, Walden et al. suggest that this poor ‘‘readability’’ could influence the range or number of learning opportunities offered by adults within social interactions. It has similarly
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been suggested that the focal nature of looks made by children with Down syndrome may also differ. Berger (1980, 1990), for example, reported that infants with Down syndrome tend to fixate on the caregiver’s eyes rather than exploring other facial features, something that may have implications for later aspects of sociocognitive development, such as emotion recognition. This heightened attention to people, also seen in toddlers with Down syndrome (Kasari, Mundy, Yirmiya, & Sigman, 1990), might be taken as indicative of enhanced levels of sociability, as opposed to a more generalized enhanced attentional style. This is also suggested by findings from Ruskin, Kasari, Mundy, and Sigman (1994) who investigated the distribution of attention by infants and toddlers with Down syndrome in contexts where the primary focus was either on a toy or on a singing experimenter. Although they found that the children attended to toys just as frequently as their mental age-matched typically developing peers in the toy play situation, in the social context they looked more frequently at the experimenter, made fewer off-task glances, and generally participated more than the control children. The reasons for this differential interest in people as opposed to objects are not clear. It could represent greater sociability, but it is also possible that––in situations where there is a choice between people and objects––it could reflect a tendency to engage preferentially in tasks that are cognitively less challenging. It is important to note that in some comparisons with typically developing children, the reverse pattern––less frequent social behavior and more frequent looks to focal toys––has also been reported (MacTurk et al., 1985). It is therefore likely that although children with Down syndrome may generally be more interested in interacting with people, the cognitive and social demands of the environment also play a role in determining the regulation of their attention (Sigman, 1999). MacTurk et al. also showed that while social behavior was often followed by task persistence in the typically developing controls, this functional link was not present in children with Down syndrome. Longer looking time toward people does, to some extent, seem to come at the expense of developing the skills of dividing and switching attention between people, objects, and the environment. Children with Down syndrome not only show reduced ability to monitor and gain information from the surrounding environment during an ongoing task (Gunn, Berry, & Andrews, 1982; Kasari et al., 1990; Krakow & Kopp, 1983) but may also show some difficulties in joint attention skills. Joint attention, the coordination of attention between people and objects, is a key route to sharing interests with others, communicating intentions and desires, and learning about the environment. It also plays a crucial role in language acquisition, which in turn plays a major role in the development of higher level sociocognitive skills (Carpendale & Lewis, 2006). Although during infancy there
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is growth in the ability to coordinate attention between people and objects, this progress is slower than that seen in typical development, with fewer instances of joint attention occurring; the children instead tend to spend more time as passive participants, sharing attention to objects with adults, rather than actively coordinating attention (Legerstee & Weintraub, 1997). However, Kasari, Freeman, Mundy, and Sigman (1995) found no difference in the frequency of coordinated joint attention among 13- to 42-month-old children with Down syndrome when looking patterns were compared to those of typically developing children of similar developmental levels. They cautioned, however, that difficulties in shifting attention between people and objects are possibly accentuated in contexts with a higher cognitive load. This interpretation is compatible with Hobson, Moore, Oates, and Goodwin’s suggestion (2008) that, although infants with Down syndrome may have the potential to engage in triadic behaviors such as joint attention, they may have a lesser tendency to use such behaviors under certain circumstances.
2.2. Nonverbal gestures Nonverbal gestures such as pointing and instrumental requesting give the developing child further social opportunities for learning about people and objects in the surrounding environment and for acquiring language. One of the first studies to investigate this area of development in children with Down syndrome was conducted by Smith and von Tetzchner (1986). They adopted a longitudinal design to study the relations among early communicative, sensorimotor, and language skills, using a wide range of standardized and observational measures to assess progress in these three domains. Thirteen children with Down syndrome were recruited at birth and tested at yearly intervals between 1 and 3 years of age, with typically developing children serving as chronological or mental age matches at different time points in the study. At age two, the young children with Down syndrome were significantly poorer than their typically developing mental age matches in terms of frequency of production of declarative behaviors (pointing) but not imperative behaviors (instrumental requesting). Statistical comparisons were rather weakly based, however, and the range of scores for both kinds of behaviors was very similar in the two child groups. At this stage, declarative skills proved to be associated with concurrent language skills in only the Down syndrome group but both declarative and imperative skills proved predictive of language development at 3 years of age, with earlier declarative skills linked to comprehension ability and earlier imperative skills linked to expression ability at this later age. This association was not found in the typically developing
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controls and remained even when the children’s developmental quotients were partialled out in analyses. Franco and Wishart (1995), in a study of toddlers with Down syndrome aged 21–47 months, found that the patterns of gestures used during communication with mothers and age-mates were very similar to those of typically developing infants of younger ages but equivalent linguistic status. There was, for example, a predominance of pointing gestures to interesting but out-of-reach objects (referential condition) and of reaching requesting gestures to toys within the partner’s reach (instrumental condition), with these combined appropriately with looks toward the mother or an age-mate. These findings suggest that children with Down syndrome clearly do relate to their social world, and in their visual checking and multichecking patterns show a sophisticated understanding of the need to ensure that the partner is attending both to them and to the object(s) of interest, adjusting this according to the communicative level of the partner. When the nonverbal gestures produced by the toddlers with Down syndrome were compared to those of the typically developing controls, it was found that not only were declarative pointing gestures used competently, but that this kind of nonverbal gesturing was produced nearly twice as frequently. Given the delays experienced in acquiring spoken language, children with Down syndrome may compensate for their lack of language by making enhanced use of nonverbal routes to communicate with others. Franco and Wishart (1995) did not report similarly increased levels of nonverbal requesting gestures in their sample, suggesting that children with Down syndrome may have greater difficulty in making use of this particular communication route. Other studies using mental-age matched typically developing controls have found that children with Down syndrome generally make fewer requesting gestures than their mental age matches, a difficulty that is not seen in children with other developmental disabilities (Fidler, Philofsky, Hepburn, & Rogers, 2005; Mundy, Sigman, Kasari, & Yirmiya, 1988). These differences between children with Down syndrome and typically developing children do, though, appear to be less pronounced when requesting behaviors during social games (e.g., a tickle game) rather than toy play situations are considered (Fidler et al., 2005). In as much as findings from these various studies can be reconciled, they seem to indicate that difficulties with pointing gestures are not seen to the same extent as with requesting gestures. As Fidler et al. (2005) report, problems with the latter are particularly evident in toy play situations, something that may be a function of poorer problem-solving skills. This is consistent with the suggestion of Hobson et al. (2008) that requesting behavior and means-end understanding may be intricately linked. The direction of causality in any such relationship remains to be determined but the study by Fidler et al. highlights once again the need to consider context carefully when evaluating findings in this field.
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2.3. Imitation Imitation is a particularly important indicator of early sociocognitive understanding. It is widely seen as the foundation of socially based learning and has featured prominently in most major theories of child development, from Piaget onward. Imitating the actions of other people is generally taken as indicating a basic recognition of the inherent ‘‘likeness’’ of the self to others in the surrounding social and physical world. It is also usually regarded as an important indicator of emerging representational skills, that is, the ability to think about people and objects irrespective of whether they are currently physically present or not. Typically developing infants show the ability to imitate simple facial gestures of adults such as tongue protrusion soon after birth (Meltzoff & Moore, 1989), with some researchers reporting that even deferred imitation (i.e., reproducing the modelled gesture after a delay) is possible at very early infant ages (Meltzoff & Moore, 1994). More complex imitative abilities involving novel actions are not generally demonstrated until the middle of the first year of life, however (Heimann & Meltzoff, 1996). Down (1866) himself drew attention to the ability of children with Down syndrome to mimic others and most descriptions of ‘‘the’’ Down syndrome personality feature ‘‘loves to imitate’’ or some variation on this theme. Despite the evidence already reviewed above that young children with Down syndrome are at times more socially oriented than their typically developing peers, the development of imitative skills in Down syndrome has been the focus of very little research. Findings from the relatively few studies carried out to date are also difficult to reconcile. Two small-scale studies (Heimann & Ullstadius, 1999; Heimann, Ullstadius, & Swerlander, 1998) have shown that infants with Down syndrome, like their typically developing peers, are capable of imitating the mouth opening and tongue protrusion gestures of an adult model at a relatively early age. However, Dunst’s large-scale longitudinal study of infants (1990) tested between birth and 36 months on a variety of standardized tests of sensorimotor development, including gestural and vocal imitation tasks, identified differences rather than simply delays in the development of vocal imitative skills. It is also worth noting that although all of the sensorimotor skills studied by Dunst showed a slowing down of developmental rate with increasing age, vocal imitation abilities showed the steepest decline. A small group of studies have suggested that imitation may nevertheless be a relative strength in children with Down syndrome, both in infancy and at later ages (Hodapp et al., 1992; Neeman, 1971; Pueschel, Gallagher, Zartler, & Pezullo, 1987; Rast & Meltzoff, 1995). If so, this apparent strength might be thought to have potential for supporting the acquisition of more advanced cognitive and sociocognitive skills. A particularly insightful set of studies by
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Wright and his colleagues (Wright, 1998; Wright, Lewis, & Collis, 2006) suggest the opposite, however. Wright et al. (2006) used a series of developmentally ordered standard and modified object permanence tasks with children with Down syndrome (mean age 23 months), comparing their performance with that of younger, cognitively matched, typically developing infants. Object permanence tasks are often regarded as ‘‘pure’’ tests of early cognitive development and emerging representational competence and as such are widely used to assess developmental status. They consist of a series of hiding tasks of increasing complexity that test understanding of some of the basic physical laws determining the unique identity of objects (including social ‘‘objects,’’ i.e., people) and the predictability of simple everyday events (e.g., where a toy will be found if it rolls under a sofa). Although the children with Down syndrome in Wright’s studies were performing at a level similar to their typically developing matches on standard object permanence tasks (in which toys were hidden by the experimenter placing cups over them), they literally ‘‘lost’’ this ability when the possibility of imitating the researcher’s hiding actions was removed in a modified, leverbased version of the same hiding task (in which the cups were put in place by a lever operated by the experimenter, i.e., without any direct contact). This suggests that in the standard version of the task, instead of mentally representing the hidden object and using an appropriate means-end solution based on the object’s location, they may simply have been reproducing the researcher’s hiding action, that is, using their imitative skills to guide their search, a much lower level cognitive strategy. Wright et al. (2006) suggest that a predisposition to attend to social rather than nonsocial aspects of the world might underlie this behavior pattern, one which perhaps reflects a poorer overall level of representational skills but could also result from the representation of features of the social environment being favored over other sources of information. As the children in the study by Wright et al. also readily imitated search behaviors even in circumstances in which no object had been hidden, this again suggests that they were relying more heavily on imitation than their typically developing peers in their interactions with the experimenter. These possible differences in the processes driving behavior in object search tasks might explain the developmental instability reported in longitudinal and cross-sectional studies of object understanding in children with Down syndrome (Dunst, 1990; Morss, 1983, 1985; Wishart, 1993, 1996; Wishart & Duffy, 1990). Although eventually able to solve the highest level tasks, this important phase in cognitive development seems to unfold in a slightly different sequence in Down syndrome. Children with Down syndrome not only show different error patterns on object concept tasks in both the pre- and post-acquisition phases, but their apparent advances in understanding are often poorly consolidated, with little coherence evidenced across developmental stages, despite the conceptual commonality
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across lower and higher level tasks (Dunst, 1990; Morss, 1983, 1985; Niccols & Latchman, 2002; Wishart, 1987, 1993; Wishart & Duffy, 1990). Pertinent here is work by Rast and Meltzoff (1995) showing that infants and toddlers with Down syndrome can often succeed on deferred imitation tasks before they can solve hiding tasks involving invisible displacements. As these are abilities which would normally emerge together, this adds further weight to the suggestion that imitative skills are not nested within cognition in the same way as in typical development, that they may not be used in the same way and that they may thus not support development to the same extent. Rast and Melzoff interpreted their findings as demonstrating the children may take a more ‘‘pragmatic’’ approach to problem solving: They may be satisfied with finding a solution but are less concerned with understanding why that solution worked. This interpretation is in line with behavior seen at this age in a wide range of other cognitively challenging contexts, from formal IQ testing through to operant conditioning tasks (for overview, see Wishart, 1996). We return to this topic later in this chapter.
2.4. Expressing emotion In addition to the differences in attention, gesture, and imitation reviewed above, the affective component of early interactions between children with Down syndrome, their parents, and others may also differ in subtle ways from that seen in typical development, in terms of both the infants’ ability to display facial expressions and also their ability to respond appropriately to the emotions of others. Emotional communication has long been recognized as central to meaningful social interaction (e.g., Jones & Raag, 1989) and, in many respects, infants and children with Down syndrome show similar patterns of affective development to typically developing children: They smile more at people than at objects (Carvajal & Iglesias, 2000; Kasari et al., 1990) and are just as sensitive as mental-age matched typically developing infants to cessation of maternal interaction during the ‘‘still face’’ paradigm, although they do show fewer ‘‘carryover’’ effects to subsequent interactions (Moore, Oates, Goodwin, & Hobson, 2008). There are also subtle differences, though, both in displays of affect and in responses to other people’s emotional expressions, something that may in part be related to overall stage of cognitive and linguistic development (see Cicchetti & Beeghly, 1990b; Kasari et al., 1990). In the first year of life there is a delay in the development of smiling and laughing, with children with Down syndrome tending to show ‘‘dampened’’ intensity in some facial expressions of affect (Sorce & Emde, 1982; for overview, see Kasari & Sigman, 1996). In the preschool years, comparisons of the emotional expressions of children with Down syndrome to those of typically developing children of similar mental age show that although the children with Down syndrome display affective expressions for a similar total length of
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time during a toy play session, their affective expression changes more frequently (Kasari et al., 1990). Carvajal and Iglesias (2006) have recently reported that the vocally expressed emotions of infants with Down syndrome are also less readily interpretable than those of typically developing infants within the first year of life, with vocalizations of joy proving particularly difficult to identify accurately. Together, these differences suggest that the emotions of children with Down syndrome may be more difficult to interpret and respond to. It may be, however, that with time caregivers are able to adapt and pick up and respond to these less intense or less clearly expressed emotions. It may also be the case that children’s expressions become more ‘‘readable’’ with age. Indeed, mothers do perceive more communicative signals in general in developmentally older infants with Down syndrome compared to younger infants (Hyche, Bakeman, & Adamson, 1992). In the absence of a strong body of longitudinal evidence tracking such changes, though, this remains an uncharted area of development. On the basis of Cicchetti and Sroufe’s finding (1978) that infants with Down syndrome seem to show less fear when tested on the ‘‘visual cliff’’ paradigm, Cicchetti and Beeghly (1990b) also suggested that the relatively slower rates of information processing in Down syndrome may result in less frequent production of certain emotions such as surprise and fear, which require faster (and possibly more complex) information processing. This interpretation fits with evidence that young children with Down syndrome show less distress during separation from their caregiver in Ainsworth’s classic ‘‘strange situation’’ (e.g., Thompson, Cicchetti, Lamb, & Malkin, 1985; Vaughn et al., 1994).
2.5. Possible links between early sociocognitive behavior and caregiver styles of interaction As we have seen above, the patterns of early attention, gesture, imitation, and affective behavior differ in a number of important ways in the development of infants with Down syndrome. Caregiver interactions with the child are likely to be influenced by these subtle differences in the child’s interactive behavior. It has been reported, for example, that mothers of infants and toddlers with Down syndrome tend to take more opportunities to stimulate their child (e.g., through play), adopt more ‘‘directive but warm’’ styles of interaction than mothers of typically developing children, and provide more supportive behaviors (e.g., Buckhalt, Rutherford, & Goldberg, 1978; Moore et al., 2008; Roach, Barratt, Miller, & Leavitt, 1998; Sorce & Emde, 1982), with some of these differences in parenting style emerging during the child’s first year (Slonims & McConachie, 2006). Differences in how mothers use verbal and gestural communication have also been reported. In a recent small-scale study of mothers of preschool
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children with Down syndrome, Iverson, Longobardi, Spampinato, and Caselli (2006) found that the mothers produced fewer utterances, fewer complex combinations of words and gesture, and were more likely to hold a gesture for the full length of an utterance during a free play situation than were mothers of typically developing children of comparable expressive language ability. Iverson et al. proposed that such differences in interactional style might support the child’s attention regulation and reflect the mother’s sensitivity to her child’s information-processing difficulties. Moore, Oates, Hobson, and Goodwin (2002), however, emphasized the bi-directional nature of caregiver–child interactions, and noted the importance of distinguishing between the short- and long-term implications of caregiver interaction style. They suggested that this more directive but warm style may indeed be a compensatory response to the infants’ attention regulation and limited information-processing capacity and that while in the short-term this may make the infants more focused on interpersonal interaction, in the longer term it may result in greater dependence on the mother for regulating attention. This in turn may make it less likely that the infants direct triadic interactions themselves, with possible effects on subsequent language development. As Moore et al. noted, further longitudinal studies are required to test this interpretation. Any such work would also need to consider the host of other factors which have the potential to impact on these early parent–child interactions, including parents’ stress levels, cognitive coping strategies, and their perceptions of their child’s behavioral characteristics (see e.g., Atkinson et al., 1995; Kasari & Sigman, 1997).
3. Later Developments in Social Cognition: Understanding and Relating to Others 3.1. Emotional understanding As noted above, infants with Down syndrome may, to some extent, differ from typically developing infants in terms of the ways in which they display facial affect. They may also differ in their ability to read and respond to the affective expressions of others. This has been demonstrated in social referencing studies, which examine how children use affective information from the caregiver to guide their actions in ambiguous situations, a skill which usually develops by the end of the first year in typical development (Sorce, Emde, Campos, & Klinnert, 1985). There have only been a few studies in this area with children with Down syndrome, and these have used a traditional social referencing paradigm in which an ambiguous toy is presented, an adult makes either a positive or a fearful expression, and the child’s own affect and actions are then observed. Findings from these studies suggest that children with Down syndrome
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make fewer and shorter social referencing looks, with their responses often incongruent with the parental expression, for example, showing more positive affect when the parent has expressed fear than when positive affect has been expressed (Kasari et al., 1995; Knieps, Walden, & Baxter, 1994). These findings suggest that some children with Down syndrome may have problems interpreting the facial expressions of others and in using this information to guide their own actions, a difficulty that may stem from specific weaknesses in emotion recognition as well as from more general problem-solving difficulties. As Knieps et al. noted, such unpredictable patterns of responding to adults’ facial expressions are likely to have consequences for interactions between parents and their children, although this is an area which has not received much research attention as yet. Studies with school-aged children with Down syndrome show that difficulties in recognizing and using emotional information from faces may still be present at later developmental stages. Work in this area has explored recognition of the six ‘‘primary’’ emotions (happiness, sadness, anger, surprise, fear, and disgust), facial expressions that in typical development are recognized and distinguished with increasing accuracy over the preschool years (Herba & Philips, 2004). Despite using different experimental paradigms and a variety of stimuli (schematic faces, puppets, photographs of facial expressions), most of these studies have found evidence of emotion recognition difficulties in children with Down syndrome when performance is compared to that of typically developing children, irrespective of whether the matching was based on receptive language level, performance-related criteria, or composite mental age measures (Kasari, Freeman, & Hughes, 2001; Turk & Cornish, 1998; Williams, Wishart, Pitcairn, & Willis, 2005; Wishart & Pitcairn, 2000). The one exception to this, a study by Celani, Battacchi, and Arcidiacono (1999), focused on expressions of happiness and sadness only. The most recent studies in this field have drawn on a number of methodological recommendations made by Moore (2001) and have been designed in such a way as to try to rule out alternative explanations for the children’s difficulties, such as visual or hearing impairments or more general problems with the cognitive and linguistic processing demands of the tasks themselves. The use, for example, of a control identity-matching task in which participants are shown a photograph of a person and then asked to identify that same person from a selection of photographs rules out the possibility that more broadly based difficulties in face processing underlie emotion recognition weaknesses, as performance has generally not been found to be impaired on these tasks to the same extent (Williams et al., 2005; Wishart & Pitcairn, 2000; Pitcairn & Wishart, 2000). As with much of the research included in this chapter, the age range of children included in these studies has inevitably been rather wide, making it difficult to draw firm conclusions about the developmental unfolding of
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emotion recognition skills in Down syndrome. It is of relevance, however, that Kasari et al. (2001), using a variety of tasks tapping understanding of emotional expressions, found that although children with Down syndrome with a developmental age of around 3 years performed similarly to their mental age-matched peers, they had fallen significantly behind by the time they had reached a developmental age of 4 years. Follow up of the Down syndrome group after two years showed little change in emotion recognition ability, despite an increase in cognitive ability in the intervening period. This suggests that emotion recognition abilities do not keep pace with either chronological age or with more general cognitive abilities, something that is consistent with the finding of a lack of significant correlations between emotion recognition and more general cognitive or linguistic abilities in the studies carried out to date (Kasari et al., 2001; Williams et al., 2005). Although the studies above found that some children with Down syndrome seemed to show difficulties in emotional understanding overall, several have also found evidence of weaknesses in the recognition of specific emotions, with fear emerging as particularly problematic (Kasari et al., 2001; Williams et al., 2005; Wishart & Pitcairn, 2000). Although difficulties with other emotions such as surprise (Wishart & Pitcairn, 2000) and anger (Kasari et al., 2001) have also been reported, fear is the emotion for which difficulties have been found most consistently across different experimental paradigms. The study by Williams et al. included ‘‘error analysis’’––an examination of which facial expressions were selected in error in these photomatching tasks––and found evidence of atypical error patterns in the fear recognition trials: surprise, the emotion that typically developing children most commonly confuse with fear (see Gosselin & Simard, 1999), was not the most common emotion selected in error by the Down syndrome group, who instead tended to make errors spread across all emotions. This is an error pattern more commonly seen in much younger typically developing children, and therefore again suggests that the Down syndrome group experienced greater difficulties with fear recognition than would be expected on the basis of their mental age. It is worth highlighting a number of caveats at this point. First, although fear recognition difficulties have been found in children with Down syndrome in several studies to date, this is not indicative of a complete absence of fear recognition ability: In some studies, although fear recognition was somewhat impaired, it was nonetheless at above chance level. Second, within many of the studies, several different tasks tapping emotional understanding were used (e.g., photomatching tasks, emotion-to-story-matching). Difficulties have tended not to be found across all tasks within a single study, suggesting that if an emotion recognition deficit does exist, it is not necessarily pervasive, affecting all recognition contexts equally. Third, the body of evidence to date does not strongly suggest a definitive syndrome-specific profile of emotion recognition strengths and weaknessesin Down syndrome. In the main, difficulties have been
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found only in comparison to typically developing children. Comparisons with children with nonspecific intellectual disabilities or with children with other etiologies, such as fragile X syndrome, have tended not to report significant between-group differences (Turk & Cornish, 1998; Wishart, Cebula, Willis, & Pitcairn, 2007), although significant difficulties in comparison to those with Williams syndrome have been reported (Porter, Coltheart, & Langdon, 2007). In the main, though, there is not currently a clear picture of how the pattern of emotion recognition strengths anddifficulties in children withDown syndrome compares to that found in children with other developmental disabilities. The extent to which small group sizes and therefore lack of power to detect significant differences underlie this lack of syndrome-specific findings is unclear. A final caveat is that studies to date have focused mainly on static facial expressions, an experimental paradigm driven by the need to minimize extraneous task demands such as memory and language requirements. Consequently, and with few exceptions (e.g., Porter et al., 2007), little is known about the children’s abilities to recognize emotions from vocally expressed emotion or from richer, more naturalistic, dynamic stimuli. It is clear from these caveats that further detailed research on emotion recognition strengths and weaknesses is required. Nonetheless, from the few studies conducted to date it does appear that, for at least some children with Down syndrome, difficulties may be evident with emotion recognition in general and with fear recognition in particular. Explanations at both an environmental and a neurological level have been put forward for this fear recognition difficulty, but these are by no means mutually exclusive. In terms of environmental influence, Kasari et al. (2001) noted evidence from Tingley, Gleason, and Hooshyar (1994) that mothers of children with Down syndrome use fewer emotional and cognitive state terms in mealtime conversations with their children than do mothers of typically developing children, and suggested that children with Down syndrome may not therefore be receiving the same input about emotions as typically developing children. In particular, they suggest that because children with Down syndrome are widely perceived as being of a positive disposition, caregivers may use fewer negative emotional terms with them, thereby decreasing their opportunities to learn about negative emotions through direct experience. This also ties in with work suggesting that the youthful craniofacial appearance of children with Down syndrome is linked to a perception that these children have specific traits such as being naı¨ve, warm, and compliant (Fidler, 2003; Fidler & Hodapp, 1999): Caregivers may be less likely to use negative emotional expressions and language with children they perceive to have these ‘‘baby-like’’ qualities. The children’s own difficulties in displaying facial expressions (as discussed above) may also contribute to their difficulties in recognizing emotions in others by influencing the emotional responses of caregivers, with this in turn potentially reducing opportunities to learn about the full range of emotions.
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At a neurological level, the findings from emotion recognition research with children with Down syndrome also tie in, to some extent, with what is known of the neurology of both Down syndrome and emotion recognition (Williams et al., 2005; Wishart & Pitcairn, 2000). In typical development, understanding of emotional expressions is tied to the temporal limbic system, with processing of fear, in particular, linked to the amygdala (Calder et al., 1996; Dolan & Morris, 2000). In people with Down syndrome, there is evidence that the temporal limbic system is disproportionately reduced in volume and complexity, although it is less clear to what extent this is true specifically of the amygdala (Aylward et al., 1999; Jernigan, Bellugi, Sowell, Doherty, & Hesselink, 1993; Krasuski, Alexander, Horwitz, Rapoport, & Schapiro, 2002; Pinter et al., 2001). Imaging studies using emotion recognition tasks may help to delineate functional neurological differences in emotion recognition in Down syndrome, but there is as yet little reported work in this area. As is clear from these tentative explanations, research into emotion recognition in Down syndrome is still at a relatively early stage, and there are a number of logical routes that future studies could take. First and foremost, as with most of the other areas of social cognition discussed in this chapter, largescale, longitudinal studies are now required if a more detailed picture of how emotion recognition skills unfold in Down syndrome is to be obtained. Emotion recognition research should also now be extended to include more naturalistic, dynamic stimuli. Cautious interpretation will be required, however, as dynamic stimuli inevitably involve increased task demands, making it more difficult to ascertain that any weaknesses demonstrated are specifically related to emotion recognition difficulties. Eye tracking research, informed by studies in autism (e.g., Klin, Jones, Schultz, Volkmar, & Cohen, 2002), might also be helpful in elucidating the extent to which emotion recognition difficulties stem from differences at a process level. Given the studies outlined earlier suggesting that children with Down syndrome show a heightened focus on caregivers’ faces, a more detailed knowledge of the range of facial features they attend to, of the patterns of scanning involved, and of how these compare to those used by typically developing children should be highly informative. An additional area of research worthy of exploration is how emotion recognition skills relate to other areas of sociocognitive development, such as theory of mind and empathy, as well as to the acquisition of specific socioadaptive skills (such as appraisal of the approachability of strangers––see e.g., Porter et al., 2007). One final, but obvious strand of future work is more pragmatically driven. The ability to understand emotional expressions is just one of a whole spectrum of sociocognitive skills, but it plays a vital role in the development of social competence (Denham et al., 2003). An obvious gap in research to date is investigation of the direct impact that emotion recognition difficulties have on the lives of children and young people
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with Down syndrome. Research of this kind is now required, exploring not only this relationship but also how children who do experience emotion recognition difficulties can be better supported in overcoming or circumventing these difficulties. This could, for example, explore whether the use of technological solutions that allow self-paced learning about a range of emotions might be of value (e.g., Golan & Baron-Cohen, 2006).
3.2. Theory of mind Much of the current debate within theories of social cognition in mainstream research revolves around what is known about the child’s emerging ‘‘theory of mind.’’ This refers to the ability to attribute mental states such as knowledge, beliefs, and desires, to oneself and others, a skill which plays a vital role in predicting and explaining behavior in social contexts. In typically developing children, these skills unfold gradually in the preschool years, with the period between 3 and 5 years marking a substantial shift in competence. During this period the understanding that another person can hold a belief that is false and contrary to one’s own develops. The child’s understanding of ‘‘false belief’’ can be tested using several classic paradigms, including the unexpected transfer task (Wimmer & Perner, 1983). In this task a character (e.g., Maxi) hides an object and leaves the room. The object is then transferred to another location and the child is asked where Maxi will look for the object when he returns. If the child has an understanding of false belief he will answer that Maxi will look in the original location. False belief understanding is only one aspect of theory of mind, but is often regarded as a key stage in conceptual development, and the ‘‘litmus test’’ of theory of mind. Skills that emerge earlier in infancy, such as joint attention and social referencing, are considered to be the precursors of these later mentalizing abilities (for overview see Flavell, 1999). Given the central role theory of mind has played in cognitive explanations for autism, it is perhaps unsurprising that relatively few studies have specifically explored the development of these skills in children with Down syndrome; often the role of the Down syndrome group has been primarily to serve as a control for level of cognitive impairment in the autism group. There is, though, evidence that those with intellectual disabilities other than autism do show theory of mind difficulties in comparison to typically developing individuals, albeit with these being significantly less severe than in autism (Abbeduto, Short-Meyerson, Benson, & Dolish, 2004; Yirmiya, Erel, Shaked, & Solomonica-Levi, 1998). The small number of studies focusing specifically on Down syndrome makes it difficult, however, to determine whether difficulties are any greater or lesser in children with
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Down syndrome than in children with intellectual disabilities of similar severity but different etiology. The evidence on theory of mind in Down syndrome is rather mixed. Early research suggested that the children’s abilities were comparable to those of typically developing children matched on receptive language, both on firstorder (‘‘Mary thinks that. . .’’) and second-order (‘‘Mary thinks that John thinks that. . .’’) belief attributions in false belief tasks (Baron-Cohen, 1989; Baron-Cohen, Leslie, & Frith, 1985). Subsequent studies, however, have reported that both children and adults with Down syndrome obtain lower scores on some theory of mind tasks, such as false belief, when compared to typically developing groups and those with fragile X syndrome (Abbeduto et al., 2001; Binnie & Williams, 2002; Yirmiya, Solomonica-Levi, Shulman, & Pilowsky, 1996; Zelazo, Burack, Benedetto, & Frye, 1996). These findings seem to hold regardless of whether groups were matched on receptive vocabulary level or on a verbal or performance mental age measure. This is an important consideration, given that the matching of those with Down syndrome to younger typically developing children on the basis of a receptive vocabulary measure may be problematic; there is evidence that some of these measures may be particularly influenced by chronological age and life experience (Chapman, 2006; Miolo, Chapman, & Sindberg, 2005). If children with Down syndrome do have difficulties on false belief tasks, though, how can this be explained? In order to rule out nontask-related explanations for failure, standard false belief tasks control for the possibility that poorer performance might simply be the result of more general memory and language task demands rather than poor interpersonal understanding by including, for example, memory control questions (e.g., Abbeduto et al., 2001; Binnie & Williams, 2002). In some studies, a comorbid diagnosis of autism in some of the children with Down syndrome cannot be ruled out as a potential explanation for the difficulties found. Although the majority of those with Down syndrome show no evidence of autism, rates of autism are still somewhat higher than would be expected by chance (Kent, Evans, Paul, & Sharp, 1999). Some studies, though, have specifically sought to rule out this possibility through their inclusion criteria (Yirmiya et al., 1996; Yirmiya, Pilowsky, Solomonica-Levi, & Shulman, 1999). Research with typically developing children and children with autism suggests some links between theory of mind and ‘‘executive function’’, the umbrella term used to describe goal-directed behaviors such as planning, impulse control, inhibition, and working memory (Hill, 2007). Given that there have been findings of difficulties with aspects of executive function in those with Down syndrome (Zelazo et al., 1996), it is possible that an executive function deficit could at least partially explain poor performance on theory of mind tasks. This idea is consistent with the findings that the frontal cortex––which plays a central role in executive functioning––is
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disproportionately reduced in volume in Down syndrome ( Jernigan et al., 1993). It also fits with neurophysiological findings of early differences in comparison to typically developing infants in brain activity in frontal sites (Karrer, Karrer, Bloom, Chaney, & Davis, 1998). In relation to other cognitive aspects of theory of mind development, it has also recently been suggested that difficulties shown by young typically developing children and by children with autism on false belief tasks may indicate a more general difficulty with counterfactual reasoning, that is, the ability to contemplate alternatives to the reality before them (Grant, Riggs, & Boucher, 2004; Riggs, Peterson, Robinson, & Mitchell, 1998; Taggart Ridley, Rudd, & Benefield, 2005). This reasoning ability should therefore perhaps also be investigated in children with Down syndrome, alongside their performance on standard theory of mind tasks, if the origin of difficulties on the latter tasks is to be better understood. Language development in children with Down syndrome may also play a role in explaining theory of mind difficulties. In relation to typically developing children, Astington and Jenkins (1999) suggested that a certain level of language skills is not simply necessary to meet the task demands of false belief testing, but that linguistic development is fundamentally related to and supportive of theory of mind development, with language competence at earlier ages predicting later theory of mind ability. They also suggested that aspects of syntactic development may be particularly important for theory of mind development. Further exploration of the link between false belief understanding and specific aspects of language development in Down syndrome may therefore be warranted, particularly given evidence that syntactic development is a relative weakness in Down syndrome (e.g., Chapman, 2003) and that children with Down syndrome use fewer internal state terms than typically developing children of similar developmental level (Beeghly & Cicchetti, 1997). Mainstream research into theory of mind is now beginning to focus on the impact of the child’s environment, and it seems that early family interactions may, at least in part, have a role to play in facilitating the development of theory of mind (see e.g., de Rosnay & Hughes, 2006). In typical development, links have been found between caregivers’ talk of mental states and children’s later performance on false belief tasks (for overview see Dunn, 1996). Siblings also appear to assist the child’s theory of mind development (e.g., Peterson, 2000); indeed, typically developing children make more references to mental state during conversations with siblings and friends than they do with their mothers (Brown, DonelanMcCall, & Dunn, 1996). Given the findings discussed earlier, suggesting that caregivers of children with Down syndrome may use fewer cognitive state terms (Tingley et al., 1994), this opens up interesting possibilities for longitudinal research looking at the relations between family interactions and theory of mind development in Down syndrome. It is currently unclear
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to what extent family interactions play a role in this key aspect of sociocognitive development, but any such research is likely to require more than a simple replication of work to date with typically developing children, as patterns of interaction are inevitably likely to differ in important ways in families who have a child with Down syndrome. In terms of other directions for future research, given the relative paucity of theory of mind studies in Down syndrome to date, it is at this stage perhaps premature to make links to the neurological basis of theory of mind, as has been done in typical development and autism spectrum disorders (e.g., Frith & Frith, 2001). There are also likely to be some limits in the extent to which more advanced theory of mind skills can be explored in Down syndrome: Many of the higher level tasks, such as ‘‘reading the mind in the eyes’’ (Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001), make complex cognitive and linguistic demands of the participant, some of which are likely to be beyond the cognitive abilities of many children with Down syndrome. A final point to consider is whether theory of mind interventions might be helpful for children with Down syndrome. There is evidence from one small-scale study that computer-based interventions may help children with Down syndrome to pass false belief tasks, although this may require lengthier interventions than for young typically developing children (Swettenham, 1996). However, the extent to which such interventions would actually assist in the development of ‘‘real world’’ mentalizing abilities is unclear and a focus on developmentally earlier skills may prove to be more helpful in the case of Down syndrome.
3.3. Empathy and prosocial behavior Empathy is an area of sociocognitive development where the skills of emotional understanding and theory of mind come together. Due to its internalized nature, empathy is inherently a particularly difficult ability to study in developmentally young children. This may explain why, with the exception of work by Sigman and Ruskin (1999) and Kasari, Freeman, and Bass (2003), this area of development in children with Down syndrome has received very little research attention to date. It may also reflect the fact that empathy is an inconsistently defined and multidimensional construct, with affective and cognitive components that include perspective-taking, discrimination of affective states and emotional responsiveness skills (Eisenberg, Losoya, & Guthrie, 1997; Feshbach, 1982; Hoffman, 1982). Empathic responses also vary according to age, gender, and contextual factors (Feshbach, 1982; Zhou, Valiente, & Eisenberg, 2003), and so if children with Down syndrome do show reduced levels of empathic responding, this could be for a host of different reasons that may prove to be exceptionally difficult to untangle empirically. Prosocial behavior
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(i.e., helpful, comforting behavior) is frequently studied alongside empathy. These are related but distinct constructs, likely to tap a somewhat different set of underlying skills (Feshbach, 1982). Studies of empathy and of prosocial behavior in children with Down syndrome have utilized paradigms that explore children’s responses to an adult’s distress (caused e.g., by the adult ‘‘accidentally’’ hitting her or his own finger), usually comparing these to the responses of typically developing controls of a similar developmental level and of children with other intellectual disabilities of a similar level of severity. The longitudinal study of Sigman and Ruskin (1999) explored empathy and prosocial behavior in children with Down syndrome from around 3 years of age, retesting them at around 11 years of age. They found that at 3 years of age the children had significantly lower ratings than the typically developing children and children with intellectual disabilities other than Down syndrome on a composite empathy/prosocial behavior scale; average ratings indicated that they looked at the experimenter, but showed very little concern, affective involvement, or prosocial behavior in response to the experimenter’s distress. When they retested their sample at approximately 11 years of age they found that they now showed similar rates of interest and concern about the experimenter when compared to the children with intellectual disabilities, although no comparisons with typically developing children were conducted at this later data point. Kasari et al. (2003), using a similar paradigm, compared children with Down syndrome of around 8 years of age to typically developing children and children with nonspecific intellectual disabilities matched on mental age and language ability. The children with Down syndrome were significantly more likely to show prosocial behavior than were the children in the comparison groups (e.g., offering comfort) when the experimenters hurt themselves, but showed very few affective responses, displaying almost no positive or negative affect. By contrast, typically developing children tended to ask questions rather than offer physical comfort and showed high rates of negative affect. More abstract, hypothetical scenarios have also been used to explore empathic responses. Kasari et al. (2003), for example, also used a puppet paradigm based on happy, sad, angry, and scared scenarios. They found that, when the children were asked how the scenarios made them feel, the 8-year-old children with Down syndrome were significantly less likely than the typically developing children to show empathy by reporting that the scenario made them feel the same as the character in the story. Differences in methodology across these studies of empathy and prosocial behavior make comparison of findings difficult, but reports to date do seem to indicate that, particularly at older ages, children with Down syndrome show equivalent––or higher––levels of prosocial behavior in situations where an adult shows distress than do typically developing children and other children with intellectual disabilities. This fits with findings
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showing that children with Down syndrome show similar levels of prosocial behavior to children with intellectual disabilities in other interpersonal contexts, for example, sharing and cooperation (Sigman & Ruskin, 1999). The findings relating to empathic sharing of affective experiences are somewhat less clear, but seem to suggest the opposite, that children with Down syndrome show lower levels of affective empathic responses than typically developing children of a similar developmental level. However, it is possible that such findings are not indicative of absent or diminished empathy. As Gilmore, Cuskelly, and Hayes (2003) noted, failure to express emotion does not necessarily mean that emotion has not been experienced: Children with Down syndrome may simply manifest empathy somewhat differently than do typically developing children. The findings from the puppet paradigm used by Kasari et al. also suggest that children with Down syndrome may have difficulty in expressing empathy verbally in more abstract, hypothetical situations, noting that there is now a need for research that further delineates the cognitive, social, and affective components of empathy in order to identify which specific components represent strengths or weaknesses in Down syndrome. Given the linguistic difficulties present in Down syndrome, another challenge for future research is to identify appropriate additional ways of measuring empathy, such as physiological measures and parental reports of key behaviors (see e.g., Zhou et al., 2003).
4. Linking Sociocognitive and Cognitive Development: Learning from and with Others Learning from others, whether directly or indirectly, is central to almost all aspects of sociocognition and, by implication, is involved in a great many aspects of cognitive development. As we have seen, while there is evidence that young children with Down syndrome may give people preferential attention over objects, there is also evidence that this may not necessarily stand them in good stead when it comes to their learning. A number of research teams have reported instances of the children using their interpersonal skills inappropriately in testing contexts, showing a predisposition to engage with the experimenter rather than with cognitively challenging tasks. Parental reports of diversionary social behaviors or passive nonengagement in learning contexts are also frequent, leading one commentator to suggest that Down syndrome is perhaps an example of an evolutionarily determined ‘‘thrifty phenotype’’, one in which a metabolically conservative brain favors energy-saving responses when cognitively stressed (Reser, 2006).
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4.1. Learning with others The diversionary interpersonal behaviors described above are seldom the direct focus of empirical study. Evidence of poor task persistence, low levels of goal-oriented behavior and elevated levels of requests for adult help––even when not needed––have, however, been reported by a number of research teams at a variety of ages and in a variety of contexts (Fidler et al., 2005; Kasari & Freeman, 2001; Landry & Chapieski, 1990; Ruskin et al., 1994; Pitcairn & Wishart, 1994; Wishart, 1996). This suggests the emergence of a generalized, other-oriented learning style, a coping strategy that may work in the short term but is unlikely to be cognitively productive, as pointed out by Zigler many decades ago (see e.g., Zigler, 1969). Wishart and colleagues, for instance, reported this type of behavior in a series of cross-sectional and longitudinal studies of object permanence development in infants and preschool children with Down syndrome, citing instances of the children producing exaggerated social behaviors during testing, including locking gaze with the researcher and producing party tricks such as hand clapping or blowing raspberries (for overview, see Wishart, 1996). What distinguished these social behaviors from those of typically developing controls was not their content or frequency, but their timing. They were most likely to be produced in the middle of a hiding trial and, as a result, the trial was often ‘‘failed’’ either because a search error was eventually made or more commonly by default because no scoreable search in fact took place. Typically developing control children, whether age- or stage-matched, were much more likely to concentrate on the task at hand, restricting their social interactions with the researcher to between trials and showing much more consistent developmental profiles of passes and fails. Pitcairn and Wishart (1994) reported similar heightened sociability in 3–5 year olds when faced with an impossible task, a shape-posting task in which two of the five shapes had no corresponding holes. Once again, these sorts of behaviors were not seen in age- or stage-matched controls who quickly learned that the task could not be solved by traditional means and simply looked for an alternative solution, such as taking the lid off the posting box, a solution twice as likely to be produced by the younger, mental age matched controls as by the children with Down syndrome. Kasari and Freeman (2001) likewise found increased adult-oriented behavior in 5–12 year olds when asked to complete a similar set of puzzles, two of which had pieces which looked as if they belonged but did not in fact fit. The children with Down syndrome in this study also persisted less with the tasks than the control children (both with and without intellectual disabilities); they also looked more often at the adult, requested help more frequently, and showed less goal-oriented behavior, suggesting that the attentional preference for people over cognitively challenging objects seen at younger ages carries over into these later school-age years. Once again, however, the picture is
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not always consistent across studies. Two studies comparing mastery motivation in young children with Down syndrome to that of mental-age matched typically developing children found that the children with Down syndrome were just as persistent on cognitively challenging tasks (Gilmore, Cuskelly et al., 2003; Glenn, Dayus, Cunningham, & Horgan, 2001). They did, however, obtain lower ratings of persistence on a parent-completed questionnaire than the typically developing children, suggesting that although lower levels of persistence are not inevitable in Down syndrome, they do occur in some contexts. It is therefore important to further understand the types of environments and tasks that maximize children’s motivation to persist with cognitively challenging tasks. The inappropriate application of interpersonal skills in some potential learning contexts causes this kind of behavior to stand out and may explain the longevity of the ‘‘friendly, sociable but none-too-bright’’ stereotype of Down syndrome. While charming, this kind of behavior seems likely to have only adverse developmental implications, particularly given parallel evidence that children with Down syndrome may become increasingly reluctant learners as their experience of learning difficulties accumulates (see e.g., Wishart, 1996). On closer inspection, many of these apparently ‘‘social’’ behaviors do not in any case seem to be truly social in that they show little accommodation to the behavior of the supposed partner in the interaction. Some of the behaviors may stem from the children’s lower and slower attention-processing capacities (Zelazo & Stack, 1997) but, regardless of origin, attempts to redirect attention to the task in hand often prove futile. These behaviors once again highlight differences in how sociocognitive skills, once acquired, may be put to use in children with Down syndrome. Given that adults already tend to perceive children with Down syndrome as being more immature and sociable than typically developing children or children with other syndromes, possibly on the basis of their baby-like features (Fidler & Hodapp, 1999), and given that some parents and professionals have lower than necessary expectations of their developmental potential (Gilmore, Campbell et al., 2003; Wishart & Manning, 1996), the stage is set for developmentally low expectations to become self-fulfilling. It is important to emphasize that this selective use of social skills does not imply that children with Down syndrome are inherently more sociable at all ages. Work with younger children (e.g., Ruskin et al., 1994) and studies of parental report measures suggest this may be a developmental trend in the early years (Fidler, Hepburn, & Rodgers, 2006), but a number of studies with children of older ages provide little support for any such outgoing temperament at later ages (see e.g., Huntington & Simeonsson, 1993; Serafica, 1990). There is indeed some evidence that socioadaptive skills may plateau at as early as 7 years of age in some children, and even that the majority of children prefer to be alone than in the company of others by
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the time they are teenagers (Dykens et al., 2002). The fact that individual variability in functioning in this area widens at older ages (Dykens, Hodapp, & Evans, 1994), however, indicates that there is not necessarily a low ceiling on skill acquisition and that higher developmental levels are achievable.
4.2. Learning from others Given that the biggest obstacles for children with Down syndrome lie in acquiring basic cognitive skills, it is perhaps surprising how little empirical research has looked directly at the role that others play in learning in these children. It is widely recognized that all children, with and without intellectual disabilities, can learn a great deal from observing and working alongside other children and as a result cultural communities worldwide are formally and informally structured to support this process (Rogoff, 2003; Tomasello, 1999). In schools, peers are a plentiful resource and research has demonstrated that two heads can indeed be better than one in problemsolving activities, with new levels of understanding often achieved by one or both learning partners. Collaborative learning is therefore widely used in mainstream education as a teaching and learning approach. It is rarely utilized with children with intellectual disabilities, however, possibly on the assumption that the metacognitive skills on which it capitalizes are less likely to be available to such children. Although there is a very large body of literature on collaborative learning outcomes for children with learning (as opposed to intellectual) disabilities, only one study to our knowledge has attempted to evaluate its effectiveness with children with significant levels of intellectual disability (Wishart, Willis, Cebula, & Pitcairn, 2007). This study examined the effects of collaborative learning experience on a core cognitive skill, sorting by category, in three child groups: typically developing 3–7 year olds and children with either nonspecific intellectual disability or Down syndrome, aged 7–17 years. Two studies with young typically developing children (Fawcett & Garton, 2005; Garton & Pratt, 2001) had already demonstrated that the ability to sort simple shapes on the basis of size, shape, and/or color improved after collaborative experience with a more able partner on an unrelated sorting task (placing toy furniture into rooms in a doll’s house). Children in the three groups in the study by Wishart et al. were therefore each paired with a child who was similar in age but slightly more advanced in shape-sorting ability and encouraged to collaborate on the furniture-sorting task, with postcollaboration shape-sorting ability then reassessed. Findings were interesting in that they differed across groups, despite sorting ability levels being broadly equivalent at entry to the study. In the typically developing pairings, basic sorting performance improved significantly in the lower ability partner only (as in Garton and Pratt’s studies). This pattern was reversed in the pairings of children with a nonspecific
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intellectual disability. Here, it was the higher ability partner who benefited from peer collaboration. In pairings where the lower ability partner had Down syndrome, however, neither partner improved significantly, suggesting that the sociability attributed to children with Down syndrome does not necessarily fully support either their or their partner’s learning in social contexts. Although these findings suggest that children with Down syndrome may not always benefit cognitively from engaging in joint problem-solving activities with other children, they should not engender unnecessary pessimism. Many of the children with Down syndrome in this study, although willing to cooperate with their partner (e.g., by handing them the pieces of furniture), made few attempts to engage in any task-related conversation, an activity known to be central to enhanced outcomes (Fawcett & Garton, 2005). In some pairings, the child with Down syndrome was in fact effectively ignored by his or her partner, with the two children simply working in parallel on the task. It is therefore not surprising that no gains were made by either partner in such pairings. This was a naturalistic study in which interaction between the two potential learning partners was encouraged but in no way directed, however, and it is easy to see ways in which the essential peer elements of the experience could be maintained while being better supported by the presence of an adult facilitator.
5. Conclusions From the extensive literature reviewed above, it is clear that although children with Down syndrome develop many of the same sociocognitive skills as their typically developing peers, these tend to emerge at later ages and sometimes show qualitative differences both in how they are expressed and in how they are put to use in social and learning contexts. Good progress has been made with respect to research on the earliest emerging indicators of social cognition and growing attention is now being paid to the higher level skills that should follow on from these, but there is still a relative dearth of studies at these later stages of sociocognitive development. There is consequently little information on either developmental trajectories or possible developmental ceilings on later core aspects of sociocognitive development in Down syndrome. There is, though, at least some support for the suggestion that sociocognitive development mirrors other aspects of cognitive development in Down syndrome in that it is somewhat fragmented and less well integrated than in typical development. More detailed knowledge of the development of sociocognitive skills in Down syndrome, and of how these relate to fundamental aspects of cognitive and linguistic development, is essential for identifying the best ways of
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providing interventions to support, not only the earlier and better development of these skills, but also those other aspects of learning that they feed into. Although it can be encouraging to establish that children with Down syndrome have sociocognitive skills in line with or not far behind those of their developmentally matched peers, it is essential that we do not lose sight of the fact that these skills are usually very much behind what would be expected for chronological age. These differences in ability to interact effectively with peers or adults, whether in social or learning contexts, have the potential to severely undermine developmental progress, as well as adversely affecting quality of life and ultimately mental health (Collacott et al., 1998; Wallander, Dekker, & Koot, 2003). If effective early intervention programs are to be designed, filling these gaps in current knowledge must be a priority. There are a number of key areas for future research in this field. However, if real progress is to be made, the complexities of carrying out research in this area should not be underestimated. Currently, a major obstacle to integrating findings on social cognition in children with Down syndrome is the diversity in methodological approaches used by different research teams. These include, for instance, differences in choice of comparison groups, in matching procedures, and in age range studied, as well as basic differences in the methods and materials used to assess sociocognitive understanding at different ages and stages. Differences in approaches can sometimes be helpful, as we have seen in the recent work on emotion recognition. If converging results are found despite contrasting methodologies, this allows increased confidence in the validity of findings. However, greater consistency in these aspects of methodology seems essential for the field to move forward. In addition, although important insights have come from some relatively small-scale studies, sample size is clearly a major obstacle to definitive research in this field. The studies reviewed above vary from single case to relatively large scale, with a sample size of anywhere about 20 generally considered to be respectable. This inevitably limits the types of analysis that can be carried out, as well as the strength of findings. It also poses a particular problem in research that seeks to compare abilities in contrasting etiological groups, many of which have even lower incidence rates than Down syndrome. Even with relatively large sample sizes, syndrome-specific difficulties may be subtle and detectable only in comparison with typically developing children and not always across etiological groupings. If the precise extent of strengths and weaknesses in social cognition in children with Down syndrome is to be identified with any confidence, the inherent constraints on sample size in this kind of research have to be overcome. Multisite (and ideally longitudinal) studies, using standardized measures, shared protocols, and reporting of effect sizes as well as statistical significance of results would seem to be the way forward.
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Impairments in sociocognitive processes are, of course, not unique to Down syndrome, and a key area of future research is to continue to profile how sociocognitive development in Down syndrome compares and contrasts with other etiologies. Only then can tailor-made interventions be designed. Difficulties in aspects of social cognition have been reported in many groups of children both with and without intellectual disabilities, including children with autism and attention deficit hyperactivity disorder (ADHD), as well as in deaf children of hearing parents (for overview see Baron-Cohen, Tager-Flusberg, & Cohen, 2000). Clearly there are many different reasons, both psychological and neurological, for failing a sociocognitive task, and parallels should not necessarily therefore be drawn between these different conditions. It seems clear, for example, that the sociocognitive difficulties experienced by children with Down syndrome are both less severe and qualitatively different from those experienced by children with autism spectrum disorders (e.g., Loveland et al., 1995), although understanding sociocognitive development in children with Down syndrome who have a dual diagnosis of autism is clearly important. Especially conspicuous by its absence in the current literature of sociocognitive development in Down syndrome is any large body of research directly investigating how the social environment in which children with Down syndrome grow and learn impacts on their sociocognitive and wider development. Mainstream research in child development has seen a welcome swing back to recognizing the important role of environment in determining behavior and psychological functioning (for overview, see Rutter, Moffitt, & Caspi, 2006). In the case of social cognition in Down syndrome, environmental factors potentially operate at two levels. As we have seen, there is some evidence that the children’s partners in learning, whether children or adults, may adjust their interactive styles in ways which are sometimes helpful but sometimes not. There is also some evidence that the children themselves may sometimes use those sociocognitive skills that they do acquire in ways that sometimes help, but may sometimes hinder, their development. There is to date also a lack of research looking at the impact that sociocognitive difficulties have on the actual day-to-day functioning and on the lives of young people with Down syndrome. As is the case for many children with intellectual disabilities, forming reciprocal friendships and taking a full and age-appropriate part in social activities with nondisabled peers is clearly not always easy (Cuckle & Wilson, 2002; Guralnick, Neville, Hammond, & Connor, 2007). Fortunately, increasing attention is now being paid to these issues in current intervention programs (see e.g., Fidler, 2006; Guralnick, 1996, 2002a, 2002b, 2005; Iarocci, Virji-Babul, & Reebye, 2006; Iarocci et al., this volume). What is not clear, though, is the precise role that sociocognitive difficulties play––alongside linguistic, physical, and cognitive difficulties, and environmental factors such as discrimination within society–– in contributing to these outcomes. This is an important area not only for the
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children themselves but also for their families. Stress trajectories for mothers of children with Down syndrome suggest that while in the early years stress may be lower in comparison to that experienced by mothers of typically developing children or children with autism or emotional disorders (see e.g., Dumas, Wolf, Fisman, & Culligan, 1991; Kasari & Sigman, 1997), this increases with increasing age. Modeling analyses suggest that this reflects changes in the behavioral, cognitive, and linguistic trajectories of the children themselves (Most, Fidler, Laforce-Booth, & Kelly, 2006), all factors, as we have seen, that may also influence the ease or difficulty with which the children are likely to interact successfully with children and adults around them. Unlike the proliferation of interventions specifically addressing sociocognitive difficulties in children with autism over the last three decades, interventions for children with Down syndrome that take account of these aspects of development––and of their potential impact on interpersonal interactions––are only now coming to the fore. The role that education plays in supporting children with Down syndrome’s sociocognitive development is also important. It is interesting to note that although educational professionals sometimes underestimate the developmental potential of children with Down syndrome, they perceive the greatest benefits of inclusive education as being likely to lie in social rather than academic advances (Gilmore, Campbell et al., 2003; Wishart & Manning, 1996). Very little research, however, has attempted to systematically evaluate the outcomes of inclusive schooling for children with Down syndrome on either of these fronts and despite the best of intentions, the reality of inclusion would appear sometimes to be somewhat removed from its underlying principles (Wishart, 2005). Many children with Down syndrome being educated in inclusive classrooms, for example, may spend part of their school day in a special support unit and much of the rest of it working with the support of an adult learning assistant in parallel rather than alongside their classmates (Lorenz, 1999). This is not uncommon for children with intellectual disabilities. Hughes et al. (1999), for example, found that even in nonacademic parts of the school day, such as lunch breaks, students with intellectual disabilities rarely engage with their typically developing peers. This is hardly conducive to forming lasting friendships with other nondisabled classmates. This review of necessity has taken a largely atheoretical approach to evaluating findings on the development and use of social cognition in children with Down syndrome. Work on social cognition is very much to the fore in mainstream research on child development and is currently a highly contested field in terms of theory (see e.g., Carpendale & Lewis, 2006; Flavell, 1999; Flavell et al., 2002; Racine & Carpendale, 2007a,b). Studies of social understanding have widely displaced studies of ‘‘purer’’ cognitive skills. Much of this is a consequence of the move away from
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Piagetian accounts of cognitive development to Vygotskian-influenced social constructivist views of how children come to understand the world around them. This trend is also now becoming evident in intellectual disability research but within research on Down syndrome there is as yet insufficient evidence to contribute to evaluation of competing theories of social cognition. It seems reasonable to suggest, however, that future findings in this area will play an important role in refining current theories, enabling them to be applied to both typical and atypical child populations. One final point is perhaps worth making. To date, a small number of research teams have contributed disproportionately to what is currently known about how social cognition develops in children with Down syndrome. Although there has been a resurgence of interest in this area in recent years, many aspects of sociocognitive functioning still remain comparatively unexplored, particularly beyond the preschool years. The classic work done in the 1970s and 1980s on the earliest appearing indicators of sociocognitive understanding in Down syndrome benefited hugely from drawing on the innovative paradigms and methodologies emerging from studies of typical child development at that time and from the new science of infant psychology. Recent years have seen an exponential growth in mainstream research on the role of social understanding in child development, and once again new paradigms and exciting technological advances in data collection methods are available. These offer huge opportunities for expanding and refining our knowledge of social cognition in Down syndrome. In doing so, it is important that we do not lose sight of the need to find ways to relate that knowledge to the real world difficulties experienced by children with Down syndrome and to incorporate it into timely and appropriate interventional support programs.
ACKNOWLEDGMENTS We gratefully acknowledge the collaboration of the children, families, and schools who have taken part in those of our studies which have been included in this review. We also thank the other members of our own research team who contributed to these studies, along with Down’s Syndrome Scotland, the Fragile X Society, and the UK Medical Research Council for their continuing support to our program of research. Especial thanks are extended to the reviewers of an earlier draft of this chapter for their generous and insightful comments.
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The Development of Social Competence Among Persons with Down Syndrome: From Survival to Social Inclusion Grace Iarocci, Jodi Yager, Adrienne Rombough, and Jessica McLaughlin Contents 1. Introduction 2. The Case for Social Competence Research on DS 3. Defining the Construct of Social Competence 3.1. Cognitive influences 3.2. Social–environmental influences 4. Status of Evidence on Social Competence in DS 4.1. Infancy and the preschool years: Dyadic and triadic interactions 4.2. Middle childhood: Peer interactions, group play, and friendships 4.3. Adolescence: Intimate relationships and social inclusion 5. Conclusion Acknowledgments References
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Abstract Socially competent behavior requires the effective coordination of multiple social-cognitive and emotion processes and contextual factors in order to adequately meet the demands of a particular social situation. The emerging evidence suggests that limitations in the child’s social-cognitive processing as well as inadequate contextual supports may compromise the development of social competence among children and adolescents with Down syndrome (DS). Research is presented on key social-cognitive processes and contextual influences that may hinder or facilitate the development of social competence among children and adolescents with DS. The review is organized around key developmental tasks thought to reflect behavioral indices of social competence
Department of Psychology, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35003-9
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(i.e., parent–child interactions, peer relations, adolescent friendships, and community integration) from infancy through to adolescence.
1. Introduction Down syndrome (DS) occurs as a result of the presence of all or a portion of an extra copy of chromosome 21 and is the most common noninherited ‘‘organic’’ cause of mental retardation. The genetic anomaly of DS has powerful and specific influences on the development of the child and also inadvertently affects significant people (i.e., parents, siblings, teachers, and friends) in the child’s life. The unique profile of disabilities associated with DS includes medical, motor, social, affective, and cognitive features. These individual factors may interact with contextual factors in the child’s family, peer group, school, community, and culture to determine variability in development. Of particular interest is the wide variability in social adaptation among people with DS that cannot be accounted for by IQ alone. In this chapter, we address the need to adopt a more differentiated view of social abilities among persons with DS. We propose that the friendly, sociable, and charming behaviors commonly observed among children with DS may reflect a cursory form of social competence. Whereas basic processes such as social interest are necessary, they are not sufficient for the development of social competence. Socially competent behavior requires the effective coordination of multiple social-cognitive and emotion processes and contextual factors in order to adequately meet the demands of a particular social situation. The emerging evidence suggests that limitations in the child’s social-cognitive processing as well as inadequate contextual supports may compromise the development of social competence among children and adolescents with DS. We begin by making the case that social adaptation is a primary concern in the lives of children with DS and we identify social competence as a relevant construct, defining it within developmental and socioecological perspectives. Research is presented on key social-cognitive processes and contextual influences that may hinder or facilitate the development of social competence among children and adolescents with DS. The review is organized around key developmental tasks thought to reflect behavioral indices of social competence (i.e., parent–child interactions, peer relations, adolescent friendships, and community integration) from infancy through to adolescence. Where research evidence is lacking, we identified potential research opportunities. We conclude with a discussion of the significance of considering risk and protective factors, multiple systems of influence, and the primacy of social development in future research with persons with DS.
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2. The Case for Social Competence Research on DS An existing impressive literature on the cognitive consequences of DS includes a detailed analysis of the specific deficits found in working memory and expressive language, and the propensity of early onset dementia in affected individuals ( Jarrold, Baddeley, & Phillips, 2002; Oliver & Holland, 1986; Tager-Flusberg, 1999). However, relatively little attention has been paid to how the cognitive sequelae of DS may affect social cognition and, more generally, social adaptation. This oversight is perplexing given the historical as well as contemporary views of cognitive development as goal oriented and socially embedded (Carpendale & Lewis, 2004; Carpendale & Muller, 2003; Piaget, 1929, 2000; Sameroff, 1990). Moreover, current trends in research on social neuroscience suggest that emotions and social factors may directly affect the way we attend to and process information and ultimately, our cognitions (Phelps, 2005). The implication for persons with DS is that atypical cognitive development will likely have repercussions on social and emotional development and vice versa. Consistent with this hypothesis, the preliminary evidence suggests that emotion processes and social-cognitive abilities are impaired among persons with DS and worthy of study on their own right (Abbeduto & Murphy, 2004; Abbeduto et al., 2006; Williams, Wishart, Pitcairn, & Willis, 2005). Considering the reciprocal influence between cognitive and social development among persons with DS is promising because it highlights that their development is not simply constrained by the effects of their chromosomes but also influenced by social and environmental factors. Cognitive development in DS is best considered within a goal-oriented context in which ‘‘cognitive tools’’ are shaped by, as well as serve, social goals for these individuals. Social competence is a construct that readily captures the reciprocal relation between the individual’s ‘‘tools’’ for adaptation (i.e., cognitive, emotion, and social processes) and the social contexts within which these must be applied. Within this framework, social competence is pertinent to understanding developmental adaptation throughout the lifespan and is particularly relevant in the lives of persons with DS who must strive for social inclusion and participation.
3. Defining the Construct of Social Competence 3.1. Cognitive influences Social competence is a construct that captures the dynamic relation between cognitive and social factors as they relate to adaptive development. Figure 3.1 depicts a hypothetical model of social competence in which
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Context factors: setting, people, mood etc... Socialcognitive processes Referencing
Gaze following
Pointing (production and following)
Emotion regulation
Emotion recognition
Perspective taking
Pragmatic language
Non-verbal comm.
Problem solving
Basic tools Memory
Arousal
Attention
Motivation
Sensation and Perception
Figure 3.1 A hypothetical model of social competence.
the construct of social competence is conceptualized as incorporating characteristics of individuals and their environments whereby these two sources of influence are transactional (Guralnick, 1996; Rose-Krasnor, 1997; Sameroff, Seifer, & Bartko, 1997; Wyman, Sandler, Wolchik, & Nelson, 2000). Within this framework, social competence involves the active and skillful coordination of multiple processes and resources available to the child. Basic sensory/perceptual and cognitive abilities (i.e., attention, memory, and motivation) are fundamental to the development of higher-order social-cognitive processes. Emotion recognition, sharing attention about an object, and understanding that others’ thoughts and feelings are different from one’s own are only a few of the higher-level social abilities involved in the development of social competence. Each of these abilities is necessary and builds the foundation for social competence. However, these abilities are not sufficient for socially competent behavior to emerge. A child must be able to coordinate his or her social-cognitive abilities along with available contextual resources to meet developmental goals in an adaptive way. Higher-order coordination of social abilities is a critical component of social competence because it permits children to appropriately match their social goals with the demands of the social context (Bost, Vaughn, Washington, Cielinski, & Bradbard, 1998; Guralnick, 1993, 2005). Accordingly, social competence entails the development of appropriate strategic processes (i.e., techniques) and resources to tackle the social demands of a particular task in a particular context. Social learning through mediation and scaffolding experiences will likely influence the development of the strategies or ‘‘techniques’’ that are particularly useful or meaningful within a specific sociocultural context. Thus, the beliefs and practices of parents and other relevant social mediators (e.g., teachers) will play a significant role in shaping social competence. Social competence is both a developmental phenomenon that can be measured over the course of a child’s development (i.e., ontogenesis) as well as a characteristic of a particular social encounter where the time scale is in the order of seconds/minutes (i.e., microgenesis). Thus,
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continuities and discontinuities in the development of social competence are expected as children are better able to coordinate abilities and take advantage of resources with increasing age but may be less competent at certain developmental stages or in specific social contexts.
3.2. Social–environmental influences According to the social–bioecological model of development, children are embedded within various sociocultural systems that interact to either support or hinder their development (Bronfenbrenner, 1977, 1979, 2000). These dynamic systems are conceptualized as different spheres of influence and include those that have a distal (i.e., indirect) effect and those that have a proximal (i.e., direct) effect on the individual (Cicchetti & Toth, 1997). Indirect influences are thought to emanate from macrosystems or globalpolitical contexts, mesosystems, which encompass the patterns, beliefs, and values of the culture in which the child exists, and the exosystems which comprise the various formal and informal social structures in the child’s environment, including the neighborhood, schools, and local government policies on education and health (Bronfenbrenner, 1977, 1979; Cicchetti & Toth). Direct influences include the children’s interactions with significant persons or events in their lives (e.g., sensory and perceptual input, parenting customs, sibling and peer relations, and teaching practices). Risk and protective factors may be present throughout the course of development in each of the systems and may operate through distal and/or proximal effects to influence the child’s development in adaptive or maladaptive ways (Bronfenbrenner & Ceci, 1994). For example, in infancy, social competence may be evident within the parent–child relationship as consistency in engaging with, and responding to the other establishes a secure and stable attachment that is integral to the infant’s very survival. Later in development as the child is increasingly able to control her or his own behavior and choose environments, social competence appears to transform into something more akin to a personal characteristic of the child (Bronfenbrenner, 1999; Sroufe & Jacobvitz, 1989). However, variability in the availability of social resources and in the quality of the parent–child relationship jointly influence a child’s ability to generate and coordinate flexible, adaptive responses to demands and capitalize on social opportunities in the environment (Waters & Sroufe, 1983). Over both ontogenic and microgenic time, key aspects of social exchanges are actively assimilated and accommodated by the child in order to achieve greater flexibility and compatibility with regard to matching social-cognitive strategies with contextual demands in subsequent interactions (Piaget, 2000). The benefits of fine tuning social strategies with social expectations is
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the achievement of more differentiated and self-directed social goals such as parent–child interactions, peer relations, intimate friendships, and community integration.
4. Status of Evidence on Social Competence in DS The review of research studies is organized around key developmental tasks that are considered to be behavioral indices of social competence. Figure 3.2 depicts four developmental tasks that will be the focus of the present review; each was selected to highlight different periods in development—those of infancy, middle childhood, and adolescence. In infancy, the quality of the parent–child interaction may be a particularly sensitive index of social competence as the interrelations between infant cues and parent sensitivity to the infant’s cues improves the odds of survival as well as the social–emotional development of the infant. Peer interactions may be especially salient in middle childhood whereas in adolescence intimate relationships and community integration are paramount. Within each task, the relevant research on social-cognitive and emotion processes in children with DS is discussed. The goal is to identify research in DS that is relevant to understanding social competence in these individuals, identify
Social competence Community integration, work and recreation Indicators of social competence
Intimate friendships Peer relationships, group play and friendships
Parent-child interactions (dyadic and triadic)
Increasing competence required
D e v e l o p m e n t
Figure 3.2 Behavioral indicators of social competence at different periods of development.
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potential gaps in the research literature, and suggest future directions for research in the area.
4.1. Infancy and the preschool years: Dyadic and triadic interactions Compared to other newborn animals, human infants could be described as ‘‘premature’’ since they rely almost exclusively on their caregivers for sustenance and nurturance. The implication is that infants’ survival and ultimately their social development are intricately linked to protective mechanisms that are inherent in the parent–child caregiving relationship (Barber, 2000). Thus, a healthy parent–child attachment increases the likelihood of behaviors that promote proximity between the dyad. Children learn early in life to use strategies, such as crying, smiling, grasping, or calling in order to keep the parent close by and ensure their survival and security. Physical closeness between the dyad increases the likelihood that parents will be aware of and respond to cues of distress and hunger as well as social bids from their child (Bowlby, 1969). The caretaking practices of the Kung San in Africa illustrate the effectiveness of physical proximity on parental responsiveness. The Kung San mothers constantly carry their infants and are able to respond to every distress cue the baby makes within 10 s (Barr, Konner, Bakeman, & Adamson, 1991). Children who have their basic needs met have a secure base (the parent–child relationship) from which to explore their environment and remain confident that their needs and social bids will not be ignored or misinterpreted (Ainsworth, 1973; Bowlby, 1969). Immediacy and compatibility of parental response may be particularly important to at-risk infants (Barr et al., 1991). Secure infants are engaged with their caregivers, are upset by a separation from their caregivers, but are easily consoled upon reunion. The essence of secure attachment behavior is thought to occur when a balance is struck between an infant moving toward the world and toward the caregiver during times of distress (Bowlby, 1973). The caregiver is responsible for responding to the infant’s cues, alleviating the infant’s distress, and providing socio-emotional and cognitive growth while the child is similarly active and responsible for providing clear cues and responses to the caregiver’s bids. This formative and formidable dyadic relationship creates a solid foundation for all future social relationships (Van Hooste & Maes, 2003). If either the child or the parent lacks the ability to engage with or respond to the other adequately, the quality of the relationship may deteriorate. Alternatively, compensatory strategies may be employed by either the child or the parent to establish adequate reciprocity and emotional nurturance. Thus, in infancy, social competence may be defined in terms of the quality of the parent–child relationship.
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4.1.1. Risk and protective factors associated with DS Compared to typically developing (TD) infants, those affected by DS develop at a slower rate, show uneven development across domains, have motor challenges, and experience more frequent hospitalizations for health concerns (Cicchetti & Ganiban, 1990; Cooley & Graham, 1991; Dunst, 1998). Specifically, these infants are challenged by impairments in motor control, information processing, language acquisition, emotion recognition, and affect regulation (Kasari, Freeman, & Hughes, 2001; Knieps, Walden, & Baxter, 1994; Moore, Oates, Hobson, & Goodwin, 2002; Wishart & Pitcairn, 2000). Any and all of these risk factors may interfere with the infant’s ability to use the parent–child relationship to meet basic needs and desires. Despite these problems, the parent–child relationship may be buffered by several protective factors. For example, infants with DS look at faces and may be socially engaging due to their attractive physical attributes and interest in people (Carr, 1994; Fidler, 2003; Hornby, 1995; Kasari, Freeman, Mundy, & Sigman, 1995). Certain aspects of social–emotional communication may be intact among infants with DS despite cognitive impairments (Kasari et al.). As compared to children with other types of developmental disorders, children with DS have fewer externalizing behaviors that might alienate or unduly stress their parents (Kasari & Hodapp, 1996). Parents of children with DS achieve scores on measures of parental stress similar to those of parents of TD children, and significantly lower than those of parents of children with autism or other undiagnosed etiologies of mental retardation (Kasari & Sigman, 1997; Seltzer, Krauss, & Tsunematsu, 1993). The disability of DS is visible, not heritable and widely recognized relative to other developmental disabilities. Many families of children with DS receive support from their extended family members and wider community and report being cohesive and harmonious (Kasari & Hodapp). 4.1.2. Parent–child interactions a. Dyadic interactions. The parent–child interaction is the primary social learning context for infants. A variety of emotion and social-cognitive processes, such as emotion regulation and recognition, referencing, gaze following, pragmatic language, and nonverbal communication are first evident in the parent–child interaction. Between the second and third month of life, there are significant developments in behavioral synchrony, turn taking, and reciprocity between the parent and the infant, precursors to a healthy attachment (Ainsworth, 1973; Fogel, 1977; Schaffer, 1977; Schore, 1994). However, infants with DS show less predictability, clarity, and frequency in social cueing and consequently, their parents are more likely to misinterpret, overinterpret, and/or occasionally miss cues. For example, infants with DS displayed dampened and fewer smiles, less eye contact, and less excited waving of their arms and legs, signs that may
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indicate a decreased intensity of emotional expressiveness toward the parent (Cicchetti & Sroufe, 1978; Emde, Katz, & Thorpe, 1978). At 12–19 months, children with DS showed diminished emotionality and separation distress as compared to their CA-matched peers (Thompson, Cicchetti, Lamb, & Malkin, 1985). In one study, seven-month-old infants with DS were described as more ‘‘difficult to read’’ than TD infants of comparable chronological age (Hyche, Bakeman, & Adamson, 1992). In addition to diminished social-communicative behaviors with their mothers, infants with DS show fewer approach behaviors, less persistence, lower thresholds for sensory stimulation, and more passivity during play (Bridges & Cicchetti, 1982; Linn, Goodman, & Lender, 2000). Difficulty in providing or responding to cues within the dyadic interaction will affect the development of social-cognitive processes and may affect the synchrony or compatibility in the interaction. Under these conditions, parents may focus their attention to structuring, scaffolding, and controlling the interaction. For example, mothers of 17-44 month-old children with DS may exert more control and direction during naturalistic play than mothers of same-aged TD children (Cielinski, Vaughn, Seifer, & Contreras, 1995; Landry & Chapieski, 1990; Mahoney, Fors, & Wood, 1990; Mahoney & Robenalt, 1986; Pino, 2000). The increased structure and guidance improves functional use of objects (Maurer & Sherrod, 1987), compliance with requests (Landry, Garner, Pirie, & Swank, 1994), and activity during play (Mahoney, 1988). Although beneficial for cognitive growth fostering (Crawley & Spiker, 1983), a focus on teaching and managing the parent–child interaction may result in a trade-off on socio-emotional growth (Ganiban, Barnett, & Cicchetti, 2000). For example, infants with DS show less intense and visible distress upon separation from their parent and brief recoveries following the return of their parent, and do not seek to maintain contact and require little to no comforting (Thompson et al., 1985; Vaughn et al., 1994). The interaction pattern between parents and children with DS during the Strange Situation Task could not be classified within the traditional attachment style framework (Vaughn et al.). Although disruptions in dyadic interactions and attachment are not evident in all parents of and children with DS (Iarocci, Virji-Babul, & Reebye, 2006), there is evidence to suggest that certain parent–infant dyads may benefit from early intervention designed to foster a balanced style that incorporates high responsiveness and scaffolding as well as supportive praise in order to meet both the cognitive and the emotional needs of infants with DS (Bornstein & Tamis-LeMonda, 1989; Spiker, Boyce, & Boyce, 2002; Vaughn, Contreras, & Seifer, 1994). A balanced approach designed to meet both the cognitive and the emotional needs of infants with DS may prevent early social-cognitive and emotion processing difficulties. For example, toddlers with DS looked
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at their parents less frequently and for a shorter duration and exhibited a different pattern of social referencing than did mental age (MA)-matched toddlers without DS (Knieps et al., 1994). Less reliable and effective referencing behaviors may indicate that toddlers with DS are failing to attend to some of the crucial information needed to understand and regulate emotions. For example, Williams et al. (2005) found that a group of children with DS (mean MA of 4 years) performed significantly poorer on emotion recognition tasks than both MA-matched TD children and children with nonspecific intellectual disabilities (ID). In addition, preverbal communication such as gaze monitoring that involves subtle changes in tracking and sharing attention with the caregiver may be qualitatively different than those in TD children (Fischer, 1988). For example, the onset, use, and subsequent development of eye gazing may differ in important ways (Berger & Cunningham, 1981). Children with DS appear to use eye gaze predominantly for ‘‘game’’ or ‘‘personal’’ purposes whereas TD children use their eye gaze predominantly for ‘‘referential’’ information to refer to another person or object ( Jones, 1980). More research is needed to explore whether children with DS are lacking experience with eye gazing for labeling emotions and objects and, if so, how this might affect their emotion and social understanding. b. Triadic interactions. Dyadic interactions in which the child and a communicative partner share attention in face-to-face interactions are the precursors to later sharing of attention toward inanimate objects or other significant adults and peers (Carpendale & Lewis, 2004). At this stage, the child’s face-to-face interactions with parents decrease as more time is devoted to attending to objects. The coordination of attention between objects and parent (or other significant adult) is an important step in a child’s learning awareness of, and interest in, significant persons or events. Accordingly, these joint attention episodes provide opportunities for children to learn to point, make requests, direct others’ attention, follow others’ gaze or point (usually their parent’s) to guide their interpretations of an ambiguous event (Klinnert, Campos, Sorce, Emde, & Svejda, 1983; Walden & Ogan, 1988) and make connections between an object and its verbal label (Carpenter, Nagell, & Tomasello, 1998). This stage of development marks the beginning of a gradual process of differentiation between the self and other that culminates in an understanding of others’ thoughts and feelings as different from one’s own (Carpendale & Lewis). In contrast to TD children, children with DS may continue to fixate on an adult’s emotionally expressive face rather than shifting attention between the adult and a salient play object (Kasari, Sigman, Mundy, & Yirmiya, 1990; Kasari et al., 1995; Ruskin, Kasari, Mundy, & Sigman, 1994). The sustained attention to emotional faces may suggest to the parent that the child is similarly engaged and motivated to interact, yet prolonged attention to the caregiver’s face may indicate difficulties with processing faces and has been associated with
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language delays in children with DS (Sigman & Ruskin, 1999). Even though these infants look at their mothers for longer amounts of time as compared to TD children of the same MA and language ability (Kasari et al., 1995), this behavior does not bootstrap development to more sophisticated sharing of attention to an object. Instead, these children show fewer social referencing looks to their mothers in ambiguous situations (Kasari et al., 1995) and make fewer attempts to direct their mother’s attention across social situations (Fischer, 1987; Landry et al., 1994). Delays in verbal and nonverbal communication and discrepancies between receptive and expressive language among children with DS may further impact triadic interactions. Fidler and colleagues found that toddlers with DS showed fewer nonverbal, instrumental requests than did TD and DD toddlers matched on MA and that these requests were significantly related to their problem-solving abilities (Fidler, Philofsky, Hepburn & Rogers 2005). Verbal language difficulties in toddlers with DS may have the added adverse effect of reducing parents’ use of inner state terms such as desires, beliefs, and feelings that promote the child’s understanding of affective and mental states in the self and other (Dunn, Brown, & Beardsall, 1991; Meins et al., 2002; Tingley, Gleason, & Hooshyar, 1994) as well as fostering attachment security within the dyad (Meins, Fernyhough, Fradley, & Tuckey, 2001; Mcquaid, Bigelow, McLaughlin, & MacLean, in press). Thus, the child’s communication delays and lower parental expectation with regard to language ability are likely to jointly constrain the development of triadic interactions in young children with DS (Iarocci, McLaughlin, Virji-Babul, & Reebye, 2005). 4.1.3. Systemic risk and protective factors in infancy and preschool years The quality of dyadic and triadic interactions may vary as a function of family and community resources and supports. During the early developmental years, the family system and parent–infant dyad may be more vulnerable to stressors as it accommodates a new member and renegotiations are necessary in the couple and parent–sibling relationships (Carter & McGoldrick, 1999). The parental subsystem must also accomplish a variety of tasks simultaneously; making sense of a host of medical and other diagnostic information on DS, procuring specialized professionals and services for their child’s special needs and the resources to finance them (Guralnick, 2000; Minnes, 1998). It is also a time when parents may experience negative attitudes from health professionals and others in their social networks, particularly with regard to expectations about their child’s future (Virji-Babul, Eichman, & Duffield, 2004). Although social services and early intervention programs are generally accessible to children with DS and their parents, they may not be specialized or integrative. For example, infant development programs are designed to meet the needs of families coping with a variety of developmental disabilities
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and thus, are not specific to children with DS (Guralnick, 2000). They offer a variety of specialized professionals (e.g., speech and language pathologists, occupational and physical therapists) who focus on treating specific domains of function such as speech or motor development while teaching parents to adopt highly structured parenting techniques that focus on stimulating cognitive development (e.g., Office of the Provincial Advisor Infant Development Programs of BC, http://www.idpofbc.ca/). An alternate specialized early intervention model that considers the reciprocal nature of the child with DS and his family’s well-being and incorporates social competence goals that link skills from across the various domains of function may be more compatible with the goals of parents and supportive to the needs of families. Such a program would target a variety of proximal and distal protective factors and the systems that support the quality of parent–child interactions and family well-being (Iarocci et al., 2006).
4.2. Middle childhood: Peer interactions, group play, and friendships During the school years, peer relationships play an increasingly prominent role in a child’s social development. In TD children between the ages of 3 and 6 years, there is a marked decrease in time spent in direct contact with caregivers and a concurrent increase in time spent with peers (Larson & Verma, 1999; Lewis, Feiring, & Brooks-Gunn, 1988). This trend continues throughout middle childhood as increased availability of social opportunities is coupled with social-cognitive maturation and increased independence and social interest. Relationships with peers are qualitatively different from those with adults and other caregivers. Children are less likely to make concessions during interactions; thus each partner in the relationship carries equal responsibility for the outcome of the interaction (Hall & McGregor, 2000). Peer relations during unstructured exchanges on the playground, as well as structured interactions in the classroom setting, provide a rich environment for learning fundamental tools for social interaction (Guralnick, 1990; Hartup, 1996). Children learn to modulate aggressive impulses, recognize and share emotions, communicate effectively, lead an activity, and resolve moral issues (Capps, Kasari, Yirmiya, & Sigman, 1993; Damon & Killen, 1982; Guralnick, 1995; Hall & McGregor, 2000; Sigman & Ruskin, 1999). Positive peer relations are predictive of adult mental health and, thus, may also guard against psychopathology in children (Nelson & Dishion, 2004; Serafica, 1990). Thus, the benefits of peer relationships during middle childhood extend beyond cognitive growth and include prosocial and self-development (Freeman & Kasari, 2002).
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4.2.1. Peer interactions Children with DS tend to seek out social interaction and thus appear to have a high level of social motivation or interest (Kasari & Freeman, 2001). They have been described as highly sociable with peers, well behaved in social situations, and active in joining a peer group (Rosner, Hodapp, Fidler, Sagun, & Dykens, 2004). Observations that some children with DS achieve socially related goals (Hodapp, 1996) or charm their way out of difficult tasks (Pitcairn & Wishart, 1994) have led some researchers to question whether sociability and friendliness is a syndrome-specific personality trait among people with DS (Kasari & Hodapp, 1996; Kasari et al., 1995). However, there is limited evidence to support this hypothesis as most studies are based on parent reports of social behavior or peer ratings of social attractiveness rather than observations of sociability or peer-related social competence among children with DS (Capps et al., 1993; Hall & McGregor, 2000; Kasari et al., 1990; Landry & Chapieski, 1990; Sigman & Ruskin, 1999). Direct observations of social behavior among children with DS reveal that these children show an absence of problematic or disruptive behaviors and diminished activity in the classroom and in group play (Guralnick, 1989; Sinson & Wetherick, 1981; Terry-Gage, 1999). a. Group Play. The majority of peer interactions in middle childhood involve group play, a behavior that promotes cognitive growth, creativity, and understanding of social rules (Guralnick, 1995). Children with DS engage in group play in a limited way (Sinson & Wetherick, 1981) and may experience social isolation at school (Sigman & Ruskin, 1999). When they are playing, children with DS do not appear to derive the same benefits as their TD peers (i.e., they have difficulty learning from social interactions). Specifically, these children have difficulty transferring supported goaldirected play behavior to independent play (Landry, Miller-Loncar, & Swank, 1998). Some researchers have suggested that the difficulty with group play among children with DS may be due to a lack of preference for social over nonsocial play (Sigman & Ruskin). Alternatively, deficits in auditory working memory in children with DS (especially when related to recall of social scripts) may limit play (Bray, Fletcher, & Turner, 1997) contribute to inconsistent play behavior and interfere with peer interactions (Guralnick, 2000). Gaining entry into a group at play requires the ability to make bids for social interaction. Children with DS may not make sufficient bids (Guralnick, 2002) and require scaffolding from adults in order to effectively entice another child or group of children to play with them. Lack of social initiations may be a key factor that hinders the development of other aspects of social competence among children with DS (Sigman & Ruskin, 1999). The ability to initiate social bids may initially be taught through parent–child interactions
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as children who are more likely to initiate social interaction with adults, are also more likely to initiate social interaction with peers (Sigman & Ruskin). Accepting social bids from others may also be challenging for children with DS and are considerably less receptive to the social bids of others as compared to their TD peers matched on MA (Sigman & Ruskin, 1999). Schlottmann and Anderson (1975) found that children with DS were more likely than MA-matched children with DD to reject another child’s bid for play by physically pushing the other child or walking away. After numerous advances proved unsuccessful, the TD children gave up. Once social contact is initiated, however, children with DS appear to maintain the interaction (Sigman & Ruskin). Requesting items and negotiating with other children about desired toys or objects in a nonconfrontational fashion are challenging skills for children with DS (Guralnick, 1995). Requesting and negotiating are most critical when conflict arises in play and must be resolved in a manner that is judged fair by both parties. Parents often describe their children with DS as less persistent than MA-matched TD children, a quality that may hinder the ability to effectively request objects or negotiate with playmates (Kasari & Freeman, 2001; Pitcairn & Wishart, 1994; Spiker et al., 2002; Wishart, 1996). Mundy and colleagues found that neither cognitive nor language delays explained the diminished verbal and nonverbal requesting (Mundy, Sigman, Kasari, & Yirmiya, 1988). However, expressive language skills may influence the ability of children with DS to negotiate during conflicts (Guralnick, Neville, Connor, & Hammond, 2003). Alternatively, good nonverbal communication and use of gestures may be adequate to model from socially appropriate peers (Sarimski, 1982) and effectively communicate with peers (Franco & Wishart, 1995). b. Friendships. Friendships represent the apex of peer-related social competence and are distinguished from peer interactions with regard to their increased reciprocity, stability over time, and changes across development (for a review, see Kasari & Bauminger, 1998). Friendships are uniquely characterized by warmth and associated with heightened responsiveness and mutuality, higher levels of play, and increased positive affect (Freeman & Kasari, 2002). True friendships are reciprocal in nature (each member independently identifies the other as a friend) in contrast with unilateral friendships (one-sided nomination). Reciprocal as opposed to unilateral friendships are associated with significant developmental gains (Freeman & Kasari). TD children tend to select friends that are similar to themselves in age, gender, and developmental level and those who share common interests, abilities, and experiences (Farmer & Farmer, 1996; Rubin, Lynch, Coplan, & Rose-Krasnor, 1994). According to parent reports, children with DS prefer younger TD friends (Sloper, Turner, Knussen, & Cunningham, 1990; Strain, 1984).
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A majority of children with DS (66–81%) are reported to have friendships. However, friends are likely to be relatives (Carr, 1994) or are less likely to be children that they play with outside of school (Byrne, 1988). In one study wherein children with DS were asked to bring a friend to a play session, 1/3 of children with DS brought a friend who was unilateral rather than reciprocal in nature (Freeman & Kasari, 2002). Although the majority of children with DS can often identify at least one peer ‘‘friend,’’ the quality of friendships differs from those of MA-matched TD children (Freeman & Kasari, 2002) and thus, may contribute less to potential developmental gains (Guralnick, 1995). Freeman and Kasari reported that the peers who were nominated as friends by children with DS were often identified as ‘‘acquaintances’’ by their parents. Thus, simply reporting that children with DS have friendships may not be sufficiently informative of the exact nature of those relationships. There is a need to examine whether children with DS derive the same benefits (e.g., emotional support, emergent sense of self ) from reciprocal friendships as their TD peers. The preliminary evidence suggests that children with DS may have difficulty making use of friends as resources or positively influencing the behavior of other children in a goal-directed fashion (Guralnick). Difficulties with developing reciprocal friendships may be due to specific emotion and social-cognitive factors. For example, children with DS do not readily recognize emotions such as fear, anger, and surprise and, at times, may confuse positive emotions with negative ones (Kasari et al., 2001; Williams et al., 2005; Wishart & Pitcairn, 2000). The ability to express affect may also be compromised as children with DS show similar incidents of smiling but briefer and less salient smiles than those of TD children matched on MA (Kasari et al., 1990). The difficulties with recognizing and expressing emotions may become evident during interactions when children must match the other’s affect (Guralnick, 2002; Knieps et al., 1994). In addition to understanding others’ emotions, children with DS may have limited ability to understand that others have feelings and thoughts that are different from their own (Abbeduto et al., 2001; Binnie & Williams, 2002). A deficit in theory of mind may impede their ability to predict what other children might be feeling or what they are thinking during interactions. Whereas TD children spend more time with their peers once they enter school and are making greater gains in social competence, children with DS rely on contact with adult caregivers and teachers during the primary school years (Lewis et al., 1988), and are less likely to initiate social interactions with peers. Further, when they engage in social interaction they do so in a limited way and stand to benefit less from the experience. The limited amount and quality of social interaction with peers coupled with less contact with their caregivers may leave children with DS at greater risk for social isolation in the school context (Sinson & Wetherick, 1986).
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4.2.2. Systemic risk and protective factors in middle childhood Two decades ago, the atypical appearance of children with DS was listed as an impediment to social inclusion (Richardson, Koller, & Katz, 1985). However, appearance is no longer associated with amount of social contact in children with DS (Sloper et al., 1990). Similarly, inappropriate behavior in the classroom or on the playground, was predictive of social exclusion of children with DS in earlier research findings (Crawley & Chan, 1982; Guralnick & Weinhouse, 1984). However, more recent studies indicate that, unlike TD classmates, behavioral problems in children with DS are not associated with lower peer acceptance ratings (Laws, Taylor, Bennie, & Buckley, 1996). Accordingly, children with DS receive average ratings of acceptance by their TD peers (Laws et al.). These findings suggest that TD children are aware of differences in their peers with DS and make concessions for unusual or disruptive behavior. This change in behavior toward peers with DS may reflect attitudinal changes at a societal level. During the school years, the educational system and associated policies are particularly powerful at impacting the development of children, especially for children with DS whose education is more dependent on the system’s resources and overall functioning (e.g., special education policies and practices, teaching expertise, and social integration initiatives). Including children with DS in mainstream classrooms in the public school system is not only desirable for most parents and children but also reflects a fundamental social value of acceptance of diversity and inclusion for all children (Rosenthal, 2001). However, research evidence suggests that simply placing children in mainstream contexts does not sufficiently benefit children with/without disabilities (Guralnick, 1996). Proponents of special education cite research that in segregated settings, children with DS display more appropriate peer-related social interaction and receive more positive guidance from adults (Terry-Gage, 1999) and that more generally children with DD in special education classes are better at playing with peers than those in mainstreamed classrooms (Freeman & Kasari, 2002). However, the variability in play and social competence may be related to the characteristics of the system (teacher scaffolding vs unstructured play) rather than the setting (special education vs mainstream) (Sigman & Ruskin, 1999). When appropriate teaching strategies are in place in the mainstream setting, children with DS are likely to seek out interactions with their TD peers (Guralnick, 1996; Rynders, Johnson, Johnson, & Schmidt, 1980) and, can be taught effectively to model their social behavior on that of their TD peers (Goldstein & Strain, 1988). The research evidence suggests that peer assistance programs (i.e., where children with DS are matched with TD peers) increase the number of social interactions and friendships experienced by children with DS (Schaefer & Armentrout, 2002). They may also have a
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positive impact upon cognitive skills such as pragmatic language use (Knox, 1983). Mentoring and tutoring by peers often teaches leadership and compassion in helpers and thus, may improve the social development of TD children as well as that of children with DS (Beveridge, 1996; Rynders & Low, 2001; Sinson & Wetherick, 1981). Research is needed to explore the potential risk and protective factors that operate in various social systems that impact the social lives of children with DS (e.g., schools, daycare facilities, and community leisure centers). Family factors, such as high levels of cohesion, harmony, expressiveness, and child-centered approaches influence whether neighborhood peers accept children with DS (Mink, Nihira, & Meyers, 1983). Although families often influence the time spent in organized age-appropriate activities with peers, parental arranging of play is not associated with increased social competence (Guralnick et al., 2003). However, large social networks mainly consisting of family members may serve as a protective factor against social isolation among children with DS (Lewis et al., 1988).
4.3. Adolescence: Intimate relationships and social inclusion The transition to adolescence is marked by an unprecedented convergence of biological, cognitive, emotional, and social changes. Whereas the majority of youth are able to successfully navigate the waves of change, for some, navigating these developmental changes in the context of greater social demands that they are not prepared to tackle, can heighten the risk for maladaptation ( Jackson & Rodriguez-Tome, 1993). During this period, key behavioral indices of social competence include the development of more intimate peer relationships and increase in community involvement (e.g., participation in postsecondary education, employment, or leisure activities). The adolescent’s abilities to engage in intimate friendships and assume diverse social roles in the community require greater facility in higher-order social cognition. This period likely involves both an emergence of new skills (e.g., social problem solving and abstract reasoning), as well as further developments in existing social-cognitive processes such as perspective-taking (theory of mind), emotion processing, and pragmatic language abilities. Whereas gains in social competence enable individuals to better contend with social developmental tasks, the successful negotiation of these tasks, in turn, creates further opportunities needed for continued social learning and growth. Indeed, the heightened demands encountered during increasingly complex social interactions provide the impetus for young people to develop more advanced skills and behaviors (Collins & Repinski, 1994). For instance, close peer friendships permit the individual to learn observationally from more competent peers, practice and refine more sophisticated social skills, and receive important social feedback (Buhrmester, 1996; Goldstein & Morgan, 2002).
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The adolescent period is also marked by fundamental developmental changes that include experimentation with social rules and structures (Zimmerman, Ramirez, Washienko, Walter, & Dyer, 1998) and adoption or rejection of cultural norms in an effort to understand the self in relation to others (Borysenko, 1996). Thus, contextual factors are especially relevant during the transition to adolescence (Weisz, 1997). Moreover, the focus on social competence during this developmental transition period permits researchers to have a unique view of developmental reorganization and maladaptation from the standpoint of an established developmental history of childhood and the initiation into the new developmental challenges of adolescence. In contrast to earlier developmental periods, few studies have investigated social-cognitive and emotion processes in adolescents and young adults with DS. The majority of available research has been conducted at the ‘‘behavioral indices’’ level of analysis (i.e., investigations of intimate relationships and community involvement). Thus, the studies provide indirect evidence regarding the social competence of youth with DS and do not inform our understanding of the social processing strengths and weaknesses displayed by these individuals. The few studies that are available at this developmental period are consistent with the childhood literature findings and suggest that young people with DS continue to display difficulties across many key social-cognitive domains. Smith and Dodson (1996) investigated the production of facial affect in adults with DS and found that although adults with DS demonstrated relatively intact expression of positive affect in response to happy stimuli as compared to CA-matched TD peers, they displayed more ‘‘nonemotional’’ or ‘‘extraneous’’ facial movements. The authors suggested that such movements could interfere with others’ interpretations of their emotional and social responses. However, the lack of a developmentally matched comparison group limits the significance of these findings. In addition, deficits in pragmatic language (the use of language in social interaction) have been documented in young people with DS. When compared to MA-matched TD individuals, adolescents and young adults with DS demonstrated difficulty taking into account the informational needs of the listener and were less likely to provide ‘‘scaffolding’’ or speech references for listeners (Abbeduto & Murphy, 2004). Difficulties taking the listener’s perspective during conversations may also be related to deficits in theory of mind among adolescents and young adults with DS. For example, compared to MA-matched TD peers and those with fragile X syndrome, adolescents and young adults with DS have significant difficulty understanding that others are not privy to knowledge that they possess and therefore, may hold a false belief (Abbeduto et al., 2001; Yirmiya, Erel, Shaked, & Solomonica-Levi, 1998; Zelazo, Burack, Benedetto, & Frye, 1996).
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Taken together, these studies provide preliminary evidence of continuity in social-cognitive deficits among adolescents and young adults with DS. Further investigation is needed to clarify the precise nature of impairments in emotion processing, pragmatic language, and theory of mind as well as to determine their influence on socially inappropriate behaviors and interpersonal problems commonly reported among persons with DS (e.g., overly friendly approaches toward strangers; ‘‘hypersocial’’ or excessive displays of affection, such as hugging that are not appropriate to the situation) (Greenspan & Shoultz, 1981; McGuire & Chicoine, 2002; Waterhouse, 2002). Empirical studies are needed to explore additional domains of social cognition that are particularly relevant during this developmental period (e.g., social problem solving, inferencing, and regulating emotion). 4.3.1. Intimate relationships During adolescence and early adulthood, peer relationships typically assume increasing significance. The intimate relationships that emerge during this time, such as close friendships or dating relationships, tend to be less based on shared play activities and more typically characterized by a higher degree of intimacy and self-disclosure (i.e., sharing of personal thoughts and feelings), greater mutuality, and increased reciprocity (Buhrmester, 1996; Collins & Repinski, 1994; Kimmel & Weiner, 1985). Adolescents and young adults with DS generally report a desire for friendships (Bottroff et al., 2002). However, many experience significant difficulty making friends and instead spend much of their social life with their family (Bochner & Pieterse, 1996). In one study investigating friendship development in adolescents and young adults with DS, fifty-five percent of parents reported that their child had no ‘‘special friend’’ (Bottroff et al.). Dating also appears to be relatively uncommon among young people with DS (Carr, 1995). Given the importance of friendships in promoting the acquisition of more sophisticated social-cognitive skills, this apparent lack of friendships is particularly concerning. Among the youth with DS that do establish peer relationships, there is some question as to how intimate or ‘‘close’’ they truly are (Carr, 1995). For instance, anecdotal observations suggest that young people with DS may misinterpret helping relationships as real friendships ( Jobling, Moni, & Nolan, 2000). Jobling et al. hypothesized that a superficial understanding of the emotional aspects of relationships may impact the quality of friendships among young people with DS. Future research on the quality (e.g., levels of intimacy and emotional support) as opposed to quantity of peer relationships among individuals with DS would be more relevant to understanding how friendships promote the development of social competence (Hartup, 1996).
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4.3.2. Community involvement and social inclusion Adolescence and early adulthood is generally a time of increasing autonomy and involvement within the wider community. Integration in the community typically involves a transition from high school to postsecondary education, the work environment, and/or leisure settings. a. Postsecondary education. The opportunity to experience college or university life may be beneficial for individuals with DS, even if they do not fully participate in academic programs. For instance, in a qualitative case study, Hamill (2003) described the positive college experience of a young woman with DS. The author suggested that an emphasis on the social experience of college life, as opposed to academic achievement, may create many opportunities to foster social development in young people with DS. b. Employment. Participation in employment or volunteer opportunities also has the potential to foster social integration and social development in the lives of young people with DS. Recent estimates of employment rates for young people with DS vary considerably, ranging from extremely low [e.g., 0% (Thomson, Ward, & Wishart, 1995)] and 10% (Carr, 1995), to moderately high [e.g., 65% ( Jobling & Cuskelly, 2002)]. Of those employed, the majority continue to be involved in sheltered as opposed to competitive employment opportunities (Carr). In light of research suggesting that vocational success relies heavily upon social competence (Chadsey-Rusch, 1992; Greenspan & Shoultz, 1981; Mueller, 1988), future studies are needed to investigate whether specific impairments in social competence limit job success among young people with DS. c. Leisure. Recent findings suggest a decrease in the frequency and breadth of participation in active recreation occurring in the mid to late 20s among adults with DS (Brown, 1995). Surveys indicate that most young adults with DS engage primarily in passive or solitary activities (such as watching TV, going to a movie, or walking) as opposed to participating in sports activities, clubs, or other community organizations that would promote greater interpersonal interaction (Brown; Putnam, Pueschel, & Holman, 1988). 4.3.3. Systemic risk and protective factors in adolescence and early adulthood As in childhood, the continued development of social competence among adolescents and young adults with DS may be impeded or facilitated by systemic factors occurring at the level of the individual, family, peer, community, or service agency. Risk or protective factors may impact the development of specific social competence skills directly or indirectly (i.e., through their effect on social interaction and learning opportunities, such as relationships or community involvement).
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Young people with DS demonstrate significant personal strengths that may promote their social development. Some reports suggest that the high levels of social interest and enjoyment apparent among children with DS persist into adolescence and early adulthood (Carr, 1995). Indeed, young people with DS are frequently described as being socially engaging, cheerful, and friendly (Rosner et al., 2004). Furthermore, as compared to children with DS, adolescents demonstrate fewer maladaptive behaviors and externalizing problems, such as aggression, arguing, and disobedience, that could alienate others (Dykens, Shah, Sagun, Beck, & King, 2002). Further research is needed to determine whether factors such as low rates of negative behaviors, high social interest, and a pleasant interpersonal style promote the social inclusion and social development of young people with DS. Peer factors also have the potential to impact the social growth of young people with DS. Opportunities to develop close relationships with TD peers may be hampered by social stigma or stereotypes; a tendency for TD peers to take on a caregiver role; challenges in the pursuit of shared interests due to cognitive and social limitations; and/or a lack of proximity (Day & Harry, 1999). While normative peer interactions are typically based on notions of equity, and thus, may not naturally encourage the participation of adolescents with DS, the presence of individual peers to play ‘‘advocacy’’ and/or ‘‘facilitatory’’ roles may support their inclusion (Harry, Day, & Quist, 1998). A better understanding of the specific peer factors that may hinder or facilitate social development among adolescents with DS would contribute information about the contextual supports needed to scaffold social competence during this developmental period. At the level of the family system, more research is needed to examine the role of parent and family factors (e.g., presence of siblings, parenting strategies, parent beliefs about social development, parent expectations) in promoting or impeding socially competent behavior among young people with DS. For instance, overprotection by parents, whether deliberate or unintentional, may interfere with continued social development in young people with DS by limiting or highly regulating key social learning opportunities (McGuire & Chicoine, 2002; Waterhouse, 2002). Conversely, parenting styles that encourage greater responsibility and freedom (with appropriate limits) may be more adaptive in facilitating the social growth of certain adolescents with DS (Brown, 1995). Service agencies may promote social competence and social opportunities through the types of programs offered to adolescents and adults with DS. Programs directly supporting social skill development, in addition to the typical emphasis on adaptive functioning at this developmental stage, may prove most beneficial and effective. For instance, Soresi and Nota (2000) developed a social skills training program that has shown promise in modifying the quality and frequency of social behavior in DS. Similarly, Jobling and colleagues (2000) describe a program for young adults with DS designed to
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enhance their understanding of the emotional aspects involved in friendships and report encouraging preliminary findings. In addition to social skill interventions, an evaluation of the services designed to more effectively support the development of relationships, particularly peer friendships, is warranted (Emerson & McVilly, 2004). Greater attention should be paid to the ways in which organizations, whether educational, employment, or recreational in nature, are structured in order to facilitate the social inclusion of young people with DS. There is some evidence suggesting that ‘‘cooperative structuring’’ of activities promotes the inclusion and acceptance of individuals with DS within community leisure settings (Rynders & Low, 2001). For instance, Rynders and colleagues (1980) compared the effects of cooperative, competitive, and individualistic goal structuring during an 8-week recreational bowling program involving adolescents with DS and their TD peers. Their results demonstrated that greater interpersonal attraction and more positive interactions occurred in the cooperative condition. 4.3.4. Social inclusion and mental health Recent evidence suggests that there may be subtle changes in sociability among individuals with DS that occur during adolescence. Dykens and colleagues (2002) presented preliminary findings that indicated a shift toward increased withdrawal and decreased sociability during this period. Specifically, sixty-three percent of the adolescents included in their sample reported that they preferred to spend time alone. Changes in sociability may represent early phases in the cognitive and social decline common in individuals with DS (Thompson, 1999). However, they may also reflect the cumulative effects of ongoing social difficulties and limited social networks. Young people with DS may find themselves ill equipped to negotiate key social developmental tasks and progressively withdraw from the social world as it becomes increasingly complex. Research findings suggest that social difficulties and/or low social support place individuals at increased risk for developing mental health problems, and particularly internalizing disorders (Brown, Andrews, Harris, Adler, & Bridge, 1986; Brown & Harris, 1978; Coyne & Downey, 1991; Turner, 1999). Thus, in adolescents with DS, subtle increases in social withdrawal or isolation may heighten the risk for the later emergence of depressive disorders. There is evidence that the rates of depression increase as individuals with DS reach adolescence and adulthood (Rowitz & Jurkowski, 1995). Furthermore, individuals with DS appear to be 2–3 times more likely to develop depression than individuals with other developmental disabilities (Collacott, Cooper, & McGrother, 1992). The high prevalence of depression in young people with DS is a concerning statistic that warrants more extensive research on the relation between social impairments and increased social withdrawal in persons with DS.
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5. Conclusion The birth of a child with DS, much like other life cycle transitions, occurs within a context of stability and change. The child enters a family system that has an established developmental history yet must adapt to ever changing developmental circumstances such as the introduction of a new child, the initiation of the child’s formal schooling, increased autonomy and peer contact in adolescence, and launching the adolescent into adulthood (Carter & McGoldrick, 1999). The process of developmental reorganization, at any transitional period in the life cycle, involves both challenges to, and opportunities for, growth within the family system. Although children with DS and the families that care for them may be referred to as ‘‘at risk’’ due to the added challenges associated with the condition of DS, they may also be considered for the ways in which they successfully manage stressors and adjust to normative life cycle transitions as effectively as typical family systems do (Iarocci et al., 2006). The developmental course of children with DS is laden with potential risk and protective factors. Consequently, multiple pathways to adaptation or maladaptation are possible. For example, families that care for a child with DS do not have the benefit of their extended family’s wisdom on how to raise their ‘‘unique’’ child yet they may be less bound by social and cultural prescriptions on parenting. These families also often face the challenges of advocating for and acquiring resources for their parenting and child’s needs; however, this very deliberate engagement in the parenting process may lead to more mindful awareness and activity in child rearing. Similarly, the social inclusion of the child with DS is not a natural process but requires commitments and concerted efforts from families, their communities, and society. Ongoing family, community, and societal efforts to accommodate diversity and change within relative stability is what propels these systems toward more flexible and creative growth and adaptation. Accordingly, the field of mental retardation, in particular as it relates to the study and practice of rearing children with DS, needs to adapt to the changing landscape of knowledge about DS and create opportunities for continued growth. Remarkable medical advances in the past decade have largely eliminated the major medical conditions that previously threatened the survival of people with DS, and, as a result, adults with DS are living longer ( Janicki, Dalton, Henderson, & Davidson, 1999). Researchers, practitioners, parents, and policymakers may now shift their focus from the survival or simple existence of persons with DS to matters that address social inclusion and the quality of their existence.
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ACKNOWLEDGMENTS We thank the families and staff of the Down Syndrome Research Foundation for inspiriting this work. Grace Iarocci and Jessica McLaughlin’s work on this chapter was supported by a research grant from the British Columbia Human Early Learning Partnership (HELP) and a research grant from the Social Sciences and Humanities Research Council of Canada to Grace Iarocci. Jodi Yager and Adrienne Rombough were supported by a fellowship from the Autism Research Training Program ( jointly funded by CIHR, NAAR, and FRSQ).
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C H A P T E R
F O U R
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† Contents 1. Introduction 2. The Flynn Effect and MR Diagnosis 2.1. MR becomes a matter of life and death 2.2. A temporary expedient 2.3. The history of the bottom 2.27% 2.4. How many of our grandparents had MR? 2.5. The WISC subtests to the rescue 2.6. Did almost everyone once have MR? 3. Possible Solutions 3.1. Piagetian approach 3.2. Psychometric approach based on item response theory 4. Concluding Remarks 4.1. Temptation to be resisted 4.2. Necessary tasks 4.3. Remaining problems 4.4. ‘‘Bring the tires to me’’ 4.5. Quid faciendum est? Acknowledgments References
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Abstract Gains in IQ over time render test norms obsolete within a decade of the publication of an intelligence test. Obsolete norms inflate IQs and drain the pool of those eligible to be classified as having mental retardation (MR). As a result, many are missing the services they need and capital offenders are being
* {
Department of Political Studies, University of Otago, PO Box 56, Dunedin, New Zealand Department of Psychology, University of California at Davis, 265 Young Hall, Davis, CA 95616, USA
International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35004-0
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2008 Elsevier Inc. All rights reserved.
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executed who should qualify as mentally incompetent. The history of IQ gains and IQ criteria for MR pose deeper and more problematic questions: Can we salvage IQ tests as measures of intelligence; can we find an IQ criterion for MR that has external validity; can we find a mental test that measures moral culpability? All solutions involve an agonizing reappraisal of present practice.
1. Introduction The Flynn effect refers to the well-documented improvement in performance on tests of intelligence that takes place over decades (Flynn, 1984, 1987, 1998). This phenomenon of massive IQ gains over time has implications for all assessment, but this chapter focuses on the diagnosis of mental retardation (MR). With that in mind, we undertake the following: 1. A description of the havoc that obsolete IQ tests and their norms have on the current classification of people as having MR. 2. Particular attention is due to capital offenders on death row. From this discussion, it will emerge that an IQ criterion of MR is indispensable if justice is not to be fatally compromised. Therefore, a way of compensating for obsolete norms will be recommended. However, that solution assumes that we have a defensible IQ criterion of MR, specifically a criterion that reflects the impaired reasoning or judgment exhibited by persons with MR. 3. Pursuing the history of IQ and MR back to 1947, we show that clinical psychology does not have and never has had a defensible criterion in terms of external validity, such as one referring to levels of reasoning. 4. That history also poses a dilemma that must be solved if IQ tests are not to be discredited as measures of intelligence. Trends on the various Wechsler Intelligence Scales for Children (WISC) subtests will suggest a solution. 5. However, when we push IQ gains back to their origin, that is, to a time no later than 1900, the dilemma will reemerge. Piagetian concepts and techniques of modern test theory will shed light on performance on tests like Similarities and Raven’s and suggest workable solutions. 6. Our solution will indicate how the use of an IQ criterion of MR can be made defensible. But this cannot be done without tears.
2. The Flynn Effect and MR Diagnosis 2.1. MR becomes a matter of life and death The best evidence of massive American IQ gains comes from the everimproving performance by succeeding cohorts on the WISC and its successors. From the WISC (normed in 1947–1948), through the WISC-R (1972),
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through the WISC-III (1989), to the WISC-IV (2002), we can compare the performance of the normative samples (Flynn, 2006a, Table 1). Whenever the same group took both an older and a newer version of the test, they found it easier to exceed the norms set by the older standardization samples. A group with a mean IQ score that was only average when scored against the WISC-IV norms achieved a mean that was well above average when scored against the WISC-III norms; a group that was average on the WISC-III was above average on the WISC-R; and so forth. Clearly, as we go back into the past, the norms become weaker, which means that representative samples of American schoolchildren set lower and lower standards of performance. Conversely, as we go from past to present, American children attained higher standards of performance. The rate at which performance improved over the 55 years between 1947 and 2002 hardly varied. For example, a group only average on the 1972 norms (with a mean of 100) would score at about 107.50 on the 1947–1948 norms, for a rate of gain of 0.3 points per year (7.50 divided by 25 years ¼ 0.3). This means that the IQ an individual receives is like a lottery, with the outcome dependent on when he or she was tested, what test was administered, and in what year that test was normed. Assume a group of children born in 1990 who were exactly normal, that is, representative of the U.S. population, and therefore deserved an IQ of 100. In 1996, at age 6, they take the WISC-R (the norms for which were by then 24 years obsolescent) and get a mean IQ of 107 (24 0.3 ¼ 7.2), a score fully 7 points more than they merit. It would be unusual not to use the WISC-III that had been published in 1991, but not unheard of. School psychologists and the administrations for which they work sometimes continue to use copies of outdated IQ test protocols that were in stock before buying new tests. In 2000, the children, now aged 10, take the WISC-III. Its norms are by now 11 years obsolescent, so they get a mean score of 103 (11 0.3 ¼ 3.3). Finally, in 2003, at age 13, they take the then-new WISC-IV whose norms are only one year obsolescent and achieve a mean score of 100.3 (1 0.3 ¼ 0.3). So, finally, they get a score fairly close to the one they deserved all along. However, schoolteachers and administrators are dismayed by the decline in their mean IQ and are trying to find what went wrong with the school environment. And yet, this ‘‘decline’’ is purely an artifact. It merely reflects the time that had passed between the year they took a given test and the year in which that test was normed. Those familiar with the mathematics of a normal curve will know that modest differences near the mean of a distribution do not have a great effect on the proportion of persons meeting or exceeding a cutoff point that is close to the mean. But, comparable score changes can make a substantial difference on the proportion of the population meeting or exceeding a cutoff point if that cutoff point is far below (or above) the mean. For example, take a population whose scores have a normal distribution with
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a mean of 100 and standard deviation (SD) of 15. By definition, 50% of the population will fall below 100 and 2.27% will fall below a score of 70. If 5 points (or 0.33 SD units) were added to each person’s score, the mean would now be 105 and the SD would remain at 15. The result would be that 37% of the population would now fall below 100 and 1% below 70. Note that the effect near the mean reduces those that fall below 100 by about one-fourth (37 50 ¼ 74%, so 26% of those who formerly had met the cutoff score of 50 no longer do so). But the percent below 70 and therefore eligible to be classified as mentally retarded has been reduced by more than one-half (0.99 2.27 ¼ 44%, so 56% of those who had formerly met the cutoff score of 70 no longer do so). Returning to our hypothetical class of children, in 1996 at age 6, taking the WISC-R inflated their IQs by over 7 points or 0.48 SD units. At that point, only 0.66% of them were eligible to be classified as having MR. By the time they were 13 in 2003, taking the WISC-IV inflated their IQs by only 0.3 points or 0.02 SD units and 2.17% were eligible to be classified as having MR. Fully 3.3 times as many were at risk even though their actual performance on IQ tests, that is, a performance that exactly matched that of their age cohort, had not altered at all. Flynn (2000) calculated a worst case scenario taking into account obsolescence of norms and the likelihood that gains may have been slightly greater at IQ levels near the cutoff score for diagnosing MR, plus the fact that the criterion of MR was altered by moving from norms based on white individuals only to norms based on representation by all racial and ethnic groups. He showed that between 1947 and 1999, the proportion of the population eligible to be classified as MR had fluctuated from 1 in 23 (4.35%) to 1/213 (0.47%), and this assumes that no one continued to use outdated protocols of a test whose successor had been published. As a description of the fate of those being assessed, ‘‘lottery’’ seems too weak a word. The above scenarios assume that IQ gains for those at low IQ levels are as robust as gains found for those who score near the mean. Flynn (2006b, Table 2) reviewed extant data and found that this was essentially true for all forms of the WISC. Two factors rendered comparable comparisons using WAIS data more complex. First, it is more difficult to obtain optimal standardization samples of adults because a representative sample is not sitting in classrooms awaiting you, as is the case with the WISC. Second, different scoring practices at low IQ levels have been employed on various forms of the WAIS (e.g., the minimum IQ a subject can get without any right answers has varied), and these scoring variations contribute to greater score volatility at low IQ levels. Bringing some order out of this chaos is now a matter of life and death. The U.S. Supreme Court in Furman v. Georgia (1972) held that the death penalty must be imposed with consistency and with due regard to the
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culpability of those who suffer its consequences. Thirty years later, in Atkins v. Virginia (2002), the Court held that the Eighth Amendment to the U.S. Constitution forbids the death penalty for those who suffer from MR. Subsequently, in Walker v. True (2005), the Fourth Circuit Court of Appeals held that, in applying this standard, the ‘‘Flynn effect’’ must be taken into account. What they meant by this was that if a capital offender’s IQ had been inflated by administering a test with obsolete norms, he should not be executed just because he had suffered from the bad luck of being given a test with out-of-date, rather than contemporary, norms. For example, the fact that someone had been given the WISC (and scored above 70) rather than the WISC-R (on which that very same person would have scored below 70) would clearly be relevant when determining whether the IQ score met criteria for a diagnosis of MR. Whether or not scores are adjusted to take obsolescence of norms into account can determine the fate of an offender. We will illustrate this by using an actual case altered only to update it so that the tests administered correspond to those given to current defendants. John Doe was convicted of murder and sentenced to death contingent on a determination of whether or not he was mentally retarded. He was born in 1984. At age 11 in 1995, Dr. Mary Smith (the school psychologist) gave him the WISC-R. This may seem odd given that the new (at that time) WISC-III had been published in 1991. Perhaps her school had limited funds and Dr. Smith needed to exhaust her supply of the protocols of the older version of the WISC before purchasing the new edition. Dr. Smith had been taught to assess adaptive functioning independently of IQ scores. However, she found it difficult to compartmentalize the two. Her report notes John’s poor performance in reading and arithmetic despite extra tutoring. But then, she rejects a diagnosis of MR on the basis of a WISC-R IQ score of 75. Today, we know that, thanks to 23 years of obsolescence of its norms, use of the WISC-R inflated Johnny’s score by 7 points and his score should have been lowered to 68, easily in the MR range. Johnny is likely to be executed simply because his school’s budget did not extend to purchasing the latest test. However, he might have had bad luck anyway. If tested at age 6 in 1990, there would have been no alternative to the WISC-R and his fate would have been the same. The consequences of misclassification due to obsolete norms extend beyond the death penalty. As Kanaya, Scullin, and Ceci (2003) pointed out, each year 2 million children are tested for special education, including MR services, and in a given school year over 600,000 actually receive MR services. Adults who are classified as having MR are eligible for social security disability benefits and are ineligible for military service. If those with inflated IQs, thanks to obsolete norms, are not classified as having MR, the government saves millions of dollars because it does not have to provide special services to these misclassified individuals. The other side of the coin
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is that the misclassified persons do not get the help they surely need. As for the military, the use of obsolete norms could lead the armed forces to enlist thousands of people who, at least in their opinion, lack the level of mental ability needed to make correct decisions on the battlefield. The losses in money and lives are potentially huge. Kanaya et al. (2003) confirmed that, when the WISC-R was replaced by the WISC-III, the scores of low-IQ children dropped by at least the amount predicted, a rate of 0.30 points per year of obsolescence. Because the norms of the latter test were set 17 years after those of the former, the predicted loss would be 5.10 IQ points, and Kanaya et al. found an average loss of 5.55 points (0.37 SDs). If IQ were the sole criterion of MR, and everyone had used the new WISC-III as soon as it became available, a score fluctuation of 0.37 SDs predicts that the number classified as MR would rise from less than 1% (0.89) in 1990 to almost 2% (1.97) in 1991; that is, there would be a doubling overnight of those who qualify for MR services. Kanaya et al. selected a large, economically and geographically diverse sample of students tested for special education. They found that school psychologists who first tested a child on the WISC-R and then retested using the WISC-III were twice as likely to submit a recommendation of MR, when compared to those who retested using the same test. However, Kanaya et al. (2003) also found that 88% of students were still being given the WISC-R in 1991, 41% in 1992, and that even in 1995, the old test was still in use. Where a single score existed, school psychologists showed a greater reluctance to trust the lower WISC-III IQ than the higher WISC-R IQ. Only half of students with an IQ score below 70 were actually recommended for a diagnosis of MR. Note that by 1996, the WISC-III was itself seven years obsolete and inflating IQs by 2.1 points. So, someone who retested a child on the WISC-III in 1996 and compared the result to a WISC-R score obtained in say 1989 (17 years of obsolescence equals 5.1 points) would notice a discrepancy of only 3 IQ points. A difference of 3 points is well within the margin of measurement error for the WISC and WISC-R. The discrepancy would neither reveal what was happening nor change what was happening: Between 1991 and 1995, many thousands of children did not receive a diagnosis of having MR simply because of the test they took. Scullin (2006) collected data from all 50 states plus the District of Columbia to trace trends concerning the percentage of students enrolled in MR programs. He found that a steady and general decline during the 1980s turned into an increase in the early 1990s in 43 states and Washington, DC. MR rates in 1993 were only 62% of the rate for 1981–1982, but had rebounded to 80% of that rate by 1999. Note that the weakening WISC-R norms predict a decline as the 1980s progressed and that the growing dominance of the new WISC-III predicts an upward trend beginning about 1994. This was precisely the trend found by Scullin.
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By 1999, the percentage of children and adolescents receiving MR-related services should have risen to that of 1982. In 1999, the WISC-III norms were 10 years out of date, exactly the same as the 10-year-old WISC-R norms in 1982. The reason that MR diagnoses reached only 80% of their old level was that the new test was swimming against a tide. The diagnosis of learning disability was replacing the diagnosis of MR, thanks in part to the reluctance of school districts to assign the latter label, particularly to minority children. If those children who avoided the label of having MR find themselves at age 25 on death row, they will not be grateful. Obsolete norms play havoc with diagnoses other than MR. The WISC-III manual notes that children with learning disabilities or reading disorders tend to do poorly on the four subtests of Arithmetic, Information, Coding, and Digit Span (the AICD profile; Wechsler, 1992). Getting the lowest scores on three of the four subtests constitutes a partial AICD profile. The WISC-IV technical manual states that low scores on Arithmetic, Information, Vocabulary, and Letter-Number Sequencing characterize reading disability; and that low scores on Arithmetic, Information, and Comprehension are associated with expressive language disorder (The Psychological Corporation, 2003, pp. 79–82). Trends over time reveal that all of the above subtests, except Coding and Comprehension, have shown virtually nil gains over time. Time-related trends for Letter-Number Sequencing are unknown because it is a new subtest (Flynn, 2006a, Table 1). Huge gains on all of the remaining subtests are the cause of the massive Full-Scale IQ gains on record (Flynn, 1984, 1987). In other words, after the WISC-III’s norms became obsolete, perfectly normal children started to show a partial AICD profile. If they were typical of their cohort, they tended to score closer to the old norms on Arithmetic, Information, and Digit Span than on any other subtest. And after the WISC-IVs norms become obsolete (circa 2015), we have reason to believe that normal children will tend to look as if they have reading or language disorders. They will tend to do worse on Arithmetic, Information, and Vocabulary, a bit below their average on Comprehension, with Letter-Number Sequencing unknown.
2.2. A temporary expedient Some might argue that a simple solution exists to the problem of obsolete norms: Dispense with IQ tests and assess MR on adaptive behavior alone. Whatever the merits of this proposal, it would perpetrate a terrible injustice. America’s adversarial legal system makes it highly likely that, when prosecution and defense experts interview defendants, they will reach opposite conclusions about whether MR is present. In John Doe’s case, the defense psychologist noted the hesitancy and conceptual vagueness typical of
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those who have MR; the prosecution psychologist found him far too alert and fluent to have MR. Therefore, IQ scores were crucial. On the face of it, John Doe’s case looked hopeless. Recall that, at age 11 in 1995, he received a Full-Scale IQ score of 75 on the WISC-R. On death row, at age 21 in 2005, both psychologists administered the WAIS-III; the defense psychologist scored him at 70, and the prosecution psychologist at 72. In fact, all of his IQ scores indicate MR. The WISC-R score should be put at 68 thanks to 23 years of obsolescence of its norms, and the WAIS-III scores should be reduced to 67 and 69 respectively thanks to 10 years of obsolescence. In addition, Flynn (2006b) reported evidence that the WAIS-III inflated IQs by 2.34 points even at the time it was normed due to a substandard normative sample. Taking this into account would lower the WAIS-III scores to a bit below 65 and 67, respectively. In order to give justice some chance of being done, we must salvage IQ scores; and to keep IQ scores from being deceptive, they must be lowered for obsolescence. To aid jurists, Flynn (2006b) proposed a simple formula: Test Score (I 0.3) ¼ IQ. The letter ‘‘I’’ stands for the interval between when the test was normed and when the subject was tested. The test must be a Wechsler (e.g., WISC or WAIS) or Stanford–Binet test normed in America. As Flynn (2000b) showed, we cannot have the same confidence that WAIS scores have become obsolescent at 0.3 points per year that we have concerning WISC scores. But the rate of 0.3 points per year is our best (even if rough) estimate, and to make no adjustment at all would leave capital offenders at the mercy of IQ scores that are clearly inflated. As we have seen, if the Wechsler test happens to be the WAIS-III, an additional 2.34 points should be deducted—because the WAIS-III inflated IQs by that amount even at the time it was normed. You may wish to know the true cutting line for MR at the time a test was administered, that is, what score was at 2.0 SDs below the mean. The formula then becomes: 100 þ (I 0.3) – 30. If the test is the WAIS-III, add an extra 2.34 points. For example, if the WAIS-III were administered in 2005: 100 þ (10 0.3) þ 2.34 ¼ 105.34; and that minus 30 ¼ 75.34 should be used as the true cutting line.
2.3. The history of the bottom 2.27% Adjusting for obsolescence is merely a temporary expedient. IQ gains over time pose deeper problems that must be faced if intelligence and its attendant IQ score are to be salvaged as a criterion of MR. The criterion of an IQ of 70 or below has no intrinsic rationale. Its selection is probably best thought of as an implicit agreement between professionals and policy makers that only a relatively small percentage of persons who exhibit the most extreme impairment on tests of intelligence can and ought to receive services under the rubric of MR. Therefore, the
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criterion is more a matter of sociology and social engineering than a precise indicator of the level of impaired reasoning that persons with IQs of 70 or below exhibit. It is, of course, not an entirely arbitrary choice. It is also supposed to signal the likelihood of impaired adaptive behavior. In effect, professionals are confident that people in at least the bottom 2.27 of the population are characterized by impaired reasoning and adaptive behavior, or more accurately, at least the bottom 2.27% of the biologically normal population are so described. There is another group whose members suffer from MR because of specific genetic or other organic or biological factors, and inclusion of this group brings those who would actually score at 70 or below closer to 3% of the population. What follows simplifies by focusing on the fact that 70 is 2.0 SDs below the ‘‘normal’’ mean and isolates the bottom 2.27% of the ‘‘normal’’ population. As we have seen, a WISC score of 70 probably does do a good job of isolating the bottom 2.27% on the dimension of general intelligence, but it does so only during the year in which the test is normed. Thanks to obsolescence of norms and other factors, a score of 70 or below isolated anything between the bottom 0.47% and the bottom 4.35% during the period between 1950 (when the WISC was published) and 1985 when the problem of obsolescence was made public (Flynn, 1985). As far as we can determine, over the relevant 35 years, no clinical or school psychologist using the various WISC tests noticed that the percentage of the population meeting the IQ criterion of MR was fluctuating wildly over time. No one who began practicing late in WISC era, say in 1970, noticed that the test scores resulted in only a small fragment of the biologically normal population receiving an MR diagnosis. When the WISC-R appeared, scholars did administer both the WISC and WISC-R to the same subjects and they did notice, to their concern, that the old test gave inflated scores compared to the recent one. But no one drew the obvious conclusion that psychologists in the field simply were not making any systematic assessment of the accuracy of the IQ criterion for MR, that is, its accuracy in terms of isolating the correct percentage eligible to be classed as having MR. Some scholars, such as Hamm et al. (1976, p. 7) were alarmed: ‘‘Results from the present study support Doppelt and Kaufman’s conclusion that the WISC-R typically yields lower IQ scores for children who function in the EMR range. Thus, more students will be classified as ‘mentally deficient’ as a result of its administration. Such findings suggest that considerable care be exercised when assigning special class placement based largely upon WISC-R scores. There may be a need for reevaluation of criteria for special class placement.’’ Excellent advice, but it did not go deep enough in its diagnosis of causes for alarm. If clinical psychologists were making a systematic assessment of whether the IQ criterion for having MR was truly matched by impaired adaptive
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behavior, they should not have had to wait for the appearance of the WISC-R (and its lower scores) to tell them something was wrong. They should have noticed either that a WISC score of 70 was too harsh at the beginning of its era (was classifying children who were not impaired) or was too lenient at the end (was failing to classify children who were clearly impaired). What does the silence of psychologists mean? It means that psychologists could not possibly have been finding a consistent relation between a particular IQ score and the level of intellectual or socially adaptive behavior it was supposed to indicate. In 1949, a child who got a WISC IQ of 70 was almost 2.0 SDs below the mean. By 1974, a child who got a WISC IQ of 70 was 2.53 SDs below the mean. So, which cutoff score criterion had external validity for indicating MR on the basis of a correlation with impaired adaptive behavior? Clearly neither did, in that psychologists were as happy with one as with the other. And yet one cutoff score isolated a pool of 2.27% of persons with a label of having MR and the other a pool of 0.57%. That no coherent criterion was operational in the field could be interpreted in any one of several ways. First, the failure to recognize the problem might mean that the possibility of a collective or professional consensus about IQ scores and MR is impossible. This seems unlikely given the general consensus that an IQ score around 70 is a reasonable cutoff score for supporting a diagnosis of MR. Second, small numbers may have been the culprit. MR is an uncommon occurrence, affecting approximately 2 children in every 100. Unless an individual psychologist tested a very large number of children, fluctuations in the number of children identified would be difficult to detect. Suppose that 1 child in 100 was identified as having MR one year, and 3 children in 100 were identified the next year. Even though this represents a 3:1 ratio in rate of identification, such small fluctuations could easily be due to chance in the clinical experience of an individual school psychologist. Of course, someone, particularly persons associated with the diagnostic test, should have been tracking the rate of identification of children as having MR ‘‘in the large,’’ for example, at the state or national level. That no psychologist at any level publicized the changing rate of identification using the WISC is puzzling indeed. The answer may lie in the persistent pressure to stop labeling children as having MR, due to the negative connotations of the label. This certainly contributed to a zeitgeist in which falling rates of identification might go unnoticed or, at least, considered unworthy of mention. These facts confer a new critical perspective on the claims the test manuals make about ‘‘evidence’’ for the criterion of MR. In 1944, Wechsler (1944, pp. 36–48) began his career by poking fun at Terman for using numerical criteria to classify subjects. He noted that Terman’s cutting lines all ended in zero (70, 80, and 90 were used to classify subjects as feebleminded, deficient, and dull) and that the odds against a statistical procedure
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giving that result were 10,000,000 to 1. He also objected that Terman gave no evidential rationale for these cutting lines rather than some other set of cutoff points. Wechsler (1944) then suggested his own statistical criterion of mental deficiency, one that later evolved into the traditional ‘‘2.0 SDs below the mean.’’ At this point, we must defend Terman’s sanity. Wechsler did not like nice, neat numbers, but what about putting cutting lines at a nice, neat number of SDs below the mean: 2.0 SDs (IQ ¼ 70) for mildly MR, 3.0 SDs (IQ ¼ 55) for moderately MR, and 4.0 SDs (IQ ¼ 40) for severely MR? Certainly, wanting SDs that end in even SD units is just as absurd as wanting IQ scores that end in zero. It was a relief when Wechsler went beyond a spurious debating point and appealed to evidence. He stated he had available various estimates of the incidence of mental deficiency and these gave a mean figure of about 3% of the total population. This would justify classifying about 2.27% of the biologically normal population as mentally retarded. However, as odd as it seems, Wechsler (1944) provided absolutely no citations. No one knows what studies he had in mind or whether they actually supported his contention. In 1974, 30 years later, the WISC-R manual introduced a new criterion of MR. Prior to 1974, the line was drawn at 2.0 SDs below the IQ mean of white Americans; now it was drawn at 2.0 SDs below the IQ mean of all Americans, including lower-scoring minority groups. The fact that a score of 70 remained the criterion masked the fact that, on paper at least, the criterion was less demanding: One must score 4.56 IQ points higher to avoid being in the bottom 2.27% of white Americans than in the bottom 2.27% of the lower-scoring all Americans (Flynn, 1985). The manual states that the scale provides ‘‘a time-tested classification of IQ equivalents for diagnostic terms in common use’’ (Wechsler, 1974, p. 24). How the same body of evidence could attest to two criteria that were 4.56 points apart was unstated. Although the new criterion was less demanding ‘‘on paper,’’ it was more demanding in terms of the real world. After all, by 1974, the WISC norms had accumulated 26.5 years of obsolescence. When these weakened norms were swept away, the criterion for MR was enormously toughened, enough to swamp the relaxation entailed by going from white to all-races norms. Practicing psychologists may have thought they were using a criterion 4.56 points less demanding but, in fact, they were using one that was 4.55 points more demanding. At the cutting line for MR, Flynn (1985) showed that the WISC-R set norms about 9 points more demanding than the old WISC norms. To summarize, in 1974, this was the state of affairs: First, during the previous 25 years, no one could possibly have been accumulating evidence for the old white American criterion of MR, because it was becoming more lenient by 8.25 IQ points (somewhat more than the 7.5 points of IQ
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gains at the level of the mean). Second, Wechsler had introduced a new criterion, one he thought to be far more lenient, apparently without any evidential justification. Third, even assuming Wechsler had evidence he did not bother to cite in favor of a more lenient criterion, the new WISC-R criterion was actually much more demanding. Indeed, at the level of MR, it was 9.11 points higher than such evidence would have justified! The alert reader will note a discrepancy of 0.86 points between the two values used in this paragraph. As Flynn (1985, p. 238) argued, a special effort to include low-IQ subjects in the WISC normative sample raised WISC IQs and this inflation was absent in the norms of the WISC-R. In 1991, the WISC-III manual appeared, and it reported results for 28 children with MR who took the WISC-III and for whom WISC-R scores were available. The children scored 8.9 points lower on the new test and psychologists were told they should consider this ‘‘during re-evaluation of children with MR who have already been assessed with the WISC-R’’ (Wechsler, 1992, pp. 211–212). The psychologists were not told that, for every biologically normal child they classified as ‘‘intellectually deficient’’ the previous month, they would now classify four more as such (2.27% divided by 0.47% ¼ 4.8), nor were they told which assessment they should trust. On the credit side, the test manual was commendably honest to present this study and to delete empty references to a ‘‘time-tested’’ body of evidence. The study itself contributes no evidence. Because the children were classified as having MR partially on the basis of the WISC-R, it is hardly surprising they had low IQs on the WISC-III as well. If they had been classified with MR on purely behavioral criteria, their comparative scores might have told us something. In 2003, the WISC-IV technical manual appeared, and comparative data on 120 children with MR were reported. Although the criteria for selection of these children were not fully described, it appears that the children had IQ scores on ‘‘some standard test’’ showing that they were almost evenly divided between a group with IQs in the range of 40 or below and a group with IQs from 41 to 70 (The Psychological Corporation, 2003, pp. 79–82). Similar problems arise as with the WISC-III study: If other IQ tests played a large part in their classification as having MR, the children should certainly get low scores on the WISC-IV simply because scores from different IQ tests exhibit high intercorrelations. But this kind of intercorrelation does not confront the problem of which cutting line for MR is really valid: the tougher cutoff score in use soon after a test is normed or the easier one in use just before the test is to be replaced. In sum, when norms are fresh rather than obsolete, a score somewhere between 60 and 75 is probably a decent criterion of MR based on impaired reasoning and low levels of adaptive behavior. But, no one has yet made a strong case for the external validity of any particular score in terms of the precise level of impaired reasoning that individuals with low IQ are likely to exhibit.
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As noted above, external validity claims seem to reflect a general agreement among all concerned (e.g., psychologists, policy makers) that a particular proportion of the population should be identified as having MR. Such external validity claims certainly do not reflect any established relation between a given IQ score criterion and the particular forms of impaired reasoning that those below the cutoff score tend to exhibit. An IQ score of 60 is 2.67 SDs below the mean of the biologically normal population and would isolate the bottom 0.40%. An IQ score of 75 is 1.67 SDs below the mean and would isolate the bottom 4.75%. As professionals in this field, we should demand research that would identify where in this score range a defensible cutoff value would lie.
2.4. How many of our grandparents had MR? Thus far, we have merely questioned whether we have ever known where to draw the line to get an IQ criterion of MR that has external validity. Now we go deeper and ask whether it makes sense to even try. IQ tests cannot help diagnose MR unless there is a plausible case that they measure intelligence. Therefore, the very magnitude of IQ gains over time poses a paradox. For example, let us take the children aged 6–16 who were used to standardize the WISC-IV as our point of reference. That gives the current generation, American children in 2002, a mean IQ of 100 by definition. Their parents would have been 4–14 in 1972 and would have been used to standardize the WISC-R. Using a rate of gain of 0.3 points per year, their mean IQ would have been 91 against recent norms. On average, the grandparents of the WISC-IV children would have been 8–18 in 1948 and used to standardize the WISC. Their mean IQ would have been 83.5 against recent norms. If this grandparent generation really had that low a level of intelligence, 18.41% of them would have had an IQ of 70 or below and, adding in a few with specific genetic defects, the real total would have been 20%—or one person in five. Anyone who lived at that time, and taught a mainstream class, knows that this is absurd: Nothing approaching 20% of the members of our grandparents’ generation exhibited seriously impaired behavior. An obvious way out of the dilemma is to dismiss IQ gains as an artifact. However, these gains are not artifacts in any normal sense of the word. The leading case for artifactual status is to attribute IQ gains to growing test sophistication. Test sophistication has to do with feeling comfortable with the format of IQ tests, or whoever administers them, or using your time better, or trying harder in the test room. The 20th century has seen us go from people who have never taken a standardized test to people bombarded by them, and a small portion of score gains in the first half of the century was undoubtedly due to growing test sophistication.
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However, since 1950, the role of test sophistication in accounting for IQ gains has been relatively modest. In the United States, gains have been steady at least since 1932 (Flynn, 1984). If gains are due to test sophistication, they should show a certain pattern. When naive subjects are first exposed to IQ tests, they gain a few points; but, after that, repeated exposures show sharply diminished returns. Gains in the United States show no such pattern and other nations show just the reverse. For example, The Netherlands shows a huge rate of gain escalating decade after decade from 1952 to 1982 (Flynn, 1987). Perhaps IQ gains are due to ‘‘cultural bias.’’ Here, we must distinguish cultural trends that make test content more familiar at one time than another from cultural trends that have truly raised the level of cognitive skills from one time to another. We measure the magnitude of IQ gains by the extent to which people do better on a test whose content is outmoded (e.g., the WISC) than they do on a test whose content is current (e.g., the WISC-R). Vocabulary or Information that was common when the test was constructed sometimes falls out of general use or general knowledge over time, and this is why the content of IQ tests is updated from time to time. Unfamiliarity with outmoded content should artificially deflate estimates of IQ gains by causing lower scores on the outmoded test. However, this pattern is the exact opposite of that caused by IQ gains, namely, higher scores on earlier, rather than later, tests. As for the IQ test items becoming public, this is least likely on tests rarely used in schools such as Raven’s. Yet these are the tests that have shown the largest gains over the entire 20th century.
2.5. The WISC subtests to the rescue Massive IQ gains are not an artifact and yet, if that is so, we are driven to conclusions that seem absurd. The solution to this paradox is to be found by focusing on the WISC subtest trends rather than Full-Scale IQ trends. As mentioned above, IQ gains vary considerably by subtest. Between 1947 (WISC) and 2002 (WISC-IV), the following trends occurred: Similarities showed a huge gain of 24 points (SD ¼ 15), the five Performance subtests showed gains ranging from 12 to 21 points, Comprehension exhibited an 11-point gain, and the remaining Verbal subtests (Information, Arithmetic, and Vocabulary) showed very limited gains of 2–4 points (Flynn, 2006a, Table 1). Gains on the Raven’s Progressive Matrices (RPM) test are also relevant. As Flynn (1998) demonstrated, advanced nations have made huge gains on the Raven’s test. Although no good data are available for Americans, if we posit gains equal to the lowest gains found elsewhere, U.S. gains would at least match Similarities; indeed, at a 0.5 points per year, they would amount to 27.5 points gained over 55 years. Let us analyze the cognitive skills needed to do well on the various IQ tests and subtests. The huge Raven’s gains show that today’s children are far
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better at solving problems on the spot without a previously learned method for doing so. The WISC Performance subtests all measure this to some degree. These WISC subtests require arranging blocks so that the view from above duplicates a presented pattern, building an object out of its disassembled parts, or arranging pictures to tell a story. In contrast, most children have some prior experience at jigsaw puzzles or reading books in which pictures are the main vehicle of the story. We suspect that the fact that the on-the-spot element is diluted in Performance subtests explains why their gains, although substantial, lag behind Raven’s gains. Children have been exposed to jigsaw puzzles and picture books for many generations, and this prior experience contributes to their success on Performance subtests. We turn next to the subtests that show minimal gains. Having an adequate fund of general information, being able to do arithmetic, and having a decent vocabulary are very close to school-taught skills. These tests require much less on-the-spot reasoning or problem solving and are more a matter of exhibiting what you know: You either know that Rome is the capital of Italy or you know only of Rome, Georgia; you know what ‘‘delectable’’ means or you do not. Arithmetic, sometimes assumed to be just as rote as the more verbal tests, is more complex, as we shall see. This contrast, the difference between on-the-spot reasoning (or Fluid Intelligence) and stored knowledge (or Crystallized Intelligence), is the key distinction made in the Horn–Cattell theory of Fluid and Crystallized Intelligence, to which Carroll has also made contributions (Carroll, 1993; Cattell, 1971; Horn, 1967, 1968, 1978). The Horn–Cattell theory is making inroads with standard intelligence tests, including the Stanford–Binet and Wechsler tests, as these tests have begun to provide subscores that correspond to constructs from the Horn–Cattell theory. In addition, the distinction parallels a distinction from cognitive psychology, the distinction between procedural and declarative knowledge. Procedural knowledge is knowledge ‘‘how,’’ or knowledge about how to get things done, which shades directly into on-the-spot reasoning about how to solve a current problem based on often-implicit notions about how similar problems have been solved in the past. In contrast, declarative knowledge is knowledge ‘‘of,’’ or knowledge of stored facts and concepts. It is illuminating to take trends in WISC subtest scores in conjunction with trends on the National Association of Educational Progress (NAEP) tests, often called the Nation’s Report Card. Between 1971 and 2002, that is, comparing the current generation of schoolchildren with its parents, young children made substantial reading gains. However, by the 12th grade, reading gains drop off to almost nothing (U.S. Department of Education, 2000, pp. 104, 110; 2003, p. 21). This is hardly surprising. Between 1972 and 2002, the WISC subtests show that schoolchildren made no gain in their stores of general information and only minimal vocabulary gains (Flynn, 2006a, Table 1). Therefore, although today’s
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children may learn to master preadult literature at a younger age, they are no better prepared for reading more demanding adult literature. You cannot enjoy War and Peace if you have to run to the dictionary or encyclopedia every other paragraph. In other words, today’s schoolchildren opened up an early lead on their grandparents by learning the mechanics of reading at an earlier age. But by age 17, their grandparents had caught up. Moreover, since current students are no better than their grandparents in terms of vocabulary and general information, the two generations at 17 are equal in their ability to read the adult literature expected of a senior in high school. From 1973 to 2000, the Nation’s Report Card shows 4th and 8th graders making mathematics gains equivalent to almost 7 IQ points. But once again, the gain falls off by the 12th grade, this time to literally nothing (U.S. Department of Education, 2000, pp. 54, 60–61; 2001, p. 24). Once again, a WISC subtest suggests why. The Arithmetic subtest and the NAEP mathematics tests present a composite picture. An increasing percentage of young children have been mastering the computational skills that the Nation’s Report Card emphasizes at those ages. However, during that very same period, children made no score gains on WISC Arithmetic. To do that subtest, you must know the mechanics of calculation plus something else. The questions are put verbally, which means the child cannot give a purely mechanical (times-table-type) answer. And some questions require you to diagnose what combination of operations (first division and then multiplication) is required to solve the problem. By the 12th grade, the lack of progress in terms of learning to think mathematically takes on significance. American schoolchildren cannot do Algebra or Geometry any better than their grandparents could. Although the older generation was slower to master computational skills, they were no worse off at graduation from high school. In one area of cognitive skills, secondary students clearly have undergone a dramatic change. The huge gains on RPM show that today’s youth are much better at problem solving in situations in which they have no previously learned or rote method of attacking the problem. It is likely that this advantage is sustained and perhaps enhanced by university study. There are a number of likely dividends. Every year America has an increased number of managerial, professional, and technical jobs to fill—jobs that often require decisions without the guidance of set rules. We now know why recent IQ gains do not imply that our grandparents should seem to be much less intelligent than their grandchildren. Assume we hear a recent high school graduate chatting with his grandfather who also finished high school. The latter would be able to discuss novels as an equal and display an equally wide range of reading. He could discuss current affairs with as broad a vocabulary and fund of general information. The grandson would be much better in terms of on-the-spot problem solving, at
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least in certain contexts. Sometimes, the grandfather’s ‘‘handicap’’ would affect social conversation, particularly because he would not think that abstract or ‘‘impractical’’ problems were very important. The grandfather might be more rule governed and would probably count that as a virtue.
2.6. Did almost everyone once have MR? Our grandparents were assigned a median birth date of 1934 to get them in school in time for the WISC. But what of their parents and grandparents, what of the cohort born in 1906 that was in school in 1918 and the cohort born in 1877 that was in school in 1900? British Raven’s data show massive gains beginning with the cohort born in 1877— they were actually tested at maturity of course (Raven, Raven, & Court, 1993, Graph G2). World War I military data show that U.S. gains were under way as far back as we can measure (Tuddenham, 1948). The Wechsler–Binet rate of gain (0.3 points per year) entails that the schoolchildren of 1900 would have had a mean IQ just under 70. The Raven–Similarities rate (0.5 points per year) yields a mean IQ of 50 (against current norms). Even if the latter accounts for most of the former, it will hardly do to say simply that our ancestors were bad at on-the-spot problem solving. After all, innovative thinking is an important real-world skill. Only the worst child of the 2,200 schoolchildren used to norm the WISC-IV would have performed as low as the 1,900 average. To presume our ancestors were that lacking in innovation or problem-solving initiative would be to characterize them as virtual automatons. Moreover, there is some connection between mental acuity and the ability to learn. Jensen (1981, p. 65) related an interview with a young man with a Wechsler IQ of 75. Despite the fact that he attended baseball games frequently, he was vague about the rules, did not know how many players were on a team, could not name the teams his home team played, and could not name any of the most famous players.
3. Possible Solutions 3.1. Piagetian approach Piaget made relevant and perhaps crucial distinctions, namely, among preoperational, concrete operational, and formal operational thinking, but others have done the fieldwork. If we assume that most people were still on the concrete level in 1900, they were handicapped most on the two IQ tests that show the largest and therefore the most embarrassing gains. We refer to the RPM test and the Similarities subtest. A person on the concrete operational level lives in the world that confronts us in everyday life. When presented with a Similarities-type
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item such as ‘‘what do dogs and rabbits have in common,’’ Americans in 1900 would be likely to say, ‘‘You use dogs to hunt rabbits.’’ The correct answer, that they are both mammals, assumes that the important thing about the world is to classify it in terms of the taxonic categories of science. Even if the subjects were aware of those categories, the correct answer would seem absurdly trivial. Who cares that they are both mammals? That is the least important thing about them on the concrete level. As long as you are on that level, it is not natural to detach abstractions and logic and the hypothetical from their concrete referents. The key issue is not whether people use abstractions. People on the concrete level often use abstractions: The concept of hunting as distinct from fishing is an abstraction. They also use syllogistic logic: Basset hounds are good for hunting; therefore, if that is a Basset hound, that dog would be good at hunting. People operating at the concrete level would of course use the hypothetical; if I had two dogs rather than only one, I could catch more rabbits. Such persons do not have MR in any sense, but in terms of current norms they will appear to do so on Similarities. Today we are so familiar with the categories of science and are so imbued with the scientific worldview, that it seems obvious that the most important attribute that things have in common is that they are both members of a common category, such as both being animate, or mammals, or chemical compounds. Beginning with its inception, what counts as a correct answer on Similarities favors the formal mode over the concrete and, by the time of the WISC-R, this was made explicit (italics added): ‘‘Pertinent general categorizations are given 2 points, while the naming of one or more common properties or functions of a member of a pair (a more concrete problem-solving approach) merits only 1 point’’ (Wechsler, 1974, p. 155). The preference for taxonic answers (categories that classify the world and extra credit for the vocabulary of science) is extraordinary and reaches an even higher level in the WISC-IV, where the ‘‘one point’’ for concrete answers is reduced to ‘‘merits no or only a partial credit’’ (The Psychological Corporation, 2003, p. 71). You are just not supposed to be preoccupied with how we use something or how much good it does you to possess it. If children are on the concrete level, they can get no more than half credit on most Similarities items. In 1900, if children aged 14 were of average intelligence and were given a prehistoric version of the WISC-IV, they would have a raw score of about 11 and be 2.0 SDs below the current mean, which is a score of 70 against today’s norms (The Psychological Corporation, 2003, p. 229). This was the ‘‘target’’ score that Full-Scale IQ gains implied when projected back to 1900. Note how the WISC manuals use the word ‘‘pertinent’’ to justify rewarding taxonic answers. This is just a synonym for claiming that classification is what is important about a pair of things. Imagine a rural child in 1900 being told that the most important
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thing about dogs and rabbits is a name that applies to both, rather than what you use them for. In sum, we need not infer that the huge gains on Similarities from one generation to another signal a general lack of intelligence on the part of our ancestors. Their minds were not permeated by the scientific worldview and they had not shifted from concrete to abstract, or formal operational, thinking. RPM presents 60 patterns each of which has a piece missing. Six alternatives picture a candidate for the missing piece and the subject must select the one that fits the logic of the matrix design. The entire test demands detaching logic from a concrete referent, but even subjects unused to this can adapt to varying degrees under examination conditions. From a larger sample of 201 children, Styles (in press) selected 60 children who were typical in terms of age and initial testing. The 60 children selected were part of a five-year study of the intellectual development of children initially 10, 12, and 14 years of age (Andrich & Styles, 1994). The children took both a Piagetian test and items of the RPM ranked in order of difficulty. They were tested yearly on the former and twice yearly on the latter over a period of four years. Five Raven’s items were used to illustrate the sections of the test and therefore, were automatic correct answers. Two items were so easy for this group of children that everyone got them correct. The remaining 53 items mapped on to ascending Piagetian competence in ascending order of difficulty. Of these, the 20 most difficult RPM items required the subject to be either on the threshold of the formal level or operating on that level. Styles asserted that these items require using either a number of rules or a very complex rule to interpret the matrix pattern; and the subject must consider the logical relations between relations, rather than the factual relationship between a proposition and concrete reality. In other words, if children aged 14 in 1900 were operating primarily on the concrete level, we would expect their raw scores to have a ceiling of about 40 correct items out of a total of 60. John Raven (2000, p. RS3 18) established norms for the United States circa 1982, and these norms show 40 items correct as the 38th percentile of 14-year olds. The age curve corresponding to a ceiling of 40 is that of 7.5-year olds. Their median is a score of 20, which is off the bottom of the curve for 14-year olds. If most people in 1900 operated below the formal level of reasoning, this would serve to resolve the paradox of the huge Raven’s gains between then and now. The gains can be as large as you wish without any presumption that most of our ancestors suffered from MR. They were quite capable of on-the-spot problem solving in the concrete situations that dominated their lives. The ingenuity of soldiers trying to say alive in the trenches of
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World War I and the improvisations of mechanics trying to keep the first motorcars running is part of the historical record. Those who wish a fuller discussion of this issue should see (Flynn, 2007), What is intelligence? The solution to our paradox does not imply that massive IQ gains over time are trivial. The scientific worldview, with its vocabulary, taxonomies, and detachment of logic and the hypothetical from concrete referents, has begun to permeate the minds of postindustrial people. This has paved the way for mass education on the university level and the emergence of an intellectual cadre without whom our present civilization would be inconceivable.
3.2. Psychometric approach based on item response theory At least one other potential approach should be mentioned, a psychometric approach founded on modern test theory, which is also called item response theory (IRT). In contrast to IRT, the traditional classical test theory approach to developing tests involves sampling items from domains of content, evaluating the relations between items and total scores, and selecting items with optimal correlations with total scores. Much of this work can be done without examining the link between an individual’s level of ability and the characteristics of the items to which the person responds. Items merely serve as the avenue to the estimation of a total score for each person, and the evaluation of an individual’s overall score depends on where his or her score falls in the population distribution of total scores. The introduction of IRT to the test development process changed all of this, and the close tie between the individual’s level on a latent trait and the content of items at that level lies at the heart of the IRT approach. Item content plays a more central role in the IRT approach, because an individual’s overall score on a test gains interpretability on the basis of the items that she or he is able to solve with a given probability. Technical details of the IRT approach go far beyond the present chapter, and readers are referred to several excellent publications (Embretson & Reise, 2000; McDonald, 1999). But, to reiterate, the IRT approach provides both person estimates (e.g., estimates of an individual’s standing on the latent trait) and item difficulty estimates that are on the same scale, enhancing the interpretation of test scores. The applicability of the IRT approach to the issue of diagnosing MR is direct. The traditional cutoff score for diagnosing MR is a score that falls at or below 2.0 SDs below the population mean. IRT methods, which have been the standard approach for scaling intelligence test items for two decades or more, can be used to identify items that supply a great deal of measurement information—and therefore discriminate well among individuals— near the cutoff score. The application of IRT methods to the normative
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sample from an intelligence test could then provide information regarding what types of items discriminate best between those who fall above the cutoff score and those who fall below. One key assumption of IRT is that a set of items is unidimensional, meaning that the set of items assesses a single, unitary underlying trait. Thus, application of an IRT model to data from all items on, say, the WAIS-III would be difficult to justify, as items on the various WAIS-III subtests are indicators of several different dimensions. However, as noted in an earlier section, most recent versions of tests including the Stanford Binet V, the WAIS-III, and the Woodcock–Johnson III provide IQ subscores on the standard IQ scale (i.e., mean of 100, SD of 15) for Fluid Intelligence and Crystallized Intelligence, which are conceived of as unitary dimensions of intelligence. The conception of Fluid Intelligence as a general form of reasoning that supports on-the-spot reasoning in novel situations is similar to that of Piagetian forms of reasoning. But, rather than presuming that reasoning conforms to hierarchically ordered levels such as concrete operational and formal operational thought, levels of Fluid Intelligence are thought to vary continuously from simpler to more complex. Even if levels of Fluid Intelligence are classified more with regard to degree than to kind, it still may be possible to identify distinctive forms of fluid reasoning that can be performed by persons who exceed the criterion of MR and that cannot be performed by persons who fall below that criterion. The second dimension is Crystallized Intelligence, which pertains to knowledge of the culture, of the meanings of cultural artifacts (including language), and of proper actions and behaviors. Lacking full and automatic knowledge of the culture could so impair one’s judgment in an on-the-spot situation that low levels of Crystallized Intelligence could also be an important impediment to making fully informed judgments, limiting legal culpability for the outcomes of one’s behaviors. The dimensions of Fluid and Crystallized Intelligence are central in current theories of ability structure and in the scoring procedures for current tests. Therefore, the future may see a move away from a score of 70 or below on Full-Scale IQ to satisfy the subnormal general intellectual functioning prong of the diagnosis of MR, toward a score of 70 or below on either Fluid Intelligence, or Crystallized Intelligence, or Full-Scale IQ. This would parallel current rules for satisfying the prong related to adaptive behavior. Regardless of whether such a major change for the intelligence prong was made, the use of IRT—with its intimate tie between item difficulty and person ability—might be another reasonable way to make the crucial distinction between those who do or do not meet a diagnostic criterion for MR, thus providing an external validity criterion for this decision.
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4. Concluding Remarks 4.1. Temptation to be resisted If IQ gains do not persist into the future, it will be tempting to forget the lessons they have taught us. That temptation must be resisted. The only problem that would be ‘‘solved’’ would be that scores on IQ tests taken after the date of cessation would not have to be adjusted for obsolete norms. The deeper problem of whether some IQ criterion of MR can qualify for external validity would remain. This point must be stressed because there is no reason to believe that cognitive progress will go on forever. After all, the persistence of IQ gains is dependent on the persistence of the trends that cause them. These trends likely include more people looking at the world through scientific spectacles; higher ratios of adults to children in families; and more leisure activities and jobs that are conceptually demanding. The future may see a reversal of these trends. The spread of the scientific ethos may be terminated by the powerful forces (particularly in America) that hate science. The trend toward a higher ratio of adults to children in the home may be reversed by more single-parent homes. If that occurs, children might get less parental attention. Our willingness to be challenged by more conceptually demanding leisure activities must eventually reach a limit. The multiplication of professional and managerial jobs already depends to some degree on featherbedding. Although IQ gains are still robust in America, they have stopped in Scandinavia (Flynn & Weiss, in press; Schneider, 2006). Perhaps Scandinavian societies are more advanced than ours is and their trends show what the future holds for us.
4.2. Necessary tasks It is time to offer a summary that suggests the tasks we must perform. In 1900, most people could cope intellectually with concrete reality but a few could not. The latter, both then and now, should be rightly classified as having MR. Massive IQ gains over time signal primarily a shift from the concrete to the formal mode, but they have not altered the ratio between those who have concrete competence and those who do not. Our first task is to investigate whether all of this is true, that is: Has the ability to cope with everyday life failed to show significant gains during a period in which IQ gains have been robust? If that is verified, we must confront our second and most fundamental task: Can we develop and justify purely behavioral criteria to validate an IQ criterion of MR? If we succeed in that, that in turn confers a third task: We should alter IQ scores inflated by obsolescence. At least as long as IQ gains persist, failure to do so allows the percentage of those classified with MR to fluctuate radically over time.
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IQ scores blur the difference between the inability to cope with everyday life (lack of concrete operational competence) and the inability to cope with school subjects (lack of formal operational competence). Therefore, we have a fourth task: We should supplement IQ tests with a Piagetian test or some other kind of reasoning test that distinguishes between reasoning on the preoperational, concrete operational, and formal operational levels. As for our first task, the Vineland Adaptive Behavior Scales can now supply relevant data. For the first time, the publishers of the Vineland have compared the performances of samples used to standardize their test in two different years (Vineland, 2006). Subjects aged 7–18 who took both tests actually found the 1984 norms more difficult to meet than current norms. That is, they received an overall Adaptive Behavior Composite of only 95.0 on the old test and one of 98.4 on the new test (SD ¼ 15). This seems to indicate that children actually lost ground in terms of adaptive behavior over the last 20 years. However, the loss in adaptive behavior is more apparent than real because the old test has lost some of its relevance in assessing adaptive behavior. Scores on the Communication and Socialization subtests were similar on the two versions. The lost ground was almost entirely on the Daily Living Skills subtest. The 1984 version of that subtest contains obsolete skills that would deflate the scores of contemporary children (items such as ‘‘sews or hems clothes,’’ ‘‘makes own bed,’’ and ‘‘uses a pay telephone’’). The most judicious conclusion is that American children have marked time in terms of adaptive behavior. During the same period (WISC-III to the WISC-IV), American children made IQ gains at the traditional rate of 0.3 points per year. Therefore, IQ gains over time do not mean that fewer and fewer children find it difficult to cope with everyday life. Our second task is the most difficult. How can we identify an IQ criterion for MR that is validated by behavioral criteria? The American Association on Intellectual and Developmental Disabilities (formerly American Association on Mental Retardation) could select a panel of 20 psychologists whose judgment they trust and ask these experts to create a pool of 400 participants (20 nominated by each) classified as mentally retarded on purely behavioral criteria. Members of the panel would then administer Wechsler–Binet tests to the participants and assess the results to see if any common IQ ceiling emerged. Supplementary information could be provided by IRT estimates of the items that discriminated between persons falling above or below the common IQ cutoff score. Ideally, most children classified as mentally retarded would fall below a particular IQ and only the rare child score would score above it. At that moment in time, that particular score on that particular test could be recommended to school psychologists as a check on their clinical judgment. Thanks to the possibility of future IQ gains over time, the whole experiment would have to be repeated after no more than seven years.
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Let us hope that the consensus does not unravel over time. If the psychologists on the panel diverged, some finding that the ceiling had stayed at 70, others finding that it had risen to 72 or even to 74, we would have reason to be disconcerted. Coherence at both the start and finish of the seven years would inspire confidence. Our third task would be to find a formula to adjust IQs during the interim on the assumption that IQ gains were still in progress. The sevenyear review, or a new standardization of an IQ test, might show that we were mistaken. But better to err on the side of caution than to sentence convicted offenders to death. As the reader knows, we have offered a formula to be used for the time being. Some might complain about the lack of precision of our formula, but this formula is clearly better than having no adjustment of any kind. Proceeding without an adjustment formula during a time of enhanced normative performance ensures that persons, perhaps many persons, who deserve the label of MR will fail to receive it. In school contexts, the label of MR may be regarded as detrimental, given the discrimination associated with it. But, in criminal proceedings, the label of MR can save a life. This brings us to our fourth and final task. Children who score as MR on the WISC should take a Piagetian test or some other form of reasoning test, such as a test of Fluid Intelligence or Crystallized Intelligence subjected to IRT analysis, to determine whether or not they are cognitively competent on the level of concrete reality. If they are competent, the label of MR should be set aside in favor of something else, perhaps school learning problems (SLPs). In other words, the diagnosis of MR should be reserved for individuals who are unable to reason adequately on the level of concrete reality in everyday situations, regardless of whether they have problems with typical school content. To give an example of a test that might be suitable, Trevor Bond has developed Bond’s Logical Operations Test (the BLOT) to distinguish whether one uses logic on a concrete or formal level (Endler and Bond, in press, p. 8). Certain items on this test explore ‘‘whether the child has the reasoning to manipulate conclusion(s) by reversing the operations of thought (i.e., reciprocity).’’ We would add that such items show the hypothetical slowly being freed from the ties that bind it to concrete situations. Using the BLOT to test a sample of low-IQ subjects might discriminate between WISC items that can be handled by someone competent on the concrete level and those items that cannot. If so, these results would provide a key that would make individual administration of the Piagetian test unnecessary. Eliminating the WISC items that require formal competence and seeing how much their elimination raised the IQ score of an individual would allow us to reassess performance that was putatively at the level of MR.
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4.3. Remaining problems The use of a test like the BLOT to distinguish whether a test taker can reason at the concrete level is, of course, not without its own problems. The items Bond uses are not linguistically simple, which is to say they have a clear verbal loading. If the core aim of the assessment were to measure on-the-spot reasoning that deals with novel everyday, concrete situations, the linguistic complexity of items might contaminate results. To guard against this problem, the wording of problems would have to be reduced to a rather simple level, while retaining a focus on the level of reasoning assessed. If the nature of the reasoning assessed were unchanged by the simplification of linguistic complexity, the items from the BLOT have clear face validity in that they require reasoning in concrete situations, something that cannot be said about the RPM. Assuming simplicity, a verbal test of on-thespot reasoning in concrete situations is advantageous. The RPM uses abstract visual stimulus patterns. None would dispute the high levels of complex reasoning required to solve many items. However, the lack of RPM items with everyday situational content would lead many to question whether ability or inability to deal or reason with highly complex spatial stimuli would have any close parallels with one’s ability to reason at a concrete level in everyday situations. We have every reason to believe that scores on the RPM would correlate very highly with scores on the BLOT, but the aims of the BLOT to distinguish whether persons can reason at the concrete level do seem to have added utility for the purpose of assessing this form of reasoning. Other objections can and should be raised regarding the use of a Piagetian test of reasoning at concrete levels. If such a test were required in addition to the current assessment requirements (an individually administered test of general intelligence and an assessment of adaptive behavior), this would be likely to be seen as a fundamental change in the definition of MR. At present, to merit the diagnosis of MR, an individual must exhibit significantly subnormal levels of general intellectual functioning and concomitant deficits in adaptive functioning. If yet another hurdle were placed in the way, namely, that the person also exhibit an inability to reason in concrete situations, research would have to be undertaken to determine whether an appropriate number of persons satisfy all the criteria of the new definition. The behavioral criterion is, after all, the most fundamental. It would be disturbing if some people tested as competent to deal with everyday life, and yet had a life history that indicated the opposite. In addition, many might question either the fundamental nature or the psychometric properties of a Piagetian reasoning test. Standard concerns cover issues such as various forms of reliability (e.g., inter-rater, test–retest), the standard error of measurement, the degree to which a test taker can fake bad or malinger without detection, the degree to which coaching can affect
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scores, and so on. Current intelligence tests have passed these hurdles reasonably well, and any Piagetian test would also have to demonstrate adequate performance on all of these dimensions. Piaget, however, was little interested in individual differences, concentrating on the delineation of stage-like developmental advances across chronological age. Many followers of Piaget have continued with these emphases. Indeed, most studies in the Piagetian tradition use only a small number of reasoning items, and participants are classified into groups (e.g., nonoperational, concrete operational) on the basis of the consistency with which they succeed on a small number of items. But, any life-or-death decision such as that confronted by defendants in capital cases cannot and should not be based on reasoning performance across a small number of items. Instead, any Piaget-based test would have to consist of a very large number of items, so that the level of reasoning by the test taker can be identified within an acceptably narrow confidence interval. Clearly, if research using converging operations—here, the use of an IRT-based index of Fluid Intelligence and/or Crystallized Intelligence to validate the decision achieved using a cutoff score from a Piaget-based test—found strong agreement between the two forms of assessment, both the Piagetbased and IRT-based cutoff scores would be mutually validated. Still, tests of either of these forms undoubtedly would take several years to develop and validate, so acceptable tests are, most probably, not near at hand.
4.4. ‘‘Bring the tires to me’’ The primary basis for the U.S. Supreme Court decision that persons with MR should not be subjected to capital punishment was the impaired judgment or reasoning that such persons exhibit. If a person with MR cannot reason clearly and fully about his or her actions, then that person is less culpable for his or her actions. Current intelligence tests in the Wechsler and Stanford–Binet tradition assess many things. Because they attempt to arrive at an estimate of general intelligence, the tests assess a nonsystematic conglomeration of Crystallized Intelligence, Fluid Intelligence, spatial ability, perceptual speed, and memory, among other mental functions. Many of these functions have little relation to the basis for the Supreme Court decision. For example, the Court did not base its decision on how quickly a defendant can make simple perceptual judgments (e.g., Digit Symbol Substitution). Intelligence test scores have a vast array of external validities, including correlations with many different measures of school success, job success, and so forth. But, very little or no external validity has been amassed with regard to the relation between particular IQ scores (e.g., scores of 70 and below) and common forms of on-the-spot reasoning in concrete situations. Once again, the Court was interested in culpability: Is this person so suggestible that someone could easily persuade him to participate in a crime?
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Current intelligence test scores, particularly a Full-Scale IQ score that reflects a complex composite of multiple functions (many unrelated to judgment or reasoning), simply fail the crucial external validity criterion of establishing benchmarks for relations between levels of IQ test performance and mature judgment in concrete situations. Without some acceptable evidence on this front, the field of psychology must push for acceptable measures of concrete reasoning that provide a clear answer that would tell the courts whether or not society should hold individuals fully responsible for their actions. We stress this point not so much because of what we have learned from ‘‘hard’’ data, such as Vineland Adaptive Behavior Scales scores or Wechsler IQs, but from reading the case histories of capital offenders who are being judged as mentally competent. For example, John Doe’s case history shows that he never passed the test for a driver’s license or held a job that required reasonable literacy or numeracy. Family and friends testified that he tended to lose focus if sent on errands. One boyhood companion testified that when the defendant and he were both 16 years of age, he pointed out a car and said: ‘‘That is Mrs. Smith’s car. She and I are friends and she said I could borrow her tires. Would you go over and take them off and bring the tires to me.’’ John Doe obeyed. Such a level of misunderstanding of everyday situations could easily lead a person to perform actions—mistakenly, and without cogent deliberation—that might have disastrous impacts and lead to capital charges. Whatever his IQ, John Doe was not mentally mature enough to be held responsible for his actions. We cannot reveal identities, so the reader must remain ignorant of whether or not the public prosecutor secured his execution. We can assure you that his zeal was great. Whatever the outcome in this case, there are others in which IQ scores have played the role of executioner. The fate of these defendants is an American tragedy.
4.5. Quid faciendum est? Perhaps a panel of philosopher kings will appeal to few except those who earn their living as philosophers. The proposal of a basic reevaluation of intelligence tests will have to overcome the enormous potency of inertia. The psychological fraternity can judge for itself the case we have made. Whatever our profession all of us are moral agents. The testers are not going to give away the application of some kind of test criterion of MR. The courts are not going to stop searching for an isle of objectivity in a sea of contradictory professional opinions. Those whose lives and welfare depend on our judgment need a ‘‘score’’ that serves as at least one criterion of MR. They deserve one with a strong, direct, and defensible claim to external validity.
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ACKNOWLEDGMENTS We thank Cambridge University Press for permission to use and adapt material from Flynn (2007). We thank the American Psychological Association for permission to use and adapt material from Flynn (2000, 2006b). This research was supported in part by grants from the National Institute of Child Health and Human Development, the National Institute on Drug Abuse, and the National Institute of Mental Health (HD047573, HD051746, and MH051361, respectively).
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[email protected] Flynn, J. R. (2006b). Tethering the elephant: Capital cases, IQ, and the Flynn effect. Psychology, Public Policy, and Law, 12, 170–178. Flynn, J. R. (2007). What is intelligence? Beyond the Flynn effect. Cambridge: Cambridge University Press. Flynn, J. R., & Rossi-Case, L. (under review). Beyond skulls and genes: La Plata, Raven’s, and gender equity; also new massive IQ gains. Flynn, J. R., & Weiss, L. G. (2007) American IQ gains from 1932 to 2002: The significance of the WISC subtests. International Journal of Testing, 7, 209–224. Furman v. Georgia. (1972) 408 U.S. 238. Hamm, H., Wheeler, J., McCallum, S., Herrin, M., Hunter, D., & Catoe, C. (1976). A comparison between the WISC and WISC-R among educably mentally retarded students. Psychology in the Schools, 13, 4–8. Horn, J. L. (1967). Intelligence: Why it grows, why it declines. Transaction, 4, 23–31.
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C H A P T E R
F I V E
Remaining Open to Quantitative, Qualitative, and Mixed-Method Designs: An Unscientific Compromise, or Good Research Practice?1 Keith R. Mcvilly,* Roger J. Stancliffe,† Trevor R. Parmenter,† and Rosanne M. Burton-Smith‡ Contents 152 153 154 156 158 159 159 162 170 175 182 182 187 192 194 195 195
1. Introduction 2. Selecting Appropriate Research Method(s) 2.1 Researcher-centered influences 2.2 Contextual influences 2.3 The clinical research paradigm and critical multiplism 3. Quantitative, Qualitative, and Mixed-Method Designs 3.1 Quantitative methods 3.2 Qualitative methods 3.3 Quantitative versus qualitative methods 3.4 Mixed-method designs 4. Collecting Data Using Different Research Designs 4.1 Obtaining consent from people with disability 4.2 Interviewing people with intellectual disability 4.3 Involving significant others 5. Summary and Concluding Remarks Authors’ note References
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Author note: This paper is based on the Doctoral Research of Keith R. McVilly, which was recognized with Australian Psychological Society’s 2005 Thesis Award for a thesis in the field of human relationships. The research was partly funded by an Australian Post Graduate Award, in the Faculty of Medicine, University of Sydney. * Division of Disability Studies, School of Health Sciences, RMIT University, P.O. Box 71, Bundoora, Victoria 3083, Australia { Centre for Developmental Disability Studies, University of Sydney, P.O. Box 6, RYDE, New South Wales 1680, Australia { School of Psychology, University of Tasmania, Hobart Campus, Humanities Building 118, Hobart, Tasmania 7001, Australia International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35005-2
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Abstract The tension between quantitative and qualitative research paradigms are discussed together with the important contribution of mixed-method designs, particularly as they are applied in the field of disability studies. Practical issues inherent in research designs involving participants with intellectual disability are explored, including sample building, participant consent, data collection and data analysis. It is concluded, scientific debate needs to move beyond the dialectic of quantitative vs qualitative research to recognise the merit of a variety of different approaches. The question is not which design is inherently superior, but which design, or combination of designs, best addresses the research question. Key Words: Methodology, Mixed-methods, Qualitative research, Quantitative research, Disability studies.
1. Introduction This is an era of methodological pluralism in applied social science, including the field of evaluation. Multiple frameworks for inquiry abound. . . . The dissonance and discord created by such competition are softened, to a degree, by continuing endeavours to embrace multiple methodologies within the same study or inquiry project (Greene & Caracelli, 1997, p. 5).
In this chapter we discuss methodological issues, from both philosophical and pragmatic points of view, in an effort to resolve some of the dissonance and discord described by Greene and Caracelli (1997). Particular attention is paid to the design and application of mixed methodologies, given their growing importance to research generally (Denzin & Lincoln, 2005; Greene & Caracelli, 1997; Johnson & Onwuegbuzie, 2004; Teddie & Tashakkori, 2003) and, specifically, to the field of disability studies (O’Day & Killeen, 2002; Schalock, 2001; Switzky & Greenspan, 2006). An enhanced understanding of the capacities and limitations of quantitative, qualitative, and mixed-method designs will better equip researchers to be of service to people with disabilities and the communities for whom they conduct their research. Importantly, a better understanding of the different methodological approaches, and how they can be utilized, will contribute to the establishment of a valid, reliable, trustworthy, and robust evidence base that will increase understanding of what it means to be a person with disability, and enhance the provision and evaluation of policy, services, and strategies intended to promote quality of life (QoL) for people with disability. The purpose of this chapter is to present a range of issues that, in particular, new investigators in the field of intellectual disability need to consider when planning a research or evaluation project. To this end, we discuss how quantitative and qualitative methods relate to each other and
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can coexist. Techniques for soliciting quantitative and qualitative data from participants with intellectual disability are addressed. We also discuss the scientific rigor required for the reliable analyses of these data, their valid interpretation and application. We begin by examining the factors that can influence a researcher’s selection of a particular methodology. The clinical research paradigm and critical multiplism are then critiqued. The key elements of quantitative and qualitative research methods are outlined, compared, and contrasted. Research strategies incorporating mixed-method designs are proposed as a means of addressing the complex questions and methodological issues that arise in research relating to people with intellectual disability. Finally, we address issues concerned with sample building, participant consent, data collection, and data processing.
2. Selecting Appropriate Research Method(s) When selecting appropriate methodology, the researcher needs to be cognizant of the complexity of the issues that influence his or her decision. In Fig. 5.1, we portray the relations among the researcher’s ontological and epistemological perspective, his or her professional formation and stance toward the subject matter, the research questions posed, the context in which the researcher conducts and reports the research, and the research design ultimately selected. Also, it needs to be noted that in the field of disability studies, research is commonly conducted in circumstances where clinical questions predominate and the researcher seeks to discover -method Mixed designs
Subjectivism Constructivism Objectivism Ontology
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Figure 5.1 A theoretical representation of the relationship between the critical factors contributing to the selection of a research design.
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knowledge that will enhance understanding of individuals, groups, service, and social systems for the purpose of promoting health, well-being, and quality of life. For these reasons, many projects take place in the context of applied research in which the researcher not only seeks to understand what is happening and why it is so, but also what can be done to make a difference that will be recognized and valued by the stakeholders. It is these multiple rationales for research within the one project that can benefit from an understanding of different methodologies and, in particular, multimethod designs.
2.1. Researcher-centered influences The selection of a method or combination of methods to be applied in a research project will be influenced by the researcher’s ontological perspective. That is, how the researcher conceptualizes reality or the essence of that which is the subject of his or her inquiry (Crotty, 1998). For example, the researcher could consider this question, ‘‘is friendship for people with intellectual disability to be conceived as an objective phenomenon to be measured and its presence or absence in the lives of the participants explained in relation to a variety of other phenomena, such as social network size or social activity?’’; or alternatively, ‘‘is friendship to be understood as a subjective reality, the qualities of which, as experienced by individuals, provide a more meaningful description of its essence and in turn give rise to a greater understanding of that phenomenon?’’ In the first instance, the researcher could collect survey and observation data on a large scale to establish a numerical profile of the participant population’s social networks and related activities (e.g., Emerson & McVilly, 2004). In the second instance, the researcher could focus on collecting narrative, interview data to profile the participants’ expectations and experiences, from their personal perspective (e.g., McVilly, Stancliffe, Parmenter, & Burton-Smith, 2006a, 2006b). As another example, in seeking to understand dementia, the researcher could focus on objective changes in the participants’ skills over time, as measured on standardized assessments (e.g., Aylward, Burt, Thorpe, Lai, & Dalton, 1997). Alternatively, the researcher could examine changes in both the objective and subjective experience of the participants (and his or her significant others) as the effects of the dementia progress (e.g., Nolan, Grant, & Keady, 1998). The research method or combination of methods selected will also be influenced by the researcher’s epistemological perspective. That is, how the researcher believes he or she can best develop an understanding of reality (Crotty, 1998). To this end, a researcher could adhere to a school of objectivism, subjectivism, or constructivism. Objectivism would suggest reality is best understood to exist independently of consciousness; reality possesses an intrinsic meaning that can be uncovered by systematic methods that give
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rise to the revelation of an ultimate, clearly discernable and measurable truth. Subjectivism would suggest meaning is imposed on an object by the subject observing it (the researcher); the object has no meaning in or of itself, only that created by the researcher. Alternatively, constructivism would assert that while there is no objective truth waiting to be discovered, meaning is not the sole prerogative of the researcher. Rather, ‘‘scientific truth’’ and meaning emerge in and through the researcher’s engagement with the subject of his or her inquiry. That is, meaning is not discovered, but constructed. In the context of the examples previously given, the researcher needs to decide if friendship or dementia is to be conceptualized in terms of absolute reality to be discovered, if what is to be known is to be essentially the interpretation of the researcher, or if knowledge and ultimately understanding of friendship or dementia is to emerge from an interaction between the researcher and the participants. The ontological and epistemological perspectives adopted by the researcher can be shaped by the discipline in which they have been formed. Nonetheless, it could be argued that the individual researcher’s ontological and epistemological perspectives themselves influence his or her choice of discipline and career path. Practically speaking, researchers commonly apply the methodologies with which they have been equipped by their training. For example, these methods might include experimental inquiry, ethnography, grounded theory, or discourse analysis. Furthermore, within these methodologies, researchers will commonly have a preferred method or methods with which they feel most confident and comfortable: laboratory-based experimental work, participant observation in naturalistic settings, unstructured or semistructured interviews, questionnaires incorporating rating scales, focus groups, case studies, or life histories. So too, researchers will have preferred means of analyzing data, such as statistical analysis that is either descriptive or inferential, content analysis, or thematic analysis. Importantly, the researcher’s stance in relation to the subject of his or her inquiry can be a further determinant of the method selected. Experimental research in which the researcher seeks to discover new knowledge or replicate previous findings (Thompson, Zarcone, & Symons, 2004); applied or action research in which the researcher aims to maximize the involvement and participation of the consumer of the research findings in the research process (Whitney-Thomas, 1997); or emancipatory research in which the researcher overtly politicizes the research with the explicit intention of bringing about change in policy or service systems (Ramcharan, Grant, & Flynn, 2004) are all possibilities. Finally, the methodology or methodologies adopted by researchers will be influenced by their ultimate aim or purpose for conducting the investigation; what specific questions they have to answer or issues they have to address: to establish a relationship of either association or cause and effect, to describe a phenomenon, to explain a phenomenon, or otherwise promote
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understanding of that phenomenon (Maykut & Morehouse, 1994). It might also be that the audience to which the findings are to be communicated needs to be considered; and whether the intended audience’s understanding of the issue will be best enhanced through quantitative, qualitative, or a combination of findings. In the field of disability studies, there is an increasing imperative for researchers to be accountable directly to people with disability, their families and friends (Balandin, 2003). To this end, mixed-method designs in particular have the potential to generate data that are accessible both to members of the scientific community and a lay audience.
2.2. Contextual influences In addition to the researcher-centered influences, indirect, contextual factors also influence the researcher’s selection of his or her method. For example, historically, research in the field of intellectual disability was dominated by individuals trained in the medical profession and then psychology. Both these disciplines have their research roots in the positivism of the Enlightenment. However, in this postmodern era other disciplines, informed by different traditions, are beginning to make a contribution to research in the disability field. Consequently, in the field of disability-related research, the suitability and sustainability of a single methodology or at least a predominant reliance on quantitative methodology to evaluate and inform developments is being challenged. Disability studies now encompass a broad field of research activities, spanning biomedical, psychosocial, educational, economic, organizational, ethical, and philosophical concerns. For evidence of this, one need only look to the proliferation of Special Interest Research Groups (SIRGs) within the International Association for the Scientific Study of Intellectual Disability (IASSID), which span physical health, mental health, ageing, QoL, parenting, families, profound and multiple disability, comparative policy, ethics, citizenship, and death and dying (see www.iassid.org). The topics of inquiry and the questions to be answered are becoming increasingly complex and cannot always be readily translated into a single null hypothesis to be tested under experimental conditions. They include issues of process and outcome, as well as relations between factors and questions that probe the meaning of phenomena. Furthermore, these issues need to be measured, assessed, and answered from multiple perspectives, including the perspective of people with disability themselves. With the growing importance of outcome-based evaluation, together with the increased priority given to conducting research that promotes continuous quality improvement and accountability to people with disability, their families, and the community generally, methodological pluralism is becoming increasingly important (Schalock, 2001). However, this increasing level of complexity in research endeavors is not unique to scientific inquiry in the field of disability (Pope,
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1995). It has been recognized more generally, for example, in the adoption by the World Health Organization (WHO, 2001) of an integrated biopsycho-social model (Engel, 1977) to understanding the needs of individuals and communities. In seeking solutions to issues on a global scale, WHO is no longer simply concerned with a mechanistic understanding of cause and effect given certain prescribed (controlled) conditions, though these remain important. Rather, WHO is now also asking questions that seek an understanding of people’s experiences in an effort to ensure that policy and strategies are not only functionally effective, but also culturally appropriate and consistent with the values and priorities of the communities in which they are to be implemented. Importantly, these processes also recognize that people possess valuable insights into their own circumstances that have an important part to play in facilitating scientific understanding. Even though some methods are more commonly associated with particular theoretical perspectives, these linkages are by no means universal (Morgan, 1998). Research can employ quantitative and/or qualitative methods, depending upon the subject of inquiry and the circumstances in which the inquiry is to take place. As Walker (1985) asserts, some questions cannot be answered by quantitative methods and others cannot be answered by qualitative ones. For example, in seeking to understand family QoL, it is important that research activities are conducted on a sound theoretical basis, founded on an in-depth knowledge of the lived experience of families with a member, or members, with disability. To this end, qualitative research appears most suited (e.g., Poston et al., 2003). However, to evaluate any proposed theory on a large scale and to establish technologies that will enable us to monitor and evaluate changes in family QoL, within families and across communities, quantitative research appears most suited (e.g., Wang et al., 2006). What appears to be important is that researchers are cognizant of their philosophical position and declare it, and that they can justify their selection of a method of inquiry based on their stated understanding of the nature of the reality they are investigating and the question(s) they are seeking to answer. Such a declaration could have implications for the validation of a study’s findings, which might not only rely on a replication of the mechanics of the methodology, but also on replicating, or at least understanding, the researcher’s a priori perspective. Here is also a caution that the researcher’s a priori perspective or political stance does not adversely influence or bias his or her choice of methodology in relation to the research question or topic of inquiry. Ultimately, valid and reliable scientific conclusions are predicated on the selection of a methodology appropriate to the nature of the inquiry. The scientific rigor of a project and its subsequent conclusions can all too easily be undermined by the selection of a methodology based on the researcher’s political/philosophical stance and without reference to the question posed or the context in which the research is to be conducted and the findings reported.
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In the current chapter itself a research endeavor investigating divergent methodologies and the possibilities for their convergence, we, the authors, need to declare the contextual influences that have shaped our perspective. These include training and postgraduate formation in the disciplines of psychology and education, together with direct experience in the delivery of services to people with disability, families of people with disability, and support networks. The issues raised are influenced by our experiences as both practitioners and researchers, and consequently our philosophical stance, both important in our understanding of people’s objectively assessed needs and their subjective perspective when developing, providing, and evaluating policy and services. Much of the argument presented in this chapter is influenced by a perspective forged in the conduct of applied research in contrast to pure basic research or experimental research activities. However, that is not to suggest the arguments should be restricted in their application to applied research. Finally, the methodologies proposed arise out of a combination of our training in traditional quantitative techniques and a growing recognition of the limitations of these techniques to satisfactorily answer all questions raised in clinical or organizational settings, or in the everyday lives of people with disability and their families; questions that commonly require that which Denzin and Lincoln (2000) describe as ‘‘a deep understanding of the other’’ (p. 2).
2.3. The clinical research paradigm and critical multiplism To understand our perspective and the context in which we are writing, it is necessary to understand the clinical research paradigm. Miller and Crabtree (2000) have suggested clinical research space is created when the researcher focuses on questions arising from clinical experience, and is open to differing possibilities by deploying the full range of qualitative data gathering and analysis methods. Clinical treatment paradigms involve a process of research into the circumstances of the client and his or her presenting problem. Clinicians begin by gathering data using purposeful or information-rich sampling. They seek to gather an objective description of the client’s circumstances, and at the same time endeavor to develop an understanding of how the person experiences his or her circumstances, what those circumstances mean to the person, and how they affect the person’s daily life. Data analysis begins almost immediately. During the initial encounter the clinician establishes a framework with which to make sense of the person’s circumstances. This framework could include both quantitative and qualitative assessment techniques. Using a participatory framework the clinician discusses his or her understanding of the situation with the client, both as a means of developing a shared understanding and validating the clinician’s construction of the client’s perspective. Ideally, the process concludes when both the clinician and the client agree that they have developed a
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sufficient understanding of the situation (i.e, data saturation) to allow for an appropriate course of action to be pursued (e.g., treatment or program development). Researchers investigating group-related clinical issues rather than individual-specific questions have available a number of different research methodologies: experimental approaches (typically pre–post test designs), surveys, documentary systems, field work, action/participatory techniques, and philosophical methods. However, clinical research will usually require the application of critical multiplism, the framework for which assumes an epistemological stance encompassing multiple ways of knowing reality and a preparedness to utilize more than one research paradigm (Coward, 1990). Clinical or applied research questions in particular are best addressed from the perspective of critical multiplism, as such questions are usually complex and multifaceted. Generally, they cannot be satisfactorily addressed in a single study employing a single methodology (Tashakkori & Teddlie, 1998). However, there is a need to balance the desire to address a complex and multifaceted question fully, with the feasibility of effectively managing the data and completing the study. Attempting to accomplish too much in any one study can be overwhelming for the researcher and can make interpretation of the findings difficult. However, narrowing the focus of the inquiry might compromise the integrity of the question. For these reasons, there is evidence in the literature of an increasing use of mixedmethod approaches in an attempt to validly address complex questions, and at the same time reliably manage complex data. This mixed- or multimethod approach has been conceptualized as the ‘‘double helix’’ of research: One strand is quantitative, providing measurement of the construct under consideration, whereas the other is qualitative, addressing issues of context, meaning, and complexity (Miller & Crabtree, 2000). In order to develop an understanding of the validity and reliability of mixed-method designs in the field of disability research, it is first necessary to analyze and to compare critically the traditional quantitative and qualitative approaches.
3. Quantitative, Qualitative, and Mixed-Method Designs 3.1. Quantitative methods 3.1.1. The characteristics of quantitative research methods Quantitative, positivistic research is arguably the most widely understood approach to scientific research and could be considered the dominant research paradigm. It is predicated on the understanding that reality exists ‘‘out there’’ and can be captured and understood with the appropriate technology. Quantitative research is most commonly concerned with
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positivistic inquiry into observable facts. These so-called facts in turn give rise to propositions (i.e., hypotheses), which can be supported or unsupported. When proven, it is asserted that such propositions can be generalized and used to predict similar events or circumstances in equivalent situations (Maykut & Morehouse, 1994). Quantitative research is characterized by the imperative to explain events, particularly in terms of cause and effect. The quantitative research process generally involves establishing hypotheses based on previous research findings. Participants are selected by means of random sampling, intended to create a statistical representation of a specified population. Observations are conducted in controlled settings or under standardized conditions determined by the researcher. The influence of the context in which data are collected can intentionally be minimized (i.e., controlled) and the researcher adopts a stance of objectivity (i.e., they stand apart from the subject of their inquiry). Alternatively, variations in the context can be assessed to evaluate empirically the relationships between the outcomes of the intervention and the contextual variables (e.g., living or support arrangements). Observations are converted (abstracted) into discrete units of data determined by the researcher, which in turn are compared to other equivalent units of data, generally by using statistical analysis. Outcomes are usually reported in an abstract format, typically numeric. These findings are then interpreted as confirming or not confirming a null hypothesis. Replication of the process is viewed as critical to any evaluation of the validity and reliability of the findings. Generalization of the findings and their predictive power are an important measure of their overall worth. 3.2.2. Quantitative research strategies and protocols The current chapter is not designed to explore specific quantitative techniques in any detail, and the reader is referred to more expansive texts (e.g., Dancey & Reidy, 2004; Neuman, 2005; Sarafino, 2005; Vogt, 2006). However, quantitative research strategies include surveys, clinical trials, controlled studies, and meta-analytic studies. Each of these general research strategies can be adapted according to the requirements of the specific investigation. For example, using a survey strategy, data collection could be conducted using a self-report questionnaire (possibly conducted electronically, online), an individual interview, or a focus group. Furthermore, researchers running clinical trials and controlled studies could select participants by means of criterion-referenced criteria or randomized criteria, they might stratify their sample, and might incorporate varying degrees of ‘‘blindness’’ to the intervention (i.e., the degree to which the participants and/or the researchers are aware of the experimental conditions). An essential part of the rigor of any research project is the sampling process by which potential participants are identified and enrolled in the investigation. As Miles and Huberman (1994) observe, the researcher cannot
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hope to study everyone, everywhere doing everything. However, quantitative and qualitative research paradigms adopt different approaches to sample building. In quantitative research, the fundamental process at work is that of probability, premised on random sampling (i.e., sampling based on a set proportion of an overall population or defined strata of a population). Probability or random sampling is statistically based. It is designed to increase the likelihood that the participant group represents the population (or particular characteristics of the population) under consideration. Furthermore, probability sampling provides a basis for the statistical generalization of the findings. That is, random sampling techniques provide the basis for inferences pertaining to the wider population, as represented by the particular sample. Inferences are made in terms of hypothesized relationships between variables relating to association or correlation, as well as those concerned with relationships of cause and effect (Cozby, 1997). Furthermore, it is asserted that random selection and/or random assignment of participants maximizes confidence in statistical inferences by minimizing the possibility of sample bias. Butterfield (1987) noted the difficulty of interpreting research findings where selection of participants or their assignment to different conditions was not random, as is commonly the case in research involving participants with disability in community settings. He asserted: When people who have lived in a special environment are found to differ from others, the question is whether the difference can be attributed to the living arrangement, to the characteristics of the people who were assigned to the living arrangement, or to an interaction of the arrangement with people’s characteristics. Unless people have been assigned randomly to the environments that are compared, no clear interpretation is possible (p. 45).
Butterfield (1987) advocated random assignment as the only way to eliminate bias and so reach scientifically valid conclusions. One suspects that Butterfield conducted his research in an era when ethics committees and protection for research participants were far less rigorous than is quite appropriately the case today. Random assignment is not always ethical or indeed feasible, particularly in applied research. Stancliffe, Emerson, and Lakin (2004) could only identify three research projects with random assignment related to community living in the past 20 years. In Butterfield’s context of quantitative research, this loss of absolute scientific rigor is one cost of moving research studies out of the laboratory and into the real world (Stancliffe, 1995b). However, it is sometimes both feasible and ethical to incorporate random assignment (e.g., to a treatment group or a waiting list control group), where in the longer term participants will have the opportunity to participate in the full range of support, treatment, or intervention options under investigation. For example, McVilly (1991) investigated
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the impact of different occupational options on the adaptive behavior of residents in an institution using random assignment of individuals and a waiting list control group. Likewise, Stancliffe, Harman, Toogood, and McVilly (in press) studied the impact of Active Support techniques on the levels of engagement in everyday activity experienced by residents in community-based accommodation by working sequentially with one group home at a time (random assignment of group homes). Furthermore, it can be argued that researchers can develop a valid understanding of the effects of environments and interventions in nonrandom assignment by thorough and systematic observation of the effects on participants (Rawlinson, 1997). This can be observed in the use of quasi-experimental designs such as time-series and multiple time-series designs, commonly employed in the evaluation of services and educational activities. For an example, see evaluation of the impact of staff training in positive behavior support by Lowe et al. (2007), and evaluation of communication training programs for staff-supporting clients with challenging behavior by Smidt, Balandin, Reed, and Sigafoos (2007). Ultimately the quality and worth of any research rests with its validity. In any appraisal of a study, consideration of validity needs to be made with respect to the methods employed to collect the data, the analytic techniques applied, and the interpretations that are made. To facilitate such an appraisal, validity in quantitative research has been conceptualized in a variety of ways (Anastasi & Urbina, 1996; Onwuegbuzie, 2003). These include consideration of the following: construct validity, the extent to which the findings are consistent with existing theory or other comparable measures; internal validity, the extent to which the researcher can confidently conclude that any change in the dependent variable, or what was being measured, was in fact a direct result of the intervention or setting under investigation; external validity, the extent to which the findings can be confidently generalized to other populations or environments; and the statistical validity of the conclusions, the likelihood of Type 1 error in which the null hypothesis is wrongly dismissed on the basis of a significant result, or Type 2 error in which the null hypothesis is wrongly upheld because results have failed to reach an agreed level of statistical significance.
3.2. Qualitative methods 3.2.1. The characteristics of qualitative research methods In contrast to the quantitative research paradigm, qualitative research is predicated on a postpositivist understanding that asserts the existence of multiple realities, which are created in an ongoing dialogue between those who experience them. Consequently, it is asserted, reality can never truly be captured and defined, only approximated. Qualitative research is primarily concerned with deciphering the meaning of reality and social
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phenomena, not predicting them. It is concerned with the meaning events have for the individuals involved in or affected by such circumstances. Qualitative research does not concern itself with objectively establishing cause and effect, but rather elucidating the understanding participants have of the processes giving rise to their subjective experience (Taylor & Bogdan, 1998). As Lincoln and Guba (1985) have suggested, qualitative research is the paradigm of choice ‘‘when the interviewer does not know what he/she does not know’’ (p. 269). Qualitative research is characterized by an exploratory and descriptive focus. Designs are generally but not exclusively emergent, informed by the data as they are collected, and are ideally determined by the participants, not the researcher. Data are usually collected in naturalistic settings, acknowledging that meaning is tied to context. The process generally commences with a personal encounter between the researcher and the participants in which the research question is given form. The research process usually involves an examination of people’s words and actions in narrative or descriptive ways, closely representing the situation as experienced by the participants and minimizing any abstraction of the data. The qualitative research process also concerns itself with the context of where, when, how, and by whom the data were collected. Outcomes are generally reported in the form of rich descriptive case studies or narrative as generated by the participants. These processes can be seen at work in the Schneider, Wedgewood, Llewellyn, and McConnell (2006) research, which examined the experiences of families supporting adolescents with disability. The analysis of in-depth interviews identified internal and external challenges faced by families and three adaptive strategies that they employed. From these findings, the authors formulated recommendations for service providers working with families supporting adolescents with disability. 3.2.2. Qualitative research strategies and protocols As with quantitative research, there are a variety of approaches available to the qualitative researcher, including phenomenology, ethnography, grounded theory, and discourse analysis. Each of these qualitative approaches can be adapted according to the requirements of the specific investigation. For example, researchers using a phenomenological approach might utilize audio- or video-recorded conversations, or written anecdotes. Researchers using ethnography could employ participant observation or unstructured interviews. Recruitment of participants in qualitative research is based on theoretical or purposive sampling. This is not to be confused with opportunistic or convenience sampling, which lacks scientific rigor. Purposive sampling is nonstatistically based and is designed to ensure that the participants selected are expert in the phenomena being investigated. It also ensures that their data will provide the greatest breadth and depth of experience of the
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phenomena under consideration, for the population of concern. Importantly, it is not the goal of purposive sampling to create a random sample from which results can be generalized statistically. Rather, it is intended that the phenomena of concern be represented accurately and in the greatest detail possible (Punch, 1998). Rice and Ezzy (1999) identified a number of sampling strategies consistent with theoretical sampling that are suitable for use in qualitative research involving people with intellectual disability. Typical case sampling is used where participants are identified on the basis of either statistical normality or a consensus view that they can present an average or typical account of the phenomenon under consideration. Extreme or deviant case sampling involves recruiting participants who can provide distinctive or contrasting insights into the phenomenon under consideration. Critical case sampling is used where the participants by virtue of their particular life experience or circumstances are identified as having the potential to make significant contributions in developing an understanding of the phenomenon under consideration. Criterion sampling is used where participants are selected on the basis of a predetermined inclusion/exclusion criterion, deemed relevant to the phenomenon under consideration. Stratified purposive sampling is used where participants are extracted from previously defined subgroups of a population with specific characteristics. Snowball or chair sampling involves initial participants identifying other participants who might have had similar or contrasting experiences. The final method identified by Rice and Ezzy is opportunistic sampling or convenience sampling, where people are involved as and when they come to the attention of the researcher. This technique lacks scientific rigor and can give rise to data that cannot be reliably interpreted. Given the difficulties often faced by researchers when seeking participants with disability, there is a high risk of opportunistic/convenience sampling influencing recruitment processes. To guard against this eventuality, researchers need to be very clear in defining inclusion and exclusion criteria. As well they should pay close attention to the populations from which they seek to recruit participants and should have a well-developed rationale as to why they are recruiting from these populations. For example, does the organization from which participants are to be recruited provide services to a representative sample of people with disability, or was it selected because the organization was most amenable to involving their clients in the research? Were the participants simply those who could read and respond to the publicity material independently, or where staff were supportive of the project? Were the participants simply those who could speak for themselves? This last issue is one which should be of major concern to all researchers in the field of disability, especially those involved in participatory or emancipatory research activities. With the increasing imperative to conduct research that supports people with disability to speak for themselves, we
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risk marginalizing the perspective of people with profound and multiple disability, who are not always active participants in the self-advocacy movement and whose communication support needs can pose a practical barrier to participation in research. Just as we cannot assume that nondisabled people can speak for people with disability, we should not assume that the views or priorities of people with, for example, mild intellectual disability or intermittent support needs reflect those of people with severe to profound intellectual disability or those with extensive to pervasive support needs. For these reasons, researchers need to use methods involving collaborative activities over prolonged periods of time or observations that can accurately capture the experience of those for whom verbal communication is not feasible. Involving significant others as proxies can provide some useful data. However, there are significant limitations to the validity and reliability of proxy data. These will be discussed later. In qualitative research, Maykut and Morehouse (1994) assert, ‘‘we cannot specify who will comprise our final sample [at the outset of the investigation], since we have not yet discovered what is most important to know about the phenomenon we are studying or who are the best people to inform our understanding’’ (p. 61). This in turn raises the question of how to determine an appropriate sample size. In quantitative research, the application of particular statistical techniques such as power analysis dictates minimum sample sizes as the prerequisite for the valid detection of effects and the appropriate interpretation of the results (McLennan, 1999). However, in qualitative research the number of participants is less important than the richness of the data that they can provide. It is the representativeness of the universe of concepts not the population of people that is crucial. In qualitative research, a sample of one could be sufficient, such as a single case study. However, the established criterion in the literature states that the investigator should continue to recruit participants and collect data until ‘‘data saturation’’ is reached in terms of the investigator gaining an understanding of the phenomena being investigated. In other words, researchers should continue to recruit participants and collect data until they have reached the point of diminishing returns, where additional participants no longer contribute new information, but only reiterate what has been said by previous participants (Glaser & Strauss, 1967; Maykut & Morehouse, 1994; Rice & Ezzy, 1999). Morse and Field (1995) asserted that sample size in qualitative research varies according to the methodology selected. As few as 6 participants may be sufficient for data saturation in a phenomenological study, whereas as many as 30–50 participants could be required when adopting a grounded theory approach. In practical terms, Douglas (1985) suggests that data saturation can be reached with as few as 25 participants. Lincoln and Guba (1985) maintain that an emergent sample can reach saturation with as few as 12 and possibly no more than 20 participants. There is no
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consensus in the literature concerning the number of participants necessary for valid and reliable qualitative analysis. Rather, the major questions of scientific concern are about the rigor with which data were collected, the representativeness of the participants of the phenomena under investigation, the depth of the subsequent analysis, and the relationship between the sample and the assertions that are made. In discussing the theoretical purposes of qualitative research together with the form of the data collection and analysis process, both Maykut and Morehouse (1994) and Datta (1997) emphasize the importance of considering the pragmatics of the available personnel and resources to conduct the investigation. These authors observe that qualitative research can be particularly resource intensive. All things considered, they suggest that the researcher needs to focus on maximizing the depth of the information they gather from individual participants, while at the same time openly acknowledging any limitations in terms of the breadth of their data and any subsequent inferences or theories concerning the focus of the investigation. In qualitative research, data are gathered in the form of words. Similar to quantitative research, qualitative data can be based on participant responses, proxy reports, or researcher observations and can be captured in a written format or electronically. As with quantitative methods, there are a variety of qualitative techniques for processing data. Each of these techniques has well defined a priori assumptions with respect to how data are gathered and the form in which they are to be documented. Each qualitative technique also has preferred formats concerning how data are to be processed and presented. Examples include tables displaying categories in thematic analysis, flowcharts portraying a grounded theory, and specified codes used to annotate data in discourse analysis. Again, the current chapter is not designed to present these techniques in any detail, and the reader is referred to more expansive texts (e.g., Creswell, 1998; Denzin & Lincoln, 2000, 2005; Fischer, 2006; Morse & Field, 1995; Rice & Ezzy, 1999; Taylor & Bogdan, 1998). However, in qualitative research one major procedural issue debated in the literature is the necessity to audio or even video record interviews in order to capture both verbatim transcripts and the context in which data were related. Patton (1990) considered audio recording an indispensable tool for the qualitative researcher. For some areas of qualitative research, it is hard to understand how the rigor of data collection and analysis could be maintained without audio or video recording, such as in the areas of discourse analysis and, possibly, grounded theory. However there are areas of qualitative research where audio recording could prove unethical, for example in methodologies employing participant observation. Moreover, recording could also be impractical, such as in the case of ethnography. Of course, in any instance where audio or video recording is proposed, this should be made clear in the explanation to potential participants of the
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research procedures and the participants’ consent explicitly obtained for the recording. Lincoln and Guba (1985) canvassed a range of issues in relation to audio recording. They suggested written transcripts provide interviewers with a tool to which they can refer back during the course of the interview to double check what the interviewee might have meant by a previous statement in light of a subsequent statement. They observed that some participants are intimidated by recordings and as a consequence might not be candid with their responses. They proposed that handwritten notes are a way of maximizing the environment of negotiation between the interviewer and the interviewee; and that participants can maintain control over what is recorded/written down as part of the official record of interview. The authors further asserted that making a handwritten transcript at the time of the interview forces the interviewer to attend carefully to the interviewee and to clarify what has been said, as and when it is said. However, it could also be argued that the activity of taking accurate notes over a long interview could be distracting for both the interviewer and the participant. Lincoln and Guba recommend that interviews should not be tape recorded unless there are legal or training reasons for doing so. They observed that the advantages of handwritten notes are sufficiently marked to make this technique the data collection mode of choice. However, in an era where recording technology is readily available, relatively unobtrusive, and, arguably, becoming increasingly socially acceptable (digital video recorders seem ubiquitous), the rigor that audio and/or video recording can add to a scientific investigation makes them the superior data collection medium of the twenty-first century. For research involving people with intellectual disability, the possibility that audio recording could be intimidating might remain a concern. However, given their limited literacy skills, if participants wanted to check what had been recorded during the interview they would be reliant upon the researcher to read back the transcript. Audio recording in this instance could therefore be both practical and reassuring for the participants. On a practical note, while electronic recording increases the rigor of data collection, it has been estimated that every hour of recorded interview could be expected to take a minimum of 3 hours to transcribe (Darlington & Scott, 2002), or between 7 and 10 hr for more complex transcription (Patton, 1990). Advances in technology could offer some efficiency. However, even with current speech-to-text software, it is necessary for the human-as-instrument to mediate the transcription accurately and to incorporate contextual data such as commentary on the actions of the participant while talking. As Miles observed, ‘‘qualitative data tend to overload the researcher badly at almost every point: The sheer range of phenomena to be observed, the recorded volume of notes, the time required for write up,
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coding and analysis can all become overwhelming’’ (cited in Lincoln & Guba, 1985, p. 591). As with quantitative research, the value of any piece of qualitative research rests with its validity. Questions of validity and reliability in qualitative data are generally addressed by means of audit trails that enable others to scrutinize the research process as well as the presentation of findings in a format that the individuals whose experience is reported, can themselves evaluate the researcher’s conclusions by recognizing their perception of reality in the researcher’s findings. Generalization of findings is not an inherent priority, as much as accurately and authentically conveying the essence of the participants’ experience (e.g., phenomenology), although the development of theory can also be a goal of qualitative research (e.g., grounded theory). Denzin and Lincoln (2005) propose a reappraisal of the terms used to address issues of validity in qualitative research, preferring the term trustworthiness. They argue that issues of validity are distinctively different from those in quantitative research and consequently the same terms should not be applied. This reappraisal of terminology and the underlying philosophical constructs are consistent with the earlier work of Lincoln and Guba (1985) who proposed the use of terms such as confirmability in contrast to construct validity, credibility in contrast to internal validity, transferability in contrast to external validity, and dependability in contrast to statistical validity. Similarly, Maxwell (1992) discussed concepts such as descriptive validity, the accuracy of the account made by the researcher; interpretative validity, the extent to which the interpretation authentically reflects the perspective of the participants; and theoretical validity, the congruence between the data and the inferences made by the researcher. Maxwell also discussed the extent to which the findings of a study could be applied to inform our understanding of other persons and circumstances which, to some degree, implies a measure of generalization. On this last point, Maxwell’s discussion of validity issues includes the concept of evaluative validity and, by inference, seemingly dismisses research that might otherwise be considered purely descriptive or interpretative, and for which purposes generalization need not be necessary. 3.3.3. Qualitative researchers and how they differ from quantitative researchers Qualitative researchers, far from being independent of their subject matter and the investigative process, have been conceptualized as the very instrument by which qualitative research is conducted. While quantitative researchers look to the validity and reliability of objective instruments with which to gather data, qualitative researchers rely heavily on ‘‘the human-asinstrument’’ for both the collection and analysis of data. They are flexible and adaptable only to the extent necessary to effectively negotiate what Lincoln
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and Guba (1985) labeled an ‘‘indeterminate situation’’ (p. 193). Guba and Lincoln (1981) perceived human social science researchers as effective instruments because of those qualities that enable them to be responsive to all personal and environmental cues relevant to the research questions. They are capable of exploring atypical or idiosyncratic responses not necessarily predicted in the design of the research protocol, and adaptable to changing circumstances and contexts affecting the research process. Positivist, quantitative researchers are suspicious of the ‘‘human-asinstrument’’ approach. They assert that reality is fixed and quantifiable and that a predesigned study employing standardized instrumentation is the best or only way of pursuing an investigation to produce findings that are considered valid and reliable. The alternative, qualitative paradigm asserts that human situations are too complex to be captured by a static, onedimensional instrument. However, Guba and Lincoln stress that the ‘‘human-as-instrument’’ also needs to be trustworthy, trained, experienced, and refined over time. To that end, the ‘‘human-as-instrument’’ has to be just as well calibrated as any tool used by a quantitative researcher. In order to calibrate themselves to deal validly and reliably with complex data, the ‘‘human-as-instrument’’ adopts a ‘‘posture of indwelling.’’ ‘‘Indwelling allows the inquirer to see differences in similar situations and similarities in different situations’’ (Maykut & Morehouse, 1994, p. 29). The posture of indwelling requires the researcher to spend time with participants, win their trust, develop understanding, reflect on new insights, and seek clarification and/or validation of these insights or new understandings. Indwelling is an essential part of the process of qualitative inquiry, part of creating meaning, establishing understanding, and revealing truth in whatever form that might emerge. As Wax (1991) suggests, ‘‘for what the social scientist realises is that while the outsider simply does not know the meanings or the patterns, the insider is so immersed that he may be oblivious to the fact that the patterns exist at all’’ (p. 3). Or as Maykut and Morehouse (1994) assert, ‘‘. . . qualitative researchers understand that they are also subject or actors and not outside the process as impartial observers. Qualitative researchers are exposed to the same constraints in understanding the world as are the persons they are investigating’’ (p. 20). To this end, qualitative researchers actively engage with their participants and develop empathy with them. They reflect on both their participants’ data and their own experience as a person involved in the research. They need to ‘‘indwell,’’ to be completely in tune with the experiences of their participants, but at the same time to develop an awareness of their own biases and preconceptions and how these could influence their understanding and interpretation of the participants’ experiences. This process is sometimes referred to as being ‘‘reflexive’’ (Creswell, 1998; Padgett, 1998). For these reasons, ‘‘qualitative research requires meditative or reflective thinking, rather than calculative thinking’’ (Maykut & Morehouse, 1994, p. 39).
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Practically speaking, Barnes (1992) has outlined four ways in which the ‘‘human-as-instrument’’ can be deployed in research activities: (a) as a complete participant, or a fully fledged member of the group in which their true identity as a researcher is concealed; (b) as a participant observer, involved in the life world of the participants, but where the participants are aware of the researcher’s identity and purpose for being with them; (c) as an observer participant, where the researcher has transient involvement in activities at particular times for the explicit purpose of collecting data; and (d) as a complete observer in which the researcher is insulated from the participants, conducting observations at a distance or at least in no way involved with the participants’ activities. This last alternative is more akin to the stance of the researcher in the positivist paradigm. Although the complete participant approach maximizes the researcher’s access to data, there are practical difficulties associated with the accurate recording of data, as well as ethical concerns in that the researcher conceals his or her identity and his or her purposes from the unwitting participants. By design, participants are not extended the opportunity to provide informed consent to their involvement in the research. The participant– observer approach avoids the problem of concealment and allows for participant consent. However, awareness of the researcher’s presence changes the dynamic of the naturalistic setting and could result in participants not providing a typical representation of their behavior. Alternatively, while the observer as participant approach provides for both informed consent and minimal impact on the naturalistic setting, it poses difficulties for the researcher in gaining access to the full range of the participants’ behaviors and experiences. When considering the merit of research findings, it is evident that we need to examine a wide range of issues, as outlined above. In this postmodern era of research, limiting our consideration to a more traditional appraisal of the sample size and psychometric properties of the tools employed in the study is insufficient. We need to ask questions about how the researchers have self-calibrated, how they have established and documented audit trails, and how they have maintained reflexive rigor throughout the research process. We need to critically evaluate if the appropriate methodology (quantitative, qualitative, or mixed-method) has been used to address the research question.
3.3. Quantitative versus qualitative methods Steckler, McLeroy, Goodman, Bird, and McCormick (1992) contrasted quantitative and qualitative methods on a number of fundamental issues: the research question or the purpose of the research process; the perceived nature of the phenomena being investigated; the technology employed in the research process, together with the relationship of the researcher to the
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data collection process; and the application of the findings. Similarly, Morse and Field (1995) compared quantitative and qualitative paradigms taking into account the ontological and epistemological issues involved, the role values are understood to play in developing an understanding of the world, the nature of cause and effect, the imperative to generalize findings from research, and the expectations concerning the contribution of research findings to knowledge generally. These contrasting issues are summarized in Table 5.1. An understanding of these issues and an appreciation of the various contrasting factors will assist researchers in selecting an appropriate methodology or combination of methodologies with which to conduct their investigations. An important comparison between quantitative and qualitative approaches that needs to be clarified is the stance and role of the researcher. Whereas quantitative researchers consider themselves to be independent of the subject of their research and will go to great lengths to devise methods and instruments to ensure this separation defined in terms of objectivity, the qualitative researcher asserts that they are intrinsically linked to their subject of inquiry while at the same time retaining a distinct identity of ‘‘researcher.’’ As Patton (1990) stated, ‘‘to understand a world you must become part of that world while at the same time remaining separate, being both a part and apart from it’’ (p. 121). For this reason, qualitative researchers engage in a process described by Katz (1987; as cited in Maykut & Morehouse, 1994, p. 123) as ‘‘Epoche´’’: to become aware of prejudices, viewpoints, or assumptions regarding the phenomenon under investigation and then set those aside or at least allow for them in the interpretation of the data. Based on their contrasting characteristics, each paradigm has a welldeveloped critique of the other (Carey, 1993; Kvale, 1994). Quantitative researchers will criticize the comparatively small sample sizes commonly employed in qualitative research projects; the unrepresentativeness of the sample arising from purposive sampling techniques, as opposed to random sampling; and the difficulties with generalizing findings and with replication. Conversely, qualitative researchers will criticize quantitative research for its comparative lack of contextual detail to aid the interpretation of findings; that data elicitation techniques are limited in their flexibility and responsiveness to changing circumstances and priorities of participants; and that response formats often lack sensitivity to the full range of possible human experience. Qualitative researchers will also assert that the quantitative ‘‘gold standard’’—random sampling of participants—is inappropriate in some smaller populations. This indeed can be the case in research involving people with intellectual disability, as it can fail to capture a representative sample. However, it is not a matter of whether one paradigm is superior to the other, or whether the ‘‘subjectivity’’ of the qualitative paradigm is inferior or superior to the ‘‘objectivity’’ of the quantitative paradigm, or vice versa.
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Table 5.1 A comparison of quantitative and qualitative paradigms, adapted from Morse and Field (1995) and Steckler et al. (1992) Research questions
The quantitative paradigm
What is the research The research question is conceptualized as a question or the hypothesis. The process purpose of the is deductive in nature. research process? The research seeks verification of a hypothesis and/or is outcome orientated. There is but one reality, What is the which has an perceived nature independent existence. of the By studying discrete phenomenon parts of that reality in a being investigated logical and sequential (how does the (controlled) manner we world exist)? can come to understand the whole. The researcher is What is the independent of the relationship subject of their between the investigation. researcher and the Objectivity is the phenomenon hallmark of good under research. investigation?
What role do values Values are to be suspended during the research (especially those process. of the researcher) play in developing our understanding the world?
The qualitative paradigm
The research question is conceptualized as a topic of inquiry. It is inductive in nature and seeks to reveal tacit knowledge. It is typically process orientated. There are multiple realities, each constructed from bio-psycho-social interactions. Reality must be studied from the point of view of the individuals involved, in their own context. The researcher and the subject of their investigation are interdependent. Objectivity is not possible. Subjectivity is critical to developing an understanding of the phenomenon and must be systematically incorporated into the research process. Values need to be acknowledged as mediators of meaning and factored into the research process and subsequent interpretation of the findings.
x
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Table 5.1 (continued) Research questions
The quantitative paradigm
Are causal linkages Preceding events can be said to cause or at least be possible and if so, associated with how? subsequent events. Cause and effect follow a lineal pattern.
What technology is Objective measurement which seeks to capture available to be the phenomenon by employed in the means of previously research process, validated scales and other together with the forms of standardized relationship of the measurement which researcher to the stand apart from the data collection researcher. process? What about the intended application of the findings; and issues of generalization?
Explanations from one time and place can be generalized to other times and places.
What does research Research is concerned with verification; proving or have to contribute disproving propositions. to our knowledge?
The qualitative paradigm
Events and the understanding we have of them are multidirectional; the event influences our understanding of the outcome and our understanding of the outcome affects the way in which we conceptualize the event which preceded it. Subjective measurement based on the narrative of the participants as they formulate an account of their experience. Typically data collection is mediated by the researcher’s personal involvement and interpretation. Only tentative explanations can be made about one event in light of another event. The focus is on describing and explaining discrete events. Research is concerned with discovering or developing propositions.
Rather, they represent different forms of knowledge. Quantitative research focuses on investigating and testing established knowledge whereas qualitative research concerns itself with tacit knowledge; ‘‘knowledge based on experiences with them, experience with propositions about them, and rumination’’ (Lincoln & Guba, 1985, p. 196). As Stake (1978) suggested, ‘‘all that is remembered somehow, minus that which is remembered in the
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form of words, symbols or other rhetorical forms. It is that which permits us to recognise faces, to comprehend metaphors, and to know ourselves’’ (p. 6). The importance of tacit knowledge is most evident in the qualitative researcher’s endeavors to apply inductive techniques to identify patterns or commonalities by inference through the examination of specific instances or events. From this process, the qualitative researcher brings knowledge of the unknown into being knowledge of the known (Morse & Field, 1995). This is in contrast with the quantitative researcher who generally employs deductive techniques in which hypotheses are generated based on previous research findings and are systematically tested to see if they are predictive of specific circumstances. The deductive approach is most valuable when there is an established body of knowledge and the constructs and concepts comprising that body of knowledge are clearly identified and can be operationalized in a controlled or systematic manner. Although it can be applied in naturalistic settings, the inductive approach is most valuable when there is a lack of specificity in the body of existing knowledge, or where it is difficult to systematically control the issues or constructs under investigation. As Rice and Ezzy (1999) suggested: if the problem could be precisely defined, if the meanings of the participants were known completely beforehand, if it were clear that a theory would explain a particular experience, if the benefits of the research could be demonstrated with certainty, qualitative research would be irrelevant (p. 191).
The ‘‘objectivity’’ of the dominant, quantitative paradigm has come to be associated with data considered as factual, real, or true and the ‘‘subjectivity’’ of the qualitative paradigm associated with being tentative, less than true, or only partially true. However, ‘‘objective’’ data can also be interpreted as being separate from the ‘‘other,’’ distant, and removed from the participant’s experience and ‘‘subjective’’ data can be interpreted as being intrinsically linked to the participant’s experience (Morse & Field, 1995). As Smith (1997) suggested, whether data happen to be in the form of words or in the form of numbers should not materially affect the process of constructing meaning from them. Furthermore, because of the valuebased, colloquial understanding of the terminology distinguishing quantitative and qualitative paradigms, Lincoln and Guba (1985) proposed that the ‘‘objective’’/‘‘subjective’’ dichotomy be replaced by a dichotomy explained in terms of ‘‘objectivity’’ and ‘‘perspectivity.’’ They suggested that these terms explain more accurately the respective stances of the two approaches. In the final analysis, both quantitative and qualitative data are symbolic and, as Miles and Huberman (1994) assert, neither one is inherently ‘‘harder’’ or ‘‘softer’’ than the other. Both types of data can contribute to exploratory and descriptive research and both can contribute to a greater
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understanding of the phenomena under investigation. More importantly, the question would appear to be: Which paradigm and method, or combination of methods, is best suited to the subject of the inquiry and which will provide maximally valid and reliable answers to questions posed by the researcher or those commissioning the research?
3.4. Mixed-method designs Given that quantitative and qualitative research paradigms deal with different aspects of knowledge and that human experience is so complex, combined methodologies have been proposed (Teddlie & Tashakkori, 2003). Steckler (1989) asserts that the issue is not whether to use quantitative or qualitative methods but rather how these methods can be combined to produce more effective research and evaluation strategies. As Johnson and Turner (2003) propose, when combined appropriately, these methods can be deployed in ways that maximize their complementary strengths and minimize any overlapping weaknesses. Because of the complexity of social phenomena, Phelan (1987) has asserted that it is important that mixed-methods be employed to maximize our understanding of the human experience. In support of this position, Strauss and Corbin (1998) propose that it is through the intentional interplay of multiple methods that researchers are able to construct dense, welldeveloped, integrated, and comprehensive theory. For example, in a study investigating the impact of stigma on the social and emotional outcomes of mothers and children with disabilities, Green (2003) integrated data from surveys, structured interviews, and personal narrative. Consequently, Green was able to both establish the issue as one of concern by quantifying the impact of perceived stigma on mothers and their children and explain this phenomenon directly from the perspective of the participants. Studies such as this further our knowledge by documenting what is happening globally as well as the experiences of the individuals involved, and in so doing provide a comprehensive framework on which to base an effective and meaningful response. However, it must be stressed that mixed-method designs are not to be considered superior to either quantitative or qualitative designs. Nor are they to be viewed as the only or indeed the dominant way for future research, only an alternative. Mixed-method designs have their own strengths and weaknesses (Morse, 2003). Creswell (1994) suggests that mixed-method designs are often (mis) interpreted as attempting to reconcile mutually exclusive ontological and epistemological stances and are therefore wrongly considered to be methodologically flawed. Such misinterpretation can be avoided when the researcher makes clear the particular questions to be addressed by the inquiry and how specific methods are to contribute data to answer those questions. For example, in a study by Bernheimer, Weisner, and
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Lowe (2003), evaluating the effect of an antipoverty initiative on the lives of families supporting ‘‘troubled children’’ with disability, quantitative assessments were made of ‘‘family troubles’’ and ‘‘family sustainability’’ based on scales completed by fieldworkers involved with the families. In addition, qualitative (ethnographic) data were gathered to develop an understanding of the participants’ daily routines, current concerns, and aspirations for the future. It was only through combining these different data sources that sense could be made of the family circumstances, and the multifaceted effects of trying to sustain a daily routine in the face of their family member’s support needs, coupled with low-wage, no-benefit, and episodic employment. 3.4.1. Practical and technical difficulties On a practical level, Mitchell (1986) highlights the difficulty merging numeric and textual data, the weighting of findings from different sources when interpreting data, and ascertaining the contribution of each method when assimilating the results. Further complications can arise when attempting to interpret and reconcile divergent results which, according to Bryman (1992), are not uncommon in mixed-method designs. Bryman asserts that where discrepancies do emerge it is not a question of determining which method, qualitative or quantitative, has given the more accurate result. Rather it is for the researcher to respond to the dissonance by asking more probing questions of the data. Riggin (1997) highlights technical problems associated with combining interpretations based on numeric and narrative data, as well as satisfying the divergent sampling requirements of the two approaches. For instance, the number of participants recruited for a qualitative study might be determined by a ‘‘saturation criterion’’ that is to say the point at which the recruitment of additional participants yields no further insights into the phenomena under investigation, but simply affirms existing findings. This criterion might not be sufficient to meet the numbers required for statistical analysis of a quantitative study. Similarly, the recruitment of participants by means of purposive sampling for a qualitative study would not satisfy the requirements for a random sample in a quantitative study. Carey (1993) asserted that it is imperative to use the different techniques correctly and not to violate basic sampling or other procedural assumptions of both qualitative and quantitative methods. Similarly, Chen (1997) cautioned that mixed-method designs must satisfy the criterion of rigor for both quantitative and qualitative paradigms. Chen further cautioned that in order to achieve satisfactory standards of methodological rigor, mixed-method designs can be resource intensive, take longer to complete and require more researchers with a greater range of skills to be involved. By implication, mixed-method designs are best conducted in team settings, with researchers possessing differing ontological and epistemological perspectives, together with the capacity to sensitize each other to these differing perspectives.
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To maximize their effectiveness and efficiency, such teams need to be able to adopt a highly collaborative interdisciplinary approach to their work or ideally, a transdisciplinary approach. The latter approach involves a mode of work in which team members freely share their skills and expertise, and in which they are prepared to work not only along side each other, but with each others’ methods. Stange, Miller, Crabtree, O’Connor, and Zyzanski (1994) suggested that by using a multimethod approach either sequentially or concurrently, researchers can improve the efficiency of research processes and increase the likelihood of reaching conclusions that are relevant, valid, and, importantly, generalizable. Here the researchers need to reflect on what is meant by a mixed-method design, and what precisely will be ‘‘mixed.’’ At the simplest level, results from two separate enquiries can be combined, with one set of results used to validate the other or to provide additional information to assist with the interpretation. Alternatively, data can be combined during the analysis. At its most complex level, the method, data, and findings can be combined, giving rise to a full mixed-method approach (Brewer & Hunter, 1989; Fielding & Fielding, 1986). When establishing mixed-method approaches, Bryman (1992) proposed a number of options for the researcher to consider: (a) using one method (quantitative) to identify appropriate participants, and another method (qualitative) to identify and define the context in which the data are collected; (b) using complementary methods to address the strengths and weaknesses of both paradigms, that is, the limited depth in exploration of issues that could arise from a quantitative study, and the limited scope for the generalization of findings that could arise from a qualitative study; (c) combining results to provide for triangulation of the data and validation of the findings; (d) combining the concerns of the researcher, usually defined a priori, with those of the participants, identified post hoc; and (e) linking the microconcerns of the individual to the macroconcerns of the wider population. However this task is undertaken, it is clear that the researcher or ideally the research team requires a high level of experience and expertise in the application of both quantitative and qualitative methods. To this end, it would appear necessary that the traditional separatist approach to teaching quantitative and qualitative research methods be replaced by more holistic curricula in which researchers are exposed to the contrasting and complementary aspects of both paradigms. To assist researchers with the decision-making process, Creswell (1994) described three models of mixed-method design. The first involves keeping the two enquiries separate until such time as the results are discussed and the conclusions are to be made. For example, a service/system-wide survey might be circulated and a series of in-depth focus groups are also conducted. In the second model, two forms of inquiry are deployed together, but one method is defined as primary and the other secondary. An example is participants being asked to rate their responses on a series of standardized
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scales, the results of which form the basis of the analysis. However, provision is made for participants also to include ‘‘comments’’ and these comments are later used to elucidate the findings from the quantitative questionnaire. The third model involves the two approaches being deployed together, as equal partners in the inquiry. Building upon this last approach, Caracelli and Greene (1997) described how a mixed-method design can be either conceptualized as a ‘‘component design’’ or an ‘‘integrated design.’’ Component designs are characterized by different methodologies being implemented as discrete aspects of the inquiry. Integrated designs are characterized by the various methods being combined throughout the inquiry. Chen (1997) suggested that mixed-methods can be flexible and are able to provide both in-depth and generalizable findings. He proposed three criteria to consider when selecting an appropriate methodological configuration: (a) What sort of information is required to answer the research question; (b) What is the current availability of data to inform the research process; and (c) To what degree can the environment in which the inquiry is to take place be controlled? How answers to these questions can be used to determine the selection of a quantitative, qualitative, or mixed-method approach is detailed in Table 5.2.
Table 5.2 The selection of a quantitative, qualitative, or mixed-method approach, adapted from Chen (1997) Qualitative approaches
Mixed-methods approaches
The interpretation of a large Information is data set is enhanced with required to be individual case scenarios or intensive and exemplars contextual The literature reports mixed Low availability of findings, not satisfactorily credible data and explained by context theory While some elements of the The environment environment can be and/or subject of controlled, individual the inquiry is open participants, or facets of to variation and/ individuals, remain subject or is not readily to significant variation controlled which could influence the interpretation of the findings
Quantitative approaches
Information is required to be extensive and precise High availability of credible data and theory The environment and/or subject of the inquiry is not open to variation and/or is readily controlled
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Whatever design is selected, the imperative must be to identify the contextual circumstances of the inquiry and select an appropriate method or compilation of methods suited to that context. For example, Morocco, Aguilar, Clay, Brigham, and Zigmond (2006) employed a mixed-method design to identify ‘‘good high schools for students with disabilities.’’ They analyzed quantitative data that were already available, such as student achievement scores. In addition, they generated new quantitative data in the form of rating scales completed by students and teachers. They also gathered qualitative data by means of reviewing existing school documents such as policies and procedures; conducting interviews with students, teachers, and parents; and conducting direct observations of student experiences in and out of the classroom. These data were then analyzed and the results used to answer five broad research questions. To effectively communicate the research findings to the schools, a series of case studies were then developed to illustrate how the policies, procedures, and approaches of the different schools affected the educational experience of their students. To address some of the difficulties associated with developing mixedmethod designs, Morse (1991) proposed the ‘‘priority sequence model.’’ In advocating this model, Morse acknowledges that it might be theoretically possible to give equal priority to both quantitative and qualitative approaches in any one investigation. However he qualifies this by saying that such an approach can complicate sampling techniques, data analysis, and the interpretation of different data. The ‘‘priority sequence model’’ is intended to assist the researcher in making decisions and in allocating resources appropriately to both quantitative and qualitative components of the investigation. This model helps to ensure that the requirements of rigor for both are met and provides a rationale for interpreting one data source in light of another. The ‘‘priority sequence model’’ requires the researcher to make two decisions. First, one form of inquiry is determined to be the principal method and the other, the complementary method. Second, it is decided that one method, either the principal or the complementary method, will be conducted as a preliminary investigation and the other, as a follow-up study. An example of four such ‘‘priority sequence designs’’ is provided in Fig. 5.2. 3.4.2. Triangulation of data and evaluating rigor A further consideration is the processing of data and its triangulation. Triangulation involves the use of at least two research techniques to address the same research problem (Morse, 1991). However, quantitative and qualitative paradigms use triangulation for different purposes and therefore mixed-method designs need to take account of the differing theoretical perspectives and practical requirements. In the quantitative paradigm, triangulation is concerned with the validation of data gained from one source by comparing it with the same or
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Complementary method
Principal method Quantitative
Qualitative
Used in a preliminary study
A qualitative study (e.g., a focus group) is conducted as a forerunner to a quantitative study, to identify issues to be investigated or variables to be manipulated
A quantitative study (e.g., a questionnaire) is conducted to identify or group participants for a qualitative study
Used in a follow-up study
A qualitative study (e.g., in-depth interviews) is conducted to explain or expand results of a quantitative study
A quantitative study (e.g., an experimental inquiry) is conducted to test a theory or generalise the findings of a qualitative study
Figure 5.2
Examples of four ‘‘priority sequence designs,’’ adapted from Morse (1991).
comparable data gained from another source. However, in the qualitative paradigm ‘‘triangulation is not a tool or strategy for validation [of data], but an alternative to validation’’ (Flick, 1998, p. 230). Rather, multiple methods are designed to add rigor, breath, depth, complexity, and richness to the inquiry. In qualitative research, triangulation is viewed in the context of a display of multiple, refracted realities simultaneously, not a sequential checking of data in an effort to define objective reality (Fontana & Frey, 2000). It is a technique designed to ‘‘measure overlapping, but different facets of a phenomenon, yielding an enriched, elaborated understanding of that phenomenon. . . . elaboration, enhancement, illustration, clarification of results from one method with the results of another method’’ (Greene, Caracelli, & Graham, 1989, pp. 258–259). Field and Morse (1985) have suggested that triangulation in the qualitative context can take place either sequentially or simultaneously. Sequential triangulation is used when the findings of one method are used to plan the strategy for the next and so forth as an overall method unfolds. Simultaneous triangulation takes place when two methods are deployed at the same time with minimal interaction between the two during the data collection, but are drawn together at the point of interpretation. Rice and Ezzy (1999) identified four possible strategies for the triangulation of data. These involve triangulation of data sources in which multiple informants with multiple perspectives are sourced; the methods employed in which multiple strategies are used to elicit data; the researchers involved in which multiple researchers working in a team are used to collect data; and theory applied to the analysis in which case multiple perspectives are used to analyze and interpret the data. Triangulation of data is an important part of establishing the trustworthiness and rigor of the method and its subsequent findings. When
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evaluating the rigor of a study there are a number of levels of evaluation to consider. In the first instance, there is the theoretical rigor of the study. Theoretical rigor focuses on the connections between the current research and any existing literature, including accepted methods of investigation and previous findings. Second, there is the methodological or procedural rigor. This is concerned with the quality of the project’s audit trail. Is there clear documentation of what was done and the means by which the findings were reached? How were participants identified? How were the researchers and their purposes presented to the participants and consent obtained? How were data elicited and recorded and how were any unexpected occurrences addressed? How were data coded and analyzed? Third, there is interpretative rigor, which is concerned with the means by which data were analyzed and the conclusions reached. Were appropriate analytic techniques used, bearing in mind the research questions and the form and quantity of data collected? Do the results accurately represent the understanding, events, and actions of the participants? Finally, there is a question of reflexive rigor. Reflexive rigor is concerned with the degree to which the research acknowledges that social research takes place in a political environment, and is shaped by the interests, priorities, and agendas of those involved, including the researcher, the participants, and other stakeholders such as those providing funding and other resources. Ethical research will declare these reflexive issues. As with both quantitative and qualitative research, the validity of mixedmethod designs is a matter of great concern to both the researcher and those who seek to make use of research findings. However, as outlined above, given that the notion of validity differs between quantitative and qualitative paradigms, there is need to develop alternative ways of thinking about and establishing validity in mixed-methods designs. Onwuegbuzie and Johnson (2006) propose the adoption of the term legitimation. The authors propose nine types of legitimation for evaluating mixed-method research. These include (a) sample integration: Does the combination of methods produce higher level inferences than would be achieved by single methods alone? (b) inside–outside: Are the perspectives of both the participants and the researcher represented? (c) weakness minimization: Are the limitations of one approach compensated by the strengths of the other? (d) sequential: Are the inferences independent of the sequence of the methods, or could a different result have been achieved if the sequence of methods had been varied? (e) conversation: Do the methods and their results have a meaningful dialogue within the study, informing each other? (f ) paradigmatic mixing: Have the researcher’s perspectives been successfully combined or blended and any dissonance eliminated? (g) commensurability: Do the inferences reflect a mixed world view? (h) multiple validities: To what extent have the fundamental requirements been met for valid research within each of the qualitative and quantitative components? and (i) political legitimation: To what extent do those reading or using the research draw on both
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quantitative and qualitative components to inform their understanding? This typology of mixed-method legitimation is currently in its infancy. To assess its discriminative power it would be useful to apply the typology in a systematic way to the review of mixed-method manuscripts submitted to peer-reviewed journals. To facilitate this, they could be formulated in a similar way to the guidelines for critical review of qualitative studies and those for quantitative studies developed by Law et al. (1998).
4. Collecting Data Using Different Research Designs 4.1. Obtaining consent from people with disability When building a sample, the issue of voluntary, informed consent is a major consideration in any research endeavor, be it quantitative, qualitative, or a mixed-method design (Dinerstein, Herr, & O’Sullivan, 1999). Gaining voluntary, informed consent is one safeguard designed to minimize the exploitation of the participants, including exploitation by means of appropriating participants’ knowledge or personal story without their understanding the purposes or intentions of the researcher (Fontana & Frey, 2000). Voluntary, informed consent is also a means by which researchers can safeguard the integrity of their findings by fostering the cooperation of the participants with the research protocol. Nonetheless, consent protocols have been predominantly formulated in the context of positivistic, quantitative research and commonly within the domain of medical research. Typically, these protocols have sought to establish voluntary, informed consent by means of participants providing signed written agreements to participate in a predetermined procedure premised on the basis of an explicit hypothesis. The nature of quantitative research is such that most often potential benefits and risks to participants can be reasonably foreseen and explained to them. With the increasing use of qualitative and mixed-method designs, there needs to be some reappraisal of consent procedures. Within qualitative research explicit hypotheses are not formulated. Research designs can be emergent, determined by the researcher in negotiation with the participants as the research is undertaken. Consequently, potential benefits and risks to participants are not as readily determined as they might be in quantitative research. Also, mixed-method designs can be inherently complex and not easily explained. Furthermore, the longer term structure of the protocol is not always determinable at the outset. For these reasons it could be argued that fully informed consent on the part of participants at the outset of a research project is an unrealistic expectation, driven by legalistic imperatives without consideration of the participants’
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reality. Rather, consent should be considered an emergent phenomenon, with protocols in the methodology designed to reappraise the participants’ consent to involvement as the research progresses through different phases. This phenomenon of emerging consent was reported by Knox, Mok, and Parmenter (2000) in their study involving multiple interviews with young adults with disability concerning relationship networks. The researchers commenced each session by discussing what had occurred in the previous session, what was proposed for the current session, and if the participant wanted to continue involvement in the project. A further complication is that whereas the typical aim of quantitative research is to gather aggregate data about a group of participants, the typical aim of qualitative research is to capture the essence of the participants’ personal experiences on an individual basis. As a consequence, although the anonymity of individual participants in quantitative research can usually be maintained, this is not necessarily the case in qualitative research where individual comments frequently form the basic unit of data analysis and samples can be comparatively small. Reference to potential difficulties maintaining anonymity under these circumstances should be included in any plain language statement and accompanying consent form for research involving qualitative or mixed-method designs. When participants have intellectual disability, issues of voluntary, informed consent can be especially complicated. Participants may be susceptible to the influence of others who might be involved in the research process and whom they could perceive to be in positions of power (e.g., parents, teachers, work supervisors, or the researchers themselves). In addition, comprehension difficulties, together with the limited experience and understanding participants with disability might have of the research process, can pose barriers to the provision of voluntary, informed consent (Berg, 1996; Clements, Rapley, & Cummins, 1999; Dalton & McVilly, 2004; Weisstub & Arboleda-Florez, 1997). Consequently, strict adherence to the Nuremberg Code of 1949 could exclude the participation of many people with intellectual disability from any scientific research, since the code clearly establishes that the voluntary and fully informed consent of the human subject is absolutely essential (Nuremberg Code, 1949, Article 1). However, it is important that every effort is made to address ethical impediments to research involving people with intellectual disability, including difficulties satisfying the requirements for consent (Dalton & McVilly, 2004; Iacono, 2006); ‘‘we must recognise that some people cannot give informed consent, but that efforts must still be made to develop ethical practices so that they are not entirely excluded from research’’ (McCarthy, 1998, p.143). The needs and interests of people with intellectual disability are all too often unrepresented in the general research literature and ‘‘the notion that individuals [with intellectual disability] can speak with the authority and from the validity of their own experience is
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often overlooked or undervalued’’ (Stalker, 1998, p.13). The views of the self-advocacy movement on this point have been made clear through the philosophical and political position given expression in the phrase: ‘‘nothing about us, without us’’ (Charlton, 1998). Consistent with this, the Canadian Tri-Council Policy Statement on Ethical Conduct Involving Humans explicitly states: Although ethical duties to vulnerable populations preclude the exploitation of those who are incompetent to consent for themselves for research purposes, there is nonetheless an obligation to conduct research involving such people because it is unjust to exclude them from the benefits that can be expected from research. (Medical Research Council of Canada, Natural Sciences and Engineering Research Council of Canada, & Social Sciences and Humanities Research Council of Canada, 1998, Section 5C).
To this end, the revised Helsinki Declaration (World Medical Association, 2000) provides for the consent of a ‘‘legally authorized representative’’ to facilitate participation in research activities (Article 24). The Helsinki Declaration also specifies that where proxy consent has been obtained, the investigator must still obtain ‘‘assent’’ from the participant (Article 25). That is, even where formal permission to proceed has been given by a person legally entitled to give that approval (e.g., the parent of a child or an appointed guardian for an adult), the uncoerced cooperation of the participant is still required, and where they indicate they do not wish to participate they must not be forced to do so. Australia’s National Health and Medical Research Council (NHMRC) also provides guidance on these matters (NHMRC, 1999, Section 5). The NHMRC guidelines stress the importance of balancing potential benefits against risks and undue burdens. The guidelines clearly state that research can only be conducted if deemed to be ‘‘in the best interests of the person’’ and that consent must be obtained directly from participants, wherever possible, or where this is not possible, from a guardian. Importantly, even where a guardian has given consent, if a person with intellectual disability does not provide clear assent, this must be respected and that person’s involvement should cease. Given that some understanding of the research process is arguably a prerequisite for informed consent to be given by participants, it would appear appropriate that the assessment of understanding and any necessary educational activities concerning research processes take place as part of the preresearch, recruitment and enrollment process. To this end, the process proposed by Arscott, Dagnan, and Kroese (1998) might have some utility. These authors accompany the presentation of a plain language information sheet with a questionnaire to establish if the potential participants can: (a) describe the research, (b) state what participation involves, (c) identify
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reasons they might not want to participate, (d) state what they could do if they did not want to participate, (e) describe the limitations of confidentiality, and (f ) indicate if they were happy to proceed. Such preparticipation consent processes emerge not only as important to the ethical and legal requirements governing research (Dalton & McVilly, 2004), but also as integral to establishing the validity and reliability of the research activities and, consequently, the research findings. Such procedures appear applicable across quantitative, qualitative, and mixed-method designs. Concerning the use of proxy consent, it is important to remember that a person’s capacity to consent can vary. For example, there might be different social and environmental circumstances including familiar and unfamiliar situations and variability over time, both increasing capacity such as with life experience and decreasing capacity such as with fatigue or failing health. For these reasons, a person might rely on a proxy to give consent on one occasion, but this might not be necessary on a different occasion. Where questions of capacity arise, researchers do have a number of formal assessment tools to use. Sturman (2005), in a comprehensive review of this issue, asserted that the ‘‘gold standard’’ for these tools is that they assess the person’s capacity to understand facts, weigh alternatives, appreciate the context in which the decision is made, and make choices. However, prior to relying solely on proxy consent, researchers would be advised to consider the suitability of a process involving supported decision making (Bach & Rock, 1996). This process begins with the assumption that many people with disability can be autonomous decision makers when provided with appropriate assistance. Processes involving supported decision making in research demonstrate the researcher’s respect for each participant and have the potential to maximize a participant’s opportunity for self-determination. Where proxy consent is necessary, researchers need to ensure that proxies involve as much as possible, the persons on whose behalf consent is to be made. Furthermore, a proxy decision to involve or not involve the person with disability in the nominated research activity could be made on the basis of substituted judgment; that is, a decision made in accord with what might be expected of the person if he or she were left to make the decision. This could be particularly applicable in the area of social research. Alternatively, where it is not possible to make an informed assumption about what decision the person might make (e.g., based on a previous decision the person has made in a similar or related circumstance), or there is a legal imperative to do so (e.g., in the case of medical research), a decision needs to be made on the basis of the person’s best interests; that is, how the person acting as proxy views the safety and interests of the person on whose behalf the decision is being made (Freedman, 2001). Researchers need to ensure that proxies themselves act in a voluntary capacity, free from coercion, and from a position of being competent and
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informed of the proposed research process. Importantly, the researcher must be satisfied that the proxy is free and able to act in the best interests of the person with disability and that he or she does so without consideration of any possible personal gain or advantage (Weisstub & Arboleda-Florez, 1997). Here it should be noted that Clements et al. (1999) assert that no person can provide a proxy response in the sense of representing another person’s true wishes. However, it could be argued that a proxy can adequately represent a participant in terms of his or her best interests. The circumstances in which people with intellectual disability find themselves must also be taken into account when considering if and how to involve them in research. On this point, the Australian NHMRC highlights the need for caution when working with vulnerable people, especially those who live independently of their family, in institutional settings, or other types of formal care. Importantly, the NHMRC requires that any information provided to participants must be provided at their level of comprehension, concerning the purpose, methods, demands, risks, inconveniences, or discomforts, and possible outcomes of the research, together with the voluntary nature of their involvement and their freedom not to participate or to withdraw at any time without repercussions for their current services (NHMRC, 1999, Section 1.7). Some of the other ethical and practical issues surrounding consent include the following: How do researchers recruit participants? Is it more appropriate that researchers approach people directly or use intermediaries such as families or service providers? How do researchers explain to participants with comprehension difficulties what their agreement to participate would involve? Importantly, how do researchers explain the purpose or application of the research and how personal data are to be used? Individuals with intellectual disability might be able to consent to discussing a particular topic with which they have some personal familiarity, but can they provide informed consent to the analysis, interpretation, and subsequent publication of the data that they report? For these reasons, it could be important for the researcher to provide potential participants with tangible examples of the questions that are to be asked or topics to be covered, video demonstrations of peers with disability involved in research activities, and examples of previous reports that have been published. These would ideally include examples of plain language reports or summaries of reports. One model of how relatively complex information can be summarized in plain language is to be found in documentation reporting a major national survey concerning the life experiences of adults with intellectual disability carried out on behalf of the UK National Health Service by the Social Care Information Centre, a division of the UK Government Statistics Service (Emerson, Malam, Davies, & Spencer, 2005). These documents were prepared in close
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consultation with self-advocates. They use plain language, complemented by a variety of pictorial aids to be used when discussing the information. Furthermore, researchers should consider the settings where the initial consent is to be obtained and where the subsequent research activities are to be conducted. Researchers need to consider how they are to become involved in the lives of participants, especially in the collection of qualitative data about sensitive personal issues such as friendship, and then disengage with minimal emotional impact on their lives (Matysiak, 2001; Stalker, 1998). They need to plan and have in place follow-up mechanisms where the participants’ disclosure of past events or current feelings concerning the topic of the inquiry give rise to psychopathology, manifest as anxiety, depression, anger, or even aggression. Finally, there needs to be a mechanism to deal ethically and legally with any disclosure by participants concerning past or current instances of exploitation or abuse. Such issues appear of particular importance to researchers using qualitative or mixedmethod designs where a personal and often prolonged encounter between the researcher and the participant is integral to the research procedure, and the data collection process remains open to the participant volunteering whatever experiential information she or he considers relevant.
4.2. Interviewing people with intellectual disability Difficulties with comprehension and expressive language skills on the part of people with intellectual disability pose significant problems for the researcher requiring direct responses from participants, be they qualitative or quantitative in nature (Dattilo, Hoge, & Malley, 1996; Perry, 2004; Perry & Felce, 2002; Stancliffe, 1999). As a consequence, when seeking to explore and understand issues of concern in the daily lives of people with intellectual disability, often the people themselves are not consulted. This lack of consultation has been justified with the assertion that individuals with intellectual disability are unable to participate in research in accord with the demands of scientific rigor. However, Wadsworth and Harper (1991) concluded that the literature supports the position that adults with moderateto-severe intellectual disability and coexisting limitations in their expressive language skills can provide accurate and reliable information about their moods, thoughts, preferences, and living environments when questions are presented in a structured and supported format. Freedman (2001) observes that the literature reflects a growing recognition that people with disabilities can speak for themselves and serve as effective agents of change in their own life circumstances. It is now generally agreed that people with intellectual disability should be involved in the evaluation of their own life experience and the services they access (Azmi,
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Hatton, Emerson, & Caine, 1997; Cooney, 2002; Emerson et al., 2005; Knox et al., 2000; Lowe, 1992; McVilly, 1995; McVilly et al., 2006a, 2006b; Pearson, Wong, & Pierini, 2002; Pitfield-Smith & Davey, 1990; Ramcharan & Grant, 2001; Ramcharan et al., 2004). Failure to actively engage people with disability in the investigation and evaluation of issues affecting their life ‘‘is to continue to condone the exclusion of retarded (sic) people from taking an active role in decisions affecting their own lives’’ (Hogg & Mittler, 1987, p. 283). On this point, given recent developments with the human genome project, Kuna (2001) has cautioned ‘‘. . . we may be facing a time where people with disabilities are seen as a disease and the potential for that disease not to be born’’ (p. 158). It is therefore an imperative that researchers and clinicians not only report accurately the interests and priorities of people with disability, but also that they clearly portray people with disability as competent participants in and contributors to the development of both disability-specific services, and the community in general (McVilly, 2002). To this end, mixed-method designs could offer some solutions to these complex methodological and ethical issues, increasing the opportunities for the direct participation of people with disability in research and at the same time promoting both the reliability of data collection and consequently the validity of research findings. Sigelman, Spanhel, and Schoenrock (1981) noted that the propensity of the individual to acquiesce (i.e., exhibit a tendency to agree with the interviewer or to provide stereotypical positive responses, regardless of their personal opinion) is observed to be negatively correlated with IQ. Also, Heal and Sigelman (1995) reported that people with intellectual disability demonstrate ‘‘nay-saying’’; that is, responding ‘‘no’’ to oppositely worded items and subsequently contradicting themselves. As with acquiescence, the tendency to ‘‘nay-say’’ correlates negatively with IQ. This response pattern is particularly pronounced when discussing social taboos (e.g., ‘‘Are you allowed to hit people?’’/‘‘Is it against the rules to hit people?’’). Sigelman et al. (1981) demonstrated that acquiescence could be minimized by the use of ‘‘either/or’’ questions, as an alternative to ‘‘yes/no’’ question formats. However, in 1983 these same authors (Sigelman et al., 1983) reported a systematic response bias with either/or question formats used with young children. The authors reported a strong tendency for respondents to reply with the last of the two response options offered, showing a recency response bias. The potential for recency response bias to undermine the validity of self-report data therefore remains a matter of concern. To assess the significance of any such bias in an interview, the periodic repetition of questions in a reversed format is recommended. Because of these difficulties, Stancliffe (1999) screened potential respondents for their propensity to acquiesce, utilizing a pair of oppositely worded ‘‘yes/no’’ questions concerning choice of clothing. The author then
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excluded potential participants who exhibited a tendency to acquiesce or exhibit a recency response bias. Various theories have been developed to explain the comparatively high level of acquiescence and ‘‘nay-saying’’ among respondents with intellectual disability. However, the factors most likely involved appear to be a combination of impaired cognitive development giving rise to a lack of understanding of the question and consequently the propensity to ‘‘guess yes.’’ These factors operate in conjunction with a strong desire to be socially acceptable to the interviewer and therefore yield a propensity to provide what is believed by the respondent to be a ‘‘positive’’ or ‘‘desired’’ response (Shaw & Budd, 1982). Furthermore, Booth and Booth (1996) observed that a multitude of factors, including lack of self-esteem, learned compliance, social isolation, and experiences of oppression can all impede people’s fluency in interviews. However, Rapley and Antaki (1996) asserted that the acquiescence bias of people with intellectual disability is not a simple phenomenon, and is not satisfactorily explained in terms of characteristics inherent in the person. They concluded that any analysis of the acquiescence bias of people with intellectual disability must include consideration of the organization and structure of the interview or assessment tool in question, and the degree to which the interview process was itself ‘‘disabling.’’ This call to review interview and other research technologies would be consistent with the findings of Heal and Sigelman (1995). Finlay and Lyons (2002) concluded that acquiescence is most likely in situations where either the researcher’s question is too complex or ambiguous, or where due to the limited life experiences of the participants they simply do not have sufficient information in order to express an opinion on the topic that has been put to them. In the latter circumstance, researchers should respect the participants’ life experiences and should avoid forcing them to formulate an opinion based on a hypothetical or abstract scenario, as might be the approach were they interviewing persons in the general population. Similar problems have been discussed in the literature with respect to the observed reluctance on the part of people with intellectual disability to criticize or provide a negative appraisal of people they know and the services they access (Lowe & dePavia, 1987). The respondents’ reluctance to criticize may arise not only as an attempt to elicit positive appraisal from the interviewer, but also from an underlying concern that if they criticize their current situation, they may be returned to a previous situation that they found to be even less favorable (Flynn, 1986). Open-ended questions have been found to be more effective at generating valid and reliable responses than closed questioning techniques (Lovett & Harris, 1987; Sugg, 1987; Wyngaarden, 1981). However, a combination of either/or and open-ended questioning techniques were successfully employed by Lowe and dePavia (1988) and Shanley and Rose (1993), with the addition
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of question reversal to evaluate the reliability of the response. Here though, the use of such questions can come at the cost of making the task too hard for people who, if they were given options or specific questions, might be able to provide a valid answer based on their personal experience. A number of strategies have been developed to augment interview techniques that are predominantly reliant upon verbal input and verbal responses. Wadsworth and Harper (1991) assert the utility of line drawings. Similarly, Cummins (1997) recommends the use of Likert scales using facial icons to facilitate the rank ordering of emotional responses. Similar methods, using pictorial response formats, were used by Emerson et al. (2005) in their national health survey. However, the experience of the present authors is that this methodology remains problematic and is limited in its application to eliciting responses from individuals whose intellectual disability is assessed as only borderline to mild (McVilly, 1995). In a study, March (1992) reported that photographs increased the rate and intelligibility of responses of participants. However, the author cautioned ‘‘. . . an increase in intelligibility [of responses] is no guarantee that participants were answering the question that the researcher thought they were being asked’’ (p. 127). Concerning the overall design of a suitable interview format, it would appear that standardized questions in conjunction with predetermined response categories are useful in eliciting evaluation data from people with intellectual disability and that they may well enhance the validity and reliability of response (Dattilo et al., 1996; McVilly, 1995; Schalock & Begab, 1990; Schalock & Keith, 1993). However, Patton (1990) maintained that highly structured assessment formats, as are common in most quantitative research, limit the expression of the respondents by requiring them to fit their knowledge, experience, and feelings into the researcher’s categorization system. He emphasized the need to use qualitative interviewing techniques that enable respondents to express themselves in their own language. These recommendations are consistent with those of Wyngaarden (1981), who proposed less structured interview formats for people with intellectual disability. In particular, Wyngaarden suggested that researchers avoid questions that require respondents to report specifically on quantifiable data such as the time and frequency of events. With the consent of participants, these data can be obtained at a later time from a proxy respondent such as a family member or support professional. Wyngaarden (1981) recommended the use of simply phrased, openended questions that provide a clear and unambiguous focus for the respondent, and which avoid any suggestion of a ‘‘preferred’’ or preformatted response. Wyngaarden illustrated the difficulties that respondents with intellectual disability can experience with multiple choice answer formats, especially where comparative or evaluative responses are required (e.g., ‘‘a big problem,’’ ‘‘a small problem,’’ ‘‘not a problem’’). This is in contrast to the findings of
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Lovett and Harris (1987) who found limited success with the use of three-point scales. Wyngaarden also recommended the use of standardized questions to enhance the reliability of instrumentation, but in the interests of ensuring that respondents with intellectual disability have understood the question, alternative question formats such as rephrasing should be allowed. However, it remains the case that, as researchers, we tend lack creativity and continue to reproduce the Likert-type response scales that have been used with participants in the general population. Even with the inclusion of pictographs, such scales remain too abstract for many participants with intellectual disability and other cognitive impairments. When developing our research technologies, we need to develop scales and other means of eliciting participant responses that use more readily comprehendible prompts, such both static and animated imagery, real-life scenarios, and in situ research techniques. Patton (1990) argued that for participants with intellectual disability, questions should focus on the present, as historical recall may not be accurate and abstract aspirations about the future are highly speculative. However, on this last point, we cannot identify any literature suggesting people with intellectual disability do not recall past events of significance or that they cannot hold hopes and aspirations for the future. Our clinical experience is that people might exhibit difficulty conceptualizing aspirations for the future in areas where they have had limited past experience: ‘‘Where else would you like to live?’’ ‘‘Where else would you like to work?’’ Nonetheless, where the issue is within the realm of their previous experience, the expression of future aspirations need not be problematic, for example, ‘‘what would you like for dinner tonight?’’ ‘‘where would you like to go on the weekend?’’ Patton (1990) also cautioned against the use of multipart questions or questions requiring multipart answers: ‘‘How well do you know and like the staff?’’ or ‘‘Tell me about living here and if you like it.’’ One strong theme that emerges from the literature is the critical role of rapport between the interviewer and respondent. Williams and Asher (1992), and Antaki, Young, and Finlay (2002) have emphasized the importance of active listening skills, avoidance of interruption, even if only to clarify a statement, as well as the exercise of patience. They have commented on the need for multiple sessions with respondents. They observed that generally speaking, people with intellectual disability do require longer to establish a trusting relationship with the interviewer, greater exposure to the issues in question, longer to consider the issues, and longer to generate an unambiguous response. Likewise, it may take the interviewer longer to develop an understanding of the idiosyncratic response style of respondents, including their vocabulary, grammar, and syntax. All these considerations appear equally relevant to those conducting quantitative, qualitative, or mixed-method designs involving data collection directly from participants with disability.
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4.3. Involving significant others Atkinson (1986) discussed the advantages of interviews with significant others prior to meeting with the primary respondent with disability. Atkinson proposed that this strategy generates information that can be included later to personalize structured interviews and provide prompts in semistructured or unstructured interviews. However, in terms of mixed-method designs, the involvement of significant others can provide a means of obtaining quantitative data that might not otherwise be accurately reported by participants with intellectual disability, while still allowing for people with disability to contribute data to the research that conveys their lived-experiences, opinions, and personal expectations or aspirations. However the involvement of third party, significant others in mixed-method designs raises several issues for consideration. First, there is an ethical issue concerning the consent of primary respondents to their issues being discussed with a third party, albeit that a third party is already involved in some form of familial or support-based relationship. To overcome this problem it might be possible to meet with the person to gain consent to speak with significant others prior to actually beginning the interview process. This procedure would also help address previous suggestions concerning the need to meet with respondents on multiple occasions in order to develop effective rapport prior to exploring personal issues. Second, there is the potential that inclusion, or simply awareness of such information from third parties on the part of the interviewer, could bias the interview process with the primary respondent. However, potential bias could be minimized if interviews commenced with strict, nonpersonalized open questions and more personal information were only included on an ‘‘as required basis,’’ to prompt discussion. Careful consideration would need to be given to developing some standardized phrases to incorporate personalized information, thereby minimizing the introduction of potential response bias into the interview. Concerning the use of data obtained from significant others acting as proxies for the informant with an intellectual disability, the literature urges caution. Schalock and Keith (1993) found satisfactory levels of agreement between respondents with intellectual disability and their proxies on objective indicators of QoL. Similarly, Stancliffe (1999) found acceptable levels of proxy/client agreement using the same instrument, although Rapley, Ridgway, and Beyer (1997) reported problems with staff/client agreement on one subscale of this instrument, the Quality of Life Questionnaire (Schalock & Keith, 1993). Cummins (1998, 2002) found evidence of significant person/proxy agreement on objective indicators of a person’s QoL, but reported disagreement on the subjective indicators of QoL (i.e., those concerning the rating of the importance of certain factors to the
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subject and the person’s satisfaction with his or her own current circumstances). Similar observations have been made by Felce and Perry (1995), Stancliffe (1995a), and Hatton and Ager (2002). It would appear that the use of standardized questionnaires can give rise to satisfactory levels of subject/proxy agreement on global scores. However, observed differences at an item level remain problematic, with reliability varying significantly as a function of the particular items in question (McVilly, Burton-Smith, & Davidson, 2000; Stancliffe, 1995a, 1999). Furthermore, any interpretation of subject/proxy agreement needs to be evaluated in light of the effects of the systematic bias contained in Cummins’ so-called ‘‘gold standard’’ for the measure of life satisfaction, which is a propensity for respondents to report or presume satisfaction with life at 75% of scale maximum, plus or minus 2.5% (Cummins, 1995, 1998, 2002). This phenomenon is proposed by Cummins to reflect an innate homeostatic state of the human person, skewed toward a positive psychological appraisal of life satisfaction in an effort to cope with life’s experiences. For respondents with extensive to pervasive support needs (American Association on Mental Retardation, 2002), observation-based methods remain the investigation tool of choice (Bilken & Moseley, 1988; Edgerton, 1984; Kaufman, 1984). Of course, such techniques need not be limited to the laboratory setting or indeed to a fixed venue such as a person’s home, classroom, or place of work. Drewett, Dagnan, Tonner, and Maychell (1993) developed a combined interview and observation technique, utilizing a ‘‘neighborhood walk.’’ This process was devised in order to bring their respondents into real-time contact with people and places that formed part of their everyday life and, in so doing, increase the likelihood of obtaining valid responses and reliable observations of actual behavior in relation to those people and places. A similar in situ interview technique was employed by Hagner, Snow, and Klein (2006) in their investigation into home ownership for people with intellectual disability. Here though, in selecting the venue for research, the ethical dilemma of intrusion into the lives of participants arises as an issue of concern and must be sensitively managed by the researcher. The ethical dilemma arising from the researcher’s presence can, in part at least, be addressed by the collection of data by persons other than the researcher who would ordinarily be present. This could include the personparticipant keeping a diary. Alternatively, with the consent of the person, family members, support staff, or significant others could record predetermined data. However, in such circumstances, a balance needs to be struck between providing the de facto research associates with sufficient information to enable them to collate appropriate data while at the same time maintaining a degree of naivete´ so as not to bias their data collection. Also, problems recruiting and utilizing in situ research associates arise, depending upon the sensitivity of the data to be collected and to which degree the research
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associates are themselves possible confounding variables. This might be the case where the research associates would need to record data on their own interactions with the person.
5. Summary and Concluding Remarks Researchers have a responsibility to conduct work that is ethical (Council for International Organizations of Medical Sciences, 2002; Dalton & McVilly, 2004; European Parliament, 2001; Griffin & Balandin, 2004; Nuremberg Code, 1949; World Medical Association, 2000). An important consideration in judging the ethical merit and scientific value of a research project is the integrity of its methodology. In this chapter we have proposed that a significant determinant of both the ethical merit and scientific value of a research project, and its subsequent findings, is the selection of an appropriate methodology: quantitative, qualitative, or mixed-method design. We have discussed a range of factors influencing the selection of a particular research design, including the philosophical and political stance or bias of the researcher, his or her training and professional background, together with the context in which the research is to be conducted and the findings communicated. Furthermore, we have observed that with the increasing diversity of researchers conducting work in the field of intellectual disability, including researchers with disability themselves, there is an expanded array of research methods and designs being employed. This proliferation and mixing of methods is not limited to scientific work in the field of disability studies, but is consistent with research trends in the wider scientific community (e.g., WHO, 2001). The commonalities and differences between quantitative and qualitative methods have been reviewed, together with the ontological and epistemological tensions that emerge when attempts are made to integrate these paradigms. Limitations on the interpretation, generalization, and application of research findings based on qualitative or poorly designed quantitative studies have been discussed. Particular attention has been paid to the advantages of critical multiplism and mixed-method designs to address the complex questions that characterize research and evaluation in the field of intellectual disability. These mixed-method approaches, we have argued, bring with them the potential to both discover new knowledge and at the same time test and verify that knowledge (Tashakkori & Teddlie, 1998). In this chapter, we have examined issues associated with sample building and participant consent. The feasibility of gaining fully informed consent from participants with intellectual disability at the outset of a research project, especially one involving qualitative or mixed-method designs, has been challenged, and the concept of emergent consent proposed as a more
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honest and viable alternative. We discussed philosophical and practical considerations concerning data collection, data processing, and data triangulation in both quantitative and qualitative designs. Although there are clear differences between how these issues are addressed across quantitative and qualitative methods, this dissonance and discord (as described by Greene & Caracelli, 1997) need not be an impediment to the careful construction and implementation of trustworthy (valid and reliable) mixed-method designs ( Johnson & Onwuegbuzie, 2004). Indeed these methods should be viewed as complementary techniques that, as Rawlinson (1997) argues, ‘‘can yield contrasting and illuminating information’’ (p. 54). Furthermore, we have argued for a reappraisal of the traditional way in which quantitative and qualitative methods have been taught separately, favoring, rather, more integrated and holistic curricula. We conduct our research in a postmodern world. As Schalock (2001) asserts, ‘‘the postmodernist approach is characterised by minimising the role of science-based, quantitative research methodology and maximising a social constructivist, qualitative and pluralistic approach’’ (p. 12). However, we must be cautious that we do not simply accept all approaches to research as valid and reliable in all contexts, or assert that we can select and combine research methods according to our individual philosophical or political perspectives. Be it the use of quantitative, qualitative, or a mixed-method design, scientific rigor and the underlying ethical priority to be accountable to people with disability, their families, and the community whose concerns we are investigating, demands that we carefully match our selected methodology to the questions posed for investigation, and the context in which the research is to be both conducted and reported. Furthermore, as professional scientists we need to work within the boundaries of our personal competencies, maximize opportunities for collaboration in order to broaden the skill-base available for our research endeavors, and only interpret and represent our findings within the perspective and limitations of the methodology we have adopted. These are the hallmarks of good research practice. Anything less is an unscientific compromise.
Authors’ note The authors would like to thank two reviewers whose advice on an earlier version of this manuscript was invaluable.
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Wadsworth, J., & Harper, D. (1991). Increasing the reliability of self-report by adults with moderate mental retardation. Journal of the Association of Severe Handicap, 16, 228–232. Walker, R. (1985). An introduction to applied qualitative research. In R. Walker (Ed.), Applied qualitative research. Aldershot, UK: Gower. Wang, M., Summers, J., Little, T., Turnbull, A., Poston, D., & Mannan, H. (2006). Perspectives of fathers and mothers of children in early intervention programmes in assessing family quality of life. Journal of Intellectual Disability Research, 50, 977–988. Wax, R. (1991). Doing fieldwork: Warning and advice. Chicago, IL: University of Chicago Press. Weisstub, D., & Arboleda-Florez, J. (1997). Ethical research with the developmentally disabled. Canadian Journal of Psychiatry, 42, 492–496. Whitney-Thomas, J. (1997). Participatory action research as an approach to enhancing quality of life for individuals with disabilities. In R. Schalock (Ed.), Quality of life, Vol. II. Application to persons with disabilities (pp. 181–198). Washington, DC: AAMR. Williams, G., & Asher, S. (1992). Assessment of loneliness at school among children with mild mental retardation. American Journal on Mental Retardation, 96, 373–385. World Health Organization [WHO] (2001). International classification of functioning, disability and health [ICF]. Geneva, Switzerland: Author. World Medical Association (2000). The Helsinki Declaration: Ethical principles for medical research involving human subjects. Helsinki, Finland: Author. Wyngaarden, M. (1981). Interviewing mentally retarded persons: Issues and strategies. In R. Bruininks, C. Meyer, B. Sigford, & K. Lakin (Eds.), Deinstitutionalisation and community adjustment of mentally retarded people (Monograph No. 4). New York: AAMD.
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C H A P T E R
S I X
Active Support: Development, Evidence Base, and Future Directions Vaso Totsika, Sandy Toogood, and Richard P. Hastings Contents 1. Introduction 2. What is Active Support? 2.1. A brief history of Active Support 2.2. Active Support as a philosophy of care 2.3. Active Support as a system of planning and review 2.4. Structural components of Active Support 2.5. Functional aspects of Active Support components 3. Staff Training in Active Support 3.1. Workshop training 3.2. On-site interactive training 4. Recent Developments in Active Support and the Training Model 5. Conceptual Issues 5.1. Active Support and Normalization 5.2. Active Support and ABA 5.3. Active Support and other approaches: PCP and PBS 6. Setting the Context for Evaluating the Effects of Active Support Implementation 7. Evidence Base for Active Support 7.1. Evaluation studies of Active Support 7.2. Indirect evidence related to Active Support 8. Discussion and Future Directions References
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Abstract Active Support is a person-focused model of care for people with an intellectual disability who live in community-based small homes. The model aims to improve each person’s quality of life by maximizing participation in all types of activities of daily life with appropriate support from staff. In this chapter, we describe the basic characteristics of Active Support, its relationship with School of Psychology, Bangor University, Adeilad Brigantia, Bangor, Gwynedd, LL58 2AS, UK International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35006-4
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2008 Elsevier Inc. All rights reserved.
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Normalization theory and Applied Behavior Analysis, and the evidence base for Active Support interventions. The methods available for training support staff and the latest developments in the Active Support model are presented. We conclude by discussing issues related to the adoption of Active Support by residential services and policymakers, and identifying dimensions that require further exploration. These future challenges include the translation of the Active Support model into real-world settings and long-term maintenance of intervention effects.
1. Introduction Active Support is a person-focused model of care for people with intellectual disabilities living with staff support in small community-based residential group homes. The main goal of Active Support is to increase the opportunities for participation in meaningful, age-appropriate activities for people with all levels of ability with appropriate support from staff. As a system for organizing life in the group homes, Active Support has a strong philosophical basis that promotes an ‘‘ordinary lifestyle’’ (King’s Fund Centre, 1980). The Active Support model includes a system for organizing activities and support for daily participation, a system for training staff to provide the right level of support to facilitate participation, and a system for promoting the residents’ personal development through goal setting and skill learning. The basic technology was developed more than 25 years ago (e.g., Felce, 1989; Felce & Toogood, 1988; Mansell, Felce, Jenkins, de Kock, & Toogood, 1987), but the approach has been updated and refined (e.g., Jones et al., 1996a, Booklet 1; Mansell, Beadle-Brown, Ashman, & Ockenden, 2005). New training methods and materials have been developed (e.g., Brown, Toogood, & Brown, 1987; Jones et al., 1996a,b,c,d,e,f, Booklets 1–6; Mansell et al., 2005; Toogood, 2004) for use in a number of applied studies across a variety of community residential service settings (Bradshaw et al., 2004; Jones et al., 1999; Mansell, Elliott, Beadle-Brown, Ashman, & Macdonald, 2002; Stancliffe, Harman, Toogood, & McVilly, 2007). A review seems timely given the amount of development that has taken place and the level of interest shown in the United Kingdom and other countries. Our aims in preparing this chapter are threefold: (a) to describe Active Support, including its development, essential components, core concepts, and historical and current influences; (b) to review evidence from previously published studies on the effectiveness of Active Support; and (c) to consider possible implications and future directions for Active Support for the research and service communities. In the sections that follow, we describe Active Support’s philosophy as a model of care and its content
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as a system for organizing life in community group homes (Section 2). The structural components that make up Active Support are described in detail along with their functional equivalents from everyday life (Section 2). The methods available for teaching staff of community residential homes to implement Active Support are briefly presented in Section 3. Section 4 describes the latest developments in the model and Section 5 discusses the relationship between Active Support, Normalization theory, Applied Behavior Analysis (ABA), and other current approaches. Section 6 reviews research evidence on engagement and staff support, which are the main outcomes used in evaluating the impact of Active Support. Section 7 describes the evidence available to date from evaluations of Active Support implementation in community residential settings. Finally, Section 8 identifies areas for future development of the model.
2. What is Active Support? 2.1. A brief history of Active Support The fundamental components of Active Support were conceived, developed, and evaluated between 1981 and 1986 in England’s first small community home for persons with severe or profound intellectual impairments. A demonstration scheme, the Andover Project, was itself conceived, developed, and subsequently evaluated by a team of researchers. The Andover Project extended previous research in the Wessex region of England and was antecedent to a large-scale program of deinstitutionalization throughout the United Kingdom during the 1990s. Active Support procedures were used during 1985–1990 in a separate demonstration project in which the Special Development Team (SDT; Emerson et al., 1987) assisted local service providers to develop small community homes for persons with intellectual disabilities and challenging behaviors. The fundamentals of Active Support owe much to the insight of three researchers in particular: Jim Mansell, David Felce, and Judith Jenkins promoted the concept of engagement as a major determinant of quality of life. They expressed emerging social policy (e.g., Department of Health and Social Security, 1971, 1981) and policy guidance (e.g., King’s Fund Centre, 1980) as practical outcomes defined by the concept of engagement (i.e., purposeful and meaningful interaction with the social and material environment). This was a significant contribution, both conceptually and practically. One of the early model’s greatest strengths was its practical demonstration of how to focus attention on what people with intellectual disabilities can do and learn to do, as opposed to emphasizing the restrictions imposed on them by their disability ( Jenkins, Felce, Mansell, de Kock, & Toogood, 1987).
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2.2. Active Support as a philosophy of care Active Support is a philosophy of care that has at its center the creation, support, and maintenance of valued lifestyles expressed in terms of image, expectation, and the moment-to-moment lived experience of daily life. A core aim is to create opportunities and provide support and assistance for meaningful participation in the full range of everyday life-defining activity, irrespective of the degree of a person’s disability ( Jenkins et al., 1987; Mansell et al., 2002). Individually and collectively, staff involved in implementing Active Support are encouraged to value each person as being unique, capable of development and growth, and able to contribute toward enhancing the quality of their own lived experience and the lives of others. Staff are orientated toward a social model of support and encouraged to interpret their own role principally as planners, enablers, and teachers. Staff plan by organizing the residential environment to promote to the fullest extent possible active participation by each person in the full range of everyday life-defining activities. They enable by providing every person the support and assistance each requires on a moment-to-moment basis to participate in activities and by bridging the person’s skills gap where necessary. They teach by differentially reinforcing behavior that corresponds with active participation (what a person can already do) and use both incidental and formal teaching programs to establish new behavior where necessary.
2.3. Active Support as a system of planning and review A philosophy of active participation requires a technology for its implementation. Active Support provides, therefore, a multicomponent paper-based system for planning, implementing, and evaluating: (a) the organization of the residential environment; (b) individualized programs of care, support, opportunity, and learning over the short and medium term; and (c) subsequently, the collective experience of life in the home environment. Jenkins et al. (1987) provided the first full description of the multicomponent planning and review systems that later came to be known as Active Support. Other early accounts can be found in Felce (1989), Mansell et al. (1987), and McGill and Toogood (1994).
2.4. Structural components of Active Support In this section, we describe the component systems of Active Support. Each component serves a particular function and works in conjunction with the others. There is a hierarchical nature in the component systems where implementation of the higher ones (such as Individual Plans) can be achieved by successful implementation of subordinate components (e.g., Opportunity Plans).
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2.4.1. Routines and rhythms Many activities of everyday life occur cyclically and most ordinary households have a system in place for ensuring everyday activities get done and everyone’s interests are satisfied. In residential houses for people with intellectual disabilities, a similar system is developed to map these everyday activities and make the routines for each person individual by involving residents as much as possible in the construction of activity plans and by taking account of individual preferences (Felce et al., 2002), thus avoiding institutional treatment of residents. Routines and rhythms are a hidden part of Active Support as activity mapping normally occurs when devising Activity Support Plans (see later description). The utility of activity mapping is based on the notion that routines are functional (e.g., Saunders & Spradlin, 1991) and that it is the rigidity and ownership of routines that are potentially problematic rather than routines per se (Goffman, 1961). Mapping daily activities to key times of the day or week produces a framework of ‘‘anchored’’ activity that has the effect of making the task environment more predictable (especially when many staff are involved), and brings a higher degree of autonomy and control to the house residents. Timetabling and individualizing routines and rhythms of daily living means the routines belong to the people whose house it is rather than the staff whose job it is to facilitate them. Routines should be flexible, however, preserving the benefits of stability without introducing the constraints of rigidity. Flexible routines help ensure that important life sustaining activities such as shopping, cooking, and cleaning are carried out in a timely fashion and to an acceptable standard. 2.4.2. Activity Protocols Activity Protocols are scripts that describe the way frequently occurring activities should be carried out. They are written in the form of task analysis, breaking down the activity into its individual components. While task analysis has mainly been used to teach new skills (e.g., Tucker & Berry, 1980), the main aim here is to ensure consistency in the way each resident experiences an activity—for example, the resident washes the dishes in the one way he or she knows, and this does not change according to which member of staff supports him or her—and to facilitate successful participation. Thus, the activity is broken down to as many steps necessary for the resident to accomplish at least a part of it (Mansell et al., 1987, p. 202; 2005, p. 53). Activity protocols specify a frequency and standard for each activity and can include a risk assessment. Some protocols are person specific, such as a personal morning routine. Others are activity based and therefore more generic, such as mealtimes or washing dishes. Systematic use of the activity protocols by all staff and regular revision of the protocols helps residents to learn, from carrying out their routines consistently, to become gradually more autonomous and independent within and across their routines.
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Residents can also avoid learned helplessness from being corrected according to staff preferences for how to do an activity rather than its functional content. 2.4.3. Activity Support Plans Activity Support Plans provide a method for (a) flexibly planning activities over a 3- to 4-h period, (b) allocating staff to provide support for persons taking part in those activities, and (c) tracking each person’s lived experience. A common format involves the use of a printed page for each day or shift. Each page has a column for each person resident in the home. Beside each column is a space to identify which staff will support which person through a particular activity or sequence of activities. Regularly occurring ‘‘anchor’’ activities for each person are preprinted on the page at the time at which they are approximately expected to occur. Thus, the printed page for each day looks a little different from the others. Two additional columns list activities that ordinarily ‘‘must’’ be done on the day and a menu of options for the day. Staff meet together briefly throughout the day to decide prospectively who will support whom in which activities. They populate all of the white space between the anchor activities with incidental activities and activities drawn from the ‘‘must do’’ and ‘‘options’’ menu. Every resident has a range of activities available throughout the day and a member of staff available to provide the support required. The procedure of selecting the activities to be included in the Activity Plans should include residents as much as possible, to make sure that activities reflect individual preferences. For residents with limited or no verbal ability, participation in the activity selection procedure can be facilitated using picture-based scheduling and manding procedures. Staff implement the plan alongside the residents and keep track using a simple tick chart called the Participation Index. The Participation Index spans one week at a time. Activities that occur on a regular basis are listed with space to add further activities as required. Staff record an event whenever a person takes part in a planned activity. Using these data (with each person acting as his or her own control), staff can monitor the rate and distribution of participation in activity within and across weeks and across activity domains. The benefits of prospective activity planning mean: (a) the task demand environment is made more predictable, controllable, flexible, and capable of accommodating individual activity and scheduling preferences; (b) residents know what they should be doing; (c) everyone knows what everyone else should be doing; and (d) there is a plan to come back to when things go wrong. Activity Support Plans help provide persons with intellectual disabilities with all of the benefits of routine without the constraints of rigidity. The Participation Index helps individual members of staff view each person’s lived experience as a whole and over time. Missed opportunities, overexposure, or unevenly loaded schedules are quickly identified and corrected and the effects
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monitored. Additional learning and practice opportunities may be targeted through the medium- and short-term goal planning systems described below. 2.4.4. Community contacts monitoring An ‘‘ordinary lifestyle’’ involves being part of the community and making use of community facilities. Community participation is important for an individual’s social inclusion, a significant dimension of quality of life (Schalock, 1996). Community presence is the first step toward this goal and Active Support puts in place a system for monitoring frequency and duration of community access. Planned community activities are preprinted on a form where staff later record whether the activity took place and its duration. Reviewing data for each person each week, staff look for stability and balance in each person’s lived experience of community involvement— stability in the frequency and duration of community contacts over successive weeks, and balance in the distribution of community contacts over the days of the week and across different types of community involvement. Monitoring community contact in this way means staff get a picture of each person’s overall lived experience of community involvement and can (a) generate relevant targets for change, either directly or through mediumand short-term goal planning systems (see later description), and (b) easily assess the impact of targets for increased or altered community involvement. 2.4.5. Individual Plans Individual Plans provide an individualized focus and sense of direction over the medium term by prioritizing a range of target outcomes and stating them in terms that are specific, manageable, achievable, realistic, and timed (SMART). Outcomes, selected by the person and significant others, cover a range of life domains and address strengths and preferences as well as weaknesses and areas of need. A balance is struck between opportunities to engage in activities for which a person already has the skills, opportunities to learn new skills, and opportunities to try out new or unusual activities. Advantages that accrue from medium-term goal planning are as follows: (a) the person has a focus and sense of direction in his or her life, (b) staff involved in mediating the plan are aware of the general direction of travel, (c) incidental goals may be targeted to complement or enhance the general direction of travel, and (d) the content of the plan can be assessed for intensity, relevance, and balance. 2.4.6. Opportunity Plans Opportunity Plans aim to create a context where residents develop their skills through regular practice, and they can also be used to occasion activities that a person can already do but seldom has the chance to perform. Opportunity Plans provide a semistructured method of simultaneous
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multiple short-term goal setting where no teaching method is specified. Staff work with behavioral objectives that specify: the person whose behavior will change, the behavior observed when successful, the level and type of assistance to be provided, the expected goal frequency, and a criterion for judging success. Up to 16 goals may be set on a weekly basis for each person. Learning opportunities are integrated into the natural flow of the day. A simple recording system is used to indicate whether the target behavior occurs under the conditions specified or more help is required. Opportunity Plans provide a useful method for implementing medium-term goals. Natural variability in the use of teaching procedures and activity materials may enhance generalization (Stokes & Baer, 1977). Simple audit procedures allow staff to assess the intensity, relevance, and balance of the goals set, and probes provide a measure of maintenance and generalization. 2.4.7. Structured Teaching Plans Structured Teaching Plans specify long-term goals that are important to the person and cannot be taught any other way. A task analysis is performed to break the long-term goal down into a series of smaller, more manageable steps. A detailed teaching plan is then developed for each step in the task analysis. Teaching plans specify time, place, preparation, antecedent presentation, correct response, reinforcement, error correction, and recording method. Structured teaching (a) provides a way for people to learn complex skills that they have been unable to learn under less precisely defined conditions, and (b) helps staff develop skills useful in semistructured and incidental learning opportunities. Behavior acquired under tight stimulus conditions may require additional programming to secure maintenance and generalization (Stokes & Baer, 1977).
2.5. Functional aspects of Active Support components Figure 6.1 shows how the components of Active Support combine functionally to create opportunities for meaningful engagement in everyday life-defining activity. The area within the triangle represents the sum of a person’s participation, social interaction, and learning. Components of Active Support form the sides of the triangle. The vertical axis labeled ‘‘many–few’’ represents the amount of staff resource (number of opportunities) each part of the system consumes and the programming capacity that can be achieved. The axis labeled ‘‘loose–tight’’ refers to the stimulus conditions under which participation and learning occur. The single largest effect accrues from the base of the triangle. The volume and quality of incidental opportunities for engagement is influenced by (a) staff’s orientation toward a social model of support, (b) routine and rhythms, (c) Activity Protocols, (d) Activity Support Plans, and (e) data derived from the Participation Index and Community Log. Participation in
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Number of opportunities
Stimulus conditions Tight Opportunity plans
Loose
Few Structured teaching plans
Activity support plans
Many
Figure 6.1 Active Support functional components.
activity creates incidental opportunities for learning that have at least two main advantages over more formally programmed support: They consume the least amount of staff resource and occur under naturally occurring (loosely specified) stimulus conditions. Behavior evoked or learned under these conditions is likely to contact naturally occurring reinforcement and to maintain and generalize (Stokes & Osnes, 1988). Opportunity Plans add one degree of structure and are useful when a person cannot learn or access activities under incidental conditions alone. The approach consumes more resources than incidental learning but fewer than structured teaching. Staff can pursue a relatively large number of objectives concurrently. Opportunity Plans impact on a smaller portion of the triangle than that associated with incidental opportunities, but it is larger than that for structured teaching. Because Opportunity Plans do not specify a teaching method, the situational context for each ‘‘trial’’ is likely to vary. Proximity with natural contingencies of reinforcement and prospects for maintenance and generalization are partially preserved. When persons cannot learn under semistructured conditions, and the goal is important to them or others, staff may elect to devise a Structured Teaching Plan. Structured teaching consumes a large amount of staff resource and the number of plans that can be run concurrently is therefore relatively small. Medium-term goal plans sit at the tip of the triangle. They give shape and direction to all programmed activities according to each person’s unique strengths, aspirations, and needs. To summarize, the base level of Active Support planning involves planning daily participation and allocation of staff support to residents. This ensures participation in meaningful, age-appropriate activities and facilitates, with appropriate staff support, successful participation irrespective of the level of disability. At a higher level, medium-term goals are set through Individual Plans and work toward these goals involves implementation of
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Opportunity Plans, Teaching Plans, and Activity Plans either independently or in parallel. The existence of medium-term goals acts as a common denominator in these components and provides a sense of direction for the life of the person with an intellectual disability. In this way, constructive and meaningful activity is combined with personal development, both necessary components of the productive well-being and, subsequently, the quality of the person’s life (Felce, 1997).
3. Staff Training in Active Support Staff are trained to implement Active Support in a two-day group workshop for all staff and managers and during on-site Interactive Training. The brief description of the workshops that follows is based on the training booklets developed by Jones and his colleagues ( Jones et al., 1996 a,b,c,d,e,f, Booklets 1-6). The description of the Interactive Training is based on a model developed by Toogood (2004).
3.1. Workshop training Off-site training occurs in a one- or two-day workshop. Materials for the workshop consist of six booklets, which present Active Support and its structural components—namely, Activity and Support Plans, Opportunity Plans, Teaching Plans, Individual Plans, and ways of monitoring participation and community presence (Jones et al., 1996a,b,c,d,e,f, Booklets 1–6), a training video, a set of presentation slides, and outline scripts for presenters (Jones et al., 1997). The aims of the workshop are (a) to introduce a number of core concepts relating to the philosophy of care, (b) to describe the structural components of Active Support, and (c) to guide staff through customizing the paper-based components of Active Support to the circumstances of the people whose home it is. For example, staff are guided through a mapping exercise to develop a timetable of weekly routines and rhythms for the home. They follow a number of prepared exercises leading to the identification of anchor activities with which to develop Activity Support Plans, and write the first set of Opportunity Plan goals.
3.2. On-site interactive training Off-site workshop training is followed quickly by on-site Interactive Training. It is an integral part of the training designed to demonstrate how staff can work on a moment-to-moment basis when Active Support is implemented. Interactive Training is delivered individually to every member of staff in the house where the member of staff works. Thus, behavior change procedures are bespoke and applied in the exact situational context within which
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behavior change is expected to occur. Interactive Training is highly context-specific, tailored to the needs and skills of the staff-resident dyad. Trainers work with staff to find ways of supporting the resident(s) to participate in meaningful activities in a way that is most beneficial and enjoyable for everyone. The goal is to aid staff in finding ways of adjusting the level of support they provide according to the resident’s needs and to sustain participation by giving attention and further assistance when it is required (Felce et al., 2002). A detailed description of Interactive Training can be found in Toogood (in press).
4. Recent Developments in Active Support and the Training Model The approach we have described so far is largely data-driven. Outcome data are collected continuously, concurrently, and contemporaneously, providing a rich seam of important information about service effort (input) and each person’s lived experience (output). An inherent assumption is that by carefully recording each person’s lived experience staff have a valid way of monitoring the overall quality of the service they provide, and of recording progress and detecting the need for change or readjustment on an individual case (McGill & Toogood, 1994). A more recent training program was published by Jim Mansell and his colleagues in 2005. It is differentiated from the previously described training model in a number of ways: (a) emphasis is placed on person-centeredness (the model is called ‘‘Person-Centered Active Support’’), (b) the paper-based system of monitoring Active Support implementation and resident progress is removed, and (c) the training manual can be used by both teams and individuals (Mansell et al., 2005). These differences between training approaches reflect largely the different experiences that researchers and practitioners had while implementing Active Support in different parts of the United Kingdom. Mansell et al. (2005) adopt a personcentered approach to reflect recent changes in British public policy (Department of Health, 2001), where Person-Centered Planning (PCP) is identified as the main strategy for supporting people with an intellectual disability. Active Support is proposed as a way of translating PCP into person-centered action (Mansell & Beadle-Brown, 2004). Active Support implementation as described in the training manual of Mansell et al. (2005) refers to activity timetables for the daily household activities (like the Activity Plans), while Opportunity, Teaching, and Individual Plans are omitted. The greatest difference though lies in the use of Participation Index and Community Logs. Mansell and his colleagues propose that by not relying exclusively on the paperwork for keeping track of participation staff will realize that Active Support is about improving
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quality of life and not making paper plans. Worksheet forms are provided for staff to evaluate broader aspects of the organizational change that Active Support involves, and for staff and managers to evaluate and plan personal practice. Mansell et al. propose three alternative ways of monitoring quality (Module 3, 2005): (a) Look and See, (b) Develop Practice, and (c) Review. Under ‘‘Look and See’’ the suggestion is to spend time watching oneself or one’s colleagues ‘‘with a pair of fresh eyes’’ while keeping in mind these themes: preparation, presentation, graded assistance, resident success, and staff helpful style. ‘‘Developing Practice’’ refers to the need to identify areas for improvement, which can be achieved through self-evaluation (either one is aware of one’s weaknesses or staff can videotape themselves while working and then watch their video), peer evaluation (buddy or mentor can give feedback after watching staff work), or supervisor evaluation (team leader spends time with one staff watching that person work). To improve the quality of Active Support, Mansell et al. suggest staff obtain coaching from a mentor, or watch videos (of oneself or others), or use role-play. In both main Active Support training models ( Jones et al., 1996; Mansell et al., 2005) service managers are ultimately responsible for maintaining quality and sustaining the Active Support model. In the approach by Jones et al., this is achieved through use of data collected on a daily basis and aggregated over the longer term (Booklet 6, 1996f ), whereas in the approach by Mansell et al. it is suggested that: ‘‘If they—senior managers—try to do this by asking staff to fill in forms about how many activities people have taken part in, they run the risk of inadvertently focusing attention on paperwork rather than on what is really happening in the relationship between staff and service user’’ (Module 4, 2005, p. 125). For this reason, Mansell et al. proposed that the best way for managers to ensure service quality is to go into the house and see for themselves how Active Support is working. If numerical data are required, there are four proposed items that can be checked on a Likert scale (1 ¼ very weak to 5 ¼ excellent): 1. ‘‘people are engaged in meaningful activities and relationships and therefore developing in independence, choice, and social inclusion. 2. senior staff are providing practice leadership by spending time with each staff member, giving feedback, and modeling good practice. 3. supervision happens sufficiently frequently and focuses on quality of support provided by each staff member. 4. staff meetings happen sufficiently frequently and focus on the engagement of each resident in meaningful activities and relationships.’’ (Module 4; Mansell et al., 2005, pp. 125–126) Shifting the focus from paper-based planning probably reflects accumulated experience of implementing Active Support in services. To date, there
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are no empirical data that enable one to establish whether the implementation of Active Support is best done to include a detailed paper-based recording system or a model of implementation that does not include these. Anecdotally, the advantage of including paper-based recording mechanisms may be the availability of data for assessing each person’s lived experience in terms of intensity, relevance, and balance of service support for activities of daily life, but the disadvantage may be that staff time resources concentrate more in monitoring and less in implementation. The disadvantage of not including paper-based recording mechanisms may be the potential for biased estimations of Active Support effects, but its advantage may be that implementation of the model becomes more user-friendly. At present, neither of the two systems appears problem-free but it has to be noted that the proposed implementation methods have a somewhat different focus: continuous data collection allows the evaluation of individual progress, whereas overall evaluation of organizational aspects and staff practice focuses more on the service as a whole.
5. Conceptual Issues In this section, we describe the relationship of Active Support with the theory of Normalization and the science of ABA to see how these two areas shaped the development of Active Support over time. We also briefly discuss the relationship between Active Support and other current approaches, namely, Person-Centered Planning (PCP) and Positive Behavior Support (PBS).
5.1. Active Support and Normalization The introduction and dissemination of Normalization in the United Kingdom began around the time the Andover project was developing and continued strongly for another decade and a half. The theory was influential in the United Kingdom impacting, for example, on the residential model proposed in the policy document An Ordinary Life (King’s Fund Centre, 1980). This document declared that people with intellectual disabilities ‘‘have the same human value as anyone else and so the same human rights . . . ; living like others in the community is both a right and a need . . . ; services must recognize the individuality’’ (pp. 14–15) of people with intellectual disabilities. The impact was such that ‘‘ordinary life’’ became almost synonymous with Normalization (Race, 1999). A convergence of values was apparent among Normalization, social policy, and the Andover model. The Andover model (and later Active Support) provided a practical demonstration of an organizational technology for
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the implementation and realization of many competency- and image-related Normalization goals. Normalization also continued to have an impact on the development of Active Support. Jones et al. (1996), for example, drew on O’Brien’s Five Essential Accomplishments (1987) when revising and updating Active Support materials, and Mansell et al. (2005) described their whole approach as ‘‘Person-Centered Active Support.’’ Active Support may be conceived as (a) an approach whose development was influenced by the dissemination of Normalization theory, and (b) an organizational technology that is suited to the implementation and accomplishment of Normalization goals.
5.2. Active Support and ABA While Normalization and related concepts correspond with the core values of Active Support, the organizational technology within Active Support is derived directly from the field of ABA. This combination of a conceptual framework with a systematic technology is an early example of ‘‘rapprochement’’ between Normalization and ABA as it was later described by McGill and Emerson (1992). ABA is an applied science of human behavior based on the experimental analysis of behavior (Skinner, 1953). It brings together a variety of empirically validated techniques and procedures derived from basic principles of behavior, and it has a philosophical stance also, which is a mixture of scientific and social values as delineated, for example, in Baer, Wolf, and Risley (1968). The philosophical and procedural aspects of ABA were well known to the originators of Active Support and have continued to influence its development ever since. Table 6.1 lists Active Support functions against Baer, Wolf, and Risley’s seven defining characteristics of ABA (1968). The organizational structure, the approach to challenging behavior, and the staff training model are the three areas of Active Support whose behavioral analytic dimensions are explored further below. 5.2.1. Organizational technology The behavioral underpinnings of the organizational technology are evident in activity participation, learning, monitoring, and working with challenging behavior. Incidental behavioral support and formal teaching programs rely for their success on the systematic application of techniques such as goal setting, task analysis, hierarchical prompting, shaping, fading, differential reinforcement, error correction, and data collection. Materials are presented so they become discriminative for participation (Mansell et al., 1987). Antecedent assistance follows a least-to-most hierarchical prompt sequence (Miltenberger, 2004), with an emphasis on nonverbal instruction (Repp, Barton, & Brulle, 1982). Assistance is varied according to need and
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Table 6.1 The dimensions of Applied Behavior Analysis as described by Baer, Wolf, and Risley (1968) and the way Active Support relates to them Dimension
Definition
Active Support (AS)
Applied
Behavior must be socially significant and important to the person or others
Behavioral
Behavior must be precisely measured and demonstrate whose behavior changed
Analytic
The procedures used must demonstrate functional relations to the best degree possible, given the nature of the behavior and context within which the procedures are being used
AS addresses participation in the material and social environment as an observable and measurable indicator and determinant of quality of life, a construct that is important to most individuals and in which society has an interest AS targets classes of staff and resident behavior for change and systematically measures the extent and nature of change Empirical research on AS has demonstrated functional relations between whole environment intervention and resident engagement and, for example, antecedent staff assistance and resident engagement AS procedures are described in training manuals and supporting materials
Technological Behavior change procedures must be completely and precisely described so others can follow them Conceptually Behavior change systematic procedures must derive from the basic principles of behavior
AS utilizes a combination of procedures derived from behavior analysis, for example, differential reinforcement, task analysis, prompting, shaping, fading, data collection, and analysis (continued)
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Table 6.1 (continued) Dimension
Definition
Active Support (AS)
Effective
Behavior change procedures must result in large amounts of behavior change
Generality
Behavior changes last over time, occur in a variety of settings, and spread to other behavior
AS studies have demonstrated statistically and clinically significant improvement in engagement and community participation AS studies have demonstrated maintenance effects. AS procedures include continuous recording to track improvement and stability. AS data inform rate, duration, balance, and distribution of engagement over time and across life-defining activities
decreasing assistance (Demchak, 1990) is used to increase resident independence over time by shifting stimulus control to more naturally occurring stimuli within the household. Maintenance is achieved by manipulating consequences. Staff attention, for example, is differentially weighted toward participation rather than lack of engagement or inappropriate behavior, which indicates that in cases where staff attention functions to reinforce resident behaviors, the probability of participation behaviors should increase (Cooper, Heron, & Heward, 1987). Active Support involves the collection of continuous data about individual people. Each person serves as his or her own control. Data are analyzed, interpreted, and displayed in ways consistent with a behavior analytic approach to provide evidence of effectiveness. These data inform decisions about individual change. At a group level, data are aggregated across the residential service to form the basis of clinical audit, a key aspect of clinical governance of care services (National Institute for Clinical Excellence, 2002). In the context of the British health care system, these practices have been strongly emphasized since 1997 (Department of Health, 1997) as a way to ensure quality and accountability of services at a local level. The continuous and concurrent nature of quantitative data generated by Active Support is especially relevant to good practice in clinical audit and provides continuous feedback for staff on service input as well as individual attainment.
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5.2.2. Active Support and challenging behavior Eliminating challenging behavior is not a primary aim of Active Support, although the model has been used in services to support people with seriously challenging behaviors (Emerson & McGill, 1993; Mansell, McGill, & Emerson, 2001). Properly implemented Active Support procedures can provide the following: (a) a rich source of data for functional descriptive assessment, (b) an excellent context for delivering functionally based multicomponent behavioral interventions, and (c) data to help evaluate the impact of those interventions. One of the main aims of Active Support is to create a whole learning environment through a combination of antecedent management and differential reinforcement. In an Active Support environment, for example, a person may be two or three times more likely to receive staff attention contingent on engagement than contingent on passivity or inappropriate challenging behavior. In this way, Active Support can provide a way of contextualizing procedures derived from ABA into the everyday lived experience of people with intellectual disabilities. The notion of creating ‘‘helpful environments’’ for individuals whose behavior may be experienced as challenging (McGill & Toogood, 1994) is consistent with Active Support as an ecological manipulation involving establishing and abolishing operations (Laraway, Snycerski, Michael, & Poling, 2003; Michael, 1982) for challenging behavior. Challenging behavior may be maintained typically by social positive reinforcement (e.g., social attention and access to tangibles), social negative reinforcement (e.g., escape from task demand or unwanted social attention), or automatic reinforcement, which may be positive or negative but its delivery is not mediated by others (Carr, 1977; Iwata, Dorsey, Slifer, Bauman, & Richman, 1994). Motivating operations momentarily establish or abolish stimulus events as reinforcing or punishing and evoke or abate behavior associated with those events (Laraway et al., 2003; Michael, 1982). The potential of Active Support in acting as a preventative intervention for challenging behaviors lies in the simultaneous modification of a large number of potential establishing operations without directly targeting the contingencies that maintain challenging behaviors. This may be particularly relevant where behavior is multiply controlled. Where deprivation of attention functions as an establishing operation for challenging behavior, an increased density of staff contact under Active Support may function as an abolishing operation and decrease the overall frequency of challenging behavior associated with obtaining staff attention in the past. Similarly, increased independence, self-direction, and personal autonomy that accrue from implementing Active Support may abolish deprivation of tangibles, such as activity materials and food, and reduce the occurrence of challenging behavior for which deprivation of tangibles was an establishing operation.
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In the cases where challenging behavior is maintained by escape from task demand, the aversive stimulus functions of task demand are modified in a number of ways. For example, under Active Support staff are trained to match the sequencing, scheduling, timing, and location of activities to each person’s behavioral ability and individual preferences; to present task demands by carefully attending to the mode, pace, and complexity of antecedent instruction; to address task difficulty by breaking complex activities into smaller more manageable components; to present welltimed verbal and nonverbal assistance as required; and to reinforce active participation in stages throughout the activity. In addition, Active Support seeks to establish a more attentive and responsive environment that ‘‘listens’’ to functionally equivalent behavior such as manding a change, more help, or a break. Tailoring the task demand environment to each person should mean escape contingencies are relevant less often and the frequency of behavior associated with escape is reduced. Supported routines and structured teaching may also lead to greater mastery over skills and reduce the aversive properties associated with task complexity. Staff can then work systematically to assist persons to increase their tolerance for high demand and to mand alternate behavior. Finally, challenging behaviors maintained by automatic reinforcement, such as sensory stimulation, may also be influenced by improved access to activities and materials. The earlier description of relationships between Active Support-induced changes in the environment and changes in challenging behavior lies at a theoretical level. In a real-world application, a number of factors could interfere to affect this relationship. One of them has to do with staff. Staff behavior has been implicated as a factor that facilitates maintenance of challenging behavior (Hastings & Remington, 1994) either by reinforcing it directly or failing to reinforce appropriate behaviors. In addition, staff may not be able to implement effective interventions (Hastings & Remington, 1993), even where they have received training in them, their beliefs are compatible with the intervention’s principles, and they believe that interventions can be effective (Hastings, 1997). Moreover, the hypothesized interaction between the ‘‘helpful environment’’ (McGill & Toogood, 1994) and the cause for some challenging behaviors might not take place. Research evidence suggests that improvements in the physical environment do not necessarily lead to a decrease in challenging behaviors (Emerson & Hatton, 1994). It is possible, for example, that automatically maintained stereotypical behaviors may still be exhibited while the person is actively engaged in an activity. To understand how the ‘‘helpful environment’’ that Active Support puts in place interacts with the causes of challenging behavior, clinicians and researchers need to examine any potential effects on challenging behaviors and then describe the changes in the function of the behaviors that Active Support may induce.
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5.2.3. The staff training model The training models in Jones et al. (1996) and Mansell et al. (2005) include group workshops and individually tailored on-site training. Group workshops follow traditional instruction methods and are useful for imparting information and developing product. On-site interactive training methods use direct observation and a combination of behaviorally derived methods (goal setting, task analysis, hierarchical prompting, shaping, fading, differential reinforcement, and error correction) to coach staff behavior (Toogood, 2005). It has been suggested that supplementing instructional methods with on-site training is more effective in producing staff behavior change and in facilitating the transfer of the skills into everyday work (Anderson, 1987; Smith, Parker, Taubman, & Lovaas, 1992). This model also includes residential service users (Purcell, McConkey, & Morris, 2000; Smith et al., 1992) and achieves a high density of trained staff by massing the training experience over a brief period of time (Landesman-Dwyer & Knowles, 1987). On-site training draws on experiential learning theory, where learning is grounded on the ‘‘here-and-now’’ experience (Kolb, 1984). It introduces variety into the learning experience mainly through varying the perspective (Fazey & Marton, 2002), for example, by verbally rehearsing or actually practicing the experience of being supported in a particular way (Toogood, 2005).
5.3. Active Support and other approaches: PCP and PBS Both PCP and PBS, approaches developed in the United States, share many similarities to the British model of Active Support. PCP is an umbrella term that describes a number of approaches that had developed ‘‘systematic ways to understand a person with a developmental disability as a contributing community member’’ (Lyle O’Brien & O’Brien, 2002, p. 3). The Normalization principle and the accomplishment framework (O’Brien, 1987) provided the value base for both Active Support and PCP ( Jones et al., 1996a, Booklet 1; Kincaid, 1996). Although there are many commonalities between the two approaches, an extensive description of those would be inappropriate as PCP includes many different approaches that focus primarily on the individual, whereas Active Support is one specific model developed, initially, with a clear focus on the individual resident of a small community home. So, whereas Active Support reorganizes the operation of an existing structure (residential home) to meet individual needs, PCP gives emphasis to the individual needs and wants, and uses structures and services to meet these. Active Support begins by organizing the person’s daily life (going down to the moment-to-moment interaction between people: Activity and Support Plans) and then moving gradually to take a long-term view of the person’s life course
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(with the Individual Plans). PCP begins by establishing the long-term goals and then proceeds to find ways of making them happen. By keeping the focus on the individual person, PCP does not put any constraints on the plans about the person’s future; systems need to change to meet the person’s needs and wants (Kincaid, 1996; Kincaid & Fox, 2002). On the other hand, Active Support’s Individual Plans will be implemented, though the Activity, Opportunity, and Teaching Plans which take place in the community home and, thus, will be naturally constrained by any resource limitations a service provider might face. Originators of the Active Support model view its relation to PCP approaches as complementary. Felce et al. (2002) suggested that when person-centered plans identify a need for an increase in the activity levels for one or more people in a home, then Active Support can be effectively used for this purpose. Mansell et al. (2005) have taken this one step further and relabeled the model as ‘‘Person-Centered Active Support’’ suggesting that PCP provides the ‘‘bigger picture’’ and the plans can be translated into person-centered action through Active Support. Case study evidence from combining PCP approaches with Active Support (Sanderson, Jones, & Brown, 2001) suggests that Active Support can improve PCP by offering a systematic way for organizing the implementation of plans, while PCP is probably more effective than Individual Plans in describing important goals for the person. Recent large-scale evaluations of PCP effectiveness indicate that PCP can facilitate gains in areas along dimensions also targeted by Active Support: daily activities, community involvement, and more choice and autonomy (Holburn, Jacobson, Schwartz, Flory, & Vietze, 2004; Robertson et al., 2005). In fact, PCP and Active Support may also be related to ABA. Holburn (2001) discussed research paradigms that support the compatibility of PCP with the ‘‘applied,’’ ‘‘behavioral,’’ and ‘‘conceptual’’ dimensions of ABA established by Baer et al. (1968). This call for integrating Active Support in the PCP framework is somewhat similar to the call for cooperation between PCP and PBS, two approaches that have in common values, philosophies, and, sometimes, techniques (Kincaid & Fox, 2002). In fact, Active Support has many similarities to PBS, in that they were both based on the principle of Normalization and derived their technologies from the science of ABA. PBS’s main aim is to improve the quality of life for all relevant stakeholders with a secondary aim of making challenging behavior ‘‘irrelevant and inefficient’’ (Carr et al., 2002). Both Active Support and PBS manipulate the environment in which the individual lives to bring about changes in the person’s quality of life. The two approaches differ in their focus or not on challenging behavior and the resulting assessment methods used to inform intervention. The reduction of challenging behavior has never been an explicit goal of Active Support. Rather, reductions in challenging behavior are a desirable by-product of the increase in participation. In PBS, multicomponent interventions are based
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on multicomponent assessment procedures, which can include information obtained by interviews, rating scales, direct observations, development of hypotheses, and sometimes hypothesis-testing using functional analysis techniques (Dunlap et al., 2000). Active Support focuses on increasing residents’ level of participation in meaningful activities and, as implemented by service staff, utilizes assessment methods that are not as extensive as the ones put forward as good practice in PBS. Complementing Active Support plans with PBS procedures for people for whom staff identify challenging behavior as an obstacle to activity participation would likely facilitate the implementation of Active Support within a service. As we discuss later, challenging behavior can affect both engagement in activities and staff behavior. This highlights the need to increase effectiveness of Active Support in relation to challenging behavior, and PBS has demonstrated its potential to do just this (Kincaid, Knoster, Harrower, Shannon, & Bustamante, 2002).
6. Setting the Context for Evaluating the Effects of Active Support Implementation The main outcomes examined in relation to Active Support effectiveness are resident engagement in meaningful activities (i.e., social interaction with staff, participation in domestic, personal, leisure, recreational activities) and staff support. The latter has been examined from the point of view of facilitating resident engagement (i.e., staff assistance) and also as an overall measure of staff contact. A secondary outcome measure for most studies has been residents’ level of challenging behaviors. Engagement has been extensively used as an objective outcome indicating residents’ quality of life. Beyond the field of intellectual disability, engaging in purposeful activity relates to the ‘‘productive well-being’’ dimension of quality of life (Felce, 1997) or personal development (Schalock, 1996) and even reflects social status, as ‘‘having a busy lifestyle’’ is characteristic of the more privileged social groups in developed societies (Gershuny, 2005a,b). Real-time direct observation of resident and staff behaviors has been the main methodological tool for assessing Active Support implementation, and rating scales have been used to assess residents’ ability level and challenging behaviors. If Active Support is to affect resident engagement, we would expect to see some evidence from existing research of relations between resident engagement and staff support. Resident engagement and staff support are outcomes that have been extensively assessed in the literature evaluating the effects of moving people with intellectual disabilities from hospitals to communitybased accommodation. In a review of 46 studies, Emerson and Hatton (1994)
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found considerable variation in these outcomes within each type of accommodation, although, on average, resident engagement was higher in community-based small houses (about 48% of the time) than in hostels or special units (25%) or hospitals (14%). The same trend was apparent for staff support: 15%, 9%, and 4% for community homes, hostels, and hospitals, respectively. The researchers suggested that about 52% of the variation in resident engagement was accounted for by staff assistance (Emerson & Hatton, 1994). The effects of deinstitutionalization on challenging behavior were less clear and seemed to vary depending on the method of measuring behaviors (rating scales vs direct observations). The conclusion was that the move to a more enriched physical environment is not necessarily accompanied by a reduction of challenging behavior (Emerson & Hatton, 1994; Hatton & Emerson, 1996). Independent of Active Support research, a number of studies have examined the factors that determine resident engagement and staff support. Engagement has been found to be strongly related to residents’ ability (Felce & Emerson, 2001; Felce & Perry, 1995, 2004; Mansell, BeadleBrown, Macdonald, & Ashman, 2003), to be significantly predicted by ability skills and staff attention (Felce, Jones, Lowe, & Perry, 2003), by more staff positive contact, and living in a community setting (Hatton, Emerson, Robertson, Henderson, & Cooper, 1996). Participation in community outings has also been directly predicted by more scheduled activity and indirectly by higher cognitive skills (Hatton et al., 1996) whereas, after controlling for adaptive and challenging behaviors, engagement in social activities has been found to be predicted by fewer hours of planned activities (Felce, Lowe, & Jones, 2002a). Studies that have taken into account adaptive skills and challenging behavior still report a significant effect of staff attention on resident engagement (Felce et al., 2002a; Perry & Felce, 2005) and residents’ engagement in domestic activities (Felce et al., 2002a). In addition to staff assistance, the study by Felce et al. (2002a) found that overall engagement was also predicted by the size of the house (more residents) and the internal organization of the care environment: Domestic engagement was negatively predicted by staff:resident ratios and percentage of staff with formal care qualifications. Staff support and residents’ adaptive skills are either unrelated (Felce & Perry, 2004) or related in a complex way. For example, Felce et al. (2003) reported a small but significant prediction of staff attention by an interaction between adaptive skills and challenging behavior (higher adaptive skills and low challenging behaviors) and by the internal organization of the care environment. Felce, Lowe, and Jones (2002b) found that staff attention and assistance were both predicted by the range in measured adaptive skills (more homogeneous ability groupings) and staff:resident ratios but that higher levels of qualified staff had a negative impact on assistance. Higher cognitive ability of residents and less institutional treatment of services
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(i.e., treating residents as a group and not as individuals, a management practice characteristic of institutions) were shown to predict indirectly staff assistance and positive contact which were also directly predicted by more hours of scheduled activity and being in a specialized service (Hatton et al., 1996). In conclusion, research evidence suggests the presence of complex relations between resident engagement and staff behaviors. Apart from the impact of ability and in addition to other environmental/service characteristics, resident engagement seems to be associated directly with staff behaviors, which, in turn, are associated, either directly or indirectly, with resident characteristics (ability and challenging behavior). These relationships set the context for the evaluation of the effects of Active Support.
7. Evidence Base for Active Support In the two sections that follow, we describe in detail the outcomes of studies that directly measured the impact of Active Support on resident and staff behaviors. We also present some outcomes from studies that investigated various aspects of quality of life or community living. These outcomes were selected because they relate to Active Support and they add a different perspective to the evaluation outcomes.
7.1. Evaluation studies of Active Support Resident engagement and staff support are examined later in more detail in studies that have directly evaluated Active Support effectiveness. Table 6.2 presents information on these studies and Table 6.3 presents the percentage of time residents were observed engaged in activities and in receipt of staff contact. As the Active Support evaluation studies extend over a period of about 20 years, the outcomes were not all defined in the same way. For example, the Andover project defined staff contact as Instruction and Physical Guidance (Table 6.3), while Jones et al. (2001b) measured total staff attention and assistance, among other staff behaviors. Initial evidence came from two early clinical projects: the Andover project (Felce, 1989) and the SDT (Mansell et al., 2001; McGill & Mansell, 1993, 1995). The goal of both projects was to create residential placements for people who were either moving from the hospital to the community (Andover) or whose challenging behavior required the development of specialized services to maintain them in the community (SDT). Data from these studies on resident overall engagement and staff contact are presented in Table 6.3. In the Andover project, increased resident engagement was found in house residents compared to people still living in institutions, while staff in homes were observed to interact more with the
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Table 6.2 Studies that have evaluated the Active Support model
Study
No of residents
Design/Methods
Study goal
Andover study; Felce (1989)
12
Observations pre- (2), postmove (2), and at follow-up (2 years after move)
Evaluate the effects of moving people from hospitals to community houses that operated using— what was later called—Active Support
Special Development Team (SDT); Mansell et al. (2001)
13
Multiple time-series observations (9 data points between 1987 and 1991)
Jones et al. (1999)
19
Multiple baseline observations: pre- (10),
Develop community services for people with serious challenging behaviors. The principles of AS are found in the operational orientation of the SDT Evaluate AS using an experimental design
Observational measures and rating scales
Resident engagement in leisure, personal, domestic, teaching activities, and in interaction with staff Resident engagement in inappropriate activities Staff behavior as antecedents and consequences to resident behavior Resident participation in leisure, personal, and practical activities Challenging behavior Staff contact
Resident engagement in nonsocial
posttraining (10), and follow-up (at 6 and 12 months after end of training) Jones et al. (2001a)
188
Observations pre- (3) and posttraining (3)
Mansell et al. (2002)
23 (Control Waiting list control group n ¼ 26) group, observations at pre- and posttraining
Compare AS implementation when training is researcher-led, researchersupervised, and independently delivered by service managers
Evaluate AS in residential services as provided by a charity
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(i.e., personal, domestic) and social activities Challenging behavior Staff contact (overall) Resident engagement in nonsocial (i.e., personal, domestic) and social activities Challenging behavior Staff assistance (verbal and nonverbal) and overall contact Index of Participation in Domestic Life, Raynes et al. (1994); Index of Community Involvement, Raynes et al. (1994) Resident engagement in meaningful activity Active Support Measure (ASM; Mansell & Elliott, 1996) (continued)
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Table 6.2 (continued) Study
Bradshaw et al. (2004) Stancliffe et al. (2007)
No of residents
11 (Control group n ¼ 11) 22
Design/Methods
Control group, observations at pre- and posttraining Observations at pre- (6), posttraining (6), and follow-up (3–9 months after end of training)
Study goal
Replicate findings from previous studies using a control group Replicate findings from British studies and evaluate AS implementation in Australia
Observational measures and rating scales
Behavior Development Survey (Conroy, Efthimiou, & Lemanowitcz, 1982) Resident activities Contact with staff Challenging behaviors Resident engagement in social and nonsocial activities and staff help Index of Participation in Domestic Life (Raynes et al., 1994); Index of Community Involvement (Raynes et al., 1994); Inventory for Client and Agency Planning (Bruininks, Hill, Weatherman, & Woodcock, 1986)
Table 6.3
Levels of overall resident engagement in activities and contact from staff before and after Active Support
Andover Project (data from Felce et al., 1986; Felce & Repp, 1992; Experiment 1; Follow-up: Saxby et al., 1988, n ¼ 10) SDT (Mansell et al., 2001)
Follow-up Staff contact
Pre
Post
Pre
Post
Engagement
23% (while in institutions)
House 1: 51%
Instruction: 1%
House 1: 44%
House 1: 9%
House 2: 56%
Physical guidance: 0% (while in institutions)
Instruction: House 1: 19.8% House 2: 11.3% Physical guidance: House 1: 5.2% House 2: 3.2%
House 2: 46%
House 2: 10%
Sig. increase (t ¼ 4.62, df ¼ 12, p ¼ .005)b 53.4%
Contact: hospital wards: 1.6% special hospital units: 12.7% Contact: 17.5%
Contact range: (13.2–42.5%)
No follow-up
Contact: 31.8%
57.2%
Assistance: 5.9%
Assistance: 23.3%
Total attention: 14.9% Assistance: 7.5%
Total attention: 14.0% Assistance: 14.6%
14% (institutions)
Jones et al. (1999) 33.1%
Jones et al. (2001b)
Staff behaviora
Resident engagement
Study
46.7%
54.6%
Contact: 28.2% Assistance: 16.0%
No follow-up
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(continued)
Table 6.3 (continued)
Mansell et al. (2002) Bradshaw et al. (2004) Stancliffe et al. (2007) a b c
Staff behaviora
Resident engagement
Study
Follow-up
Pre
Post
Pre
Post
Engagement
7%
33%
ASMc: 50%
ASM: 66%
No follow-up
16.6%
26%
Contact: 16.7%
Contact: 21.2%
No follow-up
42.46%
49.54%
Help: 7.27%
Help: 11.42%
53.81%
Staff contact behaviors were defined differenctly in each study. Overall resident engagement: 28%, based on n ¼ 11 (McGill & Mansell, 1993). ASM: Active Support Measure; Mansell and Elliott (1996). Staff contact behaviors were defined differently in each study.
Staff contact
13.56%
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residents using instruction and physical guidance (Felce, de Kock, & Repp, 1986; Felce & Repp, 1992). A follow-up on 10 of the initial 12 people, 2 years after the move into homes showed that engagement remained at high levels (Saxby, Felce, Harman, & Repp, 1988). However, there was a significant decrease in staff contact (of about 5–8%; Saxby et al., 1988) bringing the overall levels of contact to 10% of the time or below (Table 6.3). The SDT collected data on 13 people over time and found that there was a significant increase in participation in meaningful activities and staff contact after the move into the community (Mansell et al., 2001; McGill & Mansell, 1993). In the first experimental evaluation of Active Support, 5 community homes participated in a multiple baseline design with 19 residents observed 10 times for 2 h each time in their homes before and after the Active Support training, while one 2-h observation was obtained 6 and 12 months after the end of the training. The observations suggested a significant increase in resident engagement in domestic activities within each house ( Jones et al., 1999). Staff behavior was measured either as total contact or staff assistance, which are behaviors that directly facilitate resident engagement. Staff assistance increased significantly within each of the five houses and staff contact increased in four of them. The data presented in Table 6.3 reflect average times across all five houses. There was no change in resident social engagement, and there was no statistical comparison of the follow-up levels for engagement and staff contact and assistance. Pre–post change in staff assistance was related to change in engagement (r ¼ .84), indicating that increases in staff assistance were related to increases in resident engagement. Changes in staff assistance were inversely related to residents’ adaptive skills (r ¼ .77), which suggests that more assistance was available for the least able residents. Similarly, changes in engagement were inversely related to adaptive ability (r ¼ .71), which indicates that less able residents showed greater improvements in their engagement. Staff assistance and contact were positively related to residents’ ability scores before Active Support training (r ¼ .58 and .67, respectively) but this was not the case after the training (r ¼ .26 and .02, respectively). This finding suggests that, whereas before Active Support increased staff contact was more likely to be available to the most able residents, after Active Support receipt of staff contact had nothing to do with how able a resident was. Most significantly, the likelihood of resident engagement occurring given the presence of staff assistance increased after Active Support training (Felce et al., 2000), indicating that staff behaviors had become more effective in eliciting resident engagement. In the subsequent larger-scale Active Support evaluation (n ¼ 188), Jones et al. (2001a) compared outcomes in houses where Active Support training was delivered primarily from researchers (apprenticeship group), primarily from service managers with the researchers’ help (supervision group), and from managers independently (independent group). It was
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found that there were no significant changes in the houses where managers delivered the training independently, but in the other two groups there were significant increases in staff use of verbal instruction and nonverbal assistance, resident engagement in domestic activities, and more generally their nonsocial activities. The data presented in Table 6.3 are drawn from Jones et al. (2001b) where results are presented grouped for the apprenticeship and supervision groups (n ¼ 106). The significant increase in participation in domestic activities was also reflected in the Index of Participation in Domestic Activities (Raynes, Wright, Shiell, & Pettipher, 1994), and there was a significant increase in the reported type and frequency of social activities and the type of community activities ( Jones et al., 2001b). Residents’ adaptive skills were strongly correlated to engagement levels both before and after Active Support training (r ¼ .75 and .70, respectively) and moderately inversely related with the progress observed in engagement in domestic activities (r ¼ .32). These findings indicate that, although the level of ability relates to the extent of engagement, increases in engagement in domestic activities were more likely for the less able residents after the introduction of Active Support. Changes made in a composite measure of staff attention were related with changes observed in residents’ engagement in social activities (r ¼ .79), but not domestic activities, while changes in staff assistance (verbal and nonverbal behaviors) were related to changes in resident total engagement (r ¼ .40), engagement in social interactions (r ¼ .28) and strongly related to changes in engagement in domestic tasks (r ¼ .64). Therefore, it seems that an increase in attention from staff is important for subsequent increases in the amount of time a resident engages in social activities. An increase in the more specific assistance behaviors seems to be important for increases in the amount of time residents engage in domestic tasks. Interestingly, changes in staff assistance were inversely related with residents’ adaptive skills (r ¼ .35) whereas there was no association between adaptive skills and staff assistance before the Active Support training, which indicates that even though staff provided assistance to all residents, after Active Support they increased the amount of time they spent assisting the least able residents. In terms of the probability of residents’ overall engagement given staff verbal and nonverbal assistance, a significant increase in the odds of engagement given nonverbal assistance was demonstrated for the apprenticeship group in the study by Jones et al. (2001a) (Smith, Felce, Jones, & Lowe, 2002). This finding indicates that after Active Support training staff’s nonverbal assistance became more effective in eliciting residents’ engagement. The effectiveness of nonverbal assistance in increasing engagement was also seen in the group of least able residents and those with autistic-type symptoms, whereas there was no increase in the odds of engagement with either verbal or nonverbal assistance for those residents with challenging behaviors (Smith et al., 2002).
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In the first study to include a waiting list comparison in a group design, Mansell et al. (2002) evaluated the effects of Active Support training that was provided to the staff of 23 residents by another agency. The researchers observed an overall measure of engagement and they found that this increased significantly pre–post within the intervention group although there was not a significant difference between the groups after the training. The Active Support Measure (ASM; Mansell & Elliott, 1996) is a 15-item observational measure that rates the quality of staff support, with items such as age-appropriateness of activities and levels and type of staff contact. Mansell et al. (2002) reported a significant pre–post increase in the ASM scores within the intervention group (see Table 6.3 for means). Compared to the waiting list control group, ASM scores were also significantly higher in the intervention group after the training, suggesting higher quality of staff support. A significant increase in adaptive skills was found in the intervention group. Bradshaw et al. (2004) also used a comparison group and found a significant increase in levels of activity engagement for the intervention group. There was also an increase in levels of staff contact in the intervention group although the between-groups difference was not significant. Bradshaw et al. found that there was no significant relation between changes in staff contact and resident engagement (r ¼ .14) and that the largest increases in engagement were observed in the two most able house residents. In an Australian evaluation of Active Support, Stancliffe et al. (2007) found an increase in resident engagement and staff help in five homes that were observed before (pre), after Active Support training (post), and at follow-up (see Table 6.3 for means). Changes in staff help and resident engagement were strongly related between pre and post (r ¼ .73) and between pre and follow-up (r ¼ .53). Adaptive skills were not associated with changes in engagement at the end of the training or at follow-up, indicating that Active Support effects did not differ for residents of different ability level (Stancliffe et al., 2007). Comparisons made on data from rating scales suggested a significant increase in reported domestic and community activities at follow-up, and a nonsignificant increase in adaptive behavior ratings (Stancliffe et al., 2007). It is noteworthy that in one of the five houses of this Australian study, both resident engagement and staff help were observed at decreased levels post-training (but not at follow-up), which Stancliffe et al., attributed to a partial implementation of the Active Support model within that house—possibly due to the lack of managerial involvement with Active Support. The effects of Active Support on residents’ challenging behaviors are somewhat less clear than the results for engagement behaviors. For the residents of the first (n ¼ 6) of the two houses participating in the Andover project self-stimulatory behaviors were observed for 20% of the time, which was higher than the comparison group in the institution and this same
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group moved into the second house (Felce & Repp, 1992, Experiment 1). Saxby et al. (1988) reported a decrease in inappropriate behavior over a 2-year period from 14% to 4% (n ¼ 10), whereas the levels of stereotyped behaviors for 4 of the residents in the first house remained at the same levels (29%, and 2 years later 31%). The SDT reported a nonsignificant decrease in minor (mainly stereotypy) and major challenging behaviors (29% to 16% and 9% to 4%, respectively) for the 13 residents they observed, but these researchers suggest caution in the interpretation of the results. Specifically, both minor and major challenging behaviors were greatly variable and the inter-rater reliability for major challenging behaviors was low as a result of the low frequencies at which these behaviors were observed and the unsuitability of the coding system (momentary time sampling at 20-s intervals) for capturing them (Mansell et al., 2001). Jones et al. (1999) did not report the outcomes of their observations on challenging behavior because of the low frequencies that affected inter-rater reliability, but Jones et al. (2001a) reported nonsignificant changes in overall challenging behaviors in their three groups (apprenticeship group, 21.2–18.6%; supervision group, 13.5–14.6%; and independent group, 13.2–13.6%). Jones et al. (2001a) suggest that the composite score used for challenging behavior consisted mostly of stereotypy. Bradshaw et al. (2004) reported a significant increase in challenging behavior for the intervention group (pre: 8.5% to post: 20.6%), which they attributed mainly to increases in stereotypic behaviors. Using a rating scale to assess challenging behaviors, Stancliffe et al. reported no significant changes in challenging behavior in their research. In summary, studies that have evaluated the effects of Active Support in community houses show that resident engagement in meaningful activities of daily living increases significantly along with the amount/type of support residents receive from staff. With the exception of one study (Bradshaw et al., 2004), most studies have demonstrated that changes in staff behavior are closely related to the observed changes in resident engagement. There is some evidence to suggest that Active Support is more beneficial for the least able residents ( Jones et al., 1999, 2001b; Smith et al., 2002), although the finding has not always been replicated (Bradshaw et al., 2004; Stancliffe et al., 2007). The evidence regarding the effects of Active Support on residents’ challenging behavior is inconclusive so far, although there is some evidence to suggest improvements in adaptive skills (Mansell et al., 2002; Stancliffe et al., 2007).
7.2. Indirect evidence related to Active Support In this section, we present correlational data from studies that have used two rating scales that relate to Active Support: the ASM (Mansell & Elliott, 1996) and the Residential Practices Working Scale (RSWPS; Emerson, Reeves, & Felce, 2000; Lowe, Felce, Perry, Baxter, & Jones, 1998).
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The ASM is an observational rating scale of the nature and quality of staff support (Mansell et al., 2002). Inter-rater reliabilities on the measure have been reported above .95 (correlation coefficients; Mansell et al., 2002, 2003) with internal consistency .92 (Cronbach’s a; Mansell et al., 2003). In a study of 343 adults in residential accommodation, the ASM total score was found to have near zero correlations with a number of measures: staff turnover, length of service, Active Support training, management development, seniority, staff:resident ratios, and total number of staff in employment (Mansell et al., 2003). Staff support, as measured by the ASM total score in this study, was not predicted by any of these staffing or training measures, but it was predicted by residents’ younger age and higher adaptive skills scores (Mansell et al., 2003). ASM total scores did significantly predict resident engagement in activities (Mansell et al., 2003). Although the above data could suggest that improvements in staff skill and residents’ engagement levels can happen independently of staff and service characteristics, the lack of a correlation between Active Support Training and ASM total scores is somewhat puzzling, given that implementation of Active Support requires staff training. It would be interesting to examine the extent to which ASM scores relate to other observational measures of staff behavior, such as the ones used in other evaluation studies (e.g., Jones et al., 1999, 2001a). In addition, some of the ASM items (e.g., teaching embedded in activities, specific written individual programs in routine use) measure directly the presence of structural elements of Active Support, which could add an important dimension to the Active Support effectiveness literature that has so far evaluated program effects by measuring outcomes and assuming that the procedures (e.g., the paper-based system) were largely in place in the houses. The RSWPS is a questionnaire developed to measure the presence of operational procedures that relate to individual or PCP, behavioral assessment and teaching, planning of daily/weekly activities, arranging staff support for resident activity, and staff training and supervision (Lowe et al., 1998). There are no psychometric characteristics available for this measure. Researchers have reported this questionnaire as measuring the extent of ‘‘Active Support implementation’’ in the care environment (Robertson et al., 2001). RSWPS total scores were reported to be a significant predictor of staff attention after taking into account residents’ ability and staff:resident ratios (Felce et al., 2003), whereas RSWPS subscales were reported to correlate with residents’ expressed satisfaction with their accommodation, their day activities and the amount of choice they are offered (Gregory, Robertson, Kessissoglou, Emerson, & Hatton, 2001). In addition, the RSWPS subscales that measure staff support, support to staff and activity planning have been related to the presence or absence of a person with or without intellectual disability in the resident’s network of social relationships (Robertson et al., 2001). Although some of the dimensions measured
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by RSWPS are similar to Active Support evaluation outcomes (e.g., activity planning, staff support), it is not clear from the existing studies how this measure could be used to directly evaluate Active Support implementation. However, the scale has been used to describe the level of internal organization of a service in preparation for Active Support training and implementation ( Jones et al., 2001a).
8. Discussion and Future Directions In this chapter, we described the development of the Active Support model over the last 25 years and the way this can be implemented in residential services through staff training. Following the research evidence on the beneficial effects on resident participation levels and the amount/type of assistance they receive from staff, a number of issues emerge that could provide directions for future research. The first direction relates to service adoption of Active Support. Despite the fact that the model was developed more than 20 years ago, uptake of Active Support in British residential services has been quite limited. Active Support is not the only example of an intervention with limited impact on policy and service practice. Within the research field, there is mounting evidence on the effectiveness of ABAbased approaches to treating challenging behavior (e.g., Grey & Hastings, 2005), but within services written behavioral interventions are the least frequently used approach (Emerson et al., 2000). The discrepancy between research findings, policy, and practice is in contrast to the current move to employ evidence-based practices in services. Currently, there is a lack of agreement among intellectual disability researchers on the type of evidence that is indicative of effectiveness (e.g., Beail, 2005; Emerson, 2006; Lindsay, 2006; Sturmey, 2005, 2006), given the ethical and methodological difficulties in using randomization procedures in intellectual disability research (e.g., Oliver et al., 2002). The development of criteria for the type of methodology used to generate evidence and for the interpretation of evidence constitutes a significant first step in the direction of constructing an evidence base before moving on to addressing communication between the research community and services through dissemination of findings, userfriendliness of intervention protocols and guidelines and training of service staff (Corrigan, Steiner, McCracken, Blaser, & Barr, 2001). Outside the research field, the extent of the use of Active Support is less clear. In the absence of a study mapping offer and use of Active Support in the United Kingdom and abroad, it is assumed that personal choice and regional availability are key factors in its adoption. Training in Active Support is being offered to residential services staff by specialized services, usually on request of the residential services themselves. The availability of
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Active Support training within a specialized service appears to depend largely on the background and experience of the people who are in charge of the service. The latest Active Support manual (Mansell et al., 2005) attempts to address this by widening the availability of Active Support training since it is structured in a way that individuals can train themselves. This has the potential to increase adoption and implementation of the model, even outside the context of residential services, in schools and families. The limited adoption of Active Support is in direct contrast to the impact of PCP on British policy which put forward PCP approaches as the main strategy for supporting people with an intellectual disability through its influential White Paper ‘‘Valuing People’’ (Department of Health, 2001). Despite their separate parallel development, these two approaches could be combined to provide better services (Sanderson et al., 2001; Sanderson, Jones, & Brown, 2002), especially in terms of the quality of staff work (Mansell & Beadle-Brown, 2004). The experience of adopting PCP in British services has raised concerns about the relationship between planning and real life, in particular when the goals proposed have resource implications (system and skill resources; Mansell & Beadle-Brown, 2004). Small-scale implementation of Active Support so far has shown that it can be a functional model, as it addresses directly staff skills by training staff to support people to achieve the goals that have been set, and thus avoiding being an ‘‘activity trap’’ (O’Brien, 2004) or a ‘‘displacement activity’’ (Mansell & Beadle-Brown, 2004) where staff invest time and effort into creating plans that realistically cannot be put into action because of constraints. However, if Active Support were to become a system-wide approach, it is not known how large a system would need to be for Active Support to avoid this problem. There is a great amount of planning and data generated by Active Support implementation, and it has yet to be shown how large a service would need to be to cope with this amount of data. There is no research evidence so far to demonstrate the role of the monitoring system in the evaluation of effectiveness or the maintenance of the model. In our experience, only a few services so far have managed to achieve full-scale implementation of Active Support (i.e., implementation of all structural components), and one reason for this could be service restrictions related to monitoring implementation. Service resource restrictions have been identified as one of the factors implicated in the nonsuccessful implementation of behavioral programs (Corrigan, Kwartarini, & Pramana, 1992), even though data-based evidence of effectiveness is potentially a crucial factor in the adoption of behavioral programs (Backer, Liberman, & Kuehnel, 1986; Stolz, 1981). Long-term maintenance of Active Support within a service is likely to depend on some form of monitoring of individual progress and service input, and the question that future research needs to address is what form of monitoring is more effective for long-term use by services. Data on individual participation coming from
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systematic use of recording forms, and more general evaluations of implementation from staff and management (Mansell et al., 2005) are both likely candidates. Although it is likely that effectiveness might be operationalized in different ways across different services, having a specified set of outcomes and specific procedures for measuring these is essential for evaluating program success beyond the individual service. Another dimension in Active Support research that is open to investigation has to do with sufficient and necessary conditions in terms of training for Active Support to be functionally present in a house. There is some evidence from previous research ( Jones et al., 2001a) that staff training based only on workshops may not be as effective as training that includes both group workshops and individual Interactive Training. However, in the Jones et al. study the lack of effectiveness could also be attributed to the fact that the lead trainers were service managers and there was no involvement from researchers as in the other two groups. Therefore, the question about the differential impact of the two training components and whether they are both needed to make a difference still remains. If changes in staff behavior are the output and changes in residents’ behavior are the outcome, the issue of ‘‘quantity’’ of training is relevant to both of them. From an applied perspective, it is important to establish whether an incomplete or partial implementation of Active Support can have an impact on people’s quality of life or whether all elements of Active Support need to be functionally present for significant changes in the outcome. As an example, if Activity and Support Plans are being used in the house, this can make a difference in the experience of the daily living through increased participation. If, however, there are no Opportunity Plans, does this impose serious limitations on what residents could be doing and learning? So far, studies have not taken a long-term view of Active Support effects and they have not included learning as an outcome. While there is some evidence for improvements in adaptive skills (Mansell et al., 2002; Stancliffe et al., 2007), outcomes measured so far relate mainly to daily participation and staff assistance required to facilitate this participation. The degree of program implementation (or fidelity) is another dimension that is currently missing from evaluation research. Studies so far have not described the changes within the operational system of the house that happen after the introduction of Active Support and how they relate to observed changes in residents and staff. Future research needs to address this by measuring, for example, how implementation of Activity and Support Plans relates to an improvement of the current quality of life for the residents and how implementation of other system components (e.g., Teaching Plans) affects skill development of residents in the longer term and informs daily activity planning. Both participation in activities and personal development are important dimensions of the quality of a person’s life (Felce, 1997). Ensuring a better quality of life on a daily basis through
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participation in activities, without setting goals for the future, could result in daily routines becoming less purposeful and more repetitive over time and choice of activities being more of an incidental rather than a meaningful exercise. While Active Support’s main aim is to improve participation in activities—and research has demonstrated that it can do this—the question that research needs to address now is whether maintenance of these successful outcomes can be achieved in the absence of medium-term planning for skill development and learning. All the factors identified earlier as potentially important in the maintenance of Active Support relate to service or model characteristics; service restrictions in terms of capacity; extent of monitoring used for progress evaluation; and the role of medium-term planning for each resident. Successful maintenance will also depend largely on staff factors, since staff are the main deliverers of this program on a moment-to-moment basis. Staff beliefs about the effectiveness of the program and the compatibility of the program’s principles with staff attitudes are important factors in the implementation of behavioral programs (Ager & O’May, 2001; Corrigan et al., 1998; Hastings, 1997; Hastings & Remington, 1993). Active Support implementation requires changes in the organizational structure of the service in terms of team meetings and staff communication, so staff relationships and the role of managers might initially be more important in the implementation of the model than any resource restrictions. A very important dimension for future research is the effect of Active Support on challenging behavior. Outcomes have been inconsistent, with some studies reporting a significant decrease (Saxby et al., 1988), no significant changes ( Jones et al., 2001a; Mansell et al., 2002; Stancliffe et al., 2007), or significant increases (Bradshaw et al., 2004). In these studies, challenging behaviors have been observed as five different topographies: stereotypy, aggression, property damage, self-injury, and other inappropriate behavior. However, reliable measurement of challenging behaviors is not always feasible; Mansell et al. (2001) suggest that 20-s momentary time samples are not an appropriate indicator for low-frequency major challenging behaviors such as aggression. There is a need for more studies that focus on challenging behavior changes as a main outcome and where these behaviors can be reliably measured by direct observation and/or rating scales. The lack of follow-up information on challenging behavior changes needs to be addressed with more longitudinal designs, as it is very likely that short-term changes in challenging behavior can be different from any longer-term effects, given the persistence of challenging behaviors over time (Emerson et al., 2001). The relation between staff behavior changes and any potential changes in challenging behavior following Active Support training also requires further exploration. In Active Support, staff are trained to increase behaviors that initiate and maintain engagement but do not directly intervene with
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challenging behaviors. However, there are indications that the presence of severe challenging behavior interacts with adaptive skills and affects the amount of attention people receive from staff (Felce et al., 2003), which, in turn, affects directly activity engagement (Emerson, Hatton, Robertson, Henderson, & Cooper, 1999; Felce et al., 2002a; Perry & Felce, 2005). It has also been noted that staff behavior can affect the development and maintenance of challenging behavior, as its consequences are mediated by the behavior of other people (Hastings & Brown, 2000; Hastings & Remington, 1994). In addition, staff proactive behaviors, such as activity planning for every waking hour, create an environment where establishing operations that affect the motivation for exhibiting challenging behaviors are expected to change. Therefore, staff behavior can affect directly the occurrence of challenging behavior or it can do this indirectly by changing the environment. Theoretically, Active Support proposes that the latter should happen. This hypothesis, however, has yet to be tested empirically. In summary, Active Support, a model developed more than 25 years ago, based on the principles of Normalization and using techniques derived from ABA, has the potential to improve the quality of life for people with an intellectual disability who live in community settings, by increasing their opportunities to participate in activities of their daily lives, and improving the support they receive from staff. The studies described in this chapter were very important in establishing the effectiveness of Active Support, and they also have opened up a number of interesting dimensions that require further exploration in relation to the model’s adoption by services and policymakers, the factors that affect its implementation in real-world settings, and the factors that will impact on its long-term maintenance.
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C H A P T E R
S E V E N
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 Contents 1. Introduction 2. Definitional and Methodological Issues 2.1. Definitional issues 2.2. Methodological issues 3. Demographics of Child Abuse in Children with Disabilities 3.1. Prevalence studies of abuse of children with disabilities 3.2. Abuse and neglect among specific disabilities 4. Going Beyond More or Less Abuse 4.1. The ecology of child abuse: Theoretical issues 4.2. Characteristics contributing to child abuse among typically developing children 4.3. Characteristics contributing to abuse among children with disabilities 5. Remaining Issues for Research 5.1. Correlates or antecedents? 5.2. Same or different amounts of each risk factor? 5.3. What percentage of the variance is accounted for by each risk factor? 5.4. How should screening and intervention be performed? 6. Conclusion Acknowledgments References
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Abstract Information concerning abuse and neglect of children with disabilities is scarce, research suffers from definitional and methodological shortcomings, and few studies examine why these children are at an increased risk of abuse. In this Vanderbilt Kennedy Center and Department of Special Education, Peabody College at Vanderbilt University, Nashville, Tennessee 37203, USA International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35007-6
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2008 Elsevier Inc. All rights reserved.
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chapter, we first discuss general definitional and methodological limitations, specific issues related to the abuse of children with disabilities, and efforts of child abuse researchers to overcome these limitations. We then discuss the prevalence of maltreatment among children with disabilities. Next, we present and apply to children with disabilities an ecological approach to child abuse, showing how certain societal, familial, parental, and child characteristics function to increase these children’s risk of abuse and neglect. We conclude by describing four research directions for better understanding the abuse of children with disabilities.
1. Introduction It has often been said that the test of a civilized society is how well that society protects its most vulnerable members. With such federal programs as Head Start, Social Security, and Temporary Assistance for Needy Families, our society provides a safety net for many millions of our citizens. Granted, debates have raged for years as to whether there are enough of these programs, and whether each program’s funding levels, eligibility criteria, and comprehensiveness of services are adequate to address the needs. Although not always considered in such debates, children with disabilities are among those in need. Moreover, given the need to protect and support these children, it is shocking that children with disabilities are at a significantly increased risk of experiencing abuse and neglect. Even more distressing, most of this abuse comes at the hands of parents and other caregivers. In this chapter, we tackle the difficult, complicated issue of what is known and what needs to be known about the maltreatment of children with disabilities. We begin by defining the term child abuse itself, noting the types of abuse, the varying definitions used by different professionals, and other methodological problems that arise when studying child abuse. Although such problems are well-known—and researchers explicitly point out such limitations in their own studies—we explore such issues to provide a clearer picture of just how difficult it is to examine child abuse in children with disabilities. Cognizant of the many difficulties involved in this type of work, we then discuss issues of the prevalence and types of child abuse experienced by these children. Specifically, we compare rates of abuse among children with versus without disabilities, note which specific types of abuse seem most likely in children with disabilities of a certain type and explore other predisposing factors in children and their parents. Going beyond the ‘‘how many’’ debate, the next section then discusses why child abuse occurs. Using Belsky’s (1980) version of an ‘‘ecological approach’’ to child abuse, we explore the ways in which the risk of child abuse and
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neglect is a function of the interaction among societal, family, parent, and child characteristics. We end by describing four research directions for better understanding the abuse of children with disabilities.
2. Definitional and Methodological Issues Before focusing specifically on abuse among children with disabilities, it is important to first discuss the various complications that arise when studying child abuse and neglect. Because of definitional and methodological complications, it often becomes difficult to measure prevalence of abuse and to compare studies of child abuse and neglect. When studying children with disabilities, further definitional considerations must be mentioned, as studies may use varying definitions for specific types of disabilities. Finally, certain methodological difficulties arise when studying children with and without disabilities who have experienced abuse. We begin this discussion, then, with a brief background into these definitional and methodological problems, before examining questions concerning how often abuse occurs among children with disabilities.
2.1. Definitional issues Although most of us have some idea of what child abuse is, defining abuse and neglect is complicated by two considerations. The first is that abuse is divided into four distinct types. Defined in Table 7.1, the four major types of child abuse are physical abuse, sexual abuse, emotional abuse, and neglect. When reviewing studies of abuse and neglect, however, it is difficult to compare findings because authors sometimes include all four types of abuse in their investigation, while others focus on one or two specific types of maltreatment. Further, when authors examine multiple types of maltreatment, some will report findings of each type of abuse separately, while others report on abuse overall (Horner-Johnson & Drum, 2006). Finally, it is difficult to parcel out if children experienced only one type of abuse, or if the children suffered from multiple types of abuse. The term ‘‘child maltreatment’’ further complicates this issue as the definition of child maltreatment can differ for each study, in whether it includes all four major types of abuse or only a select few. A second complication relates to which criteria of abuse are used in a particular study. For some, it has become the convention in research studies to include only substantiated cases of child abuse so as to maintain some degree of internal reliability. Applying this criterion, however, will exclude reported or suspected cases of abuse, which may be particularly beneficial to study. Also, within substantiated cases of abuse, there may be differences depending on whether the parents were charged in the criminal court or if
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Table 7.1 Definitions of child abuse and neglect Type of abuse
Physical abuse Sexual abuse Emotional abuse Neglect
Definition
Physical acts that cause or could cause physical injury to the child When a person involves the child in sexual activity to provide gratification or financial benefit to the perpetrator Acts (such as verbal or emotional assault) or omissions that cause or could cause conduct, cognitive, affective, or other mental disorders Physical includes abandonment, expulsion from the home, failure to seek remedial health care or delay in seeking care, disregard for hazards in the home, inadequate supervision, or inadequate food, clothing, or shelter Emotional is proving inadequate nurturance or affection, permitting maladaptive behavior, and other inattention to emotional/developmental needs Educational is permitting chronic truancy or other inattention to educational needs
Source: Sobsey et al. (1997).
the case was settled through Child Protective Services (CPS). Such differences arise because, among the different professionals working with abused children and investigating reports of child abuse, different criteria are used to determine if the child was abused. For example, individuals in the medical field are more likely to suspect and ‘‘define’’ abuse based on visual evidence presented at the doctor’s office or hospital. Lawyers and courts, on the other hand, more often collect testimony from the child, the parents, and other possible witnesses, as well as consider the visual evidence. Most of this disagreement among professionals exists because detecting and prosecuting child abuse is still relatively new, and parents are only recently being held accountable for their actions. Thus, while the different criteria for determining child abuse overlap to some extent, they are still not perfectly in sync with one another (Pianta, Egeland, & Erickson, 1990). As Giovannoni (1990) explained, ‘‘at various times child abuse has been defined in statutes, by judges interpreting those statutes, by social workers intervening in the problem, by medical practitioners managing a medical entity, or by lawyers assuring legal rights’’ (p. 10). Specifically, then, the different criteria that have been used to define child abuse include: Medical definition: First defined by Kempe based on radiological evidence of multiple fractures, ‘‘battered child syndrome’’ became the medical
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construct of child abuse (Kempe, Silverman, Steele, Droegemueller, & Silver, 1962). These children typically presented to medical professionals with fractures, subdural hematomas, failure to thrive, and multiple soft tissue injuries. Importantly, for diagnosis of battered child syndrome, skeletal injuries in several locations at different stages of healing were also evident. Prior to Kempe’s presentation of battered child syndrome to the American Academy of Pediatrics, recognition of child abuse was only slowly arising and parents were rarely held accountable for their actions. Physicians in the twentieth century began to suspect that parents were abusing their children, as different lesions, fractures, and hematomas were frequently observed. While some physicians attempted to explain such trauma through causes such as the child having weak bones, it was becoming apparent that abuse was most often the correct diagnosis. Despite suspicion of parental abuse, most parents were never held accountable for injuring their child, as they simply denied maltreatment or claimed they could not remember any trauma occurring to the child (Lynch, 1985). Today, the medical definition of child abuse is still vague, with common diagnoses including ‘failure to thrive,’ ‘nonaccidental trauma,’ and ‘battered child syndrome.’ For these diagnoses to be considered a form of maltreatment, however, precipitating factors leading to the incident must also be taken into consideration (Giovannoni, 1990). Currently, a medical diagnosis of child abuse is provided not only to identify that abuse has occurred, but also to identify characteristics within the abuser that led to child abuse and to develop therapeutic interventions for the child who was abused (Aber & Zigler, 1981; Socolar et al., 2001). Finally, the medical definition of child abuse relies on each individual physician determining if the circumstances are indicative of abuse and worthy of reporting. The physician must not only provide medical diagnoses and treatments to the physical injury, but must also determine if the situation warrants legal and social intervention. For example, if a young child presents with a fracture, the physician must consider that certain fractures (metaphyseal and posterior rib fractures) are more indicative of child abuse than are other types of fractures ( Jenny, 2006). The medical definition of child abuse, then, varies by practitioner and hospital (Giovannoni, 1990). Legal definition: The legal definition of abuse is as vague as the medical definition, as definitions and reporting procedures vary by state (Vig & Kaminer, 2002). Within the legal system, the definition includes all four types of abuse, but this definition usually focuses on harm to the child, as well as characteristics of the abuser and the actual act of abuse. Legal definitions also consider whether the abuse was intentionally inflicted on the child. Within the legal system, there are three different but equally important statutes that relate to child abuse. The criminal statutes define child abuse as
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a criminal act that can be prosecuted; the dependency statutes relate to children who become wards of the state; and reporting statutes define who is responsible for reporting child abuse to authorities. All three statutes, however, are vague in detail and often contain such catchall phrases as ‘‘or any other care necessary for his well-being’’ (Giovannoni, 1990). As a result, the different courts that are hearing the cases are left to interpret the meaning of such statutes. Further, while every state has a mandatory reporting law if there is reasonable suspicion of child abuse, wide variations exist in the statutory language and little guidance is provided as to the definition of ‘‘reasonable suspicion.’’ Not surprisingly, there is inconsistent reporting of (possible) abuse (Levi & Brown, 2005). Finally, court intervention can occur if the child is considered to be endangered, although mandatory reporting to state social services is only necessary when the abuse has been substantiated. In order for abuse to be substantiated, there must be evidence that physical abuse caused disfigurement or other serious bodily injury, or that emotional abuse caused severe anxiety, depression, or other psychological symptoms (Aber & Zigler, 1981). Assessing such characteristics for substantiation, however, can be difficult. When courts rely on testimony from the child who was abused, difficulties arise for individuals with disabilities who cannot accurately report the event or when courts consider the individual to be an unreliable witness (Cederborg & Lamb, 2006; Mitchell & Buchele-Ash, 2000). In such situations, cases that are usually closed before an adequate investigation can be conducted. Research definition: When studying child abuse, researchers must decide which definition of abuse they are going to employ in their study. Those who rely on welfare agencies or CPS records of child abuse will be likely to collect data on substantiated cases of child abuse committed by family members. Most likely absent from these records, though, will be sexual abuse (more often committed by outside perpetrators) and abuse of children living in institutions, foster homes, and other public settings and settings outside of the family. Further, in relying solely on substantiated cases of child abuse, the researcher risks missing valuable information related to children with disabilities. This risk stems from factors directly related to children with disabilities, such as their inability to disclose the abuse. Furthermore, even if a single universal definitional standard were adopted, it would be difficult to achieve consistency because different reporting settings vary in how definitions are used in diagnosis. For example, to determine if doctors’ reporting differed by the type of hospital at which the child was seen, Trokel, Wadimmba, Griffith, and Sege (2006) investigated doctors’ detection and reports of child abuse from physical injuries treated at different hospitals across the country. These authors collected data from 2253 infant patients (<1 year of age), who presented at the hospital with either traumatic brain injuries or femur fractures (2 injuries highly
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suspicious of abuse etiology). These authors then examined if the doctors differed on their detection and reporting of child abuse based on the type of hospital in which they worked. Even when children presented with the same type of injury, those seen at children’s (vs. general) hospitals were twice as likely to receive diagnoses of child abuse. Other studies have found that doctors are more likely to suspect child abuse if the child is younger, more severely injured, from a single-parent family, and if the mother is poorly educated (Trokel et al., 2006). In examining child abuse among children with disabilities, further definitional complications arise. First, different studies may use the same term for a disability, but may apply a very different definition, usually based on who is providing the diagnosis. For example, when applying the term mental retardation, Crosse, Kaye, and Ratnofsky (1993) excluded children with fetal alcohol syndrome, prenatal substance exposure, motor delays, or language delays. The authors then compared their data to the incidence of mental retardation as determined by the US Office of Education, which would include many of the children they excluded in the category of mental retardation. A further example is the use of the term ‘‘intellectual disability.’’ As Horner-Johnson and Drum (2006) explain, ‘‘the term ‘intellectual disability’ is used in many countries to describe what has often been referred to in the United States as mental retardation, developmental disability (particularly intellectual limitations), or cognitive disability. It is also similar to the terms learning disability or learning difficulties as used in the United Kingdom, which are distinct from the US use of learning disability as a condition that affects scholastic achievement (e.g., dyslexia) without necessarily implying limitations in overall intellectual functioning’’ (p. 58). These distinctions are important to consider and must be noted when reviewing and comparing different research reports. Second, in many studies of children with disabilities, children with different types of disability are grouped into broader categories for comparison and statistical purposes. For example, in their prevalence study of child abuse among children with disabilities, Sullivan and Knutson (2000) grouped children into four main disability categories including: behavior (behavior disorders and autism); communication disorders (combined speech, language, hearing and learning disabilities); mental retardation (combined all degrees of mental retardation from mild to profound); and orthopedic and health-related (combined visual impairment, orthopedic disabilities, and health-related disabilities such as asthma and juvenile rheumatoid arthritis). In examining these categories, however, some questions may arise. Did any of the children with autism also have mental retardation? While 75% of children with autism also have mental retardation (Dawson & Toth, 2006), it would be helpful to know in which category children with both diagnoses were placed. In addition, why are learning disabilities
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combined with communication disorders? In what category are children with Attention Deficit Hyperactivity Disorder (ADHD) placed? Finally, considerations must be given to who is providing the diagnosis for the research study. Crosse and colleagues (1993) relied on disability information provided on the reports written by CPS workers rather than using a diagnosis provided by a doctor or other trained professional. The reliance on case workers to provide disability information limits the study in two important ways. First, the authors themselves recognized that CPS agencies rarely recorded disability status in a systematic fashion. Second, the CPS workers most likely never received special training to recognize and ‘‘diagnose’’ specific disabilities. Concern is raised, then, for missed diagnoses and differential diagnoses based on agency. Sullivan and Knutson (2000), on the other hand, used the diagnoses provided by a multidisciplinary school team which determined that the child met the criteria for a specific disability and was eligible for special education services. In using this criterion, however, the authors may have missed some students who had not yet received diagnoses, or those students whose disability did not impact their education and thus were not identified in the school database.
2.2. Methodological issues Just as different types and applications of definitions complicate the study of child abuse, so too is this area burdened by other methodological problems. Samples of convenience: Samples of convenience are used when the sample includes children served by a particular hospital, intervention program, or other easily accessible setting. The problem is that many such settings serve a biased sample of children and their families, a sample that may differ, often in unforeseen ways, from children and families in the larger population. Although issues involving samples of convenience are widespread within the disabilities field (Hodapp & Urbano, 2007), such concern may be exacerbated when one is examining abuse and neglect among children with disabilities (Horner-Johnson & Drum, 2006; Spencer et al., 2005). To investigate a certain population of children, then, many researchers decide to over-select for children with disabilities among those who were abused (e.g., from hospitals), or over-select for children who were abused among those who have disabilities (e.g., from CPS; Verdugo, Bermejo, & Fuertes, 1995). This concern is important because the research is ‘‘extrapolating from highly selected populations to national populations and comparing disability and abuse rates. . ..Extrapolation from selected cohorts to whole populations is open to serious potential for bias’’ (Spencer et al., 2005, p. 609). Further, selection bias may lead to examining the most extreme cases, while missing others.
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To give one example, Ammerman, Hersen, Van Hasselt, Lubetsky, and Sieck (1994) determined the prevalence of abuse among 138 children with disabilities who were hospitalized. Within that sample, 61% had experienced some form of abuse by a caregiver. Can we then conclude that three of every five children with disabilities experience some form of abuse? Probably not. Indeed, fully appreciating the limitations involved in using the hospital as a sample of convenience, Ammerman et al. cautioned against extending their prevalence rates of abuse to other samples of hospitalized (or nonhospitalized) children with disabilities. Data collection: To study abuse among children with and without disabilities, the most common approaches to data collection include: reviewing reports of child abuse to state agencies (CPS), collecting retrospective self-report data from adults about their youth, collecting questionnaires from the child’s caregiver or professionals serving the child, and (more recently) collecting evidence through whole population databases of multiple reporting agencies (Horner-Johnson & Drum, 2006; Spencer et al., 2005; Sullivan & Knutson, 2000; Verdugo et al., 1995). Aside from data collection from population database studies, the use of different reports of child abuse causes problems with validity and reliability. The first concern is that criteria for reporting child abuse vary by jurisdictions, states, and agencies, making it difficult to compare definitions between studies (Vig & Kaminer, 2002). Further, researchers using reported cases of child abuse are relying on child care professionals, family members, and neighbors to report suspected child abuse; there is no way of knowing which criteria a particular reporter has relied on to report such incidents (Aber & Zigler, 1981). Another concern is that state agencies do not always collect data on a child’s disability status. In the most recent annual publication of child maltreatment data collected via the National Child Abuse and Neglect Data System (NCANDS; US Department of Health and Human Services, Administration on Children, Youth and Families, 2007), only 39 of the 50 states reported information regarding disability. NCANDS authors recognized that children with disabilities were likely undercounted. Further, within the NCANDS report, disabilities were grouped into seven distinct categories: mental retardation, emotional disturbance, visual/hearing impairments, learning disability, physical disability, behavior disorders, and other medical conditions. Unfortunately, no accompanying definitions were provided for each disability category. Equally problematic, Bonner, Crow, and Hensley (1997) found that, while 32 states provided some assistance to state agencies in identifying disabilities among children who were abused, only 7 states required any sort of training in working with children with disabilities. Finally, when agencies do collect information on disability, some only check yes or no as to whether a disability was present, while even fewer document specific disabilities.
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Retrospective studies: A third problem relates to retrospective studies, particularly when one is attempting to determine the antecedents of maltreatment. In such studies, samples of children who were already maltreated are examined for relations between the maltreatment and past characteristics of the child or parent (Pianta et al., 1990). For studies of children with disabilities, however, it is often difficult to determine if the child’s disability was caused by maltreatment or if instead maltreatment was a consequence of the child’s disability. This ‘‘cause or consequence’’ issue characterizes most studies of abuse and neglect among children with disabilities. For some, the easiest way around this dilemma is to use samples of convenience—to focus on the abuse of specific populations of children with disabilities—thus leading to a vicious circle in child abuse research (Bonner et al., 1997). Another possible way around this problem involves prospective studies. Currently, prospective studies are typically designed for child abuse prevention research. These studies identify parents and children who are ‘‘at risk’’ for child abuse, based on such factors as low socioeconomic status (SES) and single-parent households. This methodology is problematic in four ways. First, as will be discussed later, risk assessments are short and simplistic. The assessments do not collect data on all of the different risk factors that could be present within a family. Most concerning, because these assessments are performed immediately before or after the child’s birth, they do not assess child characteristics or behaviors that could likely lead to abuse. Second, the risk assessments generally do not check for disability, and might miss many families with children with disabilities. Third, most studies are short-term, only following families for the first 6–12 months of the child’s life. Abuse may occur after the study is complete, but the authors will be unaware of such abuse if no follow-up procedures are in place. A final problem is that risk assessments will only follow families considered ‘‘at risk’’ for child abuse, thus making it difficult to compare such families to a representative sample of the general population, or to families whose largest risk for abuse is simply having a child with a disability in the family. Future studies could change prospective research in two ways. First, researchers could increase the factors used in risk assessments and then attempt to follow the large numbers of such families enrolled in longitudinal studies. Second, researchers could follow a large cohort of families, both who are considered to be at risk and those who are not considered to be at risk of abuse. Antecedents of maltreatment could then be identified while also identifying the characteristics that lead to difficulties in the parent–child relationship (Pianta et al., 1990). Although it may be easy to recommend large-scale, longitudinal, prospective studies, they are generally time-consuming and expensive, requiring resource commitment over many years. The difficulty in performing
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such studies may be one reason why so few examine abuse among children with disabilities. Even in the absence of such prospective studies, however, judicious use of retrospective population-based studies sheds some light on the cause-orconsequence question. Specifically, Sullivan and Knutson (1998a, 2000) found that certain disabilities seemed to constitute risk factors for maltreatment when the children were younger (i.e., communication and health/ orthopedic problems), whereas others were both a risk factor and a possible consequence of abuse in later years (i.e., behavior disorder, learning disabilities, mental retardation). Communication disorders and health/orthopedic problems are also conditions that may be diagnosed earlier in life than behavior disorders, learning disabilities, and mental retardation. Further the latter three disabilities could be both causes and consequences of abuse. Despite the evidence provided by Sullivan and Knutson (2000), then, more research is needed to determine the timing of abuse and disability. One further complication is that disability and child abuse are both dynamic events that often unfold throughout the lifespan. It is difficult, therefore, to determine a specific point in time when the abuse began or when the disability began. A disability could have been present from birth, yet the diagnosis might not have been given until the child was in middleto-late childhood. For example, autism cannot be accurately diagnosed until age 2 (Stone et al., 1999). Knowing the date of diagnosis, therefore, still may not accurately tell if the disability was present before the abuse. What it does make clearer, however, is the timing of when the parent was knowledgeable about the child’s disability. Although studies are far from perfect, researchers have worked hard to determine whether child abuse is a cause or consequence of various types of child disability, at various ages. Low rate of reporting: The fourth methodological problem concerns the low rate of reporting of abuse (Petersilia, 2001). Because child abuse occurs relatively rarely, determining true prevalence rates of abuse among children with disabilities may be difficult. This low rate of reporting comes from both the children with disabilities and from those who work with these children. Low rates of reporting by the children relate to a lack of recognition that they have been abused; difficulties in reporting the abuse (e.g., nonverbal children cannot tell others they are being abused); and fear of reporting the abuse (Bryen, Carey, & Frantz, 2003; Westcott & Jones, 1999). Children with disabilities are often unintentionally taught to comply with authority and to allow others to handle their bodies. Such teachings could lead to their failure to recognize abuse (Hibbard, Desch, & the Committee on Child Abuse and Neglect and Council on Children with Disabilities, 2007; Sobsey, 1994). Once the abuse has been recognized, it still may be difficult for children with disabilities to accurately report the abusive events, especially if they are interviewed in inappropriate ways
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(e.g., not providing appropriate language on communication boards, asking questions that are too advanced for the cognitive level; Westcott & Jones, 1999). Those who work with children with disabilities may also miss signs of child abuse. Few caregivers, for example, have been trained to recognize possible signs of abuse or how to respond to suspicions of abuse. From the other side, professionals who are experts in issues of child abuse may attribute certain behaviors or markings, indicative of abuse in most cases, to be a consequence of the child’s disability (e.g., self-injurious behavior, repetitive behaviors; Westcott & Jones, 1999; Zigler & Hall, 1990). Two types of misdiagnosis thus arise. In the first case, a child who has been abused—but who also has a condition predisposing to ‘‘abuse-like’’ sequelae—will not be reported as abused. Thus, if a child has osteogenesis imperfecta (brittle bones), a physician could misattribute signs of abuse to the injuries often associated with the child’s impairment and not report child abuse to authorities. Conversely, in the case of a child with an undiagnosed condition such as hemophilia, the physician might mistakenly attribute a child’s injuries (e.g., multiple bruises) to abuse, and report a nonabusive parent to authorities ( Jenny, 2006). Further, personnel working for CPS rarely receive training related to children with disabilities, so that they do not know appropriate ways to investigate and respond to these children (especially nonverbal children). Just as in the area of dual diagnosis (i.e., mental retardation and mental illness), there may be some degree of ‘‘diagnostic overshadowing’’ concerning the diagnosis of abuse and neglect among children with disabilities. It is important, then, for a multidisciplinary team to be involved in the assessment of abuse allegations for children with disabilities. Individuals from CPS would have to collaborate with individuals knowledgeable about the child’s disability to perform interviews and assessments in developmentally appropriate ways. In summary, all studies of child abuse and neglect contain definitional and methodological limitations that are inherent to this domain of research. Fortunately, most researchers acknowledge such limitations and make efforts to account for them as much as possible. First steps in confronting these limitations include providing precise definitions of the type of child abuse and neglect studied, and also providing definitions and inclusion criteria of disabilities examined. Further steps that researchers have taken include setting strict guidelines as to how abuse is determined, and explaining the source of the diagnosis of abuse and disabilities. By providing such details, future studies can make similar efforts so that data can later be compared. In the face of such definitional and methodological complications, strong studies of abuse and neglect have been conducted and important information has been learned concerning the population of children who suffer from maltreatment. The following sections will summarize the
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important information that has been learned about the demographics of child abuse in children with disabilities and about the risk factors for child abuse and neglect among children with and without disabilities.
3. Demographics of Child Abuse in Children with Disabilities Despite the above-mentioned limitations, most studies designed to estimate the prevalence of abuse among children with disabilities have found an increased rate of maltreatment (Ammerman & Baladerian, 1993; Crosse et al., 1993; Spencer et al., 2005; Sullivan & Knutson, 2000). In fact, Horner-Johnson and Drum (2006) recently conducted a meta-analysis of the prevalence literature published after 1994 concerning abuse of individuals with intellectual disabilities. Although maltreatment estimates varied widely, children and youth with intellectual disabilities had prevalence estimates for maltreatment between 11.5% and 28%, compared to a rate of 1.21% for children without disabilities (based on data from US Department of Health and Human Services, Administration on Children, Youth and Families, 2005).
3.1. Prevalence studies of abuse of children with disabilities Three comprehensive, population-based studies illustrate that maltreatment is greater among children with disabilities. Crosse et al. (1993) conducted one of the earliest studies of the prevalence of child abuse among children with disabilities. In 1991, they collected prospective data from 35 CPS agencies (a nationally representative sample) that provided information on all cases of substantiated abuse received within a 4- to 6-week period. They then compared children with and without disabilities to determine the difference in the prevalence of abuse across these two populations. Children with disabilities were 1.7 times more likely to experience abuse than were children without disabilities. Crosse et al., however, wrote, stated that these numbers likely underestimated the true percentages. Specifically, the authors relied on CPS workers to assess impairments and provide diagnoses of the children rather than obtaining diagnoses from physicians or other professionals familiar with disabilities. Further, in relying on reports to CPS, this study most likely missed children in residential care settings and most forms of abuse outside of the family. Finally, while this study was prospective in design, Crosse et al. were still unable to determine if the child’s disability was present before the abuse, as they had no information about the children prior to the CPS investigation.
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In another prevalence study, Sullivan and Knutson (2000) conducted a population-based examination of abuse and neglect among children in Omaha, Nebraska. Their study examined 50,278 children, ages 0–21, who were enrolled in early intervention services or schools during 1994–1995. To determine the prevalence of child maltreatment among these children, Sullivan and Knutson merged the schools’ electronic databases with records from the Central Registry of the Nebraska Department of Social Services, and the victimization records from the Omaha Police Department and the Douglas County Sheriff’s Office. To determine if a student had a disability, they examined enrollment in special education within the school system. Specific disabilities included behavior disorders, mental retardation, learning disabilities, health-related disorders, speech and language disorders, physical and orthopedic disabilities, hearing impairments, visual impairments, and autism. Sullivan and Knutson found a 31% rate of maltreatment of children with disabilities, as compared to a prevalence rate of 9% for children without disabilities. As previously stated, there are a few methodological considerations to remember when interpreting data from the study by Sullivan and Knutson (2000). Briefly, the authors may have missed some children with disabilities who were not identified through the school system; they were unable to determine if abuse or disability came first; and the categories of grouping disabilities may be different from those of other studies. But this study also had three important methodological strengths. First, because the study was population based, Sullivan and Knutson eliminated the need to rely on samples of convenience, and any associated selection bias or over-selection of certain conditions (e.g., children with disabilities or children who were abused). Second, by including reports of abuse to law enforcement as well as to CPS, the authors were able to account for abuse outside of the family, as well as familial abuse (Sullivan & Knutson, 1998a). Finally, because the authors used diagnoses provided by the school system, they were more accurate in their assessment of disabilities. Spencer et al. (2005) also conducted a whole-population prevalence study of child abuse in West Sussex, England. The authors retrospectively followed all children born between January 1983 and the end of December 2001. Similar to Sullivan and Knutson (2000), to estimate the prevalence of child abuse within the population, Spencer et al. merged records from the West Sussex Child Health Computer (which includes documentation of all children with special needs) with the West Sussex Social Services’ child protection register. Disabilities of interest included cerebral palsy, conduct disorder, psychological problems, autism, speech and language disorders, ‘‘learning disabilities’’ (¼mental retardation, IQ < 70), and sensory disabilities. Of the 119,729 children examined, 1,853 children (or 1.5%) were entered in the child abuse registry. Similar to findings from previous studies, children with disabilities were found to have increased child abuse
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registration. Specifically, children with conduct disorder, psychological problems, speech and language disorders, and learning disabilities were three to seven times more likely to experience abuse than children without disabilities. Again, methodological considerations must be taken into account when reviewing the Spencer et al. (2005) study. First, because the authors were unable to determine the age of onset of disability, the cause-or-consequence question cannot be addressed in this study. Spencer et al. specifically state that children with cerebral palsy could have the condition as a result of child abuse, as could those with conduct disorders. Second, the authors also acknowledge that reliance on child abuse registration most likely underestimates the true prevalence of child abuse, as unreported cases and those with poor investigations are not included. There were, however, particular strengths associated with this study as well. First, similar to Sullivan and Knutson (2000), this population-based study eliminated the confounding variables associated with convenience sampling and selection bias. Second, the use of the West Sussex Child Health Computer ensured that disabilities were identified by trained personnel. While this allowed definitions of disabilities to remain mostly consistent, the authors acknowledged that diagnostic classification standards may have changed throughout the study time period (e.g., diagnostic criteria for autism). Finally, Spencer et al. also accounted for potential confounding variables, such as the child’s birth weight and the parent’s SES, when calculating the risk status for each disability.
3.2. Abuse and neglect among specific disabilities Among children with disabilities who are reported to be abused, most studies have also found that prevalence rates vary based on type of disability. Unfortunately, only recently have databases such as the NCANDS started including disability as a demographic category in data collection. Even now, only 39 states report a child’s disability status, and only certain categories of disabilities are reported (US Department of Health and Human Services, Administration on Children, Youth and Families, 2007). Because of this lack of detailed reporting, most researchers still consider that their studies underestimate the prevalence of abuse among children with disabilities. Still, some studies have parceled out types of disabilities in order to compare prevalence rates. 3.2.1. Specific disabilities Among all disabilities examined in their study, Sullivan and Knutson (2000) found that maltreatment was most prevalent among children with behavior disorders, speech/language impairments, and mental retardation. Conversely, Spencer et al. (2005) found that children with autism and sensory disorders
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were not at increased risk of abuse. Such findings support Sullivan and Knutson, who also found that children with autism were not at as high a risk as most other disabilities. These findings are opposed, however, with reports that among those with autism and Asperger’s syndrome treated in a community mental health setting; one in five had experienced physical abuse, and one in six sexual abuse (Mandell, Walrath, Manteuffel, Sgro, & PintoMartin 2005). Girls with ADHD are found to be at higher risk of abuse than those without ADHD (some cases were able to show abuse occurred before diagnosis; Briscoe-Smith & Hinshaw, 2006). Sullivan and Knutson reported that children who are deaf and hard-of-hearing are at particular risk of child abuse compared to other disabilities (Sullivan & Knutson, 1998b). Finally, children with severe speech deficits were found to be at higher risk for maltreatment and the worse the speech impairment, the more at risk the child was for abuse (Verdugo et al., 1995). The authors agreed with more recent speculations that these children were most likely more susceptible to abuse because of their inability to report the abuse to others. 3.2.2. Levels of functioning/severity of disability While children with all types of disabilities are at increased risk of abuse (Levy & Packman, 2004), children with more mild (as opposed to more severe) disabilities are at greater risk (Verdugo et al., 1995). Verdugo et al. found that children with only slight developmental problems were at greater risk of maltreatment than were those with more severe disabilities. They concluded that children whose disabilities were less obvious were more likely to be abused. Similarly, Zirpoli, Snell, and Loyd (1987) found a significant relationship between level of functioning and abuse potential. Those whose level of functioning was considered ‘‘profound’’ were not abused as often as those whose level of functioning was considered as severe. These authors suggested that individuals with profound levels of intellectual disability may have limited interaction skills, thus reducing their contribution to the abusive cycle. Finally, in a review of sexual abuse against children and adolescents with intellectual disability, those with mild-to-moderate intellectual disabilities were more likely to have suffered abuse than those with severe intellectual disabilities (Balogh et al., 2001). Vig and Kaminer (2002) commented that children with more mild disabilities may be more susceptible to abuse because the uncertain outcomes of these children are more frustrating to their parents. Conversely, families of children with more severe impairments may have more realistic expectations for their child’s progress. Finally, children with more mild disabilities are not as readily detected. These children, then, may be diagnosed later in life, thus receiving disability services later. These same children, however, may display undesirable behaviors that, while related to the disability, may be mistakenly attributed to the child’s character.
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The main complication in understanding the relation of level of functioning to child abuse occurs when an individual’s maladaptive behavior is also examined. In their study, Zirpoli et al. (1987) found that almost twice as many subjects who were ‘‘frequently’’ violent, disruptive, rebellious, or hyperactive were abused than those who were not. Similarly, Verdugo et al. (1995) found that the worse the child’s behavior, the worse the maltreatment. More than 60% of children who had been maltreated in their study showed stereotyped behavior, eating problems, a difficult temperament, and self-injurious behaviors. While Zirpoli and colleagues suggested that individuals displaying maladaptive behaviors may be contributing to the abusive cycle, these data again raise the question: what came first, the abuse or the behavior? Experiences of physical and sexual abuse in childhood have been linked to later displays of externalizing behaviors, such as aggression and self-destructive behaviors (Margolin & Gordis, 2000). It is possible, therefore, that the maladaptive behaviors may be exacerbated by the abuse the individuals have suffered. 3.2.3. Type of abuse and type of disability While it is clear that children with disabilities are at risk of experiencing all types of abuse at greater rates than children without disabilities, some disabilities may be somewhat more susceptible to certain types of abuse. Sullivan and Knutson (2000) reported that, compared to children without disabilities, children with behavior disorders were 7 times more likely to experience neglect, physical abuse, and emotional abuse, and 5.5 times more likely to experience sexual abuse. Children with speech and language impairments were at 5 times the risk for neglect and physical abuse, almost 3 times the risk for sexual abuse, and almost 7 times the risk for emotional abuse. Finally, children with mental retardation were at 4 times the risk to experience all forms of abuse. Furthermore, compared to children without disabilities, children with learning disabilities, health-related disabilities, autism, and orthopedic disabilities were at least twice as likely to experience most forms of abuse (see also Jonson-Reid, Drake, Kim, Porterfield, & Han, 2004). Although more abuse clearly occurs in certain disabilities (e.g., behavior disorders) than in others (e.g., autism, visual impairments), children with specific disabilities may also vary slightly in their proneness to experiencing one versus another type of child abuse. Additional issues relate to types of maltreatment, the recurrent versus single-incident nature of abuse, and the perpetrators of child abuse. Sullivan and Knutson (2000) found that children with disabilities were more likely than children without disabilities to experience multiple forms of maltreatment (63% vs. 54.9%, respectively) and recurring episodes of maltreatment rather than a single episode (71% vs. 29%, respectively). Immediate family members were most often the perpetrators of abuse, accounting for 92.4% of neglect cases, 82.2% of physical abuse cases, and 89.5% of emotional
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abuse cases. Even in the area of sexual abuse, immediate and extended family members accounted for 53.1% of the cases. In all categories of disability, children were most likely to experience neglect, followed in order by physical abuse, emotional abuse, and sexual abuse. 3.2.4. Additional demographic issues In addition to the amount of abuse and other characteristics of the children with disabilities, other demographic factors have also been examined. These include the following: Age: Children with health or orthopedic and communication disabilities were most likely to be abused between birth and 5 years of age, whereas children with behavior disorders and mental retardation experienced abuse across the age ranges (Sullivan & Knutson, 2000). Gender: Boys and girls without disabilities are equally likely to experience child abuse. For children with disabilities, however, many studies have found that rates of abuse vary by gender and type of abuse. Specifically, Sobsey, Randall, and Parrila (1997) found that boys with disabilities were twice as likely to experience abuse compared to girls with disabilities (using data from Crosse et al., 1993). More specifically, these authors found that boys with disabilities were at significant risk of experiencing physical abuse and neglect. Sullivan and Knutson (2000) found that females without disabilities were more likely to experience abuse; for those with disabilities, males were more likely to experience abuse. Their results were similar to those of Sobsey et al. (1997) in that males with disabilities experienced physical abuse and neglect more often than females with disabilities. Girls without disabilities, on the other hand, were more likely to experience physical abuse, neglect, and sexual abuse than were boys without disabilities. Both studies also found that females with disabilities were more likely to experience sexual abuse than males with disabilities. It is important to note, however, that the authors of both studies assert that the higher prevalence of males with disabilities (vs. females with disabilities) in the population may account for the greater prevalence of males with disabilities in the maltreated sample. Forms of abuse: Compared to girls with disabilities, boys with disabilities were more likely to experience physical abuse and neglect. Although many more girls with disabilities (62%) than boys with disabilities (38%) were sexually abused, a significantly larger percentage of boys with (vs. without) disabilities experienced sexual abuse (Sobsey et al., 1997). Even in spite of the various definitional and methodological issues, then, the data seem clear that children with disabilities are more likely to experience abuse and neglect than are children without disabilities. Although it remains unclear exactly how often (compared to children without disabilities) such children are abused, almost every study converges on the overabundance of abuse in this population. Children with different types of
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disability also seem to differ in how likely they are to be abused; certain disability types may more often experience certain types of abuse, and boys as opposed to girls with disabilities seem more often abused.
4. Going Beyond More or Less Abuse Determining the prevalence of maltreatment among children with disabilities constitutes only an initial step in understanding the relation between abuse and disability. More important and more difficult is to understand the reason, the why of greater susceptibility. Unfortunately, little is known about why such an increased risk of abuse occurs among children with disabilities. In contrast to this meager literature about correlates of abuse among children with disabilities, a strong literature examines why abuse occurs in children who do not have disabilities. Within this literature, risk factors leading to abuse have been considered to interact, and to escalate situations to become abusive. Understanding how these risk factors relate to one another may also explain why children with disabilities are at increased risk of abuse. Starting with the ecological approach, then, in this section we explain how multiple risk variables combine to increasingly heighten the predisposition for a child to be abused. Next, we describe these risk characteristics, first for children without disabilities, then for those with disabilities.
4.1. The ecology of child abuse: Theoretical issues When considering the variables that make a family at risk for child abuse, several factors are combined to influence the way parents respond to their children. Belsky (1980) was a pioneer in creating this ecological approach to child abuse, which was derived in part from Bronfenbrenner’s model of the ecology of human development (Belsky & Vondra, 1990; Zigler & Hall, 1990). The essence of this ecological approach involves a series of nested levels. As Sidebotham (2001) notes, ‘‘the basis of an ecological model is that child maltreatment is multiply determined by forces at work in the individual, in the family and in the community and culture, and that these determinants are nested within one another’’ (p. 103). Within this model, four systems are considered. The first, termed parents’ ontogenic development, considers how the parent’s own childhood and early adult life can influence child abuse potential. For example, potentially abusive parents might themselves have been abused, have unrealistic expectations for their child, suffer from depression, or be ambivalent about having or raising the child. Although
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none of these factors are determinative—parents who were victims of child abuse during childhood will not necessarily grow up to abuse their own children (Kaufman & Zigler, 1990; Muller, 1996)—each nevertheless makes it more likely that parents will abuse their children. The second system involves the microsystem or the immediate family and environment of the child. Within this model, the effects of the child on the adult are considered (Bell, 1968), as are transactions over time between children and parents (Patterson, 1982). Aside from interactions involving the child, other family factors also enter in, including parental marital relations, the effects of other children in the home, and specific familytype variables, such as if the family has close versus distant relationships and open versus closed communication styles (Olson, 2000). As the child ages, friends, school, or playgroup peers, and other significant adults are also incorporated into the microsystem (Sidebotham, 2001). The final two systems relate more to larger environments and to cultural issues. The immediate family environment (microsystem) itself exists within a third system, or exosystem. Examples of the exosystem might include whether the parent has a job and the nature of that job, characteristics of the child’s neighborhood, and the amount, nature, and efficient functioning of the family’s social networks and supports. Finally, the macrosystem is the larger cultural context that surrounds the family. This context might involve the beliefs held either in society at large or within one’s subcultural group about the appropriate ways to parent children, and whether and in which circumstances parents should use physical discipline. Within this ecological model, the child’s behavior is a partial, but rarely a total, elicitor of abuse. Granted, children’s behaviors can powerfully influence adults (Bell & Harper, 1977). The best example might be Patterson’s work on interactions between children with conduct disorders and their parents. Within Patterson’s (1982) coercion theory, behavioral contingencies are used to explain how parents and children ‘‘train’’ each other to behave in certain ways (Granic & Patterson, 2006). For example, parents might demand compliance of a child who then refuses to comply, leading the parent to become even stricter with the child. In response, the child’s misbehavior escalates again. With this interplay of parent–child behaviors, aggression has been shown to emerge, which could sometimes escalate into child abuse (Urquiza & McNeil, 1996). Even with the example of children with conduct disorders, however, the child’s behavior does not constitute the sole cause of child abuse. Instead, the child’s behavior is examined more for how it fits within the remaining three systems. For example, if a child’s difficult externalizing behavior is combined with a parent who was abused in childhood and who has recently lost a job, then child abuse is much more likely to occur. As Sidebotham, Heron, & The Avon Longitudinal Study of Parents and Children Study Team (ALSPAC) (2003) concluded, ‘‘maltreatment requires a stressful
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environment, a parent who reacts in a particular way and a child who is in some way different’’ (p. 348). Although the listing below is provided separately for each system, these systems interact over time, making child abuse increasingly likely.
4.2. Characteristics contributing to child abuse among typically developing children 4.2.1. Parents’ ontogenic development: What the parent brings Within the literature on abuse of children without disabilities, the most prominent risk factor within parents’ ontogenic development is a parent’s own childhood history of maltreatment (Hall, Sachs, & Rayens, 1998). The intergenerational transmission hypothesis asserts that if a parent was exposed to violence as a child, then that parent may adopt similar aggressive strategies for coping with parent–child conflicts (Isaacs, 1981). In a similar way, parents who are ambivalent about having a particular child are also more likely to abuse such children. Thus, parents whose children are the result of unintended pregnancies are more likely to abuse their children, as are parents who do not rate their children with many positive characteristics at 4 weeks of age (Sidebotham et al., 2003). In addition, compared to parents who do not have a psychiatric disorder, parents who suffer from clinical depression, mania, or schizophrenia are two to three times more likely to abuse their children (DeBellis, Broussard, Herring, Wexler, Moritz, & Benitez 2001; Walsh, MacMillan, & Jamieson, 2002). Finally, a parent’s prior experience with caregiving and knowledge about child development are other ontogenic characteristics that could increase the risk of child abuse. If a new parent was never exposed to caring for a child before, the parent may respond aggressively to the demands of caregiving. Similarly, parents who do not understand child development may neglect their child simply because the parents do not understand what is expected of them (Fox, Fox, & Anderson, 1991). Such lack of knowledge may explain the recurrent finding that teenage mothers are at higher risk of abusing their children than are older mothers (Stier, Leventhal, Berg, Johnson, & Mezger, 1993). Finally, a parent’s low IQ, low self-esteem, and poor interpersonal skills are factors within ontogenic development that interact with factors from the other three systems (Kaufman & Zigler, 1990; Paavilainen, Astedt-Kurki, Paunonen-Ilmonen, & Laippala, 2001; Wolfe & Wekerle, 1993). 4.2.2. Microsystem: Immediate child and family factors Child characteristics: Although children are not the sole cause of their own abusive experiences, they are active agents in their environment (Sellinger & Hodapp, 2005) and can thus serve as elicitors of maltreatment when their
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certain characteristics interact with family characteristics (Belsky, 1980). In essence, the child’s own behavioral and developmental characteristics may predispose them to abusive situations ( Janko, 1994). Much research has been performed to identify which characteristics of children may predispose them to abuse. Children who are premature have frequently been reported to be at increased risk of abuse (Goldberg, 1979; Sidebotham et al., 2003), though some studies have not found a link between birth weight and child abuse potential (Spencer, Wallace, Sundrum, Bacchus, & Logan, 2006). Most recently, Sidebotham et al. (2003) found that children who were born with low birth weight were more than twice as likely to suffer from abuse as were children born of normal birth weight. Similarly, findings from a population-based study showed that low birth weight and premature babies were at greater risk of all four types of abuse compared to babies of normal birth weight (Spencer et al., 2006). Those who have found an association suggest this risk could be due to the premature child’s lack of social responsiveness, to the child’s aversive cry and appearance, or to the parent’s inability to bond with the child (Elmer & Gregg, 1967; Sidebotham et al., 2003). Spencer and colleagues also suggest that mothers who have premature or low birth weight babies may possess certain other characteristics that are indicative of both poor pregnancy outcomes and child abuse. The child’s temperament could also be an influence in abuse. Both children who are hyperactive and children who are lethargic have been reported to be abused more often (Belsky, 1980; Zirpoli, et al., 1987). The hyperactive child may place increased stress on a parent, thus leading to physical abuse; a lethargic child could suffer from neglect. Other characteristics of children that have been identified include a child’s discipline problems, sexual acting out, poor school performance, and permanent or chronic conditions such as developmental disabilities or medical fragility (Meier & Sloan, 1984). Children who are oppositional, aggressive, or coercive are also more likely to receive physical discipline ( Jaffee et al., 2004). Family characteristics: Certain family characteristics interact with child characteristics within the microsystem. For example, parents who are suffering from marital discord may be at greater risk as they may target their aggression toward their child (Belsky, 1980; Tajima, 2000). In addition, increased risk can result when parents are living in lower-income households, single-parent households, and households with many children (Baumrind, 1994; Ethier, Couture, & Lacharite, 2004; Wu et al., 2004). In fact, larger families and families in which the children are closely spaced are at greater risk of child abuse. Such increased risk of abuse could be due to the increased financial stress associated with raising so many children.
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4.2.3. Exosystem and macrosystem Within the exosystem, a parent’s under- or unemployment and social isolation are two characteristics that increase the risk of abuse (Belsky, 1980; Sobsey, 2002). In addition to the potential for lower self-esteem (especially for unemployed fathers), having adequate money, food, housing, and health care are all important factors that interact with the high-risk abuse status ( Janko, 1994). Child abuse also often occurs in families that are socially isolated and that lack many formal or informal supports (Grietens, Geeraert, & Hellinckx, 2004; Sidebotham, Heron, Golding, & the ALSPAC Study Team, 2002). Families who are isolated do not have others to turn to as a means of escape from the stresses of child rearing. Further, these families have little help with child care and often lack material assistance (O’Brien, 2001). Even though all of the considered characteristics within the microsystem and exosystem can interact to lead to child abuse, it is also important to consider these factors within the larger context of the macrosystem. The culture in which a family lives plays an important role in how parents will respond to stressful and trying situations. Most parents within the United States live in communities in which corporal punishment is an acceptable way of disciplining a child. Belsky (1980) argues that as long as societies accept and even promote violence (through television, lack of consequences), then child abuse will never be fully eliminated.
4.3. Characteristics contributing to abuse among children with disabilities In considering the above set of characteristics, one can see that many of them occur even more frequently in children with disabilities. Moreover, these child characteristics are also likely to interact with parent and family characteristics to lead to abuse within families of children with disabilities. 4.3.1. Parents’ ontogenic development Two important parental ontogenic risk factors are commonly found in parents of children with disabilities. The first involves depression. Several studies have now found increased rates of depression (and other psychiatric conditions) among parents who abuse their children (Walsh et al., 2002). Depression, in turn, occurs more often among mothers of children with disabilities compared to mothers of children without disabilities. In a recent meta-analysis of studies comparing depression scales for mothers of children with versus without disabilities, Singer (2006) found differences between mothers in the two groups, usually on the order of small-to-moderate-sized effects (median effect size ¼ .39). Stated another way, 29% of mothers of
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children with disabilities scored in the ‘‘clinical’’ range on commonly used depression measures (e.g., Beck, Brief Symptom Inventory, Center for Epidemiologic Studies Depression Scale), compared to 19% of mothers of children without disabilities. Of note, depression among mothers of children with disabilities is often found to occur early in the child’s life (Glidden & Schoolcraft, 2003). Similarly, child abuse occurs more often in the child’s younger, rather than older, years (US Department of Health and Human Services, Administration on Children, Youth and Families, 2007). Another ontogenic risk factor involves the lower IQ’s of some mothers of children with disabilities. Reviewing the literature on parents with mental retardation, Holburn, Perkins, and Vietze (2001) found that approximately one-fourth of the children of parents with mental retardation also had mental retardation. Furthermore, when both parents had mental retardation, the risk of their child having mental retardation was doubled. Finally, when parents with mental retardation were of lower SES, the children were at a higher risk for developmental delay (especially delayed expressive language) than those children born to middle-class families (Espe-Sherwindt, & Crable, 1993). Because lower IQ and educational attainment are risk factors of child abuse, children with disabilities from mothers with lower IQs may be at increased risk. 4.3.2. Microsystem: Immediate child and family factors Child characteristics: As described above, a child’s difficult temperament can influence the risk of abuse. Many children with disabilities display challenging and/or unmanageable behavior (e.g., self-injurious behaviors, aggression, hyperactivity; Soeffing, 1975). In fact, Ammerman (1990) stated that child characteristics that increased parental stress challenged coping skills (e.g., hyperactivity), or disrupted the parent–child bond (e.g., child irritability), were likely to lead to abusive situations. Each of these behaviors is generally found at increased rates among children with disabilities. Indeed, Ammerman and Patz (1996) substantiated this finding by studying characteristics of children with and without disabilities on the Child Domain of the Parenting Stress Index. They determined that certain child qualities, such as adaptability to changes in the environment, moodiness, and irritability, predisposed children to higher rates of potential abuse. Another risk factor often seen among children with disabilities is that of prematurity. Children who are born premature are at risk of developing disabilities, such as cerebral palsy (Escobar, Littenberg, & Petitti, 1991). Furthermore, children who are born premature often display certain characteristics of children with disabilities that elicit negative reactions from caregivers, such as prolonged crying. These behaviors could lead to abuse, as could behaviors that result in insecure attachments between the mother and child. These insecure attachments could be because of illness, or the child’s
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deficits in attachment forming behaviors, such as eye-gaze or responsiveness (Ammerman, Lubetsky, & Stubenbort, 2000; Sidebotham et al., 2003). When considering such risk factors among children with disabilities that may contribute to child abuse, it is also important to recognize that certain of these characteristics occur more often in some disabilities than in others (Dykens, 1995). Different genetic disorders predispose children to display certain characteristics at different levels. For example, compared to other children with mental retardation, children with Prader–Willi syndrome show higher rates of temper tantrums and obsessive–compulsive disorders (Dykens, Leckman, & Cassidy, 1996; Walz & Benson, 2002). These behaviors are part of the difficult temperament traits that could lead to abuse. In fact, Van Lieshout, De Meyer, Curfs, and Fryns (1998) found that, within a group of children with Prader–Willi syndrome, the child’s negative personality characteristics and parents’ degree of anger were highly correlated. When the child with Prader–Willi syndrome displayed less agreeableness, less conscientiousness, less emotional stability, less openness, and greater irritability, both parents were likely to exhibit greater anger and less warmth toward the child. The child’s behaviors were also found to relate to parental consistency, marital discord, and family stress. In another example, Johnston et al. (2003) found that the behavior problems displayed by children with fragile X syndrome were a major factor contributing to the overall stress experienced by their mothers (see also Van Lieshout et al., 1998). In both Prader–Willi syndrome and fragile X syndrome, then, certain etiology-related characteristics may predispose these children to greater risks of abuse. Such effects of the child’s etiology-related behavior on others—in this case related to child abuse—have been considered important for many types of parental and familial outcomes (Hodapp, 1997, 1999). On the other hand, some children with genetic disorders display personality and behavioral characteristics that may decrease the risk of child abuse. For example, children with Down syndrome often display personalities that might be characterized as positive and socially oriented; these children also generally display lower rates of maladaptive behavior (Dykens & Kasari, 1997; Meyers & Puecshel, 1991; Stores, Stores, Fellows, & Buckley, 1998). In turn, when compared to parents of children with other intellectual disabilities, parents of children with Down syndrome usually experience less child-related stress (Fidler, Hodapp, & Dykens, 2002). These parents also report that they feel more rewarded by their child (Hodapp, Ly, Fidler, & Ricci, 2001; Noh, Dumas, Wolf, & Fisman, 1989), particularly until the teen years (possibly not thereafter; Hodapp et al., 2001). This ‘‘Down syndrome advantage’’ may well be a protective factor from child abuse. Family characteristics: In line with findings relating higher rates of child abuse to marital discord and single-parent households, one sees that both may occur more often among families of children with disabilities. First, children with disabilities are more likely to live in single-parent-headed
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households rather than with married parents. Fujiura (1998) reported that single-parent-headed households comprised 40% of the households with children with disabilities in his survey (all with children aged 15 years and older), compared to only 21% of single-parent-headed households among families of children without disabilities (see Fujiura & Yamaki, 2000 for similar findings with younger children). Similarly, in her study of over 10,000 families surveyed in the 1981 National Health Interview Survey, Mauldon (1993) found that parents were more likely to divorce if their child had a disability or chronic health condition. In considering divorce among families with children with disabilities, however, two recent studies lead one to be cautious about these findings. First, Risdal and Singer (2004) performed a meta-analysis of all studies of divorce among parents of children with versus without disabilities. Although their conclusion was that divorce was more likely among families of a child with a disability, the effect sizes were modest. Compared to families of children without disabilities, families of children with disabilities were about 6% more likely to divorce (20% vs. 14%). Second, divorce rates may differ by diagnostic group. In a recent largescale study using statewide administrative records, rates of divorce among families of children with Down syndrome were slightly lower than divorce rates of families of children with other birth defects or of a comparison group of children without disabilities (Urbano & Hodapp, 2007). Moreover, when divorce did occur within the families with children with Down syndrome, it was more likely to occur before the child had reached 2 years of age. 4.3.3. Exosystem and macrosystem As stated above, parents with children with disabilities are often of lower SES (Fujiura, 1998). Parents living in lower SES neighborhoods often lack community resource centers and do not have alternative child care (Pianta et al., 1990). Partly as a result, many mothers of children with disabilities are reluctant to work full time (Kelly & Booth, 2002). Further, Sidebotham et al. (2003) found that children who suffer from poor health in the first 30 months of life were more likely to be maltreated. They attributed such increased child abuse levels to the stress, parents experience in looking after their sick child and making numerous hospital visits. Many children with disabilities (e.g., Down syndrome) experience increased illnesses early in life (So, Urbano, & Hodapp, 2007). Stress can also arise due to the need to provide increased care and supervision for children with disabilities. If parents do not have social supports to help care for the child or to discuss problems with, then they may experience increased stress (which may, in turn, lead to increased levels of abuse). Older studies examined the types of support characteristics available to parents of children with disabilities. Although most parents of children with
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disabilities reported having support, the social support networks of these parents were usually smaller than those of parents of children without disabilities (Kazak & Marvin, 1984). Similarly, a more recent study has found that parents of children with disabilities are likely to rely on family members and professionals before friends (Shin, 2002). As a result, such networks may be ‘‘denser,’’ that is, most individuals within the support network know and interact with one another (Byrne & Cunningham, 1985). Although little research has been conducted recently to determine if the social support of parents of children with disabilities remains smaller and denser, White and Hastings (2004) reported that informal support was associated with parental well-being, regardless of the number of formal supports. Dense social networks have both good and bad characteristics. On the positive side, such strongly bonded networks do provide parents with informational, emotional, and tangible supports. Heller, Hsieh, and Rowitz (2000) found that parents of children with disabilities who received emotional support (e.g., providing advice, being a confidant, giving encouragement) from the child’s grandparents reported lower levels of depression. This finding was still present after the authors controlled for other formal and informal resources. In a study of families of children with spina bifida, informal supports such as a supportive family climate, the parents’ marital relationship (Vermaes, Janssens, Bosman, & Gerris, 2005), and the proportion of family members in the network (Barakat & Linney, 1992) were all associated with better psychological adjustment. At the same time, however, such dense social networks can themselves be sources of stress for the parents. Dense networks tend to foster less frequent access to other resources or to different opinions, and fewer opportunities to discuss stressful events (Granovetter, 1973). It is also very difficult to get outside of the network. In addition, in those cases in which social networks are both dense and small, stress can arise due to the network’s difficulty in providing the increased care and supervision needed by many children with disabilities. White and Hastings (2004) also caution that parents who rely on small informal support networks are also vulnerable to future stress. Specifically, if the informal support sources are threatened (e.g., grandparents die, friends move away), then parents may find it difficult to ask others for support out of fear that they will be unable to reciprocate the help. In turn, parents might be forced to turn to professionals to locate alternate sources of support. In considering the abuse of children with disabilities, then, it seems as if heightened levels of many different risk factors may lead to higher prevalence rates. Although no single risk factor may by itself determine the risk of child abuse among children with disabilities, many risk factors seem increased. Following Belsky’s model, in Table 7.2 we summarize the higher levels of various risk factors within the ontogenic, microsystem, and macrosystem– exosystem. If each elevated risk factor combines—in a multiplicative
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Table 7.2 Characteristics within families with children with disabilities that may increase abuse potential
Risk factor
Is risk elevated in families with children with disabilities?
Ontogenic Development Parental history of abuse Ambivalence toward child Less knowledge about caregiving Mother’s depression Mother’s other psychiatric problems Teenage mothers Mothers with lower IQ Mother’s low self-esteem
Unknown Unknown (possibly) Likely (given child’s specific problems) Increased risk Unknown Unknown Increased risk Increased risk (¼relation to depression)
Microsystem Prematurity Difficult temperament Hyperactivity Lethargic children Low SES Divorced parents Single-parent families Larger families (more children)
Increased risk Increased risk Increased risk Increased risk Increased risk Increased risk Increased risk Unknown
Macrosystem/Exosystem Small social networks Dense social networks Unemployment
Increased risk Increased risk Increased risk for some mothers (fathers unknown?)
way—with all others, then it seems almost inevitable that children with disabilities experience higher-than-normal rates of child abuse.
5. Remaining Issues for Research Although it seems likely that Belsky’s ecological model can be profitably applied to the abuse of children with disabilities, currently much of our argument is speculative. Given that a particular risk factor predisposes
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children to greater amounts of abuse when the child does not have disabilities, so such factors should work similarly when the child does have disabilities. But in order to test this hypothesis, researchers need to tackle four additional questions.
5.1. Correlates or antecedents? Many risk factors are likely present more often in children with versus without disabilities (see Table 7.2). Such factors span the gamut of levels, from what parents bring to the interaction, to child, parent, or family factors, to factors present in the family’s surrounding support system. In all cases, we refer to each variable as a ‘‘risk factor,’’ with the assumption that the presence or higher level of each variable helps to put the child at greater risk for child abuse. For certain of these variables, however, the direction of causality remains unclear. As previously stated, one solution relates to larger scale longitudinal studies. Applying Hierarchical Linear Modeling (HLM) and other statistical techniques to data from participants examined on multiple occasions, one begins to know ‘‘what causes what’’—which correlate seems most likely to have served as the antecedent, which the outcome. At present, such studies rarely occur when examining abuse among children without disabilities, and are almost nonexistent when considering abuse among children who have disabilities. A second, related concern is the distinction between ‘‘risk indicators’’ and ‘‘risk mechanisms’’ (Rutter, Pickles, Murray, & Eaves, 2001). Risk indicators constitute markers for increased risk, but by unknown mechanisms, whereas risk mechanisms specify those processes by which an outcome occurs. Thus, lower SES, which serves as a marker for a host of poor outcomes, does not by itself explain why such poor outcomes occur. In contrast, risk mechanisms tell us which behaviors might be operating to cause the child’s increased risk. At present, many of the correlates of child abuse are markers, not mechanisms. The child’s prematurity, low family SES, smaller (or denser) social support networks, or low parental education levels may all be related to higher rates of child abuse, but we do not yet understand why. Granted, one can speculate about each of these risk factors, but the exact mechanisms remain unclear as to why each relates to greater amounts of child abuse.
5.2. Same or different amounts of each risk factor? Regardless of how one conceptualizes child abuse risk factors, a second question involves the prevalence of such factors within children with disabilities and their families. As Table 7.2 indicates, many of these factors have yet to receive sustained study. Beyond maternal depression, are
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mothers more, less, or similarly likely to suffer from other psychiatric disorders? What, exactly, are the feelings of mothers toward their newborn children with disabilities, and are all risk factors more common among families of children with disabilities? Like many basic questions in disabilities, no firm answers exist. The problems likely arise from two directions. From one side, the field has many studies using samples of convenience. Researchers in Down syndrome, Williams syndrome, Prader–Willi syndrome, and fragile X syndrome, for example, often utilize parent groups as their source of subjects. Although helpful— even necessary—in order to attain large numbers of participants, parent groups generally consist of parents and families who are White, well-educated, and of middle class or higher SES (Hodapp & Dykens, 2001). From the opposite direction, epidemiologists have delineated general characteristics of families of children with disabilities, but this information is generally less focused on specific disabilities. Parents of children with disabilities are thus slightly more likely to be divorced (Risdal & Singer, 2004), depressed (Singer, 2006), and headed by single-parent families (Fujiura, 1998; Mauldon, 1993). But all of these findings arise from either metaanalyses of small-scale studies using samples of convenience or, conversely, from large-scale epidemiological studies. Such large-scale studies often use federal surveys, which usually lump together children with various disability and health conditions. As a result, little information is available concerning which specific disability conditions might show which types of outcomes, for child abuse or for many other outcomes.
5.3. What percentage of the variance is accounted for by each risk factor? Table 7.2 presents a fairly long list of risk factors relating to parental history, child characteristics, parental and family characteristics, and outside support. Shown in such a list-like form, each separate variable seems equally important, equally predictive of higher rates of child abuse. But each predictor variable may not be equal. Indeed, when weighing the importance of any set of predictors, one is metaphorically sizing pie pieces. Some predictors matter more—they account for bigger slices of the pie—whereas others constitute smaller slices (they matter less). At present, we are still at the stage of identifying which variables matter. Although a few large-scale studies have examined the strength of effects of one versus another risk factor (e.g., Sidebotham et al., 2003), most do not. Instead, most studies show only that a particular characteristic constitutes a risk factor for abuse. The relative strength of that risk factor is rarely considered. An additional, related issue concerns how such individual risk factors relate one to another. Within epidemiology, it is commonly noted that risk factors are often correlated (Costello & Angold, 2006). Thus, the family that is
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of lower SES is also the family in which parents have less education, are more likely to be divorced and to show health, support, or other problems. It is therefore not enough to identify individual risk factors, as risk factors tend to relate to one another in ways that greatly increase risks of negative outcomes. A final issue concerns the possible presence of risk factors that might be unique to parents of children with disabilities, and their connections to other risk factors. Few parents of children without disabilities have had much experience with the special education system, Individualized Education Plans, or garnering services for their child. Similarly, if indeed maternal depression occurs more often during the early years when the child’s disability manifests itself and is diagnosed (e.g., Glidden & Jobe, 2006; Glidden & Schoolcraft, 2003), then maternal depression must be considered as a risk factor that may be time-sensitive to the age of the child. How different risk factors go together at specific time points remains virtually unexamined. In thinking about the relative strengths and interactions of various risk factors, we begin to acquire a more nuanced view of families and their risks for abusing their children with disabilities. Not all families are at higher risk of abusing their children with disabilities; only some families are at greater risk. As we come to identify those characteristics that constitute risk factors and to appreciate the strength of each individually and collectively, we can begin to predict which particular families will be most at risk. We can then screen families and intervene effectively.
5.4. How should screening and intervention be performed? Although abuse prevention and intervention programs exist for children without disabilities and their families, few such programs exist for children with disabilities Fisher (2007). Still, we can learn much from the burgeoning field that examines the nature and efficacy of child abuse interventions. A first issue involves risk assessment. Hawaii’s Healthy Start Program, one of the best known prevention programs, aims to prevent child abuse through first conducting a population-based screening and assessment of families of newborns. By screening new families, workers are able to identify those at risk before abusive situations occur. The risk assessment measures risk for abuse in 15 areas: parents not married; unemployed partner; inadequate income; unstable housing; lack of telephone; less than high school education; inadequate emergency contacts; marital or family problems; history of abortions; abortion unsuccessfully sought; history of substance abuse; history of psychiatric care; history of depression; and inadequate prenatal care (Duggan et al., 1999). Once families at risk are identified, they are invited to participate in the second phase of the program, home visiting. During this phase, home visitors work with the family members to help them cope with the challenges of raising a child through identifying family strengths and reducing
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environmental risks (Duggan et al., 1999). While this program is a wonderful first step in the identification of families at risk, Hawaii’s Healthy Start Program, unfortunately, will miss most families with children with disabilities. As displayed in Table 7.2, many of the 15 risk variables measured through this program occur at an increased rate among families of children with disabilities; however, many of the most prevalent risk factors among families with disabilities (e.g., characteristics of the child) are not measured through this risk assessment. Granted, most are missed because this assessment is performed directly after the birth of the child, when most characteristics are not yet present. Unfortunately, most disabilities are not yet identified as well. Aside from a few genetic disorders (e.g., Down syndrome) and certain obvious physical conditions (e.g., spina bifida, cleft palate), most disabilities are not diagnosed until the child is older and out of the hospital. If these mothers do not qualify as at-risk based on the 15 identified factors, then these new mothers will not receive the early intervention they need. Similarly, few child abuse prevention and intervention programs have been developed and tested specifically for children with disabilities and, unfortunately, many studies use disability status as an exclusion criterion (Fisher, 2007). Yet with mounting evidence that families of children with disabilities are at increased risk of abuse related to factors in the child, parent, and family, it is disheartening that so few studies have been designed to reduce the risk of abuse among this population. Noting this lack of riskreduction studies, Kendall-Tackett, Lyon, Taliaferro, and Little (2005) stated that welfare services should provide specialized assistance to families of children with disabilities and that disability status should be considered in studies evaluating maltreatment interventions. Unfortunately, studies specifically targeting families with children with disabilities continue to be sparse. In order to target more children with disabilities, new risk assessments must be developed that include child characteristics along with parent and family characteristics. Also, intervention studies should be designed to target the specific characteristics identified for increased abuse potential among children with disabilities. Finally, specialized programs should be developed and tested that work with both parents and their children with disabilities.
6. Conclusion Despite a host of definitional and methodological problems, it now seems clear that children with disabilities suffer abuse at alarming rates. Compared to children without disabilities, almost every study shows that children with disabilities are more prone to all types of abuse. Children with
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specific types of disability may suffer more and specific types of abuse, gender rates may vary, and recurrent (vs. one-time only) abuse and abuse from parents and other family members predominate. But the overall message involves an increased risk of child abuse among children with versus without disabilities. The goal now becomes twofold. First, we must answer the ‘‘why question,’’ to delve more deeply into why children with disabilities are so often abused. Using Belsky’s (1980) ecological framework of child abuse to organize the various strands, we see higher-than-expected amounts of almost every risk factor, at every level. Children with disabilities more often display behavioral problems, difficult temperaments, and other ‘‘abuse-inducing’’ characteristics; parents are slightly more likely to be of low SES, single-parent families, and to show depression; and smaller and denser social support networks seem common. Our first, still mostly unresolved task, then, involves better understanding whether these risk factors operate similarly in families of children with and without disabilities, with the ultimate goal of determining what percentage of the variance is accounted for by each of these many variables. On better understanding risk factors, our second task becomes the screening and intervention of the most at-risk families of children with disabilities. In contrast to the general strategy of excluding children with disabilities from abuse studies, our job now is to understand better how to identify and to intervene effectively to both prevent and treat abuse in these families. In short, given the available information, it should no longer be surprising that children with disabilities are at increased risk of abuse and neglect. Rather, it is surprising that so little is being done to prevent this abuse and neglect from occurring. If we truly are a civilized society—a society that protects its most vulnerable members—we need to learn more and to intervene more effectively to prevent and treat the abuse of children with disabilities.
ACKNOWLEDGMENTS We thank Dr. Laraine Glidden and an anonymous reviewer for their careful, detailed comments on an earlier draft of this chapter. This chapter was supported by a grant from the Family Research Program of the Vanderbilt Kennedy Center awarded to the first author and in part by grant # T32HD07226 from NICHD to Vanderbilt University, as well as NICHD P30HD 15052.
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C H A P T E R
E I G H T
Siblings of Children with Mental Retardation: The Role of Helping Elizabeth Midlarsky,* Mary Elizabeth Hannah,† Erel Shvil,* and Amanda Johnson* Contents 292 293 294 295 295 296 297 299 300 301 301 304 305 306 308 312 313
1. Introduction 2. Impact of Having a Sibling with Mental Retardation 2.1. Negative effects 2.2. Positive effects 3. Factors Associated with Adjustment 3.1. Sex 3.2. Birth order 3.3. Socioeconomic status and family size 3.4. Parental adjustment and family climate 3.5. Severity and type of mental retardation 4. Methodological Considerations 5. Helping by Siblings of Children with Mental Retardation 5.1. The definition of helping 5.2. The development of helping behavior 5.3. Consequences of helping 6. Conclusions and Future Directions References
Abstract We present the argument that the helping behavior of typical siblings of children with mental retardation may promote their positive adaptation. We begin by reviewing literature on the positive and negative impacts of having a brother or sister with mental retardation, followed by a summary of factors
* {
Department of Counseling & Clinical Psychology, Teachers College, Columbia, 525 West 120th Street, New York, NY 10027, USA Department of Psychology, University of Detroit, Mercy, 4001 W. McNichols Road, Detroit, MI 48219, USA
International Review of Research in Mental Retardation, Volume 35 ISSN 0074-7750, DOI: 10.1016/S0074-7750(07)35008-8
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2008 Elsevier Inc. All rights reserved.
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associated with psychosocial adjustment, and methodological considerations which may help explain inconsistencies among study findings. We then present theoretical and empirical perspectives on the nature and consequences of helping by typical siblings, and consider proposed links between helping in the family context and well-being of the typical sibling.
It is one of the most beautiful compensations of life that no man can sincerely try to help another without helping himself. Ralph Waldo Emerson Kindness can become its own motive. We are made kind by being kind. Eric Hoffer
1. Introduction In the past 20 years, there has been an increase in the amount of research focused on siblings who have brothers or sisters with mental retardation or other disabilities. However, as noted by Stoneman (2005), the research can be characterized as lacking in theoretical underpinnings. In this chapter, we focus on one of the most important issues for brothers and sisters of children with mental retardation—their helping behavior— and present a conceptual framework that may facilitate our understanding of the ways in which helping can affect the typically developing sibling. Over a long period of time, there has been widespread acknowledgment that a major component of being a sibling of a child with mental retardation is an increase in helping behavior (Hannah & Midlarsky, 2005). Siblings of children with developmental disabilities are required to take a significant part in the sharing of family responsibilities, usually much more than typically developing children in families that do not have a child with a disability. If it is overly taxing, the provision of help may be a source of stress. Our basic premise, though, is that helping constitutes an important contribution in families that include a child with mental retardation, and that the sibling helper may benefit as a result of his or her helping behavior. We begin this work with a brief summary of the literature on the consequences of being a brother or sister of a child with mental retardation, and factors influencing adjustment, followed by a discussion of the methodological considerations that may explain inconsistencies in study results. In a subsequent section, we consider the nature of helping, the development of helping, and its consequence for the helper. A goal of this chapter is to integrate insights and research findings from the literatures on siblings of children with disabilities, positive psychology, and altruism and helping behavior.
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2. Impact of Having a Sibling with Mental Retardation Sibling relationships play an important part in the psychosocial development of children and adolescents (Brody, 2004; Edwards, Hadfield, Lucey, & Mauthner, 2006; MacGillicuddy-DeLisi, 1993; McHale & Gamble, 1989). Children react differently to their siblings than they do both to their parents and to peers outside the family, so that relations among siblings play a unique role in human development and psychosocial adjustment. For example, in a longitudinal study of the psychosocial development of 229 men from ages 20 through 50, poor sibling relationships before age 20 served as a predictor of major depression by the age of 50; 26% of men experiencing poor sibling relationships, in contrast to 3% of those with good relationships, subsequently suffered from major depression. This effect was independent of the effect of relationships with parents prior to age 20. Sibling relationships have been hypothesized to have important effects on development (Teti, 2002). It may well be the case that within what Parke (2003) terms ‘‘the sibling subsystem,’’ children can learn and practice social skills, engage in a wide range of activities, and gain an enhanced capacity to manage interpersonal relations with peers (McCoy, Brody, & Stoneman, 1994). Sibling relationships during childhood tend to be paradoxical, with grade school children rating these relationships as more conflict-ridden, but also as more important and reliable than relationships with friends (Baskett & Johnson, 1982; Furman & Buhrmeister, 1985). Siblings may be rivals for their parents’ attention and for family resources, and questions about differential treatment may arise (Brody, 2004). However, sibling relationships also provide opportunities for nurturance, support, companionship, and involvement in a teacher/learner role (Azmita & Hesser, 1993; Howe & Ross, 1990). Although all children with siblings need to develop ways of coping with the demands associated with the sibling relationship, siblings of children with disabilities such as mental retardation may have an even greater need for adaptive coping strategies. Children’s reactions, expressed to Elizabeth Midlarsky in family therapy sessions, include statements like the following (with names and specific details altered for reasons of confidentiality): My brother Daniel’s mental retardation has made it hard for him to do what the other kids his age can do, and they tease him a lot. My ‘‘job’’ in the family is to always have good manners, to be responsible and a ‘‘miniature Mom’’ to him, which sometimes I really hate. But I want so much to help him do better and feel better—by 12-year-old Cheryl.
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Max is a brat. He gets all the attention, and every time he messes up Mom and Dad say ‘‘It’s not his fault.’’ Nothing I do is ever good enough! Sometimes I just hate him! I can’t bring anyone home from school, so I spend a lot of time ‘‘hanging out’’ with my friends around the schoolyard. But sometimes those guys are so nasty to Joseph—they punch him and call him names, like ‘‘retard.’’ I get in trouble a lot, because I won’t let anyone call my brother names. Poor kid, it’s really not his fault. I have to take care of him, and fight his battles for him. No one knows it, but I play ball with him every day after school these days—by 9-year-old Joseph.
Early research was generally based on the assumption that the presence of a child with mental retardation in the home constitutes a chronic stressor (Crnic, Friedrich, & Greenberg, 1983). In many instances that assumption is still made. In a book reporting research triggered by his daughter’s reassurance that some day she would take care of her brother, Burke (1994) wrote that because of the exposure to disability, and the experiences of neglect and social exclusion, siblings of children with disabilities become disabled by association. However, a review of the literature reveals that some studies conclude that the effects for typically developing siblings are negative, whereas other studies find that they are positive.
2.1. Negative effects Several reviews of the research literature (Cicirelli, 1995; Del Rosario & Keefe, 2003; Hannah & Midlarsky, 1985; Rossiter & Sharpe, 2001) have focused on the mental health effects of having a brother or sister with a disability. For example, in a meta-analysis on the results of 25 studies, Rossiter and Sharpe (2001) concluded that overall, when compared to control groups, siblings of children with a wide range of disabilities were at a slight disadvantage, in regard to both internalizing and externalizing behaviors. Similarly, Del Rosario and Keefe (2003) stated that, based on their review of 43 studies, about one-fourth of siblings were affected in adverse ways. Negative effects typically included anxiety, withdrawal, depression, somatization, acting-out behaviors, school problems, and lowered self-esteem. In a study comparing 50 siblings of brothers and sisters with moderate-to-severe mental retardation, with a group of 50 siblings of children with no disabilities (Hannah & Midlarsky, 1999), girls were more likely to express their distress through internalization, whereas boys were more likely to experience school problems (thus manifesting externalization). However, as the authors noted, even when siblings of children with mental retardation scored significantly higher than siblings of children with no disabilities on measures of distress, the scores were typically in the normal or nonclinical ranges.
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2.2. Positive effects Much of the research on families of children with disabilities has highlighted negative effects (Helff & Glidden, 1998). Nevertheless, having a sibling with disabilities has been found to result in benefits for the typically developing sibling (Knox, Parmenter, Atkinson, & Yazbeck, 2000; Scorgie & Sobsey, 2000). One of the positive effects is a better relationship with the sibling with special needs than with a brother or sister without a disability. Kaminsky and Dewey (2001) reported that siblings of children with Down syndrome had greater admiration for their siblings than did children whose brothers and sisters had no disability. These children also reported less arguing and competition, and more nurturance, intimacy, and affection. In addition, having a brother or sister with a disability has been found to be related to positive personality characteristics. Thus, Hannah and Midlarsky (1985) found that siblings of children with mental retardation report enhanced self-concepts. Other positive characteristics include greater tolerance and understanding of people, compassion, maturity, patience, dedication, and loyalty (Dykens, 2005; McMillan, 2005; Swenson, 2005). In their meta-analysis, Rossiter and Sharpe (2001) noted that studies showing negative outcomes may be more prevalent because they only report on short-term outcomes of having a sibling with a disability. It is possible that many of the benefits of having a sibling with special needs do not become evident until adulthood. Accordingly, Orsmond and Seltzer (2000) found that closeness and involvement between typically developing brothers and sisters and their siblings with mental retardation increased over time. The adult female participants in McGraw and Walker’s (2007) retrospective study believed that having siblings with a disability led to increases in positive characteristics such as tolerance, compassion, a commitment to the worth inherent to people, and a rejection of the negative cultural attributions to disability. Furthermore, Seltzer, Greenberg, Krauss, Gordon, and Judge (1997) found that 87% of the adult siblings of people with mental retardation perceived the effects of having such a sibling to be positive.
3. Factors Associated with Adjustment Across the studies that have been conducted, findings about the psychological adjustment of the siblings of children with mental retardation have varied. Although the inconsistencies in study results may be partly attributable to methodological differences, there are other factors that may also account for observed variations in adjustment outcome. These include the sex and age of the typically developing sibling, birth order, socioeconomic status and family size, parental adjustment and family climate, and the severity of the disability.
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3.1. Sex Sex appears to play a distinct role in the outcomes experienced by siblings of individuals with mental retardation. Indeed, in a comprehensive review, Damiani (1999) found that the sex of the typically developing sibling was most frequently mentioned in the research literature in relation to psychological adjustment, followed in frequency by responsibility and caregiving. Siblings of children with mental retardation, particularly girls, report more depression, anxiety, and lower self-esteem than do siblings of typically developing children. These outcomes are often attributed to the home and childcare responsibilities in which girls engage to a greater extent than do boys (Rossiter & Sharpe, 2001). Older sisters have been presumed to be more vulnerable to distress, anxiety, and psychosocial problems than are brothers. In apparent support of this presumption, Saxena and Sharma (2000) found that brothers of children with mental retardation had higher self-esteem than sisters of children with mental retardation. Furthermore, in a study that assessed both brothers and sisters of children with mental retardation, Hannah and Midlarsky (1999) found that sisters of children with mental retardation had significantly more internalizing behaviors than sisters of children without disabilities. Also, brothers of children with developmental disabilities were found to have significantly more difficulties at school than brothers of children with no disabilities. A continual finding in the research literature is that siblings of brothers or sisters with disabilities engage in various forms of helping behavior. Siblings typically provide physical care, comfort, advice and emotional support, and engage in teaching and babysitting. Sisters usually take on more responsibilities and caretaking activities than brothers, apparently because parents, and especially mothers, expect and ask girls to help more than they ask boys. Hannah and Midlarsky (2005) compared the amounts of perceived custodial care, emotional support, tangible aid, and information that siblings of brothers and sisters with mental retardation provided, with the amounts of help provided by siblings of children with no disabilities. They found that siblings of brothers and sisters with mental retardation provided significantly more custodial care and emotional support, but did not provide higher amounts of information and tangible aid. Furthermore, in both groups, girls provided more custodial care and emotional support than did boys. This finding indicates the fulfillment of stereotypical sex roles and the gendered nature of caretaking (McGraw & Walker, 2007). Overall, it appears that sisters of individuals with disabilities, especially those from large, low-income families, report more adverse reactions than do brothers (Hannah & Midlarsky, 1985; Powell & Ogle, 1993). This may be because sisters are given extra caregiving responsibilities that are difficult to fulfill.
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3.2. Birth order Birth order may also be related to adjustment by siblings of children with mental retardation, because of the differences in caregiving responsibilities assumed by younger and older siblings. Hannah and Midlarsky (2005) found that girls and boys who were older than the sibling with mental retardation provided more custodial care than did younger ones. In families where there are both older and younger siblings of a child with mental retardation, the older siblings tend to have more responsibility for caregiving than do the younger siblings. Cuskelly and Gunn (2003), for example, found that although siblings of different birth orders all served as caregivers of their siblings with Down syndrome, it was the first born children who were most heavily involved. Nonetheless, later born children are not spared. Research has found that younger siblings of children with mental retardation assume dominant roles that involve helping, teaching, and behavior management more often than younger siblings of children without mental retardation (Brody, Stoneman, Davis, & Crapps, 1991; Hannah & Midlarsky, 2005). Although birth order apparently affects the amount and the kind of help that is given by siblings, there is no agreement about whether the effects are predominantly positive or negative. In one study, for example, older siblings of children with mental retardation were found to exhibit behavior problems, while the younger siblings demonstrated increased anxiety. Results also indicated a significant association between the amount of care given and the anxiety scores for the younger siblings (Coleby, 1995). On the other hand, a study by Stoneman, Brody, Davis, Crapps, and Malone (1991), found no support for a negative impact on the younger siblings, or on the siblings’ relationships, when the typically developing children had an increase in responsibilities. Indeed, younger siblings who assumed more childcare roles had less conflicted interactions with their brothers and sisters with mental retardation. In addition to the magnitude of the childcare assumed by older siblings, older and younger siblings also are exposed to different family environmental factors during their years in the parental home. While older siblings have experience with family life prior to the birth of the younger sister or brother with mental retardation, younger siblings are born into a family in which they have an older sibling with the disability. These differential experiences, in fact, can yield advantages as well as disadvantages for both older and younger siblings. In contrast to the younger sibling, the older sibling has achieved emotional, cognitive, and social development prior to the birth of the sibling with mental retardation. For example, the older children are more likely to have begun developing moral feelings (Zahn-Waxler, Radke-Yarrow, Wagner, & Chapman, 1992), and may have learned how to cooperate and share (at least to some extent; Midlarsky & Hannah, 1985), and to manage their emotions (Eisenberg et al., 1996). These are capacities
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and skills that typically developing younger siblings are likely to lack, at least relative to older typically developing siblings. On the other hand, the dramatic change in the family environment following the birth of the child with mental retardation could affect an older sibling’s emotional stability more than the stability of a typically developing younger sibling who is born into and develops in a more ‘‘settled’’ family environment (Gath, 1992). Some research shows that older siblings have more adjustment problems than do younger siblings (Powell & Ogle, 1993). This may be because once the child with a disability is born, the typically developing sibling may have to care for himself or herself, with little parental help. However, other research states that when typically developing children are older than their siblings with mental retardation, they will have better psychological adjustment because they will have had time to form bonds with their parents prior to the birth of their sibling. Some studies show that older sisters and younger brothers have the highest rates of adjustment problems (Berry & Hardman, 1998; Lobato, 1983, 1990). This outcome could be a consequence, perhaps, of the increased responsibility given to older sisters and the decreased attention given to younger brothers. It may also be attributable to the fact that in some cases, the older siblings are adolescents who find the presence of a sibling with mental retardation to be a source of conflict and anxiety because of (1) their need to become separate from and independent of their family, and (2) the stigma associated with their sibling with mental retardation may evoke rejection by peers, who feel the need to shun anyone who is ‘‘different.’’ A recent study by Levy-Wasser and Katz (2004) assessed the relationships among birth order, attachment style, and adjustment in siblings of children with mental retardation. They hypothesized that the well-being of siblings of children with mental retardation is related to their attachment style, and that older siblings establish more secure attachments to their mothers than do younger siblings, who are born into a more complex family environment. Secure attachment then should act as a protective factor against potential stress that may develop from having a child with mental retardation in the family. The researchers studied 54 children ranging in ages from 7 to 13. Twenty-five of the children had either a brother or a sister with mental retardation. Of these, 13 children were born before the sibling with the mental retardation and 12 were born afterward. The remainder of the children served as a control group. Results indicated no significant differences in the degrees of secure attachment reported by the older and younger siblings. Interestingly, though, the siblings of children with mental retardation had somewhat higher mean scores on the measures of secure attachment than did the children in the control group, regardless of birth order. The authors speculated that the higher scores on attachment by siblings of the children with mental retardation may be a sampling bias, accounted for by differences in the functioning of the admittedly small
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number of families sampled here. Of course, it is also possible that this is a replicable finding, another positive result of being the sibling of a brother or sister with mental retardation. Only additional research will direct us to the answer and the investigators must carefully match families with and without children with mental retardation on characteristics relevant to attachment formation.
3.3. Socioeconomic status and family size The increased responsibility assumed by the typically developing sibling is likely to be greatest in families with lower socioeconomic status (Damiani, 1999; Lobato, 1990). According to Farber (1960) in an early landmark study, middle-class parents and lower-class parents have different views of mental retardation. Middle-class parents see having a child with mental retardation as a tragic crisis that will prevent the occurrence of normative achievements. Low-socioeconomic status families, on the other hand, become involved in a reality crisis in which limited resources, such as income, must be stretched to meet the needs of the child with mental retardation. One way to meet the needs of the disabled child is by having his or her siblings assume high levels of responsibility for caregiving. These responsibilities are then assumed to have a negative impact on the siblings’ activities outside the home and on psychosocial adjustment. In addition, families with greater financial resources may be better able to afford supplementary services than are those with lower financial resources, thus permitting the siblings in those families to have more time to spend with friends, and to participate in out-of-home activities (Opperman & Alant, 2003). However, Hannah and Midlarsky (2005) found no association between income and helping, as reported either by siblings or by mothers. Siblings of children with mental retardation from larger families have been shown to have better outcomes than siblings of children with mental retardation who come from small families (Hannah & Midlarsky, 1985; Kaminsky & Dewey, 2002; Lobato, 1990). Large families seem to protect siblings from excessive involvement in caregiving because the responsibilities are shared among family members (Stoneman, 2001). The assumption is that large families adjust better to having a family member with mental retardation than do small families (Seligman & Darling, 1997). According to McHugh (1999), particularly in families in which there is one sibling without a disability, that sibling may feel a great responsibility both to engage in high levels of care, and also to be the ‘‘perfect child.’’ If there is more than one typically developing sibling, the helping responsibilities can be shared, and the pressure to be perfect can diminish.
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3.4. Parental adjustment and family climate When parents are experiencing emotional distress or are in conflict with one another, their children suffer. Thus, for example, the adjustment of typically developing siblings is related to the psychological adjustment and mental health of the parents—especially of mothers (Brody, 1998; Powell & Ogle, 1993). In a study of 110 siblings of children with developmental disabilities aged 8 to 15, Dyson, Edgar, and Crnic (1989) found that the self-concepts of the siblings were lower under conditions of parental stress and family conflict. On the other hand, siblings whose families tended to support personal growth and the free expression of feelings manifested more social competence, and fewer behavioral problems. Thus, researchers have found that siblings’ self-concepts are predicted by maternal self-concepts and by the level of parental stress (Auletta & DeRosa, 1991). Dyson (1999) found that typically developing children’s selfconcepts were more closely related to their family’s psychological wellbeing than to their relationship with their sibling with mental retardation. In addition, other researchers have found that adolescents who perceive their mothers as modeling compassion and emphasizing the importance of acting in a caring, responsible, and empathic manner are likely to exhibit higher levels of self-efficacy (Grissom & Borkowski, 2002). Family closeness and ability to communicate effectively can also affect the adjustment of siblings of children with a disability (Lobato, 1990). Healthy relationships between parents and children are related both to self-esteem and to depression among siblings of children with disabilities (Sgandurra & Fish, 2001). Furthermore, the parent–child relationship can be predictive of the sibling relationship, with negative interactions between the parent and child positively correlating with negative interactions among siblings (McHale & Gamble, 1989). This is especially important because positive interactions between siblings indicate better adjustment (Alper, Schloss, & Schloss, 1994) and can serve as a protective factor for siblings of children with certain disabilities (Fisman et al., 1996). Moreover, in families where there is limited interaction between the parents and the children, the typically developing siblings express more guilty feelings about their sibling with a disability (Opperman & Alant, 2003). Communication in families is important to provide clarification and an outlet for emotions, which can lessen anxiety among siblings of children with disabilities (Alper et al., 1994). When there is a child with special needs within the family, the typically developing siblings may believe, correctly or not, that their parents care less for them than for the child with special needs. Parents may focus the majority of their attention on the child with the disability because of that child’s level of need, which can leave typically developing children feeling neglected (Seligman & Darling, 2007). Also, parental expectations may
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increase for the typically developing sibling, in order to compensate for the low achievement of the child with special needs (Hannah & Midlarsky, 1985). These elevated expectations can result in feelings of anxiety, guilt, and anger that manifest in internalizing or externalizing behaviors (Wolf, Fisman, Ellison, & Freeman, 1998).
3.5. Severity and type of mental retardation Another factor that serves as a major influence on the typically developing children is the severity and the nature of their sibling’s disability. The severity of the disability will affect the amount of burden and responsibility that will fall on the typically developing siblings. Moreover, the nature of the sibling’s disability can serve as a mediator of parents’ reaction to the typically developing sibling (Stoneman, 1998). In a literature review, Del Rosario and Keefe (2003) discovered that whereas some research indicated that the severity of mental retardation was related to poor adjustment, other research found no relationship. Lobato (1990) found that although the severity of the mental retardation in the sibling with a disability may not affect the typically developing sibling’s distress level, the presence of behavioral problems can. Also at issue may be the type of mental retardation. In a study by Gath and Gumley (1987), siblings of children with Down syndrome experienced no social or academic disadvantages at school, based on both the mothers’ and the siblings’ reports. On the other hand, siblings of children with non-Down mental retardation exhibited higher rates of both reading retardation and behavior problems. Another perspective suggests that the severity of the disability may be an important contributor to the stress experienced by the parents. In a study by Minnes (1988), less stress was reported by parents of children with mild retardation than by those of children with severe mental retardation. In a study comparing families of children with mental retardation, pervasive developmental disorder, and typically developing children, Fisman, Wolf, Ellison, and Freeman (2000) found that parental stress mediated the association between the disability and the typically developing siblings’ behavior problems. They concluded that the well-being of the parents affects typically developing children, more than any problematic interactions among the siblings.
4. Methodological Considerations Results of research about the well-being and competence of typically developing siblings of children of mental retardation often appear to be inconsistent in two respects. First, researchers investigating the same
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aspect of adjustment obtain different findings. For example, some find no more emotional or behavioral problems among siblings of brothers and sisters with disabilities when compared to children whose siblings have no disability (Hannah & Midlarsky, 1999); others find significantly more emotional and behavioral problems in siblings of children with disabilities (Fisman et al., 2000). Notwithstanding, all agree that having a sibling with mental retardation constitutes a major factor in the typically developing siblings’ lives, shaping their daily routine, and their family environment (Seligman & Darling, 1997). Furthermore, it is likely that in families in which there is a child with a disability, as in all families, ‘‘positive and negative reactions occur’’ (Turnbull, Turnbull, Erwin, & Soodak, 2006, p. 39). The typically developing sibling may be more anxious, as well as higher in tolerance, and in actual and perceived competence. Experience in the home may lead to certain negative effects and may serve as a strengthening factor as well. One of the ways to explain the inconsistency in the research findings is to examine the different methodologies utilized in the different studies. Methods of data collection in the studies reviewed include self-report, parental report, teacher report, and direct observation. It has been shown that self-report produces the smallest negative effect size, while direct observation produces the largest. The effect size of parental reports falls between direct observation and self-report (Cicirelli, 1995; Hannah & Midlarsky, 1999; Rossiter & Sharpe, 2001). Cuskelly (1999) has noted that a good strategy for addressing these issues would be to collect comparative data from the greatest array of sources possible, and, of course, to use reliable and valid instruments. There are, however, barriers to the employment of these strategies. In regard to data collection from diverse sources, this multisource approach is difficult to implement because the high refusal rate by certain sources (e.g., teachers) can be high, or because the siblings whose responses are of interest are too young to provide reliable self-reports. Sometimes, the choice is to accept the limitation in the number of sources used, or to study a far smaller number of potential respondents, for whom multisource data are available. In regard to the employment of reliable and valid instruments, some investigators devote considerable attention to the development or selection of good instruments (Glidden, 1993). However, there are instances in which no measures with established psychometric properties are available (but see Glidden, 1993; Midlarsky, Hannah, & Corley, 1995). According to Singhi, Mahlhi, and Pershad (2002), other frequent methodological problems in the research include the lack of control and contrast groups. Where such groups are included, they are used for different reasons. For example, some studies use control groups to address questions about siblings of children with mental retardation in comparison with children with no disabilities. Other studies use contrast groups, in order to compare siblings of children with various disabilities (Hodapp, Glidden, & Kaiser,
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2005). Where matching is used, the procedures for matching are often inadequate. While siblings are ordinarily matched on such variables as sex, birth order, or age, other important variables such as family income may not be controlled. Although obtaining representative random samples is often difficult or even impossible, the almost exclusive reliance on convenience samples limits the generalizability of the results. The sample sizes are often too small to investigate hypotheses about main and interactive effects of predictor variables with sufficient power. As a consequence, most of the studies have not evaluated the role of factors such as socioeconomic status and family size in relation to the psychosocial adjustment of the typically developing siblings. Yet another issue is the wide variation in ages of children sampled so that studies are often not comparable because of disparities in developmental stages. As Stoneman (2005) notes, it would be important to learn about the relationships between typically developing siblings and their brothers and sisters with mental retardation at various stages of their lives, and how these relationships change over time. Furthermore, many of the studies have used siblings of heterogeneous groups of children with mental retardation or have focused exclusively on siblings of children with a particular form of mental retardation, such as Down syndrome. Since the behavioral characteristics and competencies of the children with mental retardation can vary greatly among diagnostic groups, it may be difficult to generalize about their impact on the sibling of the child with mental retardation. We believe that a wise course of action may be to describe and categorize the children with mental retardation in terms of their adaptive behaviors and competencies. Such an approach may facilitate generalizability, particularly since, as noted above, it appears that the severity of the mental retardation may affect the sibling and the sibling relationship. Currently, there is little attention paid to the need for longitudinal research, which is important for at least two reasons. First, in the absence of longitudinal (or alternatively, experimental) research, it is not at all clear that variables correlated with the siblings’ well-being also are causally related. Thus, we cannot be certain whether parental stress is a cause of the typically developing sibling’s behavior problems, a consequence of those problems, or whether a third factor is responsible for both. Second, longitudinal research could examine the impact of living with a sibling with mental retardation through the life course, rather than relying on cross-sectional studies which suffer from cohort effects. There is even a paucity of research using cross-sectional methodologies to investigate the well-being and adjustment of adults who have a sibling with mental retardation (Krauss, Seltzer, Gordon, & Friedman, 1996). A few of the more recent studies on this issue explore the nature of the interaction between the siblings, as well as the role that the typically developing brother or sister fulfills in this relationship (Greenberg, Seltzer,
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Orsmond, & Krauss, 1999; Pruchno, Partrick, & Burant, 1996). Further research on adults with a sibling with mental retardation should focus more on his or her long-term outcomes. In sum, this section presents an overview of some methodological sources of the differences in research findings across studies. In some cases, the presence in the family of a sibling with mental retardation is associated with adverse outcomes, and in others the outcomes are salutary. However, there are sources of these observed differences other than, and in addition to, methodological differences. One of these, which is a focus of research conducted in accordance with the framework of family systems theory (Minuchin, 1998), is that family systems are dynamic and complex so that brothers and sisters of children with mental retardation may experience both negative and positive reactions (Brody, 1994). Perhaps those studies that appear to have contradictory findings may be providing snapshots of different aspects of the dynamic process. Second is the possibility that outcomes for the siblings may differ because the helping behavior in which they engage may serve diverse functions for them. For at least some siblings, their helping within the family may serve as a mechanism for coping with stress. In addition, helping may contribute to the development of positive character and personality traits in the typically developing sibling. In Section 5, we present our conceptualization of the role of helping in the lives of siblings of children with mental retardation.
5. Helping by Siblings of Children with Mental Retardation Our focus on helping behavior by siblings is congruent with the current emphasis on positive aspects of development and functioning. The millennial issue of the flagship journal of the American Psychological Association (The American Psychologist) was devoted to a clarion call for a shift to an emphasis on human strengths. The ‘‘new field,’’ which is termed positive psychology, represents an attempt to navigate psychology (and especially clinical psychology) away from an exclusive emphasis on the disease model, wherein the task has been to heal psychopathology and to prevent the expression of destructive and self-destructive impulses. In the words of Seligman and Csikszentmihalyi (2000), in their introduction to the January 2000 issue, The field of positive psychology is about . . . contentment and satisfaction (past), hope and optimism (future), and flow and happiness (present) . . . it is about . . . the capacity for love and vocation, courage, interpersonal skill, aesthetic sensibility, perseverance . . . and about responsibility, altruism, civility, moderation, tolerance and work ethic (p. 6).
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Research on human strengths is certainly not new. Research on altruism and helping, as well as on love, competence, social responsibility, and other positive facets of human behavior have been ongoing for several decades. However, because the dominant emphasis has been on maladjustment and psychopathology, the advent of the positive psychology movement provides a spur to efforts to investigate the development, manifestations, and consequences of phenomena such as helping in various domains, including families in which a child has mental retardation. In the following, we present theoretical and empirical perspectives on the development of helping by typical siblings, and positive consequences that they may experience. In our conceptualization of the relationships between the antecedents and consequences of helping, we assume, to begin with, that the presence in the family of a child with mental retardation is a source of stress, where stress is defined as a challenge, excitation, or threat, that is, inherently neither positive nor negative.
5.1. The definition of helping The most basic definition of helping, a form of ‘‘prosocial’’ behavior (Dovidio, Piliavin, Schroeder, & Penner, 2006), is that it is behavior that benefits one or more others. Helping can be categorized in accordance with its motives. In the most general usage, helping is any act that is intentionally performed to benefit another, even if the behavior occurs in compliance with instructions or demands, or to obtain external rewards. What matters is simply that the help is given consciously and intentionally, so that the help is not received as an unintended consequence of the person’s behavior. Altruism is a form of helping that is undertaken voluntarily and because of concern for the other—not in order to obtain extrinsic rewards such as public recognition or approval. Pure altruism is a form of helping that is undertaken voluntarily and intentionally, for the sake of the other, and without expectation of either extrinsic or intrinsic rewards (Batson, Van Lange, Ahmad, & Leshner, 2003; Cialdini, Brown, Lewis, Luce, & Neuberg, 1997). Helping can also be categorized in accordance with the type of behavior—such as a ‘‘sharing of the wealth,’’ as in donation behaviors, or in ‘‘sharing of the pain or stress,’’ when the person helps by deflecting a physical assault on another (Midlarsky, 1973), or in caregiving (Midlarsky, 1994). In the Prosocial Tendencies Measure (Carlo & Randall, 2002), six types of helping were found based on a factor analysis of items describing helping: altruistic, compliant, emotional, dire, public, and anonymous. In developing the Family Helping Inventory (Midlarsky et al., 1995), specifically designed to measure prosocial behavior in a family context, the results of a factor analysis indicated that help given by siblings falls into four categories: custodial care, emotional support, information, and tangible
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aid. Custodial care covers those areas typically thought of as caregiving, such as bathing, dressing, babysitting, and feeding. Emotional support encompasses behaviors that have a nurturing quality to them, such as comforting, praising, and hugging. Information includes advice giving, goal setting and teaching, whereas tangible aid involves lending money or possessions, running errands, or doing chores.
5.2. The development of helping behavior Genes and helping. The view of sociobiologists is that altruism is genetically based, and that it is therefore part of the natural order of things to sacrifice oneself for others, particularly kin (Rachlin, 2002). However, observers of human interaction note that people vary greatly in their help-giving and caretaking behavior. Thus, it is apparent that socialization makes an important contribution to altruism and helping. Guilt. There is general agreement that helping begins to emerge by the second year of life (Zahn-Waxler et al., 1992). A factor associated with helping is guilt, described as a ‘‘moral emotion’’ which tends to motivate people to avoid hurting people and to engage in helping (Tangney, 1995). Guilt first arises in the second year of life, at about the same time as does helping, and the two appear to be linked (Zahn-Waxler et al., 1992). Children who manifest guilt tend to help and comfort others, while strengthening their social and emotional bonds in the process. Guilt has recently been characterized as a positive emotion (partly in contrast to shame; Tangney, 1995), although people who have excessive guilt tend to help less (Estrada-Hollenbeck & Heatherton, 1998). Hence, guilt may be a factor motivating helping by brothers and sisters of children with mental retardation, in response to their presumed feelings of guilt about their relative cognitive advantage. Helping roles and norms. Another factor that may promote helping is the existence of helping norms or roles within the family. In many societies, virtually all siblings become involved in caregiving. In Polynesia and Africa, children, and particularly girls, become caregivers at especially young ages (Edwards & Whiting, 1993). Generalizing about children’s behavior in six cultures, Whiting and Edwards (1973) found that when interacting with their siblings, children tend to exhibit helping behavior and support. When interacting with younger siblings, children exhibit nurturance, the offering or sharing of material goods, comfort, and physical care (Midlarsky, 1973). There has not been a great deal of research on caregiving by children in Euro-American families, but caregiving appears to be less of a role requirement for children in competitive and highly industrialized societies such as the United States than in other cultures (Midlarsky, 1994; Miller & Bersoff, 1998). Nevertheless, in families in which there is a child with a disability such as mental retardation, helping may be more normative (Boyce, 1990;
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McHale & Gamble, 1989; Stoneman, Brody, Davis, & Crapps, 1987, 1989; Stoneman et al., 1991; Wilson, Blacher, & Baker, 1989). Hannah and Midlarsky (2005) compared the helping behavior of siblings of children with mental retardation to that of siblings of children without mental retardation. The participants in the study were drawn from a larger investigation in which we assessed 100 siblings (52 boys and 48 girls), who ranged in age from 6 to 17 (M ¼ 12 years) (Hannah & Midlarsky, 1999). Half of the participants had a sibling with mental retardation, and the other half had a sibling who did not. The siblings of children with mental retardation were found to provide more custodial care and emotional support than siblings of children with no developmental disability. On the other hand, these siblings provided no more tangible aid or information than the siblings of children without a disability. It was unclear whether the siblings of children with mental retardation were motivated by the desire to help their siblings or to alleviate the burden of care shouldered by their mothers. In any event, though, their helping appeared to be more other-centered (allocentric) rather than self-centered (egoistic). Parental modeling and discipline. Children who are helpful tend to have parents who are caring people. Their parents are more likely to demonstrate compassion and empathy, and to take pleasure in these emotions than are less caring parents. As such, they serve as models of helping for their children (Dressel & Midlarsky, 1978). When discipline is needed, caring parents also tend to reason with their children, tell them what has been done wrongly, and then clearly outline behavioral expectations, rather than administering physical punishment. This kind of discipline, called ‘‘otheroriented’’ or ‘‘inductive,’’ is reportedly used frequently by parents of prosocial children (Hoffman, 2001). Furthermore, it may be a good strategy in families in which a child has a disability, as well. Ascription of responsibility. Although it may not be normative within American society to help within the family, particularly in relation to certain other cultures (Whiting & Whiting, 1973), children assigned responsibility to care for others may be more likely to engage in helping. For example, children who gave help to other children in a laboratory situation were more likely to be helpful in other situations (Staub, 1979). The manner in which responsibility is assigned is important in determining the effects of such ascription, as are the age and personality of the potential helpers. Thus, children induced to help by suggestion were more likely to be generous in another, later situation when compared to children who had been coerced to donate. The generalizaton effect was found only in children who were older (mid-elementary school or later vs kindergarten age), and among children who placed a high value on behavioral consistency (Eisenberg, Cialdini, McGreath, & Shell, 1989). One possible explanation for this is that when children who help have a need for consistency, they may have an enhanced probability of helping on subsequent occasions. Ultimately, they may
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develop a self-concept which encompasses self-as-helper. That self-concept may, in turn, prompt further helping. Competence. In the literature on prosocial behavior in children, both competence and self-esteem have been related to helping behavior. Midlarsky & Hannah (1985) found that children with a sense of personal competence readily offered assistance in contrast to children who did not feel competent, and therefore chose not to assist. The associations between competence, self-esteem, and helping have also been observed in both laboratory and field investigations of interpersonal helping by adults (Midlarsky & Hannah, 1989). When children help, two things are likely to occur. First, they may exercise competencies that they have, and second, they may acquire additional types of competence. As competence grows, the help-giving is more likely to succeed, thus serving to further enhance the sense of competence which, in turn, motivates later helping efforts. This ‘‘benign cycle’’ is depicted in a model of competence and helping (Midlarsky, 1984), on the basis of empirical findings. In that model, competence is viewed both as a factor related to the development of helping, and as a positive consequence of engaging in helping. The factors outlined here are among the many that are likely to operate in families in general, as well as in families in which a child has mental retardation, in particular. They serve to exemplify the processes that may elicit various forms of helping, at levels ranging from the genetic through personal, interpersonal, familial and cultural.
5.3. Consequences of helping Helping by typically developing brothers and sisters may be associated with adverse effects under certain circumstances. For example, if (1) they feel inordinately guilty, (2) have parents who coerce them to engage in helping that interferes with their own lives outside the home, (3) punish them severely for noncompliance with helping demands while (4) failing to reward them for their efforts, then the helping is likely to be linked to negative reactions. On the other hand, helping can be a rewarding activity in several respects, some of which have been mentioned in other sections of this chapter, and others that are enumerated here for the first time. 1. Sibling bond. The typically developing brother or sister often reports a better relationship with the sibling with special needs, than do siblings of typically developing children. This sibling bond may remain a stable center of attachment and satisfaction in the life of the developing individual. Studies by Rosen and his colleagues (e.g., Cheuk, Wong, Swearse, & Rosen, 1997) have found that when people are spurned by those to whom they offer help, they may become tense, unhappy, and mistrustful
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of others. Conversely, the presence in one’s life of a sibling who needs and welcomes one’s help may evoke warm and pleasant feelings. Empathic concern. As children help, whatever prompted the original behavior, their genuine concern for their sibling may grow along with the growth of the sibling bond. Once instilled, empathy may potentially become an important part of the individual’s interpersonal repertoire, thus evoking positive interactions inside and outside of the home of origin. This point is primarily based on anecdotal evidence, and is therefore speculative. Self-esteem, positive self-concept, and skills. In the model of competence and helping (Midlarsky, 1984), which is based on experimental data, just as the sense of competence skills and self-esteem can increase the probability of helping, they may also be enhanced once the person engages in competent helping behavior. Helping can lead to higher achievement for the helper. For example, tutors of others also gain skills, in addition to transmitting them (Elbaum, Vaughn, Hughes, & Moody, 1999). The literature provides numerous instances wherein being called upon to care for one’s siblings may lead to the sense of competence and of compassion (Bank & Kahn, 1982; Midlarsky, 1984; Seligman, 1983). This finding seems to run counter to the prediction by equity theory, which states that if either individual in a relationship gives more than he or she gets, then both become distressed (Adams, 1963). To the contrary, research findings indicate that unreciprocated giving is not necessarily a source of distress for the helper. Indeed, if anyone suffers, it is the recipient (Newsom, 1999). Well-being and satisfaction. Even (perhaps especially) when help is given with no expectation of rewards, or in response to parental demand, helping may yield its own intrinsic rewards. Following a series of experiments in which people had the opportunity to provide helping by lessening the duration of pain for another, the authors concluded that ‘‘altruism is always rewarding’’ (Weiss, Boyer, Lombardo, & Stitch, 1973). In a study about the impact of blood donation on the donors, the preponderance of a sample of 600 donors reported feelings of satisfaction. Even when some negative effects were noted (among 19% of the sample), they lasted a far shorter time than did the positive effects, which persisted for weeks (Nilsson Sojka, & Sojka, 2003). Hence, one possible outcome for the sibling is positive moods, and the sense of satisfaction and well-being. Sense of meaning and value in one’s life. We tend to evaluate ourselves and others by what we do. The typically developing brother or sister who helps his or her sibling with mental retardation is engaged in an activity which is undeniably useful, and creates important outcomes—to a far greater than age-peers who are not so engaged. Great meaning and purpose are attributed to helping behavior even among the most dire of circumstances.
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Among siblings of children with mental retardation, instances are reported in which the siblings were the source of important values (Orsmond & Seltzer, 2003). Indeed, although systematic studies have not yet been conducted to determine the link among values, helping, and the sense of meaning in this group, it seems likely that those who have developed prosocial values will find an enhanced sense of purpose and meaning when they help their siblings. Beyond this list of five likely positive outcomes, when one steps into the framework of positive psychology other salutary outcomes become apparent. The person who has grown up in a family in which a child has mental retardation may emerge with worries that are not shared by people whose siblings are all typically developing. On the other hand, as Dykens (2005, p. 362) states, others have estimated that having a sibling with disabilities leads them to increased . . . love, sense of social justice, advocacy for those in need, protection-nurturance, loyalty, implicit understanding and acceptance of difference, and what one sibling called his ‘‘common humanity’’ with others.
The first half of this chapter reviewed recent literature focusing on the outcomes of siblings of children with mental retardation. Years of research and recent awareness of this issue have generally led to the conclusion that outcomes for siblings of children with mental retardation are based on the action of variables such as sex, birth order, socioeconomic status and family size, parental adjustment, family climate and severity, and type of diagnosis—all of which are factors beyond the children’s control. The relationships of these variables to indices of adjustment determined how the outcome for siblings of children with mental retardation were interpreted and reported. This approach is similar to the approach taken in most theories of human development, which focus almost exclusively on the causative role of factors beyond the individual’s control. Missing from some of these theories is the consideration of the child as an active agent who has the capacity to act upon his or her environment, as well as be influenced by it (Midlarsky & Suda, 1978). Our conceptualization is more optimistic than many of those in the literature, and is close to the thinking of positive psychology (Peterson & Seligman, 2004; Seligman, 2002). In positive psychology, there are three routes to happiness. The first is through pleasant sensations and emotions, the second is through the sense of meaning obtained by serving the broader community, and the third is through one’s own achievements, work, and deeper connections to others. Even for younger siblings in a home in which a child with mental retardation is in need of care, at least one pathway to happiness does exist—that of engaging in some form of helping. Also of importance in positive psychology is the development and cultivation
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of character strengths and virtues. The sibling who shoulders the work of caregiving may have increases in character in areas such as emotional intelligence, perseverance, humanity and spirituality, as well as in the growth of competence and self-esteem. Thus, in our view, the caregiving in which the typically developing sibling engages has the potential to make positive contributions to his or her growth and development. The research that has been done on caregiving indicates that there are individual differences as well as group differences in the amount of help that is given (Hannah & Midlarsky, 2005). We posit that helping is generally unlikely to have negative consequences for the siblings’ adjustment. Even when negative consequences exist, though, helping is also likely to have salutary effects for the sibling (Midlarsky, 1984, 1991; Schwartz & Sandor, 1999). In order to provide a preliminary test of our model, we conducted a secondary analysis of our own data on helping by siblings of children with mental retardation (Hannah & Midlarsky, 2005). We were interested in determining whether, within our sample of children of siblings with mental retardation, those who engaged in higher levels of helping manifested more adjustment problems, and/or more positive reactions than children who engaged in lower levels of helping. We divided the sample of siblings of children with mental retardation into the 25 who fell above the median and the 25 who fell below the median. We then conducted three multivariate analyses of variance (MANOVAS), in both of which the independent variables were the children’s sex (male, female), and the amount of help given (high, low). In the first MANOVA, the dependent variables were mother’s ratings of the siblings’ internalization, externalization, and total number of problems, on the Child Behavior Checklist (CBCL; Achenbach, 1991). Results of this analysis indicated that there were no significant sex differences or differences between the high and the low helpers. Therefore, there was little evidence that higher levels of helping were related to increased problems in this sample. The second MANOVA focused on the mother’s ratings of competence in activities, social functioning, and school on the CBCL. Again there were no significant differences in terms of sex or amount of helping. This finding suggests that when children engage in high levels of helping, that helping does not impact negatively on their friendships, out-of-school activities and hobbies, or their school functioning. The third MANOVA did, however, provide evidence that those who engaged in higher amounts of helping reported more happiness and had higher levels of self-esteem. Higher helpers reported significantly more happiness, F ¼ 4.85, p < .03, and higher degrees of self-esteem, F ¼ 4.76, p < .03. Here, again, there were no sex differences. We originally considered conducting these analyses on the entire sample. However, had we done so, the preponderance of siblings of children with
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mental retardation would have fallen into the high help group, and most of the siblings of children with no mental retardation would have fallen into the low help group. This strategy would have yielded a confound between helping and living in a family with a child with mental retardation. Results of this type would have been fallacious and misleading. The results reported here are based on a rudimentary, preliminary examination of existing data. However, they do provide some initial empirical support for the link between helping and positive consequences for siblings of children with mental retardation.
6. Conclusions and Future Directions A variable that is consistently present in the research on siblings of children with mental retardation is increased responsibilities and/or helping behavior. While some research states that increases in sibling helping behavior leads to poor outcomes (Coleby, 1995; Rossiter & Sharpe, 2001), we take a very different view, that is, that helping may result in positive consequences for the typically developing sibling. One issue that must be addressed is why siblings of children with mental retardation from different families, who may be the same in regard to variables such as sex, socioeconomic status, and birth order, exhibit different outcomes, even though all of them help their siblings to some extent. One possible answer could be related to the child’s personality. There are marked individual differences in traits that predispose children to perceive and react to similar situations. Second, parents vary in the ways in which they ask, motivate, and reward their children for helping their sibling with mental retardation. It is therefore important that additional research be conducted on personality and family variables that promote helping. It is important to investigate what underlies the helping behavior that leads to better outcomes. Is it based on personality variables such as empathy and the sense of social responsibility (Midlarsky, Fagin Jones, & Corley, 2005)? Is it based on the modes of discipline used by parents or other adult caregivers in the family (e.g., induction; Hoffman, 2001)? Is it the sense of competence with which children approach helping, and which is further enhanced when their helping is successful (Midlarsky, 1984)? If so, how can positive engagement as caregivers to siblings with mental retardation be fostered or taught to children who do not have it? To conclude, further research should be done on how to assess and foster the traits that lead to successful coping through helping. Moreover, there needs to be a focus on helping parents to express their own positive feelings about helping their child with mental retardation, so as to serve as models of helping, and to express their positive feelings in response to their children’s
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caregiving behavior. Generally, the research in the area of siblings of children with mental retardation would benefit by conducting investigations of the ways in which typically developing children can be productive agents, and thereby reap positive benefits both for their families and for themselves.
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Index
A Abstract thinking, 8 Active Support Australian evaluation of, 235 conceptual issues ABA, 218–223 normalization, 217–218 PCP and PBS, 223–225 definition of, 206 developments, 215–217 evaluation effects, 225–227 evidence base evaluation studies, 227–236 indirect evidences, 236–238 functional aspects of, 212–214 historical overview, 207 as philosophy of care, 208 and residents’ challenging behaviors, 235–236 staff skill and residents’ engagement levels, 237 staff training on-site interactive training, 214–215 workshop training, 214 structural components of, 208–212 as system of planning and review activity protocols, 209–210 community contacts monitoring, 211 opportunity plans, 211–212 routines and rhythms, 209 structured teaching plans, 212 support plans, 210–211 techniques, for residents, 162 Active Support Measure (ASM), 235 Activity protocols, 209–210 Adaptive behavior, loss in, 143 Adolescence education, employment and leisure activities, 106 facial affect, 104 intimate relationships, 105 social-cognitive and emotion processes, 104 social competence in DS, 103–108 social inclusion and community involvement, 106 mental health, 108 systemic risk and protective factors, 106–108 cooperative structuring of activities, 108
role of parent and family factors, 107 social skill interventions programme, 107–108 Adult-infant interactions, 50 Affect-regulation system, 8 Altruism, 305. see also Helping behavior, by siblings American Association on Intellectual and Developmental Disabilities, 143 American Association on Mental Retardation, 143 Anchor activities, 210 Andover project, 207, 217, 227, 231–233 Anxiety disorders, 7, 10 Applied behavior analysis, 219–220 Arithmetic, Information, Coding, and Digit (AICD) Span, 127 Arousal activation and emotion processes, 5, 7–12 Asperger’s Syndrome (AS), 2, 11, 14–15, 266 Attention and information-processing difficulties, in autism, 16–18 Attention Deficit Hyperactivity Disorder (ADHD), 74, 258 Autism. see also Children amygdala activity, 9 characteristics, 2–3, 7–28 arousal activation and emotion processes, 5, 7–12 cognitive characteristics, 16–19 communication and language, 23–25 motor characteristics, 14–16 repetitive, restricted and stereotyped behavior, 25–28 sensory processing, 12–14 social interaction deficiencies, 19–23 cognitive explanations for, 63 comorbid diagnosis of, 64 critical periods of influence, 29–30 descriptive, comparative and process-oriented research on, 28–29 developmental theory, 4–7, 29–31 diagnosis, 3 environmental restriction and deprivation effects, 32–33 genetic basis, 2–3, 31, 33 incidence of, 3 longitudinal designs research needs, 30–31 mediational and moderational relationships and, 30
319
320
Index
Autism. see also Children (cont.) research directions, 28–31 stress and, 9, 32–33 subtypes and etiology, 30 Autism Diagnostic Observation Schedule, 25 Autism spectrum disorders (ASD), 17, 22–23, 74 Autistic disorder, 266 B Battered child syndrome, 254–255 Behavioral disorganization, 8 Behavioral objectives, 212 Belsky’s model, of risk factors of abuse, 278 Benign cycle, 308 Biopsycho-social model, 157 Bond’s Logical Operations Test (the BLOT), 144–145 British health care system, 220 British model of Active Support, 223 C Calm-alert state, 7 Canadian Tri-Council Policy Statement, on ethical conduct, 184 Caregiver interaction, in children with DS, 57–58, 93 Caregiving services, 306 Challenging behaviors, 221–222, 224, 226 Child abuse with disabilities among typically developing children, 271–273 characteristics, 273–278 definitional complications in research of legal, 255–256 medical, 254–255 research, 256–258 demographics, 263–269 ecology of, 269–271 methodological complications in research of, 258–263 data collection, 259 low rate of reporting, 261–263 retrospective studies, 260–261 samples of convenience, 258–259 Child Behavior Checklist (CBCL), 311 Child maltreatment, 253, 260, 264 Child neglect, 254 Child Protective Services (CPS), 254, 258 Children with autism amygdala activity in, 9 arousal activation and emotion processes, 5, 7–12 attention and information-processing difficulties in, 16–18 cognitive difficulties, 16–19 communication and language deficiencies, 23–25
executive function deficiency, 18 face processing in, 11–12 language and communication system development in, 10–11 limbic system dysfunctions in, 9–10 mood and anxiety disorders in, 7 motor characteristics, 14–16 parental stress and, 94 repetitive, restricted and stereotyped behavior, 25–28 sensory processing and disturbances in, 12–14 social cognition, theory of mind and empathy, 19 social interaction deficiencies, 19–23 stereotyped behaviors, 26 stress in, 9, 32–33 temperament in, 8 and childhood disintegrative disorder, 2 development theories, 45 with disability, 176 Children with Down syndrome articulation, and deciphering speech, 47 behavioral problems, 102–103 carryover effects, 56 communication development in, 46–47 developmental course of, 109 emotional understanding, 58–63 empathy, 66–68 environmental influence, 61 face paradigm, 56 false belief tasks, difficulties in, 63–65 family interactions role, 66 fear recognition difficulties, 60 friendships, 100–101 group play, 99–100 interpersonal functioning, 46, 49 intervention programs, 74 language development in, 46–47, 65 learning, 68–72 limbic system, 62 object permanence development in, 69 prosocial behavior, 66–68 rates of depression in, 108 social cognition, 43–76 definition, 44, 47 development, 68–72, 76 environmental factors, 74 future research areas, 73–76 impairments processes, 74 indicators, 49–58 literature on, 45–49 social interactions, 46 social understanding in, 49 sociocognitive behavior and caregiver styles of interaction, 57–58 and cognitive development, 68–72
321
Index
skills, 72–73 sociocognitive understanding indicators affective expressions, 56–57 expressing emotion, 56–57 imitation, 54–56 nonverbal gestures, 52–53 people, objects, and wider environment, 50–52 stress trajectories for mothers of, 75 test with visual cliff paradigm, 57 theory of mind and, 63–66 Clinical treatment paradigms, 158 Cognitive abilities, 90 Cognitive difficulties in autism attention and information-processing difficulties, 16–18 executive function deficiency, 18 social cognition, theory of mind and empathy, 19 Cognitive processes, 5–6 development, in Down syndrome (DS), 89 flexibility, 18 influences, and social competence, 89–91 skills in, 134, 136 Collaborative learning, 71 Communication in children with DS, 46–47 and language characteristics in autism, 23–25 processes, 5, 10 and Socialization subtests, 143 Communication disorders, 261 Community contacts monitoring, 211 Community involvement and social inclusion, in adolescence with DS, 106 Community Log, 212 Concrete operational competence, 143 Contextual influences, on research method selection, 156–158 Cooperative structuring of activities, for adolescence with DS, 108 Critical multiplism, 159 Crystallized intelligence, 135, 141, 144, 146 D Daily life activities, 208 activity mapping/planning, 209–210 Daily Living Skills subtest, 143 Data collection, for research design consent, people with disability, 182–187 Deciphering speech, in children with DS, 47 Dementia, 155. see also Anxiety disorders Developmental theory, of autism, 4–7 Development, social-bioecological model, 91 Diagnostic overshadowing, 262 Digit Symbol Substitution, 146 Distal (indirect) effect, 91
Down syndrome (DS), 21, 27, 33, 280, 295, 297, 301, 303. see also Children with Down syndrome cognitive development in, 89 neuropsychological profiles of strengths and weaknesses, 48 parental stress and, 94 risk and protective factors associated with, 94 sociability and friendliness and, 99 social cognition of children with, 43–76 and social competence in adolescence, 103–108 evidence on, 92–108 in infancy and preschool years, 93–98 in middle childhood, 98–103 research on, 89 DSM-IV classification system, 2, 5 Dyadic interactions, in parent–child interaction, 93–96 E Ecological model, of child abuse, 269–271 Education and employment, in adolescence with DS, 106 Emotional abuse, of child, 254 Emotional understanding, in children with DS, 58–63 Empathy, in children with DS, 19, 66–68, 309 Engagement, concept of, 207 Environmental influence, in children with DS, 61 Epistemological perspectives, of researcher, 155 Executive function, 8 deficiency in autism, 18 and theory of mind, 64 Exosystem and abuse, 273, 276–278 Experiential learning theory, 223 Eye-gaze avoidance, 17 Eye tracking research, 62 F Face-to-face interactions, 96 Facial affect in adolescents with DS, 104 in children with DS, 56 deficits in pragmatic language, 104–105 False belief tasks, difficulties in children with DS, 63–65 understanding, 63–64 Family environment, influence on child behavior, 270–272 Family Helping Inventory, 305 Family interactions role, in children with DS, 66 Fear recognition difficulties, in children with DS, 60 Females, autism in, 3 Fetal alcohol syndrome, 257
322
Index
Five Essential Accomplishments, 218 Flexible routines, 209–210 Fluid intelligence, 135, 141, 144, 146 Flynn effect and MR diagnosis of grandparent generation, 133–134 history of bottom normal population, 128–133 matter of life and death, 122–127 solutions, 137–141 Piagetian approach, 137–140 psychometric approach, 140–141 temporary expedient, 127–128 WISC subtests, 134–137 Formal operational competence, 143 Fourth Circuit Court of Appeals, 125 Fragile X syndrome, 280 Friendships, in middle childhood, 100–101 Furman v. Georgia case, 124 G Genetic basis, of autism, 2–3 Goal planning, 211–212 medium term, 213 Grounded theory, for qualitative researcher, 155, 163 Group play, in middle childhood, 99–100 Guilt, 306 H Hawaii’s Healthy Start Program, 281–282 Head Start program, 252 ‘‘Helpful environment’’, 222 Helping behavior, by siblings consequences of helping behavior, 308–312 definition of helping, 305–306 development of helping behavior, 306–308 Helsinki declaration, 184 Hemophilia, 262 Hierarchical Linear Modeling (HLM), 279 High-functioning autism (HFA), 14 Horn-Cattell theory of Fluid Intelligence, 135 ‘‘Human-as-instrument’’, in research activities, 170 Human Genome Project, 48 Hypothalamic-pituitary-adrenal (HPA) reactivity, 7 I IASSID. see International Association for Scientific Study of Intellectual Disability Immature self-regulatory system concept, 26 Incidental activities, 210 Individualized Education Plans, 281 Individual Plans, 213, 224 Indwelling, in qualitative inquiry, 169 Infancy and preschool years
parent-child interaction in, 94–97 risk and protective factors associated with DS, 94 social-communicative behaviors, 95 social competence in DS, 93–98 social services and early intervention programs, 97–98 systemic risk and protective factors, 97–98 verbal and nonverbal communication delays, 97 Infant-caregiver relationship, 27 In situ interview technique, for people with disability, 193 Intellectual development and social understanding, 45 disabilities, 16, 207, 217, 257, 263 Intellectually deficient, 132 Interactive training, 214–215 International Association for Scientific Study of Intellectual Disability, 156 Interpersonal functioning. in children with DS, 46, 49 Intimate relationships, in adolescence with DS, 105 Involuntary motor behaviors, 15 IQ criterion, and mental retardation (MR), 122–147 Item response theory (IRT), 140–141, 143–144, 146 L Language acquisition and development, 10–11, 24 communication in children with DS, 46–47 processes, 5–6 skills development, 46 Learning by children with DS, 68–72 Learning disability, 257, 264 Leisure activities, in adolescence with DS, 106 Lethargy, 8, 13 Likert scales, 190–191 Limbic system dysfunctions, 9–10 M Macrosystem and abuse, 273, 276–278 immediate child and family factors, 274–276 Maladaptive behaviors, 267 Males and autism, 3 Mediation, social learning through, 90 Mental deficiency criterion, 131 Mental health and social inclusion, in adolescents with DS, 108 Mental retardation (MR), 257 capital punishment and, 146–147 criterion of, 122, 124, 126, 128–133, 141–142, 147 diagnosis of, 122
323
Index
of grandparent generation, 133–134, 136–137 IQ role, 122–147 matter of life and death, 122–127 necessary tasks for, 142–144 problems for tests, 145–146 temptation and, 142 Methodological pluralism, 152 and people with disability, 156 Microgenesis, 90–91 Middle childhood benefits of peer relationships, 98 friendships, 100–101 group play, 99–100 peer interactions, 99–101 social competence in DS, 99–103 systemic risk and protective factors in, 102–103 Mind-blindness, 19 Mind theory, 19 and children with DS, 63–66 and child’s environment, 65 cognitive aspects of, 65 and executive function, 64 neurological basis of, 66 Mirror neuron system, 23 Mixed-method designs, for research method selection, 175 data triangulation and rigor evaluation, 179–182 practical and technical problems, 176–179 third party involvement, 192 Monitoring, of community, 211 Mood disorders, 7 Motor processes, 5, 14–16 N National Association of Educational Progress (NAEP) tests, 135–136 National Child Abuse and Neglect Data System (NCANDS), 259 National Health and Medical Research Council (NHMRC), 184, 186 National Health Service by the Social Care Information Centre (U. K.), 186 Nation’s Report Card, 135–136 ‘‘Nay-saying’’, in intellectually disabled individuals, 188–189 Non-autism spectrum disorder (non-ASD) controls, 11 Normalization theory, 217–218, 223 Nuremberg Code (1949), 183 O Object permanence tasks, 55 Off-site workshop training, 214 On-site interactive training, 214–215, 223
On-the-spot reasoning (Fluid intelligence), 135, 141, 146 Ontogenesis, 90–91 Ontological perspectives, of researcher, 155 Opportunity plans, 211–212 Ordinary lifestyle, 211 Organizational technology, 217–220 P Paper-based system, of Active Support, 208, 214 recording mechanisms, 217 Parental abuse, child, 255 Parental influence, on child behavior, 270–272 Parental ontogenic risk factors, 273–274 Parent and family role, for adolescence with DS, 107 Parent-child interaction, 91–92, 94–97, 99 caregiving relationship, 93 dyadic interactions, 93–96 in infancy and preschool years, 94–97 parent-sibling relationships, 97 siblings of children with disability, 300 triadic interactions, 93, 96–97 Participants recruitment, in qualitative research, 163 Participation Index, 210, 234 Peer interactions, in middle childhood, 99–101 People with disability acquiescence bias of, 189 autonomous decision makers, 185 consent for data collection, 182–187 interview, 187–191 ‘‘nay-saying’’, 188–189 participants, 191 quality of life (QoL) for, 152 in situ interview technique, 193 Person-Centered Planning (PCP), 215, 217 Pervasive developmental disorder-not otherwise specified (PDD-NOS), 2, 4, 11 Pervasive developmental disorders (PDD), 2, 7 Phenomenology, for qualitative researcher, 163 Physical abuse, of a child, 254 Piagetian approach, to Flynn effect and MR diagnosis solutions, 137–140, 143–146 Planned community activities, 211 Positive Behavior Support (PBS), 217, 224 Positive psychology, 310 Prader-Willi syndrome, 280 Prenatal substance exposure, 257 Priority sequence model, 179 Problem solving, 8 Prosocial behavior, in children with DS, 66–68 Prosocial Tendencies Measure, 305 Proximal (direct) effect, 91 Proxy consent, 184–185
324
Index
Psychometric approach, to Flynn effect and MR diagnosis solutions, 140–141 Purposive sampling, 163
Rett’s disorder, 2 Risk and protective factors, associated with DS in infancy and preschool years, 94
Q
S
Qualitative research methods aim, 183 characteristics, 162–163 data triangulation, 180 focus on tacit knowledge, 173–174 and quantitative research methods, 170–175 strategies and protocols, 163–168 Quality of life (QoL), for people with disability, 152, 207 Quantitative research methods aim, 183 characteristics, 159–160 focus on investigation and testing, 173 and qualitative research methods, 170–175 strategies and protocols, 160–162 Quasi-experimental designs, 162
Sampling technique, for qualitative research, 164 School learning problems (SLPs), 144 SDT. see Special Development Team Secure attachment behavior, 93, 298 Self-concept, 307–308 Self-monitoring, 8 Self-regulation processes, 5–6, 27–28 Self-understanding, 8 Sensory distortions and overloads, 12 Sensory processing, in autism, 5, 12–14 Sexual abuse, child, 254 Sibling bond, 308–309 Siblings with mental retardation, impacts factors associated with adjustment birth order, 297–299 parental adjustment and family climate, 300–301 severity and nature of retardation, 301 sex and age differences, 296 socioeconomic status and family size, 299 helping behavior by siblings consequences of helping behavior, 308–312 definition of helping, 305–306 development of helping behavior, 306–308 methodological considerations, 301–304 negative, 294 positive, 295 Social classes, incidence of autism across, 3 Social cognition, 19 in children with Down syndrome (DS), 43–76 definition, 44, 47 development, 68–72, 76 environmental factors, 74 future research areas, 73–76 impairments processes, 74 indicators, 49–58 literature on, 45–49 definition, 44, 47 processes, 90 Social communicative behaviors, 22 Social competence behavioral indices of, 88, 92 construct of, 89–92 cognitive influences, 89–91 social-environmental influences, 91–92 coordination of social abilities for, 90 in Down syndrome (DS) adolescence, 103–108 evidence on, 92–108 infancy and preschool years, 93–98 middle childhood, 98–103 research on, 89
R Random sampling, 160 Raven-Similarities rate, 137 Raven’s Progressive Matrices (RPM) test, 134, 136–137, 139, 145 Repetitive behavior, in autism, 25–28 Researcher-centered influences, on research methods selection adherence of, 154–155 clinical research paradigm and critical multiplism, 158–159 collection and observation of data, 154 contextual influences, 156–158 and disability study, 156 ontological and epistemological perspectives, 155 Research method(s) selection clinical research paradigm and critical multiplism, 158–159 contextual influences, 156–158 data collection with disabled people consent and, 182–187 interview and, 187–191 qualitative research methods, 162–168 quantitative research methods, 159–162 researcher-centered influences, 154–156 Residential Practices Working Scale (RSWPS), 236–238 Residents adaptive behavior, 162 Response inhibition, 18 Restricted behavior, in autism, 25–28 Reticular activating system, 8
325
Index
in infancy, 91, 93–98 model of, 89–90 Social comprehension, 8 Social development, 11 Social-environmental influences, and social competence, 91–92 Social inclusion in adolescence and community involvement, 106 and mental health, 108 Social interactions, 46 in children with DS, 46 deficiencies in autism, 19–23 emotional communication and, 56 processes, 5–6 Social learning, through mediation, 90 Social neuroscience, research trends in, 89 Social Security program, 252 Social services and early intervention programs, for infancy and preschool years, 97–98 Social skill interventions programme, for adolescence with DS, 107–108 Social understanding in children with DS, 49 and intellectual development, 45 Socioadaptive skills, development of, 46 Sociocognitive and cognitive development, in children with DS, 57–58, 68–73 Sociocognitive understanding indicators in children with DS affective expressions, 56–57 attending to people, objects, and wider environment, 50–52 expressing emotion, 56–57 imitation, 54–56 nonverbal gestures, 52–53 Special Development Team, 207, 227–228, 233 Special Interest Research Groups (SIRGs), 156 Specific, manageable, achievable, realistic, and timed (SMART), 211 Staff attention, 220 Staff preferences, on activity, 210 Stanford-Binet and Wechsler tests, 135, 141, 146 Stereotyped behavior, in autism, 25–28 Stored knowledge (Crystallized intelligence), 135 Strange Situation Task, 95 Stress trajectories for mothers, of children with DS, 75 Structured Teaching Plan, 213 Synesthesia, 12
Systemic risk and protective factors in adolescence, 106–108 in infancy and preschool years, 97–98 in middle childhood, 102–103
T Tacit knowledge and qualitative research, 173–174 Task analysis, 209, 212 Teaching plans, in community home, 224 Temporary Assistance for Needy Families program, 252 Test with visual cliff paradigm, in children with DS, 57 Tongue protrusion, 54 Triadic interactions, in parent–child interaction, 93, 96–97 Triangulation of data, for research techniques, 179–182 Typically developing (TD) infants, 94–98, 104 behavioral problems, 102–103 friendships, 100–101 group play, 100 U Uncomfortable feelings, 8 Unexpected transfer task, 63 V Validity in quantitative research, 162 Vineland Adaptive Behavior Scales, 143, 147 Voluntary motor behaviors, 15 W WAIS data, 124, 128, 141 Weak central coherence, 17–19 Wechsler-Binet tests, 137, 143, 146 Wechsler Intelligence Scales for Children (WISC), 122–125, 129–138, 144 Wechsler IQs, 147 West Sussex Social Services’ child protection register, 264–265 White Paper ‘‘Valuing People’’, 239 Williams syndrome, 61, 280 Working memory, 18
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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
327
328
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
329
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
330 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
331 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
332
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
333 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
334 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
335 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
336 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
337 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
338 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
339 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
340 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 BARBARA TYLENDA, JACQUELINE BECKETT, AND ROWLAND P. BARRETT Adaptive Behavior Scales DENNIS R. DIXON 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
341 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 Pain Assessment FRANK ANDRASIK AND CARLA RIME Index
