Advances in Psychology Research Volume 57

ADVANCES IN PSYCHOLOGY RESEARCH VOLUME 57

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

ADVANCES IN PSYCHOLOGY RESEARCH Advances in Psychology Research, v. 56 Alexandra Columbus (Editor) ISBN 978-1-60456-508-9 Advances in Psychology Research, v. 55 Alexandra Columbus (Editor) ISBN 978-1-60456-176-0 Advances in Psychology Research, v. 54 Alexandra Columbus (Editor) ISBN 978-1-60456-129-6 Advances in Psychology Research, v. 53 Alexandra Columbus (Editor) ISBN 978-1-60021-924-5 Advances in Psychology Research, v. 52 Alexandra Columbus (Editor) ISBN 978-1-60021-662-6 Advances in Psychology Research, v. 51 Alexandra Columbus (Editor) ISBN 978-1-60021-660-2 Advances in Psychology Research, v. 50 Alexandra Columbus (Editor) ISBN 978-1-60021-530-8 Advances in Psychology Research, v. 49 Alexandra Columbus (Editor) ISBN 978-1-60021-580-3 Advances in Psychology Research, v. 48 Alexandra Columbus (Editor) ISBN 1-60021-373-1 Advances in Psychology Research, v. 47 Alexandra Columbus (Editor) ISBN 1-60021-293-X Advances in Psychology Research, v. 46 Alexandra Columbus (Editor) ISBN 1-60021-248-4 Advances in Psychology Research, v. 45 Alexandra Columbus (Editor) ISBN 1-60021-152-6 Advances in Psychology Research, v. 44 Alexandra Columbus (Editor) ISBN 1-60021-150-X Advances in Psychology Research, v. 43 Alexandra Columbus (Editor) ISBN 1-60021-105-4 Advances in Psychology Research, v. 42 Alexandra Columbus (Editor) ISBN 1-60021-104-6 Advances in Psychology Research, v. 41 Alexandra Columbus (Editor) ISBN 1-60021-061-9 Advances in Psychology Research, v. 40 Alexandra Columbus (Editor) ISBN 1-59454-836-6 Advances in Psychology Research, v. 39 Alexandra Columbus (Editor) ISBN 1-59454-420-4

Advances in Psychology Research, v. 38 Alexandra Columbus (Editor) ISBN 1-59454-478-6 Advances in Psychology Research, v. 37 Alexandra Columbus (Editor) ISBN 1-59454-262-7 Advances in Psychology Research, v. 36 Alexandra Columbus (Editor) ISBN 1-59454-255-4 Advances in Psychology Research, v. 35 Alexandra Columbus (Editor) ISBN 1-59454-079-9 Advances in Psychology Research, v. 34 Serge P. Shohov (Editor) ISBN 1-59454-079-9 Advances in Psychology Research, v. 33 Serge P. Shohov (Editor) ISBN 1-59454-078-0 Advances in Psychology Research, v. 32 Serge P. Shohov (Editor) ISBN 1-59033-969-X Advances in Psychology Research, v. 31 Serge P. Shohov (Editor) ISBN 1-59033-985-1 Advances in Psychology Research, v. 30 Serge P. Shohov (Editor) ISBN 1-59033-943-6 Advances in Psychology Research, v. 29 Serge P. Shohov (Editor) ISBN 1-59033-921-5 Advances in Psychology Research, v. 28 Serge P. Shohov (Editor) ISBN 1-59033-868-5 Advances in Psychology Research, v. 27 Serge P. Shohov (Editor) ISBN 1-59033-803-0 Advances in Psychology Research, v. 26 Serge P. Shohov (Editor) ISBN: 1-59033-798-0 Advances in Psychology Research, v. 25 Serge P. Shohov (Editor) ISBN: 1-59033-59033-765-4 Advances in Psychology Research, v. 24 Serge P. Shohov (Editor) ISBN: 1-59033-739-5 Advances in Psychology Research, v. 23 Serge P. Shohov (Editor) ISBN: 1-59033-693-3 Advances in Psychology Research, v. 22 Serge P. Shohov (Editor) ISBN 1-59033-652-6 Advances in Psychology Research, v. 21 Serge P. Shohov (Editor) ISBN 1-59033-651-8

Advances in Psychology Research, v. 20 Serge P. Shohov (Editor) ISBN 1-59033-614-3 Advances in Psychology Research, v. 19 Serge P. Shohov (Editor) ISBN 1-59033-569-4 Advances in Psychology Research, v. 18 Serge P. Shohov (Editor) ISBN 1-59033-547-3 Advances in Psychology Research, v. 17 Serge P. Shohov (Editor) ISBN 1-59033-537-6 Advances in Psychology Research, v. 16 Serge P. Shohov (Editor) ISBN 1-59033-472-8 Advances in Psychology Research, v. 15 Serge P. Shohov (Editor) ISBN 1-59033-410-8 Advances in Psychology Research, v. 14 Serge P. Shohov (Editor) ISBN 1-59033-393-4 Advances in Psychology Research, v. 13 Serge P. Shohov (Editor) ISBN 1-59033-326-8 Advances in Psychology Research, v. 12 Serge P. Shohov (Editor) ISBN 1-59033-248-2 Advances in Psychology Research, v. 11 Serge P. Shohov (Editor) ISBN 1-59033-186-9

Advances in Psychology Research, v. 10 Serge P. Shohov (Editor) ISBN 1-59033-162-1 Advances in Psychology Research, v. 9 Serge P. Shohov (Editor) ISBN 1-59033-139-7 Advances in Psychology Research, v. 8 Serge P. Shohov (Editor) ISBN 1-59033-124-9 Advances in Psychology Research, v. 7 Frank Columbus (Editor) ISBN 1-59033-054-4 Advances in Psychology Research, v. 6 Frank Columbus (Editor) ISBN 1-59033-014-5 Advances in Psychology Research, v. 5 Frank Columbus (Editor) ISBN 1-56072-953-8 Advances in Psychology Research, v. 4 Frank Columbus (Editor) ISBN 1-56072-952-X Advances in Psychology Research, v. 3 Frank Columbus (Editor) ISBN 1-56072-897-3 Advances in Psychology Research, v. 2 Frank Columbus (Editor) ISBN 1-56072-903-1 Advances in Psychology Research, v. 1 Frank Columbus (Editor) ISBN 1-56072-774-8

ADVANCES IN PSYCHOLOGY RESEARCH VOLUME 57

ALEXANDRA M. COLUMBUS EDITOR

Nova Science Publishers, Inc. New York

Copyright © 2008 by Nova Science Publishers, Inc.

All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA (Available on request)

ISBN: 978-1-60876-245-3 (E-Book)

Published by Nova Science Publishers, Inc.

New York

CONTENTS Preface

ix

Short Communication Body Image Figure Performance in Sorority Women Rachel Moericke, F. R. Ferraro and Jennifer Muehlenkamp Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

1

The Development of Epistemic Complexity in Adulthood: Personal Conceptualizations of Self and Culture Gabriel Bukobza

9

The Role of Omega-3 Fatty Acids in the Prevention and Treatment of Neuropsychiatric and Neurodevelopmental Disorders Sa’eed Bawa

39

Student Reports of Bullying: Results from the 2001 School Crime Supplement to the National Crime Victimization Survey Jill F. DeVoe and Sarah Kaffenberger

75

Factors that Influence Subjective Time: Gender, Type of Person, and Time of Day? David P. Austin, F. Richard Ferraro, Ryan Kerzman, Thomas V. Petros and Jeffrey N. Weatherly Cognitive and Behavioral Alterations in Corticobasal Degeneration Presenting as Dementia Phenotype Rita Moretti, Paola Torre, Cristina Vilotti, Maja Ukmar, Francesca Capozzoli and Rodolfo M. Antonello

119

135

A Possible Role of the BDNF/Trkb Pathway in the Pathogenesis of Bipolar Disorder and Potential Therapeutic Targets Shih-Jen Tsai and Chen-Jee Hong

149

Difficulty Coping and Stressors in the First Year Postpartum for Mothers and Fathers Stephen Matthey

163

viii Chapter 8

Contents Cocaine-Dependent Patients with Antisocial Personality Disorder, Cocaine-Dependence, and Treatment Outcomes Nena Messina, David Farabee and Richard Rawson

Chapter 9

Childhood Sexual Abuse and Borderline Personality Disorder Randy A. Sansone and Lori A. Sansone

Chapter 10

Post-Partum Depression: Prevalence and Demographic, Obstetric and Perinatal Risk Factors Alexandre Faisal-Cury and Paulo Rossi Menezes

Index

173 197

211 223

PREFACE Advances in Psychology Research presents original research results on the leading edge of psychology research. Each article has been carefully selected in an attempt to present substantial research results across a broad spectrum. Short Communications- Sorority women and non-sorority women participated in an experiment that examined perceptions of body image and body shape. Participants were asked to endorse body silhouettes, which ranged from very thin to very obese, in order to assess their perceptions of several aspects of body image including what they believed to be the ideal body shape for themselves as well as how others should look. The researchers hypothesized that sorority women would endorse smaller silhouettes than non-sorority women and that more years in a sorority would lead to endorsing even smaller silhouettes. The results indicated sorority women endorsed figures that were significantly smaller than figures endorsed by the non-sorority women, and the more years in a sorority was also significantly negatively associated with endorsement of smaller body image silhouettes. These results will be discussed as they relate to contributing factors related to the onset of eating disorders in college women. Chapter 1- This study examined how adult individuals construe knowledge. Eighty participants, aged 17-70 were interviewed regarding their personal knowledge of self and culture. Content analysis of the interviews revealed four fundamental structures of knowledge, or epistemes, which differed in level of complexity and consistently appeared in both domains. The four epistemes are, in ascending level of complexity: MonolithicMonoformal, Relativist-Relational, Dialectical-Deconstructive, and Integral-Inclusive. The implications of the findings to the areas of development, self, culture, post-formal cognition, and wisdom are discussed. Chapter 2- Dietary factors may, to some extent, be responsible for the increase in the incidence of neuropsychiatric and neurodevelopmental disorders in Western societies and in some developing countries. One factor that may be particularly important is the high level of the consumption of omega-6 fatty acids compared with omega-3 fatty acids. Anthropological data suggest that the intake of omega-6 and omega-3 fatty acids during the Palaeolithic age was almost the same, but the present omega-6 to omega-3 fatty acids ratio in Western diets has been estimated to be between 10 and 25 to 1. Even in Japan, where seafood has traditionally been consumed at very high levels, the ratio of omega-6 to omega-3 fatty acids is increasing as diets become more westernized, leading some authors to suggest that fish consumption be increased, particularly amongst young people. The omega-6 to omega-3

x

Alexandra M. Columbus

PUFA imbalance has been brought primarily by the increase in vegetable and seed oil use, and a decrease in fish or fish oil intake. Fats constitute sixty percent of the brain and nerves that are responsible for running every system in the human organism. Omega-3 fatty acids (αlinolenic, eicosapentaenoic, docosahexaenoic) play an important role in the development and function of the central nervous system. Epidemiological data suggest that there is a link between the development of neurodevelopmental disorders, such as dyslexia, dyspraxia, attention-deficit hyperactivity disorder and autistic spectrum disorders as well as neuropsychiatric disorders, such as major depression, dementia, schizophrenia and Parkinson’s disease and the consumption of fish. There are several mechanisms, whereby omega-3 fatty acids may decrease the risk of neurodevelopmental and neuropschiatric abnormalities. Omega-3 fatty acids are an essential component of CNS membrane phospholipid acyl chains and are therefore critical to the dynamic structure and function of neuronal membranes. Omega-3 fatty acids can alter membrane fluidity by displacing cholesterol from the membrane and optimal fluidity, influenced by essential fatty acids, is required for neurotransmitter binding and the signaling within the cell. Essential fatty acids, especially of the omega-3 family can act as sources for second messengers within and between neurons. Omega-3 fatty acids may exert significant influence in major depression via cytokine modulation. Although, epidemiological and clinical data have shown beyond reasonable doubts the significance of omega-3 fatty acids in the prevention of cardiovascular and neurodegenerative diseases, the focus of this chapter is to demonstrate the role of omega3 fatty acids in the prevention and management of neuropsychiatric and neurodevelopmental disorders. Chapter 3- Bullying in schools is an issue that continues to receive attention from researchers, educators, parents, and students. Despite the common assumption that bullying is a normal part of childhood and encompasses minor teasing and harassment, researchers increasingly find that bullying is a problem that can be detrimental to students’ well-being. Bullying is commonly defined as being “exposed, repeatedly and over time, to negative actions on the part of one or more other students”. Olweus also suggests that bullying can be characterized by two distinct forms of negative actions: direct and indirect bullying behaviors. Direct bullying takes the form of overt, physical contact in which the victim is openly attacked. Indirect bullying takes the form of social isolation and intentional exclusion from activities. Both forms of bullying, occurring separately or together, can be harmful to students’ well-being and development. This chapter examines the prevalence and nature of bullying in relation to student characteristics, school characteristics, and victimization. In addition, the study explores other behaviors that were reported by the victim, such as fear, avoidance behavior, weapon carrying, and academic grades. It also examines student reports of being bullied by direct means only, bullied by indirect means only, and bullied both directly and indirectly. Readers are alerted to the limitations of the survey design and analysis approach with regard to causality. Conclusions about causality can not be made due to the cross-sectional, nonexperimental design of the survey used. And, while certain characteristics discussed in this chapter, such as school control, gang presence, security guards, and hallway monitors, may be related to one another, this analysis does not control for such relationships. Therefore, no causal inferences should be made between the variables of interest and bullying when reading these results.

Preface

xi

Chapter 4- The present study focused on short-duration time estimation, which by definition is vital for assessing the immediate environment. This study explored the roles of time of day, type of person, and gender on empty and complex intervals and 60-s fixed-time and 30/90-s variable-time periods. The participants (N = 104) were students from a psychology department subject pool who were prescreened using the Horne and Ostberg scale. Participants were then randomly assigned to participate either in the morning or in the evening. The participants operated a stopwatch to measure the amount of time they believed had passed across 10 trials in each of four different conditions (empty intervals for a 60-s fixed-time period, complex intervals for a 60-s fixed-time period, empty intervals for a variable-time period that averaged to 60-s, and complex intervals for a variable-time period that averaged to 60-s). The results revealed that gender does not influence time estimation. However, the Time of Day X Type of Person vs. Complex/Variable interaction was significant. Surprisingly, the intervals containing complex stimuli had a longer reported duration than the empty intervals, suggesting that time passes by slower when the interval is filled with a complex event. Chapter 5- "In dementias, one may find all sorts of specific losses … and, as the disease worsens, a reduction of personal identity. And yet this reduction is virtually never complete; it is as if identity has such a robust, widespread neural basis; as if personal style is so deeply ingrained in the nervous system that it is never wholly lost, at least while there is still any mental life present at all. (This, indeed, is what one might expect if the personal quality of experience and feeling and thought has molded the structure of the brain from the start.) And it is this that makes a continuing possibility of being affected by music, even in the most deeply damaged patients, long inaccessible to language and most other modes of communication. For it is the inner life of music that can still make contact with their inner lives, with them; that can awaken the hidden, seemingly extinguished soul; and evoke a wholly personal response of memory, associations, feelings, images, a return of thought and sensibility, an answering identity." (O. Sacks) Chapter 6- Brain-derived neurotrophic factor (BDNF), a member of the neurotrophic factor family, promotes neuronal development, survival and function. In addition, BDNF can modulate synaptic plasticity and neurotransmitter release across multiple neurotransmitter systems, as also modulate various intracellular signal-transduction pathways. BDNF exerts its effect through the receptor tropomyosin related kinase B (TrkB) and the p75 low affinity neurotrophin receptor. Recent studies have demonstrated that the BDNF/TrkB pathway may play an important role in the pathogenesis and therapy of bipolar disorder (BPD). In rodents, mood-stabilizing treatments have been shown to alter the BDNF/TrkB activity. Furthermore, recent genetic association studies have demonstrated that the BDNF genetic polymorphism is associated with BPD. Stress has been shown to markedly alter BDNF levels in certain brain areas including the hippocampus, which is thought to be involved in the pathogenesis of mood disorders. In this review, the authors summarize their current understanding of the involvement of the BDNF/TrkB pathway in the pathogenesis of BPD. They also discuss medications related to the treatment of BPD, and make several recommendations for future studies into the relationship between the BDNF/TrkB signaling pathway and BPD. Chapter 7- Much of the work that documents new parents coping experiences is based upon small sample sizes, thus making it difficult to know the rate at which such experiences occur. This study combined qualitative and quantitative information on this issue.

xii

Alexandra M. Columbus

First time parents (221 mothers; 179 fathers) were surveyed one year after the birth about their experiences of coping. Results showed that 24% of women and 10% of men had experienced at least one episode of difficulty coping for more than 2 weeks. For approximately half of these women and men the onset of these longer duration episodes occurred after six weeks postpartum. All mothers and fathers reported that adjusting to the change in their life had impacted on them. In addition, other frequently reported stressors included: baby-care issues and fatigue (mothers and fathers); household chores; infant illness; financial concerns; lack of support; a lack of confidence; and tension with family members (mothers). For men frequent stressors included work-related stress and concern for his partner. There were few differences in reported stressors between women experiencing longer episodes and short episodes of difficulty coping. These data complement the qualitative studies on the experiences of new mothers and fathers, by quantifying the frequency of perceived stressors. This information can be used to normalise the experiences of new parents when providing them with appropriate services. In addition, the data suggest that just screening for psychosocial difficulties at one time point (e.g., 6 weeks postpartum) will miss a considerable proportion of women or men who may have difficulty coping at a later date. The lack of discernible differences in stressors between women self-reporting difficulty coping for long and short durations lends some support to the questionable usefulness of just focusing on women meeting diagnostic criteria for a mood disorder. Chapter 8- This study compared the efficacy of two commonly used treatment approaches (cognitive–behavioral treatment and contingency management) for the treatment of cocaine dependence among methadone-maintained patients with and without antisocial personality disorder (ASPD). This disorder is strongly associated with substance abuse and recent study findings provide a strong argument against the perception that substance abusers with ASPD are unresponsive to drug treatment. Chapter 9 - In this chapter, the relationship between childhood sexual abuse and borderline personality disorder (BPD) is discussed. An overview of BPD, including the epidemiology is presented, as well as a working definition of the disorder, diagnostic approaches, treatment strategies, and outcome. The difficulties in assessing trauma in clinical populations is also discussed, regardless of the individual’s Axis II diagnosis. Then the literature regarding the role of sexual abuse in BPD is reviewed, which is generally conceptualized as one of several contributory variables to the development of the disorder. This chapter is concluded by integrating childhood sexual abuse into the other known causal factors for BPD. Chapter 10 - Objectives: to estimate the prevalence and risk factors for postpartum depression (PPD), among post-partum women from a private clinic at Osasco, São Paulo. Methods: The authors performed a cross sectional study of 267 women from 8/28/00 to 5/15/03.The instruments used were the Beck Depression Inventory (BDI) and a questionnaire for socio-demographic and obstetric characteristics. Inclusion criteria were: women with no past or present history of depression, psychiatric treatment, alcohol or drug addiction, and whose child was alive. The prevalence of PPD, according to the BDI, and odds ratios for the associations between PPD and exposures variables were estimated. Hypothesis testing was done with x2 tests, or x2 tests for linear trend, when categories were ordered. A p value of < 0.05 was considered statistically significant. Results: the prevalence of PDD was 19.1% (95% IC: 14,3 a 23,8%). In the univariate analysis, only low birth weight was associated with PPD (OR 5.88, IC 95% 1.78-20.0,

Preface

xiii

p<0,001). Conclusions: PPD was highly prevalent among women from this private setting and was associated with new-born low birth weigth.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Short Communication

BODY IMAGE FIGURE PERFORMANCE IN SORORITY WOMEN Rachel Moericke, F. R. Ferraro1 and Jennifer Muehlenkamp University of North Dakota

ABSTRACT Sorority women (n = 91) and non-sorority women (n = 85) participated in an experiment that examined perceptions of body image and body shape. Participants were asked to endorse body silhouettes, which ranged from very thin to very obese, in order to assess their perceptions of several aspects of body image including what they believed to be the ideal body shape for themselves as well as how others should look. The researchers hypothesized that sorority women would endorse smaller silhouettes than non-sorority women and that more years in a sorority would lead to endorsing even smaller silhouettes. The results indicated sorority women endorsed figures that were significantly smaller than figures endorsed by the non-sorority women, and the more years in a sorority was also significantly negatively associated with endorsement of smaller body image silhouettes. These results will be discussed as they relate to contributing factors related to the onset of eating disorders in college women.

Keywords: College Women, Body Image, Body Shape, Sorority

The prevalence of eating disorders often shows higher rates in college women as compared to non-college women and the general population (Alexander, 1988). Due to these prevalence rates, it is especially important to identify subgroups within the college setting that have an even higher risk of developing eating disorders so these groups can be targeted for prevention and intervention. Previous research findings have suggested college women who

2

Rachel Moericke, F. R. Ferraro and Jennifer Muehlenkamp

are members of a sorority may be at an even higher risk for the onset of an eating disorder because they show a drive for thinness, which can consequently lead to body dissatisfaction (Allison and Park, 2004). Schulken et al. (1997) reports that thinness is the ideal among sorority women and these women are also more dissatisfied with their bodies than nonsorority women. Furthermore, Schulken, et al. (1997) found that sorority women exhibit greater fear of becoming fat, are more preoccupied with their weight, more concerned about dieting, and exhibit more body dissatisfaction than college women from previous studies (Brookings and Wilson, 1994; Garner and Olmstead, 1984; Klemchuk, Hutchinson, and Frank, 1990; Kurzman, et al., 1989). In order to determine if sorority women were at a greater risk for developing an eating disorder, Schulken et al. (1997) compared their results from these measures to the results from five previous research studies, which also utilized the same measures on samples from the general college population in four of the studies, (Brookings and Wilson, 1994; Garner and Olmstead, 1984; Klemchuk, Hutchinson, and Frank, 1990; and Raciti and Norcross, 1987) and from a sorority population in the fifth study(Kurzman, et al., 1989). Sorority women sampled in Schulken’s study were significantly higher on drive for thinness and body dissatisfaction than all other comparative study samples and significantly higher on bulimia scores from one of the previous studies. In another study, Alexander (1998) found a trend for sorority women to have higher scores than controls on eating disorders measures including the Eating Attitudes Test (Garner and Garfinkel, 1979), Bulimia Test-Revised (Thelen, Farmer, Wonderlich, and Smith, 1991), and the Bulimia subscale of the Eating Disorders Inventory (Garner, Olmstead, and Polivy, 1983). Unfortunately, in this study the results were not strong enough to be statistically significant. One reason for Alexander’s findings may be explained by Allison and Park’s (2004) study that found no differences in disordered eating attitudes or behaviors between newly pledged sorority members and controls who were not affiliated with a sorority. Allison and Park assessed eating attitudes and behaviors using the Drive for Thinness, Bulimia, and Body Dissatisfaction subscales of the Eating Disorder Inventory-2, self-esteem was assessed using the Rosenberg Self-Esteem Scale, and body mass index was calculated for each woman. In this study, Allison and Park (2004) only found a difference between sorority members and non-sorority college women during a three-year follow-up in which non-sorority members had a decrease in preoccupation with body size as measured by Drive for Thinness while sorority women maintained the initially high score over the same amount of time. This finding may indicate that dieting and weight issues are emphasized more within sororities, possibly causing sorority members to maintain their body preoccupations while non-sorority women decrease their attention to weight issues without the additional exposure. Overall, Allison and Park (2004) contend that before entering a Greek organization, sorority women began college with similar eating attitudes and behaviors, but over 3 years time, preoccupation with weight issues continued whereas, in non sorority women it tended to dissipate. This finding supports the assumption that Greek societies do not select or attract individuals who differ from general college population on these issues, but rather, drive for

1 Address all correspondence to: F. Richard Ferraro, Ph.D.Professor of Psychology, Chester Fritz Distinguished Professor, Director, General/Experimental Ph.D. Program, Dept. Psychology - University of North Dakota, Corwin-Larimore Rm. 215, 319 Harvard Street Stop 8380, Grand Forks, ND 58202-8380, 701-777-2414 (O), 701-777-3454 (FAX), [email protected].

Body Image Figure Performance in Sorority Women

3

thinness and body dissatisfaction may develop after being immersed in the sorority environment for a few years.

THE PRESENT STUDY The present study seeks to investigate how number of years in a sorority corresponds to body image. We hypothesize that college sorority women will endorse smaller figures, relating to body image questions, than non-sorority college women and more years in a sorority will be associated with endorsement of smaller figures in regards to the body image questions.

METHOD Participants A total of 176 college women from a Midwestern university signed up for this study which provided extra credit upon completion to be used in any currently enrolled psychology class of their choosing.

Measures The Background Questionnaire was developed for the purpose of the current study and assessed age, sex, educational history, self-rated health (where 1 = excellent and 5 = poor), height, weight, current medications and number of years in a sorority. The Geriatric Depression Scale-Short Form (GDS-SF; Brink et al, 1982). The GDS-SF is a 15 item scale evaluating symptoms of depression in elderly adults. Items are answered based on a Yes-No scale and scores are obtained by summing the number of positively endorsed statements. Scores of 5 or higher indicate probable depression. The GDS-SF has demonstrated strong psychometric properties in the elderly population (Brink, Yesavage, Lum, Heersema, Aday, and Rose, 1982) and has been shown to correlate positively with Beck Depression Inventory (BDI, Beck) performance in young adults (Ferraro and Chelminski, 1996). The Eating Disorder Inventory – Body Dissatisfaction Subscale (EDI-BDS; Garner, Olmstead, and Polivy, 1983) is a 12 item instrument in which participants rate statements (e.g., I think my stomach is too big) on a 1 = never to 6 – always scale. The EDI has extensive validity and reliability data supporting its use (Garner et al, 1983). The WAIS-R Vocabulary Subtest (WAIS-R; Wechsler, 1981) is an estimate of adult verbal intelligence. Participants are given 35 words one at a time and must provide a short definition of the word provided. Responses to each word are scored on a 0, 1 or 2 basis, with higher scores being indicative of greater verbal intelligence. Scores can range from 0 to 70, with higher scores suggesting higher verbal intelligence. The WAIS-R vocabulary subtest has

4

Rachel Moericke, F. R. Ferraro and Jennifer Muehlenkamp

extensive psychometric data suggesting it is both a valid and reliable indicator of verbal intelligence across age groups (Wechsler, 1981). The Body Shape Questionnaire (BSQ; Copper, Taylor, Cooper, and Fairburn, 1986) is a 34-item questionnaire that asks participants to read a series of questions (e.g., Has feeling bored made you bored about your shape?) related to how they have been feeling about their appearance over the past four weeks. Participants rate each question on a 1 (never) to 6 (always) scale. Scores are obtained by averaging the response values, with higher scores indicating greater body dissatisfaction. They then rate each question on a 1 (never) to 6 (always) scale. The BSQ displays adequate validity and reliability data (Copper et al, 1986). The Body Image Perceptions Scale (BIPS) was developed for the present study. Participants were given 8 statements (e.g., I think my stomach is …) and answered on a -3 (much too small) to 0 (just the right size) to +3 (much too big) scale. Response values are summed to obtain a total score and higher scores indicate greater body dissatisfaction. The State/Trait Anxiety Inventory (STAI; Speilberger, 1983) was used to measure state anxiety and trait anxiety. Participants responded to 40 items (item 1-20 for state anxiety, item 21-40 for trait anxiety) on a 4-point scale, ranging from 1 (not at all) to 4 (very much so). The STAI demonstrates strong psychometric properties (Speilberger, 1983). The line drawings from Rand and Wright (2000) were used to assess perceived body size and dissatisfaction. The line drawings range from male and female babies to children to young adults to middle-aged adults to old age adults (Collins, 1991; Sorenson, Strunkard, Teasdale, and Higgins, 1983). Participants rated all line drawings for all age groups on a 1 (very thin) to 9 (very obese) scale in response to a series of seven questions. These questions included a) What figure(s) corresponds to the ideal body size (most attractive), b) Which figure(s) are socially acceptable (which look OK), c) Which figure(s) are acceptable, d) Which figure(s) do you like best, e) For your age group, which figure(s) best represents your current body size, f) For your age group, which figure(s) do you feel mean and women should be, g) For your age group, which figure(s) would you like to be. Reliability of these figures within a middle-age group was strong, estimated at an alpha of .92 (Rand and Wright, 2000).

Procedure Participants signed up for this study at the psychology experimental research posting site and chose a listed time and date in which to complete the study. The location and contact information, as well as a copy of the informed consent and information about the study was available for potential participants to look through before volunteering for this study. Upon arriving at the research lab, all participants were provided with written and verbal informed consent. Participants were then asked to complete a packet of questionnaires assessing demographic data, body image/shape variables, and mood symptoms. Participants were assured that no identifying information would be attached to these questionnaires and were instructed to proceed at their own pace. It took participants approximately 30 minutes to complete the study. After completing the questionnaires, participants were thanked for their time and given extra credit to be used towards their psychology class. All procedures were approved by the IRB affiliated with the authors’ institution.

Body Image Figure Performance in Sorority Women

5

RESULTS In comparison to sorority women, non-sorority women were older, had more education, rated their health as being better, and had a higher BMI (see Table 1). Table 1. Mean, Standard Deviation, and Range performance as a function of group Sorority

Non-Sorority

(n=91)

(n=85)

Variable

Mean (SD) Range

Mean (SD) Range

Age

20.15 (1.25) 18-24

22.04 (5.09) 18-52

11.68 (***)

Education

14.24 (1.01) 13-16

14.74 (1.10) 13-18

9.78 (**)

Health

2.23 (.86) 1-5

2.49 (.78) 1-4

2.89 (*)

Meds

.65 (.81) 0-3

.66 (.95) 0-5

.01 (ns)

BMI

22.32 (2.44) 17.6-30.3

23.67 (4.73) 17.5-2.8

5.72 (*)

GDS-SF

1.12 (2.06) 0-13

.79 (2.61) 0-14

.79 (ns)

EDI-BDS

3.22 (1.11) 1.83-4.08

3.36 (1.32) 1.83-38.3

1.81 (ns)

WAIS-R V

47.44 (8.61) 26-64

46.18 (8.67) 29-66

.94 (ns)

BSQ

2.76 (.86) 1.03-5.09

2.64 (.88) 1.18-5.82

.36 (ns)

BIPS

.68 (.59) -1.00-2.5

.79 (.61) -.75-3.0

1.61 (ns)

State Anx.

32.41 (10.8) 20-70

32.11 (10.11) 20-66

.04 (ns)

Trait Anx.

35.37 (10.41) 21-76

35.25 (11.04) 20-71

.01 (ns)

LDQ1

3.21 (.91) 1-5

3.34 (.85) 1-5

.91 (ns)

LDQ2

3.30 (.78) 1-5.5

3.54 (.78) 2.5-6

4.02 (*)

LDQ3 LDQ4

3.88 (.88) 2-6 3.32 (.87) 1-5

4.00 (.94) 2.5-9 3.58 (.82) 2-6

.71 (ns) 3.88 (*)

LDQ5

4.37 (.88) 2-7

4.69 (1.04) 2-9

5.01 (*)

LDQ6

3.74 (.85) 1-5.5

4.01 (.77) 2-6

4.63 (*)

LDQ7

3.19 (.92) 1-5

3.55 (.79) 2-6

7.71 (**)

F (1, 174)

Note: BMI indicates Body Mass Index; GDS-SF indicates Geriatric Depression Scale-Short Form; EDIBDS indicates Eating Disorder Inventory- Body Dissatisfaction Subscale; WAIS-R V indicates Wechsler Adult Intelligence Scale-Revised Vocabulary; BSQ indicates Body Shape Questionnaire; BIPS indicates Body Image Perception Scale; LDQ indicates line drawing silhouette question, * p < .05, ** p< .01, *** p < .001.

6

Rachel Moericke, F. R. Ferraro and Jennifer Muehlenkamp

Sorority women did not differ from non-sorority women on medications currently being taken, GDS-SF, EDI-BDS, WAIS-R vocabulary, BSQ, BIPS, or State and Trait anxiety. However, significant differences were found between the two groups on the figure rating scale. A series of one-way ANCOVAs were conducted with the significant demographic variables serving as covariates for each of the seven figure questions. As can be seen in Table 1, significant differences were found between groups on five of the seven questions. The sorority group endorsed a significantly thinner figures than the non-sorority group on the following items: (a) Which figure is socially acceptable? (b) Which figure do you like best? (c) Which figure represents your current body size? (d) Which figure do you feel men and women should be? (e) Which figure would you like to be? A series of correlation coefficients were calculated to examine the association between number of years in a sorority and body image-related variables. It was observed that the more years in a sorority was significantly negatively associated with lower Body Mass Index (BMI, r = -.17, p < .03) and better self-rated health (r = -.21, p < .01). Likewise, more years in a sorority were related to endorsement of a smaller body image figure when describing a) which figure best represented participants’ current body size, r = -.15, p < .05; b) which figure participants felt men and women should be, r = -.18, p < .02; and c) which figure participants would like to be, r = -.19, p < .02.

DISCUSSION The results supported the hypotheses that women in a sorority would endorse smaller body figures and that years in the sorority would be associated with endorsement of smaller body figures. The implications of the present study are that sorority women do indeed endorse smaller body images and this endorsement seems to be related to the number of years a member is in the sorority. It appears that college women in sororities may potentially be at a greater risk for developing an eating disorder because they may be placing more emphasis on appearance within their social group, therefore creating an atmosphere in which drive for thinness is exacerbated and exceeds the demands experienced by non-sorority college women. However, further research is needed to investigate the reasons why sorority members endorse smaller silhouettes as a function of years of sorority membership. The limitations of the present study are that it only indicates that sorority members endorse smaller figures compared to non-sorority women and newly pledged sorority members. Although our findings are in line with previous research, we are still unable to discern why sorority women are more likely to embrace thinness. One possible explanation may be that socialization of women living within a sorority reinforces the larger societal emphasis on thinness. Being exposed to body concerns or others who may emphasize thinness could potentially lead to a collective mentality that supports a drive for thinness. Future research that is longitudinal in nature is needed to evaluate this possibility. Another limitation of the present study is that sorority membership was not broken up and examined as different groups in addition to number of years of membership. It may be that different sororities place different levels of importance on thinness and if perhaps there was unequal representation from the different sororities a majority of one sorority that supported or negated a drive for thinness could have potentially skewed the results in either

Body Image Figure Performance in Sorority Women

7

direction. Although uncertain at this time, it may be true that supporting a thinner ideal will easily allow women who fall short of the ideal to become more dissatisfied with their bodies. Furthermore, since greater body dissatisfaction has been linked to the development of eating disorders one might assume, it would be beneficial to investigate this topic area further as a means to develop and implement prevention plans and/or educational interventions aimed directly at college women, especially those involved in a sorority. In summary, our results add to the growing literature that suggests living within a sorority may have a negative impact on college women’s body image. Although the women within the current study did not differ on measures specific to body dissatisfaction, sorority women were significantly more likely to endorse thinner body figures are being acceptable and desirable. Our findings also continue to confirm that sorority women are susceptible to social influences towards a drive for thinness that may be associated with eating disorder risk since longer time in the sorority was associated with endorsement of smaller body figures. Additional research is needed to tease apart the mechanisms contributing to the development of skewed body images among sorority women so appropriate prevention strategies can be designed.

REFERENCES Alexander, L. (1998). The prevalence of eating disorders and eating disordered behaviors in sororities. College Student Journal, 32, 66-76. Allison, K. and Park, C. (2004). A prospective study of disordered eating among sorority and nonsorority women. International Journal of Eating Disorders, 35, 354-358. Brink, T. L., Yesavage, J., Lum, O., Heersema, P. H., Aday, M., and Rose, T. S. (1982). Screening tests for geriatric depression. Clinical Gerontologist, 1, 37-43. Brookings, J., and Wilson, J. (1994). Personality and family environment predictors of selfreported eating attitudes and behaviors. Journal of Personality Assessment, 63, 313-326. Collins, M. E. (1991). Body figure perceptions and preferences among adolescent children. International Journal of Eating Disorders, 10, 199-208. Cooper, P. J., Taylor, M. J., Cooper, Z. and Fairburn, C.G. (1986) The development and validation of the Body Shape Questionnaire. International Journal of Eating Disorders 6, 485-494. Ferraro, F. R., and Chelminski, I. (1996). Application of the Geriatric Depression Scale-Short Form (GDS-SF) to younger adults. Journal of Clinical Psychology, 52, 443-447. Garner, D. M., and Olmsted M. P. (1984). Eating Disorder Inventory (EDI) Manual. Florida: Psychological Assessment Resources. Garner, D. M., Olmstead, M. P., and Polivy, J. (1983). Development and validation of a multidimensional eating disorder inventory for anorexia nervosa and bulimia. International Journal of Eating Disorders, 2, 15-34. Garner, D. M., and Garfinkel, P. E. (1979). The eating attitudes test: An index of the symptoms of anorexia nervosa. Psychological Medicine, 9, 1-7. Klemchuk, H., Hutchinson, C., and Frank, R. (1990). Body dissatisfaction and eating-related problems on the college campus: Usefulness of the eating disorder inventory with a nonclinical population. Journal of Counseling Psychology, 37, 297-305.

8

Rachel Moericke, F. R. Ferraro and Jennifer Muehlenkamp

Kurzman, F., Yager, J., Landsverk, J., Wiesmeier, E., and Bodurka, D. (1989). Eating Disorders among selected female student populations at UCLA. Journal of American Dietary Association, 89, 45-53. Raciti, M., and Norcross, J. (1987). The EAT and EDI: Screening, interrelationships, and psychometrics. International Journal of Eating Disorders, 6, 579-586. Rand, C. S. W., and Wright, B. (2000). Continuity and change in the evaluation of Ideal and acceptable body sizes across a wide age span. International Journal of Eating Disorders, 28, 90-100. Schulken, E., Pinciaro, P., Sawyer, R., Jensen, J., and Huban, M. (1997). Sorority women’s body size perceptions and their weight-related attitudes and behaviors. Journal of American College Health, 46, 69-75. Thelen, M. H., Farmer, J., Wonderlich, S., and Smith, M. (1991). A revision of the bulimia test: The BULIT-R. Psychological Assessment, 3, 119-124. Wechsler, D. (1981). Wechsler Adults Intelligence Scale – Revised. NY: The Psychological Corp.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 1

THE DEVELOPMENT OF EPISTEMIC COMPLEXITY IN ADULTHOOD: PERSONAL CONCEPTUALIZATIONS OF SELF AND CULTURE Gabriel Bukobza1 School of Education, Tel Aviv University, Israel

ABSTRACT This study examined how adult individuals construe knowledge. Eighty participants, aged 17-70 were interviewed regarding their personal knowledge of self and culture. Content analysis of the interviews revealed four fundamental structures of knowledge, or epistemes, which differed in level of complexity and consistently appeared in both domains. The four epistemes are, in ascending level of complexity: MonolithicMonoformal, Relativist-Relational, Dialectical-Deconstructive, and Integral-Inclusive. The implications of the findings to the areas of development, self, culture, post-formal cognition, and wisdom are discussed.

Keywords: epistemology, complexity, adult development, post formal, self conceptualization, cultural conceptualization, monolithic monoformal, relativistic relational, dialectical deconstructive, integral inclusive, spiral development.

The things people know and the ways by which they obtain and organize this knowledge change throughout life. Different developmental periods generate epistemological principles whose purpose it is to perceive, organize, and interpret information and experience (Inhelder and Piaget, 1958). Thus, in infancy the world is discovered primarily through movements and sensations of the body; later on in life, individuals rely more heavily on words and symbols to explore and understand reality (Piaget, 1952/1936). This article refers to the set of epistemological principles an individual uses to know the world as an episteme, and this episteme will be the focus of the following investigation. 1 Mailing address: 17 Borochov St., # 4, Ra'anana 43434 Israel, [email protected], T: 972-97483686.

10

Gabriel Bukobza

Epistemes were studied in the past – under different names – from philosophical, scientific, cultural, linguistic and psychological standpoints. Foucault used the term in his analysis of scientific and cultural discourse. He argued that the episteme represents the set of relations that define the conception of knowledge during a particular historical period. According to his view an episteme may be conceived of as something like a world-view which consists of a preconditioned system of regulations that unite at a given moment the discursive practices that generate scientific and cultural knowledge (Foucault, 1970/1966; 1972/1969). Pepper (1942) examined various systems of philosophy and science that form the basis for corroborated knowledge statements. He categorized them into four fundamental groups or "world hypotheses": Formalism, Mechanism, Contextualism, and Organisicm, and argued that each functions as an independent epistemological framework that organizes information about the world in a coherent, consistent and unique manner. Subsequently, knowledge derived by a particular world hypothesis is markedly distinct from that derived by a different hypothesis. In psychology, it was the seminal work of Piaget (1952/1936; 1954/1937), which empirically assessed epistemological frameworks in the individual knower. Piaget (1970) was a developmental structuralist, who believed that scientific knowledge is the most refined and valid form of human knowing. Accordingly, his empirical efforts focused on the development in individuals of an episteme that generates scientific reasoning. Researchers following Piaget often chose to focus on other epistemic facets of the individual knower. They examined several related topics including the ways by which people order knowledge (Belenky, Clinchy, Goldberger, and Tarule, 1986; Commons and Richards, 2002; Kegan, 1982; Miller, 1994; Perry, 1970), the interaction between epistemic beliefs and identity (Fowler, 1981; Moshman, 1999), principles that determine the formation and reformation of beliefs (Kruglansky, 1989), and methods used by individuals to construct reasoned arguments (Kuhn, 1991), or solve sophisticated problems (King and Kitchener, 1994). Epistemic patterns and principles were further related to psychological phenomena such as moral reasoning (Nisan, 1995; Nisan and Applebaum, 1995), ego identity (Cook-Greuter, 1999; Loevinger, 1976), scholastic achievements (Schommer, 1990; 1993; 1994), and issues in the theory of mind (Burr and Hofer, 2002). Based on this line of previous work the present study postulates that an episteme consists of systematic operations, regulations, and methods which aim it is to perceive, process, order, and present knowledge in an intelligible way. The episteme shares some of its general qualities with other knowledge systems (Kuhn, 1970; Pepper, 1942). In particular, the episteme has an internal logical coherence; it interprets information and thus offers an explanation for occurrences in the world and a meaning to personal experience; it has implications for attitudes and behavior in daily life; and it varies in degrees of complexity.

The Development of Epistemic Complexity in Adulthood

11

DEVELOPMENT OF THE EPISTEMES IN ADULTHOOD, AND THE QUESTION OF COMPLEXITY Piaget’s theory postulated that as life unfolds cognitive maturation and environmental support contribute to the construction of a formal-symbolic epistemological system which is reliable, functional, and adaptive (Flavell, 1963; Moshman, 1999). It further argued that the ability to think abstractly and use logic and deduction – which matures in late adolescence – mark the peak and endpoint of mental development. Presumably, further changes in these skills are possible throughout the course of life, but the basic structural cognitive apparatuses of the mind remain constant from late adolescence onwards. When change does occur in late adulthood, it is usually the result of cognitive decline rather than a sign of new growth (Denney, 1982). Many others contended, however, that meaningful transformations in ways of knowing could potentially occur in post-adolescent years, beyond or alongside formal operations (Cavanaugh, Kramer, Sinnott, Camp, and Markley, 1985; Chandler and Boutilier, 1992; Edelstein and Noam, 1982; Kegan, 1982; 1994; King and Kitchener, 1994; Kitchener and King, 1981; Labouvie-Vief, 1982; 1992; Mansfield and Clinchy, 2002; Perry, 1970; 1981; Richards and Commons, 1984; Riegel, 1973; 1975; Sinnott, 1981; 1998). Perry (1970), for example, was one of the first to suggest that mature adult reasoning involves awareness and use of relativism, doubt and change, combined with the ability to commit to chosen alternatives. Several other theorists have described a dialectical stage of cognitive development that substitutes formal operations with a contextual, contradictory, and changing system of knowing (Basseches, 1980; 1984; Broughton, 1975; Kramer, 1983; Riegel, 1973). This array of studies suggested that the mind has the potential to develop highly complex cognitive networks, which cannot be explained with reference to formal thinking alone. The degree of epistemic complexity in these studies was determined by how well defined and inter-connected the relations between basic epistemic principles in the network were. Complexity was assumed to increase with the number of factors and interactions that contributed to the process of interpreting information. Changes in the epistemic framework were considered to be of a developmental nature if and only if they transformed a working system of organizing knowledge into a sub-system or a component in a more complex system (Edelstein and Noam, 1982; Souvaine, Lahey, and Kegan, 1990). This conceptualization produced a hierarchy of systems of knowing wherein each advanced system enveloped a previous mature system and added to it a new level of explanation and meaning. Thus, in Perry's (1970) model relativism was considered a more advanced position than dualism and in Riegel's (1973) model dialectical thought was assumed to be more progressed than formal operations.

LIMITATIONS OF PREVIOUS MODELS AND AIMS OF THE PRESENT STUDY The psycho-epistemological literature consists of different models that portray the trajectory of post-formal epistemic growth during adulthood. However, although the numbers

12

Gabriel Bukobza

and names of stages or levels they present vary, it is possible to identify basic recurring patterns in the developmental changes they depict (Burr and Hofer, 2002; Moshman, 1999). The starting point for most models is an objectivist and absolutist episteme, which evaluates knowledge as either true and right or false and wrong. True knowledge is considered irrefutable, certain, and eternally stable and the individual is strongly committed to it. Any other form of knowledge is considered completely false and is discarded. At a more progressive level a subjectivist and relativistic episteme is a dynamic and versatile system for organizing knowledge, which forms a clear relation between elements of knowledge and the subjective perspective of the individual holding them. Furthermore, such a system acknowledges the legitimacy of different perspectives in the world and conceives of truth as uncertain, open to refutation, and constantly changing. The final episteme presented in these models is meta-subjective and evaluative. This is a system that draws from both objective and subjective worldviews, and forms a reflective construction. It proposes no claim for absolute truth, and instead advocates a systematic process of evaluation and justification of knowledge statements. On the basis of this review it is possible to outline certain limitations in past research and theory. First, similar to Piaget’s these models consider rational-scientific knowledge to be the ultimate form of human knowing. The developmental trajectories they outline depict a calculated, reasoned, and individuated knower, who fundamentally uses logical operations in order to construe meaning. As a result, the appropriateness of these models to the understanding of non-scientific knowledge systems is found lacking. So, for example, the way knowledge is processed and constructed in a system based on non-linear thinking, faith, or intuition is not accounted for. Religious, mystical, meditative, embodied, aesthetic, musical, a-logical, paradoxical, dialogical, relational, collectivistic, and alternative states of consciousness and thinking are neglected. Though these types of knowledge have been articulated in philosophical (Adorno, 1990/1966; Marcuse, 1954; Gebser, 1985/1949), theological (Rosenzweig, 1985/1921; Tillich, 1951), artistic (Storr, 1972), as well as psychological writings (Broughton and Freeman-Moir, 1982; Kohlberg and Ryncarz, 1990; Lomranz, 1998; Wilber, 2000), they do not permeate these models. This is a cardinal point since these types of knowing represent highly complex epistemological levels which have yielded some of the most profound creations of the human mind. A second point is that psycho-epistemological studies that did focus on other orders of knowing need further corroboration. For instance, Basseches’ (1984) original work on dialectical thought did not separate empirically between relativistic and dialectical mental operations. Koplowitz’s (1984; 1990) unitary stage of thought was not examined in different contextual settings. In a similar way, Fowler (1981) wrote of an epistemic level of universalizing faith but could not find evidence for its existence in the interviews he conducted. Finally, most models of epistemic growth are based on a sequential developmental structure with a clear beginning and termination (Commons and Richards, 2002; Fischer, 1980; Fowler, 1981; Inhelder and Piaget, 1958; King and Kitchener, 1994; Perry, 1970). They tend to gradually advance in a systematic and linear manner along the hierarchical trajectory until reaching a final point where development halts. Though the caveats associated with a linear-hierarchical view of development have been examined in the past (Fischer and Bidell, 1998; Vygotsky, 1978), empirical non-linear models of epistemological growth are scarce.

The Development of Epistemic Complexity in Adulthood

13

In summary, previous models did not properly define or differentiate between advanced levels of epistemic development. In addition, they were sometimes limited in terms of the empirical tests they conducted. The present study aims to address some of these issues. The following three empirical questions are posed to meet this purpose: (1) What are the epistemes adults use in order to cognize and order knowledge? (2) Are the epistemes domain specific? (3) How do the epistemes relate to age, level of education, and gender?

EMPIRICAL EXAMINATION OF THE EPISTEMES Previous psycho-epistemological research used different settings to learn about individuals’ patterns of knowing. Epistemic probing appeared in the form of scientific assignments (Inhelder and Piaget, 1958), moral dilemmas (Gilligan, 1982; Kohlberg, Levine, and Hewer, 1984), learning experiences (Baxter-Magolda, 1999; Perry, 1970), religious beliefs (Fowler, 1981), perceptual skills (Peng and Nisbett, 1999), and direct questioning (Basseches, 1976; Broughton, 1975; King and Kitchener, 1994; Miller, 1994; Schommer, 1990). Interviews using hypothetical or abstract questions often showed that participants experienced difficulties in reasoning that were related not to low cognitive ability, but to their encounter with unfamiliar material that was irrelevant to their lives (Chandler, Boyes, and Ball, 1990). A concrete and clear stimulus that is taken from the person’s inventory of life experiences was therefore recommended instead. In accordance with this conclusion the present investigation addressed two real-life domains, namely participants’ personal conceptualizations of self and culture. Apart from being a relatively familiar topic to discuss, another advantage of working with such concepts is their similarity to ill-structured questions (King and Kitchener, 1994) that can be understood and presented from various perspectives. Unlike well-structured questions, ill-structured ones presuppose the use of a logic that makes it possible to insert them into a concrete, contextual reality, and that facilitates an awareness of the fluid and even contradictory nature of this same reality (Kramer, 1990). This allows for a high degree of flexibility in the interview process and gives the interviewee room for expression.

SELF-CONCEPTUALIZATION Self-conceptualization (SC) is a personal epistemological scheme (Brim, 1976; Bukobza, 2007), or a theory regarding the self (Epstein, 1973). It contains traits, values, images and memories about the self, as well as emotions and evaluations. SC controls the elaboration, interpretation, and ordering of information and activity relevant to the self, and provides incentives, standards, plans, rules, and scripts for personal and social behavior (Campbell, Trapnell, Heine, Katz, Lavallee, and Lehman, 1996; Damon and Hart, 1982; Epstein, 1973; Markus and Wurf, 1987; see also Baumeister, 1998; Levin, 1992; Linville and Carlston, 1994; Yardley and Honess, 1987).

14

Gabriel Bukobza

There is a vast and highly heterogeneous literature dealing with the characteristics of self and self-conceptualizations. One group of researchers presented evidence showing that the knowledge components of SC are plural, versatile (Gergen, 1991; Greenwald and Pratkanis, 1984; Harter and Monsour, 1992; Higgins, 1987; Sande Goethals, and Radloff, 1988), and inconsistent (Ewing, 1990; Hampson, 1997; 1998; Harter and Monsour, 1992; Lifton, 1993; Neisser, 1988). This group generally claimed that the structure of the SC is dynamic (Markus and Wurf, 1987), consists of several distinct principles (Hermans, 1996; Linville, 1987), which co-exist at different levels of integration and differentiation (Donahue, Robins, Roberts, and John, 1993), and different levels of clarity and coherence (Campbell, et al., 1996). Another group of researchers reached different findings that can be summarized by Baumeister’s (1998) succinct remark that the need for consistency is a powerful motivating force in self construction and presentation. This line of research suggested that SC is characterized by a high degree of stability and congruence across different contexts (Funder, 1983; Schroeder, 1983; Sheldon, Ryan, Rawsthorne, and Ilardi., 1997). In yet another line of research the development of SC along the life cycle was analyzed. Damon and Hart (1982) wrote in their comprehensive study that SCs go through significant changes in the years between infancy and adolescence. The main transformation in this period is from a bodily-focused SC to a psychological one which includes personality traits, selfreflection, and an inclination to conceptual integration of distinct facets into one unitary system. Harter and Monsour (1992) found that around the time of mid-adolescence there is a gradual increase in the differentiation of the self which elicits experiences of conflict resulting from collisions between contradicting traits. However, in accordance with Damon and Hart’s (1982) research they additionally found that towards the end of adolescence the conflict is resolved as a result of cognitive maturation allowing for reconciliation between opposing sides of the SC.

CULTURAL-CONCEPTUALIZATION Cultural-conceptualization (CC) is a personal worldview (Jensen, 1997) or a theory of knowledge about an individual’s culture and cultural identity (Phinney, 1989). It is the part in the epistemological matrix stemming from the relation between an individual and a cultural group, including the emotional significance that is attributed to this relation (Phinney, 1990) and the commitment that comes with it (LaFromboise, Coleman, and Gerton, 1993). CC includes collective meanings, values, norms, ethics, laws, ideas, thoughts, and behaviors (Geertz, 1984; Harris, 1999) which assist the person in understanding social reality and lay guidelines for action in it. In other words, they provide a model of reality together with instructions about how to behave in that reality (Kuper, 1999). In a multi-cultural environment, or whilst moving between cultures, individuals confront cultural worldviews that differ from those they grew up with in their original habitat. The direct and longstanding contact with foreign systems that generates an adaptive change in thought and behavior is known as acculturation (Berry, 1988; Moghaddam, Taylor, and Lalonde, 1987; Sayegh, and Lasry, 1993). The complex process of acculturation affects the individual’s CC; it may strengthen the original CC a person had or alternatively reshape and

The Development of Epistemic Complexity in Adulthood

15

transform it as happens in assimilation, alternation, multiculturalism and integration (Berry, 1988; Berry, Trimble, and Olmedo., 1986; LaFromboise et al., 1993; Moghaddam et al., 1987; Sayegh and Lasry, 1993; Wurzel, 1988). CCs are often studied through the ethnic prism – by looking at people’s self-definitions, emotions and motivations in regard to their affiliation with a certain ethnic group (Dien, 2000; Phinney, 1989, 1990, 2000; Phinney and Chavira, 1992; Tzuriel and Klein, 1977; Zak, 1976). These studies show that cultural-ethnic identity develops through a process that begins with low interest and involvement and proceeds to a phase of search and examination, and finally to a commitment to one stabilized identity. Conscious commitment to a cultural identity gives the individual a feeling of purpose and fulfillment (Dien, 2000; Phinney, 1990), enhances self-esteem (Phinney and Chavira, 1992), and may help to protect from mental stress (Berry, 1988).

METHOD Participants Eighty participants were drawn from four different age groups representing the span of adult life. Each group consisted of 20 individuals, and was evenly divided by gender. The range and means of the age groups were 17-22 years (M age = 19 yrs, 11 months), 26-32 years (M age = 28 yrs, 7 months), 37-47 years (M age = 40 yrs, 4 months) and 56-70 years (M age = 59 yrs, 10 months). The first two age groups represented the years of emergent adulthood where one's identity is in its formative stages (Arnett, 2000; Erikson, 1968). The next two groups sampled individuals at mid-life and in the mature adulthood ages, to cover as large a part as possible of the adult years. In addition participants' educational background was recorded resulting in 3 groups of education level (high-school, undergraduate degree, graduate degree). Previous research has shown that a positive correlation exists between age, education, and epistemological level (King and Kitchener, 1994). The participants were recruited from different contexts, professions, and walks of life, in order to increase the heterogeneity of the sample.

The Interview and its Coding Participants discussed their SC and CC in a semi-structured quasi-clinical interview. This is an indirect method of investigation that focuses on a specific overt topic, while aiming to uncover underlying mental principles (Inhelder and Piaget, 1958; Kegan, 1982; Kitchener et al., 1989; Kohlberg, Levine, and Hewer, 1984; Perry, 1970). In this method the interviewer asks questions about a certain knowledge domain, in order to understand how this domain is constructed in the mind of the person. Following a stimulus in the form of self-report in the SC section, and cultural dilemmas in the CC section, participants were asked to reason about their personal conceptualizations in each of the two domains. The interview consisted of a battery of questions on which the

16

Gabriel Bukobza

interviewer was free to improvise according to the nature of the interview. Interviews were recorded and fully transcribed. The interviews were content analyzed based on seven epistemological principles which were derived from basic queries about the state of knowledge statements and units of meaning. These included questions such as: Is the knowledge system about self or culture clear and consistent? How does knowledge in the system of self or culture get verified and corroborated? What is the reaction to foreign or refuting information? Some of these questions appeared previously in various forms in psycho-epistemological research (Chandler, Lalonde and Sokol, 2000; King and Kitchener, 1994; Pepper, 1942; Perry, 1970; Piaget, 1970; Ross, 1989). They all strive to uncover the implicit ways in which knowledge is constructed and organized (Kelley, 1955; Medin, 1989). This is a traditional method in psycho-epistemological research (Belenkey, et al., 1986; King and Kitchener, 1994; Kohlberg, et al.,1984; Koplowitz, 1984; 1990; Perry, 1970), in which interview content is sorted into categorical ”pigeonholes” – basic predefined concepts of interpretation (Holsti, 1969). The resulting seven principles were: Consistency – Inconsistency, Fixedness – Dynamics, Form preservability – Transformation, Singularity – Plurality, Context independent – Context dependent, Other independent – Other dependent, Epistemic apparatuses. A thorough discussion of each principle appears elsewhere (Bukobza, 2007). All interviews were carried out, analyzed and scored by the author. In addition, two assistants were trained to use the coding system and they scored half of the interviews. The SC and CC sections were separated for each interview before coding began, in order to yield independent scores for each domain. Coders were blind to age, educational level or gender of the participants, as well as to their score on the corresponding part of the interview. Inter-rater reliability between the three coders had an alpha value of 0.72 (p < 0.005). The epistemic score for each category depended on participants’ reasoning when explaining the epistemological principle at stake. An elaborate example of this process appears in the Results section. The final score for the whole interview was based on the aggregate scores given for all categories, and on the rater’s comprehensive evaluation. Because participants did not always exhibit an ideal and whole epistemic stance, a grid system was used (Kegan, 1982). Coders could score an interview as representing a complete episteme, or a transitional one. The transitional epistemes divided into two groups. In the first, a dominant epistemic orientation was identified together with weak but significant expressions of another episteme. The second group consisted of cases with mixed orientations where it was impossible to decide on the dominant-subordinate relations. For the purpose of statistical analysis the results of the content analysis were transformed into numeric figures using an existing scale (Perry et al., 1986).

RESULTS The Different Epistemes Content analysis of the interviews yielded four distinct and independent epistemes that underlie the conceptualizations of both self and culture. These were named MonolithicMonoformal (MM), Relativist-Relational (RR), Dialectic-Deconstructive (DD), and Integral-

The Development of Epistemic Complexity in Adulthood

17

Inclusive (II). In what follows the four epistemes will be illustrated in detail. using two of the seven epistemic principles in order to exemplify the method of analysis and to outline differences in complexity between the epistemes. The first principle, Consistency vs. Inconsistency, will be presented in the SC context, and the second, Other-independent vs. Other-dependent, will be presented in the CC context. In each of the following excerpts the participant is presented by means of a pseudonym and her or his age, gender, and educational level.

Consistency vs. Inconsistency in the SC Context Monolithic-Monoformal Episteme Yafit, a 54 year- old woman, has a Bachelor’s degree. Q: You say that there are no contradictions in your self-portfolio. Could you explain? A: I’m not pessimistic, but I’m not optimistic either. It’s not that I have both traits, but I’m standing somewhere in the middle. I don’t have these contradictions. I don’t think that I have contradictory traits that make me behave like this one time and next like that. When I say that I’m stable that’s exactly what I mean: stability is stability. Q: You put down that you are cheerful, warm, and friendly. Don’t you have opposite traits too? A: No. Q: And what if the situation you’re in changes? Will you still be warm and friendly? A: Yes. This will never change.

Yafit reported an SC that included the following 12 traits: Friendly, cheerful, warm, direct, flexible, patient, serious, self-controlled, stable, realistic, planned, introvert. Her selfprofile did not include any antinomies; she exhibited an understanding for contradictions, but chose to describe herself in a congruous way. Yafit mentioned that for her “stability is stability”. This is an interesting statement as it is a reflection of the law of identity in Aristotle’s formal logic: ”A is A”. According to that law every object in reality is perfectly identical to its image and cannot be any different without consequently refuting itself. Yafit’s words followed that logic in two ways: First through their syntactic structure, and second through their content, since she proclaimed her internal stability and hence declared the unchanging nature of her consistent knowledge system about the self. In the final part of this excerpt the interviewer tried to establish the level of internal coherence in Yafit’s SC. She was presented with two challenging questions that could potentially disrupt the law of identity to which her SC adheres. In the first question Yafit was asked if she had any qualities that were opposite to the ones she described. In the second question she was asked whether she would still have a consistent portfolio if situational conditions changed. Yafit responded to both questions in the negative, and hence showed that her SC indeed did not have any opposing traits and that her consistency was independent of environmental factors.

18

Gabriel Bukobza

This excerpt was coded as an example of high internal consistency and coherence. Yafit’s SC was devoid of polarity, negation and oppositions, and this did not alter even in the face of questions potentially undermining this stable SC.

Relativist-Relational Episteme Galya, a 28 year-old woman with a Bachelor’s degree. Q: You’ve outlined some contradictory traits in your description. Can you explain to me how it is that you have these contradictions inside you? A: I believe that different situations bring out different things in you. I can behave in a particular way when I’m with certain people and in a certain place, and then in other circumstances I might behave differently. I’m not some unified whole of a person that will always react the same. Often my behavior is influenced by external situations that are beyond my control. I can find myself traveling in India and there my behavior will be completely different. When you travel you find yourself in foreign places that have ways unfamiliar to you, especially if you come from the Western world. And then in those places you are something else. You react differently. You externalize unfamiliar aspects of yourself. And this also works for how I am in a relationship with my partner, or how I am when I’m at work.

Galyas’s overall SC had 34 traits, which included 10 antinomies. She divided the latter into the following pairs: stable-unstable, individualistic-social, considerate-demanding, light hearted – anxious, confident-indecisive. Galya acknowledged that her SC had inconsistent traits and attributed them to the influence of varying situational circumstances. She explained that she wasn’t a “unified whole” that always reacted in the same manner, but was susceptible to the influence of outside factors. Her self was presented as a complex structure encompassing a wide range of traits, which manifested themselves according to changes in her environment. Galya said, “you are something else”, words which are of great significance since their logical implication is that the self can have more than one interpretation and meaning. The statement "you = something else" clashes with the basic logical law of identity: ”A” is no longer always and under any circumstances identical with ”A”, as ”A” may now be something else, like ”B” for example. Whereas the MM episteme is consistent according to the law of identity, the RR episteme is internally inconsistent and consciously divided into potentially contradictory parts. Galya had as many self-aspects as the number of situations she encountered; these included different locations in the world, social environments, and human relationships. The plurality of Galya’s self was represented by a diversified and inconsistent episteme that is made from separate and distinct parts. This is an instance of the RR episteme, and the excerpt was coded accordingly.

Dialectical-Deconstructive Episteme Gideon, a 28 year- old man, has a Masters’s degree . Q: You described yourself as embodying contradictions. How do they relate to one another? A: Well, all these terms that we use are laden with so much meaning, and who knows if both of us share the same idea about what they really mean. Let’s see. I’m serious in the social

The Development of Epistemic Complexity in Adulthood

19

sphere where I go by the rules of society, etc., and then there are situations where I find myself laughing, acting crazy, and going wild. But here it is: In these moments of acting ridiculous, I feel that to a certain extent I’m actually extremely serious. I might be frivolous or act foolishly but there’ll be a feeling of profound seriousness too. What I’m saying is that in what looks like a very serious moment there is also something that is routine, carefree, and extremely unserious. And the other way around – in those situations where I break away from the serious circle there is still a very serious element at work.

Gideon attributed 19 traits to himself, 11 of which were contradictory. He lined these up in the following manner: Individualistic-social, serious-daring-frivolous-sudden-unstable, cynic-stormy-cheerful-optimistic. In reasoning about the contradictory traits Gideon first said that different contexts make him behave in different ways. This is a RR justification, which asserts that behavior is relative to relevant circumstances. But as he carried on Gideon exposed another level of meaning in his episteme. He described the reciprocal relations among his opposing traits: they are interrelated, yet they also inter-penetrate and affect each other. Each trait is affected and to a certain extent constituted by other traits. Furthermore, a trait that usually appears in one context may abandon this location and immigrate to another, where it interacts with a different trait – an interaction that influences both traits. For instance, the meaning of ”frivolous” is not hermetic and strictly limited to its role as opposite of ”seriousness”, and vice versa –at the very core of the ”frivolous” trait antithetical elements to its own meaning exist. This is a specific dialectical relation I would like to term connected contradiction, in which oppositions are consciously juxtaposed against one another resulting in an epistemic tension that cannot be reconciled by straightforward Aristotelian logic. In such a nonconventional case every element of knowledge is defined and experienced from its position in a dissonant relation with another element which refutes it. Connected contradictions may lead to a deep and powerful insight and they often appear in elevated states of creative thought (Storr, 1972). This expereince peaks when the individual is able to hold several contradictory elements at the same time, without attempting to separate them into different contexts as happens in the RR episteme, or cancel out their sharp polarity as is the case with the MM episteme. A subsequent part of the interview with Gideon bears this out. Q: Can you be both serious and frivolous at once? A: It’s obvious that I can have each of these traits separately. But to have frivolous seriousness – yes. Absolutely. I can say it’s true even in relation to the same object in question. Let's say I went through a specific experience and later I reflect upon it – there is the sudden experience which is not so serious or deep, and then there is a serious state. And… ah…yes. Yes. For example, when you’re going through an experience and at the same time you are aware that you are in the experience. So that awareness – It's not always like this but I know that it’s possible – that awareness makes everything magnificent and significant in the serious meaning of the word. You’re both in the experience and at the same time you’re examining it from the outside. It’s like you’re dismantling a fundamental core of the world. In these situations I suddenly feel something unexpected; a side that is very light and carefree. I feel at the same moment that I’m both light and also that I’m digging something very deep and very serious. So yes, it can absolutely happen.

Gideon demonstrated his ability to grasp opposing momentums and to create a connected contradiction of ”awareness” and ”experience” or of ”seriousness” and ”frivolousness”. This

20

Gabriel Bukobza

experience encompasses meanings of lightness that are related to being frivolous, together with meanings of seriousness and reflection. These are states of great significance to Gideon, when he felt like he was deciphering something very fundamental about the world. Both of these excerpts were coded as DD due to their emphasis on and use of contradictions and inconsistency.

Integral-Inclusive Episteme Ze’ev, a 50 year- old man with a Bachelor’s degree. Q: You included in your portfolio all the traits that appeared in the original list. Can you please explain that? A: Yes. When you become aware of who you are, and when you decide to work to improve yourself, you strive to unite all the powers that you have. In other words you become spiritual. When you do that you discover something that might surprise you – that almost all things exist in you already. So I’m an extrovert, and I’m active; I’m talkative and disciplined, and I’m certainly social; I’m calm, naïve, trusting, excited and daring. All the things in that list and more are me. Q: And traits that are considered contradictory – what do they lead to? A: In the past it meant conflict. I remember the feeling of bifurcation, internal struggle and conflict. But today it’s different. When I was young, or let’s call it inexperienced, I was an absolutist and this was a core trait of mine. But I used this core trait in a uni-dimensional, unequivocal, unrealistic and shortsighted way. But today this quality of living things in an absolute way is expressed in a more open and inviting manner. I’m open to others and I listen to them. I’m more balanced and I take in other components. So I’m still an absolutist, but my construction is more stable and unified and is made up out of many more parts.

When Ze’ev described his SC he pointed out that all traits have the potential to accurately represent him. He paid attention to the fact that some traits clashed with others, but that did not prevent him from including them in his description. His reasoning was that the entire range of traits could be attributed to a super-structure or a meta-concept such as ”uniting all powers” or “being spiritual”. This common structure encompassed all differences and contradictions, and united them into an integral whole. Ze’ev admitted that holding different contradictory elements did contribute to a state of conflict in the past, but his present episteme was able to reconcile between the various forces and create an equilibrium. The result was that the dynamic and dissonance-inducing state caused by conflicting oppositions was replaced by a new, harmonious state of congruence and consistency. The fact that Ze’ev was able to hold so many contradictory elements under one conceptual umbrella indicated that he had an II epistemic structure. It is important to note at this point that the II episteme does not reach consistency through negating or ignoring contradictory elements as does the MM episteme, but through subjecting them to a more comprehensive and totalizing order.

The Development of Epistemic Complexity in Adulthood

21

Other-Independent – Other-Dependent in the CC Context Monolithic-Monoformal Episteme Yossi, a 20 year- old man with a high school diploma. Q: What kind of education would you give your children if you were moving abroad, say to the US? A: I’ll send my children to a Jewish school abroad because I want them to be Jewish. I don’t really care about other alternatives. Other ways of life are irrelevant to me. I want to be Jewish. This is the existential system of my life. And even if you prove to me in the most convincing way that tomorrow the world is going to end, I still will raise them as Jews. And since this is what I want, and only this, then I have to act and give them a Jewish education. You may ask why I insist so much on this, and I’ll answer you – I don’t know why, all I know is that this is what I want.

Yossi preferred the Jewish way of life to any other. He disregarded and rejected other cultural models. In epistemic terms his MM episteme adhered to one meaning system, which he assumed to be totally reliable and undisputed. Unfamiliar systems were seen as either false or irrelevant, unless they could be subjugated to the original one. Yossi was aware that there are plenty of cultural options in the world, but he didn’t wish to be exposed to any of them, and chose to give his children a homogeneous education. This is an example of a strong dependence on one’s original culture, and a MM-type independence from other cultural forms.

Relativist-Relational Episteme Anat, a 37 year- old woman with a Bachelor’s degree. A: I would like my children to feel comfortable in their social world, to interact with other people, and not to feel alienated or estranged. I don’t want them to form a secluded Israeli or Jewish group within the school. On the other hand I wouldn’t want them to forget their Judaism. So I would send them to a regular American public school, and in the afternoon to Jewish classes or to Sunday school. Q: And what do you generally think about the exposure to a different culture? A: I value it. I think it’s a good and positive thing. It helps you develop your personality both intellectually and emotionally. It’s good to know that there are other forms of life on this planet. It teaches you many things, and personally it really fascinates me. (…) The only way it might confuse you is if you take things from it that you’re not happy with. What you need to do is to look at those other people and cultures and learn from them. But you don’t have to necessarily adhere to their ways or become like them. I stick to what I have and I try to learn from others.

In Anat’s mind acquiring different cultural knowledge is interesting and beneficial. She opted to get exposed to unfamiliar knowledge and constructed an other-dependent meaning system. Nevertheless, Anat regarded the new knowledge as belonging to a different system, which is distinct from her own. She acknowledged the importance of learning or experiencing foreign norms and values, but placed them at a distance from her own cultural system. She did not exhibit a wish to reconcile the differences between the worlds, nor did she want to let one world influence the other.

22

Gabriel Bukobza

Anat’s excerpt is an example of the RR episteme; she is a type of person who views all ways of life as equal in value and validity, and places her own beliefs in dependent relation to them. Her episteme is structured in a way which keeps each cultural form separate in its own context, without the possibility of mutual influence and change.

Dialectical-Deconstructive Episteme Tahel, a 30 year- old woman who has a Bachelor’s degree. A: I think that encountering contradictory values from different cultures is a good thing. Why? Because it allows you to be in the same place but different; because it brings you choice. Knowing that things are different somewhere else may make life more difficult because then you’ll have to make difficult choices. You might feel confused and messed up, and maybe incomplete. But you need to know that the mess in your mind is caused by your expanding horizons. You finally know how much you don’t know, and things that you do know get an extra level of depth. For example, I might not accept all the different Jewish movements and schools, but I know that they inject Judaism with more content and more life. It becomes a much richer entity because of them. Now some ideas may be radical enough to change the original form of Judaism, but I think that it’s better that way than with a narrower perspective that doesn’t allow for any change at all. It’s better to have it different and rich than similar and narrow.

Tahel encouraged dependence on unfamiliar cultural knowledge and accepted the changes that might accompany such a relationship. Foreign knowledge for her is a source for growth and enrichment, even if it leads to an increase in the level of epistemological chaos and uncertainty. She embraced the plurality of different cultural forms and made an effort to simultaneously include as many aspects of them as possible in her own life. Tahel exemplified the dialectical preference for dynamic interactions with other knowledge systems in her belief that her culture can include opposing ideas without trying to synthesize them into a singular and unified form.

Integral-Inclusive Episteme Dalit, a 27 year- old woman who has a Master’s degree. A: We belong to many circles in our life. One circle of belonging is the family, or local culture, or your religion. And another circle of belonging is the world. The closer the circle is to you, the more time and thought, study and depth you will give to it. But you must never ignore the circle of the world, even if it seems far away. You are still and always will be a child of the Earth. A child of your time, and a child of humanity. The final aim I have is to reach unity. In the end we are all one. We are a multitude, which forms a unity. We need to reduce the multitude into something singular. The more interaction with the world and the more learning you have, the more you understand that the basis for all religions is one. The idea behind all religions is one. That’s why I’ll teach my children about everything. Everybody believes in something. Even if you’re going from Tel-Aviv to Haifa, you believe you’ll eventually get to Haifa. If you had no belief, you wouldn’t go. Now the religious person worships God, but each one worships some kind of God, even if that God is a tree, nature, it doesn’t matter. And the God at the end is one. (…) And then you realize that everything you see is the fragmentation of that One into thousands of small components that show themselves to you in their multiplicity, sometimes in oppositions and conflict and sometimes not. I

The Development of Epistemic Complexity in Adulthood

23

understand that these ideas clash with the world of concepts as we know it, but once you live with that unity you merge with all that comes to you and then there is no good and bad and duality but one love for everything.

Dalit interpreted the multitude of elements that make up reality as being the abundant reflection of a deeper unity. Through her epistemic lens, every phenomenon in reality stems from a fundamental source and can be explained by it. However, she completely ignored other explanatory or interpretive systems. Since she viewed everything through one particular meta-system or core concept, she could not form relations with other potential systems. Dalit is unable to perceive anything as alien; even things that might be experienced as foreign were interpreted by her as necessary parts in the integrated order of things. Accordingly, this excerpt was coded as representative of II episteme, which is independent of other knowledge.

DISTRIBUTION OF THE FOUR EPISTEMES IN THE SAMPLE Participants’ scores were collapsed to 7 basic groups representing the 4 complete and the 9 transitional epistemes of the original scale. The following diagrams display the distribution of epistemes for the self concept and cultural concept, respectively. 50

40

30

20

Frequency

10

(%) 0

16.3% MM

10%

40% RR

M M/RR

7.5%

16.3% DD

RR/DD

1.3%

8.8% II

DD/II

Epistemic score Diagram 1. Frequency distribution for epistemic scores in the SC context

Diagram 1 shows that in the self concept context 16% of the participants presented a MM episteme, 40% were RR, 16% DD, and 9% II. Overall 81% or participants had a complete and whole episteme as opposed to 19% who showed patterns belonging to more than one epistemic orientation. In the cultural concept context (diagram 2) 20% of participants were of MM episteme, 40% were RR, 12.5% were DD, and 15% were II. 87.5% of participants in the

24

Gabriel Bukobza

cultural concept context were found to possess a whole episteme, and 12.5% were in a transitional position.

50

40

30

20

10

Frequency

(%) 0

20% MM

7.5% MM/RR

40.0% RR %

5.0% RR/DD

12.5% DD

15% II

Epistemic score Diagram 2. Frequency distribution for epistemic scores in the CC context.

DOMAIN SPECIFICITY OF THE EPISTEMES A paired sample t test revealed that the difference between epistemic scores in the two domains for the entire population was insignificant, t = -0.453, n = 80. Further, there was a strong correlation between the SC and CC scores, r(80) = 0.705, p < 0.001. This relation was expressed in yet another way; 53 participants (66.3% of population) received an epistemic score in one domain that was identical to, or not different by more than one unit, than their score in the second domain. These results indicate that participants exhibited a high degree of consistency across the two domains. The cross-domain correlation was positive for all age groups but was significant only for the two older groups, as can be seen in Table 1. Table 1. Correlations between SC and CC epistemic scores for each age group

r N ** p<0.01.

17-22 yrs 0.423 20

26-32 yrs 0.362 20

37-47 yrs 0.752** 20

56-70 yrs 0.781** 20

The Development of Epistemic Complexity in Adulthood

25

RELATIONS BETWEEN THE FOUR EPISTEMES, AGE, LEVEL OF EDUCATION AND GENDER Age groups. An ANOVA test for age groups yielded a significant difference in self concept scores F(2,76) = 3.723, p < 0.01, and in cultural concept scores F(2,76) = 3.87, p < 0.01. Tukey post-hoc tests indicated that the mean epistemic scores for the youngest age group (17-22 yrs) were significantly lower (p < 0.05) than the scores for the two middle age groups (26-32 and 37-47 yrs) in both domains. However, the mean score for the youngest group was not significantly different from the mean score for the eldest one (56-70 yrs) in both domains. The similarity in the mean scores of the youngest and oldest age groups does not tell the whole story. In the self concept domain 90% of the participants in the young group had a MM or RR score, and only 10% had a RR/DD or DD score. In the oldest group, however, there was more diversity: 65% were MM or RR, 15% were RR/DD or DD, and 20% were II. In the cultural concept domain 100% of young participants were MM or RR, as opposed to 70% MM or RR, 5% DD, and 25% II of the older participants. The significance of these findings will be outlined in the Discussion section. Educational background. An ANOVA test for education-based groups yielded a significant difference in self concept scores F(2,74) = 6.259, p < 0.005, and cultural concept scores F(2,74) = 5.128, p < 0.01. The Tukey post-hoc test showed that the least educated group had markedly lower mean scores than the other two groups in both domains (p < 0.01). Gender. Independent t test revealed no significant gender differences in both domains, as can be seen in table 2. Table 2. t tests for gender differences in epistemic SC and CC scores

SC CC

Women X=1.43, sd=4.23 X=4.26, sd=1.61

Men X=1.93, sd=4.58 X=4.68, sd=1.86

t 0.921 1.071

Sig NS NS

N 80 80

DISCUSSION This research examined the ways by which adults construe personal knowledge about self and culture. It identified four distinct epistemes that organize knowledge in both contexts in different levels of complexity. In what follows the four epistemes will be presented in detail, based on the empirical results obtained from the interviews.

Monolithic-Monoformal (MM) Episteme The MM episteme assumes that there is a fundamental, stable, and a-historic matrix or framework that can determine the truth of all concepts and theories (Bernstein, 1988). The MM episteme has a consistent and coherent form. It is characterized by a very low tolerance to contradiction and opposition. Internal or external forces that negate it are ignored,

26

Gabriel Bukobza

repressed or reconciled, and are not considered a part of the system in their contradictory state. The episteme strives to sustain a balanced and equilibrated condition, which avoids paradox and inconsistency. It is a fixed entity, which is guided by the assumption that its components are true and valid, and therefore do not need to be questioned, discussed, or be open to criticism. This is a self-identical, unchanging formation, which preserves its form regardless of context or time. Its properties are all constant, since they are believed to be part of a harmonious and absolutely true system. The episteme has a singular form, which is concise and undifferentiated. Divisions and fragmentations are unified through a process of reduction to a crystallized core. This formation is context-independent; it retains the same form in all circumstances, in the same way a logical necessity or a reasoned truth does not alter with a change in context. This episteme rejects foreign knowledge and is independent of it. Assertions belonging to different belief systems are seen as strange, alien, mistaken, and false. Finally, the MM episteme adheres to a dominant way of knowing that is considered totally reliable. Other ways can be used as long as their results are consistent with the dominant form of knowledge acquisition.

Relativist-Relational (RR) Episteme The RR episteme assumes that different orders of meaning exist in the world and that their truthfulness is contingent to subjective mentalities, cultural contexts, historical forces, conceptual frameworks, and the like (Bernstein, 1988; Mandelbaum, 1982; Williams, 1972). It hence constructs a diversified knowledge system that can make sense of these different orders. Each separate sub-order follows the guidelines of a MM construction, but overall the system is multiple, relative, and relational. The RR episteme has an inconsistent and incoherent form. It acknowledges its own versatility and the lack in consistency that results from having many facets. It attributes its own contradictions to difference resulting from changes in location, time, language, culturally-determined relations with others, etc. The RR formation exists in a state of relative motion: Self-knowledge in this episteme is relative to the conditions of discourse and since these conditions are dynamic the knowledge they produce is dynamic too. The structure of the RR episteme undergoes relative transformations which occur when the conditions of knowledge change, and when its relations to other systems of knowledge change. This is a plural and fragmented formation; it is composed of many components, facets, and subsystems, which function as related units in the episteme. These cannot be reduced or generalized to a core center without the episteme losing its peculiar character. The RR formation is context-dependent. Its parts are contingent on the particular context in which they arose and cannot be stretched beyond that context. This episteme is accepting of and dependent on foreign knowledge. Being relational means being influenced and directed by the connections one has with other referential systems of significance. Hence, this episteme values information and knowledge from other sources, and views them as relevant and meaningful to its own identity. Moreover, it uses different methods to gather information about the world, since every method has its own contextual validity. This methodology additionally means that the value of knowledge is limited to the ways by which it was constructed and verified.

The Development of Epistemic Complexity in Adulthood

27

Dialectic-Deconstructive (DD) Episteme The DD episteme assumes that knowledge systems are susceptible to interruptions and refutations, that the meanings they include are paradoxical and volatile, and that their identity is in constant flux. It deconstructs the regular structures of signs and systems, exposing their internal dynamics, their non-identical features, and their ever-changing character (Adorno, 1990; Marcuse, 1954). It aims to constitute a diversified “knowing system” that can accommodate cases of paradox, contradiction and irrationality, side by side with instances that abide by the rules of traditional logic. The DD formation is radically inconsistent as it emphasizes the multitude of opposing elements that exist in mutually dependent relationships. These oppositions dwell inside the system without aspiring to achieve a non-contradictory end-state (Piaget, 1980; Tolman, 1981; 1983). This episteme undermines its own structure through a process of constant negation that uncovers the “untruth of identity” (Adorno, 1990; p. 5). It consists of antinomies, and lacks a consistent unifying line or theme. The conflicted elements form complex relations: they collide, interpenetrate, and influence one another. This is an episteme in perpetual motion; nothing in it is fixed for more than a short while. Its parts and the relation they form with other parts are dynamic and active, and their movement proceeds in unpredictable patterns. The DD episteme is in a mode of constant transformation and therefore never ceases to alter between different shapes. Change rather than form is its guiding rule. It is never identical to itself, as it constantly sheds old skins and wraps itself with new ones. It is a plural form composed of multiple components. Its parts are influenced by the conditions marked by particular contexts, but they are also able to cross contexts and to penetrate novel surroundings. Moreover, knowledge associated with one context does not stay confined to that context alone, since it is allowed to flow between different locations of meaning. The DD episteme does not pull to bring its own multiplicity under one conceptual roof; on the contrary, it is characterized by a dispersive force. Its parts strive to remain in their heterogeneous existence, and resist any kind of homogenizing effort. This episteme is dependent on foreign and opposing facts and figures. The boundaries of the episteme are open and function like a diffusive membrane, which can be penetrated and acted upon by elements from other systems. Finally, it uses multiple sources of knowing, which are all interdependent. This leads to an accumulation of conflicting results, which are all embraced but not integrated.

Integral-Inclusive (II) Episteme The II episteme assumes that there is an overriding order of knowledge which includes within it all possible forms of order and non-order. It aims to constitute a knowledge system that renders unitary and transcendent the diverse forms reality takes. In contrast to the MM episteme which stems from a similar assumption about a unitary system, the II episteme is driven by the belief that all available knowledge, including that which is paradoxical or contradictory, must be accounted for and subsumed under one frame of meaning. It works to reconcile between multiple, non-identical systems of meaning in order to fuse them into a singular, all-inclusive, integrated, and absolute structure (Lovejoy, 1960/1936; Wilber, 2000; Wilson, 1998).

28

Gabriel Bukobza

In the II episteme a knowledge edifice is constructed from previously disparate and incompatible elements. The new formation includes properties of the original components set in a new synthetic web of relations. The II episteme is consistent and coherent; it contains a plurality of contradictory parts momentums, but it is able to cohesively gather them into a comprehensive narrative, theory, or conceptual equilibrium. This is a fixed formation: it registers the dynamics of knowledge, yet claims that all motion is part of a large body of meanings that is constant. The II episteme has a stable and immutable identity, though it encompasses many minor adjustments and alterations. It is additionally a singular episteme: All the properties that are embraced by it are weaved into an all-including single Metastructure. Further, this episteme is context independent, since it assumes that its own knowledge is completely valid beyond the particular contexts of its acquisition. It is furthermore independent of other factors, since it holds its truth-value to be undisputed. However, unlike the MM episteme it does not reject unknown or foreign knowledge, but instead integrates it to its preexisting conceptual structure. Finally, it views different ways of gathering knowledge as methods that corroborate its own truthfulness.

Cross-Domain Consistency of the Epistemes Psycho-epistemological studies tend to assume that peoples' ways of knowing can be generalized beyond the particular context of their examination (Basseches, 1984; Commons and Richards, 2002; Kegan, 1994; King and Kitchener, 1994). These studies have been largely influenced by Piaget’s structural-developmental model that claimed universal validity (Inhelder and Piaget, 1958). Others criticized this belief, arguing that knowing forms in particular contexts that must be taken into account in determining cognitive abilities (Dewey, 1933; Vygotsky, 1978). The epistemes in the present study were examined in two distinct domains, and so it was possible to test for domain specificity. The results showed that a high degree of correlation exists between self and culture scores, and that no significant difference differentiates between them. In addition, 2/3 of the interviewees received a score in one domain, which was identical or not different by more than one unit of score to their score in the second domain. These results suggest that the epistemes are not domain specific, and that the logic that guides the processes of knowing works in a similar fashion across at least two different contexts. An intriguing finding in the area of cross domain consistency was that the level of consistency grew stronger with age; for example, the correlation for the two young age groups was averaging 0.39 and was not significant, as opposed to the average for the two older groups which was 0.77 and significant. This might indicate that in late adolescence and early adulthood the epistemes are still in a state of formation (Harter and Monsour, 1992). As years go by a more stable equilibrium is established, and a higher degree of epistemic generalization across domains is achieved.

The Development of the Four Epistemes A fundamental issue in the investigation of a psychological concept is its developmental character. Studies by Baldwin, Piaget, Vygotsky, Werner, Kohlberg, Perry, Loevinger,

The Development of Epistemic Complexity in Adulthood

29

Kegan, and others revealed that psychological structures develop in a hierarchical way. Each new stage encompasses the qualities of previous stages, adding a new set of elements, functions, and relations. The present research used a cross-sectional method, and therefore any discussion about development is purely suggestive. Nevertheless, both the theoretical model and evidence from the interviews do suggest a possibility of epistemic development. This can be exemplified by looking at the DD episteme in relation to the MM and RR ones. The MM episteme acknowledges one order of knowledge that is coherent, consistent and constant. The RR episteme includes other orders that are each coherent, consistent, and constant. The DD episteme acknowledges the first order of the MM episteme, as well as the new ones revealed by the RR episteme. Moreover, it recognizes the interactive and reciprocal relationship between the different orders. In addition, the DD episteme can interpret orders that are incoherent, inconsistent, and in an ongoing flux, which the first two epistemes cannot comprehend. It perceives, moreover, the elements of self-negation that each system actually includes, and their constitutive relations with other elements inside the system. The DD episteme therefore holds more cognitive tools that enable it to organize and eventually understand more sophisticated types of knowledge. These added abilities make for a more a complex way of knowing. In the present research the correlation between age and level of complexity was very low (r = 0.12 and r = 0.14 for SC and CC, respectively). Nevertheless, another result that is taken into account in assessing development is the differences in scores between different age groups (Broughton, 1975; Kegan, 1982). In this study, the overwhelming majority of participants from the youngest age group revealed either MM or RR epistemes in both domains. In the next two age groups there were more instances of DD and II epistemes, and the oldest age group consisted of 25% MM in both contexts, 20% II in the self-concept context and 25% II in the cultural-concept one. These results show that some relation between age and epistemic complexity does exist; the frequency of more complex epistemes goes up with age. This is consistent with findings from other studies that showed that advanced ways of knowing are more apparent in older populations (King, Kitchener, Davison, Parker, and Wood, 1983; Kitchener and King, 1981; Kramer and Woodruff, 1986). Based on these findings it may be suggested that epistemological development in adulthood is not determined by age; however, with the progression of time the probability of it happening increases.

THE SHAPE OF DEVELOPMENT: THE CONTINUOUS SPIRAL MODEL In contrast to most psycho-epistemological models, which depict a sequential linear developmental structure (Commons and Richards, 2002; Fischer, 1980; Inhelder and Piaget, 1957; King and Kitchener, 1994; Kohlberg, et al., 1984; Perry, 1970), the present one suggests that epistemic growth progresses in a continuous spiral way. Continuous development means that no episteme, including the Integral-Inclusive one, marks the final point for the potential growth of the knowledge system. Spiral development means that advanced positions along the trajectory share the same structural form with more basic ones, and hence may have similar characteristics. This is indeed the case with the MM and II

30

Gabriel Bukobza

epistemes which are both characterized by a unitary, stable, consistent, and coherent organization of knowledge. The II episteme does encompass many more sub-systems of knowledge than the MM episteme, but it ultimately constructs a singular Meta-system that has the same structural traits as the latter system. Its content is therefore richer and its explanatory value much higher, but its epistemological form is identical with that of the MM episteme. This means that the initial position in the developmental trajectory is similar to the last one, and that the most developed epistemic form is not different in its structure from the least developed one. Granted, the two positions differ in the breadth of their perspective, but from a formal-epistemological standpoint they are located at the same point. The singular and coherent formation of the II episteme has another crucial significance for development. Since it is structurally identical to the MM episteme, it is prone to the effects of higher-order forms of relativism and dialectics. In this manner further transformations of the episteme occur, and more advanced forms of RR, DD, and II epistemes evolve. This can be seen in Diagram 3 which illustrates how a second-order RR episteme lies beyond the first-order II episteme. In similar fashion more advanced forms of DD and II epistemes exist further ahead. Since the internal epistemic structure of the MM and II epistemes is identical, the dynamic spiral later consists only of RR, DD, and II structures, as the MM episteme exists only in the beginning of development. It is this relationship between the epistemes that makes the entire developmental model continuous and spiral.

II2

II1

MM1

DD1 DD2

Diagram 3. The Continuous Spiral Model.

RR1 RR2

The Development of Epistemic Complexity in Adulthood

31

IMPORTANCE OF THE PRESENT RESEARCH The findings from this research may contribute to several areas of study. In the field of psycho-epistemology they support the growing understanding of the different and complicated facets of the adult’s knowledge system. In the field of post-formal and postconventional thought, the results shed light on ways of knowing that are more advanced in complexity than formal operational thought. The RR, DD, and II epistemes use cognitive abilities that encompass and transcend hypothetico-deductive operations. This allows them to successfully respond to complicated problems and challenges of adult life. The DD and II epistemes in particular are further related to the concept of wisdom (Baltes and Staudinger, 2000; Labouvie-Vief, 1990), since they actualize the abilities to comprehend the significance of relativity and relations, to recognize and allow for diversity and contradictions, and to attain the most complicated mental unifications and integration.

LIMITATION OF THE PRESENT INVESTIGATION The four epistemes in the current model were constructed according to seven fundamental principles. The principles that were selected therefore determined to a large extent the type of epistemes that were eventually constructed. A relevant question here is why it was these principles that were selected and not others, and whether they are exhaustive. The seven factors were selected since they deal with fundamental issues of organizing knowledge. However, it can be argued that there exist other such fundamental issues which would obviously have led to the definition of different principles. Potential issues that were not addressed here include the certainty of knowledge, the reaction to knowledge from authority, and the systematic use of questions and doubt. Future research might wish to expand the range of epistemic issues and principles in order to reach a more comprehensive epistemological picture. Another caveat deals with the level of generalization of the epistemes. The present study examined individuals’ conceptions of self and culture. The question here is whether the conclusions from these contexts can be generalized to other areas of meaning making. The strong relation between the SC and CC indicates that a consistent cognitive structure might exist, but there is a need for further research in order to strengthen this finding.

AUTHOR'S NOTE: The author gratefully acknowledges the constructive remarks of Prof. Mordecai Nisan during the progression of this work.

32

Gabriel Bukobza

BIBLIOGRAPHY Adorno, T. W. (1990). Negative dialectics. London: Routledge and Kegan. (Original published 1966). Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55, 469-480. Baltes, P. B., and Staudinger, U. M. (2000). Wisdom: A meta-heuristic (pragmatic) to orchestrate mind and virtue towards excellence. American Psychologist, 55(1), 122-136. Basseches, M. A. (1976). Beyond closed-system problem-solving: A study of meta-systematic aspects of mature thought. Unpublished Ph. D. thesis, Harvard University. Basseches, M. (1980). Dialectical schemata: A framework for the empirical study of the development of dialectical thinking. Human Development, 23, 400-421. Basseches, M. (1984). Dialectical thinking and adult development. Norwood, NJ: Ablex. Baumeister, R. F. (1998). The self. In D. T. Gilbert, S. T. Fiske, and G. Lindzey (Eds.), The handbook of social psychology, Vol. 1. (pp. 680-740). New York: McGraw-Hill. Baxter-Magolda, M. B. (1999). The evolution of Epistemology: Refining contextual knowing at twentysomething. Journal of College Student Development, 40(4), 333-344. Belenky, M. F., Clinchy, B. M., Goldberger, N. R., and Tarule, J. M. (1986). Women’s ways of knowing: The development of self, voice, and mind. New York: Basic Books. Bernstein, R. J. (1988). Beyond objectivism and relativism: Science, hermeneutics, and praxis. Philadelphia, PA: University of Pennsylvania Press. Berry, J. W. (1988). Acculturation and psychological adaptation: A conceptual overview. In J. W. Berry, and R. C. Annis (Eds.), Ethnic psychology: Research and practice with immigrants, refugees, native peoples, ethnic groups and sojourners (pp. 41-52). Amsterdam: Swets and Zeitlinger. Berry, J. W., Trimble, J. E., and Olmedo, E. L. (1986). Assessment of acculturation. In W. Lonner, and J. W. Berry (Eds.), Field methods in cross- cultural research (pp. 291-324). Newbury Park, CA: Sage. Brim, O. G. (1976). Life-span development of the theory of oneself: implications for child development. In H. W. Reese (Ed.), Advances in child development and behavior, Vol. 2 (pp. 241-251). New York: Academic Press. Broughton, J. M. (1975). The development of natural epistemology in adolescence and early adulthood. Unpublished Ph. D. thesis, Harvard University. Broughton, J. M., and Freeman-Moir, D. J. (Eds.). (1982). The cognitive- developmental psychology of James Mark Baldwin: Current theory and research in genetic epistemology. Norwood: Ablex. Bukobza, G. (2007). The epistemological basis of selfhood. New Ideas in Psychology, 25(1), 37-65. Burr, J. E., and Hofer, B. K. (2002). Personal epistemology and theory of mind: Deciphering young children’s beliefs about knowledge and knowing. New Ideas in Psychology, 20, 199-224. Campbell, J. D., Trapnell, P. D., Heine, S. J., Katz, I. M., Lavallee, L. F., and Lehman, D. R. (1996). Self-concept clarity: Measurement, personality correlates, and cultural boundaries. Journal of Personality and Social Psychology, 70(1), 141-156.

The Development of Epistemic Complexity in Adulthood

33

Cavanaugh, J. C., Kramer, D. A., Sinnott, J. D., Camp, C. J., and Markley, R. P (1985). On missing links and such: Interfaces between cognitive research and everyday problemsolving. Human Development, 28, 146-168. Chandler, M. J., and Boutilier, R. G. (1992). The development of dynamic system reasoning . Human Development, 35, 121-137. Chandler, M. J., Boyes, M., and Ball, L. (1990). Relativism and stations of epistemic doubt. Journal of Experimental Child Psychology, 50, 370-395. Chandler, M. J., Lalonde, C. E., and Sokol, B. W. (2000). Continuities of selfhood in the face of radical development and cultural change. In L. P. Nucci, G. B. Saxe, and E. Turiel (Eds.), Culture, thought, and development. (pp.65-84). Mahwah, NJ: Lawrence Erlbaum. Commons, M. L., and Richards, F. A. (2002). Four postformal stages. In J. Demick (Ed.), (pp. 199-219). Handbook of adult development. New York: Plenum. Cook-Greuter, S. R. (1999). Postautonomous ego development: A study of its nature and measurement. Unpublished Ph. D. thesis, Harvard University. Damon. W., and Hart, D. (1982). The development of self-understanding from infancy through adolescence. Child Development, 53, 841-864. Denney, N. W. (1982). Aging and cognitive changes. In B.B. Wolman (Ed.), Handbook of developmental psychology. (pp. 807-827). NJ: Prentice-Hall. Dewey, J. (1933). How we think: A restatement of the relation of reflective thinking to the educative process. Boston: D. C. Heath. (Original published 1910). Dien, D. S. (2000). The evolving nature of self-identity across four levels of history. Human Development, 43, 1-18. Donahue, E. M., Robins, R. W., Roberts, B. W., and John, O. P. (1993). The divided self: Concurrent and longitudinal effects of psychological adjustment and social roles on selfconcept differentiation. Journal of Personality and Social Psychology, 64(5), 834-846. Edelstein, W. and Noam, G. (1982). Regulatory structures of the self and ‘postformal’ stages in adulthood. Human Development, 25(6), 407-422. Epstein, S. (1973). The self-concept revisited, or a theory of a theory. American Psychologist, 28, 404-416. Erikson, E. H. (1968). Identity: youth and crisis. New York: Norton. Ewing, K. P. (1990). The illusion of wholeness: Culture, self, and the experience of inconsistency. Ethos, 18(3), 251-278. Fischer, K. W. (1980). A theory of cognitive development: The control and construction of hierarchies of skills. Psychological Review, 87(6), 477-531. Fischer, K. W., and Bidell, T. R. (1998). Dynamic development of psychological structures in action and thought. In W. Damon (Series Ed.) and R. M. Lerner (Vol. Ed.), Handbook of child psychology: Vol. 1: Theoretical models of human development. (pp. 467-561). New York: Wiley. Flavell, J. H. (1963). The developmental psychology of Jean Piaget. N. J.: Van Nostrand. Foucault, M. (1970). The order of things: An archeology of the human sciences. New York: Pantheon Books. (Original published 1966). Foucault, M. (1972). The archaeology of knowledge and the discourse on language. New York: Pantheon Books. (Original published 1969). Fowler, J. W. (1981). Stages of faith: The psychology of human development and the quest for meaning. San Francisco: Harper and Row.

34

Gabriel Bukobza

Funder, D. C. (1983). The “consistency” controversy and the accuracy of personality judgments. Journal of Personality, 51(3), 346-359. Gebser, J. (1985). The ever-present origin. Athens: Ohio University Press. (Original published 1949; part 2 published 1953). Geertz, C. (1984). From the native’s point of view: On the nature of Anthropological understanding. In R. Shweder and R. Levine (Eds.), Culture theory: Essays on mind, self, and emotion. (pp. 123-136). Cambridge University Press. Gergen, K. J. (1991). The saturated self. New York: Basic Books. Gilligan, C. (1982). In a different voice: Psychological theory and women’s development. Cambridge: Harvard University Press. Greenwald, A. G., and Pratkanis, A. R. (1984). The self. In R. S. Wyer, and T. K. Srull (Eds.), Handbook of social cognition, Vol. 3 (pp. 129-178). Hillsdale, NJ: Erlbaum. Hampson, S. E. (1997). Determinants of inconsistent personality descriptions: Trait and target effects. Journal of Personality, 65(2), 249-290. Hampson, S. E. (1998). When is an inconsistency not an inconsistency? Trait reconciliation in personality description and impression formation. Journal of Personality and Social Psychology, 74(1), 102-117. Harris, M. (1999). Theories of culture in postmodern times. AltaMira Press. Harter, S., and Monsour, A. (1992). Developmental analysis of conflict caused by opposing attributes in the adolescent self-portrait. Developmental Psychology, 28(2), 251-260. Hermans, H. J. M. (1996). Voicing the self: From information processing to dialogical interchange. Psychological Bulletin, 119(1), 31-50. Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. Psychological Review, 94(3), 319-340. Holsti, O. R. (1969). Content analysis for the social sciences and humanities. Reading: Addison-Wesley. Inhelder, B., and Piaget, J. (1958). The growth of logical thinking from childhood to adulthood. New York: Basic Books. Jensen, L. A. (1997). Different worldviews, different morals: America’s culture war divide. Human Development, 40, 325-344. Kegan, R. (1982). The evolving self: Problem and process in human development. Cambridge: Harvard University Press. Kegan, R. (1994). In over our heads: The mental demands of modern life. Cambridge: Harvard University Press. Kelley, G. A. (1955). The psychology of personal constructs, Vol. 1. New York: Norton. King, P. M., and Kitchener, K. S. (1994). Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults. San Francisco: Jossey-Bass Publishers. King, P. M., Kitchener, K. S., Davison, M. L., Parker, C. A., and Wood, P. K. (1983). The justification of belief in young adults: A longitudinal study. Human Development, 26, 106-116. Kitchener, K. S., and King, P. M. (1981). Reflective judgment: Concepts of justification and their relationship to age and education. Journal of Applied Developmental Psychology, 2, 89-116.

The Development of Epistemic Complexity in Adulthood

35

Kitchener, K. S., King, P. M., Wood, P. K., and Davison, M. L. (1989). Sequentiality and consistency in the development of reflective judgment: A six-year longitudinal study. Journal of Applied Developmental Psychology, 10, 73-95. Kohlberg, L., Levine, C., and Hewer, A. (1984). The current formulation of the theory. In L. Kohlberg (Ed.), Essays on moral development, Vol. 2: The psychology of moral development. (pp. 212-319). San Francisco: Harper and Row. Kohlberg, L., and Ryncarz, R. A. (1990). Beyond justice reasoning: Moral development and consideration of a seventh stage. In C. N. Alexander, and E. J. Langer (Eds.), Higher stages of human development: Perspectives on adult growth. (pp. 191-207). New York: Oxford University Press. Koplowitz, H. (1984). A projection beyond Piaget’s formal-operations stage: A general system stage and a unitary stage. In M. C. Commons, F. A. Richards, and C. Armon (Eds.), Beyond formal operations: Late adolescence and adult cognitive development. (pp. 272-295). New York: Praeger. Koplowitz, H. (1990). Unitary consciousness and the highest development of mind: The relation between spiritual development and cognitive development. In M. L. Commons, C. Armon, L. Kohlberg, F. A. Richards, T. A. Grotaer, and J. D. Sinnott (Eds.), Adult development: Models and methods in the study of adolescent and adult thought; Volume 2. (pp. 105-111). New York: Praeger. Kramer, D. A. (1983). Post formal operations? A need for further conceptualization. Human Development, 26, 91-105. Kramer, D.A. (1990). Conceptualizing wisdom: the primacy of affect-cognition relations. In R. Sternberg (Ed.), Wisdom: Its nature, origins and development (pp. 279- 309). Cambridge: Cambridge University Press. Kramer, D. A., and Woodruff, D. S. (1986). Relativistic and dialectical thought in three adult age-groups. Human Development, 29, 280-290. Kruglansky, A. W. (1989). Lay epistemics and human knowledge: Cognitive and motivational bases. New York: Plenum. Kuhn, D. (1991). The skills of argument. Cambridge University Press. Kuhn, T. (1970). The structure of scientific revolutions. University of Chicago Press. Kuper, A. (1999). Culture: The anthropologists’ account. Cambridge: Harvard University Press. Labouvie-Vief, G. (1982). Dynamic development and mature autonomy: A theoretical prologue. Human Development, 25, 161-191. Labouvie-Vief, G. (1990). Wisdom as integrated thought: Historical and developmental perspectives. In R. J. Sternberg (Ed.), Wisdom : Its nature, origins, and development. (pp. 52-83). New York: Cambridge University Press. Labouvie-Vief, G. (1992). A neo-Piagetian perspective on adult cognitive development. In R. J. Sternberg, and C. A. Berg (Eds.), Intellectual development. (pp. 197-228). Cambridge University Press. LaFromboise, T., Coleman, H. L. K., and Gerton, J. (1993). Psychological impact of biculturalism: Evidence and theory. Psychological Bulletin, 114(3), 395-412. Levin, J. D. (1992). Theories of the self. Washington: Hemisphere. Lifton, R. J. (1993). The Protean self: Human resilience in an age of fragmentation. New York: Basic Books.

36

Gabriel Bukobza

Linville, P. W. (1987). Self-complexity as a cognitive buffer against stress- related illness and depression. Journal of Personality and Social Psychology, 52(4), 663-676. Linville, P. W., and Carlston, D. E. (1994). Social cognition of the self. In P. G. Devine, D. L. Hamilton, and T. M. Ostrom (Eds.), Social cognition: Impact on social psychology. (pp. 143-193). San Diego: Academic Press. Loevinger, J. (1976). Ego development: Conceptions and theories. San Francisco: JosseyBass. Lomranz, J. (1998). An image of aging and the concept of Aintegration. In J. Lomranz (Ed.), Handbook of aging and mental health: An integrative approach. (pp. 217-250). New York: Plenum Press Lovejoy, A. O. (1960). The great chain of being: A study of the history of an Idea. New York: Harper and Row. (Original published 1936). Marcuse, H. (1954). Reason and revolution: Hegel and the rise of social theory. New York: The Humanities Press. Mansfield, A. F. and Clinchy, B. M. (2002). Toward the integration of objectivity and subjectivity: Epistemological development from 10 to 16. New Ideas in Psychology, 20, 225-262. Markus, H., and Wurf, E. (1987). The dynamic self-concept: A social psychological perspective. Annual Review of Psychology, 38, 299-337. Medin, D. L. (1989). Concepts and conceptual structure. American Psychologist, 44(12), 1469-1481. Mandelbaum, M. (1982). Subjective, objective, and conceptual relativism. In J. W. Meiland, and M. Krausz (Eds.), Relativism: Cognitive and moral. (pp. 4-61). University of Notre Dame Press. Miller, M. E. (1994). World Views, ego development, and epistemological changes from the conventional to the Postformal: A longitudinal perspective. In M. E. Miller, and S. R. Cook-Greuter (Eds.), Transcendence and mature thought in adulthood. (pp. 147-179). Lanham: Rowman and Littlefield. Moghaddam, F. M., Taylor, D. M., and Lalonde, R. N. (1987). Individualistic and collective integration strategies among Iranians in Canada. International Journal of Psychology, 22, 301-313. Moshman, D. (1999). Adolescent psychological development: Rationality, morality, and identity. Mahwah, NJ: Erlbaum. Neisser, U. (1988). Five kinds of self-knowledge. Philosophical Psychology, 1(1), 35-59. Nisan, M. (1995). Moral balance: A model for moral choice. In W. M. Kurtines, and J. L. Gewirtz (Eds.), Moral development: An introduction. (pp. 475- 492). Needham Heights: Allyn and Bacon. Nisan, M. and Applebaum, B. (1995). Maintaining a balanced and respectable identity: Moral choice in late adulthood. In G. Ben-Shakhar, and A. Lieblich (Eds.), Studies in psychology in honor of Solomon Kugelmass. (pp. 139-152). Jerusalem: The Magnes Press. Peng, K., and Nisbett, R. E. (1999). Culture, dialectics, and reasoning about contradiction. American Psychologist, 54(9), 741-754. Pepper, S. C. (1942). World hypotheses: A study in evidence. Berkeley: University of California Press.

The Development of Epistemic Complexity in Adulthood

37

Perry, B., Donovan, M. P., Kelsey, L. J., Paterson, J., Statkiewicz, W., and Allen, R. D. (1986). Two schemes of intellectual development: A comparison of development as defined by William Perry and Jean Piaget. Journal of Research in Science Teaching, 23(1), 73-83. Perry, W. G. (1970). Forms of intellectual and ethical development in the college years: A scheme. New York: Holt, Rinehart and Winston. Perry, W. G. (1981). Cognitive and ethical growth: The making of meaning. In A. Chickering (Ed.), The modern American college. (pp. 76-116). San Francisco: Jossey-Bass. Phinney, J. S. (1989). Stages of ethnic identity development in minority group adolescents. Journal of Early Adolescents, 9(1), 34-49. Phinney, J. S. (1990). Ethnic identity in adolescents and adults: Review of research. Psychological Bulletin, 108(3), 499-514. Phinney, J. S. (2000). Identity formation across cultures: The interaction of personal, societal, and historical change. Human Development, 43, 27-31. Phinney, J. S., and Chavira, V. (1992). Ethnic identity and self-esteem: An exploratory longitudinal study. Journal of Adolescence, 15, 271-281. Piaget, J. (1952). The origins of intelligence in children. New York: International University Press. (Original published 1936). Piaget, J. (1954). The construction of reality in the child. New York: Basic Books. (Original published 1937). Piaget, J. (1970). Genetic epistemology. New York: Columbia University Press. Piaget, J. (1980). Experiments in contradiction. Chicago: University of Chicago Press. (Original published 1974). Richards, F. A., and Commons, M. L. (1984). Systematic, Metasystematic, and crossparadigmatic reasoning: A case for stages of reasoning beyond formal operations. In M. C. Commons, F. A. Richards, and C. Armon, (Eds.) Beyond formal operations: Late adolescence and adult cognitive development. (pp. 92-119). New York: Praeger. Riegel, K. F. (1973). Dialectic operations: The final period of cognitive development. Human Development, 16, 346-370. Riegel, K. F. (1975). Toward a dialectical theory of development. Human Development, 18, 50-64. Ross, M. (1989). Relation of implicit theories to the construction of personal histories. Psychological Review, 96(2), 341-357. Rosenzweig, F. (1985). The star of redemption. University of Notre Dam Press. (Original published 1921). Sande, G. N., Goethals, G. R., and Radloff, C. E. (1988). Perceiving one’s own traits and other’s: The multifaceted self. Journal of Personality and Social Psychology, 54(1), 1320. Sayegh, L., and Lasry, J. C. (1993). Immigrants’ adaptation in Canada: Assimilation, acculturation, and orthogonal cultural identification. Canadian Psychology, 34(1), 98109. Schommer, M. (1990). Effects of beliefs about the nature of knowledge on comprehension. Journal of Educational Psychology, 82(3), 498-504. Schommer, M. (1993). Epistemological development and academic performance among secondary students. Journal of Educational Psychology, 85(3), 406-411.

38

Gabriel Bukobza

Schommer, M. (1994). Synthesizing epistemological belief research: Tentative understanding and provocative confusions. Educational Psychology Review, 6(4), 293-319. Schroeder, D. J. (1983). The adjective generation technique: Consistency of self-description in psychiatric patients. Journal of Personality, 51(4), 631- 639. Sheldon, K. M., Ryan, R. M., Rawsthorne, L. J., and Ilardi, B. (1997). Trait self and true self: Cross-role variation in the big-five personality traits and its relations with psychological authenticity and subjective well-being. Journal of Personality and Social Psychology, 73(6), 1380-1393. Sinnott, J. D. (1981). The theory of relativity: A Metatheory for development? Human Development, 24, 293-311. Sinnott, J. D. (1998). The development of logic in adulthood: Postformal thought and its applications. New York: Plenum. Souvaine, E., Lahey, L. L., and Kegan, R. (1990). Life after formal operations: Implications for a psychology of the self. In C. N. Alexander, and E. J. Langer (Eds.), Higher stages of human development (pp. 229-257). Oxford: Oxford University Press. Storr, A. (1972). The dynamics of creation. New York: Atheneum. Tolman, C. (1981). The metaphysic of relations in Klaus Riegel’s ‘Dialectics’ of human development. Human Development, 24, 33-51. Tolman, C. (1983). Further comments on the meaning of ‘Dialectics’. Human Development, 26, 320-324. Tzuriel, D., and Klein, M. M. (1977). Ego identity: Effects of ethnocentrism, ethnic identification, and cognitive complexity in Israeli, Oriental, and western ethnic groups. Psychological Reports, 40, 1099-1110. Tillich, P. (1951). Systematic theology, (Vol. 1). University of Chicago Press. Vygotsky, L. (1978). Mind in society. Cambridge: Harvard University Press. Williams, B. (1972). Morality: An introduction to ethics. New York: Harper and Row. Wilber, K. (2000). Integral psychology: Consciousness, spirit, psychology, therapy. Boston: Shambhala. Wilson, E. O. (1998). Consilience: The unity of knowledge. New York: Vintage Books. Wurzel, J. S. (1988). Toward multiculturalism: A reader in multicultural education. Yarmouth: Intercultural Press. Yardley, K., and Honess, T. (Eds.). (1987). Self and identity: Psycho-social serspectives. New York: John Wiley and Sons. Zak, I. (1976). Structure of ethnic identity of Arab-Israeli students. Psychological Reports, 38, 239-246.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 2

THE ROLE OF OMEGA-3 FATTY ACIDS IN THE PREVENTION AND TREATMENT OF NEUROPSYCHIATRIC AND NEURODEVELOPMENTAL DISORDERS Sa’eed Bawa Warsaw University of Life Sciences, Faculty of Human Nutrition and Consumer Sciences, Department of Dietetics, Nowoursynowska Street 159C, PL-02776 Warsaw, Poland

ABSTRACT Dietary factors may, to some extent, be responsible for the increase in the incidence of neuropsychiatric and neurodevelopmental disorders in Western societies and in some developing countries. One factor that may be particularly important is the high level of the consumption of omega-6 fatty acids compared with omega-3 fatty acids. Anthropological data suggest that the intake of omega-6 and omega-3 fatty acids during the Palaeolithic age was almost the same, but the present omega-6 to omega-3 fatty acids ratio in Western diets has been estimated to be between 10 and 25 to 1. Even in Japan, where seafood has traditionally been consumed at very high levels, the ratio of omega-6 to omega-3 fatty acids is increasing as diets become more westernized, leading some authors to suggest that fish consumption be increased, particularly amongst young people. The omega-6 to omega-3 PUFA imbalance has been brought primarily by the increase in vegetable and seed oil use, and a decrease in fish or fish oil intake. Fats constitute sixty percent of the brain and nerves that are responsible for running every system in the human organism. Omega-3 fatty acids (α-linolenic, eicosapentaenoic, docosahexaenoic) play an important role in the development and function of the central nervous system. Epidemiological data suggest that there is a link between the development of neurodevelopmental disorders, such as dyslexia, dyspraxia, attentiondeficit hyperactivity disorder and autistic spectrum disorders as well as neuropsychiatric disorders, such as major depression, dementia, schizophrenia and Parkinson’s disease and the consumption of fish. There are several mechanisms, whereby omega-3 fatty acids may decrease the risk of neurodevelopmental and neuropschiatric abnormalities. Omega-

40

Sa’eed Bawa 3 fatty acids are an essential component of CNS membrane phospholipid acyl chains and are therefore critical to the dynamic structure and function of neuronal membranes. Omega-3 fatty acids can alter membrane fluidity by displacing cholesterol from the membrane and optimal fluidity, influenced by essential fatty acids, is required for neurotransmitter binding and the signaling within the cell. Essential fatty acids, especially of the omega-3 family can act as sources for second messengers within and between neurons. Omega-3 fatty acids may exert significant influence in major depression via cytokine modulation. Although, epidemiological and clinical data have shown beyond reasonable doubts the significance of omega-3 fatty acids in the prevention of cardiovascular and neurodegenerative diseases, the focus of this chapter is to demonstrate the role of omega-3 fatty acids in the prevention and management of neuropsychiatric and neurodevelopmental disorders.

INTRODUCTION Depression is one of the most common mental health problems in the general population. The World Health Organization estimates that major depressive disorders will become the second leading cause of disability worldwide by the year 2020, after ischaemic heart disease [1]. In the report titled ‘The Global Burden of Disease’, Murray and Lopez comprehensively assessed the mortality and disability from all diseases, injuries and risk factors using inclusive methodological approaches [1]. The summary of this landmark study highlighted the finding that ‘the burden of mental illnesses, such as mood disorders, alcohol and drug dependence and schizophrenia have previously been seriously underestimated by approaches that focus on mortality, rather than morbidity and mortality [1]. There has been an association between depression and nutrition since the first emergence of mood disorders. This association has persisted over the centuries and is now reflected in the great deal of research investigating the links between dietary components and the development and treatment of depression. The majority of the research explores the biological changes seen in depression and the potential for nutrients to exert beneficial effects on modulating or correcting such biochemical imbalances. Epidemiological data suggests that there is a link between depression and fish consumption, and although it is true that correlation is not causation, there is evidence that fish and fish oils may be protective against depression. Omega-3 fatty acids are long-chain, polyunsaturated fatty acids (PUFA) of plant and marine origin. Because these essential fatty acids cannot be synthesized by the human body (due to lack of the enzymes Δ-12 and Δ-15 desaturase), they must be derived from dietary sources. Flaxseed, hemp, canola and walnut oils are all generally rich sources of the parent omega-3, that is, α-linolenic acid (ALA). Dietary ALA can be metabolized in the liver to the longer-chain omega-3 eicosapentaenoic (EPA) and docosahexaenoic acid (DHA). This conversion is limited in human beings, it is estimated that only 5-15% of ALA is ultimately converted to DHA [2]. Aging, stress, smoking, excess intakes of omega-6 fatty acids (corn, safflower, sunflower, and cottonseed), alcohol abuse as well as diseases, such as diabetes mellitus can all compromise conversion [3].

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

41

DIETARY SOURCES OF OMEGA-6 AND OMEGA-3 FATTY ACIDS, RECOMMENDATIONS AND THEIR METABOLISM There has been a dramatic surge in interest recently, amongst the public and health professionals alike, of the health effects of omega-3 fatty acids derived from fish and fish oils - consisting of highly unsaturated fatty acids (HUFA), DHA as well as EPA. DHA is required in high levels in the brain and retina as a physiologically essential nutrient to provide for optimal neuronal functioning (learning ability, mental development) and visual acuity, in young and old alike. DHA plus EPA are both considered to have beneficial effects in the prevention and management of cardiovascular disease plus associated risk factors as well as other chronic disorders. Whereas considerable amounts of the plant-derived omega-3 fatty acid known as α-linolenic acid (ALA) is consumed daily in North America and Europe (approximately 2 g/day), the physiologically essential nutrient, DHA is consumed at much smaller levels (approximately 80 mg/day) while EPA is consumed at the level of approximately 50 mg/day in a typical North American diet. DHA plus EPA are absent from plant food sources rich in ALA (such as flax, canola oil, and walnuts). Since the metabolic conversion of ALA to DHA/EPA (combined) by metabolism is very limited in humans, the most direct way of providing DHA plus EPA for the body is via their direct consumption. Current intakes of DHA are approximately 20% of the target (300 mg/day) suggested by an expert scientific group during pregnancy and lactation. The extremely low intake of DHA in young children (e.g., approximately 19 mg DHA/day on average for 3-year olds in North America) is also of particular concern. Current intakes of DHA/EPA (combined) of 130 mg/day are approximately 15% of the target (900 mg/day) officially recommended by the American Heart Association for those with coronary heart disease and 20% of the 650 mg/day advised by an expert scientific group for healthy individuals. In view of the widespread reluctance of the public to consume sufficient amounts of fish, functional foods containing DHA plus EPA will become increasingly important sources of these important nutrients in the coming years to support optimal brain, visual and visual performance as well as to prevent cardiovascular diseases and mental disorders. The recommended minimal intake for omega-3 fatty acid in the form of ALA has been set at 0.5% of total energy in different countries. This translates into recommended intakes for ALA of 0.5 gm/day (as example) of 1.2-1.4 grams for children aged 10-12 years (male and female respectively) and 1.1-1.5 gm/day for 25-49 year old adults (female and male, respectively). These old recommendations have recently been applied and slightly modified by the Food and Nutrition Board in the United States [4]. They established recommended Adequate Intakes (AI values) for ALA are presented in Table 1. The term AI refers to the recommended average daily intake level based on observed or experimentally determined approximations or estimates of nutrient intake via a group (or groups) of apparently healthy people that are assumed to be adequate - used when an RDA (recommended dietary allowance) cannot be determined. Current mean estimates of ALA (omega-3) in a North American and European adult population have been reported to range from approximately 1.3-2.5 gm/day with approximately 40-50% derived mainly from ALA. It is noteworthy, recommendations allow for up to 10% of the Adequate Intakes for ALA (omega-3) to be in the form of the longer-chain derivatives as DHA plus EPA. However, no obligatory intakes of DHA and/or EPA were established in these recommendations.

42

Sa’eed Bawa Table 1. Recommended Adequate Intakes (AI) for Omega-3 Fatty Acids [4]

Life Stages Infants Infants Children Children Children Children Adults Pregnancy Breastfeeding

Age 0-6 months 7-12 months 1-3 years 4-8 years 9-13 years 14-18 years 19 years and older All ages All ages

Males (g/day) 0.5 0.5 0.7 0.9 1.2 1.6 1.6

Females (g/day) 0.5 0.5 0.7 0.9 1.2 1.1 1.1 1.4 1.3

AMERICAN HEART ASSOCIATION SUMMARY OF RECOMMENDATIONS FOR OMEGA-3 FATTY ACID INTAKE Patients without documented coronary heart disease (CHD): -

Eat a variety of (preferably fatty) fish at least twice a week. Include oils and foods rich in alpha-linolenic acid (flaxseed, canola and soybean oils; flaxseed and walnuts).

Patients with documented CHD: -

Consume about 1 g of EPA+DHA per day, preferably from fatty fish. EPA+DHA supplements could be considered in consultation with the physician.

Patients who need to lower triglycerides: -

2 to 4 grams of EPA+DHA per day provided as capsules under a physician’s care.

Patients taking more than 3 grams of omega-3 fatty acids from supplements should do so only under a physician’s care. High intakes could cause excessive bleeding in some people. Evidence from prospective secondary prevention studies suggests that taking EPA+DHA ranging from 0.5 to 1.8 grams per day (either as fatty fish or supplements) significantly reduces deaths from heart disease and all causes. For alpha-linolenic acid, a total intake of 1.5-3 grams per day seems beneficial. Increasing omega-3 fatty acid intake through foods is preferable. However, people suffering from certain diseases and disorders, such as cardiovascular disease, schizophrenia, dementia, autisms etc. may not be able to get enough omega-3 fatty acids by diet alone. These people may consider supplementing their diets with these fatty acids, but should be accomplished under the supervision of physician. Supplements also could help people with high triglycerides, who need even larger doses. The availability of high-quality omega-3 fatty acid supplements, free of contaminants, is an important prerequisite to their use.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

43

Table 2. Amounts of ALA in selected foods Dietary source of ALA Almonds Beechnuts (dried) Butternuts (dried) Chia seeds (dried) Flaxseed Hickory nuts (dried) Mixed nuts Peanuts Pecans Soybean kernels Walnuts, black Walnuts, English and Persian Beans, navy, sprouted (cooked) Beans, pinto, sprouted (cooked) Broccoli (raw) Cauliflower (raw) Kale (raw) Leeks (freeze-dried) Lettuce, butterhead Lettuce, red leaf Mustard Purslane Radish seeds, sprouted (raw) Seaweed, Spirulina (dried) Soybeans, green (raw) Soybeans, mature seeds, sprouted (cooked) Spinach (raw) Beans, common (dry) Chickpeas (dry) Cowpeas (dry) Lentils (dry) Lima beans (dry) Peas, garden (dry) Soybeans (dry) Barley, bran Corn, germ Oats, germ Rice, bran Wheat, bran Wheat, germ Wheat, hard red Winter Avocados, California (raw) Raspberries (raw) Strawberries (raw)

Amount of ALA (g/100 g) Nuts and seeds 0.4 1.7 8.7 3.9 22.8 1.0 0.2 0.003 0.7 1.5 3.3 6.8 Vegetables 0.3 0.3 0.1 0.1 0.2 0.7 0.1 0.1 0.1 0.4 0.7 0.8 3.2 2.1 0.1 Legumes 0.6 0.1 0.3 0.1 0.2 0.2 1.6 Grains 0.3 0.3 1.4 0.2 0.2 0.7 0.1 Fruit 0.1 0.1 0.1

Adapted from: Kris-Etherton et al. [5]; USDA Nutrient Database http://www.nal.usda. gov/fnic /foodcomp/search/.

44

Sa’eed Bawa Table 3. The content of DHA and EPA in selected foods of marine origin Sources of DHA and EPA Fish Anchovy, European, raw Carp, cooked, dry heat Catfish, channel, farmed, cooked, dry heat Cod, Atlantic , cooked, dry heat Eel, mixed species, cooked, dry heat Flatfish (flounder and sole), cooked, dry heat Haddock, cooked, dry heat Halibut, Atlantic and Pacific, cooked, dry heat Herring, Atlantic , cooked, dry heat Mackerel, Pacific and jack, mixed species, cooked, dry heat Mullet, striped, cooked, dry heat Perch, mixed species, cooked, dry heat Pike, northern, cooked, dry heat Pollock, Atlantic , cooked, dry heat Salmon, Atlantic , farmed, cooked, dry heat Sardine, Atlantic , canned in oil, drained solids with bone Sea bass, mixed species, cooked, dry heat Shark, mixed species, raw Snapper, mixed species, cooked, dry heat Swordfish, cooked, dry heat Trout, mixed species, cooked, dry heat Tuna, skipjack, fresh, cooked, dry heat Whiting, mixed species, cooked, dry heat Crustaceans Crab, Alaska king, cooked, moist heat Shrimp, mixed species, cooked, moist heat Spiny lobster, mixed species, cooked, moist heat Mollusks Clam, mixed species, cooked, moist heat Conch, baked or broiled Mussel, blue, cooked, moist heat Octopus, common, cooked, moist heat Oyster, eastern, farmed, cooked, dry heat Scallop, mixed species, cooked, breaded and fried

Content of DHA and EPA (g/100 g) 1.449 0.451 0.177 0.158 0.189 0.501 0.238 0.465 2.014 1.848 0.328 0.324 0.137 0.542 2.147 0.982 0.762 0.843 0.321 0.819 0.936 0.328 0.518 0.413 0.315 0.480 0.284 0.120 0.782 0.314 0.440 0.180

Adapted from: Williams and Burdge (6); USDA Nutrient Database http://www.nal.usda.gov /fnic/foodcomp/search/

As mentioned earlier, ALA, EPA and DHA are the most common omega-3 fatty acids in the diet. Until fairly recently, the commonly accepted pathway for the metabolic conversion of ALA to DHA involved the sequential utilization of delta-6, 5-, and 4-desaturases along with elongation reactions, that is addition of 2 carbon atoms (Figure 1). It has been demonstrated, however, that the metabolism of docosapentaenoic acid (DPA; 22:5n-3) is

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

45

independent of delta-4-desaturase, and instead involves microsomal elongation of 22:5n-3 to 24:5n-3, followed by desaturation to 24:6n-3 and peroxisomal retroconversion to 22:6n-3 [1]. The conversion of ALA to LCPUFA (EPA, DPA, and DHA) is limited in humans and has been estimated to be anywhere from less than 5% to 15 [2]. Interestingly, DHA can also be “retroconverted” to EPA at rates in humans of about 10%.

Figure 1. Metabolism of omega-6 and omega-3 and the production of highly unsaturated fatty acids.

C18-C22 = number of carbon atoms; 2-6 = number of double bonds; n-6 or n-3 = position of the first double bond counting from the methyl end; desaturase: introduction of an additional double bond; elongase: elongation of the carbon chain by two units

46

Sa’eed Bawa

Dihomo-γ-linolenic acid (DGLA) and arachidonic acid (AA) from the omega-6 series, and EPA and DHA from the omega-3 series are the four HUFA that are particularly important for brain development and function. • • •

AA and DHA are major structural components of neuronal membranes (making up 20% of the dry mass of the brain and more than 30% of the retina). EPA and DGLA are also crucial, but they play functional rather than structural roles. EPA and DHA are both essential for optimal brain function, but for different reasons. DHA is important in the structure of neuronal membranes, hence adequate supplies are needed during early development to support brain growth, and throughout life to maintain membrane fluidity. EPA plays little or no structural role in the brain, but it is nonetheless essential for the moment-by-moment regulation of brain function via its eicosanoid derivatives such as prostaglandins, leukotrienes and thromboxanes.

EPIDEMIOLOGICAL INVESTIGATIONS ON THE SIGNIFICANCE OF OMEGA-3 FATTY ACIDS IN THE ETIOLOGY OF DEPRESSION Manic-depressive disease, also known as bipolar disorder is a common, severe mental disorder involving repeated episodes of depression, mania (rapid mood changes, hyperactivity, and excessive cheerfulness) or both. It is usually treated with drugs such as lithium carbonate or valproate. Unfortunately, these drugs are not very effective and recurrence rates are high. It is generally believed that bipolar disorder involves overactivity in the neuronal signal pathways. Omega-3 fatty acids are known to diminish this overactivity and the hypothesis has been advanced that they may be useful in the treatment of bipolar disorder. Studies comparing the rates of the prevalence of mood disorders in different nations show that countries with lower consumption of fish per capita have 30- to 60-fold higher rates of major depression, postpartum depression, and bipolar disorder [7]. Most studies analyzing populations within individual countries also find a higher incidence of depressive symptoms associated with lower fish consumption. In addition, some countries with high per capita seafood consumption, for example, Iceland (225 lb/person per year) and Japan (147 lb/person per year) have lower prevalence rates of seasonal affective disorder than countries at the same latitude, which get more winter sunlight but have average annual fish intakes as low as 50 to 70 lb/person [8]. Early studies demonstrate that fish and fish oils may be protective against depression, for example, Hibbeln [9, 10] compared the rates of depression in nine countries with the estimated per capita fish consumption and showed an inversely proportional relationship Western countries had an annual prevalence of depression in the range of 3-6% and a low to moderate per capita fish intake of 11-32 kg, whereas countries with high per capita fish consumption, such as Japan at 68 kg, had a depression rate of 0.12%. New Zealand with an annual fish consumption of only 40 lbs had an annual incidence rate of depression of 5.8 per cent while Korea with a fish consumption of more than 50 kg/year had an annual incidence rate of only 2.3 percent. Overall, these data suggest an 84% correlation between high fish intake and demonstrates that the risk of having depressive symptoms is significantly higher

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

47

among infrequent fish-consumers than in people who ate fish at least once per week (odds ratio = 1.31; 95% CI 1.10-1.56). Hibbeln [10] found a significant negative correlation between worldwide fish consumption and prevalence of depression. A recent cross-sectional study conducted in New Zealand found fish consumption is significantly associated with higher self-reported mental health status [11]. Hibbeln [12] found a similar negative correlation between total seafood (including shellfish) consumption and the prevalence of postpartum depression in 22 countries. Higher concentrations of DHA in mother's milk and greater seafood consumption both predicted lower prevalence of post-partum depression [12]. National per capita fish consumption has also been correlated with protection against seasonal affective disorder [13]. While this does not prove causation, and cultural, social, and economic factors are possible confounding factors, it does provide support to the notion omega-3 fatty acids might play a role in depression. The inhabitants of Greenland, generally known as the Eskimos consume extremely high levels of fish consumption. The predominant fish species in such diets are the cold-water adapted marine animals, the fat of which is uniquely rich in the long-chain omega-3 PUFA, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). This ethnic group rarely experience, in spite of the extreme climate and challenging environmental conditions [14]. Not all studies support the relationship between omega-3 intake and mood. Crosssectional study of male smokers, using data collected between 1985 and 1988, demonstrated that subjects reporting anxiety or depressed mood had higher intakes of both omega-3 and omega-6 fatty acids [15]. In a large population-based study of older males aged 50-69 years, there was no relation between the intakes of omega-3 fatty acids from the diet or fish consumption and depressed mood, major depressive episodes, or suicide [16]. A large study carried out in 29 133 Finnish men aged 50-69 years did not show any relationship between dietary intake of omega-3 PUFA or fish consumption and lowered mood or major depressive episodes [17]. Epidemiological data that support the relationship between fish ingestion and depression obviously do not prove causation. There are a number of factors that may confound the results of these studies, including cultural, economic and social factors. Just like vegetarians, people who consume more fish may generally have healthier lifestyle habits, including exercise and stress management. Despite the limitations, the epidemiological data certainly justify a closer examination of omega-3 fatty acids in those actually with depression.

OMEGA-3 FATTY ACIDS AND POST-PARTUM DEPRESSION Women experience their highest risk of having a depressive episode during pregnancy and following childbirth. Up to 70% of new mothers notice a transient change in their mood, usually describing themselves as being more anxious, tearful, irritable and emotional than normal, in the days following childbirth [18]. Research suggests that the incidence and prevalence of antenatal depression are similar or equivalent to those of the postnatal period, with the rate of antenatal depression showing an increase in the past decade [19]. Relationships between omega-3 status and post-partum depression have also been investigated. In a cohort of 380 Australian women, plasma DHA was investigated at 6 months post-partum. Logistic regression analysis indicated that a 1% increase in plasma DHA was

48

Sa’eed Bawa

associated with a 59% reduction in the reporting of depressive symptoms [20]. It is well known that during pregnancy there is a significant transfer (up to 2.2 g/day) EFAs to the developing fetus [21]. Increased risk of post-partum depressive symptoms has recently been associated with a slower normalization of DHA levels after pregnancy [22]. Suicide attempts have also been associated with low levels of RBC EPA. In a study involving 100 suicide attempt cases in China compared to 100 hospital admission controls, there was an eightfold difference in suicide attempt risk between the lowest and highest RBC EPA level quartiles [23]. The seasonality of depression and suicide has been described by investigators, with more deaths in spring and summer vs. autumn and winter. Total serum cholesterol has been highly significantly synchronized with the annual rhythms in violent suicide deaths [24]. Recently, investigators found that EFA levels also vary by season, with peaks of EPA and DHA from August to September. The parent omega-3 and 6 levels did not have a seasonal variation, suggesting a seasonal interference with delta-5-desaturase conversion. The authors of this study suggest that the seasonal variation in EPA or DHA may, in part, explain seasonality of violent suicide occurrence [25]. The overlap between cardiovascular disease and depression has also been noted, with omega-3 status emerging as a common thread. Indeed, major depression in acute coronary syndrome patients is associated with significantly lower plasma levels of omega-3 fatty acids, particularly DHA [26]. In addition, elevated homocysteine levels, a known risk factor for cardiovascular disease, has been associated with the excess omega-6 fatty acids found in the Western diet [27]. Finally, lowered intake of the parent omega-3 ALA has been associated with depression in 771 Japanese patients with newly diagnosed lung cancer [28]. It is important to note that not every study supports an association between lowered omega-3 status and depression. Two studies have actually shown significant increases in plasma and RBC omega-3 status among depressed patients [29, 30]. A recent study involving depressed adolescent patients found no significant relationship between adipose tissue EFA levels and depression [31].

TISSUE STUDIES EXAMINING THE RELATIONSHIP BETWEEN OMEGA3 INTAKE AND MAJOR DEPRESSIVE DISORDERS Several studies have found lower levels of omega-3 fatty acids in the blood or fat tissue of subjects with major depressive disorder than in controls [7, 32-35]. There are a number of methods used to assess essential fatty acid status in human tissues, particularly the plasma and red blood cell (RBC) phospholipids. The Plasma and RBC phospholipids content of essential fatty acids reflect their intakes within the preceding few weeks. Some studies show the existence of significant correlations between blood and brain phospholipids. A number of studies have found decreased omega-3 content in the blood of depressed patients [21-24]. Furthermore, the EPA content in RBC phospholipids is negatively correlated with the severity of depression, and the omega-6 arachidonic acid to EPA ratio positively correlates with the clinical symptoms of depression [36]. More recently, investigators have been utilizing adipose tissue as a longer term measurement of EFA intake (1-3 years). In a study of 150 elderly males from Crete, the

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

49

parent omega-3 ALA adipose tissue stores were negatively correlated with depression [36]. A separate study found a negative correlation between adipose tissue DHA and rates of depression. In this case, mildly depressed adults had 34.6 percent less DHA in adipose tissue than nondepressed subjects [37]. While this suggests an association between the two conditions, this kind of study cannot determine whether the low levels occurred before or after a person became depressed nor what caused them. Having a psychiatric disorder may influence a person’s eating habits and therefore cause low levels of omega-3 fatty acids through dietary choices. Also, genetic factors may influence how fatty acids are metabolized, degraded, or oxidized in patients with psychotic or affective disorders. Smoking may also lower omega-3 fatty acids levels. Smokers have lower levels of omega-3 fatty acids than nonsmokers, and there is a higher incidence of smoking among patients with psychiatric disorders than in the general population. The severity of psychiatric symptoms may influence diet, smoking, and self-care. Conversely, poor nutrition may contribute to the aggravating symptoms.

CLINICAL AND INTERVENTION STUDIES The epidemiological and laboratory studies as well as investigations which demonstrate that depressed patients appear to have lower omega-3 status have led scientists to conduct clinical studies. For the past 20 years there have been a number of case reports, in which flaxseed oil (source of the parent omega-3 ALA) at various dosages, was reported to improve the symptoms of bipolar depression and agoraphobia [38]. An additional case report documented an improvement in depressive symptoms during pregnancy with the use of 4 g EPA/2 g DHA per day. Interestingly, improvements in symptoms (measured via the Hamilton Rating Scale for depression – HRDS) occurred at four weeks, and with the exception of insomnia and anxious thoughts, all symptoms resolved at six weeks [39]. Despite the interesting results, there are major scientific problems with case reports, most notably the placebo response. A recently published case report published took advantage of modern brain imaging to corroborate clinical improvements. In this case a patient with treatment resistant depression was placed on a daily dose of 4 g pure EPA, and after one month there were significant improvements, including a co-morbid social phobia. After nine months the patient was reportedly symptom free. It was found that over the course of the nine months of treatment, there was a 53 percent increase in cerebral phosphomonoesters and the ratio of cerebral phosphomonoesters to phosphodiesters increased 79 percent, indicating reduced neuronal phospholipid turnover. Utilizing MRI technology, the researchers found that the EPA treatment was associated with structural brain changes, including a reduction in lateral ventricular volume. This is likely to be a result of increased phospholipids biosynthesis and reduced phospholipid breakdown [40]. Given the recent research indicating a decrease in volume in various areas of the brain of depressed patients, this is certainly an important case study [41]. A series of case reports also suggest that 1-4 g of pure EPA may be helpful in anorexia nervosa, a condition with the highest risk of morbidity and mortality among psychiatric disorders [42]. In all six of the cases, EPA was reported to improve mood to varying degrees.

50

Sa’eed Bawa

For some, discontinuing EPA therapy resulted in deteriorations in mood and other psychiatric symptoms. An interesting study examined fish oil vs. marine oil extracted from Antarctic krill in premenstrual syndrome. Krill is similar to fish oil, with the exception that it contains naturally-occurring phospholipids, and contains more EPA per gram than standard fish oil capsules (240 mg/g EPA in krill vs.180 mg/g in standard fish oil). In the 3-month trial, patients (n = 70) received 2 g of krill oil or 2 g fish oil daily for one month, then for eight days prior to, and two days during, menstruation for the following two months. Evaluation at 45 days and three months showed that krill oil significantly improved depressive symptoms of premenstrual syndrome. The absence of significant effects of fish oil on mood suggests that the presence of the phospholipids and/or higher amounts of EPA may be responsible for the therapeutic effect of krill oil [43]. There have been some controlled studies that have examined omega-3 fatty acids and a placebo intervention in depression. Harvard Medical School researchers [44] carried out a double-blind, placebo-controlled study involving 30 patients (men and women 18 to 65 years of age) who had all been diagnosed with bipolar disorder. Half the patients were given seven fish oil capsules twice a day while the placebo group was given seven olive oil capsules twice a day. Each fish oil capsule contained 440 mg of eicosapentaenoic acid and 240 mg of docosahexaenoic acid. All of the participants except four in the fish oil group and four in the placebo group also continued to receive a standard mood stabilizing drug prescribed previously. The mental state of the participants was measured using four scales (Clinical Global Impression Scale, Global Assessment Scale, Young Mania Rating Scale, and the Hamilton Rating Scale for Depression) at the start of the study and after two, four, six, eighth, twelve and sixteen weeks. Twelve of the 14 participants in the fish oil group completed the four-month study without major episodes of mania or depression as compared to only six out of 16 participants in the placebo group. Also, while nine of the placebo group members experienced worsening depression none of the fish oil group members did. The four patients in the fish oil group who had not been prescribed mood-stabilizing drugs all completed the study without major episodes, but only one member in the placebo group not on moodstablizing drugs did. The average decline in depression rating on the Hamilton Scale was almost 50 per cent in the fish oil group as compared to an increase of 25 per cent in the control group. The Harvard researchers urge further trials of fish oils in the treatment of depression and manic-depressive illness. In a separate double-blind, placebo-controlled study (n = 22), the addition of 2 g of pure EPA to standard antidepressant medication enhanced the effectiveness of that medication vs. medication and placebo. This 3-week study, involving patients with treatment-resistant depression, showed that EPA had an effect on insomnia, depressed mood, and feelings of guilt and worthlessness. There were no clinically relevant side effects noticed [45]. Zanarini et al. [46] performed a double-blind, placebo-controlled pilot study in women with borderline personality disorder and found out that 90 percent of participants remained in the study and no clinically relevant side effects were noticed with EPA. In a double-blind, placebocontrolled trial over two months, high dose fish oil (9.6 g/day) was added to standard antidepressant therapy in 28 patients with major depressive disorders. In this study the patients who received the omega-3 fish oil capsules had a significantly decreased score on the HRSD compared to those taking the placebo. Once again, the fish oil, even at this high dose, was well tolerated with no adverse events reported [47].

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

51

Various doses of pure EPA have also been investigated in depression. In a 12-week, randomized, double-blind, placebo-controlled study, patients (n = 70) were given ethyl- EPA at doses of 1 g, 2 g or 4 g. The patients in this case had experienced persistent depression, despite ongoing standard antidepressant pharmacotherapy at adequate does. Interestingly, in this study, "less was more." Those in the 1 g per day group had the best outcome. The patients who received 1 g per day of EPA were the only group to show statistically significant improvements. Among the 1 g/day group, 53 percent achieved a 50 percent reduction in HRSD scores. The 1 g EPA led to improvements in depression, anxiety, sleep, lassitude, libido, and suicidal ideation. These findings suggest that omega-3 fatty acids can augment antidepressant pharmacotherapy and/or alleviate depression by entirely different means than standard medications [48]. A large study examining the effects of omega-3 or placebo added to cognitive-behavior therapy would be of interest. To date, the published data on supplementation with pure EPA on major depressive disorders or depressive symptoms have been positive. With regard to DHA or a combination of EPA and DHA, there have been three negative reports. A trial on DHA alone as monotherapy in the treatment of major depressive diosrders was recently reported. In this study, 2 g pure DHA or placebo was administered to 36 patients with depression for six weeks. The response differences between the groups, as measured by scores on the Montgomery-Asberg Depression Rating Scale did not reach statistical significance [49]. In an open label pilot study, the combination of 1.7 g of EPA and 1.2 g of DHA failed to show benefits among seven women with a past history of post-partum depression. The omega-3 monotherapy was initiated between the 34th-36th week of pregnancy and was assessed through 12 weeks post-partum. In these women the fish oil combination did not reduce the risk of relapse [50]. Finally, a pure DHA supplement, at low doses of 200 mg per day for 4 months postpartum, did not improve selfrated or diagnostic measures of depression over placebo. However, the women enrolled (n = 89) in this study were not clinically depressed as a group, which precludes interpretation that DHA is ineffective in post-partum depression [51].

POSSIBLE MECHANISMS, WHEREBY OMEGA-3 FATTY ACIDS ALLEVIATE THE SYMPTOMS OF DEPRESSION Detailed mechanisms, whereby omega-3 fatty acids decrease the risk of different types of depression can be found in some review papers and therefore are beyond the scope of article [52, 53]. Due to its complexity, the impact of omega-3 fatty acids in the central nervous system has not been fully elucidated and our knowledge of the action of these fatty acids is mainly based on the result of their deficiency in animal models. However, it is worth mentioning that omega-3 fatty acids are an essential component of CNS membrane phospholipid acyl chains and are therefore critical to the dynamic structure and function of neuronal membranes [54]. Proteins are deposited in the lipid bilayer of the cell and the conformation or quaternary structure of these proteins is sensitive to the lipid components. The proteins in the bilayer have critical cellular functions as they act as transporters and receptors. Omega-3 fatty acids can alter membrane fluidity by displacing cholesterol from the

52

Sa’eed Bawa

membrane [55]. An optimal fluidity, influenced by omega-3 essential fatty acids, is required for neurotransmitter binding and the signaling within the cell [56]. Essential fatty acids, particularly from the omega-3 family can act as sources for second messengers within and between neurons [52]. Another mechanism, whereby omega-3 fatty acids decrease the risk of depression is via their anti-inflammatory activity. A growing body of research has documented an association between depression and the production of proinflammatory immune chemicals, including cytokines, among others interleukin-1 beta (IL-1α), -2 and -6, interferon-gamma, and tumor necrosis factor alpha (TNF-α), which have direct and indirect effects on the CNS. Some of the documented activities of these cytokines include lowering neurotransmitter precursor availability, activation of the hypothalamic-pituitary axis, and alterations of the metabolism of neurotransmitters and neurotransmitter mRNA [57]. Researchers have demenostrated that elevations of IL-1α, and TNF-α are associated with the severity of depression [58]. Psychological stress can cause an elevation of these cytokines. It is worth noting that various tricyclic and selective serotonin reuptake inhibiting antidepressants can inhibit the release of these inflammatory cytokines [57]. Omega-3 fatty acids and EPA in particular, are well documented inhibitors of proinflammatory cytokines such as IL-1α and TNF-α. In addition, it has recently been suggested that the anti-inflammatory role of omega-3 fatty acids may influence brain derived neurotrophic factor (BDNF) in depression [53]. BDNF is a polypeptide that supports the survival and growth of neurons through development and adulthood. Serum BDNF has been found to be negatively correlated with the severity of depressive symptoms [59]. Antidepressant medications and voluntary exercise can enhance BDNF, while diets high in saturated fat and sucrose, and psychological stress inhibit BDNF production [53].

OMEGA-3 FATTY ACIDS AND SCHIZOPHRENIA Schizophrenia is best described as a group of psychotic disorders whose symptoms include altered perceptions of reality. These altered perceptions can include delusions (fixed, unchallengeable, false opinion or beliefs) and hallucinations (seeing, hearing, or smelling things that are not actually present). People with schizophrenia also have illogical thinking patterns, and often have behavioral, emotional or intellectual disturbances. People who have schizophrenia may show very little emotion and appear apathetic and disconnected from the world around them. They may also have problems with memory and attention. Unlike some other conditions, such as anxiety or depression, there is no single complementary alternative medicine (CAM) or treatment for Schizophrenia. There is strong evidence (Category B = this complimentary medicine has at least some clinical studies in humans to support their use along with a long history of traditional use. it can be recommended for use on the basis of its traditional use and its relative safety) from research for the use of Omega-3 fatty acids as a supplement, but oils containing these fatty acids can not be used as the sole treatment for schizophrenia.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

53

Figure 3. Antiinflammatory effects of EPA; decrease in a process or parameter [57].

Clinical studies carried out in patients with schizophrenia have shown an increase in the breakdown of phospholipids, which particularly affects arachidonic acid metabolism leading to the deficiency of essential fatty acids [60]. Several studies have shown reduced levels of n-3 and n-6 PUFA in cell membranes from erythrocytes [61-63], fibroblasts [64] and brain [65] in schizophrenic patients. However, most of the studies are confounded by the possible effects of medication, smoking and other factors, so further studies are required. Although schizophrenia is remarkably consistent in incidence in different countries, there are variations in outcome, such that developing countries have a better long-term outcome of schizophrenia than western developed countries. This finding has never been satisfactorily explained and is usually assumed to be related to cultural differences. However, an epidemiological study found that international variations in the outcome of schizophrenia, showed a strong correlation with the relative amounts of saturated and unsaturated fats in the national diet, such that eating relatively more unsaturated and less saturated fats was associated with a better outcome [66]. Mellor et al. [67] as well as Peet et al. [68] have found within a group of schizophrenic patients, that those who consumed more n-3 PUFA in their normal daily diet had less severe schizophrenic symptoms. In their study with omega-3 fatty

54

Sa’eed Bawa

acid supplementation, Mellor et al. [67] found a significant improvement in schizophrenic symptomology, and a striking improvement in tardive dyskinesia, a movement disorder which can occur in untreated schizophrenic patients but which can be worsened by long term treatment with conventional antipsychotic drugs. This effect on tardive dyskinesia is of particular interest because this movement disorder appears to be a manifestation of the fundamental neuropsychological deficit in schizophrenia [69]. In another study, Peet et al. [70] attempted to distinguish between the possible clinical effects of EPA and DHA by comparing an EPA enriched oil, DHA enriched oil and a corn oil placebo given in addition to existing antipsychotic medication for three months. The subjects were 45 outpatients who were still significantly symptomatic despite stable antipsychotic medication, which was considered optimal by the treating psychiatrist. Improvement in the EPA group was significantly superior to that in the DHA group, and EPA was also superior to placebo on a secondary analysis based on percentage improvement. All patients treated with EPA improved, and half of them improved more than 25% on the total positive and negative syndrome scale (PANSS). Pete et al. [71] carried out a multi centre study in the UK in a group of 115 patients, who were given one, two or four grams of ethyl EPA or placebo in addition to their background antipsychotic medication which was either typical antipsychotic drugs, atypical antipsychotics or clozapine. The distinction between different types of antipsychotic is important because the older ‘typical’ drugs cause extrapyramidal side-effects, the newer ‘atypical’ antipsychotics are much less likely to cause this type of side effect, and clozapine is unique because it has greater efficacy than other antipsychotic drugs for reasons which are not understood. All patients were highly symptomatic at the start of the study. Patients on a background medication of clozapine showed a clear and highly significant benefit relative to placebo from having ethyl EPA added to their treatment regime, with an average improvement of 25% in PANSS rating scale scores. Depression ratings also improved. In contrast there was a large placebo effect but no additional benefit when ethyl EPA was added to other antipsychotic agents. It was found that the 2 g dose was the most effective and that the effect decreased at the higher 4 g dosage. We measured changes in erythrocyte membrane fatty acids. There was a dose related increase in membrane levels of EPA, which indicates compliance with treatment. With the two-gram dose, not only EPA but also DHA and AA showed a significant increase in clozapine-treated patients. Multiple regression analysis across all treatment groups and background medications indicated that the rise in AA predicted clinical improvement but changes in DHA or EPA did not relate to clinical change. All these studies demonstrate the usefulness of omega-3 supplementation along with antioxidants in improving related psychopathology of schizophrenia. Arvindakshan et al. [72] conducted research in a group of 33 schizophrenic patients, whose diet was supplemented with a mixture of EPA/DHA (180:120 mg) and antioxidants (vitamin E/C, 400 IU:500 mg) given orally in the mornings and evenings for the period of 4 months. Post-treatment levels of essential fatty acids in red blood cells were significantly higher than pretreatment levels as well as levels in normal controls without any significant increase in plasma peroxides. Parallel to this, there was significant reduction in psychopathology based on reduction in individual total scores for brief psychiatric rating scale (BPRS) and PANSS, general psychopathology-PANSS and increase in Henrich’s Quality of Life (QOL) Scale. The essential fatty acid levels returned to pretreatment levels after 4 months of supplementation washout. However, the clinical improvement was significantly retained.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

55

In spite of the promising results of many studies, a recent Cochrane meta-analysis preformed by Joy et al. [73] failed to include more than 6 studies, and the benefits of adjunctive omega-3 use in psychiatry are more established for mood disorders than schizophrenia [74]. However, because Omega-3 supplements might help reduce impulsive and aggressive behaviors in persons with and without major mental disorder [75, 76], it seems reasonable to recommend higher consumption foods rich in omega-3. In fact, preliminary results of ongoing studies have shown less violence in schizophrenic patients receiving capsules of omega-3 fatty acids [77]. In this study lasting 12 weeks, 12 violent male inpatients with chronic schizophrenia without diabetes received capsules of Omega-3 (400 mg EPA/200 mg DHA, 3 times daily before each meal and daily vitamin E at the dose of 400 IU. The number of pro re nata (PRN) administrations of anxiolytic medication (an index of agitation; average of 32.7 vs. 22.6; paired t = 2.87, p = 0.015) and the mean score at the Brief Psychiatric Rating Scale (47.3 vs. 43.4, paired t = 3.26, p < 0.01) had significantly decreased at the end of this period compared with day 1, while the score of the Global Assessment of Functioning scale significantly increased (33.8 vs. 37.6; paired t = 2.79, p = 0.018). The glycaemia index also significantly increased (4.9 vs. 5.4; paired t = 3.19, p < 0.05). While the Clinical Global Impression index tended to improve (5.8 vs. 5.5; paired t = 2.15, p = 0.054), body weight and cholesterol (both HDL and LDL) and triglyceride levels did not change significantly (although a trend was observed for a diminution in total cholesterol levels with p = 0.099). No significant side effects, such as gastro-intestinal complaint or lower glucose blood level have been noted so far, but participants experienced unpleasant fishy taste. These pilot data suggest that nutritional supplement including Omega-3 might facilitate reduction of agitation and psychopathology among inpatients with schizophrenia. Future studies need to be done in placebo-controlled trials and also with a comparison group supplemented with fatty acids alone in a larger number of patients, both chronic as well as never medicated, and for a longer duration of treatment while the dietary intake is monitored. This may establish the essential fatty acid supplementation a very effective treatment to improve the outcome for an extended period of time.

MECHANISMS OF ACTION OF OMEGA-3 FATTY ACIDS IN SCHIZOPHRENIA Increased levels of calcium independent phospholipase A2 (PLA2) have been shown in platelets [78], serum [79] and temporal cortex [80] of schizophrenic patients. This enzyme is involved in the breakdown of phospholipids by cleaving fatty acids from the Sn2 position. This is an important part of cell signalling, for example releasing AA, which is vital for brain cell-signaling mechanisms [81]. Altering phospholipid metabolism and composition affects neurotransmitter receptor function by at least two mechanisms. Receptors are embedded in a phospholipids matrix and changing the fatty acid microenvironment leads to changes in the physical disposition and function of the neurotransmitter receptor leading to altered binding characteristics. Secondly fatty acids and their derivatives are themselves intimately involved in cell signaling processes [81-84].

56

Sa’eed Bawa

The neurodevelopmental hypothesis of schizophrenia proposes that there is a genetically determined abnormality of neurodevelopment which therefore manifests itself from the foetus onwards, but which may be compounded by environmental insults such as cerebral anoxia at birth [84]. It is therefore of great significance that the polyunsaturated fatty acids, particularly docosahexaenoic acid (DHA) and AA, are essential for normal neurodevelopment [85].

THE ROLE OF OMEGA-3 FATTY ACIDS IN THE ETIOLOGY AND MANAGEMENT OF DEMENTIA AND ALZHEIMER DISEASE Dementia is a common disorder among elderly people. Its prevalence increases with age to more than 30% among those aged 85 years and over [86]. Environmental and genetic factors, notably ApoE4, contribute to the etiology of late-onset Alzheimer's disease (LOAD). Reduced mRNA and protein for an apolipoprotein E (ApoE) receptor family member, SorLA (LR11) has been found in LOAD but not early-onset Alzheimer disease (AD), suggesting that LR11 loss is not secondary to pathology. LR11 is a neuronal sorting protein that reduces amyloid precursor protein (APP) trafficking to secretases that generate β-amyloid (Aβ). Genetic polymorphisms that reduce LR11 expression are associated with increased AD risk. However these polymorphisms account for only a fraction of cases with LR11 deficits, suggesting involvement of environmental factors. Dietary fatty acids and antioxidants may contribute to decrease dementia risk, but epidemiologic data remain controversial. Because lipoprotein receptors are typically lipid-regulated, it has been suggested that LR11 is regulated by highly unsaturated fatty acids, especially DHA, an essential omega-3 fatty acid related to reduced AD risk and reduced Aβ accumulation. Ma et al. [87] demonstrated that DHA significantly increased LR11 in multiple systems, including primary rat neurons, aged non-Tg mice and an aged DHA-depleted APPsw AD mouse model. DHA also increased LR11 in a human neuronal line. In vivo elevation of LR11 was also observed with dietary fish oil in young rats with insulin resistance, a model for type II diabetes, which is another AD risk factor. DHA induction of LR11 in the investigation by Mai et al. [87] does not require DHA-depleting diets and is not age dependent. Because reduced LR11 is known to increase Aβ production and may be a significant genetic cause of LOAD, the results of this research indicate that DHA increases in SorLA/LR11 levels may play a significant role in preventing LOAD. Epidemiological studies have shown that fish intake is a protective factor against dementia and Alzheimer’s disease. In a prospective study with the participation of 5386 Dutch aged ≥55 years Kalmijn et al. [88] showed that subjects with a fish consumption of more than 20 g day) had a reduced risk of cognitive impairment, cognitive decline, dementia and Alzheimer’s disease. In another study performed by the Kalmijn group [89] in 476 men aged 69-89 years it was reported that a high intakes of the omega-6 linoleic acid was associated with cognitive impairment after adjustment for confounders, whereas high fish consumption was inversely associated. The results of a prospective study conducted by Morris et al. [90] revealed a strong inverse link between fish intake and Alzheimer disease. Elderly people who ate fish at least once a week had a 60% lower risk of developing the disease over a 4-year period.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

57

In a recent study carried out in France in 8085 people aged ≥ years, Barberger-Gateau et al. [91] showed that Weekly consumption of fish was associated with a reduced risk of AD (HR 0.65, 95% CI 0.43 to 0.994) and all cause dementia but only among ApoE ε4 noncarriers (HR 0.60, 95% CI 0.40 to 0.90). Regular use of omega-3 rich oils was associated with a decreased risk of borderline significance for all cause dementia (HR 0.46, 95% CI 0.19 to 1.11). Regular consumption of omega-6 rich oils not compensated by consumption of omega3 rich oils or fish was associated with an increased risk of dementia (HR 2.12, 95% CI 1.30 to 3.46) among ApoE ε4 non-carriers. It was also demonstrated in this study that daily consumption of fruits and vegetables was associated with a decreased risk of all cause dementia (hazard ratio [HR] 0.72, 95% CI 0.53 to 0.97) in fully adjusted models. Plasma studies support the evidence that low n-3 levels are associated with dementia. Conquer et al. [92] found lower levels of plasma phospholipids DHA in patients with Alzheimer’s disease and other dementias. They also found a significantly decreased level of plasma DHA in a group of elderly individuals who were cognitively impaired but did not have dementia. The authors hypothesized that decreased omega-3 polyunsaturated fatty acids prior to disease onset may be at least partly responsible for the lower levels of plasma DHA and the cognitive decline. Heude et al. [93] confirmed the above hypothesis in a study in which they measured erythrocyte membrane fatty acid composition and cognitive function in 246 elderly people and followed them up 4 years later. Those with high omega-6 fatty acids and low omega-3 fatty acids in their erythrocytes were most likely to experience cognitive decline. In a small pilot investigation, Terano et al. [94] supplemented 10 elderly Japanese with 0.72 g DHA for 12 months and compared them with an unsupplemented group. A significant improvement in dementia scores was found in the DHA group, but not in controls, after 3 months. The potential usefulness of DHA in this field now needs to be verified by larger intervention studies.

PARKINSON’S DISEASE Contrary to Alzheimer’s disease, scientific data relating the consumption of fat and the risk for the development of Parkinson’s disease is very scarce. The results of prospective studies, based on food frequency questionnaire performed by Chen et al. [95] as well as de Lau et al. [96] showed association between high dietary consumption of saturated fat and low intake of unsaturated fatty acids with higher risk of developing Parkinson’s disease. It is worth mentioning that this is in accord with some earlier retrospective studies [97-99]. However, no study to date has directly associated n-3 PUFA intake and the risk of suffering from Parkinson’s disease. Julien et al. [100] carried out research to determine the fatty acid profile of levodopatreated patients with Parkinson’s disease compared to control their control counterparts using gas chromatography. The results of their investigation did not reveal any significant differences in omega-3 fatty acid concentration in the brain cortex between patients with Parkinson’s disease and controls. Short-term administration DHA at the dose of 100 mg/kg body weight reduced by up to 40% L-DOPA-induced dyskinesias in nonhuman primate model of Parkinson disease treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) [101. This suggests that DHA

58

Sa’eed Bawa

can reduce the severity or delay the development of L-DOPA induced dyskinesias in a nonhuman primate model of Parkinson disease. A DHA-enriched diet may represent a new approach to improve the quality of life of Parkinson disease patients. Samadi et al. [101] proposed that this effect of DHA in reducing dyskinesias can be explained by the activation of nuclear receptors that operate as transcription factors, such as retinoid X receptors. Another study reports that a 1-month treatment with levodopa decreased DHA concentrations in the brain cortex in a primate animal model of PD, but increased arachidonic acid and n-6 docosapentaenoic acid levels [100]. Data consistent with an upregulating effect of chronic levodopa treatment on post mortem brain arachidonic acid have also been reported in levodopa-treated PD patients (100). Thus, the most prescribed treatment against the symptoms of PD appears to modulate brain PUFA while its effect on motor activity appears to be regulated by DHA. Of further interest, recent data also demonstrate a protective effect of DHA against MPTP-induced neurotoxicity in a mouse model of acute parkinsonism, in terms of preserved dopamine levels, tyrosine hydroxylasepositive neurons and nurr-1 expression [102]. There are many mechanisms, whereby highly unsaturated fatty acids, such as DHA may protect the brain. One of the first proposed mechanisms for the neuroprotective action of DHA is that it exerts anti-oxidative activity in vivo [103, 104-107]. Indeed, evidence of DHA increasing glutathione reductase activity [105], decreasing the accumulation of oxidized proteins [103, 106] and levels of lipid peroxide and reactive oxygen species [105, 106] have been published. Data supporting DHA-induced inactivation of a cell-signaling pathway leading to caspase activation [103, 108] or to hyperphosphorylation of tau [109] have also been shown. Interestingly, the capacity of DHA to regulate the phosphatidylinositol-3 kinase (PI3-K)-Akt cascade has been elegantly demonstrated in vitro [110-112]. An action of DHA on beta-secretase or gamma-secretase complex activity has been partly ruled out, but recent data indicated that DHA can downregulate presenilin-1 in vitro and in vivo [113, 100]. Other potential mechanisms of action that remain to be thoroughly studied in animal models include regulation of inflammatory process, gene transcription or cell membrane properties [114116].

NEURODEVELOPMENTAL DISORDERS Neurodevelopmental disorders are disabilities in the functioning of the brain that affect a child’s behaviour, memory or ability to learn. They include mental retardation, dyslexia, attention deficit hyperactivity disorder (ADHD), learning deficits, autism and autism-like disorders, affecting between 3-8 % of the children in USA and Europe, with a male to female ratio of around 4-6:1 [117]. Twenty to twenty five percent of children with ADHD show one or more specific learning disabilities in math, reading, or spelling. Hyperactive children have also been reported to experience increased thirst, eczema, asthma, and other allergies, which are known to be symptoms of essential fatty acid (EFA) deficiency, more often than normal children [118]. Although previously thought to be a condition of childhood, it is now recognized that in up to 60% of sufferers, ADHD persists into adulthood [119]. In adults, ADHD is manifest by disorganization, impulsivity, and poor work skills, and sufferers tend to be impatient and easily bored.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

59

Recent epidemiological data seem to indicate that for at least two of these disorders (autism and ADHD) the prevalence rate has increased in the last two decades [120, 121]. Although such increase may reflect increased awareness of these disorders and broader diagnostic criteria, there is general concern on the possible implication of environmental factors in the etiology of neurodevelopmental disorders. For most of neurodevelopmental disorders characterized by cognitive and behavioral deficits the neural basis and the etiology are still poorly understood [122]. A large number of environmental factors have been implicated as causes, in addition to the genetic components of the disorders. The nervous system is in fact vulnerable during development to a wide range of environmental factors and agent. Maternal stress during pregnancy, exposure to neurotoxicants in the prenatal/postnatal phase, or poor psychosocial environment are all factors that may affect the correct development of brain functional circuitries, particularly when acting on a vulnerable genetic background [123]. Rodier et al. [124] reported that some forms of autism might arise from toxic insult. Thalidomide and valproic acid effects during a specific time window (neurulation) are an example of critical gene-brain-environment interaction that can affect neurobehavioral development. Furthermore, the kind of damage that may occur depends upon a variety of factors, including the stage of development, the particular agent/environment factor and magnitude, route and duration of exposure. Nervous system damage may be characterized by anatomical, neurochemical, behavioral and/or cognitive deficits. In some cases behavioral and cognitive alterations may be the only marker of effect accessible and thus would be important for risk assessment.

LONG-CHAIN FATTY ACID DEFICITS AND NEURODEVELOPMENTAL DISORDERS There is a growing body of evidence that during early pregnancy a deficit of omega-3fatty acids is responsible through a defective brain lipid metabolism for an increased vulnerability to depression in the offspring [125]. It is also known that oligodendrocyte dysfunction and defective myelination may play a role in schizophrenia and bipolar disorders [126]. Since the 1980’s, both n-3 and n-6 long chain polyunsaturated fatty acids (LCPUFAs) have been suspected of being associated with ADHD. In one of the first investigative studies conducted, the serum levels of DHA, dihomogamma-linolenic acid (DGLA, 20:3n-6), and arachidonic acid (AA, 20:4n-6) were found to be significantly lower in hyperactive children than in controls [127]. Results of studies carried out by Stevens et al. [128] in 53 boys with ADHD compared to 43 boys without ADHD showed that plasma and red blood cell (RBC) levels of AA, EPA, and DHA were significantly lower in ADHD patients as compared to controls, and that a subgroup of ADHD patients exhibiting symptoms of long-chain polyunsaturated fatty acid deficiency had even lower plasma concentrations of AA and DHA than did ADHD subjects with few long-chain polyunsaturated fatty acid deficiency symptoms. Another study of children with ADHD also reported reduced plasma concentrations of EPA, DHA, and arachidonic acid [129]. In a study of boys with behavior, learning, and health problems, it was found that boys with lower omega 3 EFA levels had

60

Sa’eed Bawa

more behavior problems, more temper tantrums, and more sleep problems [130]. It is worth mentioning that all of the above symptoms are commonly observed in autism. In a study of EFA levels in children with Rett’s syndrome (which has many similarities with autism) performed by Stradomska et al. [131] it was found that very long chain fatty acid levels were significantly lower than the reference range for healthy children. Results of studies on EFA levels in the plasma of children with autism by Vancassel et al. [132] showed that participants had normal levels of omega-6 fatty acids, but 20% lower levels of EPA and DHA (p= 0.03). It should be noted that the control group was a group of children with mental retardation, but their levels were generally consistent with other values reported for typical children. Their work is consistent with preliminary results of investigations conducted by Gordon et al. [133] who reported that, in seven children with autism, the red blood cells contained less EPA and DHA, and sometimes more arachidonic acid, than control subjects. Young et al. [134] demonstrated that adults with ADHD also have an altered phospholipids fatty acid status, specifically having lower levels of omega-6 fatty acids and DHA in serum and lower levels of omega-3 fatty acids, including DHA in red blood cells. Low levels of these long-chain polyunsaturated fatty acids in blood could be related to marginal consumption, inefficient conversion of precursors (linoleic acid and ALA) to highly unsaturated fatty acids, or enhanced metabolism long-chain polyunsaturated fatty acids [118]. Preliminary work suggests no difference in dietary intakes of fatty acids between children with ADHD and healthy children [128]. Recently, Ross et al. [135] demonstrated that children with ADHD exhaled increased levels of ethane, a non-invasive measure of oxidative damage to omega-3 fatty acids, indicating increased breakdown. Based on this body of research, it has been hypothesized that supplementation with LCPUFAs, particularly of the n-3 fatty acid family, may result in an improvement in the learning and behavioral symptoms of ADHD. However, very few clinical trials have been conducted in this field. In 2001, Voigt et al. [136] supplemented 63 children with ADHD with either placebo or 345 mg DHA·day–1 for 4 months. DHA levels in blood increased but there were no significant improvements in any measure of ADHD symptoms. However, Richardson and Puri [137] showed that supplementation with a mixture of EPA, DHA, gamma-linolenic acid (GLA, 18:3n-6), vitamin E, AA, LA and thyme oil for 12 weeks in children with specific learning disabilities, improved symptoms in 7 out of 14 symptoms of ADHD (although only 3 were significant) compared to none for placebo. Recently, Stevens et al. [138] supplemented children with ADHD with (per day) 480 mg DHA, 80 mg EPA, 40 mg AA, and 96 mg GLA for 4 months. There was an increase in both EPA and DHA in plasma as well as improvement in parent-rated conduct, teacher-rated attention and oppositional defiant behavior. Furthermore, there was a significant correlation between increased RBC EPA and DHA and a decrease in disruptive behaviour. Harding et al. [139] compared the effect of Ritalin and dietary supplements including, among other ingredients, omega-3 fatty acids (180 mg EPA, 120 mg DHA) and 45 mg GLA per day. Although small and non-randomized, this study suggested that dietary supplementation resulted in equivalent improvements in attention and self control as Ritalin. Finally, Hirayama et al. [140] examined the effect of DHA supplementation in food sources for 2 months on symptoms of ADHD. On average, children received 0.5 g DHA·day–1 vs. control foods. There was no improvement of ADHD

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

61

symptoms in this study. These findings seem to suggest that a combination of LCPUFAs is more likely to exert a positive effect on ADHD symptoms than omega-3 fatty acids alone. Fish as well as fish oil can as well be helpful in decreasing gastrointestinal disorders frequently seen in autistic children. One epidemiological study found that increasing incidence of Crohn’s disease correlated strongly (r = 0.792) with the ratio of omega-6 to omega-3 fatty acids, such that low levels of omega-3 corresponded to a higher incidence of Crohn’s disease [141]. Belluzi et al.[142] conducted a one-year, double-blind, placebocontrolled trial of fish oil (1.8 g of EPA, 0.9 g of DHA) in people with Crohn’s disease and found that subjects taking the fish oil had a significantly reduced relapse rate, with no significant adverse effects. It is worth underlying that similar gastrointestinal problems are experienced frequently in patients with autism. The results of several studies preformed by researchers, among others, Horvath et al. [143] showed higher prevalence of gastrointestinal abnormalities in children with autism compared to their healthy counterparts. Similarly, endoscopies of children with autism have found mild inflammation typically throughout most of the gastrointestinal tract, which has been termed “autistic enterocolitis” [144, 145]. The above mentioned studies, clearly demonstrate that fish oil supplements which were shown to be useful in alleviating the symptoms of Crohn’s disease may also be useful in reducing the GI problems observed in children with autism. It has been hypothesized that those GI problems may result in an exacerbation of some of the behavioral and sleep problems in autism. Fatty acids and their metabolism affect the functioning of major neurotransmitter systems implicated in ADHD and related psychiatric disorders, as reviewed elsewhere [146]. Effects of omega-3 on both serotonergic and noradrenergic function may help to account for the apparent links between omega-3 status and hostility-aggression, depression and other moodrelated disorders as noted above. The effects of fatty acids on neural signaling can be mediated via a huge variety of different mechanisms, direct and indirect, as HUFA and their derivatives not only affect membrane structure and function, but help to regulate blood flow, endocrine and immune functions and can also modulate ion channels, neurotransmitter uptake, synaptic transmission, apoptosis and gene expression among other biological processes. Of particular relevance to many psychiatric disorders are their effects on cytokine and endocannabinoid metabolism, which are receiving serious attention in relation to schizophrenia, [147] and may be equally important in related childhood neurodevelopmental disorders including ADHD. Besides the perturbations arising from omega-3 fatty acid deficiency mentioned, additionally, DHA deficiency leads to reduced dendritic arborisation [149) and impaired gene expression for regulation of neurogenesis, neurotransmission, and connectivity [150]. In severe conditions of DHA deprivation, such as Zellweger disease and peroxisomal disorders, mental retardation is common, yet restoration of dietary DHA intake improves clinical outcomes and neuronal myelination [151-153].

62

Sa’eed Bawa

Table 4. Consequences of omega-3 fatty acid deficiency in the central nervous system [148] Decrease of a parameter/process Dopamine vesicle pool Dopamine content in frontal cortex Dopamine content in olfactory bulb

Increase of a parameter/process Dopamine content in nucleus accumbens (NA) Pre/post synaptic dopamine receptor DR2 in NA Serotonin receptor (5HT2) density in frontal cortex (compensatory response)

Dopamine release from vesicle storage Normal inhibitory control over NA dopamine Vesicular monoamine transporter (VMAT2) Pre/post synaptic dopamine receptor DR2 in frontal cortex Glucose uptake by neurons Neuronal cytochrome oxidase activity Blood-brain barrier integrity Normal cerebral microperfusion Sodium/potassium ATPase at nerve terminal Fluidity at surface polar membrane Phosphatidylserine in cortex, olfactory bulb, and mitochondria Hippocampal CA1 pyramidal neuron cell body size

CONCLUDING REMARKS While far from robust, there is enough epidemiological, laboratory and clinical evidence to suggest that omega-3 fatty acids may play a role in the etiology and management of certain cases of neuropsychiatric and neurodevelopmental disorders. Fish oil supplements are well tolerated, and have been shown to be without significant side effects over large scale in studies lasting up to 3 years. Generally, omega-3 supplements are inexpensive, which makes them an attractive option as an adjuvant to standard care. At this time, however, the routine use of omega-3 fatty acids for the treatment of depressive disorders cannot be recommended. Optimum fetal neurodevelopment is dependent on specific nutrients derived solely from dietary sources, including docosahexaenoic acid (DHA), an omega-3 essential fatty acid present in large amounts in seafood. Low seafood intake during pregnancy could lead to fetal deficiency in essential long-chain omega-3 fatty acids such as DHA and eicosapentaenoic acid, (EPA) resulting in adverse effects on neurodevelopment [116]. In 2004, advice was issued jointly by two US Federal Government agencies for pregnant women or women likely to become pregnant to restrict their overall consumption of seafood to 340 g per week, [154] to avoid fetal exposure to trace amounts of neurotoxins. However, such control of seafood consumption could cause intake of long-chain omega-3 fatty acids to

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

63

fall below quantities adequate for best fetal neurodevelopment [155, 156]. Hibbeln et al. [157] recently analyzed an observational cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC), to assess whether the advice is successful in providing protection from adverse neurodevelopmental outcomes. They recorded no evidence to lend support to the warnings of the US advisory [154] that pregnant women should limit their seafood consumption. By contrast, they observed that children of mothers who ate small amounts (<340 g per week) of seafood were more likely to have suboptimum neurodevelopmental outcomes than children of mothers who ate more seafood than the recommended amounts. Putting into consideration the current excess intake of omega-6 fatty acids from oils and other foods, and the emerging research on omega-3 fatty acids and neuropsychiatric as well as neurodevelopmental disorders, all mental health professionals should at least ensure adequate intake of omega-3 fatty acids among patients with these disorders. The current average intakes of EPA and DHA in Europe and North American 130 mg per day, well short of the minimum 650 mg recommended by the international panel of lipid experts [2]. In addition to increasing fish consumption, alternative strategies for increasing levels of omega-3 fatty acids in the diet, and/or decreasing the omega-6 to omega-3 fatty acid ratio, include the use of omega-3 fatty acid supplements, consumption of other omega-3 containing foods such as flaxseed, and decreasing the intake of omega-6 rich vegetable oils such as corn, grapeseed, and sunflower oil. Further studies are needed to fully elucidate the exact mechanisms of the actions of essential fatty acids, especially of the omega-3 family in the brain and their role in influencing outcome of standard care in patients with neuropsychiatric and neurodevelopmental disorders.

REFERENCES [1]

[2] [3] [4]

[5]

[6]

Murray, C; Lopez, A, eds. The Global Burden of Disease Study: A Comprehensive Assessment of Mortality and Disability from Disease, Injuries, and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press on behalf of the World Health Organization and the World Bank, 1996. Holub, BJ. Clinical nutrition: 4. Omega-3 fatty acids in cardiovascular care. CMAJ, 2002, 166, 608-615. Bourre, JM. Roles of unsaturated fatty acids (especially omega-3 fatty acids) in the brain at various ages and during ageing. J. Nutr. Health Aging, 2004, 8, 163-174. Food and Nutrition Board, Institute of Medicine. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). A report of the Panel on Macronutrients, Subcommittess on Upper Reference Levels of Nutrients and Interpretation and Uses of Dietary Reference Intakes, and the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. National Academy Press, Washington, D.C., 2002. Kris-Etherton, PM; Taylor, DS; Yu-Poth, S; Huth, P; Mortarty, K; Ftshell, V. Polyunsaturated fatty acids in the food chain in the United States. AJCN, 2000, 71, 179188. Williams, CM; Burdge, G. Long-chain n-3 PUFA: plant v. marine sources. Proc. Nutri. Soc., 2006, 65, 42-50.

64 [7]

[8] [9] [10] [11] [12]

[13] [14] [15] [16]

[17]

[18]

[19] [20] [21] [22]

[23]

[24]

Sa’eed Bawa Freeman, MP; Hibbeln, JR; Wisner, KL; Davis, JM; Mischoulon, D; Peet, M; Keck, PE; Marangell, LB; Richardson, AJ; Lake, J; Stoll, AL. Omega-3 fatty acids: Evidence basis for treatment and future research in psychiatry. J Clin Psychiatry, 2006, 67, 19541967. Cott, J; Hibbeln, JR. Lack of seasonal mood change in Icelanders. Am. J. Psychiatry, 2001, 158, 328. Hibbeln, J; Salem, N. Dietary polyunsaturated fats and depression: when cholesterol does not satisfy. Am. J. Clin. Nutr., 1995, 62, 1-9. Hibbeln, JR. Fish consumption and major depression. Lancet, 1998, 351, 1213. Silvers, KM; Scott, KM. Fish consumption and self-reported physical and mental health status. Public Health Nutr., 2002, 5, 427-431 Hibbeln, JR. Seafood consumption, the DHA content of mothers' milk and prevalence rates of postpartum depression: a cross-national, ecological analysis. J. Affect Disord., 2002, 69, 15-29. Richardson, AJ. Omega-3 fatty acids in ADHD and related neurodevelopmental disorders. Int. Rev. Psychiatry, 2006, 18, 155-172 O’Keefe H Jr, Harris W. From Inuit to implementation: omega-3 fatty acids come of age. Mayo Clin. Proc., 2000, 75, 607-614. Hakkarainen, R; Partonen, T; Haukka, J; Virtamo, J; Albanes, D; Lonnqvist, J. Food and nutrient intake in relation to mental wellbeing. Nutr. J., 2004, 3, 14. Hakkarainen, R; Partonen, T; Haukka, J; Virtamo, J; Albanes, D; Lonnqvist J. Is low dietary intake of omega-3 fatty acids associated with depression? Am. J. Psychiatry, 2004, 161, 567-569. Tanskanen, A; Hibbeln, J; Hintikka, J; Haatainen, K; Honkalampi, K; Viinamaki, H. Fish consumption, depression and suicidality in general population. Arch. Gen. Psychiatry, 2001, 58, 512-13. Pope, S; Watts, J; Evans, S; McDonald, S; Henderson, S. An Information Paper on Postnatal Depression: A Systematic Review of Published Scientific Literature to 1999. Canberra: National Health and Medical Research Council, 2000. Evans, J; Heron, J; Francomb, H; Oke, S; Golding, J. Cohort study of depressed mood during pregnancy and after childbirth. BMJ, 2001, 323, 257-60. Makrides, M; Crowther, CA; Gibson, RA; Gibson, RS; Skeaff, CM. Docosahexaenoic acid and post-partum depression – is there a link? Asia Pac J Clin Nutr, 2003, 12, S37. Bourre, JM. Roles of unsaturated fatty acids (especially omega-3 fatty acids) in the brain at various ages and during ageing. J. Nutr. Health Aging, 2004, 8, 163-174. Otto, SJ; de Groot, RH; Hornstra, G. Increased risk of postpartum depressive symptoms is associated with slower normalization after pregnancy of the functional docosahexaenoic acid status. Prostaglandins Leukot. Essent. Fatty Acids, 2003, 69, 237-243. Huan, M; Hamazaki, K; Sun,Y; Itomura, M; Liu, H; Kang, W; Watanabe, S; Terasawa, K; Hamazaki, T. Suicide attempt and n-3 fatty acid levels in red blood cells: a case control study in China. Biol. Psychiatry 2004, 56, 490-496. Maes, M; Scharpe, S; D'Hondt, P; Peeters, D; Wauters, A; Neels, H; Verkerk, R. Biochemical, metabolic and immune correlates of seasonal variation in violent suicide: a chronoepidemiologic study. Eur. Psychiatry, 1996, 11, 21-33.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

65

[25] De Vriese, SR; Christophe, AB; Maes, M. In humans, the seasonal variation in polyunsaturated fatty acids is related to the seasonal variation in violent suicide and serotonergic markers of violent suicide. Prostaglandins Leukot. Essent. Fatty Acids, 2004, 71, 13-18. [26] Frasure-Smith, N; Lesperance, F; Julien, P. Major depression is associated with lower omega-3 fatty acid levels in patients with recent acute coronary syndromes. Biol. Psychiatry, 2004, 55, 891-896. [27] Assies, J; Lok, A; Bockting, CL; Weverling, GJ; Lieverse, R; Visser, I; Abeling, NG; Duran, M; Schene, AH. Fatty acids and homocysteine levels in patients with recurrent depression: an explorative pilot study. Prostaglandins Leukot. Essent. Fatty Acids, 2004, 70, 349-356. [28] Suzuki, S; Akechi, T; Kobayashi, M; Taniguchi, K; Goto, K; Sasaki, S; Tsugane, S; Nishiwaki, Y; Miyaoka, H; Uchitomi, Y. Daily omega-3 fatty acid intake and depression in Japanese patients with newly diagnosed lung cancer. Br J Cancer, 2004, 90, 787-793. [29] Ellis, FR; Sanders, TA. Long chain polyunsaturated fatty acids in endogenous depression. J. Neurol. Neurosurg. Psychiatry, 1977, 40, 168-169. [30] Fehily, AMA; Bowey, OAM; Ellis, FR; Meade, BW; Dickerson, JWT. Plasma and erythrocyte memebrane long chain polyunsaturated fatty acids in endogenous depression. Neurochem. Int., 1981, 3, 37-42. [31] Mamalakis, G; Kiriakakis, M; Tsibinos, G; Kafatos, A. Depression and adipose polyunsaturated fatty acids in an adolescent group. Prostaglandins Leukot. Essent. Fatty Acids, 2004, 71, 289-294. [32] Adams, PB; Lawson, S; Sanigorski, A; Sinclair, AJ. Arachidonic acid to eicosapentaenoic acid ratio in blood correlates positively with clinical symptoms of depression. Lipids, 1996, 31, S157-S161. [33] Peet, M; Murphy, B; Shay, J; Horrobin, D. Depletion of omega-3 fatty acid levels in red blood cell membranes of depressive patients. Biol. Psychiatry, 1998, 43, 315-319. [34] Maes, M; Christophe, A; Delanghe, J; Altamura, C; Neels, H; Meltzer, HY. Lowered omega3 polyunsaturated fatty acids in serum phospholipids and cholesteryl esters of depressed patients. Psychiatry Res., 1999, 85, 275-291. [35] Tiemeier, H; van Tuijl, HR; Hofman, A; Kiliaan, AJ; Breteler, MM. Plasma fatty acid composition and depression are associated in the elderly: the Rotterdam Study. Am. J. Clin. Nutr., 2003, 78, 40-46. [36] Mamalakis, G; Kiriakakis, M; Tsibinos, G; Kafatos, A. Depression and adipose polyunsaturated fatty acids in the survivors of the Seven Countries Study population of Crete. Prostaglandins Leukot. Essent. Fatty Acids, 2004, 70, 495-501. [37] Mamalakis, G; Tornaritis, M; Kafatos, A. Depression and adipose essential polyunsaturated fatty acids. Prostaglandins Leukot. Essent Fatty Acids, 2002, 67, 311318. [38] Rudin, DO. The major psychoses and neuroses as omega-3 essential fatty acid deficiency syndrome: substrate pellagra. Biol. Psychiatry, 1981, 16, 837-50. [39] Chiu, CC; Huang, SY; Shen, WW; Su, KP. Omega-3 fatty acids for depression in pregnancy. Am. J. Psychiatry, 2003, 160, 385. [40] Puri, BK; Counsell, SJ; Hamilton, G; Richardson, AJ; Horrobin, DF. Eicosapentaenoic acid in treatment-resistant depression associated with symptom remission, structural

66

[41]

[42]

[43]

[44]

[45]

[46]

[47]

[48]

[49]

[50]

[51]

[52] [53] [54] [55]

Sa’eed Bawa brain changes and reduced neuronal phospholipid turnover. Int. J. Clin. Pract., 2001, 55, 560-563. Bremner, JD; Vythilingam, M; Vermetten, E; Nazeer, A; Adil, J; Khan, S; Staib, LH; Charney, DS. Reduced volume of orbitofrontal cortex in major depression. Biol. Psychiatry, 2002, 51, 273-279. Ayton, AK; Azaz, A; Horrobin, DF. A pilot open case series of ethyl-EPA supplementation in the treatment of anorexia nervosa. Prostaglandins Leukot. Essent. Fatty Acids, 2004, 71, 205-209. Sampalis, F; Bunea, R; Pelland, MF; Kowalski, O; Duguet, N; Dupuis, S. Evaluation of the effects of Neptune Krill Oil on the management of premenstrual syndrome and dysmenorrhea. Altern. Med. Rev., 2003, 8, 171-179. 44. Stoll, AL; Severus, WE; Freeman, MP; Rueter, S; Zboyan, HA; Diamond, E; Cress, KK; Marangell, LB. Omega 3 fatty acids in bipolar disorder: a preliminary doubleblind, placebo-controlled trial. Arch. Gen. Psychiatry, 1999, 56, 407-412. Nemets, B; Stahl, Z; Belmaker, RH. Addition of omega-3 fatty acid to maintenance medication treatment for recurrent unipolar depressive disorder. Am. J. Psychiatry, 2002, 159, 477-479. Zanarini, MC; Frankenburg, FR. omega-3 Fatty acid treatment of women with borderline personality disorder: a double-blind, placebo-controlled pilot study. Am. J. Psychiatry, 2003, 160, 167-169. Su, KP; Huang, SY; Chiu, CC; Shen, WW. Omega-3 fatty acids in major depressive disorder. A preliminary double-blind, placebo- controlled trial. Eur. Neuropsychopharmacol., 2003, 13, 267-271. Peet, M; Horrobin, DF. A dose-ranging study of the effects of ethyl-eicosapentaenoate in patients with ongoing depression despite apparently adequate treatment with standard drugs.Arch. Gen. Psychiatry, 2002, 59, 913-919. Marangell, LB; Martinez, JM; Zboyan, HA; Kertz, B; Kim, HF; Puryear, LJ. A doubleblind, placebo-controlled study of the omega-3 fatty acid docosahexaenoic acid in the treatment of major depression. Am. J. Psychiatry, 2003, 160, 996-998. Marangell, LB; Martinez, JM; Zboyan, HA; Chong, H; Puryear, LJ. Omega-3 fatty acids for the prevention of postpartum depression: negative data from a preliminary, open-label pilot study. Depres.s Anxiety, 2004, 19, 20-23. Llorente, AM; Jensen, CL; Voigt, RG; Fraley, JK; Berretta, MC; Heird, WC. Effect of maternal docosahexaenoic acid supplementation on postpartum depression and information processing. Am. J. Obstet. Gynecol., 2003, 188, 1348-1353. Locke, CA; Stoll, AL. Omega-3 fatty acids in major depression. World Rev. Nutr. Diet, 2001, 89, 173-185. Logan, AC. Neurobehavioral aspects of omega-3 fatty acids: possible mechanisms and therapeutic value in major depression. Altern Med. Rev., 2003, 8, 410-425. Bourre, JM; Dumont, O ; Piciotti, M. et al. Essentiality of omega 3 fatty acids for brain structure and function. World Rev. Nutr. Diet, 1991, 66, 103-117. Yehuda, S; Rabinovitz, S; Mostofsky, DI. Modulation of learning and neuronal membrane composition in the rat by essential fatty acid preparation: time-course analysis. Neurochem. Res., 1998, 23, 627-634.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

67

[56] Heron, DS; Shinitzky, M; Hershkowitz, M. et al. Lipid fluidity markedly modulates the binding of serotonin to mouse brain membranes. Proc. Natl. Acad. Sci. USA, 1980, 77, 7463-7467. [57] Maes, M; Smith, RS. Fatty acids, cytokines, and major depression. Biol. Psychiatry, 1998, 43, 313-314. [58] Suarez, EC; Krishnan, RR; Lewis, JG. The relation of severity of depressive symptoms to monocyte-associated proinflammatory cytokines and chemokines in apparently healthy men. Psychosom. Med., 2003, 65, 362-368. [59] Shimizu, E; Hashimoto, K; Okamura, N. et al. Alterations of serum levels of brainderived neurotrophic factor (BDNF) in depressed patients with or without antidepressants. Biol. Psychiatry, 2003, 54, 70-75. [60] Horrobin, DF; Glen, AIM; Vaddadi, KS. The membrane hypothesis of schizophrenia. Schizophr. Res., 1994, 13, 195-208. [61] 61. Peet, M; Laugharne, J; Rangainjan, N;, Horrobin, DF; Reynolds, G. Depleted red cell membrane fatty acids in drug treated schizophrenic patients. Psychiatr. Res., 1995, 29, 227-232. [62] Glen, AM; Glen, EMT; Horrobin, DF; Vaddadi, KS; Spellman, M; Morse-Fisher, N., et al. A red blood cell membrane abnormality in a sub group of schizophrenic patients: evidence for two diseases. Schizophr. Res., 1994, 12, 53. [63] Assies, J; Lieverse, R; Vreken, PR; Wanders, JA; Dingemans, PMJA; Linszen, DH. Significantly reduced docosahexaenoic acid concentrations in erythrocyte membranes from schizophrenic patients compared with a carefully matched control group. Biol. Psychiatry, 2001, 49, 510-522. [64] Mahadik, SP; Mukerhee, S; Corrent, E; Kelhar, HS; Wakade, CG; Costa, RM; et al. Distribution of plasma membrane phospholipids and cholesterol in skin fibroblasts from drug naïve patients at the onset of psychosis. Schizophr. Res., 1994, 13, 239-247. [65] Yao, JK; Leonard, S; Reddy, RD; Membrane phospholipids abnormalities in post mortem brains from schizophrenic patients. Schizophr. Res., 2000, 42, 7-17. [66] 66. Christensen, O; Christensen, E. Fat consumption and schizophrenia. Acta Psychiatr. Scand., 1988, 78, 587-591 [67] Mellor, JE; Laugharne, JDE; Peet, M. Omega-3 fatty acid supplementation in schizophrenia patients. Hum Psychopharmacol, 1996, 11 39-46. [68] Peet, M ; Laugharne, JD; Mellor, J ; Ramchand, CN. Essential fatty acid deficiency in erythrocyte membranes from chronic schizophrenic patients, and the clinical effects of dietary supplementation. Prostaglandins Leukot. Essent Fatty Acids, 1996, 55, 71-75. [69] McCreadie, RG; Thara, R; Kamoth, S. et al. Abnormal movements in never-medicated Indian patients with schizophrenia. Br. J. Psychiatry, 1996, 168, 221-226. [70] Peet, M; Horrobin, DF. A dose-ranging exploratory study of the effects of ethyl eicosapentaenoate in patients with persistent schizophrenic symptoms. J. Psychiatr. Res., 2002, 36, 7-18. [71] Peet, M; Brind, J; Ramchand, CN; Shah, S; Vankar, GK. Two double-blind placebocontrolled pilot studies of eicosapentaenoic acid in the treatment of schizophrenia. Schizophr Res., 2001, 49, 243-251. [72] Arvindakshan, M; Ghate, M; Ranjekar, PK; Evans, DR; Mahadik, SP. Supplementation with a combination of omega-3 fatty acids and antioxidants (vitamins E and C) improves the outcome of schizophrenia. Schizophr Res., 2003, 62, 195-204.

68

Sa’eed Bawa

[73] Joy, CB; Mumby-Croft, R; Joy, LA. Polyunsaturated fatty acid supplementation for schizophrenia. The Cochrane Database of Systematic Reviews, 2006, Issue 3. [74] Freeman, MP; Hibbeln, JR; Wisner, KL; Davis, JM; Mischoulon, D; Peet, M; Keck Jr., PE; Marangell, LB; Richardson, AJ; Lake, J; Stoll, AL. Omega-3 fatty acids: evidence basis for treatment and future research in psychiatry. J. Clin. Psychiatry, 2006, 67, 1954-1967. [75] Gesch, CB; Hammond, SM; Hampson, SE; Eves, A; Crowder, MJ. Influence of supplementary vitamins, minerals and essential fatty acids on the antisocial behaviour of young adult prisoners. Br. J. Psychiatry, 2002, 181, 22-28. [76] Sagduyu, K; Dokucu, ME, Eddy, BA; Craigen, G; Baldassano, CF; Yildiz, A. Omega-3 fatty acids decreased irritability of patients with bipolar disorder in an add-on, open label study. Nutr. J., 2005, 4, 1-6. [77] Légaré, N. Omega-3 and violence in schizophrenia. Schizophr Res, 2007, 96, 269 [78] Gattaz, WF; Schmitt, A; Maras, A. Increased platelet phospholipase A2 activity in schizophrenia. Schizophr Res, 1995, 16, 1-6. [79] Ross, BM; Hudson, C; Erlich, J; Warsh, JJ; Kish, SJ. Increased phospholipid breakdown in schizophrenia. Evidence for the involvement of a calcium-independent phospholipase A2, Arch Gen Psychiatry, 1997, 54, 487-494. [80] Ross, BM; Hudson, C; Turennes, A; Moszcynska, JJ; Warsh, JJ; Kish, SJ. Differential alteration of phospholipase A2 activities in brain of patients with schizophrenia. Brain. Res., 1999, 821, 407-413. [81] Nomura, T; Nishizaki, T; Enomoto, T; Itoh, H. Along lasting facilitation of hippocampal neurotransmission via a phospholipid A2 signalling pathway. Life Sci., 2001, 68, 2885-2891. [82] Hudson, CJ; Young, T; Warsh, JJ. CNS signal transduction in the pathophysiology and pharmacotherapy of affective disorders and schizophrenia. Synapse, 1993, 13, 278-293. [83] Farooqui, AA; Horrocks, LA; Farooqui, T. Glycerophospholipids in brain: their metabolism, incorporation into membranes and involvement in neurological disorders. Chem. Phys. Lipids, 2000, 106, 1-29. [84] Pilowsky, LS; Kerwin, RW; Murray, RM. Schizophrenia: a neurodevelopmental perspective. Neuropsychopharmacology, 1993, 9, 83-91. [85] Uauy, R; Hoffman, DR; Peirano, P; Birch, DG; Birch, EE. Essential fatty acids in visual and brain development. Lipids, 2001, 36, 885-895. [86] Ott, A; Breteler, MMB; Van Harskamp, F. Prevalence of Alzheimer’s disease and vascular dementia association with education. The Rotterdam Study. Br. Med. J., 1995, 310, 970-973. [87] Ma, QL; Teter, B; Ubeda, OJ; Morihara, T; Dhoot, D; Nyby, MD; Tuck, ML; Frautschy, SA; Cole, GM. Omega-3 fatty acid docosahexaenoic acid increases SorLA/LR11, a sorting protein with reduced expression in sporadic Alzheimer's disease (AD): Relevance to AD prevention. J. Neurosci., 2007, 27, 14299-14307. [88] Kalmijn, S; Launer, LJ; Ott, A; Witteman, JC; Hofman, A; Breteler, MM. Dietary fat intake and the risk of incident dementia in the Rotterdam Study. Ann. Neurol., 1997a, 42, 776-782. [89] 89. Kalmijn, S; Feskens, EJ; Launer, LJ; Kromhout, D. Polyunsaturated fatty acids, antioxidants, and cognitive function in very old men. Am. J. Epidemiol., 1997b, 145, 33-41.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

69

[90] Morris, MC; Evans, DA; Bienias, JL; Tangney, CC; Bennett, DA; Wilson, RS; Aggarwal, N; Schneider, J. Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease. Arch. Neurol., 2003, 60, 940-946. [91] . Barberger-Gateau, P; Raffaitin, C; Letenneur, L; Berr, C; Tzourio, C; Dartigues, JF; Alpérovitch, A. Dietary patterns and risk of dementia: The Three City Cohort Study. Neurology, 2007, 69, 1921-1930 [92] Conquer, JA; Tierney, MC; Zecevic, J; Bettger, WJ; Fisher, RH. Fatty acid analysis of blood plasma of patients with Alzheimer’s disease, other types of dementia and cognitive impairment. Lipids, 2000, 35, 1305-1312. [93] Heude, B; Ducimetiere, P; Berr, C. Cognitive decline and fatty acid composition of erythrocyte membranes - the EVA Study. Am. J. Clin. Nutr., 2003, 77, 803-808. [94] Terano, T; Fujishiro, S; Ban, T; Yamamoto, K; Tanaka, T; Noguchi, Y; Tamura, Y; Yazawa, K; Hirayama, T. Docosahexaenoic acid supplementation improves the moderately severe dementia from thrombotic cerebrovascular diseases. Lipids, 1999, 34, S345-346. [95] Chen, H; Zhang, SM; Hernan, MA; Willett, WC; Ascherio, A. Dietary intakes of fat and risk of Parkinson’s disease. Am. J. Epidemiol., 2003, 157, 1007-1014. [96] de Lau, LM; Bornebroek, M; Witteman, JC; Hofman, A; Koudstaal, PJ; Breteler, MM. Dietary fatty acids and the risk of Parkinson disease: the Rotterdam study. Neurology, 2005, 64, 2040-2045. [97] Anderson, C; Checkoway, H; Franklin, GM; Beresford, S; Smith-Weller, T; Swanson, PD. Dietary factors in Parkinson’s disease: the role of food groups and specific foods. Mov. Disord., 1999, 14, 21-27. [98] . Logroscino, G; Marder, K; Cote, L; Tang, MX; Shea, S; Mayeux, R. Dietary lipids and antioxidants in Parkinson’s disease: a population-based, case-control study. Ann. Neurol., 1996, 39, 89-94. [99] Johnson, CC; Gorell, JM; Rybicki, BA; Sanders, K; Peterson, EL. Adult nutrient intake as a risk factor for Parkinson’s disease. Int. J. Epidemiol., 1999, 28, 1102-1109. [100] Julien, C; Berthiaume, L; Hadj-Tahar, A; Rajput, AH; Bedard, PJ; Di Paolo, T; Julien, P; Calon, F. Postmortem brain fatty acid profile of levodopa-treated Parkinson disease patients and parkinsonian monkeys. Neurochem. Int., 2006, 48, 404-414. [101] Samadi, P;, Gregoire, L; Rouillard, C; Bedard, PJ; Di Paolo, T; Levesque, D. Docosahexaenoic acid reduces levodopa-induced dyskinesias in 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine monkeys. Ann Neurol, 2006, 59, 282-288. [102] Bousquet, M; Saint-Pierre, M; Julien, C; Salem, JN; Cicchetti, F; Calon, F. Beneficial effects of dietary omega-3 polyunsaturated fatty acid on toxin-induced neuronal degeneration in an animal model of Parkinson’s disease, FASEB J., 2008, in press. [103] Calon, F; Lim, GP; Yang, F; Morihara, T; Teter, B; Ubeda, O; Rostaing, P; Triller, A; Salem Jr., N; Ashe, KH; Frautschy, SA; Cole, GM. Docosahexaenoic acid protects from dendritic pathology in an Alzheimer’s disease mouse model. Neuron, 2004, 43, 633-645. [104] Hashimoto, M; Hossain, S; Shimada, T; Sugioka, K; Yamasaki, H; Fujii, Y; Ishibashi, Y; Oka, J; Shido, O. Docosahexaenoic acid provides protection from impairment of learning ability in Alzheimer’s disease model rats. J. Neurochem., 2002, 81, 1084-1091.

70

Sa’eed Bawa

[105] Bazan, NG. Neuroprotectin D1 (NPD1): a DHA-derived mediator that protects brain and retina against cell injury-induced oxidative stress. Brain Pathol., 2005, 15, 159166. [106] Wu, A; Ying, Z; Gomez-Pinilla, F. Dietary omega-3 fatty acids normalize BDNF levels, reduce oxidative damage, and counteract learning disability after traumatic brain injury in rats. J. Neurotrauma, 2004, 21, 1457-1467. [107] Hashimoto, M; Tanabe, Y; Fujii, Y; Kikuta, T; Shibata, H; Shido, O. Chronic administration of docosahexaenoic acid ameliorates the impairment of spatial cognition learning ability in amyloid {beta}-infused rats. J. Nutr., 2005, 135, 549-555. [108] Calon, F; Lim, GP; Morihara, T; Yang, F; Ubeda, O; Salem Jr., N; Frautschy, SA; Cole, GM. Dietary n-3 polyunsaturated fatty acid depletion activates caspases and decreases NMDA receptors in the brain of a transgenic mouse model of Alzheimer’s disease. Eur. J. Neurosci., 2005, 22, 617-626. [109] Green, KN; Martinez-Coria, H; Khashwji, H; Hall, EB; Yurko-Mauro, KA; Ellis, L; LaFerla, FM. Dietary docosahexaenoic acid and docosapentaenoic acid ameliorate amyloid-beta and tau pathology via a mechanism involving presenilin 1 levels. J Neurosci, 2007, 27, 4385-4395. [110] Akbar, M; Calderon, F; Wen, Z; Kim, HY. Docosahexaenoic acid: a positive modulator of Akt signaling in neuronal survival. Proc. Natl. Acad. Sci. USA, 2005, 102, 1085810863. [111] Akbar, M; Kim, HY. Protective effects of docosahexaenoic acid in staurosporineinduced apoptosis: involvement of phosphatidylinositol-3 kinase pathway. J. Neurochem., 2002, 82, 655 665. [112] Kim, HY. Novel metabolism of docosahexaenoic acid in neural cells. J. Biol. Chem., 2007, 282, 18661-18665. [113] Lim, GP; Calon, F; Morihara, T; Yang, F; Teter, B; Ubeda, O; Salem Jr., N; Frautschy, SA; Cole, GM. A diet enriched with the omega-3 fatty acid docosahexaenoic acid reduces amyloid burden in an aged Alzheimer mouse model. J. Neurosci., 2005, 25, 3032-3040. [114] de Urquiza, AM; Liu, S; Sjoberg, M; Zetterstrom, RH; Grifiths, W; Sjovall, J; Perlmann, T. Docosahexaenoic acid, a ligano for the retinoid X receptor in mouse brain. Science, 2000, 290, 2140-2144. [115] Jump, DB. Dietary polyunsaturated fatty acids and regulation of gene transcription. Curr Opin Lipidol, 2002, 13, 155-164. [116] Salem Jr., N; Litman, B; Kim, HY; Gawrisch, K. Mechanisms of action of docosahexaenoic acid in the nervous system. Lipids, 2001, 36, 945-959. [117] Weiss, B; Landrigan, PJ. The developing brain and the environment: an introduction. Environ Health Perspect, 2000, 108 (Suppl. 3), 73-76. [118] Burgess, JR; Stevens, L; Zhang, W; Peck, L. Long-chain polyunsaturated fatty acids in children with attention-deficit hyperactivity disorder. Am. J. Clin. Nutr., 2000, 71, 327330. [119] Spencer, T; Biederman, J; Wilens, TE; Faraone, SV. Is attention deficit hyperactivity disorder in adults a valid disorder? Harv. Rev. Psychiatry, 1994, 1, 326-335. [120] 120. Gurney, JG; Frotz, MS; Ness, KK; Sievers, P; Newschaffer, CJ; Shapiro, EG. Analysis of prevalence trend of autism spectrum disorder in Minnesota. Arch. Pediatr. Adolesc. Med., 2003, 157, 619-21.

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

71

[121] Charman, T. The prevalence of autism spectrum disorders. Recent evidence and future challenges. Eur. Child Adolesc. Psychiatry, 2002, 11, 249-56. [122] Murphy, C; Boyle, C; Schendel, D; Decouflè, P; Yeargin-Allsopp, M. Epidemiology of mental retardation in children. Mental Retardation Develop. Disab. Res. Rev., 1998, 4, 6-13. [123] Schroeder, SR. Mental retardation and developmental disabilities influenced by environmental neurotoxic insults. Environ. Health Perspect., 2000, 108 (Suppl. 3), 395399. [124] Rodier, PM; Ingram, JL; Tisdale, B; Nelson, S; Romano, J. Embryological origin of autism: development anomalies of cranial motor nerve nuclei. J. Comp. Neurol., 1996, 370, 247-61. [125] Mischoulon, D; Fava, M. Docosahexanoic acid and omega-3-fatty acids in depression. Psychiatric Clin. North America, 2003, 23, 785-94. [126] Tkachev, D; Mimmack, ML; Ryan, MM; Wayland, M; Freeman, T; Jones, PB; Starkey, M; Webster, MJ; Yolken, RH; Bahn, S. Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet, 2003, 362, 798-805. [127] Mitchell, EA; Aman, MG; Turbott, SH; Manku, M. Clinical characteristics and serum essential fatty acid levels in hyperactive children. Clin. Pediatr., 1987, 26, 406-411. [128] Stevens, LJ; Zentall, SS; Deck, JL; Abate, ML; Watkins, BA; Lipp, SR; Burgess, JR. Essential fatty acid metabolism in boys with attention-deficit hyperactivity disorder. Am. J. Clin. Nutr., 1995, 62, 761-768. [129] Burgess, JR; Steens, L; Zhang, W; Peck, L. Long-chain polyunsaturated fatty acids in children with attention-deficit hyperactivity disorder. Am. J. Clin. Nutr., 2000, 71, 327330. [130] 1Stevens, LJ; Zentall, SS; Abate, ML; Kuczek, T; Burgess, JR. Omega-3 fatty Acids in boys with behavior, learning, and health problems. Physiol. Behav., 1996, 59, 915-920. [131] Stradomska, TJ; Tylki-Szymanska, A; Bentkowski, Z. Very long-chain fatty acids in Rett syndrome. Eur. J. Pediatr., 1999, 158, 226-229. [132] Vancassel, S;, Durand, G; Barthelemy, C; Lejeune, B; Marineau, J; Guilloteau, D; Andres, C; Chalon, S. Plasma fatty acid levels in autistic children. Prostaglandins Leukot. Essent. Fatty Acids, 2001, 65, 1-7. [133] Bell, JG; Dick, JR; MacKinlay, EE; Glen, ACA; MacDonald, DJ; Boyle, RM; Riordan, DV. Abnormal fatty acid metabolism in autism and Asperger’s syndrome. In: Phospholipid Spectrum Disorder in Psychiatry and Neurology (2nd edition), Marius Press, Carnforth, 2003. [134] . Young, GS; Maharaj, NJ; Conquer, JA. Blood phospholipid fatty acid analysis of adults with and without attention deficit/hyperactivity disorder. Lipids, 2004, 39, 117123. [135] Ross, MA. Could oxidative stress be a factor in neurodevelopmental disorders? Prostaglandins Leukot. Essent. Fatty Acids, 2000, 63, 61-63. [136] Voigt, RG; Llorente, AM; Jensen, CL; Fraley, JK; Berretta, MC; Heird, WC. A randomized, double-blind, placebo-controlled trial of docosahexaenoic acid supplementation in children with attention-deficit/hyperactivity disorder. J. Pediatr. 2001, 139, 189-196. [137] Richardson, AJ; Puri, BK. A randomized double- blind, placebo-controlled study of the effects of supplementation with highly unsaturated fatty acids on ADHD-related

72

Sa’eed Bawa

symptoms in children with specific learning difficulties. Prog Neuro-Psychopharmacol Biol. Psychiatry, 2002, 26, 233-239. [138] Stevens, L; Zhang, W; Peck, L; Kuczek, T; Grevsted, N; Mahon, A; Zentall, SS; Arnold, E; Burgess, JR. EFA supplementation in children with inattention, hyperactivity, and other disruptive behaviours. Lipids, 2003, 38, 1007-1021. [139] Harding, KL; Judah, RD; Gant, CE. Outcomebased comparison of ritalin versus foodsupplement treated children with ADHD. Altern. Med. Rev., 2003, 8, 319-330. [140] Hirayama, S; Hamazaki, T; Terasawa, K. Effect of docosahexaenoic acid-containing food administration on symptoms of attention deficit/hyperactivity disorder-a placebocontrolled double-blind study. Eur. J. Clin. Nutr., 2004, 58: 467-473. [141] Shoda, R; Matsueda, K; Yamato, S; Umeda, N. Epidemiologic analysis of Crohn’s disease in Japan. Am. J. Clin. Nutr., 1996, 63, 741-745. [142] Belluzi, A; Brignola, C; Campieri, M; Pera, A; Boschi, S; Miglioli, M. Effect of an enteric-coated fish-oil preparation on relapses in Crohn’s disease. N. Engl. J. Med., 1996, 334, 1557-1560. [143] Horwath, K; Papadimitriou, C; Tildon, JC. Gastrointestinal abnormalities in children with autistic children. J. Pediatr., 1999, 135, 559-563. [144] Wakefield, AJ; Anthony, A; Murch, SH; Thomson, M; Montgomery, SM; Davies, S; O'Leary, JJ; Berelowitz, M; Walker-Smith, JA. Enterocolitis in children with developmental disorders. Am. J. Gastroenterol., 2000, 95, 2285-95 [145] Horvath, K; Papadimitriou, JC; Rabsztyn, A; Drachenberg, C; Tildon, JT. Gastrointestinal abnormalities in children with autistic disorder. J. Pediatr., 1999, 135, 559-63 [146] Yehuda, S. Omega-6/omega-3 ratio and brain-related functions. World Rev. Nutr. Dietetics, 2003, 92, 37-56. [147] Yao, JK; van Kammen, DP. Membrane phospholipids and cytokine interaction in schizophrenia. Int. Rev. Neurobiol. 2004, 59, 297-326. [148] Logan, AC. Neurobehavioral aspects of omega-3 fatty Acids: possible mechanisms and therapeutic Value in major depression. Altern. Med. Rev., 2003, 8, 410-425 [149] Calderon, F; Kim, HY. Docosahexaenoic acid promotes neurite growth in hippocampal neurons. J. Neurochem., 2004, 90, 1540. [150] Rojas, CV; Martinez, JI; Flores, I; Ho man, DR; Uauy, R. Gene expression analysis in human fetal retinal explants treated with docosahexaenoic acid. Invest Ophthalmol. Vis. Sci, 2003, 44, 3170-3177. [151] Eldho, NV; Feller, SE; Tristram-Nagle, S; Polozov, IV; Gawrisch, K. Polyunsaturated docosahexaenoic vs docosapentaenoic acid differences in lipid matrix properties from the loss of one double bond. J. Am. Chem. Soc., 2003; 125, 6409-6421. [152] Niu, SL; Mitchell, DC; Lim, SY; Wen, Z-M; Kim, H-Y; Salem Jr., N; Litman BJ. Reduced G protein-coupled signaling efficiency in retinal rod outer segments in response to n-3 fatty acid deficiency. J. Biol. Chem., 2004, 279, 31098-31104. [153] Martinez, M. Restoring the DHA levels in the brains of Zellweger patients. J. Mol. Neurosci., 2001, 16, 309-316. [154] US Department of Health and Human Services, US Environmental Protection Agency. What you need to know about mercury in fish and shell fish 2004 EPA and FDA advice for: women who might become pregnant women who are pregnant nursing mothers

The Role of Omega-3 Fatty Acids in the Prevention and Treatment…

73

young children. Washington, DC, 2004. Report number EPA-823-R-04-005 http://www.cfsan.fda.gov/~dms/admehg3.html (accessed February 11, 2008). [155] FAO/WHO. Fats and oils in human nutrition. Report of a joint expert consultation. Food and Agriculture Organization of the United Nations and the World Health Organization.FAO Food Nutr. Pap., 1994, 57, 1-147. [156] Simopoulos, AP; Leaf, A; Salem N, Jr. Workshop on the essentiality of and recommended dietary intakes for omega-6 and omega-3 fatty acids. J. Am. Coll. Nutr., 1999, 18, 487-489. [157] Hibbeln, JR;, Davis, JM;, Steer, C; Emmett, P; Rogers, I; Williams, C; Golding, J.Maternal seafood consumption in pregnancy and neurodevelopmental outcomes in childhood (ALSPAC study): an observational cohort study. Lancet, 2007, 369, 578-585

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 3

STUDENT REPORTS OF BULLYING: RESULTS FROM THE 2001 SCHOOL CRIME SUPPLEMENT TO THE NATIONAL CRIME VICTIMIZATION SURVEY ∗

Jill F. DeVoe and Sarah Kaffenberger ABSTRACT Bullying in schools is an issue that continues to receive attention from researchers, educators, parents, and students. Despite the common assumption that bullying is a normal part of childhood and encompasses minor teasing and harassment (Lawrence 1998), researchers increasingly find that bullying is a problem that can be detrimental to students’ well-being (Nansel et al. 2001, 2003; Haynie et al. 2001). Bullying is commonly defined as being “exposed, repeatedly and over time, to negative actions on the part of one or more other students” (Olweus 1991). Olweus also suggests that bullying can be characterized by two distinct forms of negative actions: direct and indirect bullying behaviors. Direct bullying takes the form of overt, physical contact in which the victim is openly attacked. Indirect bullying takes the form of social isolation and intentional exclusion from activities. Both forms of bullying, occurring separately or together, can be harmful to students’ well-being and development. This chapter examines the prevalence and nature of bullying in relation to student characteristics, school characteristics, and victimization. In addition, the study explores other behaviors that were reported by the victim, such as fear, avoidance behavior, weapon carrying, and academic grades. It also examines student reports of being bullied by direct means only, bullied by indirect means only, and bullied both directly and indirectly. Readers are alerted to the limitations of the survey design and analysis approach with regard to causality. Conclusions about causality can not be made due to the cross-sectional, nonexperimental design of the survey used. And, while certain characteristics discussed in this chapter, such as school control, gang presence, security guards, and hallway monitors, may be related to one another, this analysis does not control for such relationships. Therefore, no causal inferences should be made between the variables of interest and bullying when reading these results. ∗

Excerpted from NCES 2005-310, dated July 2005.

76

Jill F. DeVoe and Sarah Kaffenberger As reported by public and private school students, ages 12 through 18, in the 2001 School Crime Supplement (SCS) to the National Crime Victimization Survey (NCVS), major findings include the following: ♦

♦

♦

♦ ♦

♦

♦

♦

Fourteen percent of students reported being the victims of bullying. In 2001, 14 percent of students ages 12 through 18 reported that they had been bullied at school in the 6 months prior to the interview (appendix B, table 1). About 3 percent reported that they had been bullied only through direct or physical means, almost 7 percent reported being bullied only indirectly through social exclusion or rejection, and approximately 5 percent reported being bullied both directly and indirectly.1 Sex differences were not detected in most types of bullying. No measurable differences were detected between boys and girls in reports of being bullied, directly or indirectly, in the 6 months prior to the survey (appendix B, table 1). However, differences did emerge between boys and girls who were bullied both directly and indirectly. Specifically, boys were more likely than girls to report being the victims of both direct and indirect bullying (5 percent of boys vs. 4 percent of girls). White, non-Hispanic students were more likely than Black, non-Hispanic students and Other, non-Hispanic students to report being bullied2 (15 percent of White students vs. 12 percent and 11 percent of Other and Black students, respectively) (appendix B, table 1). When reports of indirect bullying only were examined, White students’ and Black students’ reports exceeded those of Hispanic students (7 percent, 7 percent, and 4 percent, respectively). White students (5 percent) were more likely than Black students (3 percent) to report being bullied both directly and indirectly. Younger students were more likely than older students to report being bullied. Students’ reports of being bullied (either directly or indirectly) decreased as grade level increased from 6th (24 percent) to 12th grade (7 percent) (appendix B, table 1). Differences were not detected between public and private school students’ reports of being bullied at school. No measurable differences were detected in public and private school students’ reports of being bullied, directly or indirectly, or in both ways (appendix B, table 2). Students in schools where gangs were present were more likely to report being the victims of bullying. In 2001, students who reported the presence of street gangs at school were more likely to report being bullied (21 percent) than those who reported no presence of street gangs (13 percent) (appendix B, table 2). Fewer students reported bullying in schools with supervision by police officers, security officers, or staff hallway monitors. In schools where a security guard or assigned police officer was present, fewer students (13 percent) reported being bullied compared to students in schools with no such supervision (16 percent) (appendix B, table 2). Fewer students in schools with staff hallway monitors reported being bullied than did students in schools without such hallway supervision (14 vs. 18 percent). Victims of bullying were more likely to experience a criminal victimization at school. Bullied students were more likely to experience any type of victimization (13

1 Youth ages 12 through 18 were first asked “Have you been bullied at school? That is, has anyone picked on you a lot or tried to make you do things you did not want to do (e.g., give them money)?“ This is referred to as direct bullying. Students were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. References to “bullying“ include youth who reported they were either directly or indirectly bullied. Categories are mutually exclusive. Directly Only, Indirectly Only, and Both Directly and Indirectly are distinct categories. Students appearing in one category do not appear in other categories. 2 For ease of presentation, White, non-Hispanic, Black, non-Hispanic, and Other, non-Hispanic race/ethnicities will be described as White, Black, and Other.

Student Reports of Bullying

♦

♦

♦

♦

77

percent), a serious violent victimization (2 percent), a violent victimization (7 percent), or a property victimization (8 percent) at school when compared to those students who were not bullied (4 percent, 0.3 percent, 1 percent, and 4 percent, respectively) (appendix B, table 3).3 Students who reported only direct bullying were more likely to be violently victimized than students who reported only indirect bullying (11 percent vs. 3 percent). Victims of bullying were more afraid of being attacked at school and elsewhere. Bullied students were more likely to report being fearful of attack at school at least some of the time (18 percent), on the way to and from school (11 percent), and away from school (12 percent) than were students who were not bullied (3 percent, 2 percent, and 3 percent, respectively) (appendix B, table 4). Victims of bullying were more likely to avoid certain areas of the school and certain activities out of fear of an attack. Specifically, bullied students were more likely than nonbullied students to report the following avoidance behaviors: avoiding the shortest route to school (6 percent of bullied students vs. 2 percent of nonbullied students); the entrance to the school (4 percent vs. 1 percent); hallways or stairs (7 percent vs. 1 percent); and the school cafeteria (6 percent vs. 1 percent) (appendix B, table 5). Bullied students were also more likely than nonbullied students to avoid restrooms (7 percent vs. 2 percent), the parking lot (5 percent vs. 1 percent), and other places inside the school building (5 percent vs. 1 percent) or other places on school grounds (6 percent vs. 1 percent). Victims of bullying were more likely to report that they carried weapons to school and were engaged in physical fights. Specifically, students who were bullied were more likely to report that they carried a weapon to school for protection (4 percent), as compared to students who were not bullied (1 percent) (appendix B, table 6). Bullied students were also more likely to report being involved in a physical fight (15 percent), compared to nonbullied students (4 percent). Of those students who reported lower grades, victims of bullying were more likely to report receiving D's and F's than their nonbullied counterparts. Bullied students were more likely to report receiving lower academic grades, or mostly D's and F's, than their nonbullied peers (8 percent vs. 3 percent) (appendix B, table 7). Victims of both forms of bullying were more likely to report mostly D's and F's (12 percent) than those bullied either directly only or indirectly only (7 percent and 6 percent).

INTRODUCTION Students are victims of a spectrum of problem behaviors at school, ranging from minor disciplinary problems to criminal victimization (DeVoe et al. 2004). Bullying is one form of these problem behaviors that concerns students, educators, and parents because of its potential detriment to the students’ well-being (Nansel et al. 2001, 2003; Haynie et al. 2001). Defining bullying is a difficult task; however, most research agrees that bullying comprises physical, verbal, and psychological behaviors such as hitting, teasing, taunting, and manipulating social relationships (Banks 1997; Ericson 2001). The investigation of bullying is further complicated by the complex dynamics of bullying scenarios and the developmental context for social development in which bullying plays a role. Further, aggression among youth often serves varied purposes for children at different stages of development. 3 Serious violent crimes include rape, sexual assault, robbery, and aggravated assault. Violent crimes include serious violent crimes and simple assault. Any crimes include violent crimes and theft.

78

Jill F. DeVoe and Sarah Kaffenberger

Hawkins, Pepler, and Craig (2001) found that peers were present in 88 percent of bullying episodes. Thus, bullying frequently involves the support of peers within the school community and is often not an isolated event between two individuals. In addition, aggressive behavior, such as bullying, is expressed differently over time and may change in purpose, as children transition from middle to secondary school. As Cairns et al. (1989) discuss, patterns of, and motivation for aggression change over the course of childhood and cannot be examined independently of the developmental context in which aggression occurs. Cillessen and Mayeaux (2004) found that physical and relational aggression, peer approval, and popularity were intricately linked, but that the relationships between these variables vary with age, gender, and by type of aggression. While resolution to these definitional, contextual, and developmental complexities are unable to be addressed in the current investigation, this chapter provides a broad summary of bullying reported by student victims in 2001. Olweus (1993) has produced an instructive definition of bullying that includes three essential elements of bullying behavior: (1) the behavior is aggressive and negative; (2) the behavior is carried out repeatedly; and (3) the behavior occurs in a relationship where there is an imbalance of power between the parties involved. This tripartite definition of bullying is now used by many researchers (e.g., Smith et al. 2002). In a further refinement of the variety of behaviors that encompass bullying, Olweus identifies two subtypes of bullying that are used as the basis of this chapter. The first subtype is direct, physical aggression, and the second is indirect behavior such as social exclusion or rejection. Direct bullying often takes the form of overt, physical contact in which the victim is openly attacked. Indirect bullying often takes the form of social isolation and intentional exclusion from activities. Research suggests that indirect forms of bullying are more often employed by girls than boys (Ericson 2001; Banks 1997; Carney and Merrell 2001; Crick and Grotpeter 1995). Researchers of aggression stress the importance of the distinction between its physical and social forms. Underwood, Galen, and Paquette (2001) more recently coined the term “social aggression“ to encompass the less physical and indirect forms of hurtful behavior. These authors discourage the use of the term “indirect” because the term implies that the behavior does not involve direct or overt interaction with the victim. They also favor the term “social aggression” as it more aptly targets the purpose of the behavior as harmful. Finally, they believe that this type of aggression can be conveyed through nonverbal means, such as social exclusion and the term “social aggression” is more accurate. For the purposes of this article, the term “indirect“ will be retained to show the dichotomy of behaviors being discussed and to maintain the conceptualization proposed by Olweus, recognizing that more current conceptualizations exist in the literature. The term “indirect bullying” includes both verbal and nonverbal behaviors, and does not imply that the victim was unaware of the activity. This Statistical Analysis Report provides estimates of bullying at school as reported by students ages 12 through 18 who were enrolled in grades 6 through 12 in the 6 months prior to survey administration. School-related data are drawn from the 2001 School Crime Supplement (SCS) to the National Crime Victimization Survey (NCVS). Data about characteristics of the individual (including sex, race/ethnicity, household income, and urbanicity) and victimization are drawn from NCVS variables appended to the SCS data. The NCVS is the nation’s primary source of information on crime victimization and the victims of crime. The NCVS collects detailed information on the frequency and nature of crimes experienced by Americans and their households each year. The survey measures both

Student Reports of Bullying

79

crimes reported and not reported to police. The NCVS collects data on all members of selected households and surveys all who are age 12 and above, for a total of about 79,000 people, every 6 months. The SCS is a supplement to the NCVS that was created to collect additional information about school-related victimization on a national level. It is administered for a 6-month period from January through June in all NCVS households. The SCS is a nationally representative sample of students ages 12 through 18 and has been administered in 1989, 1995, 1999, 2001, and 2003, with plans for collection in 2005. This study focuses on the 2001 collection. Respondents eligible for the supplement were those in the specified age range who attended school during the 6 months prior to the interview and were enrolled in grades 6 through 12. A total of 8,374 students participated in the 2001 SCS. The 2001 SCS questionnaire measures respondents’ perceptions of whether they have been bullied directly and/or indirectly, and specifies the aggressive nature of the behavior and whether or not the behavior happens “often” or “a lot.” Specifically, youth were first asked “Have you been bullied at school? That is, has anyone picked on you a lot or tried to make you do things you did not want to do (e.g., give them money)?” This is referred to as direct bullying. In a separate question, students were also asked if they have often felt rejected by other students at school: “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This type of bullying is referred to as indirect bullying. This chapter focuses not only on the prevalence of bullying, but also on those subsets of students who reported being the victims of direct bullying, indirect bullying, and both direct and indirect bullying. Different types of bullying may affect different groups of students, occur in different types of schools, or affect student behavior in different ways. These distinctions allow readers to differentiate between students who were either physically (directly) or socially (indirectly) bullied, and also to identify those students who were bullied both physically and socially.4 Additional analysis describes the characteristics of students affected by these types of behavior and the characteristics of schools in which these behaviors occur. Because of prior research that suggests victims of bullying may resort to aggressive behaviors in response to being bullied (Nansel et al. 2003), the extent to which reports of bullying arerelated to victim behaviors such as weapon carrying, physical fights, fear, and avoidance is explored. Finally, for educators, the academic success of students is of paramount importance. For this reason, self-reported academic performance of bullied students is also examined. Readers should note that estimates of bullying presented in this study are derived from victims' self-reports of bullying experiences. Limitations inherent to victimization surveys such as the SCS might impact estimates of bullying (Cantor and Lynch 2000). First, the SCS includes unbounded interviews, or interviews that include victimizations that exceed the 6month reference period asked of SCS respondents. This may artificially increase reports of victimization since respondents may recall events outside of the given reference period. Second, the SCS does not use a classification scheme for determining bullying events. That is, the larger NCVS uses sets of characteristics to classify events as criminal whereas the SCS 4

Students who reported being the victims of both forms of bullying were not necessarily bullied more than students who reported either direct or indirect bullying. Rather, these students simply reported that they were subject to a wider variety of bullying behaviors including both direct and indirect means.

80

Jill F. DeVoe and Sarah Kaffenberger

often relies on the respondent to self-determine a condition. This allows for the victim to use his own interpretation or conceptions to define a situation, when the same situation may not have been labeled bullying by a bystander or the offender. Third, victim surveys emphasize crime events as incidents at one point in time. Reality tells us that victims can often live in a state of victimization where they are threatened or victimized regularly. While the NCVS does allow for these series to be flagged for criminal victimizations, reports of bullying behaviors are not collected in this way. Additional caution is in order when examining bullying as well as the other variables used in this report. Because all variables of interest on the SCS are self-reported, information about the respondent and his school may be inaccurate due to error in recall, falsification, or exaggeration. For example, a student either may not be forthright or artificially inflate his self-reported academic grades. In addition, the respondent may forget a bullying event entirely or recall the characteristics of the event inaccurately. This would lead to an underestimation of victimization. There is no independent or external verification of any of the SCS variables used in this report. Finally, readers are alerted to the limitations of the survey design and analysis approach with regard to causality. Conclusions about causality can not be made due to the crosssectional, non-experimental design of the SCS. And, while certain characteristics discussed in this report, such as school control, gang presence, security guards and hallway monitors, may be related to one another, this analysis does not control for such relationships. Therefore, no causal inferences should be made between the variables of interest and bullying when reading these results.

PREVALENCE OF BULLYING IN SCHOOLS In 2001, approximately 14 percent of students ages 12 through 18 were victims of bullying at school in the 6 months prior to the survey administration (figure 1 and appendix B, table 1). For this report, the total percentage of students bullied refers to those students who were either directly or indirectly bullied. Three percent reported only direct bullying— that someone had picked on them a lot or tried to make them do something they did not want to do. Seven percent of students reported only indirect bullying—that other students had rejected them or excluded them from activities. Five percent reported being bullied both directly and indirectly.

CHARACTERISTICS OF BULLIED STUDENTS When looking at the direct and indirect forms of bullying, prior research suggests, first, that boys typically engage in more direct bullying methods than girls and are more often the victims of this type of bullying (Nansel et al. 2001; Olweus 1997). Second, research suggests indirect bullying, such as social exclusion and rejection, is the type of bullying used more frequently by girls than boys (Banks 1997; Olweus 1997, 1999).

Student Reports of Bullying

81

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school.Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“This is referred to as indirect bullying. Total includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to total because of rounding. Figure 1. Percentage of students ages 12–18 who reported being bullied, bullied directly only, bullied indirectly only, and bullied in both ways: 2001.

In this analysis of the 2001 SCS, no measurable differences were detected between boys and girls in their reports of direct or indirect bullying only, but when looking at students who were bullied both directly and indirectly, measurable differences did emerge (appendix B, table 1). In the 2001 SCS, boys were more likely than girls to report being both directly and indirectly bullied (5 percent of boys vs. 4 percent of girls) (appendix B, table 1). White, non-Hispanic students were more likely than Other, non-Hispanic students and Black, non-Hispanic students to report being bullied (15 percent of White, non-Hispanic students vs. 11 percent and 12 percent of Other, non-Hispanic and Black, non-Hispanic students, respectively) (appendix B, table 1).5 When indirect bullying behavior was examined, White and Black students’ reports (7 percent each) were higher than those of Hispanic students’ (4 percent). Those students who were bullied both directly and indirectly were more likely to be White than Black (5 percent vs. 3 percent).6 No measurable - racial/ethnic differences in bullying were detected among victims of only direct bullying behavior. While the research on race/ethnicity and bullying is scant, the findings by Nansel et al. (2001) found that Black youth were less likely than their White and Hispanic peers to report being bullied. As the grade levels of students in the 2001 SCS increased, from 6th through 12th grades, the total percentage of students reporting that they were bullied decreased (figure 2 and

5 For the remainder of this report, White, non-Hispanic; Black, non-Hispanic; and Other, non-Hispanic race/ethnicities are described as White, Black, and Other, respectively, for ease of presentation. 6 While estimates among other race/ethnicity categories may appear to be different, these differences may not be statistically significant due to large standard errors. Please refer to Appendix A for further discussion about standard errors and the design of the survey.

82

Jill F. DeVoe and Sarah Kaffenberger

appendix B, table 1). Specifically, 24 percent of 6th-graders reported being bullied at school, compared to 7 percent of 12th-graders. Sixth-grade students were more likely than 12th-grade students to report both direct (5 percent vs. 1 percent) and indirect (10 percent vs. 5 percent) bullying. This finding is consistent with previous research on bullying and grade level and is explained in terms of establishing social hierarchies. Specifically, prior researchers suggest that bullying may be used as a way to establish dominance in social structures and that the transition to middle school (which traditionally occurs around the 6th grade) should be accompanied by an increase in bullying and then follow an age-related decline as dominance hierarchies are solidified (Pellegrini and Long 2002; Pellegrini and Bartini 2001). Another possible reason for this finding comes from Olweus’ (1993) research, which suggests that younger and weaker students are exposed more frequently to bullying and that a considerable part of bullying behavior is carried out by older students against these younger victims. Olweus (1978, 1980) found no relationship between socioeconomic status of the family and being the victim of bullying and suggests that there are similar proportions of bullies and victims across all socioeconomic levels. Interestingly, Olweus attributes this finding to the relative homogeneity in the Scandinavian countries in which his studies were conducted. He speculates that in other countries, such as the United States, stronger associations between bullying and socioeconomic indicators, such as income, would be found. However, no pattern was detected between student reports of bullying and student household income in the 2001 SCS, a nationally representative U.S. data set (appendix B, table 1). Likewise, no measurable differences were detected in the total percentage of students who reported bullying by students’ residential urbanicity (appendix B, table 1). Nansel and her colleagues (2001) found no measurable differences among rural, suburban, and urban students’ reports of bullying in their investigation as well.

STUDENT REPORTS OF SCHOOL CHARACTERISTICS WHERE BULLYING OCCURS7 About 14 percent of students in both public schools and private schools reported being bullied (appendix B, table 2). Three percent of public and private school students reported direct bullying only, and 7 percent of public and private school students reported indirect bullying only. In 2001, students who reported the presence of street gangs at school were more likely to report being bullied in any way (21 percent) than those who reported that street gangs were not present (13 percent) (appendix B, table 2). Similarly, those who reported street gangs at school were more likely to report direct bullying only (5 percent), indirect bullying only (8 percent), and both direct and indirect bullying (8 percent) than those students who did not report a street gang presence (3 percent, 6 percent, and 4 percent, respectively).

7

These data on school characteristics do not represent a sample of schools, rather they represent a sample of students. Thus, school characteristics are discussed in terms of student reports of school characteristics in this section.

Student Reports of Bullying

83

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. 1 Categories are mutually exclusive. Directly Only, Indirectly Only and Both Directly and Indirectly are distinct categories. Students appearing in one category do not appear in other categories. Figure 2. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by grade level: 2001.

Schools take various measures to guard against criminal victimization and disciplinary problems. Increasing supervision of students is one avenue toward decreasing bullying in schools (Olweus 1993). Supervision, such as the employment of security personnel and the use of hallway monitors may deter bullies from attacking or threatening other students, calling them names, or making fun of them. In 2001, fewer students reported being bullied in schools with a security guard or an assigned police officer (13 percent), compared to students in schools with no such supervision (16 percent) (figure 3 and table 2). No measurable differences were detected (between schools with and without security officers) for either direct bullying or indirect bullying considered separately. More students were victims of both types of bullying in schools with security personnel (6 percent) than in schools without security guards or assigned police officers (4 percent). Another common practice of supervision is hallway monitoring by school staff. Hall monitoring by school staff was associated with fewer bullied students (14 percent of students were bullied in schools with staff hallway monitors, vs. 18 percent of students being bullied in schools without such monitors). However, no measurable differences were detected in students’ reports of direct bullying in schools with and without hallway supervision (figure 3 and appendix B, table 2).

84

Jill F. DeVoe and Sarah Kaffenberger

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Figure 3. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by security presence and hallway supervision: 2001 1Categories are mutually exclusive. Directly Only, Indirectly Only and Both Directly and Indirectly are distinct categories. Students appearing in one category do not appear in other categories.

Students were less likely to report being indirectly bullied only in schools with hallway supervision (6 percent) than in schools without such supervision (9 percent). No measurable differences were detected in both direct and indirect bullying in schools with and without hallway supervision. Readers should note that while school characteristics such as school control, gang presence, security guards, and hallway monitors may be related to one another, the analysis does not control for such relationships. These data cannot address the question of whether having security guards or hallway monitors had an impact on bullying. Therefore, no causal inferences should be made when reading these results.

BULLYING AND VICTIMIZATION Elliott (1994) suggests that bullied students are at higher risk for criminal victimization at school, especially violent victimization. The purpose of this section is to examine student

Student Reports of Bullying

85

reports of bullying and their reports of serious violent, violent, and property victimization. Prior to presenting the results, some explanation of the differences between these two constructs, bullying and criminal victimization, and how they are collected is necessary. Information on criminal victimization is collected in the main NCVS, to which the SCS is a supplement. Victimization is collected using a classification scheme in which the respondent identifies the characteristics of an event and those characteristics are used to classify the event as criminal. (For more information on the construction of the NCVS victimization variables used in this report, see the Glossary in appendix A). Readers may suspect that students who report direct bullying, or more overt physical attacks, may be reporting many of the same instances in their reports of criminal victimization. However, these two concepts are addressed quite differently during data collection for the SCS and therefore are reported as distinct events in this report. As stated, the larger NCVS uses sets of characteristics to classify events as criminal. This was the approach taken for determining the serious violent, violent, and property victimizations reported here. In contrast, the SCS relies on the respondent to self-determine if they are bullied. Specifically, respondents are asked if they are bullied and allowed to determine if they fall into the bullying category based on the definition provided, rather than asked about characteristics of the situation and allowing the analyst to determine if the respondent has been bullied. This allows for the victim to use his or her own interpretation to define a situation, when the same situation may not have been labeled bullying by a bystander or the offender. Results show, in 2001, 6 percent of all students ages 12 through 18 reported any form of criminal victimization at school (appendix B, table 3).8 Serious violent victimization at school (including rape, sexual assault, robbery, and aggravated assault), was reported by less than 1 percent of students, and violent victimization at school (which includes those offenses in the serious violent category plus simple assaults) was reported by 2 percent of all students. Property victimization, which includes theft of a student’s property at school, was reported by 4 percent of students (figure 4 and appendix B, table 3). Students who report being bullied at school were at least twice as likely to report being the victims of crime at school compared to nonbullied students. When focusing on the total sample of students who reported being bullied at school (14 percent of the entire sample) (see appendix B, table 1), these students were more likely to experience any victimization, a serious violent victimization, a violent victimization, or a property victimization at school when compared to those students who were not bullied (figure 4 and appendix B, table 3). Specifically, 13 percent of bullied students reported any victimization at school compared to 4 percent of nonbullied students. About 2 percent of bullied students reported a serious violent victimization, 7 percent reported a violent victimization, and 8 percent reported a -property theft; 0.3 percent of nonbullied students reported a serious violent victimization, 1 percent reported a violent victimization, and 4 percent reported a property theft. When looking at those students who were directly and/or indirectly bullied, interesting results emerge. First, the findings show that 18 percent of directly, or physically bullied students reported any victimization, and 7 percent of indirectly bullied students reported any

8 Any victimization includes those students who reported being the victim of a violent crime or a property crime. Students who reported being the victim of both a property and a violent crime are counted once in the “any“ category.

86

Jill F. DeVoe and Sarah Kaffenberger

victimization (figure 4 and appendix B, table 3). About 17 percent of students who reported both direct and indirect bullying reported any victimization. Second, the findings show that students who reported both types of bullying were more likely than students who reported only direct or indirect bullying to report being seriously violently victimized. About 1 percent of only directly bullied students and 0.3 percent of only indirectly bullied students reported a serious violent victimization, compared to larger percentage (4 percent) of students reporting both types of bullying. Third, directly bullied students were more likely than indirectly bullied students to be violently victimized (11 percent vs. 3 percent). Eleven percent of students reporting both forms of bullying also reported a violent victimization, a finding that is consistent with previous literature (Elliott 1994). Finally, victims of direct bullying only (9 percent) or both forms of bullying (10 percent) were more likely than those who reported only indirect bullying (5 percent) to be the victims of property victimization.

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: Serious violent crimes include rape, sexual assault, robbery, and aggravated assault. Violent crimes include serious violent crimes and simple assault.Any crimes include violent crimes and theft. “At school” includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Figure 4. Percentage of students ages 12–18 who reported being victimized at school during the previous 6 months, by reports of being bullied directly only, bullied indirectly only, or being bullied directly or indirectly at school: 2001. 1 Categories are mutually exclusive. 2 Serious violent crimes are also included in violent crimes. # Rounds to zero.

Student Reports of Bullying

87

BULLYING AND VICTIM OUTCOMES/BEHAVIORS Psychological research suggests that passive victims of bullying are anxious and insecure (Olweus 1999; Wilton, Craig, and Pepler 2000; and Dodge et al. 1990). Passive victims often react to provocation by crying, withdrawing, or becoming quiet. This signals that they will not react or retaliate if they are attacked or insulted. Another type of victim, the “provocative” victim, is characterized by both anxious and aggressive reaction patterns (Olweus 1999). Provocative victims are likely to counter attack and have difficulty relating emotionally, whereas passive victims often avoid and acquiesce to their attackers (Wilton, Craig, and Pepler 2000). In fact, some research has shown that socially “rejected” boys are more likely to follow an act of aggression with another act of aggression than are boys who did not experience social rejection (Dodge et al. 1990). The purpose of this section is to investigate whether students who report only direct bullying respond with different defensive mechanisms or reactive behaviors than students who are bullied only indirectly or those who are bullied in both ways. While the SCS is a cross-sectional survey that does not allow the reader to know which event occurred first, the data do show that students who are victims of different types of bullying at school more often experience or engage in a variety of behaviors different from those of students not bullied. These behaviors include fear of attack; avoidance behaviors such as truancy from school; skipping classes, or not participating in extracurricular activities; weapon carrying; involvement in physical fights; and varied academic performance. These data cannot address the question of whether bullying has an impact on these behaviors and outcomes, whether these behaviors elicit bullying from others, or whether some other combination of factors influences both bullying and these other behaviors Fear is one by-product of threats and violence, and those students who are bullied at school may be afraid to attend school (Ericson 2001; Berthhold and Hoover 2000). The 2001 SCS findings are consistent with this research. Bullied students were more likely than nonbullied students to report being “sometimes or most of the time” afraid of an attack at school (18 percent vs. 3 percent), on the way to and from school (11 percent vs. 2 percent), and away from school (12 percent vs. 3 percent) (appendix B, table 4). Bullied students who were targeted both directly and indirectly were the most likely group of bullied students to sometimes or most of the time be afraid of an attack at school compared students who were bullied only directly and only indirectly (31 percent, 14 percent and 11 percent, respectively). Similar results were found for fear on the way to and from school, with 17 percent of students who were bullied both directly and indirectly reporting fear sometimes or most of the time, compared to 10 percent of students who were bullied only directly and 7 percent who were bullied only indirectly. As discussed above, bullying can coincide with fear. Student reaction to this fear may lead to avoidance behavior or truancy. Specifically, students may act upon their feelings of fear and actually start avoiding places in school or be truant from school, classes, or extracurricular activities. Bullied students were more likely than nonbullied students to report avoidance behavior, such as avoiding the shortest route to school (6 percent of bullied students vs. 2 percent of nonbullied students), the entrance to the school (4 percent vs. 1 percent), hallways or stairs (7 percent vs. 1 percent), and the school cafeteria (6 percent vs. 1 percent) (appendix B, table 5). They were also more likely than nonbullied students to avoid restrooms (7 percent vs. 2 percent), the parking lot (5 percent vs. 1 percent), and other places

88

Jill F. DeVoe and Sarah Kaffenberger

inside the school building (5 percent vs. 1 percent) or on school grounds (6 percent vs. 1 percent). The SCS data also show that victims of both forms of bullying were more likely than victims of only direct and indirect bullying to avoid the shortest route to school (9 percent vs. 3 and 5 percent, respectively), the entrance to the school (7 percent vs. 3 and 2 percent), the school cafeteria (10 percent vs. 5 and 3 percent), and school restrooms (10 percent vs. 6 and 5 percent). Taken to an extreme, this avoidance behavior may lead to truancy. Students who are bullied are at higher risk for truancy and subsequent dropout (Carney and Merrell 2001). In the 2001 SCS, bullied students were more likely than nonbullied students to skip school entirely because they thought someone might attack or harm them (4 percent vs. 1 percent) (figure 5 and appendix B, table 5). Bullied students were more likely to skip classes than were nonbullied students (3 percent vs. 0.2 percent). Bullied students were also more likely to skip extracurricular activities compared to nonbullied students (4 percent vs. 1 percent). Truancy was more likely to occur among students who were victims of direct bullying than among victims of indirect bullying. Specifically, 4 percent of students who were directly bullied skipped school compared to 1 percent of students who were indirectly bullied.

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Figure 5. Percentage of students ages 12–18 who reported skipping school, class, or extra-curricular activities during the previous 6 months, by reports of being bullied directly only, bullied indirectly only, or being bullied directly and indirectly at school: 2001. 1 Categories are mutually exclusive. # Rounds to zero.

Student Reports of Bullying

89

Students who were victims of both types of bullying were more likely to skip school (7 percent), class (7 percent), and extracurricular activities (6 percent) than were students who were only indirectly bullied (1 percent, 1 percent, and 2 percent, respectively), and were also more likely than students who were only directly bullied to skip class (3 percent). Research suggests that being victimized by bullying may be an antecedent to aggressive behavior (Nansel et al. 2003, Loeber and Stouthamer-Loeber 1998). As discussed above, bullied students may resort to aggression in retaliation or be more inclined to respond to negative behaviors with antisocial responses. In the 2001 SCS, about 2 percent of all students ages 12 through 18 reported carrying a weapon (gun, knife, or some other weapon) to school for protection, and 5 percent reported being involved in a physical fight (figure 7 and appendix B, table 6). While the 2001 SCS cannot be used to establish causality, results show that more bullied students carried a weapon to school for protection (4 percent) in the 6 months prior to the survey than did nonbullied students (1 percent). Consistent with this finding, Carney and Merrell (2001) also report that victims of bullying are more likely than their nonbullied counterparts to bring weapons to school in order to protect themselves. No measurable differences were detected in the 2001 SCS in student reports of weapon carrying among victims of only direct, only indirect, and both forms of bullying. Bullied students were also more likely to be involved in physical fights at school. About 15 percent of bullied students reported being involved in a physical fight, compared to 4 percent of nonbullied students (figure 6 and appendix B, table 6). Bullied students were more likely than nonbullied students (4 percent) to engage in fights regardless of whether they were bullied only directly (15 percent) or only indirectly (10 percent). Victims of indirect bullying only were less likely to engage in fights than were victims of both forms of bullying (10 percent vs. 21 percent). Lawrence (1998) suggests that victims of bullying may become aggressive toward other students. In this case, regardless of the type of bullying—whether physical or social—bullied students may tend to react through physical confrontation. Academic achievement is a focal concern for educators and schools across the nation. Past research demonstrates that students who are targeted by bullies often have difficulty concentrating on their schoolwork, resulting in academic achievement that is marginal to poor (Batsche and Knoff 1994). Farrington (1993) also suggests that the psychological consequences of bullying can include lack of concentration on schoolwork. The SCS 2001 allows for the examination of bullying behavior and self-reports of academic grades. A few patterns emerged in the data, first, bullied students were less likely to report getting mostly A’s than students who did not report or experience bullying at school (27 percent of bullied students vs. 34 percent of non bullied students) (appendix B, table 7). However, bullied students were more likely to report receiving A's and B's than D's and F's (27 percent and 41 percent vs. 8 percent, respectively). Second, of those students who reported lower grades, bullied students were more likely to report receiving mostly D's and F's than their non-bullied counterparts (8 percent vs. 3 percent). Victims of both forms of bullying were more likely to report getting D's and F's than those who were bullied directly or indirectly (12 percent, 7 percent, and 6 percent, respectively).

90

Jill F. DeVoe and Sarah Kaffenberger

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Students included as carrying weapons reported carrying a gun, knife or other weapon to school in the 6 months prior to the survey. Population size for students ages 12–18 is 24,315,000. Figure 6. Percentage of students ages 12–18 who reported carrying a weapon for protection or being involved in a physical fight at school during the previous 6 months, by reports of being bullied directly only, indirectly only, or being bullied directly and indirectly at school: 2001.1 Categories are mutually exclusive.

SUMMARY AND CONCLUSIONS The analyses in this study employ specific subtypes of bullying which may be useful when looking at bullying interactions. This study shows that 14 percent of students ages 12 through 18 reported they had been bullied at school in the previous 6 months. Three percent reported being the victims of direct or physical bullying only, 7 percent reported being the victims of indirect, or social bullying, and 5 percent reported being the victims of both types of bullying. This study also shows that the specific subtypes of bullying are often related to different individual-level and school-level characteristics. Bullied students are generally younger students of either sex, and are more often White than Black. No measurable differences were detected when comparing the prevalence of bullying by students’ household income or urbanicity.

Student Reports of Bullying

91

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Figure 7. Percentage of students ages 12–18 who reported receiving different academic grades during the school year, by reports of being bullied directly only, indirectly only, or being bullied directly and indirectly at school: 2001.1 Categories are mutually exclusive.

Bullied students report that their schools are more likely to have gangs and less likely to have supervision in the form of police officers, security guards, or school staff in the hallways. Finally, student reports of attending public or private schools are not associated with student reports of bullying. The findings also suggest that students who are victims of bullying at school more often are victimized in other ways. When compared to nonbullied students, bullied students are more likely to fear attack at school, on the way to and from school, and away from school. Bullied students engage in a variety of avoidance behaviors and are more likely to be truant from school, classes, or extracurricular activities than their nonbullied peers. A highlight of this study is the finding that victims of bullying are more likely to exhibit negative outcome behaviors, such as weapon carrying or being involved in physical fights, compared to students who are not bullied. In fact, more students who were bullied reported carrying a weapon to school for protection (4 percent), compared to nonbullied students (1 percent). In addition, more bullied students were involved in a physical fight than were nonbullied students (15 percent vs. 4 percent). One prior research investigation suggests that victims of bullying are more likely to engage in violent behaviors (Nansel et al. 2003), and those findings are confirmed in this national analysis. Of final import to educators, parents, and practitioners, the findings show that bullied students were less likely to report receiving A’s than nonbullied students, but were more likely to report receiving A’s and B’s than D’s and F’s. When focusing on poorly performing

92

Jill F. DeVoe and Sarah Kaffenberger

students, bullied students were more likely to report getting mostly D’s or F’s than their nonbullied counterparts.

APPENDIX A: TECHNICAL NOTES Survey The National Crime Victimization Survey (NCVS) and the School Crime Supplement (SCS) to the NCVS were used to provide estimates in this report. The NCVS, administered for the U.S. Bureau of Justice Statistics by the Census Bureau, is the nation’s primary source of information on crime victimization and the victims of crime. Initiated in 1972 and redesigned in 1992, the NCVS collects detailed information on the frequency and nature of the crimes of rape, sexual assault, robbery, aggravated and simple assault, theft, household burglary, and motor vehicle theft experienced by Americans and their households each year. The survey measures crimes reported as well as those not reported to police. The 2001 NCVS sample consists of about 53,730 households selected using a stratified, multistage cluster design. In the first stage, the primary sampling units (PSUs), consisting of counties or groups of counties, were selected. In the second stage, smaller areas, called Enumeration Districts (EDs), were selected from each sampled PSU. Finally, from selected EDs, clusters of four households, called segments, were selected for interview. At each stage, the selection was done proportionate to population size in order to create a self-weighting sample. The final sample was augmented to account for housing units constructed after the 1990 Decennial Census. Within each sampled household, Census Bureau personnel interviewed all household members ages 12 and older to determine whether they had been victimized according to the measured crimes during the 6 months preceding the interview. About 79,360 persons ages 12 and older are interviewed each 6 months. Households remain in the sample for 3 years and are interviewed 7 times at 6-month intervals. Created as a supplement to the NCVS and codesigned by the National Center for Education Statistics (NCES) and Bureau of Justice Statistics (BJS), the SCS survey was conducted in 1989, 1995, 1999, 2001, and 2003 to collect additional information about school-related victimizations on a national level. The survey was designed to assist policymakers as well as academic researchers and practitioners at the federal, state, and local levels in making informed decisions concerning crime in schools. The SCS asks students a number of key questions about their experiences with and perceptions of crime and violence that occurred inside their school, on school grounds, on a school bus, or on the way to or from school. Additional questions not included in the NCVS were also added to the SCS, such as the presence of weapons and street gangs in school, whether students were bullied or rejected at school, attitudinal questions relating to fear of victimization and avoidance behavior at school, preventive measures used by the school, participation in afterschool activities, perceptions of school rules, the presence of hate-related words and graffiti in school, as well as the availability of drugs and alcohol in school. In all SCS survey years, the SCS was conducted for a 6-month period from January through June in all households selected for the NCVS. Within these households, the eligible respondents for the SCS were those household members ages 12 through 18 who had

Student Reports of Bullying

93

attended school at any time during the 6 months preceding the interview, and were enrolled in grades 6 through 12 in a school that would help them advance toward a high school diploma. Eligible respondents were asked the supplemental questions in the SCS only after completing their entire NCVS interview. In 2001, the definition for “at school” pertaining to victimizations included those that occurred on school property, going to and from school, or while attending school. The NCVS variables appended to the SCS data file asking where the incident happened and what the victim was doing when it happened were used to ascertain whether the incident happened at school. The NCVS “type of crime” variable appended to the SCS data file was used to classify victimizations of students in the SCS as violent or property victimization. Any victimization is a combination of violent victimization and property. If the student reported an incident of either violent or property victimization or both, he or she is counted in the any victimization measure. Violent crimes include serious violent crimes—rape, sexual assault, and aggravated assault —and simple assault. See the Glossary for more detailed information about the construction of these and other variables. Readers should note that several limitations inherent to victimization surveys, such as the NCVS SCS, might impact estimates of bullying (Cantor and Lynch 2000). First, the SCS includes unbounded interviews, or interviews that include victimizations that exceed the 6month reference period asked of SCS respondents. This may artificially increase reports of victimization since respondents may recall events outside of the given reference period. For example, a respondent may mistakenly report an event that happened 1 year ago and not within the requested past 6 months. Second, the SCS does not use a classification scheme for determining bullying events. That is, the larger NCVS uses sets of characteristics to classify events as criminal whereas the SCS often relies on the respondent to self-determine a condition. For example, respondents are asked if they are bullied and allowed to determine if they fall into the bullying category based on the definition provided, rather than asked about characteristics of the situation and allowing the analyst to determine if the respondent has been bullied. This allows for the victim to use his own interpretation or conceptions to define a situation, when the same situation may not have been labeled bullying by a bystander or the offender. Third, victim surveys emphasize crime events as incidents at one point in time. Reality tells us that victims can often live in a state of victimization where they are threatened or victimized regularly. While the NCVS does allow for these series to be flagged for criminal victimizations, reports of bullying behaviors are not collected in this way. Finally, respondent recall of bullying events may be inaccurate. People may forget the event entirely or recall the characteristics of the event inaccurately. This would lead to an underestimation of victimization.

Unit and Item Response Rates Unit response rates indicate how many sampled units have completed interviews. Because interviews with students could only be completed after households had responded to the NCVS, the unit completion rate for the SCS reflects both the household interview completion rate and the student interview completion rate. A total of 8,374 students participated in the SCS 2001. The household completion rate was 93 percent, and the student

94

Jill F. DeVoe and Sarah Kaffenberger

completion rate was 77 percent. Thus, the overall SCS response rate (calculated by multiplying the household completion rate by the student completion rate) was 72 percent in 2001. The rate at which the respondents provide a valid response to a given item is referred to as its item response rate. Item response rates for items used in this report were generally high. Most items were answered by over 95 percent of all eligible respondents. The only exception was the household income question, which was answered by approximately 84 percent of all households in 2001 and approximately 86 percent of all households in the 1999 administration of the survey. Income and income-related questions typically have relatively low response rates compared to other items due to their sensitive nature. No explicit imputation procedure was used to correct for item nonresponse. However, restricting the analysis to those responses that were provided and ignoring the missing responses is an implicit form of imputation. The assumption is that the missing responses are completely random, and represent a subsample of the full sample. Weights were developed to compensate for differential probabilities of selection and nonresponse. The weighted data permit inferences about the 12- to 18-year-old student population enrolled in schools in 2001. The weight used with the 2001 SCS datafile is V297 (SCS person weight).

Survey Standard Errors As a result of the complex sampling design of the SCS and the NCVS, the resulting statistics are more variable than they would have been had they been based on data from a simple random sample of the same size. Several procedures and statistical software packages are available for calculating precise estimates of sampling errors for complex samples. The analyses carried out in this report used the Taylor Series procedure to calculate standard errors and was done through the AM statistical software package that is available for free downloading at http://am.air.org. The sample of students selected for each SCS is just one of many possible samples that could have been selected. It is possible that estimates from a given SCS student sample may differ from estimates that would have been produced from other student samples. This type of variability is called sampling error, or the standard error, because it arises from using a sample of students rather than all students. The standard error is a measure of the variability of a parameter estimate. It indicates how much variation there is in the population of possible estimates of a parameter for a given sample size. The probability that a complete census count would differ from the sample estimate by less than 1 standard error is about 68 percent. The chance that the difference would be less than 1.65 standard errors is about 90 percent, and that the difference would be less than 1.96 standard errors, about 95 percent. Standard errors for the percentage estimates are presented in the appendix tables. Standard errors are typically developed assuming that the sample is drawn purely at random. The sample for the SCS was not a simple random sample, however. Calculation of the standard errors requires procedures that are markedly different from the ones used when the data are from a simple random sample. To estimate the statistics and standard errors, this report used the Taylor series

Student Reports of Bullying

95

Statistical Tests Comparisons that have been drawn in the text of this report have been tested for statistical significance to ensure that the differences are larger than those that might be expected due to sampling variation. The statistical comparisons in this report were based on the t statistic. Whether the statistical test is considered significant or not is determined by calculating a t value for the difference between a pair of means or proportions and comparing this value to published tables of values, called critical values (cv). The alpha level is an a priori statement of the probability that a difference exists in fact rather than by chance. The t statistic between estimates from various subgroups presented in the tables can be computed by using the following formula:

where x1 and x2 are the estimates to be compared (e.g., the means of sample members in two groups) and SE1 and SE2 are their corresponding standard errors. While many descriptive comparisons in this report were tested using a t statistic, some comparisons among categories of an ordered variable with three or more levels involved a test for a linear trend across all categories, rather than a series of tests between pairs of categories. In this report, when differences among percentages were examined relative to a variable with ordered categories, Analysis of Variance (ANOVA) was used to test for a linear relationship between the two variables. To do this, ANOVA models included orthogonal linear contrasts corresponding to successive levels of the independent variable. These were used to create mean squares for the within- and between-group variance components and their corresponding F statistics, which were then compared with published values of F for a significance level of 0.05. Significant values of both the overall F and the F associated with the linear contrast term were required as evidence of a linear relationship between the two variables.

Glossary—Definitions of Variables Used Each row (student and school characteristics) and column variable used in the analyses for this report is described below. All variables are constructed from the 2001 SCS data file. The data file contains all variables collected by the SCS as well as select variables collected in the 2001 NCVS-1 Basic Screen Questionnaire and the NCVS-2 Crime Incident Report that have been appended to the SCS. The data are available for download from the InterUniversity Consortium for Political and Social Research via NCES’ Crime and Safety Surveys portal web site located at: http://nces.ed.gov/programs/crime/surveys.asp. Prior to analysis, the 2001 SCS data file was filtered to include only students who were ages 12 through 18 (using v212 [RESPONDENT AGE]), were enrolled in primary or secondary education programs (using v217 [GRADE LEVEL IN SCHOOL]), were enrolled in school in the past 6 months (using v215 [DID YOU ATTEND SCHOOL DURING THE LAST 6 MONTHS?]), and were not home-schooled during that time (using v3958 [HOME

96

Jill F. DeVoe and Sarah Kaffenberger

SCHOOLED DURING LAST 6 MONTHS?]). Students who did not fulfill these characteristics were deleted from the analysis. The final unweighted sample size was 8,374.

Student Characteristics SEX (v140): This variable was taken directly from v140 for the sex of the respondent: Male or Female. This variable was collected in the NCVS-1 Basic Screen Questionnaire and appended to the SCS data file. RACE/ETHNICITY (v145 and v146): This variable was taken directly from v145 for the race of the respondent and v146 for the Hispanic origin of the respondent. If the respondent identified themselves as Hispanic in v146, they were categorized as Hispanic, regardless of their response to v145. Non-Hispanics in v145 were classified as White, Black, or Other. Those individuals included in the “Other” category identified themselves as Asians, Pacific Islanders, and American Indians (including Alaska Native). The resulting categories were: 1) White, non-Hispanic; 2) Black, non-Hispanic; 4) Hispanic; and 5) Other. Race categories exclude Hispanic origin unless specified. Variables v145 and v156 were collected in the NCVS-1 Basic Screen Questionnaire and appended to the SCS data file. GRADE (v217): This variable was taken directly from v217. Response options included “Fifth and under”, “Sixth” through “Twelfth” grades, “Other”, and “College/GED/Postgraduate/Other non-eligible” All respondents not in grades six through twelve were excluded from the analysis. This variable was collected in item 2a of the SCS instrument (located in appendix D). HOUSEHOLD INCOME (v22): This variable was taken directly from v22 for the household income of the respondent and collapsed into the following categories: 1) Less than $7,500; 2) $7,500–14,999; 3) $15,000–24,999; 4) $25,000–34,999; 5) $35,000–49,999; 6) $50,000–74,999; and 7) $75,000 or more. This variable was collected in the NCVS-1 Basic Screen Questionnaire and appended to the SCS data file. PLACE OF RESIDENCE (v119): This variable was taken directly from v119 for the Metropolitan Statistical Area (MSA) Status of the respondent’s household as defined by the 1990 U.S. Bureau of the Census. Categories include: Central city of an (S)MSA (Urban) ; In (S)MSA but not in central city (Suburban); and Not (S)MSA (Rural). This variable was appended to the SCS data file by the U.S. Bureau of the Census. BULLIED (v272 and v3971): This variable was constructed using v272 and v3971. If respondents’ answered affirmatively to either v272 and v3971 they were categorized as “Bullied.” v272 asks, “During the last 6 months, have you been bullied at school? That is, has anyone picked on you a lot or tried to make you do things you didn’t want to do like give them money?” v3971 asks, “During the last 6 months, have you often felt rejected by other students at school? For example, have you ever felt rejected because other students have made fun of you, called you names, or excluded you from activities?” Variables v272 and v3971 were collected in items 19 and 20a of the SCS instrument. BOTH DIRECTLY AND INDIRECTLY (v272 and v3971): This variable was constructed using v272 and v3971. If respondents’ answered affirmatively to both v272 and v3971 they were categorized as “Bullied Both Directly and Indirectly.” Variables v272 and v3971 were collected in items 19 and 20a of the SCS instrument. DIRECTLY ONLY (v272): This variable was constructed using v272. If respondents’ answered affirmatively to v272 they were categorized as “Bullied Directly.” This variable was collected in item 19 of the SCS instrument.

Student Reports of Bullying

97

INDIRECTLY ONLY (v3971): This variable was constructed using v3971. If respondents’ answered affirmatively to v3971 they were categorized as “Bullied Indirectly.” This variable was collected in item 20a of the SCS instrument.

School Characteristics SCHOOL TYPE (v221): This variable was taken directly from v221 that asks the type of school for each student: Pubic or Private. This variable was collected in item 7a of the SCS instrument. GANG PRESENCE (v263): This variable is taken directly from v263 that asks students whether there are street gangs present at their school. Instructions for defining street gangs were as follows: “You may know these as street gangs, fighting gangs, crews, or something else. Gangs may use common names, signs, symbols, or colors. For this survey, we are interested in all gangs, whether or not they are involved in violent or illegal activity.” Response options included “Yes”, “No”, and “Don’t Know.” This variable was collected in item 30 of the SCS instrument. PRESENCE OF SECURITY OFFICERS OR ASSIGNED POLICE (v233): This variable was taken directly from v233 that asked students whether there are security guards and/or assigned police officers present at their school to ensure the safety of students. Response options included “Yes”, “No”, and “Don’t Know.” This variable was collected in item 14a of the SCS instrument. HALLWAY SUPERVISION BY SCHOOL STAFF (v234): This variable was taken directly from v234 that asked students whether there is hallway supervision by other school staff or other adults to ensure the safety of students. Response options included “Yes”, “No”, and “Don’t Know.” This variable was collected in item 14b the SCS instrument. Column Variables VICTIMIZATION (v819, v1341, v1863, v2385, v2907, v3429, and v3951): Each SCS respondent represents a student who may have reported at least one and as many as 7 incident(s) of victimization on the NCVS-1. For each incident of victimization reported, a Crime Incident Report NCVS-2 was completed. These (up to 7) Crime Incident Reports were appended to the SCS data file for each respondent who reported at least one incidence of victimization. The victimization categories used in this report for each of these incidents of victimization were determined using the Type of Crime (TOC) code reported in the Crime Incident Reports for each incident. The TOC codes used to determine the type of victimization were taken directly from variables v819 (first incident), v1341 (second incident), v1863 (third incident), v2385 (fourth incident), v2907 (fifth incident), v3429 (sixth incident), and v3951 (seventh incident). Each TOC variable contains several types of crime that have been categorized into “serious violent,” “violent,” “property,” and “any” for the purposes of this report. “Serious violent crime” includes: completed and attempted rapes, all sexual attacks, all completed and attempted robberies, all aggravated assaults, all verbal threats and threats with weapons, sexual assault without injury and unwanted sexual contact without force. “Violent crime” includes: serious violent crimes listed above, simple assault with injury, assault without a weapon and without injury, and verbal threat of assault. “Property crime” includes: purse snatching, pick pocketing, all burglaries, attempted forcible entry, completed and attempted motor vehicle theft, and completed thefts valuing less than $10 or greater. “Any crime” includes one or more reports of any of the crimes listed above.

98

Jill F. DeVoe and Sarah Kaffenberger

Each of these measure the prevalence of victimization, that is, if a respondent reported one or more incidents in one of these types of victimizations, they were included as a victim only once under the specified category. AFRAID OF ATTACK AT SCHOOL, ON THE WAY TO OR FROM SCHOOL AND AWAY FROM SCHOOL (v284, v285, and v286): These variables were taken directly from v284, v285 and v286 that asked students if they were afraid someone would attack or threaten to attack them at school, on the way to or from school, and away from school, respectively. Response options were collapsed into the following categories: “Never,” “Almost Never,” and “Sometimes/Most of the time.” These variables were collected in items 24, 25, and 26 of the SCS instrument. AVOIDING CERTAIN AREAS OF THE SCHOOL AND SKIPPING SCHOOL, CLASS OR EXTRA-CURRICULAR ACTIVITIES (v273, v274, v275, v276, v277, v278, v279, v280, v281, v282, and v283): Student reports of avoiding certain areas in school were taken directly from the following variables: v273 (avoided shortest route to school), v274 (avoided entrance to school), v275 (avoided hallways or stairs), v276 (avoided school cafeteria), v277 (avoided restrooms), v278 (avoided other places in school building), v279 (avoided parking lot), v280 (avoided other places on school grounds), v281 (avoided extracurricular activities), v282 (avoided class), and v283 (stayed home from school). Response options included “Yes” or “No.” These variables were collected in items 23a, 23b, 23c, and 23d of the SCS instrument. CARRIED A WEAPON (v287, v288, and v289): This variable was constructed from three separate variables that asked the student if they had carried a gun (v287) or knife (v288) intended as a weapon or any other weapon (v289) to school or on to school grounds during the last 6 months. If a respondent answered “Yes” to any of these items, they were included in the derived variable. These variables were collected in items 27a, 27b, and 27c of the SCS instrument. INVOLVED IN A PHYISICAL FIGHT (v3969): This variable was taken directly from v3969 that asked students whether they had been involved in one or more physical fights at school in the last 6 months. Response options included “Yes” and “No”. This variable was collected in item 18a of the SCS instrument. SELF-REPORTS OF GRADES (v3982): This variable was taken directly from v3982 that asked students what grades they mostly received across all subjects in the past school year. Response options included “A’s,” “B’s,” “C’s,” “D’s,” “F’s,” and “School does not give grades/no alphabetic grade equivalent.” This variable was collected in item 34 of the SCS instrument. For further information. NCES has collected and published data on school crime and safety through a number of publications. Readers who are interested in further information about these studies and downloading available data files, including the SCS data file used in this article, should contact Kathryn Chandler at [email protected] or visit the Crime and Safety Surveys web site at http://nces.ed.gov/programs/crime/.

Student Reports of Bullying

99

APPENDIX B: ESTIMATE TABLES Table 1. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by selected student characteristics: 2001 Student characteristics

Number of students 24,315,000

Total Student sex Male 12,591,000 Female 11,724,000 Student race/ethnicity2 White, non-Hispanic 15,784,000 Black, non-Hispanic 3,793,000 Hispanic 3,446,000 Other, non-Hispanic 1,063,000 Student grade Sixth 2,113,000 Seventh 3,848,000 Eighth 3,947,000 Ninth 4,093,000 Tenth 3,774,000 Eleventh 3,581,000 Twelfth 2,960,000 Student household income Less than $7,500 836,000 $7,500–14,999 993,000 $15,000–24,999 2,524,000 $25,000–34,999 2,874,000 $35,000–49,999 4,074,000 $50,000–74,999 4,279,000 $75,000 or more 4,861,000 Student place of residence Urban 6,574,000 Suburban 12,812,000 Rural 4,929,000

Total 14.4

Both Directly and Indirectly1 4.5

Directly Only1 3.4

Indirectly Only1 6.5

15.0 13.7

5.0 3.9

3.6 3.1

6.4 6.7

15.4 12.3 13.0 10.8

4.9 3.2 4.3 3.7

3.5 2.6 2.9 3.3

6.9 6.6 4.2 5.3

24.3 21.6 16.0 13.9 10.4 9.5 7.4

9.3 8.0 5.3 3.9 2.1 3.1 1.0

4.8 5.0 3.9 4.6 2.5 1.2 1.4

10.1 8.6 6.8 5.3 5.8 5.2 4.9

15.0 13.3 17.5 15.0 14.8 13.2 12.9

3.8 4.9 5.9 5.4 4.7 4.2 3.5

4.0 3.1 4.2 4.1 2.8 2.5 2.6

7.1 5.4 7.3 5.5 7.4 6.5 6.8

13.2 14.9 14.7

4.1 4.5 5.0

2.7 3.6 3.7

6.4 6.8 6.0

1 Categories are mutually exclusive. Directly Only, Indirectly Only, and Both Directly and Indirectly are distinct categories. Students appearing in one category do not appear in other categories. 2 Other includes Asians, Pacific Islanders, and American Indians (including Alaska Natives). Race categories exclude Hispanic origin unless specified. Note: “At school“ was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they

100

Jill F. DeVoe and Sarah Kaffenberger

were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data. Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001.

Table 2. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by selected school characteristics: 2001 School characteristics

Number of students

Bullied Total

Total School type Public Private Gang presence Yes No Presence of security officers or assigned police Yes No Hallway supervision by school staff Yes No

Directly only1

Indirectly only1

3.4

6.5

24,315,000

14.4

Both directly and indirectly 4.5

22,176,000 2,098,000

14.4 14.0

4.6 4.5

3.4 2.7

6.5 6.7

4,896,000 15,993,000

21.1 13.0

8.1 3.7

4.9 3.1

8.1 6.2

15,475,000 8,840,000

13.3 16.2

3.8 5.7

3.4 3.4

6.1 7.1

21,479,000 2,836,000

13.9 17.9

4.4 5.6

3.3 3.7

6.2 8.5

1 Categories are mutually exclusive. Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school“ includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

Student Reports of Bullying

101

Table 3. Percentage of students ages 12–18 who reported being victimized at school during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001

Total Not Bullied Bullied Both Directly and Indirectly2 Directly Only2 Indirectly Only2

Number of students

Victimization Any Serious Violent1

Violent

Property

24,315,000 20,680,000 3,494,000 1,095,000 816,000 1,583,000

5.5 4.2 13.0 17.4 18.3 7.3

1.8 0.8 7.3 10.9 10.8 2.9

4.2 3.6 7.6 9.9 9.2 5.3

0.4 0.3 1.5 3.7 0.7 0.3

1 Serious violent crimes are also included in violent crimes. 2Categories are mutually exclusive. Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: Serious violent crimes include rape, sexual assault, robbery, and aggravated assault. Violent crimes include serious violent crimes and simple assault. Any crimes include violent crimes and theft. “At school“ includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

Table 4. Percentage of students ages 12–18 who reported fearing attack during the previous 6 months at school, on the way to and from school, and away from school, by reports of being bullied directly and/or indirectly at school: 2001 Victim behaviors

Total Not Bullied Bullied Both Directly and Indirectly1 Directly Only1 Indirectly Only1 1

Number of students

Afraid of attack at school Never

Almost Never

24,315,000 20,680,000 3,494,000

80.7 85.2 55.9

13.9 11.9 26.1

Afraid of attack on the way to or from school Sometimes/ Never Almost Sometimes/M Most of the Never ost of the Time Time 4.7 87.5 8.2 3.6 2.5 90.1 7.2 2.4 17.9 74.4 14.7 10.7

1,095,000 816,000 1,583,000

42.0 52.5 67.3

26.4 33.4 22.0

31.2 14.1 10.6

64.1 76.0 80.6

18.3 13.7 12.7

16.9 10.3 6.6

Afraid of attack away from school1 Never Almost Sometimes/ Never Most of the Time 80.9 13.7 4.6 83.9 12.3 3.4 65.3 22.3 12.2 60.1 62.8 70.2

23.8 26.8 18.9

15.5 10.4 11.0

Categories are mutually exclusive.

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school“ was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

Table 5. Percentage of students ages 12–18 who reported avoiding certain areas of school and skipping school, class, or extracurricular activities during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001 Victim behaviors

Number of Avoided Avoided Avoided Avoided Avoided Avoided Avoided restrooms other parking students shortest entrance hallways school places in lot to school or stairs cafeteria route school building 24,315,000 2.5 1.2 2.1 1.4 2.2 1.4 1.6 20,680,000 1.9 0.8 1.3 0.7 1.5 0.8 1.1 3,494,000 5.9 3.6 7.1 5.8 6.9 5.3 5.0

Total Not Bullied Bullied Both Directly and Indirectly1 1,095,000 9.3 Directly Only1 816,000 3.4 1 Indirectly Only 1,583,000 4.9 1

6.6 2.7 2.0

12.2 7.5 3.4

9.8 5.0 3.4

10.4 6.2 4.8

9.4 4.8 2.8

7.5 4.7 3.4

Avoided other places on school grounds 1.7 1.1 5.5

Skipped school

Skipped Skipped class extracurricular activities

1.1 0.7 3.8

0.6 0.2 3.0

1.1 0.6 3.8

9.4 5.3 2.8

7.2 4.3 1.3

6.5 2.5 0.8

6.0 4.2 2.1

Categories are mutually exclusive.

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school“ was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

103

Student Reports of Bullying

Table 6. Percentage of students ages 12–18 who reported carrying a weapon for protection or being involved in a physical fight at school during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001 Victim behaviors Number of students Total 24,315,000 Not Bullied 20,680,000 Bullied 3,494,000 Both Directly and Indirectly1 1,095,000 Directly Only1 816,000 Indirectly Only1 1,583,000 1 Categories are mutually exclusive.

Carried a weapon 1.8 1.4 3.7 4.4 3.3 3.4

Involved in a physical fight 5.2 3.6 14.6 21.1 15.0 9.8

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: Students included as carrying weapons reported carrying a gun, knife or other weapon to school in the 6 months prior to the survey. “At school“ includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

Table 7. Percentage of students ages 12–18 who reported receiving different academic grades during the school year, by reports of being bullied directly and/or indirectly at school: 2001 Number of students Total Not Bullied Bullied Both Directly and Indirectly1 Directly Only1 Indirectly Only1 1

24,315,000 20,680,000 3,494,000 1,095,000

Self-reports of grades Mostly Mostly B’s A’s 32.6 40.8 33.7 41.0 26.6 40.6 21.2 38.6

816,000 1,583,000

26.5 30.3

39.4 42.5

Mostly C’s 20.8 20.4 23.7 26.7

Mostly D’s and F’s 3.9 3.2 8.3 12.1

26.7 20.1

7.1 6.3

Categories are mutually exclusive. Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school“ includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?“ This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?“ This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000. Detail may not sum to totals due to missing data.

104

Jill F. DeVoe and Sarah Kaffenberger

APPENDIX C: STANDARD ERROR TABLES Table S1. Standard errors Table 1. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by selected student characteristics: 2001 Student Characteristics

Total Student sex Male Female Student Characteristics

Bullied Total 0.54 0.72 0.62 Bullied Total

Student race/ethnicity White, non-Hispanic 0.63 Black, non-Hispanic 1.32 Hispanic 1.16 Other, non-Hispanic 1.72 Student grade Sixth 1.59 Seventh 1.33 Eighth 1.12 Ninth 1.02 Tenth 0.90 Eleventh 0.80 Twelfth 0.99 Student household income Less than $7,500 2.29 $7,500–14,999 2.33 $15,000–24,999 1.73 $25,000–34,999 1.29 $35,000–49,999 1.11 $50,000–74,999 0.94 $75,000 or more 0.91 Student place of residence Urban 0.82 Suburban 0.65 Rural 1.63

Both Directly Directly Only and Indirectly 0.23

0.22

Indirectly Only 0.37

0.35 0.32

0.36 0.28

0.45 0.43

Both Directly and Indirectly

Directly Indirectly Only Only 0.31 0.54 0.68 0.86

0.27 0.60 0.42 0.84

0.45 0.86 0.70 1.08

0.98 0.75 0.60 0.55 0.42 0.53 0.32

0.90 0.58 0.53 0.71 0.45 0.28 0.43

1.23 1.01 0.73 0.65 0.78 0.70 0.83

1.13 1.20 1.00 0.74 0.55 0.56 0.50

1.12 1.08 0.76 0.77 0.49 0.41 0.39

1.73 1.61 1.13 0.74 0.84 0.68 0.63

0.44 0.32 0.57

0.37 0.26 0.69

0.54 0.45 1.01

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Student Reports of Bullying

105

Table S2. Standard errors for Table 2. Percentage of students ages 12–18 who reported being bullied directly and/or indirectly at school during the previous 6 months, by selected school characteristics: 2001 School Characteristics

Bullied Total

Both Directly and Indirectly

Total 0.54 0.23 School type Public 0.56 0.89 Private 1.18 0.23 Gang presence Yes 1.13 0.70 No 0.57 0.26 Presence of security officers or assigned police Yes 0.60 0.27 No 0.86 0.45 Hallway supervision by school staff Yes 0.53 0.23 No 1.31 0.82

Directly Only

Indirectly Only

0.22

0.37

0.23 0.68

0.39 0.87

0.52 0.28

0.73 0.42

0.30 0.33

0.41 0.64

0.23 0.57

0.36 1.01

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Table S3. Standard Errors for Table 3. Percentage of students ages 12–18 who reported being victimized at school during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001

Total Not Bullied Bullied Both Directly and Indirectly Directly Only Indirectly Only

Victimization Any Serious Violent

Violent

Property

0.31 0.27 1.13 2.19 2.47 1.26

0.19 0.10 0.94 2.03 2.01 0.89

0.24 0.24 0.78 1.63 1.64 1.09

0.08 0.06 0.41 1.20 0.46 0.23

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: Serious violent crimes include rape, sexual assault, robbery, and aggravated assault. Violent crimes include serious violent crimes and simple assault. Any crimes include violent crimes and theft. “At school” includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Table S4. Standard errors for Table 4. Percentage of students ages 12–18 who reported fearing attack during the previous 6 months at school, on the way to and from school, and away from school, by reports of being bullied directly and/or indirectly at school: 2001 Victim behaviors

Total Not Bullied Bullied Both Directly and Indirectly Directly Only Indirectly Only

Afraid of attack at school Never

Almost Never

0.62 0.53 1.84 2.77 3.53 2.69

0.55 0.48 1.82 2.39 3.55 2.57

Sometimes/ Most of the Time 0.29 0.23 1.35 2.63 2.28 1.56

Afraid of attack on the way to or from school Never Almost Sometimes/ Never Most of the Time 0.44 0.35 0.24 0.44 0.38 0.23 1.30 1.15 0.94 2.61 2.13 2.09 2.83 2.39 1.83 1.76 1.51 1.00

Afraid of attack away from school Never Almost Never 0.60 0.62 1.52 2.34 3.57 2.10

0.52 0.53 1.34 2.19 3.70 1.63

Sometimes/ Most of the Time 0.28 0.26 1.08 1.90 2.02 1.65

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Table S5. Standard errors for Table 5. Percentage of students ages 12–18 who reported avoiding certain areas of school and skipping school, class, or extra-curricular activities during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001

0.16 0.11 0.75

Avoided Avoided other Rest rooms places in school building 0.19 0.14 0.16 0.11 0.74 0.71

1.78 1.35 0.82

1.59 1.38 0.98

Victim behaviors

Avoided shortest route

Avoided entrance to school

Avoided hallways or stairs

Avoided school cafeteria

Total Not Bullied Bullied Both Directly and Indirectly Directly Only Indirectly Only

0.20 0.17 0.82

0.11 0.11 0.56

0.18 0.15 0.81

1.61 1.11 1.17

1.28 1.05 0.57

1.80 1.63 0.82

1.64 1.27 0.76

Skipped Skipped school class

Skipped extracurricular activities

0.14 0.12 0.57

Avoided other places on school grounds 0.15 0.12 0.70

0.13 0.11 0.66

0.09 0.06 0.53

0.12 0.10 0.48

1.31 1.28 0.75

1.56 1.47 0.68

1.59 1.00 0.60

1.42 0.84 0.46

1.18 1.00 0.66

Avoided parking lot

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” was defined as in the school building, on school property, on a school bus, or going to and from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

108

Jill F. DeVoe and Sarah Kaffenberger

Table S6. Standard errors for Table 6. Percentage of students ages 12–18 who reported carrying a weapon for protection or being involved in a physical fight at school during the previous 6 months, by reports of being bullied directly and/or indirectly at school: 2001 Victim behaviors Total Not Bullied Bullied Both Directly and Indirectly Directly Only Indirectly Only

Carried a weapon 0.19 0.18 0.69 1.08 1.18 0.96

Involved in a physical fight 0.26 0.22 1.12 2.06 2.38 1.44

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: Students included as carrying weapons reported carrying a gun, knife or other weapon to school in the 6 months prior to the survey. “At school” includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Table S7. Standard errors for Table 7. Percentage of students ages 12–18 who reported receiving different academic grades during the school year, by reports of being bullied directly and/or indirectly at school: 2001

Total Not Bullied Bullied Both Directly and Indirectly Directly Only Indirectly Only

Self-reports of grades Mostly A’s Mostly B’s 0.69 0.64 0.72 0.68 1.35 1.50 2.35 2.66

Mostly C’s Mostly D’s and F’s 0.55 0.26 0.59 0.24 1.41 0.93 2.53 1.66

3.36 2.19

3.18 1.82

2.95 2.39

1.53 1.35

Source: U.S. Department of Justice, Bureau of Justice Statistics, School Crime Supplement (SCS) to the National Crime Victimization Survey, 2001. Note: “At school” includes inside the school building, on school property, or on the way to or from school. Youth ages 12 through 18 were first asked if “they had been bullied at school. That is, had anyone picked on them a lot or tried to make them do things they did not want to do (e.g., give them money)?” This is referred to as direct bullying. They were also asked, “Have you felt rejected because other students have made fun of you, called you names, or excluded you from activities?” This is referred to as indirect bullying. Total bullied includes youth who reported they were bullied directly or indirectly. Population size for students ages 12–18 is 24,315,000.

Student Reports of Bullying

109

APPENDIX D: 2001 SCHOOL CRIME SUPPLEMENT TO THE NATIONAL CRIME VICTIMIZATION SURVEY INSTRUMENT

110

Jill F. DeVoe and Sarah Kaffenberger

Student Reports of Bullying

111

112

Jill F. DeVoe and Sarah Kaffenberger

Student Reports of Bullying

113

114

Jill F. DeVoe and Sarah Kaffenberger

Student Reports of Bullying

115

ACKNOWLEDGMENTS The School Crime Supplement to the National Crime Victimization Survey would not be possible without the continued support for data collection given by the U.S. Department of Education, Office of Safe and Drug-free Schools under the sponsorship of Bill Modzeleski.

116

Jill F. DeVoe and Sarah Kaffenberger

Staff from the National Center for Education Statistics provided valuable comments and suggestions on drafts of this study, including Jeffrey Owings, Tai Phan, Marilyn Seastrom, Marilyn Binkley, and Carl Schmitt. In addition, Ann Ricciuti of the Institute for Education Sciences gathered and mediated comments from two anonymous external reviewers that greatly improved this article. The authors would like to acknowledge Mike Planty, Sally Ruddy, Amanda Miller, Margaret Noonan, and Martin Hahn of the American Institutes for Research, Education Statistics Services Institute (ESSI), for their comments and guidance. Finally, the authors are grateful to Elina Hartwell, also from ESSI, for the artful production and layout of this study.

REFERENCES Addington, L.A., Ruddy, S.A., Miller, A.K., and DeVoe, J.F. (2002). Are America’s Schools Safe? Students Speak Out: 1999 School Crime Supplement (NCES 2002–331). U.S. Department of Education, National Center for Education Statistics. Washington, DC: U.S. Government Printing Office. Banks, R. (1997). Bullying in Schools. Office of Educational Research and Improvement. U.S. Department of Education, ERIC: Washington DC: U.S. Government Printing Office Bastian, L. and Taylor, B. (1991). School Crime 1991 (NCJ 131645). U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics. Washington, DC: U.S. Government Printing Office. Batsche, G. M. and Knoff, H. M. (1994). Bullies and their Victims: Understanding a Pervasive Problem in the Schools. School Psychology Review, 23: 165-174. Berthhold, K. and Hoover, J. (2000). Correlates of Bullying and Victimization Among Intermediate Students in the Midwestern USA. School Psychology International, 21: 65– 79. Cairns, R.B., Cairns, B.D., Neckerman, H.G., Ferguson, L.L., and Gariepy, J. (1989). Growth and Aggression: 1. Childhood to Early Adolescence. Developmental Psychology, 25: 320-330. Cantor, D. and Lynch, J. P. (2000). Self-Report Surveys as Measures of Crime and Criminal Victimization. In David Duffee (Ed.), Measurement and Analysis of Crime and Justice. Washington, DC: National Institute of Justice. Carney, A. and Merrell, K. (2001). Bullying in Schools: Perspectives on Understanding and Preventing an International Problem. School Psychology International, 21: 364–382. Cillessen, A.H.N., and Mayeux, L. (2004). From Censure to Reinforcement: Developmental Changes in the Association Between Aggression and Social Status. Child Development, 75: 147–163. Crick, N.R., and Grotpeter, J.K. (1995). Relational Aggression, Gender, and Socialpsychological Adjustment. Child Development, 66: 710–722. DeVoe, J.F., Peter, K., Kaufman, P., Miller, A.K., Noonan, M., Snyder, T.D., and Baum, K. Indicators of School Crime and Safety: 2004. NCES 2005–002/NCJ 205290. U.S. Departments of Education and Justice. Washington, DC: 2004. Dodge, K., Coie, J., Pettit, G.S., and Price, J. (1990). Peer Status and Aggression in Boys Groups: Developmental and Contextual Analyses. Child Development,61: 1289–1309.

Student Reports of Bullying

117

Ericson, N. (2001). Addressing the Problem of Juvenile Bullying. OJJDP Fact Sheet #27. U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention. Washington, DC: U.S. Government Printing Office. Elliott, D.S. (1994). Youth Violence: An Overview. Boulder, CO: University of Colorado, Center for the Study and Prevention of Violence. Farrington, D.P. (1993). Understanding and Preventing Bullying. In M. Tonry and N. Morris (Eds). Crime and Justice, Vol. 17. Chicago: University of Chicago Press. Hawkins, D.L., Pepler, D.J., and Craig, W.M. (2001). Naturalistic Observations of Peer Interventions in Bullying. Social Development, 19: 512-527. Haynie, D.L., Nansel, T.R., Eitel, P., Crump, A.D., Saylor, K., Yu, K.,and Simons-Morton, B. (2001). Bullies, Victims, and Bully/Victims: Distinct Groups of At-Risk Youth. Journal of Early Adolescence, 21: 29–49. Lawrence R. (1998). School Crime and Juvenile Justice. New York: Oxford University Press. Loeber, R., and Stouthamer-Loeber, M. (1998). Juvenile Aggression at Home and at School. In Elliott, D.S., Hamburg, B.A., and Williams, K.R. (Eds.), Violence in American Schools: A New Perspective (pp. 94–126). New York, NY: Cambridge University Press. Nansel, T., Overpeck, M., Pilla, R., Ruan, J., Simons-Morton, B., and Scheidt, P. (2001). Bullying Behaviors Among U.S. Youth: Prevalence and Association With Psychosocial Adjustment. Journal of the American Medical Association, 285: 2094–2100. Nansel, T., Overpeck, M., Haynie, D., Ruan, J. and Scheidt, P. (2003). Relationships Between Bullying and Violence Among US Youth. Archives of Pediatric and Adolescent Medicine, 157: 348–353. Olweus, D. (1999). Bullying in Sweden. In Smith, P.K., Morita, Y., Junger-Tas, J. Olweus, D., Catalanao, R., and Slee, P. (Eds). The Nature of School Bullying: A Cross-National Perspective. New York: Routledge. Olweus, D. (1997). Bully/Victim Problems in School: Knowledge Base and an Effective Intervention Program. The Irish Journal of Psychology, 18: 170–190. Olweus, D. (1993) Bullying at School: What We Know and What We Can Do. Cambridge, MA: Blackwell. Olweus, D., (1991). Bully/Victim Problems Among School Children: Some Basic Facts and Effects of a School-based Intervention Program. In Pepler, D. and Rubin, K. (Eds.) The Development and Treatment of Childhood Aggression, (pp. 411–438). Hillsdale, NJ: Earlbaum. Olweus, D. (1980). Familial and Temperamental Determinants of Aggressive Behavior in Adolescent Boys: A Causal Analysis. Developmental Psychology, 16: 644–660. Olweus, D. (1978). Aggression in the Schools. Bullies and Whipping Boys. Washington, DC: Hemisphere Press (Wiley). Pellegrini, A., and Bartini, M. (2001). Dominance in Early Adolescent Boys: Affiliative and Aggressive Dimensions and Possible Functions. Merrill-Palmer Quarterly, 47: 142–63. Pellegrini, A., and Long, J. (2002). A Longitudinal Study of Bullying, Dominance, and Victimization During the Transition from Primary School Through Secondary School. British Journal of Developmental Psychology, 20, 259–280. Smith, P., Dowie, H., Olafsson, R., and Liefooghe, A. (2002). Definitions of Bullying: A Comparison of Terms Used, and Age and Gender Differences, in a Fourteen-Country International Comparison. Child Development, 73: 1119–1133.

118

Jill F. DeVoe and Sarah Kaffenberger

Underwood, M.K., Galen, B.R., and Paquette, J.A. (2001). Top Ten Challenges for Understanding Gender and Aggression in Children: Why Can't We All Just Get Along? Social Development, 10: 248-266. Wilton, M.M., Craig, W., and Pepler, D. (2000). Emotional Regulation and Display in Classroom Victims of Bullying: Characteristic Expressions of Affect, Coping Styles and Relevant Contextual Factors. Social Development, 9: 226–245

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 4

FACTORS THAT INFLUENCE SUBJECTIVE TIME: GENDER, TYPE OF PERSON, AND TIME OF DAY? David P. Austin1, F. Richard Ferraro, Ryan Kerzman, Thomas V. Petros and Jeffrey N. Weatherly University of North Dakota

ABSTRACT The present study focused on short-duration time estimation, which by definition is vital for assessing the immediate environment. This study explored the roles of time of day, type of person, and gender on empty and complex intervals and 60-s fixed-time and 30/90-s variable-time periods. The participants (N = 104) were students from a psychology department subject pool who were prescreened using the Horne and Ostberg scale. Participants were then randomly assigned to participate either in the morning or in the evening. The participants operated a stopwatch to measure the amount of time they believed had passed across 10 trials in each of four different conditions (empty intervals for a 60-s fixed-time period, complex intervals for a 60-s fixed-time period, empty intervals for a variable-time period that averaged to 60-s, and complex intervals for a variable-time period that averaged to 60-s). The results revealed that gender does not influence time estimation. However, the Time of Day X Type of Person vs. Complex/Variable interaction was significant. Surprisingly, the intervals containing complex stimuli had a longer reported duration than the empty intervals, suggesting that time passes by slower when the interval is filled with a complex event.

SHORT DURATION TIME ESTIMATION: EFFECTS OF GENDER, TYPE OF PERSON, AND TIME OF DAY Our sense of time involves short-term time estimations and long-term time estimations. Short-term time estimations range from seconds to minutes and can influence what decisions 1 Contact Information: David P. Austin, Department of Psychology, University of North Dakota, Box 8380, Grand Forks, ND 58203, Phone: (406) 671-6905, Email: [email protected].

120

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

we make throughout the day. For example, Espinosa-Fernandez et al. (2002) stated, “…while driving down or crossing a busy street, speed and time estimates are constantly required. While waiting at the bus stop or accessing a specific web page a feeling of lengthened duration may influence whether a person continues to wait or returns on a subsequent visit” (p. 222). Timing is crucial to how humans function in society. Almost every daily situation that we encounter involves our sense of time (Block, 1990). Long-term time estimations can influence the decisions we make that affect the rest of our lives such as career and spousal choices. These are choices that include “how long should I stay in school?” and “will my spouse be a good parent?” Whether the situation involves short-term or long-term time estimations, our notion of time involves perceptual changes that allow us to measure time by observing a sequence of successive events (Fraisse, 1984). Gibbon, Church, and Meck (1984) and Treisman et al. (1994) both suggest a very popular and similar model of temporal information processing. They believed that time estimation can be explained in terms of a complex internal system that includes a variety of different components. This model of a time keeping system relies on four different but related mechanisms. The first mechanism is referred to as the clock, which includes a pacemaker and a switch. The pacemaker produces pulses at a specific rate while the switch triggers an accumulator. The pacemaker speed can be influenced by different physiological processes and conditions such as overall health, metabolism, body temperature, and sleep (Miro, Cano, Espinosa-Fernandez, and Beula-Casal, 2003; Treisman et al., 1994). The accumulator then adds up the pulses and enters the information into the second mechanism, the organism’s working memory. The third mechanism is the comparator, which contrasts the value in the accumulator with a value in the fourth mechanism, an organism’s reference memory. Once this contrast is complete, a decision is made on the amount of time passed and a response can now be made based on the values. There are many vital issues to consider when studying time estimation including which method to use to obtain duration judgments (Block, Hancock, and Zakay, 1998). There are presently three main methods cited in the literature: verbal estimation, production, and reproduction. In the verbal estimation method, a participant is asked to identify when a certain time period has elapsed by saying stop, for instance. The method of production has the participant produce a set period of time. For example, the researcher will ask the participant to produce a minute. The participant will start at a specific time and stop when they think that the minute is up. The reproduction model is when the participants are asked to attend to a certain stimuli for a set duration, and then reproduce that duration at a later time (Block, Hancock, and Zakay, 1998). Another important issue is which specific time duration paradigm to use. The prospective paradigm is one in which the participants are told in advance that they will have to pay attention to the passage of time (Block, Hancock, and Zakay, 1998; Fernandez et al., 2002; Fraisse, 1984). When using the retrospective paradigm, the participants are told after an amount of time has passed to then judge its duration (Fernandez et al., 2002; Fraisse, 1984). An additional interesting problem in the area of time duration estimations is that of complex and empty intervals. This issue has been discussed even as early as the times of Socrates and Aristotle, but William James (1890) was the first modern scientist to explore this issue. “In general, a time filled with varied and interesting experiences seems short in passing but as long as we look back. On the other hand, a tract of time empty of experiences seems

Factors that Influence Subjective Time

121

long in passing, but in retrospect short” (p.624). The prominent thought in the time estimation area after the cognitive revolution is to agree with James; that intervals of time which contain complex stimuli seem to pass by quickly, while empty intervals, those that minimize sensory stimulation, pass by slowly and in many cases more accurately (Block, George, and Reed, 1980; Fraisse, 1984; Zakay, 1990). Chastain and Ferraro (1997) explain, “According to this model, estimating the passage of time involves reference to an internal counter or timer, which shares attention or resources with a visual information processor. As more resources are devoted to processing information, fewer are available to the counter, which becomes less reliable in that it tends to run too slowly” (p. 50). Many agree with James and use empty intervals in their experiments dealing with duration estimations (Espinosa-Fernandez, Miro, Cano, and Buela-Casal, 2003; Hancock, Vercruyssen,and Rodenberg, 1992; Lennings and Burns, 1998). However, these authors are not saying that empty intervals are the only intervals to be used in experimentation. Individual differences in the area of time perception are only beginning to be explored. This variable alone may be able to explain differences between studies (Fraisse, 1984). Block et al. (2000) explain why scientists are interested in individual differences, “Because many everyday perceptual and cognitive situations lead a person to estimate short durations it is important to understand the underlying processes and whether or not individual differences exist within these processes” (p. 584).

Gender Modern science has given us a better understanding of the many facets of gender differences. Darley and Smith (1995) attribute gender differences into two basic sources: biological and sociological. The biological standpoint can show evidence of variations in brain organization and functioning. One example has shown that sexual hormones can cause significant gender differences in perceptual – motor skills (Bursin et al. 1980). Other physiological examples include muscle mass and fat content. The sociological standpoint considers that gender is attributed to the structure of a child’s developmental environment. Boys are given trucks to play, taught not cry, and to be tough, while girls are given dolls to play with and told to stay in the kitchen with mom (Meyers-Levy, 1994). Further information-processing research has often described how males are characterized as more analytic and logical than females, while females tend to be more subjective and intuitive than males (Broverman et al., 1968). Silverman (1970) suggested that these observed differences are the result of dissimilar attention styles. He believed that the analytical and logical males tend to focus only on the task at hand, blocking out all other ideas and concepts. Meyers-Levy and Sternthal (1991) concur with Silverman’s theory, suggesting that males are selective in what information is processed. Males tend to filter out much of the available information in order to come to a decision. This information is usually in the form of cues or prompts. The subjective and intuitive females are known as comprehensive processors, which means that females try to absorb all of the available ideas, concepts, and cues in order to make a decision (Meyers-Levy and Sternthal, 1991). In the area of time estimation, the results of gender differences are also varied. Hancock, Vercruyssen, and Rodenberg (1992) pointed out that it is important to include the gender variable in any experimental design dealing with duration estimation because of the

122

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

inconsistent results. Many studies have found significant differences between males and females involving time estimation (Eisler and Eisler, 1992; Hancock et al., 1992). In these studies, males were generally more accurate in their estimations. Females seemed to overestimate time intervals when the verbal estimation method was used (Block et al., 2000; Kirkaldy, 1984). In many other studies that deal with this type of gender difference, no significant findings were reported (Lennings and Burns, 1998; Marmaras et al., 1995). One purpose of this study was to reveal whether the paradigm and method used will generate a gender difference in short-duration time estimation.

Time of Day In a study by Dunne et al. (1990), the experimenters examined time of day effects on immediate recall of a list of words and sustained retrieval (a list of words where more that eight minutes had passed) from semantic memory. The results showed that immediate recall of the list of words was better when participants were tested in the morning, and the sustained retrieval from semantic memory was better when they were tested in the evening. This study also revealed that there are many differences in humans depending on the time of day. Because memory is directly related to the estimation of time durations (Anderson et al., 1991; Fraisse, 1984; Smythe, 1999), it would seem relevant to include the time of day factor in a time estimation study in order to replicate or dispute the previous results.

Type of Person Because many physiological and cognitive differences vary as a function of time of the day, scientists started to look at when these factors were at optimal levels for an individual. This research led to whether an individual was a morning person or an evening person. Mecacci and Rocchetti (1998) administered a morningness-eveningness questionnaire to 232 participants in order to reveal the time of day that they prefer. The participants were also given a battery of questionnaires of personality and psychological disorders in order to find out which type of person, if any, was more prone to a disorder or had different personalities. The results showed that evening types reported more frequent and more intense psychological disturbances than the morning types. It was also reported that the evening types had more problems coping with social and environmental stressors than the morning types. A key individual difference in the area of time estimation may have to do with whether the participant is a morning person or an evening person, according to the Horne and Ostberg Morningness/Eveningness Scale (1978), and what time of the day they are tested. Another study on memory, dealing with this morning versus evening participants has shown that the time of day is indeed a significant factor. “Performance of morning type Ss decreased across time of day, whereas the performance of evening types improved throughout the day. Results suggest that the effect of diurnal variations on memory performance is critically dependent on whether the S is a morning or evening type” (Anderson et al., 1991, p. 241). Petros, Beckwith, and Anderson (1990) suggested that the type of person and the time of day were significant individual differences that may be applied to areas other than memory. Memory is directly related to the estimation of time durations, so it would be relevant to include the type

Factors that Influence Subjective Time

123

of person and the time of day factors as well (Fraisse, 1984 and Smythe, 1999). These factors are needed in order to replicate or dispute the previous results on memory and to examine any interactions that might occur. Understanding more about these factors and interactions is a step in the right direction to being able to understand the whole picture of time duration estimations.

Hypotheses The focus of the present study is to use the prospective paradigm of duration estimations and the production method to determine what impacts, if any, gender, the type of person, and the time of day have on short-duration time estimations. This study also explored the role of complex and empty intervals and their relation to the factors mentioned above. The following hypotheses were examined: 1) It has been suggested that time durations that are filled with complex stimuli pass by quickly, while empty durations pass by slowly. To complement previous research, empty and complex intervals were examined in the present study to further validate their respective contributions. The hypothesis being that the empty intervals and the complex intervals of duration estimation will be statistically significant. 2) There will be a main effect of gender, such that females will report higher duration estimations than males. The literature in this area is contradictory, so it would be relevant to empirically validate our hypothesis. 3) There will be differences in the reported estimations at different times of the day (i.e., morning and evening). Time of day is an important difference that few studies dealing with time estimation have explored (Kuriyama et al., 2002). In the few studies that have, it has been reported that time estimations do fluctuate across the day (Aschoff, 1998; Morofushi et al., 2001). The goal of the present study was to replicate some of these time of day findings to further complement the previous research. 4) There will be a significant interaction between the type of person (i.e., morning or evening) and the time of day (i.e., morning or evening) that the subject is tested. Previous research (Anderson et al., 1991; Petros, Beckwith, and Anderson, 1990) on memory has revealed that these are significant factors, but no research has been done to explore these factors in the area of time estimation. 5) In previous research on memory (Anderson et al., 1991, Petros et al., 1990), the Time of Day X Type of Person interaction was statistically significant. The present study will investigate this interaction further, applying it to short-duration time estimations.

METHOD Participants The participants (N=104) were students from introductory and advanced level psychology classes. Each received extra credit for participation. All of the participants were between the ages of 18 and 24 years (M=19.9, SD=1.6). Detailed demographic information is presented in Table 1. A meta-analysis by Block (1998) revealed effect sizes for duration judgments on several prominent studies in the time estimation area.

124

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al. Table 1. Demographic Information for Participants as a function of Gender Male

Female

N

52

52

Age

20.0 (1.8)

19.8 (1.3)

WAIS III Vocab.

39.4 (11.1)

38.9 (9.1)

Temperature

97.5 (1.0)

97.9 (1.1)

Health

4.3 (.7)

3.7 (.8)

BP Systolic

121.2 (11.2)

113.2 (12.2)

BP Diastolic

74.2 (6.9)

74.1 (6.5)

He also provided an overall combined effect size of .40, which was used to calculate the power for this experiment. An a priori power analysis was conducted using the computer program G power (Erdfelder et al., 1996) to determine the number of participants needed. As previously stated, subjective time can be influenced by many di`fferent physiological processes. To control for this, all participants were asked about their general health on a scale of 1 to 5. The general health scale was a subjective measure where a score of 5 was “excellent health”, 4 was “good health”, 3 was “average”, 2 was “fairly healthy”, and a score of 1 was “not healthy” (M=4.0, SD=.8). They also had their blood pressure (M=117.2/74.2, SD=12.4/6.7) as well as temperature (M=97.7, SD=1.0) taken before the experiment began. According to the Harvard Medical School Family Guide (1999), the normal range for blood pressure is between 80/50 and 130/85. The normal range for body temperature is between 96.8° F and 98.6° F. If the participant did not immediately fall within either of the normal ranges, both procedures were administered a second time after a waiting period of approximately five minutes. All of the subjects were required to fall within the normal ranges to be included in this study.

Materials The participants were pre-screened in psychology classes with the Horne and Ostberg Morningness/Eveningness (1976) questionnaire to determine which time of day they prefer. The participants were also be asked to rate their overall health to determine if they met the health criterion for this study. If the participants rated their overall health as not healthy, they were excluded from the study. Each participants’ response was above the “not healthy” criterion, therefore no participants were prohibited from taking part in this study. The participants were also required to complete the vocabulary section of the WAIS III (Wechsler, 1997), which is highly correlated to full scale IQ, in order to control for the intelligence of the subjects.

Factors that Influence Subjective Time

125

Procedure The participants were asked to use the production method of time estimation to approximate 30, 60, or 90 seconds in either the empty or complex interval condition of their session. The participants were then randomly assigned to the time of day groups. The participants were told in advance and at the testing area to take off their watches and to turn off and put away their cellular telephones. As suggested by Lennings and Burns (1998) and Smythe and Robertson (1999), the participants were then given a stopwatch and instructed how to use it. The stopwatch was placed on the table, upside-down, next to the participant so that he/she could not see the numbers. The participants were then asked to use the production method to estimate 30 seconds, 60 seconds, or 90 seconds. The empty interval task involved the participants passively waiting for the time to pass. Most complex stimuli in this interval had been removed from the environment (i.e., background noise, etc.). The complex interval task required the participants to shuffle a deck of cards and arrange them according to suit. After the participants produced the estimated time, the stopwatch was shown to the experimenter who wrote down the time out of view of the participant. Ten trials were empty intervals for 60 seconds, 10 trials were complex intervals for 60 seconds, 10 trials were empty intervals for 30/90 seconds, and 10 trials were complex intervals for 30/90 seconds for a total of 40 trials. The dependent variable was the summed totals, in seconds, for each of the four conditions. The participants were never able to see their times. The participants were tested between 7am and 10am for the morning groups and between 7pm and 10pm for the evening groups. Upon completion, the participants were debriefed and compensated for their time.

RESULTS Demographics Initially, a series of mixed-factor ANOVAs were preformed on the participants demographic data in order to assess whether the groups had been sufficiently matched. Across Gender, the participants did not differ on age, F(1,102)=1.34, p>.05, temperature, F(1,102)=3.72, p>.05, systolic blood pressure, F(1,102)=2.02, p>.05, diastolic blood pressure, F(1,102)=.21, p>.05, or WAIS III vocabulary scores, F(1,102)=.24, p>.05. Participants did differ on their self reported health scores, F(1,102)=5.37, p<.05. The results indicated that an Analysis of Covariance (ANCOVA) was needed to analyze the main effect of Gender, with health as the covariate. For Time of Day, participants did not differ on temperature, F(1,102)=3.48, p>.05, systolic blood pressure, F(1,102)=.82, p>.05, diastolic blood pressure, F(1,102)=.04, p>.05, health, F(1,102)=.97, p>.05, or WAIS III vocabulary scores, F(1,102)=.39, p>.05. There was a difference in age, F(1,102)=8.05, p<.05, where the morning type participants were older than the evening types, revealing the need for an ANCOVA when analyzing the main effect of Time of Day, with age as the covariate. For Type of Person, the results illustrate that the participants did not differ on age, F(1,102)=1.38, p>.05, temperature, F(1,102)=.18, p>.05, systolic blood pressure, F(1,102)=.43, p>.05, diastolic blood pressure, F(1,102)=1.19, p>.05, or the WAIS III scores,

126

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

F(1,102)=.18, p>.05. They did differ on their self-reported health scores, F(1,102)=4.44, p<.05. The results indicated that an Analysis of Covariance (ANCOVA) is needed to analyze the main effect of Type of Person, with self-rated health as the covariate.

Main Effects A 2 (Male/Female) X 2 (Morning/Evening type) X 2 (Morning/Evening time of day) X 2 (Empty/Complex intervals) X 2 (Fixed/Variable time period) mixed-factorial ANCOVA was used to analyze the main effects. Results indicated there was no main effect of gender, F(1,96)=.40, p=.53. Males (M=748.2, SD=168.4) and females (M=737.9, SD=194.1) showed no statistically significant differences. The results also indicated there was no main effect of the time of day, F(1,96)=.00, p=.99, revealing that, when tested in the morning (M=741.9, SD=162.5) or in the evening (M=744.2, SD=199.2), the participants showed no statistically significant differences in the estimation tasks. Furthermore, there was no main effect of the type of person, F(1,96)=.05, p=.82, revealing no differences in morning types (M=743.1, SD=213.5) and evening types (M=742.9, SD=143.2).

Five-Way and Four-Way Interactions The results were analyzed using a 2 (Male/Female) X 2 (Morning/Evening type) X 2 (Morning/Evening time of day) X 2 (Empty/Complex intervals) X 2 (Fixed/Variable time period) mixed-factorial ANCOVA. The ANCOVA was used due to differences that were found in age and reported health scores. The five-way interaction was not significant, F(1, 94)=.09, p=.76, nor were any of the four- way interactions (all Fs<1.65, all ps>.05).

Between-Subjects Factors There were no statistically significant differences reported in the overall interaction between Gender, Time of Day, and Type of Person, F(1,96)=.00, p=.99. There were also no statistically significant differences found in the overall interaction between Gender and Time of Day, F(1,96)=.03, p=.87, or in the overall interaction between Gender and Type of Person, F(1,96)=1.56, p=.22. There were no statistically significant differences reported in the overall interaction between Time of Day and Type of Person, but the findings were marginally significant, F(1,96)=3.78, p=.055. Interactions on each level of the dependent variable were also analyzed and the results are as follows: Time of Day X Type of Person vs. Empty/Fixed, F(1,96)= 2.86, p=.09, Time of Day X Type of Person vs. Empty/Variable, F(1,96)=2.41, p=.12, and Time of Day X Type of Person vs. Complex/Fixed, F(1,96)=2.87, p=.09, all yielding no significant differences. However, significant results were found on the interaction of Time of Day X Type of Person vs. Complex/Variable, F(1,96)=4.81, p<.05. Subsequent analyses were preformed on the condition of Time of Day X Type of Person vs. Complex/Variable to assess which simple effects had the most influence. Results revealed that when tested in the Morning, the morning types (M=734.7, SD=181.7) had a more

Factors that Influence Subjective Time

127

accurate estimation than the evening types (M=839.2, SD=172.8). When tested in the evening, the morning types (M=824.3, SD=252.5) had a less accurate estimation than the evening types (M=755.5, SD=171.3).

Within-Subjects Factors Several pairwise comparisons were used to analyze the differences in each level of the dependent variable. The levels were 1) Empty intervals/Fixed time period, 2) Complex intervals/Fixed time period, 3) Empty intervals/Variable time period, and 4) Complex intervals/Variable time period. As expected, the pairwise comparisons (α=.00) revealed statistically significant differences in the Empty Intervals/Fixed Time vs. Complex Intervals/Fixed Time, t(103) = -6.49, p < .05. The pairwise comparison (α=.00) also revealed statistically significant results for the Empty Intervals/Variable Time vs. Complex Intervals/Variable Time, t(103) = -7.69, p < .05. In addition, the third pairwise comparison (α=.00) for the Empty Intervals/Fixed Time vs. Complex Intervals/Variable Time condition was found to be statistically significant, t(103) = -8.01, p < .05. Moreover, the pairwise comparison (α=.00) for the Empty Intervals/Variable Time vs. Complex Intervals/Fixed Time condition also revealed a statistically significant difference, t(103) = 5.67, p < .05. However, as expected, pairwise comparisons (α=.84) revealed no significant differences in Empty Intervals/Fixed Time vs. Empty Intervals/Variable Time, t(103) = -.21, p = .84. Again as expected, the pairwise comparisons (α=.91) revealed no statistically significant differences in Complex Intervals/Fixed Time vs. Complex Intervals/Variable Time, t(103) = -.112, p = .91. These findings suggest that the participants differed in terms of which interval was used, empty or complex. The complex intervals were found to have a longer reported estimation than the empty intervals. Also, the findings suggest that participants did not differ in terms of the fixed-time or variable-time estimations. A subsequent Tukey Test was used to verify the accuracy of the pairwise comparisons. Table 2. Tukey Test for the Means of each level of the Dependent Variable

Empty/Fixed 697.4 Empty/Variable 699.3 Complex/Fixed 786.9 Complex/Variable 788.4

Empty/Fixed 697.4 -

Empty/Variable 699.3 1.9

Complex/Fixed 786.9 89.5*

Complex/Variable 788.4 91.0*

-

-

87.6*

89.1*

-

-

-

1.5

-

-

-

-

Critical Difference .05 = 32.93.

128

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

DISCUSSION The present study evaluated the effects of gender, time of day, and type of person on short-duration time estimations. Complex and empty intervals were also assessed, along with fixed and variable time intervals. This study was performed to better understand some of the factors that can influence short-duration time estimations and to try and clear up some of the inconsistencies between much of the research in this area. The most inconsistent results in time estimation studies deal with gender. Therefore, it was important to include this factor. The time-of-day factor is also a subject for debate. Little research has been done in the area time estimation dealing with time of day (morning/evening) and type of person (morning/evening), and the interaction between them. Studies dealing with memory on this interaction, however, have found significant results. Surprisingly, many of the proposed hypotheses were not supported. First, gender was not a factor in time estimation. The male participants and female participants showed equivalent time estimations in all conditions with short-duration time estimations. These findings are consistent with some studies in this area (Lennings and Burns, 1998; Marmaras et al., 1995), but not others (Eisler and Eisler, 1992; Hancock, Vercruyssen, and Rodenberg, 1992). The results of gender in time estimation are widely varied and additional research is needed for a more conclusive answer. The reason for the differences in gender may lie in which duration paradigm used and the method in which the results are obtained. These differences make it clear that any research done in this area needs to be invariable when using these factors, or test all the factors in one experiment. Previous studies dealing with memory have shown that the time of day tested can be a significant factor on a participants’ performance (Anderson et al., 1991). Because memory is believed to be directly related to time estimations, one hypothesis of this study was to reveal a significant finding with the time of day factor. The present study investigated the effect of time of day (morning/evening) on time estimation performance. The results indicated that time estimation was not influenced by the time of day that the subject is tested. These results conflict with Aschoff (1998) and Morofushi et al.(2001), who both observed that time estimations do fluctuate across the day. The present results also conflict with some studies dealing with memory (Anderson et al., 1991; Dunne et al., 1990) that reported significant fluctuations in performance at different times of the day. The type of person (morning/evening) factor has yielded many significant results in areas other than time estimation (Anderson et al., 1991; Mecacci and Rocchetti, 1998). For example, type of person differences have been found in personality, psychological disorders, and response to environmental stressors when dealing with morning and evening people (Mecacci and Rocchetti, 1998). The present study examined the differences that occur between morning and evening type people in their time estimations. The results showed no overall differences in estimates between morning or evening types. It had also been suggested that the type of person (morning/evening) and the time of day (morning/evening) interaction will influence time estimations (Myers and Tilley, 2003). For example, morning type participants tested in the morning will show similar time estimations as compared to evening types that were tested in the evening, but will not show comparable estimations with morning type participants tested in the evening and evening types that were tested in the morning. The present results showed that although statistically significant results were not found overall,

Factors that Influence Subjective Time

129

the main effect was marginally significant, F(1,96)=3.78, p=.055. When examined at each condition of the dependent variable, significant results were reported in the Time of Day X Type of Person vs. Complex/Variable interaction. These results specify that only under the Complex/Variable condition did the morning type subjects tested in the morning and the evening types tested in the evening show differences in estimations from morning types tested in the evening and evening types tested in the morning. In other words, participants’ yielded statistically different estimates under the complex/variable condition if the participant was tested at his/her preferred time of day. Continuing research should focus more on the time of day X type of person interaction in order to understand more about it. The present study showed a trend in the duration estimations of this interaction, and the results were marginally significant. It is not surprising that the present results indicated differences in the empty and complex interval conditions. It is surprising, however, that the intervals of time that contain complex stimuli, the deck of cards procedure in the present study, seem to pass by slowly. The participants “overestimation” of time was indicated by larger reported duration estimations. It is also surprising that the intervals of time where sensory stimuli had been reduced seemed to pass by more quickly. The participants “underestimation” of time was indicated by lower reported duration estimations. These results conflict with most of the research (Block, George, and Reed, 1980; Fraisse, 1984; Zakay, 1990) in the area of short-duration time estimation.

ALTERNATIVE INTERPRETATIONS The gender variable is needed in any experimental design when dealing with duration estimations mainly because the results are very inconsistent from one study to another. One possible explanation of this inconsistency is because the methods used to obtain the duration judgments and the duration paradigms are also inconsistent from study to study. The three main methods used to obtain the duration judgments are the verbal estimation, production, and reproduction. The duration paradigms are the prospective and retrospective paradigms. Block et al., (2000), published a meta-analytic review that concluded gender effects widely varied with the type of paradigm used, as stated above. “Relative to males, females sustain attention to time more in the prospective paradigm and have better episodic memory in the retrospective paradigm” (p.1333). The present study used the production method and the prospective paradigm to obtain duration judgments (Block, Hancock, and Zakay, 1998). Most of the authors in the past decade have also used these in order to control for some of the confounds in the literature, such as gender. It is unclear why time of day was not significant in many of the present analyses. Many previous studies in different areas other than time estimation showed significant differences, including some on memory (Anderson et al., 1991). Time estimations are directly related to memory (Fraisse, 1984; Smythe, 1999), so it would be sensible to include this variable. An explanation may be that the time of day factor can only be useful when it interacts with the type of person in dealing with duration estimations. It is also unclear why type of person was not significant in many of the analyses. Previous studies have shown that morning people are somewhat different from evening

130

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

people in terms of psychological disorders and personalities. Evening types are more likely to have more psychological disorders, in frequency and intensity, and cannot appear to handle themselves as well as morning types when in a stressful situation (Mecacci and Rocchetti, 1998). These results would imply that the two types have different ways of processing information and are different in many other areas as well, such as duration estimation. The overall interaction between type of person X time of day was marginally significant (p=.055). In a related time of day X type of person study by Myers and Tilley (2003), the results were also marginally significant. Myers and the present study may have resulted in significant interactions if more participants had been tested. In the present study, 104 subjects total were used, but in the Myers and Tilley study, only 55 total were used. The interactions between type of person X time of day at each of the four conditions of the dependent variable were also assessed. All of these interactions were marginally significant, except for the type of person X time of day at the complex variable condition, which was statistically significant (p<.05). Greater control of the methodology should be employed to control for the many confounds (i.e., score on the morningness/eveningness scale vs. actual time of day tested) that may arise. The present study found significant differences between the empty and complex intervals, where the participants reported that the complex intervals seemed to pass by slower than the empty intervals. These differences were the opposite of the findings of many other authors in the area of time estimation (Block, George, and Reed, 1980; Fraisse, 1984; Zakay, 1990). A possible explanation of the present findings may be dual task interference. The dual task interference theory states that when two tasks are preformed simultaneously, they are often carried out slower and with many more errors (Klingberg, 1998). In the complex interval condition, the participant was required to keep track of time and perform the deck of cards procedure. This would explain the longer reported time estimations in the complex interval condition. Further research needs to consider many of the issues previously discussed before beginning a study in the area of time estimation. The method used to obtain the duration judgments (verbal estimation, production, and reproduction) has been shown to produce different results (Block et al., 2000). The researcher must also decide which duration paradigm to use. The prospective paradigm is where the subjects are told in advance that they will have to pay attention to the passage of time (Block, Hancock, and Zakay, 1998; Fernandez et al., 2002; Fraisse, 1984) and the retrospective paradigm is where the subjects are told after an amount of time has passed to judge its duration (Fernandez et al., 2002 and Fraisse, 1984). Finally, the researcher needs to decide what type of time intervals (empty/complex) are needed. Any future study needs to be consistent with all of these factors.

REFERENCES Anderson, B., Burd, L, Dodd, J, and Kelker, K. (1980). A comparative study in estimating time. Journal of American Indian Education, 19(3), 1-4. Anderson, M., Petros, T.V., Beckwith, B.E., and Mitchell, W.W. (1991). Individual differences in the effect of time of day on long term memory access. American Journal of Psychology, 104(2), 241-255.

Factors that Influence Subjective Time

131

Aronson, E. (1972). The social animal. San Francisco: W. H. Freeman and Company. Aschoff, J. (1998). Human perception of short and long time intervals: Its correlation with body temperature and the duration of wake time. Journal of Biological Rhythms, 13, 437442. Block, R.A., Hancock, P.A., and Zakay, D. (2000). Sex differences in duration judgment: A meta-analytic review. Memory and Cognition, 28(1), 1333-1346. Block, R.A., Zakay, D., and Hancock, P.A. (1998). Human aging and duration judgments: A meta-analytic review. Psychology and Aging, 13, 584-596. Block, R.A., (1990). Cognitive models of psychological time. Hillsdale, NJ: Erlbaum. Block, R.A., George, E.J., and Reed, M.A. (1980). A watched pot sometimes boils: A study of duration experience. Acta Psychologica, 46, 81-94. Broverman, D.M., Edward L.K., Yutaka K., and William V. (1968). Roles of activation and inhibition in sex differences in cognitive abilities. Psychological Review, 75 (8), 23-50. Burstein, B., Lew, B. and Lissy, J. (1980). Sex differences in cognitive functioning: evidence, determinants, implications. Human Development, 23 (8), 289-313. Buyusse, D.J., Nofzinger, E.A., Germain, A., Melzer, C.C., Wood, A., Ombao, H., Kupfer, D.J., and Moore, R.Y. (2004). Regional brain glucose metabolism during morning and evening wakefulness in humans: A preliminary finding. Journal of Sleep and Sleep Disorders Research, 27(7), 1245-1254. Chastain, G., and Ferraro, F.R. (1997). Duration ratings as an index of processing resources required for cognitive tasks. Journal of General Psychology, 124(1), 49-76. Chelminski, I., Petros, T.V., Plaud, J.J., and Ferraro, F.R. (2000). Psychometric properties of the reduced Horne and Ostberg questionnaire. Personality and Individual Differences, 29, 469-478 Cole, N.S. (1997). The ETS gender study: How females and males perform in educational settings. Educational Testing Service. Retrieved from the World Wide Web on December 29, 2004, at http://www.csua.berkeley.edu/~stephy/gre/gender.pdf Darley, W.K., and Smith, R.E. (1995). Gender differences in information processing strategies: An empirical test of the selectivity model in advertising response. Journal of Advertising, 24 (1), 41-65. Drakulic, B., Tenjovic, L., and Lecic-Tosevski, D. (2003). Time integration questionnaire. European Journal of Psychological Assessment, 19(2), 101-116. Dunne, M.P., Roche, F., and Hartley, L.R. (1990). Effects of time of day on immediate recall and sustained retrieval from semantic memory. Journal of General Psychology, 117 (4), 403-410. Eisler, H., and Eisler, A. (1992). Time perception: Effects of sex and sound intensity on scales of subjective duration. Scandinavian Journal of Psychology, 33, 339-358. Erdfelder, E., Faul, F. and Buchner, A. (1996). GPower: A general power analysis program. Behavior Research Methods, Instruments, and Computers,28, 1-11. Espinosa-Fernandez, L., Miro, E., Cano, M., and Buela-Casal, G. (2003). Age related changes and gender differences in time estimation. Acta Psychologica, 112(3), 221-234. Fausto-Sterling, A. (1985). Myths of gender: Biological theories about women and men. New York: Basic Books. Fraisse, P. (1984). Perception and estimation of time. Annual Review of Psychology, 35, 1-36. Freidman, L. (1989). Mathematics and the gender gap: A meta-analysis of recent studies on sex differences in quantitative tasks. Review of Educational Research, 59, 185-213.

132

David P. Austin, F. Richard Ferraro, Ryan Kerzman et al.

Gibbon, J., and Church, R.M. (1981). Time left: Linear vs. logarithmic subjective time. Journal of Experimental Psychology: Animal Behavior Processes, 7(2), 87-107. Gibbon, J., Church, R.M., and Meck, W.H. (1984). Scalar timing in memory. In J. Gibbon and A. Allan (Eds.), Annals of New York Academy of Sciences. Vol.423. Timing and Perception (pp.52-77). New York: New York Academy of Sciences. Hancock, P.A., Vercruyssen, M., and Rodenberg, G. (1992). Estimation of duration and mental workload at differing time of day by males and females. Current Psychology: Research and Review, 11, 203-225. Holbrook, M. B. (1986). Aims, concepts, and methods for the presentation of individual differences in esthetic responses to design features. Journal of Consumer Research, 13 (12), 337-347. Horne, J.A. and Ostberg, O. (1976) A self assessment questionnaire to determine morningness and eveningness in human circadian rhythms. International Journal of Chronobiology, 4,(2), 97-110. James, W. (1890). The principles of psychology. New York: Holt. Kirkaldy, B.D. (1984). Individual differences in time estimation. International Journal of Sport Psychology, 15, 11-24. Klingberg, T. (1998). Concurrent performance of two working memory tasks: Potential mechanisms of interference. Cerebral Cortex, 8, 593-601. Komaroff, A.L. (1999). Harvard medical school family guide. New York: Simon and Schuster. Kuriyama, K., Uchiyama, M., Suzuki, H., Tagaya, H., Ozaki, A., Aritake, S., Kamei, Y., Nishikawa, T., and Takahashi, K. (2003). Circadian fluctuation of time perception in healthy human subjects. Neuroscience Research, 46(1), 23-31. Kuroda, R. (1936). Time estimation of longer intervals in the white rat. Acta Psychologica Keijo, 2, 155-159. Lennings, C.J., Burns, A.M. (1998). Time perspective: Temporal extension, time estimation, and impulsivity. The Journal of Psychology, 132(4), 367-380. Long, G.L., and Beaton, R.J. (1980). The effects of spatial frequency and target type on perceived duration. Perception and Psychophysics, 28, 413-421. Marmaras, N., Vassilakis, P., and Dounias, G. (1995). Factors affecting accuracy of producing time intervals. Perceptual and Motor Skills, 80, 1043-1056. Mazur, J.E. (2005). Learning and behavior, 6th ed. Upper Saddle River: Prentice Hall. Mecacci, L. and Rocchetti, G. (1998). Morning and evening types: Stress related personality aspects. Personality and Individual Differences, 25(3), 537-542. Miro, E., Cano, M., Espinosa-Fernandez, L. Buela-Casal, G. (2003). Time estimation during prolonged sleep deprivation and its relation to activation measures. Human Factors, 45,(1), 148-519. Moore-Ede, M.C., Czeisler, C.A., and Richardson, G.S. (1983). Circadian time keeping in health and disease: Basic properties of circadian pacemakers. New England Journal of Medicine, 309, 469-476. Morofushi, M., Shinohara, K., and Kimura, F. (2001). Menstrual and circadian variations in time perception in healthy women and women with premenstrual syndrome. Neuroscience Research, 41(4), 339-344.

Factors that Influence Subjective Time

133

Meyers-Levy, J. (1989). Gender Differences in Information Processing: A Selectivity Interpretation. In P. Cafferata and A. M. Tybout, Eds., Cognitive and affective responses to advertising. Lexington, MA: Lexington Books. Meyers-Levy, J. and Sternthal, B. (1991). Gender differences in the use of message cues and judgements. Journal of Marketing Research, 28 (2), 84-96. Myers, P.M. and Tilley, A. (2003). The relationship between diurnal type and time duration estimation at morning and evening times of day. Personality and Individual Differences, 35(5), 1141-1150. Ornstein, R.E. (1969). On the experience of time. Harmondsworth, England: Penguin. Petros, T.V., Beckwith, B.E., and Anderson, M. (1990). Individual differences in the effects of time of day and passage difficulty on prose memory in adults. British Journal of Psychology, 81(1), 63-72. Reed, S.K. (2004). Cognition: Theory and applications. 6th ed., Wadsworth: Belmont. Roberts, S. (1981). Isolation of an internal clock. Journal of Experimental Psychology: Animal Behavior Processes, 7, 242-268. Roberts, S., and Holder, M.D. (1984). What starts an internal clock? Journal of Experimental Psychology: Animal Behavior Processes, 10(3), 273-296. Silverman, J. (1970). Attentional styles and the study of sex differences. In D.I. Motofsky (Ed), Attention: Contemporary theory and analysis. New York: Appleton-CenturyCrofts. Smythe, J.A. and Robertson, I.T. (1999). On the relationship between time management and time estimation. British Journal of Psychology, 90, 333-347. Thomas, E.A. and Brown, I. (1974). Time perception and the filled duration illusion. Perception and Psychophysics, 16, 449-458. Treisman, M., Cook, N., Naish, P.I., and MacCrone, J.K. (1994). The internal clock: Electroencephalographic evidence for oscillatory processes underlying time perception. Quarterly Journal of Experimental Psychology, 47A, 241-289. Wechsler, D. (1997). Wechsler adult intelligence scale III: Administration and scoring manual. New York: Psychological Corp., Harcourt Brace Jovanovich. Zakay, D. (1990). The evasive art of subjective time measurement: Some methodological dilemmas. In Block, R.A. (Ed.), Cognitive models of psychological time. (pp.59-84), Hillsdale, NJ: Erlbaum. Zillmer, E.A., and Spiers, M.V. (2001). Principles of neuropsychology. Belmont: Wadsworth.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 5

COGNITIVE AND BEHAVIORAL ALTERATIONS IN CORTICOBASAL DEGENERATION PRESENTING AS DEMENTIA PHENOTYPE Rita Moretti1, Paola Torre, Cristina Vilotti, Maja Ukmar*, Francesca Capozzoli and Rodolfo M. Antonello Clinical Neurology. Department of Internal Medicine and Clinical Neurology University of Trieste, * Department of Radiology, University of Trieste, Italy

"In dementias, one may find all sorts of specific losses … and, as the disease worsens, a reduction of personal identity. And yet this reduction is virtually never complete; it is as if identity has such a robust, widespread neural basis; as if personal style is so deeply ingrained in the nervous system that it is never wholly lost, at least while there is still any mental life present at all. (This, indeed, is what one might expect if the personal quality of experience and feeling and thought has molded the structure of the brain from the start.) And it is this that makes a continuing possibility of being affected by music, even in the most deeply damaged patients, long inaccessible to language and most other modes of communication. For it is the inner life of music that can still make contact with their inner lives, with them; that can awaken the hidden, seemingly extinguished soul; and evoke a wholly personal response of memory, associations, feelings, images, a return of thought and sensibility, an answering identity." (O. Sacks)

1

Address for correspondence: Rita Moretti MD, Clinical Neurology, Department of INTERNAL MEDICINE AND Clinical Neurology, CLINICAL NEUROLOGY, University of Trieste, Ospedale di Cattinara, Strada di Fiume, 447 34149 Trieste, Italy; phone: 0039-40-3994321; fax:0039-40-910861; e-mail: [email protected].

136

Rita Moretti, Paola Torre, Cristina Vilotti et al.

INTRODUCTION The clinical syndrome which presents asymmetric parkinsonism (rigidity, and dystonia) associated to cortical abnormalities (and focal reflex myoclonus), along with peculiar pathology come to be known as corticobasal degeneration (CBD) (Riley et al., 1990; Rinne et al. 1999). Lang et al. (1994) defined the following as “qualifications ” of clinical features: rigidity without reinforcement, apraxia in clear absence of cognitive or motor deficit, sufficient to explain disturbance, cortical sensory loss, in preservation of primary sensation and asymmetric, alien limb phenomenon more than simple levitation, dystonia, focal limb, reflex myoclonus. Exclusion criteria comprised: early dementia, early vertical gaze palsy, rest tremor, severe autonomic disturbances, sustaine responsiveness to levo dopa, lesions on imaging studies indicating another pathologic process is responsible to what seen. It is now recognized that CBD patients usually present with two phenotypes reflecting its diverse anatomic involvement (Litvan et al., 1999). The most familiar presentation which may occur in approximately in one-half of autopsy-confirmed patients, “lateralized CBD,” is characterized by unilateral jerky, tremulous, akineto-rigid and apraxic extremity held in a fixed dystonic posture and displaying the alien limb syndrome (Litvan et al., 1999; Riley et al., 1990; Rinne et al., 1994;). The other pattern of presentation, is the “dementia phenotype,” characterized by severe cognitive deficits, particularly, frontal lobe disturbances characterized by severe executive dysfunction, and attention disorder; and later development of bilateral motor (e.g., non-levodopa responsive parkinsonism, pyramidal signs) and urinary (incontinence) disturbances (Grimes et al., 1999; Litvan et al., 1997; Litvan et al., 1999; Litvan et al., 2000; Litvan, 2001). The lateralized CBD phenotype (unilateral akineto-rigid syndrome unresponsive to levodopa and associated with dystonic postures; myoclonus and/or ideomotor apraxia) usually corresponds pathologically to CBD, however, occasionally, it has been found to correspond to progressive supranuclear palsy (PSP), Alzheimer’s disease, basal ganglia infarctions or dementia with Lewy bodies (Bhattia et al., 2000; Litvan, 2001). The dementia phenotype (which can have alternative clinical presentations, including progressive aphasia or frontal lobe dementia) is difficult to differentiate from Pick disease, frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) or dementia lacking distinctive histologic features. Interestingly, FTDP-17 with a P301S mutation in exon 10 of the tau gene may present with either a frontotemporal dementia or a lateralized CBD presentation (Bugiani et al., 1999). This suggest that the same primary gene defect in tau can lead to two distinct clinical phenotypes (Litvan, 2001). We have described (Moretti et al., 2004) the results of cognitive and behavioral observations observed in ten patients (six males and four females) came to our observation, with a confirmed diagnosis of probable lateralized CBD phenotype. All patients were followed for 16 months, with periodical neurological and neuropsychological examinations. Visits were scheduled to take place one, four, eight, 12 and 16 months from baseline. A complete neuropsychological examination was conducted at baseline and at the last visit, and results were compared. Our data, for the first time, as far as we know, comprise the results in a CBD group of patients, with a definite diagnosis of lateralized phenotype. What we have found is the evidence of a dysexecutive syndrome, with a discrete preservation of memory, more impaired in encoding, rather than of retrieval. In our patients,

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

137

the most salient aspects of cognitive impairment are: an evident alteration of rapid alternating operative strategies (such as in synonym/antonym production test), associated to the evident impairment of set shifting, of executive operations, of operative and sequential procedure, and of implementation of judgement and abstract reasoning. Moreover, the self activation of retrieval processes is partly preserved in CBD. Here, we present the results derived from the observation of two patients with a diagnosis of a dementia phenotype CBD. We discuss the data, by comparing the two groups, and ideally with a speculative overview on the topic.

SUBJECTS AND METHODS To assess the cognitive ability of these patients we used an extensive battery of tests suitable to demonstrate eventual neuropsychological defects. We evaluated them at the admission, when diagnosis was made. We have decided, in order to avoid a sterile reproduction of numbers and scores collected to divide them into some different subheadings. During a period comprised between 1st January 1997 and 20th August 2006, two patients (females) came to our observation. Their mean age was 54.6 ± 2.23 years old, right-handed (+ 22.56, as average score at Briggs and Nebes test) [10]. In an average time of 8.7 + 4.23 months, these patients and their caregivers complained for the evidence of an asymmetric akinetic syndrome, lateralized, associated to bradykinesia, alien limb syndrome, gait difficulties and slurred speech. Nobody stated specific cognitive impairment. Their past history was mute for relevant pathologies, but they have presented for an average time of 5.23± 1.2 years a progressive social withdrawal, with a macroscopic reduction of the output speech, marked signs of dysartria, and a various behavioral symptomatology, characterised by delusions, but not halluciantions, depression and anxiety. Frequently they presneted sundowning. Objectively, the patients showed modest signs of akinetic rigid-lateralized syndrome, without characteristic dystonic postures of the arm and hand (flexed and adducted arm). The two patients showed asymetric ideomotor apraxia, but not the alien hand syndrome; astereognosia was evident in both. The two patients did not show a defect in range of vertical eye movements with an increased saccadic latency and some degree of hypometria, especially for upgaze. They presented dysarthria, characterized mainly by hpokinetic features of low vocal intensity, monotonal speech, monoloudness, and imprecise articulation. These patients underwent to a brain-MRI, performed using a 1.5 T magnet. The examination were performed using axial and coronal slices. The following sequences were performed: a SE proton density and T2 weighted sequences (TR/TE: 2780/2080), a turboFLAIR (TR/TE/TI: 9832/150/2000), and a TSE T2 weighted sequence (TR/TE: 2876/120). All the patients had asymmetrical cortical atrophy contralateral to the more affected limbs. One patient showed an asymmetrical fronto-parietal atrophy mostly involving the posterior right frontal and right parietal areas. The other patient, which actually is the left side, showed on the most atrophic side, the lateral ventricle was larger and the sulci more dilated. As a result of atrophy, the bulk of the white matter was reduced, particularly in the parietal region. The fronto-parietal distribution of the atrophy was best appreciated on sagittal T1-weighted images.

138

Rita Moretti, Paola Torre, Cristina Vilotti et al.

Procedure: we decided to study general linguistic and praxis capabilities in our patients, as well as specific reading procedures. Social alterations and behavioural misconduct were evaluated by Neuropsychiatric Inventory (Cummings, Mega, Gray, Rosemberg-Thompson, Carusi, and Gornbei, 1994). Depression and anxiety have been tested in accordance with the Hamilton Rating Scale for Depression (Hamilton, 1967). Attention and global participation have been detected by the Mini Mental State Examination (Folstein, Folstein, and McHugh, 1975), by Stroop test (Stroop, 1935). Frontal lobe functions have been evaluated by execution of Raven Standard Progressive Matrices (Raven, 1960), by The Wisconsin Card Sorting Test (Heaton, 1981), by The Interpretation of Proverbs (Gorham, 1956). Memory was evaluated with digit – forward and backward span (Wechsler, 1945), with the Retrieval of a story (Barbizet and Cany, 1968), and with the retrieval of past events (Warrington and Sanders, 1971). Linguistic capabilities were tested with Bilingual Aphasia Test-part B (Italian language) (Paradis and Canzanella, 1990) and visuo-spatial abilities were measured by ability to carry out the Benton Line Orientation Test (Benton, Hamsher, Varney, and Spreen, 1983) and by reproduction of Koh’s block (Wechsler, 1981).

RESULTS Both the subjects showed marked signs of ideomotor apraxia with the affected hand. When given a determined tool, their performance was better, but not easy or fluid. The opposite hand showed mild tendency to ideomotor apraxia. That evidence was not so dramatic as in the CBD lateralized phenotype described elsewhere (Moretti et al., 2005a; Moretti et al., 2005b). Social skills. The two patients manifested, more than five years previous from the admission, personality changes, behavioral withdrawal, lack of insight and disinhibition. Both of them manifested a evident dietary change, which consist in an evident hypofagia, with a drastic reduction of the food intake. Moreover, they showed an obsessive compulsion towards specific and selected foods, e.g. salad, or apples, or bread; during their “dedicated periods”, they did not eat any other food. Both of them loss more than ten kilos in that period, Finally, 4.5 ± 1.3 months prior to the admission, they manifested craving for carbohydrates. Both of them were described by caregivers as irritable and impulsive, but they did not manifest loss of empathy towards relatives. Their relatives, and in particular their caregivers have been idolized by the patients, who felt sorrow and pain when they did not see them, due to hospital timetable. Both of them manifested agitation, anxiety and depression. Often, they showed their sorrow by crying and snivel. They have been disturbed by delusions, specifically as noxiousness thoughts, or as abandonment ideations. Therefore, they have been suspicious, and they follow constantly their relatives, or the examiners, when they have been confident with them. They presented an irrepressible tendency to wandering After the developing, their psychic condition maintained stable, almost associating poor judgement, but with an excellent insight and awareness into their situation. They obtained an average score of 65.4/144 ( + 7.45) in the Neuropsychiatric Inventory (Cummings et al., 1994). In the same session, depression and anxiety was evaluated and their average score in Hamilton Rating Scale for Depression was of 32.3/55 + 2.32 (normal range in our healthy control group is: 14/55) (Hamilton, 1967).

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

139

Attention and concentration At first examination, the two patients were fully alert, cooperative but disoriented to place and time. Their attention was easily distracted, in particular by visual interference stimulus. Their responses were often impulsive and some tasks were readily abandoned. Failure to understand instructions and irrelevant replies to questions might gave the impression of a comprehension impairment. The Mini-Mental State Examination (Folstein, Folstein, and McHugh, 1975) score was 15/30 (healthy control: 29.9/30) in one patient. The other is such in a devastated situation that she could not attend to MMSE any more. Paced Auditory Serial Addition Task (PASAT) (Gronwell, 1977) was impossible to perform (easy number; total correct) as well as Stroop (Stroop, 1935); in simple and elementary tasks, produced by the examiners test in divided attention subitems, both the patients made an elevated number of mistakes (more than 70% of their production) (healthy control group: 1%). Frontal lobe functions It ahs been impossible to perform the Raven Standard Progressive Matrices (Raven, 1960), standardized by age and education, as well as the Wisconsin Card Sorting Test (Heaton, 1981). At the Follow-Through of Stimulus Words using single letters (Warrington and Weiskrantz, 1982) these patients produced 14.21 ± 1.12 neologisms/20, (such as “gutrumpi” for giustiziare, or “muntrallo” for martello) (healthy control: 0/20 total mistakes. In simple tasks, defined by the examiners, which implements judgment and analogical properties (height, size, weight, shapes), they tend to perseveration errors and gave 19.89 ± 2.1 incorrect responses/50 (healthy control: 50 correct responses). The Interpretation of Proverbs (Gorham, 1956) (where ten standard and ten difficult proverbs were asked to be explained: a score of 2 is obtained when answer is appropriate; 1 if the answer is partially correct, and 0 if the answer is completely wrong), only one patient could be tested, and she obtained a score of 3/ 20 (healthy control group: 18.9/20). In the Similarities subtests of the WAIS-R (Wechsler, 1981), the same patient obtained a score of 3/26 (healthy group: 20/26total correct). When asked to solve simple problems of daily living, both the patients were limited and gave awkard solutions, if any. Memory Digit – forward and backward span (Wechsler, 1945) was impossible to (healthy volunteers: digit-forward span 7.5; digit –backward span 4.3). Retrieval of a story was impossible to obtaine (Barbizet and Cany, 1968) (healthy volunteers: 17.8/22). Finally, the retrieval of personal past events was remarkably preserved, but the linguistic limitation arose important difficulties in the interpretation of the data. (Warrington and Sanders, 1971). Visuospatial abilities At the first visit, perceptual and spatial abilities were macroscopically impaired; it was impossible to carry out the Benton Line Orientation Test (Benton, Hamsher, Varney, and Spreen, 1983). They could not reproduce all the pictures with the Koh’s block (Wechsler, 1981). In different elementary tasks, made by the examiners, the patients showed asimultagnosia. Thus, they manifested a real inability to grasp the meaning of an overall complex scene, although the different isolated elements that constitute it are well recognized, doubled by an inability to perceive more than one stimulus at a time. Moreover, they showed a loss of voluntary but not reflex eye movements and, generally, a poor visualmotor coordination. Language We decided to use the Bilingual Aphasia Test (BAT) (Paradis, and Canzanella, 1990), which uses a quadrimodal linguistically multidimensional approach. It is quadrimodal because it examines language performance in all four modalities: hearing, speaking, reading and writing. For each modality, language performance is investigated along three dimensions:

140

Rita Moretti, Paola Torre, Cristina Vilotti et al.

linguistic (phonological, morphological, syntactic, lexical, semantic), linguistic task (comprehension, repetition, judgement, lexical access, propositioning) and linguistic unit (word,. sentence, paragraph) (Paradis, and Canzanella, 1990). We used some parts of it, as clearly stated in the following parts. The BAT part B – Italian language, the patients showed great difficulties in executing complex commands and in syntactic comprehension tasks (37.56 ± 5.32 mistakes, normal error range, as stated by test parametric values =11). They could not read properly, they did fail in mental arithmetic tasks, oral and written tasks, in reading comprehension, in copying or in dictation tasks. Verbal fluency was dramtically impaired, (2 words with T, 3 with M, and 2 with P; our healthy volunteers: 43.5 ± 3.3). Five minutes of spontaneous speech was studied with a neurolinguistic analysis. The mean length of the utterances was 1.13 ± 2.34 words (our healthy volunteers: 11.7 ± 5.3 words), with 10 ±5.1 types and 14 ± 3.4 tokens, which revealed an impaired and very limited ability for word selection (our healthy volunteers: 75 ±1.56 types, 121 ±4.43 tokens). We found verbal and phonological paraphasias (e.g. respectively, “amico” for “marito”, and “trevolo” for “tavolo”) and substitutions of free grammatical morphemes and a high number of perseverations. The discourse was not pragmatically sound and it contained some semantically deviant sentences. Speech was markedly dysarthric; in one patient, for the most of the time, it has been unintelligible.

Figure 1. A coronal MRI image: marked parietal atrophy. One of the two patients described in the text.

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

141

DISCUSSION What we have previously found (Moretti et al., 2005) in the lateralized CBD phenotype, is the evidence of a dysexecutive syndrome, with a discrete preservation of memory, more impaired in encoding, rather than of retrieval. Moreover, it can be observed an evident alteration of rapid alternating operative strategies (such as in synonym/antonym production test), associated to the evident impairment of set shifting, of executive operations, of operative and sequential procedure, and of implementation of judgement and abstract reasoning. Moreover, the self activation of retrieval processes is partly preserved in CBD. These results could be over-simplified as due to an evident impairment of frontal subcortical circuits; the anatomical regions involved in CBD comprise primarily the frontal-subcortical circuits and related temporal limbic regions and parietal areas (Snowden et al., 2001). Structures included in the frontal-subcortical system are differentially vulnerable to cellular abnormalities caused by hyperphosphorylated tau protein. Three frontal-subcortical circuits have been identified (Cannatà et al, 2002). Their disruption causes an evident alteration of explorative behavior, apathy, abulia, disinhibition, alteration of set-shifting, and of working memory. What we observed reflects the evidence of subortical fronto-parietal pathways alterations, evidently progressive concomitant to the ingravescent decourse of the motor impairment. On the contrary, what it has been described in this chapter, is obviously different. The two patients manifested marked signs of behavioral alterations as well as cognitive disruption. Their course is progressive, slow, insidious and ingravescent. Sporadic studies explored behavior and cognition in CBD as a whole; Litvan et al. (1998) demonstrated marked behavior alteration. In particular, the irritability of patients with CBD was significantly associated with disinhibition and apathy. In that study, disinhibition was associated with aberrant motor behaviour and with delusions. On the other hand, these Authors noted that depression was not associated with any other behavior, suggesting a possible different pathophysiological mechanism. One of the most interesting point in Litvan et al. (1998) study was that total motor score was not associated with any behavior or cognitive scores. Even the presence of cognitive impairment in corticobasal degeneration is widely recognized. The review by Graham et al (2003) showes that, although the pattern of neuropsychological impairments can be highly variable across patients, several trends can be identified. The most characteristic impairments are limb apraxia, constructional and visuospatial deficits, acalculia, frontal dysfunction and nonfluent aphasia. It has been suggested (see data and literature in Graham et al., 2003) that it can be possible a clinical and neuropathological overlap between progressive nonfluent aphasia (a form of frontotemporal dementia) and CBD. What we have produced is the first description, as far as we know, of two cases of dementia-presenting CBD. The marked alterations are consistent with frontal behavioral alterations (Food intake alterations, obsessive behaviour, perseverations, agitation and delusions) and frontal-parietal network alterations which produced speech and language alterations, visuo-spatial disruption, loss of judgement and of analogical capabilities, executive alterations, and apraxia.

142

Rita Moretti, Paola Torre, Cristina Vilotti et al.

Dedicated studies (Traykov et al., 2002; Sawle et al., 1991) demonstrated that CBD patients have serotoninergic (secondary to involvement of raphe nuclei), noradrenergic (secondary to changes in the locus coeruleus), a well as dopaminergic abnormalities. This biochemical profile is similar to that of Parkinson’s disease; striatal abnormalities have been correlated with frontal lobe type behavioral disturbances and obsessive compulsive behaviors, presumably secondary to interruption of frontal subcortical circuits (Sawle et al., 1991; Cummings and Litvan, 2000). Cortical involvement in cognition is not so obvious as it appears: for the highest levels of intellectual functioning the entire brain must be intact. Although the brain functions as an integrated unit, certain areas have major influences on specific functions. Hence the history of clinical neurology was dominated by the attempt of localising specific functions in definite cortical areas. Therefore, peculiar and detailed evidence remain the traditional gold standard for differential diagnosis: lesions of the Broca’s area are tightly bound to motor aphasia for example. Dominant hemisphere parietal lesions produce classically ideomotor apraxia and dysphasia or aphasia, with either inability to understand commands or inability to speak or a combination of both. Very often, patients with left parietal lesions are wrongly assumed to be confused, due to their poor communication capacity (Patten, 1996.) Data concerning parietal lobe are still controversial, even considering that it is still debated the possible nexus between language formulation and praxis execution as far as parietal lobe is concerned. The extraordinary histological resemble of the areas 5 and 7 to frontal cortex structure consent to detect these areas as a superior and integrated system for sensory-associative elaboration: from these regions, different neural pathways project directly to the ventral-posterior thalamus. On the contrary, areas 39 and 40 of Broadmann are tightly bound with diffuse neural projections to the pulvinar: these areas mediated the gnosis perception and some authors postulate their function to be a possible integrative device for visual, auditory and sensitivity process. Parietal regions are in fact a convergent trait-d’union between anterior cortical areas and subcortical regions. Traditionally, parietal lobe is involved in the semantic monitoring procedure , through a neural net which connect the language formulation anterior cortex, via pulvinar projections through a constant control of the posterior language cortex. Then, the parietal posterior cortex is tightly bound to the release of formulated language, via the diffuse projections through the caudate and globus pallidus and via the ventral anterior thalamus end in the motor programming cortex . Moreover, recent studies demonstrate a prominent participation of parietal cortex in a particular human form of working memory, the verbal working memory. It appears to play a significant role in language comprehension and problem solving. Neuroimaging indicate that brain activation accompanying verbal working memory are found in dorsolateral prefrontal, inferior frontal, supplementary motor, premotor and parietal cortex. These results suggest that parietal regions are part of a network of brain areas that mediate the short term storage and retrieval of phonologically coded verbal material; the sequence series which the patient underwent are nothing different from problem solving strings (Schumacher et al.,1998). The parietal lobe is the guarantee of higher control of sequential, complex process of motor reach and finalized grap: if vision is restricted to one hemisphere, and all of thefore brain commissures are cut in the midline, monkeys can still guide either arm rapidly toward a visual target using either eye (Myers et al., 1962).They can also reach accurately after all

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

143

intracortical fibers have been severed by making deep cuts in the white matter between the parietal lobe visual areas and the frontal motor areas. Brinkman and Kuypers (1973) suggested that when vision is restricted to one hemisphere,and the corpus callosum is cut, the monkey uses the surviving corticocortical links from visual cortex to the ipsilateral motor cortex. The reach is then directed by a nondecussating descending corticospinal pathway that connects to neurons in the cord that control proximal muscles. Three subcortical targets of the parietal lobe visual areas probably play a role in various aspects of visually guided movement. The parietal lobes project to the basal ganglia, the superior colliculus and, by way of a relay in the pontine nuclei, the cerebellum (Glickstein, 2003). Study of subcortical targets of the parietal lobe of rats reveals a virtually complete laminar segregation of the cells that project to subcortical targets. Most of the projections to subcortical targets, other than reciprocal connections to the thalamus, are pyramidal cells located in lamina V. Ferrier first suspected a visual role for the angular gyrus, because electrical stimulation in this parietal lobe area caused eye movements (Ferrier, 1876). The eye movements are probably evoked by way of connections to the superior colliculus. Saccadic eye movements elicited by stimulation of the parietal lobe visual areas are abolished by ablation of the superior colliculus (Keating et al., 1983). Parietal lobe visual areas project densely to intermediate and deep layers of the superior colliculus (Lynch et al., 1985). The projection is particularly dense from the lateral intraparietal area (LIP), a region of the parietal lobes whose cells are active prior to saccadic eye movements (Andersen, 1989). Cells in area LIP that are activated antidromically following electrical stimulation of the superior colliculus are active prior to saccadic eye movements (Pare and Wurtz, 1997). There is a systematic difference in the average latency of cell activity in LIP and the colliculus relative to the eye movement. Parietal lobe visual cells are activated earlier, and they are more closely tied to the sensory stimulus than to the execution of the saccade. Collicular neurons are activated later, and they are more closely tied to the eye movement. Pare and Wurtz (1997) suggested that the circuit from parietal lobe to the colliculus constitutes "a progressive evolution in the neuronal processing for saccades." Thus, visual motion information is relayed simultaneously to two independent targets; the colliculus for guiding movements of the eyes and neck, the other to the cerebellum, perhaps for guiding the limbs.Nearly all of the cortical visual input to the pons and superior colliculus comes from the parietal lobe. These differences in the pattern of projection to subcortical targets must reflect a major difference in the function of the two pathways. The projection to the colliculus and pontine nuclei probably represents a pathway that is involved directly in the sensory guidance of movement (Glickstein, 2003). All these data largely justify the visuo-spatial alterations described in our patients. But, it has been said that the superior parietal lobule receives a massive corticocortical input from the primary somatosensory cortex; that was the reason for the fact that this brain areas was traditionally regarded to be a higher – order somatic association area (Kalasaka, 1996). But it responds to complex combinations of multi-joint motions, limb postures, and tactile inputs. This is consistent with extensive evidence that the parietal lobe plays a critical role in generating the so-called body schema, the neural mechanism underlying the perception and introspective awareness of body form, posture and movement (Graziano et al., 2000). The representation of limb posture and movement in the superior parietal lobule is not based only on somatosensory and somatomotor information; many neurons in area 5 and in

144

Rita Moretti, Paola Torre, Cristina Vilotti et al.

the medial intraparietal respond in combinations of both somatic and visual inputs (Colby, 1998). The most medial parts of the superior parietal lobule (including V6a, 7m, medial intraparietal) discharges and is modulated as a function of different combinations of inputs, including the direction of intended and executed arm movements, static arm postures, retinal input about target stimuli, motion of the target and visual feedback about movements of the arm, as well as the direction of the gaze and of eye movements (Kalaska et al., 2003). This combination of control, underlying on the progressive shift in reference frames, may be consistent with the sensorimotor coordinate transformation hypothesis for the planning and control of reaching movements. The most extrabiliant aspect is the online control exerted by the parietal lobe, throughout the movement. The initial motor command for reaching movements is only an approximation of the correct motor command, and the errors are corrected as the movement goes on (Gordon et al., 1994; Gordon et al., 1994 II). Visual feedback received early in the movement contributes to this refinement, even when the vision of the arm during the movement is not permitted (Glover and Dixon, 2001). Left parietal regions effectively are the storage not only of motor action representations, but also of movement formules sequences (Faglioni et al., 1985). In this so-called “ideomotor aphasia”, on the contrary, the patient cannot express the correct dynamic evolution of the different sequential operations which she practically can execute. It seems that some information do not transfer from the “inner speech – motor programming pathway” to the “verbal output-motor execution pathway”(Moretti et al, 2000). These results, in accordance with what previously presented indicate that lesions in left parietal cortex lead to an alteration of spatio-temporal organization of movements, that becomes increasingly prominent for more complex movements. Parietal cortex is tightly bound, as evidenced by what has been reported previously, to correct sequence of motor act realization and motor sequence development. That largely explains the motor alterations and the apraxia, described in our patients. The parietal lobe and more particularly its posterior part is involved in the control of saccades and attention. The lateral intraparietal area is involved in the control of saccades (Leigh and Zee, 1999), but also in attentional processes (Wardak et al., 2002; Bilsey and Goldberg, 2003). Furthermore, light stimulation of this area in the monkey results in a simple shift of visual attention (without eye movement), whereas stronger stimulation results in a saccade (Cutrell and Marrocco, 2002). The human parietal eye fields (PEF) projects to both the FEF and the superior colliculus (Pierrot Deseilligny et al., 2004). The parieto-FEF projection could be mainly involved in visual fixation (Rivaud et al., 1994). These results largely justify the attention defects evidenced in our patients. Moreover, degeneration occurring in CBD involves frontoparietal cortex and striatal structures. Together, the anatomical regions involved by this tauopathy comprise primarily the frontal-subcortical circuits and related temporal limbic regions (Lichter, 2001; Patients with CBD have a pattern of memory impairment similar to that of other patients with subcortical dementia, suggesting alterations of encoding, but overall of retrieval. Three frontal-subcortical circuits have been identified (Miller, 2000). A common feature of all these circuits is their unification of different parts of the frontal cortex with the basal ganglia and the thalamus in closed circuits with open elements that receive input from and project to other regions outside the loops.

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

145

The hypothesized function of the orbitobasal circuit is the correction of social control as the deficits seen with the selective disruption are disinhibition, impulsiveness, confabulation and antisocial conduct. The dorsolateral net supports attention and alternative programming capacities, as well as working memory (area 46) programs. Its deficit causes poorly focus attention, marked alteration of working memory, poor organization, defective planning capacities, lack of insight, and abnormal expression of empathy and sympathy. The medial frontal circuit might be involved in energy, motivation and selectivity of thoughts, while its disruption may cause apathy, abulia and marked depression. Within each of the circuits there are two pathways: a direct, which links the striatum with the globus pallidus interna/substantia nigra complex and an indirect pathway, which projects from striatum to globus pallidus externa, to subthalamus, to globus pallidus interna/substantia nigra to thalamus. The composite projections to deep subcortical parietal areas and to frontal regions seem able to justify the behavioural alterations observed in our patients.

CONCLUSIONS It has been suggested that over half of the pathologically diagnosed cases of CBD would not even have been considered for clinical evaluation because they do not present with the "classic" symptomatology (which includes a movement disorder), but rather present primarily with dementia (both the two patients have been diagnosed throughout the five and more years, as suffering from depression, acute psychosis, anxiety). Therefore, there are few cases described; it is not even known if it is a unique and almost not controversial pathology or, on the contrary, it is a part of a bigger syndrome, the so-called Pick complex. Different authors are struck by the pathological and clinical similarities between other well- (or better say, a little more -) known pathologies such as primary progressive aphasia or frontal variants of frontal dementia. The resemblance is evidently twofolded: pathological signs, such as ballooned neurons, identical or very similar to Pick cells (even if CBD degeneration involves, quite isolately affecting the perikarium and cell process of neurons, but also of astrocytes and oligodendroglia), and the fact that frontal dementia is linked to chromosome 17, pathologically close to CBD, too. What we have observed, however, arose different questions: 1) Dementia presenting CBD is a different pathological entity? 2) why can we detect even marked signs of cognitive deterioration in lateralized phenotype, but, on the contrary, the motor akinetic syndrome is not so clearly represented even five years after the pathology onset? 3) why the dementia phenotype seems to have a slower progression than lateralized phenotype? 4) why frontal signs dramatically merge only in dementia phenotype, considering that parietal-frontal projections seem to be involved in both syndromes?

146

Rita Moretti, Paola Torre, Cristina Vilotti et al.

Even if rare, CBD is not so infrequent; as usually occurs, when only subtle signs are observable on at the beginning of clinical presentation of degenerative disorders, one has to know what to look for, in order to be able to recognize the pathologic findings. Future studies are strongly needed to improve our knowledge and to clarify lots of doubts and, at the moment, not answerable answers.

REFERENCES Bilsey JW, Goldberg ME. Neuronal activity in the lateral intraparietal area and spatial attention. Science 2003; 299:81–86. Briggs GC, Nebes RD. Patterns of hand preference in a student population. Cortex 1975; 11, 230-238. Bugiani O, Murrell JR, Giaccone G, Hasegawa M, Ghigo G, Tabaton M, et al. Frontotemporal dementia and corticobasal degeneration in a family with a P301S mutation in tau. J. Neuropathol. Exp. Neurol. 1999; 58: 667-77. Cannatà AP, Alberoni M, Franceschi M, Mariani C. Frontal impairment in subcortical ischemic vascular dementia in comparison to Alzheimer’s Disease. Dementia Geriatric Cognitive Disorders 2002; 13: 101-111. Colby CL. Action-oriented spatial reference frames in cortex. Neuron 1998; 20: 15-24. Cummings JL, Litvan I. Neuropsychiatric aspects of corticobasal degeneration. In: I. Litvan, CG. Goetz, AE Lang (Eds). Corticobasal degeneration. Vol.82 Lippincott Williams and Wilkins, Philadelphia, 2000. Pp. 147-152.. cummings Jl, Mega M, Gray K et al. The NEuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia. Neurology 1994; 44: 2308-2014. Cutrell EB, Marrocco RT. Electrical stimulation of primate posterior parietal cortex initiates orienting and alerting components of covert attention. Exp Brain Res 2002; 144:103–113. Ferrier D. The functions of the brain, 1st ed. London: Smith, Elder and Co., 1876. Folstein M, Folstein S, McHugh P. Mini-Mental state. A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975,12:189–98. Glickstein M. Subcortical projections of the parietal lobes. . In: AM Siegel, RA. Andersen, HJ Freund, DD Spencer: The parietal lobes. Advances in neurology. Vol. 93. 2003. Lippincott Williams and Wilkins, Philapdelphia. Pp. 43-55. Glover S, Dixon P. Motor adaption to an optical illusion. Exp. Brain Res. 2001; 137: 254-258. Gordon J, Ghilardi MF, Cooper SE et al. Accuracy of planar reaching movements. Systematic extent errors resulting from inertial anisotropy. Exp. Brain Res. 1994; 99: 112-130. II. Gordon J, Ghilardi MF, Ghez C. Accuracy of planar reaching movements. I Independence of direction and extent variability. Exp. Brain Res. 1994; 99: 97-111. Gorham D.R.. The proverbs test. Psychological Test Specialists, 1956; Missoula, Montana. Graham NL, Bak TH, Hodges JR. Corticobasal degeneration as a cognitve disorder. Mov. Disord. 2003; 18 (11): 1224-1232. Graziano MSA, Cooke DF, Taylor CSR. Coding the location of the arm by sight. Science 2000; 290: 1782-1786. Grimes DA, Lang AE, Bergeron C. Dementia is the most common presentation of corticalbasal ganglionic degeneration. Neurology 1998; 50 (suppl 4): a96.

Cognitive and Behavioral Alterations in Corticobasal Degeneration …

147

Grimes DA, Lang AE, Bergeron C. Dementia is the most common presentation of corticalbasal ganglionic degeneration. Neurology 1998; 50 (suppl 4): a96. Kalaska JF, Cisek P, Gosselin-Kessiby N. Mechanism of selection and guidance of reaching movements in the parietal lobe. In: AM Siegel, RA. Andersen, HJ Freund, DD Spencer: The parietal lobes. Advances in neurology. Vol. 93. 2003. Lippincott Williams and Wilkins, Philapdelphia. Pp. 95-119. Kalaska JF. Parietal cortex area 5 and visuomotor behaviour. Can. J. Physiol. Pharmacol. 1996; 74: 483-498. Lang AE, Riley DE, Bergeron C. Cortical-basal ganglionic degeneration. In: DB Calne (Ed.) Neurodegenerative Diseases. Philadelphia: WB Saunders, 1994; 877-894. Lang AE, Riley DE, Bergeron C. Cortical-basal ganglionic degeneration. In: DB Calne (Ed.) Neurodegenerative Diseases. Philadelphia: WB Saunders, 1994; 877-894. Leigh RJ, Zee DS. The neurology of eye movements. 3rd ed. Oxford: Oxford University Press; 1999. Lichter DG, Cummings JL. Introduction and Overview. New York: The Guilford Press; 2001. Litvan I, Agid Y, Goetz C, Jankovic J, Wenning GK, Brandel JP, et al. Accuracy of the clinical diagnosis of corticobasal degeneration: a clinicopathologic study. Neurology 1997;48:119-125. Litvan I, Cummings JL, Mega M. Neuropsychiatric features of corticobasal degeneration. J. Neurol, Neurosurg. Psychiatry 1998; 65 (5): 717-721. Litvan I, Grimes DA, Lang AE, Jankovic J, McKee A, Verny M, et al. Clinical features differentiating patients with postmortem confirmed progressive supranuclear palsy and corticobasal degeneration. J. Neurol. 1999; 246 Suppl 2: II1-5. Litvan I, Grimes DA, Lang AE. Phenotypes and Prognosis: Clinicopathologic Studies of Corticobasal Degeneration. In: Litvan I, Goetz CK and Lang AE, editors. Advances in Neurology. Vol Corticobasal degeneration and related disorders. Philadelphia: Lippincott Williams and Wilkins, 2000: 183-96. Litvan I. Corticobasal degeneration. American Academy of Neurology 2001 Honolulu, 3PC.007:1-34. Lynch JC, Graybiel AM, Lobeck LJ. The differential projection of two cytoarchitectonic subregions ofthe inferior parietal lobule of macaque upon the deep layers of the superior colliculus. J. Comp. Neurol. 1985;235:241-254. Manos PJ. The utility of the ten-point clock test as a screen for cognitive impairment in general hospital patients. Gen. Hosp. Psych. 1997;8:469–76. Miller BL. Frontotemporal dementia: clinical and behavioral features. American Academy of Neurology, San Diego, 2000; 3PC.007: 11-22. Moretti R, Torre P, Ukmar M., Antonello RM, Cazzato G. A left-parietal lesion: a particular case of impairment in sequential procedure. Nuova Rivista di Neurologia, 2000: 10 (5): 187-191. Moretti R, Torre P., Antonello RM, Cattaruzza T, Cazzato G. Cognitive impairment in lateralized phenotype of corticobasal degeneration. Dementia and Geriatric Cognitive Disorders, 2005; 20: 158-162. Moretti R, Torre P., Antonello RM, Cazzato G. Corticobasal Ganglionic Degeneration: Cognitive and Functional Aspects. Novascience Editor, New York; 2005. B Myers RE, Sperry Rw, McCurdy NM. Neural mechanisms in visual guidance of movement. Arch. Neurol. 1962;7:195-202.

148

Rita Moretti, Paola Torre, Cristina Vilotti et al.

Paradis M, Canzanella M. Test per l’afasia in un bilingue. Versione Italiana. Hillsdale, NJ, 1990. Pare M, Wurtz B. Monkey posterior parietal neurons antidromically activated from superior colliculus. J. Neurophysiol. I997; 78:3493-3497. Patten J. Neurological differential diagnosis. Springer Verlag, London, 1996. Pierrot-Deseilligny, Milea D, Mu RM. Eye movement control by the cerebral cortex. Curr. Opin. Neurol. 2004; 17: 17-25. Raven JC. Standard Progressive Matrices. London: Lewis, 1938. Reisberg B, Borenstein J, Salob SP. Et al. Behavioural symptoms in Alzheimer’s disease: phenomenology and treatment. J. Clin. Psychiatry 1987;48(S):9–15. Riley DE, Lang AE. Cortical-basal ganglionic degeneration. In: SH. Appel (Ed) Current Neurology, Vol.12, St. Louis: Mosby, 1992; 155-171. Rinne J., Lee M., Thompson P., Marsden C. Corticobasal degeneration: a clinical study of 36 cases. Brain, 1994, 117: 1183-1196. Rivaud S, Mu¨ ri RM, Gaymard B, et al. Eye movement disorders after frontal eye field lesions in humans. Exp. Brain Res. 1994; 102:110–120. Sawle GV, Brooks DJ, Marsden CD, Frackowiak RSJ. Corticobasal degeneration: a unique pattern of regional cortical oxygen metabolism and striatal fluorodopa uptake demonstrated by positron emission tomography. Brain 1991;114:541-556. Schumacher EH, Smth E, Koeppe R, Awh E, Reuter-Lorenz PA, Marshuetz C, Willis C. The role of parietal cortex in verbal working memory. J. Neuroscience 1998; 18(13): 50265034. Snowden J, Bathgate D, Varma A, Blackshaw A, Gibbons ZC, Neary D. Distinct behavioural profiles in fronototemporal dementia and semantic dementia. J. Neurol. Neurosurg. Psychiatry 2001;70:323-332. Snowden J, Bathgate D, Varma A, Blackshaw A, Gibbons ZC, Neary D. Distinct behavioural profiles in fronototemporal dementia and semantic dementia. J. Neurol. Neurosurg .Psychiatry 2001;70:323-332. Spinnler H., Tognoni G. Standardizzazione e taratura italiana dei test neuropsicologici. The Italian Journal of Neurological Sciences, 1987; S6: 23-116. Traykov L, Baudic S, Thibaudet MC, Rigaud AS, Smagghe A, Boller F. Neuropsychlogical deficit in early subcortical vascular dementia: comparison to Alzheimer’s disease. Dementia Geriatric Cognitive Disorders 2002; 14: 26-32. Wardak C, Olivier E, Duhamel JR. Saccadic target selection deficits after lateral intraparietal area inactivation in monkeys. J. Neurosci. 2002; 22:9877– 9884. Wechsler D. WAIS-R manual. New York: The Psychological Corporation 1981.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 6

A POSSIBLE ROLE OF THE BDNF/TRKB PATHWAY IN THE PATHOGENESIS OF BIPOLAR DISORDER AND POTENTIAL THERAPEUTIC TARGETS Shih-Jen Tsai1a,b and Chen-Jee Honga,b a

Department of Psychiatry, Taipei Veterans General Hospital, Taiwan and b Division of Psychiatry, School of Medicine, National Yang-Ming University, Taiwan

ABSTRACT Brain-derived neurotrophic factor (BDNF), a member of the neurotrophic factor family, promotes neuronal development, survival and function. In addition, BDNF can modulate synaptic plasticity and neurotransmitter release across multiple neurotransmitter systems, as also modulate various intracellular signal-transduction pathways. BDNF exerts its effect through the receptor tropomyosin related kinase B (TrkB) and the p75 low affinity neurotrophin receptor. Recent studies have demonstrated that the BDNF/TrkB pathway may play an important role in the pathogenesis and therapy of bipolar disorder (BPD). In rodents, mood-stabilizing treatments have been shown to alter the BDNF/TrkB activity. Furthermore, recent genetic association studies have demonstrated that the BDNF genetic polymorphism is associated with BPD. Stress has been shown to markedly alter BDNF levels in certain brain areas including the hippocampus, which is thought to be involved in the pathogenesis of mood disorders. In this review, we summarize our current understanding of the involvement of the BDNF/TrkB pathway in the pathogenesis of BPD. We also discuss medications related to the treatment of BPD, and make several recommendations for future studies into the relationship between the BDNF/TrkB signaling pathway and BPD.

Keywords: Bipolar disorder, brain-derived neurotrophic factor, receptor tropomyosin related kinase B, genetic

1

Corresponding author: Dr. Shih-Jen Tsai, Department of Psychiatry, Taipei Veterans General Hospital, No. 201 Shih-Pai Road, Sec. 2, 11217, Taipei, Taiwan, Tel: +886-2-28757027 ext. 276, Fax: +886-2-28725643, Email: [email protected].

150

Shih-Jen Tsai and Chen-Jee Hong

INTRODUCTION Bipolar disorder (BPD) is a severe, chronic and disabling mental disease which afflicts approximately 1.5-3.0% of both men and women, and is the sixth leading cause of disability worldwide [Angst, 1998; Narrow et al., 2002; Post, 2005]. It is often characterized by two seemingly opposite mood states; mania and depression. When a patient is in the "manic stage" of their illness, they may be talkative, energetic and portray a decreased need for sleep. Patients may switch quickly from one topic to another, as if they cannot get their thoughts out fast enough. This stage often feels good to the patient, but others may feel irritable and easily become angry during this stage. Judgment is often impaired, and they may go on shopping sprees. Furthermore, patients may have grand plans that are unrealistic, and some may experience delusions or hallucinations similar to schizophrenia. The depressed stage of the illness presents with similar symptoms to those associated with major depression: including low mood, changes in eating and sleeping patterns, feelings of hopelessness and helplessness and often suicidal thinking. Typically, the patient may have reduced energy levels, slowed thinking and movements and difficulties with concentration. Mood stabilisers (e.g. lithium, valproate, and carbamazepine) are recommended in all phases of treatment for BPD. In more severe manic or depressive stages with psychosis, antipsychotics are recommended for use in combination with the above regimens for treatment [Kahn et al., 2000]. Although genetics and familial studies strongly suggest that a neurobiological basis may underlie the pathophysiology of BPD [Lenox et al., 2002], to date, the pathophysiological mechanisms underlying this disease are still not understood. During the past decade, there has been growing evidence supporting roles of neurotrophic factors (which regulate neuronal growth, development, survival and plasticity) in major depressive disorder (MDD), another major disorder of mood. Among the neurotrophic factors, brain-derived neurotrophic factor (BDNF) is the most promising candidate and study focus in the pathogenesis of MDD [Duman et al., 2001]. BDNF, a member of the neurotrophic factor family, is the most abundant neurotrophin in the brain [Leibrock et al., 1989]. BDNF plays a key role in the regulation of neuronal survival during the development and maintenance of the mature-neuron phenotype, promoting neuronal survival and preventing neuronal death [Maisonpierre et al., 1990; Tuszynski and Gage, 1994]. In addition, BDNF modulates synaptic plasticity and modulates neurotransmitters across many neurotransmitter systems as well as the intracellular signaltransduction pathway [Pezet and Malcangio, 2004]. In the brain, BDNF exerts its influences by signaling through TrkB receptors [one of the tyrosine kinase (Trk) family of receptors] and the p75 low-affinity neurotrophin receptor (p75NTR) [a member of the tumour necrosis factor-receptor superfamily] [Pezet and Malcangio, 2004]. Once it is bound to the TrkB receptor, BDNF initiates multiple signalling cascades, including the phosphatidylinositol 3kinase (PI3K)/Akt pathway and the extracellular signal-regulated kinase 1/2 (ERK1/2) pathway [Encinas et al., 1999]. Both of these pathways regulate the transcription factors that control gene expression and production of cyclic AMP response element binding protein (CREB), a key mediator of BDNF-induced gene expression [Finkbeiner, 2000]. The role of BDNF in MDD was revealed in research conducted by Nibuya and colleagues, [Nibuya et al., 1995; Nibuya et al., 1996] where long-term administration of several types of antidepressants (including selective serotonin reuptake inhibitors) increases

A Possible Role of the BDNF/TrkB Pathway …

151

BDNF expression in the hippocampus. Another study reported that centrally administered BDNF produces antidepressant-like activity in animal models of depression [Siuciak et al., 1997]. These findings suggest that BDNF has antidepressant-like effects and that by extrapolation, it may be implicated in the pathogenesis of MDD [Duman et al., 1997]. This hypothesis is further supported by animal studies that demonstrate that stress, which is thought to be involved in the pathogenesis of mood disorders, markedly alter BDNF levels in selected brain areas, including the hippocampus [Smith et al., 1995]. Furthermore, a trend towards increased BDNF immunoreactivity has been demonstrated in postmortem studies of several regions of brains taken from depressed patients who were treated with antidepressants compared with controls who were untreated at the time of death [Chen et al., 2001]. With the important role of BDNF in MDD pathogenesis and the depressed states also present in BPD, BDNF becomes an attractive candidate in the study of BPD pathogenesis and treatment. In this present paper, an overview of the roles of BDNF in BPD and its treatment will be presented.

BDNF AND BPD TREATMENT Lithium and sodium valproate are the two most prevalently used therapeutic agents in the treatment of BPD. Therefore, the common sites of action for these two agents could be related to the pathogenesis of BPD. In 2001, Fukumoto and colleagues first showed that long-term treatment with lithium-containing diets in rats increased BDNF protein levels by up to 90% in the frontal, hippocampal and temporal cortices. In contrast, the same lithium treatment did not alter TrkB levels. Moreover, repeated administration of valproate also increased the expression of BDNF in the frontal cortex and hippocampus [Fukumoto et al., 2001]. The finding that prolonged lithium treatment increases cortical and hippocampal BDNF has also been confirmed in three other studies [Angelucci et al., 2003; Einat et al., 2003; Jacobsen et al., 2004]. Jakobsen and Mørk [2004] observed that these changes in BDNF protein levels in the hippocampus and frontal cortex in rats were associated with an overall reduction in BDNF mRNA expression, suggesting that there is not a direct correspondence between changes in BDNF mRNA and protein expression induced by lithium treatment. The association between the BDNF/TrkB signaling pathway and a possible mechanism underlying the therapeutic effects of lithium was further investigated by Hashimoto and colleagues [2002] in a study that used cultured cerebral cortical neurons prepared from wildtype mice (+/+) or heterozygous (−/+) and homozygous (−/−) mice lacking BDNF. They showed that lithium failed to protect against in vitro glutamate-induced excitotoxicity in cultures from BDNF knockout mice, in contrast to the complete protection in cultures from wild-type mice. Furthermore, K252a (an inhibitor of the Trk receptor) and a BDNF neutralizing antibody suppressed the neuroprotective effect of lithium in wildtype mice. Treatment of cortical neurons with lithium increased the cellular BDNF content in three days and the phosphorylation of TrkB at Tyr490 in five days, suggesting that long-term lithium administration enhances BDNF expression and/or secretion, leading to the activation of the TrkB receptor. These findings suggest that the BDNF/TrkB pathway plays an essential role in mediating the neuroprotective effect of lithium. In addition, some studies have demonstrated

152

Shih-Jen Tsai and Chen-Jee Hong

that lithium induces some of the signaling cascades downstream from TrkB in the rodent frontal cortex and hippocampus [Einat et al., 2003; Mai et al., 2002; Nemeth et al., 2002]. Although most studies have demonstrated increased central BDNF levels or activation, a recent study by Rantamaki and colleagues, [2006] has found that prolonged lithium treatment did not have a significant effect on BDNF levels in either the anterior cingulate cortex or hippocampus in mice. Moreover, acute and long-term lithium treatment induces TrkB activation in the anterior cingulate cortex but not in the hippocampus. Interestingly, reduced activation in the hippocampus of a major intracellular target of TrkB, CREB, was observed following acute lithium treatment . These findings suggest that lithium-induced changes in BDNF levels or activity may only occur within defined cortical regions. This is in line with a study by Angelucci and colleagues [2003] using an animal model of depression, the Flinders Sensitive Line (FSL) rats and their controls, the Flinders Resistant Line (FRL). In controls, there are significant increases in BDNF levels only within the occipital cortex but not in the frontal cortex. Conversely, in FSL rats, lithium treatment decreased or failed to alter BDNF levels in frontal cortex and hippocampus. These findings also suggest that BDNF response to lithium treatment can vary between different rat strains. Electroconvulsive therapy (ECT) is an effective somatic treatment for BPD. Studies have demonstrated that chronic administration of ECT increases and prolongs the induction and duration of BDNF and TrkB mRNA in rat hippocampus [Nibuya et al., 1995; Lindefors et al., 1995]. In addition, repeated ECT has been shown to increase BDNF protein in the hippocampus, frontal cortex, occipital cortex, parietal cortex, entorhinal cortex, striatum and septum [Altar et al., 2003; Angelucci et al., 2002]. Moreover, using BDNF knock-out models (BDNF+/-), it has been demonstrated that BDNF contributes to ECT-induced mossy fiber sprouting; which may contribute to the therapeutic effects of ECT [Vaidya et al., 1999].

BDNF IN ANIMAL MODELS OF BPD Amphetamine-induced hyperactivity is the most established rodent model for mania. This characterised hyperactivity is attenuated by a number of mood stabilizers, including lithium, anticonvulsants, and antipsychotics [Cappeliez and Moore, 1990; Gould et al., 2001]. A recent study by Frey and colleagues [In press] investigated the effects of the mood stabilizers lithium and valproate in an animal model of BPD based on chronic D-amphetamine administration. They demonstrated that chronic D-amphetamine administration decreased BDNF levels, and lithium and valproate increased BDNF levels in the rat hippocampus.

Central and Peripheral BDNF Levels in BPD So far there is only one study investigating BDNF levels in human BPD brains. Since abnormalities in BDNF activity have been postulated in patients with mood disorders, Chen and colleagues [2001] have considered the BDNF levels in postmortem hippocampi of patients diagnosed with mood disorders. They found that BDNF levels were deceased in drug-free MDD patients but not in BPD patients.

A Possible Role of the BDNF/TrkB Pathway …

153

Although BDNF is highly concentrated in the brain, it is also present in blood, with higher concentrations seen in serum than in plasma [Radka et al., 1996]. Although the specific cellular sources of serum/plasma BDNF are still not known, it has been reported that platelets, vascular endothelial cells and neurons may contribute to the circulating BDNF load [Lommatzsch et al., 2005]. Furthermore, studies in rats have revealed a strong positive correlation (r = 0.81) between serum and cortical BDNF levels that continues from early maturation and throughout the aging process [Karege et al., 2002]. This suggests that serum BDNF levels may reflect brain BDNF levels. Previous studies have reported that untreated MDD patients exhibit lower serum BDNF levels than healthy controls, and that antidepressant treatment in these patients can restore serum BDNF levels to that within the normal range [Aydemir et al., 2005]. In 2005, Machado-Vieira1 and colleagues, first reported that BDNF plasma levels were significantly lower in drug free (224.8 ± 76.5mg/L) and lithium treated BPD groups (115.7 ± 43.8 mg/L), when compared to controls (318.5 ± 11.2 mg/L) (P < 0.001). Furthermore, the severity of manic episode negatively correlated with plasma BDNF levels (r = 0.78; P < 0.001). This suggests that decreased plasma BDNF levels may be involved in the clinical presentation and biological basis of bipolar disorder. This finding is further supported by a recent report on serum BDNF levels in manic, depressed and euthymic BD patients compared with matched healthy controls [Cunha et al., (In press)]. Serum BDNF levels were decreased in manic (P = 0.019) and depressed (P = 0.027) BPD patients, as compared with euthymic BPD patients and healthy controls. In addition, serum BDNF levels were negatively correlated with the severity of manic (r = -0.37, P = 0.005) and depressive (r = -0.30, P = 0.033) symptoms. These findings suggest that changes in BDNF levels may be state-related rather than trait-related, and BDNF signaling may be associated with the BPD pathogenesis and pharmacological response [Cunha et al., (In press)]. Lymphoblasts have been demonstrated to express BDNF mRNA and are increased upon activation of cAMP signaling [Karege et al., 2004]. One particular study has investigated BDNF expression through cAMP activation in 10 BPD and 10 control subjects. However, no difference in BDNF expression was observed between BPD and controls in either resting or stimulated cells [Karege et al., 2004]. This raises the question of BDNF involvement in BPD pathogenesis, but this study is limited by its sample size and was conducted on a peripheral model cell, whose role in BDNF is still unclear.

Genetic and Pharmacogenetic Studies of BDNF in BPD The human BDNF gene has been mapped to chromosome 11p13 [Maisonpierre et al., 1991]. Two linkage studies have suggested that chromosome 11p13-14 is a putative locus for the genes responsible for the development of BPD [McInnes et al., 1996; Detera-Wadleigh et al., 1999]. From this evidence and the above findings in animal studies it appears that BDNF may be an appropriate candidate gene for BPD studies. Recently a common single nucleotide polymorphism (reference number rs6265), consisting of a missense change (G196A) [that produces a non-conservative amino acid change (Valine to Methionine) in the coding exon of the BDNF gene at position 66 (Val66Met)] was described as a functional polymorphism; depolarization-induced secretion was reduced in Met BDNF-transfected neurons compared with Val BDNF analogs [Egan et al., 2003].

154

Shih-Jen Tsai and Chen-Jee Hong

In 2002, two large family-based association studies have undertaken analysis of BDNF markers in BPD. The haplotype analysis by Skalar and colleagues [2002] reported a haplotype containing the Met allele of the BDNF Val66Met polymorphism was undertransmitted whilst Neves-Pereira and colleagues [2002] reported that a haplotype containing the Val allele was over-transmitted in certain cases. These findings suggest that the BDNF gene (or a nearby analogue) may be related to BPD susceptibility. However, studies in Japanese populations [Nakata et al., 2003; Kunugi et al., 2004], Chinese populations [Hong et al., 2003] and Polish populations [Skibinska et al., 2004] failed to find an association between this BDNF polymorphism and BPD. Further case-control association study in individuals of Belgian origin also found no association between BPD and this polymorphism or another BDNF polymorphism (11757C > G) [Oswald et al., 2004], as did a study in a Japanese population fail to find association between BPD and the purported BDNF polymorphism (1360C>T) [Nakata et al., 2003]. However, in a family-based association study in children with a prepuberal and early adolescent bipolar disorder phenotype, it was demonstrated that the BDNF Val allele was preferentially transmitted (P = 0.014) [Geller et al., 2004]. The association between the BDNF Val66Met polymorphism and early onset BPD was supported completely by one study [Skibinska et al., 2004], and partially by another study using childhood onset mood disorders (COMD; including BPD and MDD) [Strauss et al., 2004]. The later study group also investigated genetic variation in the BDNF receptor TrkB, and did not find support for TrkB as a potential susceptibility gene for COMD [Adams et al., 2005]. Another study using 99 adults with a history of COMD and matched psychiatrically healthy controls found that the alleles of val66met were not significantly associated with COMD. However, alleles of the BDNF (GT)(n) polymorphism were highly associated with COMD in this sample (P = 0.0032) [Strauss et al., 2004]. Recently there were two large-scale case-controlled association studies of the BDNF Val66Met polymorphism with BPD. The first involved 621 patients with BPD and 998 control subjects of European descent [Lohoff et al., 2005]. All BPD patients had a positive family history for mood disorder. The result demonstrated that the frequency of the Val allele was significantly increased in BPD patients when compared to controls (P = 0.028; OR = 1.22; 95% CI: 1.02-1.47). Another study of a UK-White BPD case-controlled sample (n = 3062) found no overall evidence of allele or genotype association [Green et al., 2006]. However, they did find an association with disease status in a subset of 131 individuals that had experienced rapid cycling at some time (P = 0.004). This suggests that the BDNF Val66Met polymorphism does not play a major role in influencing susceptibility to BPD as a whole, but is associated with susceptibility to the rapid-cycling subset of this disorder [Green et al., 2006]. In another study in a Brazilian population with 226 BPD patients and 252 controls, it was also demonstrated that the allele frequencies were found to be different between BPD and controls, with a higher frequency of the Val allele in BPD patients than in controls (P = 0.0005) [Michelon et al., 2005]. The distribution of genotypes also differed significantly between cases and controls (P = 0.0025), with a higher frequency of heterozygous and homozygous Val/Val genotypes in the BPD-patients group. From the above reports, the BDNF Val66Met polymorphism may be associated with BPD as a whole or in a subset of this disease (e.g. childhood onset, rapid cycling, positive family history) with a higher frequency of the Val allele in BPD patients. Another possible factor contributing to these disparities is the difference in ethnic background of the studied populations. Most of the negative replication studies were conducted in Asian populations

A Possible Role of the BDNF/TrkB Pathway …

155

and allele frequencies differ significantly between individuals of Asian decent and European decent, who have higher Val allele frequencies. It is also possible that another BDNF genetic variant is involved in BPD pathogenesis, and that the linkage disequilibrium between this genetic variant and the Val66Met polymorphism does not occur in all ethnic populations. Finally, another possible reason for inconsistency is the lack of statistical power due to small sample size in some of the studies associated with negative finding: alternatively, the positive results in some studies might have arisen by chance or due to sample stratification. Studies also investigated the BDNF Val66Met polymorphism in the various BPD phenotypes. Regarding age of onset in BPD, one study found that BPD subjects with Val/Val have an earlier age of onset of the illness than subjects with the Val/Met genotype (27 years versus 38 years) [Rybakowski et al., 2003]. However, other studies found no association [Kunugi et al., 2004; Hong et al., 2003]. Studies in Asian patients also show that the BDNF Val66Met polymorphism is not associated with the presence of psychotic features, family history and suicidal history in BPD subjects [Kunugi et al., 2004; Hong et al., 2003]. Another common BDNF polymorphism tested in schizophrenia is the C-270T polymorphism (GENBANK, AF411339), which is located in the 5’ non-coding region of BDNF and has been associated with late-onset Alzheimer’s disease [Kunugi et al., 2001]. The only association study of the C-270T polymorphism in BPD is negative [Nakata et al., 2003]. Since BDNF may play a role in BPD pathogenesis and lithium may change central BDNF levels, studies have also investigated the association between BDNF genetic variants and lithium’s therapeutic response. In 88 Polish BPD subjects, Rybakowski and colleagues [2005] looked at two BDNF polymorphisms, Val66Met and -270C/T, and response to lithium prophylaxis, through stratifying the subjects into three groups: excellent responders, partial responders and non-responders. The result demonstrated that there is an association between BDNF genetic variation and quality of lithium prophylaxis; excellent lithium responders were significantly more likely to have the Val/Met genotype than non-responders. Also, it was noted that the C/T genotype of the 270C/T BDNF polymorphism occurred more frequently in excellent lithium responders than non-responders. However, recent study in Japanese population did not support an association between lithium response and BDNF Val66Met polymorphism in patients with BPD [Masui et al., 2006]. The BDNF Val66Met polymorphism is reported to affect human episodic memory and hippocampal general function in schizophrenic patients, siblings of schizophrenic patients and healthy volunteers [Egan et al., 2003]. Study has tested a possible association between the BDNF Val66Met polymorphism and performance in a neurocognitive test, the Wisconsin Card Sorting Test (WCST), in 54 BPD patients [Rybakowski et al., 2003]. It was found that the performance in all domains of the WCST was significantly better in subjects with the Val/Val BDNF genotype compared with the Val/Met genotype, suggesting a role of BDNF in prefrontal cognitive function in BPD patients [Rybakowski et al., 2003]. Recently, the same authors expanded this study to 129 schizophrenic patients and 111 BPD patients. They further confirmed that BPD patients with the Val/Val genotype obtained significantly better results on three of five domains in the WCST. However, no relationship between the BDNF polymorphism and the results in the WCST test was found in the schizophrenic group, suggesting that the BDNF Val66Met polymorphism may be associated with cognitive performance in the WCST in BPD but not in schizophrenia [Rybakowski et al., 2006].

156

Shih-Jen Tsai and Chen-Jee Hong

CONCLUSION BDNF is an extremely versatile molecule that is involved in numerous processes, including embryogenesis, the control of neural plasticity in adults, regulation of synaptic neurotransmitter activity and the maintenance of neuronal structural integrity. Studies into animal models, mood stabilizer treatments, serum BDNF levels and BDNF genetics in BPD have demonstrated that the BDNF/TrkB pathway may be associated with BPD pathogenesis or focuses for therapy. Several recommendations for future studies into BDNF/TrkB in BPD have been proposed. Firstly, in animal as well as human studies, alterations in central and peripheral BDNF levels in BPD have suggested BDNF dysfunction may play a role in the pathogenesis of BPD and mood stabilizers may restore the balance seen in healthy controls. However, the exact nature of BDNF dysfunction and the specific brain regions involved that in BDP pathogenesis are still unknown and need further clarification. Secondly, genetic studies have tried to link different variants in gene coding for BDNF with BPD or its clinical manifestations, but have not been conclusive. Discrepancies among these studies could arise from factors such as the diversity of allele distribution between populations from different races, the heterogeneity of BPD, stratification effects and inadequate sample sizes. Future investigations, especially family-based association studies, with larger sample sizes involving different populations are needed to determine whether BDNF is truly a genetic locus for susceptibility to BPD. In addition, for genes containing multiple polymorphisms, haplotype distribution represents the best genetic approach. Therefore, a haplotype consisting of multiple BDNF genetic polymorphisms may have better power to detect the association between the BDNF gene and BPD, or its phenotypes such as treatment response or age of onset. Thirdly, since BDNF/TrkB signaling dysfunction may be implicated in the pathogenesis of BPD and this pathway is affected by mood stabilizer treatment in animal studies, this may represent a target to attenuate or reverse the deficits in neuroplasticity and cellular resilience observed in BPD patients [Quiroz et al., 2004]. The BDNF Val66Met polymorphism lies within the proBDNF region of the genes and is not translated into the final mature BDNF protein product. In vitro study has demonstrated that the Met allele is associated with impaired intracellular trafficking and regulated secretion [Egan et al., 2003]. In addition, agents such as antidepressants and thyroxine that potentially induce manic states also increase central BDNF [Nibuyaet al., 1996; Meredith et al., 2002]. For example, mania-like symptoms sometimes manifest in hyperthyroid patients [Evans et al., 1995]. Higher levels of BDNF mRNA were measured in the hippocampus of hyperthyroid rats, as compared to normal controls [Luesse et al., 1998]. From these findings, it has been suggested that BDNF overactivity may play a key role in the pathogenesis of the manic state [Tsai, 2004]. Thus, agents that can decrease BDNF/TrkB activity may be therapeutic for BPD. However, blocking BDNF-TrkB pathways with TrkB antagonists may be harmful, as BDNF-TrkB deficiency has been related to MDD, as well as some degenerative diseases. A partial agonist is an agent that elicits a maximum response that is less than that of an agonist (e.g., the physiological ligand), so, in the presence of excess full agonist, a partial agonist would act as an antagonist. Recently, specific TrkB partial agonists have been synthesized by O'Leary and Hughes [2003]. If BPD is to be associated with BDNF-TrkB hyper-function, it is proposed

A Possible Role of the BDNF/TrkB Pathway …

157

that these partial TrkB agonists may provide a novel strategy for the treatment of BPD [Tsai, 2006]. In this report we have focused on the review of BDNF/TrkB in the pathogenesis of BPD because BDNF is the most abundantly distributed neurotrophic factor in the brain, and the most widely studied in BPD. Other neurotrophic factors (e.g., nerve growth factor, neurotrophin 3 and neurotrophin 4/5) may also be of importance in the pathogenesis of BPD. Further exploration of both primary genetic alterations and secondary impairments in the receptors and signal transducers associated with these neurotrophic factors, as well as of the neurotrophic factors themselves, involved in the pathogenesis of BPD may be needed.

REFERENCES Adams JH, Wigg KG, King N, Burcescu I, Vetro A, Kiss E, Baji I, George CJ, Kennedy JL, Kovacs M, Barr CL. Association study of neurotrophic tyrosine kinase receptor type 2 (NTRK2) and childhood-onset mood disorders. Am. J. Med. Genet. B. Neuropsychiat.r Genet 2005;132:90-5. Altar CA, Whitehead RE, Chen R, Wortwein G, Madsen TM. Effects of electroconvulsive seizures and antidepressant drugs on brain-derived neurotrophic factor protein in rat brain. Biol. Psychiatry 2003;54:703-9. Angelucci F, Aloe L, Jimenez-Vasquez P, Mathe AA. Electroconvulsive stimuli alter the regional concentrations of nerve growth factor, brain-derived neurotrophic factor, and glial cell line-derived neurotrophic factor in adult rat brain. J ECT 2002;18:138-43. Angelucci F, Aloe L, Jimenez-Vasquez P, Mathe AA. Lithium treatment alters brain concentrations of nerve growth factor, brain-derived neurotrophic factor and glial cell line-derived neurotrophic factor in a rat model of depression. Int. J. Neuropsychopharmacol.2003;6:225-31. Angst J. The emerging epidemiology of hypomania and bipolar II disorder. J. Affect Disord. 1998;50:143-51. Aydemir O, Deveci A, Taneli F. The effect of chronic antidepressant treatment on serum brain-derived neurotrophic factor levels in depressed patients: a preliminary study. Prog. Neuropsychopharmacol. Biol. Psychiatry 2005;29:261-5. Cappeliez P, Moore E. Effects of lithium on an amphetamine animal model of bipolar disorder. Prog Neuropsychopharmacol Biol. Psychiatry 1990;14:347-58. Chen B, Dowlatshahi D, MacQueen GM, Wang JF, Young LT. Increased hippocampal BDNF immunoreactivity in subjects treated with antidepressant medication. Biol. Psychiatry 2001;50:260-5. Cunha AB, Frey BN, Andreazza AC, Goi JD, Rosa AR, Goncalves CA, Santin A, Kapczinski F. Serum brain-derived neurotrophic factor is decreased in bipolar disorder during depressive and manic episodes. Neurosci. Lett (press). Detera-Wadleigh SD, Badner JA, Berrettini WH, Yoshikawa T, Goldin LR, Turner G, Rollins DY, Moses T, Sanders AR, Karkera JD, Esterling LE, Zeng J, Ferraro TN, Guroff JJ, Kazuba D, Maxwell ME, Nurnberger JI Jr, Gershon ES. A high-density genome scan detects evidence for a bipolar-disorder susceptibility locus on 13q32 and other potential loci on 1q32 and 18p11.2. Proc. Natl. Acad. Sci. U S A 1999;96:5604-9.

158

Shih-Jen Tsai and Chen-Jee Hong

Duman RS, Heninger GR, Nestler EJ. A molecular and cellular theory of depression. Arch. Gen. Psychiatry 1997;54:597-606. Egan MF, Kojima M, Callicott JH, Goldberg TE, Kolachana BS, Bertolino A, Zaitsev E, Gold B, Goldman D, Dean M, Lu B, Weinberger DR. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 2003;112:257-69. Einat H, Yuan P, Gould TD, Li J, Du J, Zhang L, Manji HK, Chen G. The role of the extracellular signal-regulated kinase signaling pathway in mood modulation. J. Neurosci. 2003;23:7311-6. Encinas M, Iglesias M, Llecha N, Comella J X. Extracellular-regulated kinases and phosphatidylinositol 3-kinase are involved in brain-derived neurotrophic factor-mediated survival and neuritogenesis of the neuroblastoma cell line SH-SY5Y. J. Neurochem. 1999;73:1409-21. Evans DL, Byerly MJ, Greer RA. Secondary mania: diagnosis and treatment. J. Clin. Psychiatry 1995;56 Suppl:31-7. Finkbeiner S. CREB couples neurotrophin signals to survival messages. Neuron 2000;25:1114. Frey BN, Andreazza AC, Cereser KM, Martins MR, Valvassori SS, Reus GZ, Quevedo J, Kapczinski F. Effects of mood stabilizers on hippocampus BDNF levels in an animal model of mania. Life Sci. (press). Fukumoto T, Morinobu S, Okamoto Y, Kagaya A, Yamawaki S. Chronic lithium treatment increases the expression of brain-derived neurotrophic factor in the rat brain. Psychopharmacology 2001;158:100-6. Geller B, Badner JA, Tillman R, Christian SL, Bolhofner K, Cook EH Jr. Linkage disequilibrium of the brain-derived neurotrophic factor Val66Met polymorphism in children with a prepubertal and early adolescent bipolar disorder phenotype. Am. J. Psychiatry 2004;161:1698-700. Gould TJ, Keith RA, Bhat RV. Differential sensitivity to lithium's reversal of amphetamineinduced open-field activity in two inbred strains of mice. Behav. Brain Res. 2001;118:95105. Green EK, Raybould R, Macgregor S, Hyde S, Young AH, O'Donovan MC, Owen MJ, Kirov G, Jones L, Jones I, Craddock N. Genetic variation of brain-derived neurotrophic factor (BDNF) in bipolar disorder: case-control study of over 3000 individuals from the UK. Br J. Psychiatry 2006;188:21-5. Hashimoto R, Takei N, Shimazu K, Christ L, Lu B, Chuang DM. Lithium induces brainderived neurotrophic factor and activates TrkB in rodent cortical neurons: an essential step for neuroprotection against glutamate excitotoxicity. Neuropharmacology 2002;43:1173-9. Hong CJ, Huo SJ, Yen FC, Tung CL, Pan GM, Tsai SJ. Association study of a brain-derived neurotrophic-factor genetic polymorphism and mood disorders, age of onset and suicidal behavior. Neuropsychobiology 2003;48:186-9. Jacobsen JP, Mork A. The effect of escitalopram, desipramine, electroconvulsive seizures and lithium on brain-derived neurotrophic factor mRNA and protein expression in the rat brain and the correlation to 5-HT and 5-HIAA levels. Brain Res. 2004;1024:183-92.

A Possible Role of the BDNF/TrkB Pathway …

159

Kahn DA, Sachs GS, Printz DJ, Carpenter D, Docherty JP, Ross R. Medication treatment of bipolar disorder 2000: a summary of the expert consensus guidelines. J. Psychiatr. Pract. 2000;6:197-211. Karege F, Schwald M, Cisse M. Postnatal developmental profile of brain-derived neurotrophic factor in rat brain and platelets. Neurosci. Lett. 2002;328:261-4. Karege F, Schwald M, Papadimitriou P, Lachausse C, Cisse M. The cAMP-dependent protein kinase A and brain-derived neurotrophic factor expression in lymphoblast cells of bipolar affective disorder. J. Affect. Disord. 2004;79:187-92. Kunugi H, Iijima Y, Tatsumi M, Yoshida M, Hashimoto R, Kato T, Sakamoto K, Fukunaga T, Inada T, Suzuki T, Iwata N, Ozaki N, Yamada K, Yoshikawa T. No association between the Val66Met polymorphism of the brain-derived neurotrophic factor gene and bipolar disorder in a Japanese population: a multicenter study. Biol. Psychiatry 2004;56:376-8. Kunugi H, Ueki A, Otsuka M, Isse K, Hirasawa H, Kato N, Nabika T, Kobayashi S, Nanko S. A novel polymorphism of the brain-derived neurotrophic factor (BDNF) gene associated with late-onset Alzheimer's disease. Mol. Psychiatry 2001;6:83-6. Leibrock J, Lottspeich F, Hohn A, Hofer M, Hengerer B, Masiakowski P, Thoenen H, Barde YA. Molecular cloning and expression of brain-derived neurotrophic factor. Nature 1989;341:149-52. Lenox RH, Gould TD, Manji HK. Endophenotypes in bipolar disorder. Am. J. Med. Genet 2002;114:391-406. Lindefors N, Brodin E, Metsis M. Spatiotemporal selective effects on brain-derived neurotrophic factor and trkB messenger RNA in rat hippocampus by electroconvulsive shock. Neuroscience 1995;65:661-70. Lohoff FW, Sander T, Ferraro TN, Dahl JP, Gallinat J, Berrettini WH. Confirmation of association between the Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene and bipolar I disorder. Am J Med Genet B Neuropsychiatr. Genet. 2005;139:51-3. Lommatzsch M, Zingler D, Schuhbaeck K, Schloetcke K, Zingler C, Schuff-Werner P, Virchow JC. The impact of age, weight and gender on BDNF levels in human platelets and plasma. Neurobiol. Aging 2005;26:115-23. Luesse HG, Roskoden T, Linke R, Otten U, Heese K, Schwegler H. Modulation of mRNA expression of the neurotrophins of the nerve growth factor family and their receptors in the septum and hippocampus of rats after transient postnatal thyroxine treatment. I. Expression of nerve growth factor, brain-derived neurotrophic factor, neurotrophin-3, and neurotrophin 4 mRNA. Exp. Brain Res. 1998;119:1-8. Machado-Vieira1 R, Kapczinski F, Souza DO, Portela LWC, Gentil V. Neurochemical evaluation of neurotrophic factors and markers of neuronal damage during manic episode in drug naïve and lithium treated subjects: the possible role of severity of symptoms. Bipolar Disord. 2005;7(suppl. 2):73. Mai L, Jope RS, Li X. BDNF-mediated signal transduction is modulated by GSK3beta and mood stabilizing agents. J. Neurochem. 2002;82:75-83. Maisonpierre PC, Belluscio L, Friedman B, Alderson RF, Wiegand SJ, Furth ME, Lindsay RM, Yancopoulos GD. NT-3, BDNF, and NGF in the developing rat nervous system: parallel as well as reciprocal patterns of expression. Neuron 1990;5:501-9.

160

Shih-Jen Tsai and Chen-Jee Hong

Masui T, Hashimoto R, Kusumi I, Suzuki K, Tanaka T, Nakagawa S, Suzuki T, Iwata N, Ozaki N, Kato T, Kunugi H, Koyama T. Lithium response and Val66Met polymorphism of the brain-derived neurotrophic factor gene in Japanese patients with bipolar disorder. Psychiatr. Genet. 2006;16:49-50. McInnes LA, Escamilla MA, Service SK, Reus VI, Leon P, Silva S, Rojas E, Spesny M, Baharloo S, Blankenship K, Peterson A, Tyler D, Shimayoshi N, Tobey C, Batki S, Vinogradov S, Meza L, Gallegos A, Fournier E, Smith LB, Barondes SH, Sandkuijl LA, Freimer NB. A complete genome screen for genes predisposing to severe bipolar disorder in two Costa Rican pedigrees. Proc. Natl. Acad. Sci. U S A 1996;93:13060-5. Meredith G, Callen S, Scheuer D. Brain-derived neurotrophic factor expression is increased in the rat amygdala, piriform cortex and hypothalamus following repeated amphetamine administration. Brain Res. 2002;949:218-27. Michelon L, Cordeiro Q, Vallada H. Association study between the Val-66-Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene and bipolar disorder. Bipolar Disord 2005;7(suppl. 2):77. Nakata K, Ujike H, Sakai A, Uchida N, Nomura A, Imamura T, Katsu T, Tanaka Y, Hamamura T, Kuroda S. Association study of the brain-derived neurotrophic factor (BDNF) gene with bipolar disorder. Neurosci. Lett. 2003;337:17-20. Narrow WE, Rae DS, Robins LN, Regier DA. Revised prevalence estimates of mental disorders in the United States: using a clinical significance criterion to reconcile 2 surveys' estimates. Arch. Gen. Psychiatry 2002;59:115-23. Nemeth ZH, Deitch EA, Szabo C, Fekete Z, Hauser CJ, Hasko G. Lithium induces NF-kappa B activation and interleukin-8 production in human intestinal epithelial cells. J. Biol. Chem. 2002;277:7713-9. Neves-Pereira M, Mundo E, Muglia P, King N, Macciardi F, Kennedy JL. The brain-derived neurotrophic factor gene confers susceptibility to bipolar disorder: evidence from a family-based association study. Am. J. Hum. Genet. 2002;71:651-5. Nibuya M, Morinobu S, Duman RS. Regulation of BDNF and trkB mRNA in rat brain by chronic electroconvulsive seizure and antidepressant drug treatments. J. Neurosci. 1995;15:7539-47. Nibuya M, Nestler EJ, Duman RS. Chronic antidepressant administration increases the expression of cAMP response element binding protein (CREB) in rat hippocampus. J. Neurosci. 1996;16:2365-72. O'Leary PD, Hughes RA. Design of potent peptide mimetics of brain-derived neurotrophic factor. J. Biol. Chem. 2003;278:25738-44. Oswald P, Del-Favero J, Massat I, Souery D, Claes S, Van Broeckhoven C, Mendlewicz J. Non-replication of the brain-derived neurotrophic factor (BDNF) association in bipolar affective disorder: a Belgian patient-control study. Am. J. Med. Genet. B. Neuropsychiatr. Genet 2004;129:34-5. Pezet S, Malcangio M. Brain-derived neurotrophic factor as a drug target for CNS disorders. Expert. Opin. Ther. Targets 2004;8:391-9. Post RM. The impact of bipolar depression. J Clin Psychiatry 2005;66 Suppl 5:5-10. Quiroz JA, Singh J, Gould TD, Denicoff KD, Zarate CA, Manji HK. Emerging experimental therapeutics for bipolar disorder: clues from the molecular pathophysiology. Mol. Psychiatry 2004;9:756-76.

A Possible Role of the BDNF/TrkB Pathway …

161

Radka SF, Holst PA, Fritsche M, Altar CA. Presence of brain-derived neurotrophic factor in brain and human and rat but not mouse serum detected by a sensitive and specific immunoassay. Brain Res. 1996;709:122-301. Rantamaki T, Knuuttila JE, Hokkanen ME, Castren E. The effects of acute and long-term lithium treatments on trkB neurotrophin receptor activation in the mouse hippocampus and anterior cingulate cortex. Neuropharmacology 2006;50:421-7. Rybakowski JK, Borkowska A, Czerski PM, Skibinska M, Hauser J. Polymorphism of the brain-derived neurotrophic factor gene and performance on a cognitive prefrontal test in bipolar patients. Bipolar Disord. 2003;5:468-72. Rybakowski JK, Borkowska A, Skibinska M, Szczepankiewicz A, Kapelski P, LeszczynskaRodziewicz A, Czerski PM, Hauser J. Prefrontal cognition in schizophrenia and bipolar illness in relation to Val66Met polymorphism of the brain-derived neurotrophic factor gene. Psychiatry Clin. Neurosci. 2006;60:70-6. Rybakowski JK, Suwalska A, Skibinska M, Szczepankiewicz A, Leszczynska-Rodziewicz A, Permoda A, Czerski PM, Hauser J. Prophylactic lithium response and polymorphism of the brain-derived neurotrophic factor gene. Pharmacopsychiatry 2005;38:166-70. Siuciak JA, Lewis DR, Wiegand SJ, Lindsay RM. Antidepressant-like effect of brain-derived neurotrophic factor (BDNF). Pharmacol. Biochem. Behav. 1997;56:131-7. Skibinska M, Hauser J, Czerski PM, Leszczynska-Rodziewicz A, Kosmowska M, Kapelski P, Slopien A, Zakrzewska M, Rybakowski JK. Association analysis of brain-derived neurotrophic factor (BDNF) gene Val66Met polymorphism in schizophrenia and bipolar affective disorder. World J. Biol. Psychiatry 2004;5:215-20. Sklar P, Gabriel SB, McInnis MG, Bennett P, Lim YM, Tsan G, Schaffner S, Kirov G, Jones I, Owen M, Craddock N, DePaulo JR, Lander ES. Family-based association study of 76 candidate genes in bipolar disorder: BDNF is a potential risk locus. Mol. Psychiatry 2002;7:579-93. Smith MA, Makino S, Kvetnansky R, Post RM. Stress and glucocorticoids affect the expression of brain-derived neurotrophic factor and neurotrophin-3 mRNAs in the hippocampus. J. Neurosci. 1995;15:1768-77. Strauss J, Barr CL, George CJ, King N, Shaikh S, Devlin B, Kovacs M, Kennedy JL. Association study of brain-derived neurotrophic factor in adults with a history of childhood onset mood disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2004;131:16-9. Tsai SJ. Is mania caused by overactivity of central brain-derived neurotrophic factor? Med. Hypotheses 2004;62:19-22. Tsai SJ. TrkB partial agonists: potential treatment strategy for epilepsy, mania, and autism. Med. Hypotheses 2006;66:173-5. Tuszynski MH, Gage FH. Neurotrophic factors and diseases of the nervous system. Ann. Neurol. 1994;35 Suppl:S9-12. Vaidya VA, Duman RS. Depresssion--emerging insights from neurobiology. Br. Med. Bull. 2001;57:61-79. Vaidya VA, Siuciak JA, Du F, Duman RS. Hippocampal mossy fiber sprouting induced by chronic electroconvulsive seizures. Neuroscience 1999;89:157-66.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 7

DIFFICULTY COPING AND STRESSORS IN THE FIRST YEAR POSTPARTUM FOR MOTHERS AND FATHERS Stephen Matthey∗ Sydney South West Area Health Service, Sydney, Australia.

ABSTRACT Much of the work that documents new parents coping experiences is based upon small sample sizes, thus making it difficult to know the rate at which such experiences occur. This study combined qualitative and quantitative information on this issue. First time parents (221 mothers; 179 fathers) were surveyed one year after the birth about their experiences of coping. Results showed that 24% of women and 10% of men had experienced at least one episode of difficulty coping for more than 2 weeks. For approximately half of these women and men the onset of these longer duration episodes occurred after six weeks postpartum. All mothers and fathers reported that adjusting to the change in their life had impacted on them. In addition, other frequently reported stressors included: baby-care issues and fatigue (mothers and fathers); household chores; infant illness; financial concerns; lack of support; a lack of confidence; and tension with family members (mothers). For men frequent stressors included work-related stress and concern for his partner. There were few differences in reported stressors between women experiencing longer episodes and short episodes of difficulty coping. These data complement the qualitative studies on the experiences of new mothers and fathers, by quantifying the frequency of perceived stressors. This information can be used to normalise the experiences of new parents when providing them with appropriate services. In addition, the data suggest that just screening for psychosocial difficulties at one time point (e.g., 6 weeks postpartum) will miss a considerable proportion of women or men who may have difficulty coping at a later date. The lack of discernible differences in stressors between women self-reporting difficulty coping for long and short durations lends some support to the questionable usefulness of just focusing on women meeting diagnostic criteria for a mood disorder. ∗ Correspondence concerning this article should be addressed to Dr. Stephen Matthey, Sydney South West Area Health Service, Research Director: Infant, Child & Adolescent Mental Health Service, Area Mental Health (ICAMHS) Mental Health Centre (Level 1), Locked Bag 7103, Liverpool BC NSW 1871. Australia. ph: (02)9616 4262; Fax: (02) 9601 2773; e-mail: [email protected].

164

Stephen Matthey Keywords: postnatal depression; distress; coping; fathers; mothers

INTRODUCTION The term postnatal depression (PND), while not a diagnostic category in DSM-IV, is usually confined to women (or men) who meet DSM-IV criteria for major or minor depression, and have an infant of less than 12 months old. While DSM-IV does have a postpartum onset specifier (within 4 weeks of the birth), this short time span is rarely used by clinicians and researchers alike. The rate of PND, using these criteria, has consistently been found to be between 8% and 15% for women (O’Hara and Swain, 1996), and between 1.0% and 5.3% for men (Matthey, Barnett, Ungerer and Waters, 2000; Matthey, Barnett, Howie, and Kavanagh, 2003). Expanding the criteria to include DSM-IV anxiety disorders increases the rate of caseness to around 20% for women and 10% for men (Matthey et al, 2003). The terms postnatal depression or anxiety, being based upon a symptomatology model that originates from a medical model, are equated by some as indicating a mental illness. While this term does not necessarily mean that the aetiology is organic (cf. Barnett, Matthey and Boyce, 1999), this view is often put forward as an argument against the use of such terms or labels. Creedy and Schochet (1996) consider that diagnosing a woman with postnatal depression, and basing treatment upon such a ‘disorder’, results in treatment which “induce a false-coping strategy because the cause of the problem is not addressed" (p.14). The view that the label PND is unhelpful for women, in that it either fails to capture the experience of women, or implies an organic/hormonal aetiology with resulting medical-type interventions (e.g., medication), has also been expressed by others, including Barclay and Kent (1998), Barclay and Lloyd (1996), Jebali (1993), Lewis and Nicolson (1998), Mauthner (1998), and Nicolson (1990; 1999). These investigators report on the experiences of women in the first year without using such diagnostic labels. They paint a common picture of women coming to terms with the changes or losses they experience, a sense of isolation, lack of support from their partners and physical adjustments (e.g., pain, sleep deprivation). This picture is usually collected through in-depth interviews with a small number of women. Thus Nicolson (1990, 1999) interviewed 24 women; Lewis and Nicolson (1998) report on a sample of 12 women, Mauthner (1993; 1998; 1999) reports on samples of 20 and 40 women, Ugarizza (2002) on 30 women and Beck (1992) investigated the experiences of seven women with high levels of postnatal distress. A slightly larger study was undertaken by Brown, Lumley, Small and Astbury (1994) who reported on the experiences of 45 depressed and 45 non-depressed women. With regard to fathers, small-scale qualitative studies (e.g., n = 15) have shown that men experience strain in their relationship with their partner and find fatherhood more difficult than they expected. Stressors include the sense of responsibility, settling a crying baby, the balancing of work and family demands and struggling for recognition as a father (Jordan, 1990; Barclay and Lupton, 1999; Lupton and Barclay, 1997). While such qualitative studies on mothers and fathers provide us with a much better understanding of the difficulties they experience than the quantitative studies focusing on rates of diagnostic disorders, they do not describe how many women and men experience

Difficulty Coping and Stressors in the First Year Postpartum …

165

different stressors. We do not know, for example, what percentage of new mothers or fathers experience a sense of isolation or family tension in the first year postpartum that they consider contributed to any difficulty they had in coping. In part this is because the studies use small sample sizes, a necessity of qualitative research; in part it may also reflect a philosophy behind qualitative research, that research findings should not be “arrived at by means of statistical procedures or other means of quantification” (Strauss and Corbin, 1990; p.17). There is, however, an argument for reporting both individual’s experiences, as well as the rate at which these events are experienced. By knowing which stressors are commonly reported by new parents, and which are less frequent, we can feed this back to new, or expectant, parents, thereby normalising some experiences. It can also serve to help health professionals plan preventive work. Clearly there will be more demand to address common stressors in postpartum services than infrequent ones; at the same time there needs to be an awareness of the infrequent stressors to ensure that women, and men, do not fall through the net.

Aims of the Study Duration of Episodes This study utilised a survey sent to women and men at 1 year postpartum. The survey aimed to collect data about their beliefs as to the aetiology of any episodes of self-defined distress they had experienced in that first year, as well as their recollection as to the onset and duration of these episodes. As such it is important to emphasise that the parents’ perceptions, and reports, of their distress are not considered equivalent to any diagnostic category, such as major or minor depression.

METHOD Participants English-speaking couples expecting their first child who attended antenatal classes at a public hospital in South West Sydney, Australia, were recruited for the study, the main aim of which was to investigate the effectiveness of a postnatal distress prevention programme (see Matthey, Kavanagh, Howie, Barnett and Charles, 2004). This study followed the couples through the transition to parenthood, with assessments antenatally (at recruitment) and again at 6 weeks and 6 months postpartum, with the Experiences Survey being completed at one year postpartum. Mean age for the women was 27.1 years (S.D. = 4.2) and for the men 29.0 years (S.D. = 4.6). Of the women 48.7% had 11 years of education, and of the men 59.1% had this level of education. A further 21.7% of women and 14.3% of men had a tertiary education qualification (i.e. at least 16 years of education).

166

Stephen Matthey

Measure The ‘Experiences Survey’ was devised by the author. It consisted of five questions: Q1: an open-ended question about what had made becoming a parent enjoyable or easy; Q2: an open-ended question about what had made becoming a parent difficult or unenjoyable; Q3: whether she/he had found it difficult to cope since the baby was born, with five options (‘No’; ‘Yes – for less than a week’; ‘Yes, for between 1 and 2 weeks’; ‘Yes, for a period longer than 2 weeks’ (duration then specified); and ‘Yes, for several periods’ (each duration specified, up to a maximum of three such periods); Q4: If she/he answered ‘yes’ to Q3, to specify how old the baby was when she/he started having difficulty coping (if more than one episode, to document this for each episode); Q5: a checklist of 21 possible stressors that may have contributed to the woman/man feeling stressed. These were based upon the literature, and are subsumed under the categories shown in Table 2. All responses to the open-ended stressors question (Q2) were coded. Two investigators then reviewed these responses, and collapsed them into a smaller number of categories. For example, responses stating that the infant was unsettled, or that there had been feeding difficulties, were grouped into a ‘baby-care’ stressor. Discriminant validity for this measure was determined by analysing diagnostic interview data at six week postpartum.

Procedure The Experiences Survey was mailed at 1 year postpartum to all participants who had responded to the previous assessment at six months postpartum. The surveys were sent separately to the women and men, and each contained a stamped-addressed envelope for return to the research team.

RESULTS Participants From the original sample of 441 couples recruited in pregnancy, 221 women (50%) and 179 men (40.5%) responded to this survey at 12 months postpartum. These represented 71.3% of women and 57.7% of the men who had participated at the six-month assessment point. Some respondents failed to complete all 5 questions on the Experiences Survey. Thirteen women and seven men completed one or other of the open-ended stressor question or checklist question, but not both. Given that the results combine their responses to these two questions, they have been expressed as a percentage of the total surveys received.

Difficulty Coping and Stressors in the First Year Postpartum …

167

Difficulty Coping Table 1 details the percentage of women and men reporting difficulty coping in the first year postpartum. Half of the 23.6% of women, and also of the 9.8% of men, who reported an episode of more than 2 weeks duration stated that this episode started after six weeks postpartum. Table 1. Percentages of Self-Reported Periods of Difficulty Coping in the First Year Postpartum: Difficulty coping category No difficulty coping 1 period for less than 1 week 1 period, between 1 and 2 weeks Several periods, none more than 2 weeks long At least 1 period for more than 2 weeks*

Mothers (N = 221) 26.7 27.1 11.8 10.0 23.6a

Fathers (N = 179) 52.5 22.3 10.6 0 9.8b

Note: Each column does not tally to 100% due to missing data on a few women and men. * Includes those who report several episodes, of which at least one was more than 2 weeks long. a Range 3-52 weeks duration (52 = still ongoing); bRange 4-56 weeks duration (56=still ongoing).

Responses to the Open-Ended Questions and Checklist There were initially over 110 stressors reported by the men and women to the open-ended question. Re-classification of these into categories resulted in 24 stressors being coded. Rates of responses to each category were combined for the open-ended question and the checklist, as shown in Table 2. On one stressor only, that of baby care issues (which includes unsettled behaviour and feeding difficulties), was there a statistically significant difference in the rate between women reporting being distressed for more than 2 weeks and those distressed for 2 weeks or less (91.5% vs 46.8%; χ2 (1,141) = 24.61, p < .001, φ = 0.42). Lacking support approached significance in this comparison (12.8% vs 4.3%; χ2 (1,141) = 2.27, p = .06, φ = 0.13). For men also only one stressor was reported significantly more often by those feeling distressed for more than 2 weeks compared to those feeling distressed for 2 weeks or less that of work-related stress (29.4% vs 8.8%; χ2 (Fisher’s exact) (1, 74) = 4.77, p < .05, φ = 0.21). Cramer’s phi values indicate that these associations range from low (0.1-0.29) to moderate (0.3- 0.49) (Matthey, 1998). Table 2 also shows the significant differences in reported stressors between mothers and fathers.

168

Stephen Matthey Table 2. Rates of Reported Stressors, Combining Responses to the Open-Ended Question and the Checklist: Mothers and Fathers.

Stressor Adjusting to the new situation (including the sense of responsibility) The baby had sleep, settling or feeding difficulties I was exhausted I was trying to do too many household chores Feeling isolated or lonely My baby was ill I lacked confidence in caring for the baby1 Worried about money A lack of support There was tension with family members My health was poor Our marriage was suffering difficulties I was stressed at work2 Someone I loved was very ill or died My partner was having difficulty coping Feeling bored There were problems with the delivery I am prone to feeling depressed anyway My partner’s physical health was poor Worried may be pregnant again Partner’s shopping habits Finding adequate daycare Renovating/moving house Baby growing up too quickly Being a single parent Baby responding to others more than to self Caring for more than 1 child3

φ

Total sample Mothers (N = 221)

Fathers (N = 179)

100 66.2 54.1 29.7 25.7 20.3 19.8 19.4 19.4 16.2 14.4 13.5 11.7 5.4 5.4 5.0 4.1 2.3 0.5 0.5 1.0 1.0 1.0 0.5 0.5 0.5

100 50.3** 36.3*** 6.1*** 3.9*** 17.3 9.5** 22.9 6.7*** 6.1** 6.7* 6.1* 24.6** 4.5 21.2*** 1.7 6.1 1.7 8.4*** 0.5 -

0.16 0.17 0.30 0.30 0.14 0.18 0.16 0.12 0.12 0.17 0.24

0.20

*p < .05; **p < .01; ***p < .001; women vs men (phi values of 0.3 or higher indicate a moderate degree of association - Matthey, 1998) 1 This item only included for a subsample of those surveyed (total N = 91 women and 83 men) 2 The percentage of women that this item applied to (i.e., were working) is not known. 3 While all participants were first-time parents, one mother cared for another child on a regular basis.

LIMITATIONS The checklist component of the Experiences Survey is not a definitive list of all possible stressors that could be experienced by new parents, which in part is why this was preceded by the open-ended stressor question. However, it is accepted that neither method can be sure of capturing all possible stressors that women might acknowledge on a self-report survey. It is likely that face-face in-depth interviews provide a richer understanding of not only the types of stressors, but also how these stressors affect women and men differently. However, as

Difficulty Coping and Stressors in the First Year Postpartum …

169

previously mentioned, by necessity such interviews cannot be undertaken on large samples of women and men. We feel the survey used therefore complements both the qualitative and quantitative research findings of other investigators. That no formal psychometric properties of questions 3 and 4 in the survey have been investigated (eg., test-retest reliability; concurrent validity) is acknowledged as a limitation. The rates of difficulty coping for more than two weeks (23.6% for women; 9.8% for men) should not be compared to diagnostic rates of postnatal depression in other studies, for several reasons. Firstly, this study did not use a diagnostic interview, but a self-report measure of difficulty coping. Secondly, the time frame is different - diagnostically the time frame is 2 weeks or more; in this study we used more than two weeks. Thirdly, only around half the original sample of women and men recruited antenatally responded to this survey at 12 months postpartum – there may therefore be a bias with respect to likelihood of staying in the study and experiences of coping. Fourthly, diagnostic rates tend to only assess depression. This study used whatever the adult considered defined ‘difficulty coping’ - thus it could include concepts such as anxiety and distress. The rationale for this is very much along the lines of those arguing that we need to understand women’s experiences from their perspective (e.g., Mauthner, 1998). Whether or not a woman meets objective diagnostic criteria is not as relevant as whether a woman herself says she is having difficulty coping - it is this latter concept that should determine the offer of help from professionals, and not whether she meets criteria for a mental disorder. The same view also applies to the mental health of men.

DISCUSSION The most frequently cited stressors associated with both women’s and men’s difficulties in coping in the first year postpartum were adjustment to their new situation, sleep, settling or feeding difficulties with their infant, and exhaustion. In addition, a substantial percentage of women (i.e., at least 20%) reported the following stressors: doing too many chores; feeling isolated or lonely; and her infant being sick. For men these other stressors were financial worries, stress at work, and concern for how his partner was coping. In addition, other frequent stressors for women (i.e., 10-19%) included a lack of confidence in caring for the baby, financial concerns, a lack of support, and tension with family members. For men the only additional frequent stressor was the health of his baby. It is interesting that only one stressor was more prevalent for women (baby care issues) and men (work-related) reporting difficulty coping for more than two weeks compared to those with shorter periods of difficulty coping. This lends credence to investigators who believe focusing on women meeting diagnostic criteria for depression may be pathologising their condition. By simply focusing on such women it could be easy to (incorrectly) presume that women not meeting diagnostic criteria do not experience such stressors. As this study shows, this may be a false presumption. Clearly the experience of an event as stressful is an interaction of the event, the person’s personality (e.g., coping style), and the context (e.g., the degree of support he/she receives). Given this, it is not surprising that for nearly all the stressors there is no simple relationship with reported duration of difficulty coping. A similar percentage (40% approximately) of women and men report that the time of onset of an episode of distress that lasted more than two weeks was after six weeks

170

Stephen Matthey

postpartum. This is similar with the study of Brown et al (1994), who found that 55% of their women reported an onset of depression after three months postpartum. The importance of this finding is that much research conducted into rates of postnatal depression is done at 6 weeks postpartum. While self-reported distress is not pnd, this finding would suggest that clinicians and researchers need to keep in mind that it is likely that the onset of significant periods of distress can occur at any time in the first year postpartum. Thus assessing for such conditions at just one time point will likely fail to convey a full picture of women’s experiences. In addition, it points to a need to continue to monitor a woman’s mood during the first year postpartum as she has regular contact with the health services. As new events occur (e.g., teething; introduction of solids), and as environmental contexts may change (e.g., level of support may alter over time), so a mother, and possibly father, may experience a significant episode of difficulty coping. If we become too fixated on screening for distress in mothers only at one time point (e.g., the 6-week postnatal check-up) we are likely to miss the opportunity to offer professional support that may be helpful to the family at other times. In the same way that a recent paper described the rate of expectant mothers’ and fathers’ postpartum concerns during pregnancy (Matthey, Morgan, Healey, Barnett, Kavanagh and Howie, 2002), so this study has documented the rate of reported stressors in a reasonable size sample of first time mothers and fathers in the first year postpartum. It is hoped that this information will prove helpful for clinicians conducting postpartum groups or services focusing on the experiences of new parents.

CONCLUSION This study provides information as to the frequency of stressors in the first year postpartum for both mothers and fathers. Such information should prove useful for preventative services, as well as for parents who may feel reassured that their experiences are also experienced by substantial numbers of other parents. That baby-care stress is associated with longer periods of difficulty coping for women lends support to interventions aimed at reducing infant sleep and settle problems in order to also ameliorate postnatal distress in women (e.g., Hiscock and Wake, 2002). Whether there is a way of impacting on work-related stress for fathers to reduce the longer duration of difficulty coping for them remains to be seen.

ACKNOWLEDGMENTS Prof. Bryanne Barnett This project was funded by a grant from the Commonwealth Department of Health and Family Services (Research section), Australia, and Karitane, Australia.

Difficulty Coping and Stressors in the First Year Postpartum …

171

REFERENCES Barclay, L. and Kent, D. (1998). Recent immigration and the misery of motherhood: a discussion of pertinent issues. Midwifery, 14, 4-9. Barclay, L. M. and Lloyd, B. (1996). The misery of motherhood: alternative approaches to maternal distress. Midwifery, 12, 136-139. Barclay, L. and Lupton, D. (1999). The experiences of new fatherhood: a socio-cultural analysis. Journal of Advanced Nursing, 29, 1013-1020. Barnett, B. E. W., Matthey, S., and Boyce, P. Migration and motherhood: a response to Barclay and Kent (1999). Midwifery, 15, 203-207. Beck, C. T. (1992). The lived experience of postpartum depression: a phenomenological study. Nursing Research, 41, 166-170. Brown, S., Lumley, J., Small, R. and Astbury, J. (1994). Missing voices - the experience of motherhood. Melbourne: Oxford University Press. Creedy, D. and Shochet, I. (1996). Caring for women suffering depression in the postnatal period. Australian and New Zealand Journal of Mental Health Nursing, 5, 13-19. Hiscock, H., and Wake, M. (2002). Randomised controlled trial of behavioural infant sleep intervention to improve infant sleep and maternal mood. British Medical Journal, 324, 1062-1065. Jebali, C. (1993). A feminist perspective on postnatal depression. Health Visitor, 66, 59-60. Jordan, P. L. (1990). Laboring for relevance: expectant and new fatherhood. Nursing Research, 39, 11-16. Lewis, S. E. and Nicolson, P. (1998). Talking about early motherhood: recognizing loss and reconstructing depression. Journal of Reproductive and Infant Psychology, 16, 177-197. Lupton, D. and Barclay, L. (1997). Constructing fatherhood: discourses and experiences. London: Sage Publications. Matthey, S. (1998). p < .05. But is it clinically significant? Practical examples for clinicians. Behaviour Change, 15, 140-146. Matthey, S., Barnett, B., Ungerer, J., Waters, B. (2000). Paternal and maternal depressed mood during the transition to parenthood. Journal of Affective Disorders, 60, 75-85 Matthey, S., Morgan, M., Healey, L., Barnett, B., Kavanagh, D.J. and Howie, P. Postpartum issues for expectant mothers and fathers. (2002). Journal of Obstetrics, Gynecology and Neonatal Nursing, 31, 428-435. Matthey, S., Barnett, B.E.W., Howie, P and Kavanagh, D.J. (2003). Diagnosing postpartum depression in mothers and fathers: whatever happened to anxiety? Journal of Affective Disorders, 74, 139-147. Matthey, S., Kavanagh, D. J., Howie, P., Barnett, B., Charles, M. (2004). Prevention of Postnatal Distress or Depression: An evaluation of an intervention at Preparation for Parenthood classes. Journal of Affective Disorders, 79, 113-126. Mauthner, N. (1993). 1. Towards a feminist understanding of ‘postnatal depression’. Feminism and Psychology, 3, 350-355. Mauthner, N. S. (1998). “It’s a woman’s cry for help”: a relational perspective on postnatal depression. Feminism and Psychology, 8, 325-355.

172

Stephen Matthey

Mauthner, N. S. (1999). "Feeling low and feeling really bad about feeling low": Women's experiences of motherhood and postpartum depression. Canadian Psychology, 40, 143161. Nicolson, P. (1990). Understanding postnatal depression: a mother-centred approach. Journal of Advanced Nursing, 15, 689-695. Nicolson, P. (1999). Loss, happiness and postpartum depression: The ultimate paradox. Canadian Psychology, 40, 162-178. O'Hara, M.W. and Swain, A.M. (1996) Rates and risk of postpartum depression - a metaanalysis. International Review of Psychiatry, 8, 37-54. Strauss, A. and Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage Publications. Ugarriza, D. N. (2002). Postpartum depressed women’s explanation of depression. Journal of Nursing Scholarship, 34, 227-233.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 8

COCAINE-DEPENDENT PATIENTS WITH ANTISOCIAL PERSONALITY DISORDER, COCAINEDEPENDENCE, AND TREATMENT OUTCOMES Nena Messina1, David Farabee and Richard Rawson UCLA Integrated Substance Abuse Programs, USA

ABSTRACT This study compared the efficacy of two commonly used treatment approaches (cognitive–behavioral treatment and contingency management) for the treatment of cocaine dependence among methadone-maintained patients with and without antisocial personality disorder (ASPD). This disorder is strongly associated with substance abuse and recent study findings provide a strong argument against the perception that substance abusers with ASPD are unresponsive to drug treatment. Method: Patients were randomly assigned to four study conditions including cognitive–behavioral treatment (CBT), contingency management (CM), CBT with CM, or methadone maintenance (also the control condition). The Structural Clinical Interview for Mental Disorders–IV was administered to 108 patients to assess ASPD. Hypotheses: We hypothesized that ASPD patients in the three treatment conditions (CBT, CM, CBT + CM) would have better treatment responsivity over the 16-week course of treatment than would ASPD patients in the control condition (MM). Moreover, we hypothesized that there would be a cumulative treatment effect among ASPD patients over the course of treatment, with good performance in the CBT condition, better performance in the CM condition, and optimum performance in the CBT + CM condition. Conversely, we hypothesized that the positive treatment effect of CM would decline for the ASPD patients once the incentive was removed (i.e., during the posttreatment outcome period). Results: A two-way analysis of variance showed that patients with ASPD were more likely to abstain from cocaine use during treatment than patients without ASPD. The 1 Corresponding Author: Nena Messina, Ph.D., 1640 S. Sepulveda Blvd., Suite 200 Los Angeles, CA. 90025, Phone: (310) 445-0874 ext. 335, Fax: (310) 312-0559, [email protected], [email protected], [email protected].

174

Nena Messina, David Farabee and Richard Rawson strong treatment effect for ASPD patients was primarily due to the CM condition. A series of regression analyses showed that ASPD remained significantly related to CM treatment responsivity while controlling for other related factors. Conclusion: Monetary incentives appear to reduce cocaine use among substance abusers with ASPD more than among those without ASPD. The results of the present study and other recent publications suggest that substance abusers with ASPD may be more responsive to treatment than previously believed.

INTRODUCTION Antisocial personality disorder (ASPD) is a personality disorder officially recognized by the American Psychiatric Association and often associated with substance abuse and criminal behavior. The key features of the disorder are outlined in the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, commonly known as the DSM-IV. The essential feature of this disorder is “a pervasive pattern of disregard for, and violation of, the rights of others that begins in childhood or early adolescence and continues into adulthood” (American Psychiatric Association, 1994: 645). Common signs of childhood development of ASPD are lying, stealing, fighting, resisting authority, and cruelty to animals. Aggressive sexual behavior, drinking and drug abuse are common in adolescence. Adult manifestations include illegal behavior, deceitfulness, recklessness, violence, job troubles, and marital difficulties. (For a complete description of ASPD, see Messina, 2002.) Previous research indicates that this disorder is also strongly associated with excessive substance abuse in adulthood, with about 40% to 50% of substance abusers meeting the criteria for ASPD (Messina, Wish, and Nemes, 1999; Tims, DeLeon, and Jainchill, 1994) and approximately 90% of persons diagnosed with ASPD being substance abusers (Gerstley, Alterman, McLellan, and Woody, 1990). In light of the prevalence of ASPD among substance-abusing populations, it became imperative that effective treatment strategies be identified. Thus, the recurring association among ASPD, substance abuse, and crime led to a variety of treatment outcome evaluations for substance abusers with this disorder. Yet, there is a widely held belief among treatment providers that persons with ASPD will not respond well to treatment as a direct result of the symptoms of their disorder (e.g., habitual lying and lack of emotional insight). In fact, treatment providers and therapists alike often state that patients with ASPD will manipulate their therapy for their own self-serving needs (Abram, 1989; Davidson and Neale, 1990; Evans and Sullivan, 1990; Forrest, 1992). As one expert notes: “If it is to their advantage to act cured, they will do so, but they will return to former patterns of behavior at the first opportunity” (Coon, 1983: 465). This belief was substantiated by a frequently cited report that stated that, compared to other types of patients, antisocial opioid abusers responded poorly to both routine drug abuse counseling and specialized psychotherapy (Woody, McLellan, Luborsky, and O’Brien, 1985). Results from more recent studies that have empirically assessed the relationship between ASPD and substance abuse treatment outcomes have not supported the previous findings regarding this disorder and treatment response (Brooner, Kidorf, King, and Stoller, 1998; Gil, Nolimal, and Crowley, 1992; Messina et al., 1999; Silverman et al., 1998). Gil et al. (1992) compared the treatment outcomes of 55 consecutively admitted methadone maintenance patients with ASPD (42%) and those without ASPD. Although the findings were limited by

Cocaine-Dependent Patients with Antisocial Personality Disorder …

175

the small sample and ambiguous design, no significant differences were found between those with and those without ASPD on any 12-month outcome variable (e.g., treatment retention, urine test results, therapy session attendance). It appeared that ASPD patients did as well as those without ASPD in a traditional methadone maintenance program. However, a lack of difference did not necessarily imply good treatment responsivity. The authors reported low overall retention in this sample of clients. Valliant (1975) had previously speculated that structured behavioral programs with incentives for participation might produce the best results for antisocial opioid patients. Evans and Sullivan (1990) also stated that “[it] is highly unlikely that antisocials will develop genuine remorse and altruistic reasons for staying clean and sober. However, they may be interested if it will help them win at poker, make more money, or stay out of jail” (p. 104). Brooner and his colleagues (1998) directly tested Valliant’s hypothesis regarding the use of incentives. Forty opioid abusers with co-occurring ASPD were randomly assigned to an experimental treatment condition combining methadone maintenance and contingency management techniques (i.e., a structural behavioral intervention using rapid delivery of positive and negative contingencies) or a control condition (i.e., standard methadone maintenance). In the experimental condition, take-home methadone doses and dose alterations were contingent on drug-free urine specimens and counseling session attendance. Preliminary findings did not reveal significant differences between the groups; yet, both groups showed marked reductions in heroin and cocaine use during the 17-week outcome evaluation. The authors contend that these findings are not only contrary to what is commonly thought about ASPD clients in traditional methadone treatment, but also about ASPD clients in enhanced methadone (i.e., methadone maintenance combined with contingency management) treatment programs as well. However, this study was limited by a small sample and by the absence of a non-ASPD control group. Other contingency management approaches include giving vouchers that are exchangeable for goods and services in response to drug-free urine specimens. Silverman et al. (1998) compared the treatment responsiveness of 59 methadone maintenance patients with ASPD (19%) and without ASPD who were participating in voucher-based cocaine abstinence reinforcement therapy. Patients were randomly assigned to two levels of voucher-based interventions or a control group in which vouchers were given on a noncontingent basis. The authors found that both contingent interventions significantly increased abstinence from cocaine and opiates, compared with the control group. Moreover, a diagnosis of ASPD was unrelated to treatment outcomes. However, the small sample size (and low prevalence of ASPD) may have rendered any differences in outcomes between substance abusers with ASPD and those without ASPD difficult to detect. Another study explored the relationship of ASPD and treatment outcomes in therapeutic communities (TCs) with random assignment of (primarily cocaine dependent) respondents to two residential programs differing primarily in length (Messina et al., 1999). TCs often rely on cognitive behavioral methods to change existing behavior patterns. Clients diagnosed as having ASPD (n=166) were compared to 172 clients with no ASPD on three outcome measures. After controlling for relevant factors, clients with ASPD were as likely to complete treatment as other clients and they exhibited the same patterns of reduced drug use and criminal activity as did non-ASPD clients. The findings from the above recent studies could indicate that ASPD is not a strong predictor of treatment nonresponsivity, as previously believed.The implications of these

176

Nena Messina, David Farabee and Richard Rawson

findings are important in light of the fact that substance abusers with ASPD are more likely than those without ASPD to engage in violent and serious criminal behaviors (Abram, 1989; Brooner, Schmidt, Felch, and Bigelow, 1992). However, the empirical literature assessing the relationship between ASPD and substance abuse treatment outcomes is lacking, and the existing research is limited by small sample sizes, nonrandom designs, and/or the absence of an appropriate control group. The present study sought to examine the relationship between ASPD and substance abuse treatment responsivity by addressing these primary weaknesses of the literature. This study directly compares the efficacy of two commonly used treatment approaches (cognitive behavioral treatment and contingency management) for the treatment of cocaine dependence among methadone-maintained patients with and without ASPD. These two treatment approaches represent two of the most promising psychological-behavioral approaches for the treatment of substance abuse. However, the rationales for these two approaches differ considerably. Cognitive behavioral treatment (CBT) strategies are based upon social learning principles (Bandura, 1977). These techniques include a wide range of treatment strategies designed to prevent relapse to drug use. The primary focus of CBT is maintaining a habit-changing process. This process is twofold: to prevent the occurrence of initial lapses to drug use after one has embarked on a program of habit change, and to prevent any lapse from escalating into total relapse (Marlatt and Gordon, 1985). Contingency management (CM) techniques, on the other hand, are founded on principles of operant conditioning (Skinner, 1938). The CM techniques create systems of incentives and disincentives to motivate behavior change. Some positive incentive strategies include takehome methadone doses and cash incentives for drug-free urine specimens. One of the most promising applications of CBT and CM is in the area of cocaine abuse treatment. Cocaine abuse continues to be a serious public health problem and is an important factor in drugrelated crime and violence (Everingham and Rydell, 1994). Moreover, cocaine abuse among methadone-maintained patients continues to be a serious challenge for treatment clinicians (Farabee, Rawson, and McCann, 2002; Rawson, Obert, McCann, and Ling, 1991; Silverman, Chutuape, Bigelow, and Stitzer, 1999). Both CBT and CM have been shown to be effective in treating cocaine-dependent patients (Carroll, 1999; Carroll et al., 1994; Farabee et al., 2002; Foote et al., 1994; Marlatt and Gordon, 1985; Silverman et al., 1996; Silverman et al., 1998; Silverman et al., 1999). This study offers an excellent opportunity to compare the relative efficacy of an information-based “talk therapy” (CBT) with a purely operant paradigm (CM) for producing desired behavior change among substance-abusing clients with co-occurring ASPD. Furthermore, this study assesses the relative efficacy of combining these interventions (CBT+CM) for reducing cocaine use among methadone-maintained patients with ASPD. Since all patients are involved in a “platform” condition of methadone maintenance, it is possible to use a study design in which three active cocaine treatment conditions (CBT, CM, and CBT+CM) are compared to a control condition in which patients receive no additional treatment for their cocaine disorder. Because of the limited literature (both in number and design) regarding substance abuse treatment responsivity for ASPD patients, findings are somewhat difficult to interpret. It is possible that group differences within the methadone maintenance studies have not been found because of the low power generated by the insufficient sample sizes. For example, it is likely that Brooner et al. (1998) would have found a significant difference between the ASPD

Cocaine-Dependent Patients with Antisocial Personality Disorder …

177

patients in the experimental (CM) condition and the ASPD patients in the control condition had they used a larger sample. (By our calculations, their preliminary study generated a power of only .07, with an effect size of .15). The ASPD patients in the CM condition had a larger number of drug-free urine specimens, on average, than did the ASPD patients in the control condition. Monetary incentives for cocaine abstinence could be a strong external motivator for patients with ASPD. Monetary incentives combined with drug-relapse education and peer support (i.e., CBT) might prove to be a strong treatment intervention for co-disordered patients. Therefore, we hypothesized that ASPD patients in the three treatment conditions (CBT, CM, CBT+CM) would have better treatment responsivity over the 16-week course of treatment than would ASPD patients in the control condition (i.e., methadone maintenance only). Moreover, we hypothesized that there would be a cumulative treatment effect among ASPD patients over the course of treatment, with good performance in the CBT condition, better performance in the CM condition, and optimum performance in the CBT+CM condition. [CBT] < [CM] < [CBT + CM] Conversely, we hypothesized that the positive treatment effect of CM would decline for the ASPD patients once the incentive is removed (i.e., during the posttreatment outcome period). Because it has been speculated that ASPD patients have little internal motivation, it is reasonable to hypothesize that they will be less likely to remain abstinent in the absence of external incentives. Because the available literature assessing the relationship between ASPD and treatment outcomes is lacking, we also posed the more general research question: Is a diagnosis of ASPD a significant predictor of treatment outcomes?

METHOD The data for this study is from the “Behavioral/Cognitive Behavioral Trial for Cocaine Abuse Project”, a treatment outcome study for methadone-maintained, cocaine-dependent patients. The main treatment outcome report for this project can be found in Rawson et al. (2002). The current chapter focuses on the ASPD diagnosis and its relation to treatment outcomes.

Patients Study participants were volunteers from two licensed narcotic treatment programs in Los Angeles, California (Matrix Institute and West Los Angeles Treatment Program). To be eligible for the study, all candidates were required: (1) to have been on methadone maintenance treatment at one of the two clinics for a minimum of 90 days; (2) to meet DSMIV criteria for cocaine dependence; and (3) to show evidence of cocaine use (cocainemetabolite positive urine sample) during the month prior to study enrollment. Individuals were ineligible if they (1) were also dependent upon alcohol or benzodiazepines to the point

178

Nena Messina, David Farabee and Richard Rawson

of requiring withdrawal medication; (2) if they had received specific treatment for cocaine in the previous 30 days; or (3) if they were court-mandated to treatment. During a 30-month recruitment period, 120 individuals met study eligibility criteria, were enrolled in the study, and were randomly assigned into one of the four study conditions (CBT, CM, CBT+CM, or MM). 2 At admission, slightly more than half (56%) of the sample was male and the mean age was 43. With respect to race/ethnicity, 38% of the sample were White, 31% African American, 28% Hispanic, and 6% “other.” The majority of patients (72%) had completed at least 12 years of school. A small percentage (15%) of the sample reported that they had steady employment over the past 3 years. Among the four conditions, none of the between-group differences in patient characteristics was statistically significant. Similar to the demographic profiles, self-reported prevalence of past-month drug and alcohol use did not vary significantly by study condition.

Procedures Random assignment into one of the four study conditions (30 patients in each condition) took place following informed consent procedures and a 2-week baseline data collection period. Demographic and background information was captured using the Addiction Severity Index (ASI). The ASI is a semi-structured interview instrument used for both clinical and research purposes to determine service needs (McLellan et al., 1992). It is a comprehensive instrument consisting of questions pertaining to demographics, employment, living situation, past and current health status, past and current drug use, past and current drug treatment history, past and current criminal and criminal justice involvement, and past and current mental health status and treatment. The Structural Clinical Interview for Mental Disorders-IV (SCID) was administered during the first 30 days of study participation by a trained masters- or Ph.D.-level staff person to confirm the substance use diagnosis and to determine the presence of ASPD. The SCID is a semi-structured interview for making Axis I and Axis II diagnoses based on DSM-IV criteria (Kranzler, Rounsaville, and Tennen, 1995). SCID interviews were supervised and reviewed by a Ph.D.-level staff member. A total of 108 clients were evaluated by the SCID diagnostic interview and are the focus of this study (12 patients dropped-out of treatment prior to administration of the SCID). Forty-four percent of the target sample met the DSM-IV criteria for ASPD. The frequency of ASPD among the study patients is consistent with other reports on the psychiatric co-morbidity among methadone maintained-individuals (Rounseville, Eyre, Weissman, and Kleber, 1983; Sievewright and Daly, 1997).

2

Only four individuals volunteered for study participation in the first 60 days of recruitment. The two study clinics operated on a fee-for-service basis in which patients paid either $140 (Matrix Clinic) or $180 (West LA Clinic) per month for methadone maintenance treatment services. Only after a $40 per month methadone program fee-reduction was offered as an incentive for study participation did study recruitment become adequate. Thus, the group of individuals who participated in this study can be characterized as having relatively low motivation to stop their cocaine use as defined by the requirement of a $40 per month incentive to encourage study participation.

Cocaine-Dependent Patients with Antisocial Personality Disorder …

179

Treatment Interventions CBT procedures. The CBT procedure consisted of a total of 48 group sessions (3 per week for 16 weeks). Typical groups had four to eight patients. Each group session was scheduled to be 90 minutes in duration, and the material for each session was provided in a workbook. Each workbook presented a concept or a brief written exercise that explained or illustrated an aspect of cognitive-behavioral therapy. This method has been found in previous work by Rawson, Obert, McCann, Smith, and Scheffey (1989) to help stimulant users achieve and maintain abstinence. Many of the concepts were distilled from Marlatt and Gordon (1985) and/or are consistent with the National Institute on Drug Abuse manual on CBT (Carroll, 1999). Each session was led by a master’s level therapist who had received 40-60 hours of supervised training in delivering the materials in a standardized manner. All sessions were audiotaped and reviewed by a counseling supervisor. Feedback was given to the therapist to shape and reinforce consistency. The session format consisted of the topic being introduced by the staff member/group leader, the sheet being read aloud by the leader or a participant volunteer, and group members being given approximately 5 to 10 minutes to discuss the relevance of the topic to him/herself. Those individuals who were unwilling to discuss the topic were allowed to sit and listen. At the end of the topic discussion (typically 45-60 minutes into the session), each individual was asked to discuss his/her drug use/nonuse over the previous time period since the last group. The group leader and other group members verbally reinforced those reporting no use, less use, and/or the initiation of some new prosocial behavior. Finally, each member was asked to describe his/her behavioral plan for the time period leading up to the next session. Plans that included activities based upon the cognitive behavioral principles presented in the treatment groups received praise from the group leader and other members. CM procedures. Patients in the CM-only condition were required to provide three urine samples per week and meet briefly (2-5 minutes) with the CM technician. The meetings with the CM technician covered four topics: (1) a review of the results of the urine test (tested immediately using enzyme multiplied immunoassay tests [EMIT]); (2) the delivery of the appropriate paper voucher certificate, if earned; (3) a discussion of how the voucher or accumulated voucher account could be redeemed; and (4) the delivery of the earned items when the vouchers were redeemed. On occasions when vouchers were earned, the CM technician provided praise and encouragement for successful performance. Patients who provided samples positive for stimulants (there were no contingencies for drug use other than stimulants) were not “scolded” or punished (other than the punishment of withholding the voucher). The voucher value was based upon an escalating schedule that was similar to that used in previous studies (Higgins et al., 1993, 1994). The initial voucher value started at $2.50 per stimulant-negative sample, increasing in value by $1.25 with each successive negative sample, and with a $10 bonus for three consecutive stimulant-negative samples. The maximum voucher value was $46.25 per sample (excluding the $10 bonus). Across the course of the entire 16 weeks, the maximum possible earning (48 consecutive stimulant-free samples) was $1,277.50. Cash was never given to patients. As the voucher account increased in value as a result of stimulant-free urine samples, patients were encouraged to “spend” their savings on items that could support drug-free activities.

180

Nena Messina, David Farabee and Richard Rawson

Patients in all study conditions received identical methadone maintenance (MM) services. The average dose of methadone at baseline was 72 milligrams for the CBT group, 62 milligrams for the CM group, 68 milligrams for the CBT+CM group, and 71 milligrams for the MM-only group. Participation in the study had no effect on the nature of their MM treatment. There were very clear rules for the termination of patients from the study. Termination could be a result of: (1) study completion (16-weeks); (2) missing two consecutive weekly data collection visits; or (3) missing either six consecutive CBT groups or six consecutive urine samples. Therefore, a consistent 2-week absence from protocol participation was the criterion for study termination across all study conditions.

Study Measures The cocaine treatment intervention lasted 16 weeks for all conditions. Cocaine use, as measured by urinalysis, was the principal dependent measure during and after treatment. All study patients were required to give three urine samples per week throughout the 16-week study period and at each of the three follow-up interviews (17, 26, and 52 weeks). All samples were analyzed for metabolites of cocaine (benzoylecognine, BE) and methamphetamine. (Methamphetamine was included as a target along with cocaine to prevent “stimulant switching”; however, the frequency of methamphetamine use in this population was almost nonexistent. Hence, the study findings are specific to cocaine). A 300 ng/ml urinary BE cutoff was used to define a positive sample. All samples were analyzed on-site using EMIT (SYVA) reagent test procedures. All samples were monitored (i.e., collected in bottles equipped with temperature strips, and the bathrooms where samples were collected did not have hot water to prevent tampering). In addition, approximately 33% of all samples were collected under observation. Observation of urine specimens was conducted on a random basis. All subjects were breath alcohol tested at the time of the collection of each urine sample. Follow-up urine specimens were analyzed for cocaine, methamphetamine, metabolites of illicit opiates, benzodiazepines, barbiturates, and cannabinoids. Ninety percent of the sample provided urine specimens at the 17-week follow-up, 83% provided specimens at the 26-week follow-up, and 83% provided specimens at the 52-week follow-up. There were no significant differences in follow-up rates between those with and those without ASPD across the four study conditions at any of the follow-up periods (percentages shown below). •

•

17-Week Follow-Up: Non-ASPD CBT = 86%; ASPD CBT = 93%; Non-ASPD CM = 92%; ASPD CM = 93%; Non-ASPD CBT+CM = 89%; ASPD CBT+CM = 100%; Non- ASPD control = 87%; ASPD control = 83%. 26-Week Follow-Up: Non-ASPD CBT = 79%; ASPD CBT = 93%; Non-ASPD CM = 83%; ASPD CM = 87%; Non-ASPD CBT+CM = 89%; ASPD CBT+CM = 86%; Non-ASPD control = 73%; ASPD control = 75%.

Cocaine-Dependent Patients with Antisocial Personality Disorder …

181

Table 1. Sample Characteristics at Admission, by ASPD Status (N = 108)

Characteristics

Gender Male Female Race/Ethnicity White Black Hispanic/Other

Mean Age at Admission (SD) Education Less than 12 years High-school Degree or more Full Time Employment Past 3 Years

No ASPD (N = 60) %

ASPD (N = 48) %

Total (N = 108) %

43** 57 100%

71** 29 100%

56 44 100%

43 40** 17 100%

31 21** 48 100% 1

38 31 31 00%

43.7 (7.6)

43.5 (8.1)

43

18* 82 100%

40* 60 100%

28 72 100%

17

13

15

23 20 32 25 100%

29 31 15 25 100%

26 25 24 25 100%

Study Condition CBT CM CBT+CM MM *p < .05. **p < .01.

Data Analysis The distribution of demographic and drug-use characteristics by ASPD status was evaluated using chi-square analysis and t-tests. Similarly, the distribution of SCID-I and II diagnoses across study conditions was evaluated by chi-square analysis. In-treatment cocaine use measures were analyzed using a Two-Way Analysis of Variance (ANOVA). To control for inflated alpha error, Tukey-Kramer tests were used for all post hoc comparisons. In addition, a series of regression analyses were conducted to assess in-treatment cocaine use while controlling for pre-existing differences between those with and those without ASPD. To assess cocaine and heroin use following treatment, separate chi-square analyses were conducted for those with and those without ASPD at each of the follow-up time periods. All statistical tests were considered significant at p ≤ .05 and were two-tailed.

182

Nena Messina, David Farabee and Richard Rawson

RESULTS Demographic characteristics for ASPD and non-ASPD patients were similar across the four study conditions; however, small cell sizes limited reliable statistical inference. Although patients were randomly assigned to the study conditions, they were not randomly assigned by ASPD diagnosis. To further explore any pre-existing differences, all ASPD patients were compared with all non-ASPD patients with regard to their demographic and drug use characteristics. Table 2. Self-Reported Drug/Alcohol Use 30 Days Prior to Admission, by ASPD Status (N = 108) No ASPD (N = 60) %

ASPD (N = 48) %

Total (N = 108) %

Alcohol Use

57

60

58

Alcohol Use to Intoxication

23

35

29

Marijuana

30

27

29

Heroin Use

58*

79*

68

Other Opiates

08**

31**

18

Cocaine Use

100

98

99

03

08

06

Substance Use 30 Days Prior to Admission

Amphetamines

Table 3 SCID-I and II Diagnoses, by Study Condition (N = 108)a

Diagnosesb

CBT (N=28) %

CM CBT+CM (N=27) (N=26) % %

SCID-I Substance Use Disorder 100 100 100 Mood Disorder 18 33 23 Anxiety Disorder 18 37 27 SCID-II Antisocial Personality Disorder (ASPD) 50 56 27 All Diagnoses Substance Use Disorder Only 29 23 50 Substance Use and Other Axis I Disorders 21 22 23 Substance Use and ASPD 36 22 12 Substance Use, ASPD, and 33 15 Other Axis I Dis. 14 100% 100% 100% a N’s vary slightly due to missing data. b Only diagnoses prevalent in 5% or more of the sample are shown. Note. Differences are not significant.

MM (N=27) %

Total (N=108) %

100 19 19

100 23 25

44

44

36

34

19 26

21 24

19 100%

21 100%

Cocaine-Dependent Patients with Antisocial Personality Disorder …

183

Consistent with previous literature, patients diagnosed with ASPD were significantly more likely to be male (71% vs. 43%, p < .01) and to have less than a high school education (40% vs. 18%, p < .05) than non-ASPD patients (see Table 1). With regard to ethnicity, patients with ASPD were significantly more likely than non-ASPD patients to be Hispanic (48% vs. 17%, p < .01). No significant differences between those with and those without ASPD were found with regard to age or employment, and patients with ASPD were equally distributed among the study conditions. Comparisons of demographic characteristics of ASPD-patients only across the four study conditions were also conducted. No significant differences were found with regard to age, gender, race/ethnicity, or high school education (results are not shown). Table 2 displays the self-reported drug and alcohol use patterns by ASPD status during the 30 days prior to study admission. Those with ASPD were significantly more likely to have used heroin (79% vs. 58%, p < .05) and other opiates (31% vs. 8%, p < .01) during this time period, than non-ASPD patients. No other substance-use differences were found. Cocaine (99%) and heroin (68%) were most likely to be used during the 30 days prior to study admission, followed by alcohol (58%), marijuana (29%), other opiates (18%), and amphetamines (6%). Table 3 displays the prevalence of ASPD, substance use disorder, and other SCID-I psychiatric disorders by study condition. Only those diagnoses prevalent in more than 5% of the sample are shown. There were no significant differences among the four study conditions with regard to prevalence of psychiatric disorders. All subjects met the criteria for substance use disorder and almost half (44%) had co-occurring ASPD. Of those evaluated by the SCID, 34% had no disorders other than substance use, 21% had substance use and other Axis I disorders, 24% had substance use with co-occurring ASPD, and 21% had substance use disorder, co-occurring ASPD, and other Axis I disorders. (All analyses combine clients with substance use disorder only and those with other Axis I disorders into the non-ASPD group.)

In-Treatment Performance Treatment retention. Treatment retention is frequently an important outcome indicator and is sometimes used as one measure of treatment efficacy. In this study, the value of treatment retention as a dependent measure was compromised by the necessity to reduce patients’ monthly methadone program fees by $40 to promote study enrollment. Therefore, not surprisingly, there was no significant difference in study retention for patients with and those without ASPD across four study conditions. The average number of weeks in treatment for the ASPD group was 14.7 (SD = 3.4), ranging from 12 to 16. The average number of weeks in treatment for the non-ASPD group was 13.2 (SD = 4.9), ranging from 10 to 15 weeks. Cocaine-abstinence during treatment. The primary dependent measure in this study was cocaine use as measured by urine toxicology. Since retention in treatment was not significantly different for those with and without ASPD across study conditions, the most direct measure of cocaine use across the 16 weeks of the trial was the number of cocainenegative urine samples given by each participant during their 48 opportunities to give samples (3 times per week for 16 weeks). There were no significant differences between those with

184

Nena Messina, David Farabee and Richard Rawson

and those without ASPD across the four study conditions with regard to the rates of missing urines. Table 4. Treatment Effectiveness Scores for In-Treatment Cocaine-Free Urine Samples, by Study Condition and ASPD Status ASPD Status

CBT

CM*

CBT+CM

MM

No ASPD Mean TES for Cocaine (s.d)

17.6 (17.9)a

25.5 (20.7)a

24.2 (21.1)a

14.5 (16.9)a

24.8 (15.6)a

39.4 (11.4)b

37.7 (13.3)ab

9.3 (11.3)c

ASPD Mean TES for Cocaine (S.D.)

Note. Subscripts represent the results of pairwise comparisons between study conditions; means that do not have a subscript in common are significantly different from each other (p < .05). *The CM condition was the only condition with a significant difference between those with and without ASPD (p < .05).

A Two-Way ANOVA was performed to determine differences in the mean number of cocaine-negative samples (CNS) provided by ASPD status and by study condition. The possibility of an interaction effect (ASPD status X study condition) was also explored. We initially asked if ASPD would be a significant predictor of in-treatment responsivity. There was a significant main effect for ASPD status. The mean number of CNS for patients with ASPD (CNS = 27.4, SD = 17.5) was significantly higher than the mean number of CNS for those without ASPD (CNS = 20.5, SD = 19.4) [F (1,107) = 4.74, p < .05), suggesting that ASPD patients performed better during the 16-week treatment course than non-ASPD patients. However, there was no interaction effect between ASPD status and study condition. We also hypothesized that ASPD patients in the three cocaine treatment conditions (CBT, CM, CBT+CM) would have better outcomes than ASPD patients in the control condition (MM). This hypothesis was supported. Pairwise comparisons of the mean number of CNS indicated that ASPD patients in each of the treatment conditions had significantly higher scores than those in the control condition (CBT = 24.8; CM = 39.4; CBT+CM = 37.7; vs. MM = 9.3, p < .05). The same pattern was found among the study conditions for the nonASPD group, but differences were not statistically significant (see Table 4). The above findings indicate that ASPD patients responded positively to the three cocaine treatment conditions; however, we also hypothesized a cumulative treatment effect for ASPD patients, with optimum performance in the CBT+CM condition (CBT< CM < CBT+CM). This hypothesis was not supported. Pairwise comparisons did show that the mean number of CNS for the ASPD patients in the CM condition was significantly higher than the mean number of CNS for the ASPD patients in the CBT-only condition (CBT = 24.8 vs. CM = 39.4, p < .05). However, no differences were found for the ASPD patients in the CBT+CM condition compared with the ASPD patients in the CM or CBT-only groups (shown in Table 4).

Cocaine-Dependent Patients with Antisocial Personality Disorder …

185

45 40

Mean CNS

35 30 ASPD

25

Non-ASPD

20

p<.05

15 10 5 0 CBT

CM

CBT+CM

MM

Study Conditions

Figure 1.: Cocaine-Negative Specimens Provided During Treatment (N=108).

Moreover, ASPD patients in the CM condition performed significantly better than the non-ASPD CM patients (ASPD/CM CNS = 39.4 vs. non-ASPD/CM CNS = 25.5, p < .05). The differences in CNS means were not significant for ASPD and non-ASPD patients in any of the other study conditions (shown in Figure 1). The above bivariate analyses, however, do not take into account pre-existing differences between those with and without ASPD that might be related to in-treatment performance. Initially, no demographic differences were found between those with and those without ASPD in any of the treatment conditions; however, when we compared all of the ASPD patients with all of the non-ASPD patients (see Tables 1 and 2), some pre-existing differences were evident (i.e., gender, race, high school education, and opiate use). Therefore, we decided to further explore the association of ASPD with CM treatment using multivariate analyses. Because the total number of patients in the CM condition fell below 30, we were limited in the number of independent variables (or predictors) that could be included in the multivariate analyses (Keppel, 1991). Thus, we conducted a series of regressions pairing ASPD with each of the above characteristics. In all of these pairings, a diagnosis of ASPD remained significantly related to the mean number of CNS (p<.01). We further confirmed the lack of an association of ASPD to in-treatment performance among the other study conditions (analyses not shown).

Post-Treatment Performance Cocaine urinalysis results for ASPD patients at each follow-up period. We hypothesized that the positive treatment effect of CM would decline for the ASPD patients once the incentives were removed (i.e., no vouchers were given during the posttreatment outcome periods). This hypothesis was not supported. ASPD patients in the CM conditions continued

186

Nena Messina, David Farabee and Richard Rawson

to abstain from cocaine use throughout the three follow-up time periods. Figure 2 shows that ASPD patients in the CM-only condition were as likely as those in the other study conditions to have cocaine-free urine specimens at weeks 17, 26, and 52. In fact, over 70% of the CMonly group provided cocaine-free specimens at each follow-up time period. Overall, differences in percentages of cocaine-free specimens between the treatment groups and the control group were not significant at weeks 17 and 26. However, percentages were significantly different at week 52, indicating that between 65% and 80% of the ASPD patients in any of the three treatment conditions were abstaining from cocaine use at the 52-week follow-up period, compared to 20% in the control condition (p < .05). 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

CBT CM CBT+CM MM

17-Week

26-Week

52-Week (p<.05)

Follow-Up Time Periods Figure 2. Cocaine-Free Urine Specimens During Follow-Up [ASPD Patients].

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

CBT CM CBT+CM

17-Week

26-Week

52-Week

Follow-Up Time Periods Figure 3. Cocaine-Free Urine Specimens During Follow-Up [Non-ASPD Patients].

Cocaine-Dependent Patients with Antisocial Personality Disorder …

187

100 90 80 70 60

58.3

CM

50

CBT+CM

40 30 20

CBT

40 30 25 22.2 18.2

MMTP

30.8

10 0

0 Non-ASPD

ASPD (p<.05)

Figure 4. Percentage of Cocaine-Free Urine Specimens at All Three Follow-Up Periods (N=91).

Cocaine urinalysis results for non-ASPD patients at each follow-up period. The rates of cocaine abstinence for the non-ASPD patients did not follow the same trends as those for the ASPD patients. Figure 3 shows that the percentages of cocaine-free specimens were similar across the four study groups for each follow-up time period (i.e., no significant differences were found). However, the CBT-only group was the only treatment group that showed substantial increases in abstinence over the three follow-up time periods (33%, 64%, and 81% respectively). Post-treatment responsivity. To assess overall differences in posttreatment performance between those with and those without ASPD, we created a posttreatment responsivity measure that totaled the percentages of patients who had cocaine-free urine specimens at all three of the follow-up periods. Figure 4 shows the posttreatment results by study condition for those with and those without ASPD. Among non-ASPD patients, there were no significant differences in cocaine negative specimens at each of the three follow-up time periods. In contrast, the ASPD patients in the three cocaine treatment conditions showed large differences in continued abstinence from cocaine compared with those in the control condition (p < .05). Over half of the ASPD patients in the CM-only condition had cocainefree urine results at each follow-up interview (58%), followed by those in the CBT+CM condition (40%), and those in the CBT-only condition (31%). None of the MM-only group had three consecutive cocaine-free urine results. Because the posttreatment findings regarding cocaine use were not as expected, we explored the possibility that ASPD patients were more likely than non-ASPD patients to be using heroin at the follow-up time periods. These results are shown below.

188

Nena Messina, David Farabee and Richard Rawson

100% 90% 80% 70% CBT

60%

CM

50%

CBT+CM

40%

MM

30% 20% 10% 0% 17-Week

26-Week

52-Week

Follow-Up Time Periods

Figure 5. Heroin-Free Urine Specimens During Follow-Up [ASPD Participants].

Post-treatment heroin urinalysis results. Overall, study patients were less likely to abstain from heroin use, compared to cocaine use, at the three follow-up time periods regardless of treatment group or ASPD status (see Figures 5 and 6). However, abstinence rates were not trivial. At the 26-week follow-up, between 40% and 50% of the ASPD patients tested negative for heroin, whereas between 50% and 60% of the non-ASPD patients tested negative for heroin. In addition, non-ASPD patients in the CBT-only condition were significantly more likely to abstain from heroin at the 17-week follow-up compared with those in the other treatment conditions (CBT = 75% vs. CM = 36% vs. CBT+CM = 35% vs. MM = 23%, p < .05). 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

CBT CM CBT+CM MM

17-Week (p=.05)

26-Week

52-Week

Follow-Up Time Periods

Figure 6. Heroin-Free Urine Specimens During Follow-Up[Non-ASPD Participants].

Cocaine-Dependent Patients with Antisocial Personality Disorder …

189

Post-treatment heroin urinalysis results. Overall, study patients were less likely to abstain from heroin use, compared to cocaine use, at the three follow-up time periods regardless of treatment group or ASPD status (see Figures 5 and 6). However, abstinence rates were not trivial. At the 26-week follow-up, between 40% and 50% of the ASPD patients tested negative for heroin, whereas between 50% and 60% of the non-ASPD patients tested negative for heroin. In addition, non-ASPD patients in the CBT-only condition were significantly more likely to abstain from heroin at the 17-week follow-up compared with those in the other treatment conditions (CBT = 75% vs. CM = 36% vs. CBT+CM = 35% vs. MM = 23%, p < .05).

CONCLUSION Recent findings of successful treatment outcomes for methadone-maintained patients with ASPD provides a strong argument against the perception that substance abusers with ASPD are unresponsive to drug treatment (Brooner et al., 1998; Gil et al., 1992; Silverman et al., 1998). However, these studies have been limited by small sample sizes and ambiguous designs. The current study sought to overcome the limitations of the previous research. The primary goal of this study was to determine the efficacy of two commonly used treatment approaches, separately and combined, for the treatment of cocaine dependence in methadonemaintained patients with co-occurring ASPD.

In-Treatment Responsivity Three major trends of in-treatment responsivity are evident. First, in contrast to previous findings (and beliefs), we found that a diagnosis of ASPD was significantly and positively related to treatment responsivity. Those with ASPD were more likely to abstain from cocaine use during treatment than those without ASPD. Second, ASPD patients in each of the treatment conditions performed significantly better than ASPD patients in the control condition, whereas no differences in performance by study condition were found for the nonASPD patients. Third, the strong treatment effect for ASPD patients was primarily due to the CM condition. During the 16-week course of treatment, those in the CM condition were significantly more likely to abstain from cocaine use than those in the CBT-only condition. In contrast, abstinence levels in the combined treatment group (CBT+CM) fell between the CBT- and CM-only levels and did not differ significantly from either. Furthermore, ASPD patients in the CM condition were significantly more likely to abstain from cocaine use than non-ASPD patients in the CM condition, even after controlling for pre-existing differences. As earlier theorists hypothesized (Evans and Sullivan, 1990; Valliant, 1975), monetary incentives appear to be a successful treatment intervention for reducing cocaine use among substance abusers with co-occurring ASPD, and a more successful intervention than for those without ASPD. Furthermore, patients with ASPD responded significantly better to this type of intervention than ASPD patients in “talk-based therapy.” The larger question, however, was whether the positive treatment effects of the CM intervention would continue beyond the course of treatment, once the incentive was removed.

190

Nena Messina, David Farabee and Richard Rawson

Post-Treatment Responsivity Four major results are evident from our posttreatment outcomes. First, and contrary to our hypothesis, ASPD patients in the CM conditions continued to abstain from cocaine use throughout the three follow-up periods. Although differences in cocaine abstinence between the groups were not significant, ASPD patients in the CM conditions appeared to maintain the highest levels of posttreatment cocaine abstinence. In addition, comparable numbers of ASPD and non-ASPD patients were abstaining from heroin at the follow-up time periods. Second, ASPD patients in all three treatment conditions were significantly more likely to abstain from cocaine use at the 52 week follow-up than those in the control condition. Third, a clear pattern of posttreatment performance between the treatment groups was not evident for the nonASPD patients. Non-ASPD patients in the CM conditions appeared to do well at the first follow-up, but their performance declined substantially during the remaining follow-up periods. In contrast, non-ASPD patients in the CBT-only group were the only treatment group whose performance increased over the follow-up time periods. And fourth, ASPD patients in each of the treatment conditions were significantly more likely to test negative for cocaine at all three of the follow-up periods than those in the MM-only condition, whereas no differences were found for non-ASPD patients. Most importantly, ASPD patients in the CM condition were twice as likely as non-ASPD patients in the CM condition to have negative urine test results for cocaine at all follow-up periods. These findings provide a strong argument against the perception that substance abusers with ASPD are unresponsive to drug treatment. Consequently, these findings are important in light of treatment program exclusionary criteria and current public policy. Many substance abuse treatment programs across the nation exclude persons with ASPD on the assumption that they will not respond well to treatment efforts (Messina et al., 1999). Furthermore, a diagnosis of ASPD is among the exclusionary criteria for Maryland’s newly constructed Public Mental Health System, and ASPD is the only personality diagnosis deemed untreatable within this system of health service delivery (Brooner et al., 1998). The results of the present study and other recent publications suggest that substance abusers with ASPD may be more responsive to treatment than previously believed.

Study Strengths The primary strength of our study was the rigorous study design. Random assignment of patients across study conditions created comparable groups. As a result, any differences between group performance tend to reflect the effect of the treatment intervention, rather than error variance (Bordens and Abbott, 1991). Random assignment also eliminated the issue of self-selection, which can be affected by such client attributes as personal motivation, perception of treatment modality, and treatment availability (Hser, 1995). In addition, the “platform” condition of methadone maintenance made it possible to use a study design with a true control condition. Another strength of our study was the high prevalence rate of ASPD (45%), which is similar to other estimates of ASPD among methadone-maintained patients (ranging from 25% to 54%; Rounsaville, Eyre, Weissman, and Kleber, 1983). The high prevalence of this disorder within our sample allowed us to make comparisons of ASPD patients across study

Cocaine-Dependent Patients with Antisocial Personality Disorder …

191

conditions, as well as between those with and those without ASPD. Thus, we were able to assess the treatment responsivity of ASPD patients in each treatment condition and compare their performance to those without ASPD. The use of objective measures of drug use to assess treatment outcomes was an additional strength of this study. Self-reported drug use may be considerably less valid than previously reported (Messina, Wish, Nemes, and Wraight, 2000). For example, Wish, Hoffman, and Nemes (1997) found that among substance-abusing populations, clients were more likely to truthfully report heroin use than cocaine use. The authors further suggest that self-reports may be less valid at follow-up than at intake.

Study Limitations Some limitations of this study should also be kept in mind when interpreting the results. The primary limitation is the sample size. Although our study had a larger sample than previous research among methadone-maintained patients, our posttreatment comparisons were limited by small cell sizes due to the four study conditions. However, we were able to improve power as compared to our calculations for Brooner’s (1998) study. (Power calculation for our study =.47, effect size = .37; power calculation for Brooner = .07, effect size = .15). Another limitation of this study (and others) is the existence of other psychiatric disorders among the sample. Patients with and without ASPD may have been diagnosed with various other psychiatric disorders. It is difficult to know the degree to which the various combinations of other disorders confounded the distinction between those with and those without ASPD, or if the presence of additional psychiatric disorders in patients with ASPD moderates the effect of the ASPD diagnosis on treatment response. However, recent findings from a large sample of methadone-maintained patients (N = 518) demonstrated minor differences between patients with ASPD only and patients with ASPD and other psychiatric disorders (King, Kidorf, Stoller, Carter, and Brooner, 2001). ASPD-only patients exhibited higher rates of heroin use during treatment, whereas ASPD patients with additional disorders exhibited higher rates of benzodiazepine use. No differences between the two groups were found for cocaine use during treatment. An additional roadblock facing those who study and treat ASPD is the lack of agreement about a basic definition and the use of different definitions. There is much controversy among social scientists and clinicians over the proper measurement of ASPD among substance abusers. Although social scientists most often use diagnostic interviews that follow DSM-IV criteria to assess ASPD (such as the SCID-II), many have raised concerns about possible limitations of the DSM (Messina, Wish, Hoffman, and Nemes, 2001). It has been suggested that the DSM criteria for ASPD focus on behavioral characteristics instead of underlying personality traits and do not require that ASPD occur independently of substance abuse (Gerstley et al., 1990). Rounsaville et al. (1983) suggest that clients whose antisocial activities are independent of the need to obtain drugs are “primary antisocial addicts” and those whose antisocial activities are directly related to drug use are “secondary antisocial addicts.” The authors speculated that secondary antisocial addicts might have better treatment responses. If most of our sample members were secondary antisocial addicts, it could account for their more positive treatment outcomes.

192

Nena Messina, David Farabee and Richard Rawson

Summary The relationships between ASPD, substance abuse, and crime is the nexus of a major social problem and understanding the interactions among these patterns of behavior will help identify the individuals and groups who most need effective intervention. The findings from the current study and other recent literature indicate that substance abusers with co-occurring ASPD can benefit from drug treatment programs. Furthermore, methadone-maintained ASPD patients participating in CM interventions show substantial reductions in cocaine use beyond the intervention period. It is therefore suggested that treatment programs make efforts to attract and retain substance abusers with a diagnosis of ASPD. Future research should continue to explore the many issues surrounding the diagnosis of ASPD, as well as its relationship to treatment outcomes.

ACKNOWLEDGMENTS We are grateful to the staff and the patients at the Matrix Institute and the West Los Angeles Treatment Program for their participation. We would like to thank Alice Huber, Christie Thomas, Vikas Gulati, Al Hasson, and Michael McCann for their assistance with the conduct of this study.

REFERENCES American Psychiatric Association (APA). (1994). Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). Washington, DC. Abram, K. M. (1989). The effect of co-occurring disorders on criminal career: Interaction of antisocial personality, alcoholism, and drug disorders. International Journal of Law and Psychiatry, 12, 133-148. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191-215. Bordens, K., and Abbott, B. (1991). Research design and methods: A process approach (2nd Ed.). Mountain View, CA: Mayfield Publishing Company. Brooner, R., Kidorf, M., King, V., and Stoller, K. (1998). Preliminary evidence of good treatment response in antisocial drug abusers. Drug and Alcohol Dependence, 49, 249260. Brooner, R., Schmidt, C., Felch, L., and Bigelow, G. (1992). Antisocial behavior of intravenous drug abusers: Implications for diagnosis of antisocial personality disorder. American Journal of Psychiatry, 149, 482-487. Carroll, K. (Ed.) (1999). A cognitive-behavioral approach: Treating cocaine addiction. Therapy Manuals for Drug Addiction. Rockville, MD: National Institute on Drug Abuse, U.S. Department of Health and Human Services, National Institutes of Health. Carroll, K.M., Rounsaville, B.J., Nich, C., Gordon, L.T., Wirtz, P.W., and Gawin, F.H. (1994). One year follow-up of psychotherapy and pharmacotherapy for cocaine

Cocaine-Dependent Patients with Antisocial Personality Disorder …

193

dependence: Delayed emergence of psychotherapy effects. Archives of General Psychiatry, 51, 989-997. Coon, Dennis. (1983) Introduction to Psychology: Exploration and Application. 3rd ed. Los Angeles: West Publishing Company. Davison, G. C., and Neale, J. M. (1990). Abnormal psychology (5th ed.). New York: Wiley and Sons. Evans, K., and Sullivan, J. (1990). Dual diagnoses: Counseling mentally ill substance abusers. New York: The Guilford Press. Everingham, S., and Rydell, C. (1994). Modeling the demand for cocaine. Santa Monica, CA: RAND. Farabee, D., Rawson, R., and McCann, M. (2002). Adoption of drug avoidance activities among patients in contingency management and cognitive-behavioral treatments. Journal of Substance Abuse Treatment, 23, 343-350. Foote, J., Seligman, M., Magura, S., Handelsman, L., Rosenblum, A., Lovejoy, M., Arrington, K., and Stimmel, B. (1994). An enhanced positive reinforcement model for the severely impaired cocaine abuser. Journal of Substance Abuse Treatment, 11(6), 525539. Forrest, G. G. (1992). Chemical dependency and antisocial personality disorder: Psychotherapy and assessment strategies. New York: The Hawthorne Press. Gerstley, L. J., Alterman, A. I., McLellan, A. T., and Woody, G. E. (1990). Antisocial personality disorder in patients with substance abuse disorders: A problematic diagnosis? American Journal of Psychiatry, 147(2), 173-178. Gil, K., Nolimal, D., and Crowley, T. (1992). Antisocial personality disorder, HIV risk behavior and retention in methadone maintenance therapy. Drug and Alcohol Dependence, 30(3), 247-252. Higgins, T., Budney, J., Bickel, K., Foerg, F., Donham, R., and Badger, J. (1994). Incentives improve outcome in outpatient behavioral treatment of cocaine dependence. Archives of General Psychiatry, 51(7), 568-576. Higgins, T., Budney, J., Bickel, K., Hughes, R., Foerg, F., and Badger, J. (1993). Achieving cocaine abstinence with a behavior approach. American Journal of Psychiatry, 150, 763769. Hser, Y. (1995). Drug treatment counselor practices and effectiveness: An examination of literature and relevant issues in a multilevel framework. Evaluation Review, 19(4), 389408. Keppel, G. (1991). Design and analyses: A researcher’s handbook. Prentice Hall: Englewood Cliffs, New Jersey. King, V., Kidorf, M., Stoller, M., Carter, J., and Brooner, R. (2001). Influence of antisocial personality subtypes on drug abuse treatment response. Journal of Nervous and Mental Disease, 189, 593-601. Kranzler, H., Rounsaville, B., and Tennen, H. (1995). Validity of the SCID in substance abuse patients (NIDA Research Monograph, 2, 35). Rockville, MD: National Institute on Drug Abuse. Marlatt, G. and Gordon, J. (Eds.). (1985). Relapse prevention: Maintenance strategies in the treatment of addictive behaviors. New York: Guilford Press.

194

Nena Messina, David Farabee and Richard Rawson

McLellan, A.T., Kushner, H., Metzger, D., Peters, R., Smith, I., Grissom, G., Pettinati, H., and Argeriou, M. (1992). The fifth edition of the Addiction Severity Index. Journal of Substance Abuse Treatment, 9, 199-213. Messina, N. (2002). The antisocial personality. In Levinson, D. (Ed.). Encyclopedia of Crime and Punishment, vol.1. Great Barrington, Mass.: Berkshire Reference Works. Messina, N., Wish, E., Hoffman, J., and Nemes, S. (2001). Diagnosing antisocial personality disorder among substance abusers: The Structured Clinical Interview for the DSM-III-R versus the Millon Clinical Multiaxial Inventory. The American Journal of Drug and Alcohol Abuse,27(4), 699-717. Messina, N., Wish, E., and Nemes, S. (1999). Therapeutic community treatment for substance abusers with antisocial personality disorder. Journal of Substance Abuse Treatment, 17(12), 121-128. Messina, N., Wish, E., Nemes, S., and Wraight, B. (2000). Correlates of underreporting of post-discharge cocaine use among therapeutic community clients. Journal of Drug Issues, 30(1), 119-132. Rawson, R., Huber, A., McCann, M., Shoptaw, S., Farabee, D., Reiber, C., and Ling, W. (2002). A comparison of contingency management and cognitive-behavioral approaches for cocaine dependent methadone maintained individuals. Archives of General Psychiatry, 59, 817-824. Rawson, R., Obert, J., McCann, M., and Ling, W. (1991). Psychological approaches to the treatment of cocaine dependency. Journal of Addictive Diseases, 11, 97-120. Rawson, R., Obert, J., McCann, M., Smith, P., and Scheffey, H. (1989). The neurobehavioral treatment manual, Matrix. Beverly Hills, CA. Rounsaville, B., Eyre, S., Weissman, M., and Kleber, H. (1983). The antisocial opiate addict. In B. Stimmeo (Vol. Ed.). Psychosocial constructs: Alcoholism and substance abuse, (pp. 29-43). New York: Hawthorne Press. Skinner, B. (1938). The behavior of organisms: An experimental analysis. Englewood Cliffs, NJ: Prentice-Hall. Seivewright, N., and Daly, C. (1997). Personality disorder and drug use: A review. Drug and Alcohol Review, 16, 235-250. Silverman, K., Chutuape, M.A., Bigelow, G., and Stitzer, M. (1999). Voucher-based reinforcement of cocaine abstinence in treatment-resistant methadone patients: Effects of reinforcement magnitude. Psychopharmacology, 146, 128-138. Silverman, K., Higgins, S., Montoya, I., Cone, E., Schuster, C., and Preston, K. (1996). Sustained cocaine abstinence in methadone maintenance patients through voucher-based reinforcement therapy. Archives of General Psychiatry, 53, 409-415. Silverman, K., Wong, C., Umbricht-Schneiter, A., Montoya, I., Schuster, C., and Preston, K. (1998). Broad beneficial effects of cocaine abstinence reinforcement among methadone patients. Journal of Consulting and Clinical Psychology, 66(5), 811-824. Tims, F. M., DeLeon, G., and Jainchill, N. (Eds.). (1994). Therapeutic community: Advances in research and application (NIDA Research Monograph No.144). Rockville, MD: National Institute on Drug Abuse. Valliant, G. (1975). Sociopathy as a human process: A viewpoint. Archives of General Psychiatry, 32, 178-183. Wish, E., Hoffman, J., and Nemes, S. (1997). The validity of self-reports of drug use at treatment admission and at follow-up: Comparisons with urinalysis and hair assays. In L.

Cocaine-Dependent Patients with Antisocial Personality Disorder …

195

Harris (Ed.), The validity of self-reports: The implications for survey research (NIDA Research Monograph No. 167, pp. 200-225). Rockville, MD: National Institute on Drug Abuse. Woody, G., McLellan, A.T., Luborsky, L, and O’Brien, C. (1985). Sociopathy and psychotherapy outcome. Archives of General Psychiatry, 42, 1081-1086.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 9

CHILDHOOD SEXUAL ABUSE AND BORDERLINE PERSONALITY DISORDER Randy A. Sansone1 and Lori A. Sansone Departments of Psychiatry and Internal Medicine at Wright State University School of Medicine in Dayton, Ohio, USA

ABSTRACT In this chapter, we discuss the relationship between childhood sexual abuse and borderline personality disorder (BPD). We begin by presenting an overview of BPD, including the epidemiology, working definition of the disorder, diagnostic approaches, treatment strategies, and outcome. We next discuss the difficulties in assessing trauma in clinical populations, regardless of the individual’s Axis II diagnosis. We then review the literature regarding the role of sexual abuse in BPD, which is generally conceptualized as one of several contributory variables to the development of the disorder. We conclude this chapter by integrating childhood sexual abuse into the other known causal factors for BPD.

Many clinicians and investigators view borderline personality disorder (BPD) as a trauma-based syndrome, and identify sexual abuse as a contributory factor to its development. In this chapter, we will overview the clinical and diagnostic features of this intriguing Axis II disorder, describe the potential limitations of childhood trauma assessment, examine the empirical role of sexual abuse in relationship to BPD, and integrate the role of sexual abuse into the general etiological fabric of BPD.

1 Corresponding author: Randy A. Sansone, M.D., 2115 Leiter Road, Miamisburg, Ohio, 45342. Telephone: 937384-6850. FAX: 937-384-6938. E-mail: [email protected].

198

Randy A. Sansone and Lori A. Sansone

AN OVERVIEW OF BPD The “Borderline” Designation The term BPD was first broached during the 1930s. During this era, mental health clinicians recognized a unique group of psychiatric patients who defied diagnostic classification, which at the time heavily relied on an initial symptom division between neurosis and psychosis. Oddly, these patients manifested multiple neurotic features but also periodically experienced transient psychosis. Because this patient cohort appeared to be sandwiched between the two general diagnostic categories of the era, they were perceived as “on the border” of neurosis and psychosis, or “borderline” (Stern, 1938).

Epidemiology of BPD General US population. Compared with other types of personality disorders, BPD is relatively common. To provide some context for this impression, in the US general population, the prevalence of all types of personality disorders is between 5% and 10% (Ellison and Shader, 2003). According to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR; American Psychiatric Association, 2000), the community prevalence of BPD is around 2%, although individuals with characteristics, traits, or subthreshold syndromes may account for up to 10% of the population (Stone, 1986). Psychiatric settings. Compared to individuals with other types of psychiatric disorders, those with BPD are seemingly over-represented in psychiatric settings (Quigley, 2005), most likely because of their engagement in chronic self-harm behavior. Indeed, approximately 25% of psychiatric inpatients as well as nearly 30% of outpatients are diagnosed with BPD (American Psychiatric Association, 2000; Widiger and Rogers, 1989). With regard to BPD symptomatology, which includes traits and subclinical or subthreshold syndromes, we have found prevalence rates of 50% and 22% among psychiatric inpatients and outpatients, respectively (Sansone, Rytwinski, and Gaither, 2003; Sansone, Songer, and Gaither, 2001). Very little empirical work has been done in the area of prevalence rates in US subcultures. However, in a psychiatric sample, Chavira et al. (2003) found a higher prevalence rate of BPD among Hispanics, compared with Whites or Blacks. Gender patterns and styles. According to the DSM-IV-TR, BPD is more commonly encountered in women than men. However, this seeming disparity may be an illusion and accounted for by sampling bias (Skodol and Bender, 2003). To explain this phenomenon, the two genders appear to manifest different types of BPD symptoms, which result in different types of social dispositions. Explicitly, women with BPD tend to have histrionic personality features, engage in self-directed self-harm behavior (e.g., self-cutting), and carry diagnoses of eating disorders and post-traumatic stress disorder (D. M. Johnson et al., 2003). Therefore, they tend to be treated in psychiatric settings where epidemiological studies frequently take place. Men, on the other hand, tend to manifest antisocial personality features, engage in externally directed self-harm behavior (e.g., bar fights), and have comorbid diagnoses of substance abuse (D. M. Johnson et al.; Zanarini et al., 1998). Therefore, a number of males

Childhood Sexual Abuse and Borderline Personality Disorder

199

with this disorder eventually end up in police custody and ultimately in prison settings, thereby eluding detection in epidemiological studies.

A Working Definition of BPD Understandably, the borderline concept initially appears diffuse and ill-defined because of (a) the broad functional levels of affected patients (i.e., low versus high functioning), (b) the broad array of accompanying psychiatric symptoms, which are represented by high frequencies of comorbid Axis I and II diagnoses, and (c) the polythetic nature of the diagnostic criteria in the DSM-IV-TR (i.e., only five of nine criteria are required for diagnosis, resulting in various diagnostic permutations and clinical presentations; Jackson and Jovev, 2006). However, regardless of the countless clinical variations in the presentation of this disorder, all affected individuals share three common clinical characteristics: (a) a transiently intact social façade or veneer, which tends to abruptly erode under stress; (b) chronic difficulties with self-regulation (e.g., eating disorders, substance abuse); and (c) chronic selfharm behavior. These features are consistently present in afflicted individuals and function as a practical working definition of BPD.

The Diagnosis of BPD The DSM. While there are a number of diagnostic approaches to BPD, the criteria that are listed in the DSM-IV-TR remain the authoritative standard. These criteria are: (a) frantic efforts to avoid abandonment; (b) a history of unstable and intense relationships with others; (c) identity disturbance; (d) impulsivity in at least two functional areas such as spending, sex, substance use, eating, or driving; (e) recurrent suicidal threats or behaviors as well as selfmutilation; (f) affective instability with marked reactivity of mood; (g) chronic feelings of emptiness; (h) inappropriate and intense anger or difficulty controlling anger; and (i) transient stress-induced paranoid ideation or severe dissociative symptoms. As noted previously, five of the preceding nine criteria are required for the diagnosis of BPD. Non-DSM Diagnostic Approaches. In addition to the DSM criteria, there are a number of available structured and semi-structured interviews for the diagnosis of BPD. Examples of these include the Diagnostic Interview for Borderlines-Revised (Zanarini, Gunderson, Frankenburg, and Chauncey, 1989), the Personality Disorder Examination (Loranger, 1988), the Structured Clinical Interview for DSM-III-R Personality Disorders (Spitzer, Williams, Gibbon, and First, 1990), and the Diagnostic Interview for DSM-IV Personality Disorders (Zanarini, Frankenburg, Sickel, and Yong, 1996). There are also various self-report measures for the diagnosis of BPD such as the SelfHarm Inventory (Sansone, Wiederman, and Sansone, 1998), the borderline personality scale of the Personality Diagnostic Questionaire-4 (Hyler, 1994), and the McLean Screening Inventory for Borderline Personality Disorder (Zanarini et al., 2003). The selection of a particular approach or measure is typically based upon the level of diagnostic rigor required (i.e., research versus clinical purposes), ease of administration (i.e., interviews versus self-report measures), cost, and the suspected prevalence of BPD within a

200

Randy A. Sansone and Lori A. Sansone

given clinical subpopulation (i.e., for populations with suspected high prevalence rates, such as in those with substance abuse and eating disorders, the clinician may want a rapid screening method for large numbers of patients).

The Treatment of BPD According to the Practice Guideline for the Treatment of Patients with Borderline Personality Disorder (American Psychiatric Association, 2001), “The primary treatment for borderline personality disorder is psychotherapy…” (p. 4). Various psychotherapy approaches have been utilized and most consist of eclectic combinations of psychodynamic, interpersonal, and cognitive-behavioral therapies as well as contracting strategies, psychoeducation, and skills training (Sansone and Sansone, 2006). Several of these treatment components are available as packaged, intensive, time-limited, and highly structured programs that have predominant cognitive-behavioral components. Examples of these programs are Dialectical Behavior Therapy (DBT) (Linehan, 1993) and Systems Training for Emotional Predictability and Problem Solving (STEPPS) (Blum, Pfohl, St. John, Monahan, and Black, 2002). We are not aware of any totally manualized or computer-based approaches to the treatment of BPD.

Clinical Outcomes in BPD There appear to be three general clinical outcomes for individuals suffering from BPD: (a) significant and gradual improvement over time in the overall personality pathology, which the majority experience (Zanarini, Frankenburg, Hennen, Reich, and Silk, 2006; Zanarini, Frankenburg, Hennen, and Silk, 2003); (b) ongoing and intense personality disorder symptoms, at least up to age 60, which seem to affect a minority (Sansone, Gaither, and Songer, 2002); and (c) suicide, which affects up to 10% of individuals (Paris, 2002). Studies indicate that poor prognostic outcomes in patients with BPD are associated with histories of multiple suicide attempts (Mehlum, Friis, Vaglum, and Karterud, 1994), comorbid personality pathology (Links, Heslegrave, and van Reekum, 1998), high levels of impulsivity (Links, Heslegrave, and van Reekum, 1999), parental cruelty (Stone, 1993), and substance abuse (Zanarini, Frankenburg, Hennen, Reich, and Silk, 2004).

CHILDHOOD SEXUAL ABUSE AND DIFFICULTIES WITH ASSESSMENT Regardless of the patient’s Axis II diagnosis in adulthood (i.e., whether BPD or not), the accurate assessment of sexual abuse in childhood is an extremely challenging clinical undertaking. First, the abuse may have occurred during a time when the child was at a preverbal level of development. During this developmental period, infants and toddlers literally lack the cognitive, verbal, and psychological skills to interpret and intellectually encode an abuse experience. However, under such circumstances, there is likely to be emotional encoding of the trauma.

Childhood Sexual Abuse and Borderline Personality Disorder

201

Second, young children have fairly limited and unsophisticated psychological defenses. As a result, in response to stress, they may employ somewhat primitive defenses, which tend to mirror their simplistic thought processes and absolutist (i.e., black/white) cognitive style. These defenses typically include: (a) repression (i.e., the unconscious relegation of unacceptable thoughts and feelings to the unconscious); (b) suppression (i.e., the conscious relegation of unacceptable thoughts and feelings to the unconscious); and (c) denial (i.e., the intentful disavowal of past experiences). Third, patients may misinterpret the abuse experience (i.e., normalize the events or assume personal responsibility). For example, in the case of sexual abuse, the victim may have experienced some level of physical pleasure and/or benefited from a favored status in the family household. Some victims perceive this positive aspect of the experience as evidence that they were not actually “abused.” Other patients may be too embarrassed by the experience to acknowledge or report the abuse, fearing its potential implications and/or subsequent meaning (e.g., a young male who is subjected to sexual abuse from an older male and is subsequently worried about sexual orientation). To summarize, while the actual assessment of childhood sexual abuse is beyond the scope of this chapter, it is important to recognize the inherent difficulties in accessing traumatic histories from childhood victims, regardless of the measure used or the presence or not of an Axis II diagnosis. Repression, suppression, denial, misinterpretation, and embarrassment are all factors that may obscure the actual childhood events.

CHILDHOOD SEXUAL ABUSE AND BPD As we noted earlier in this chapter, BPD is perceived by many clinicians and investigators as a trauma-based syndrome—one that ultimately has a profound effect upon the developing personalities of its victims. The effects of trauma may impair the development of affective and behavioral regulation, the ability to successfully achieve intimacy with other human beings, appropriate boundaries with others, and a healthy self-concept as well as precipitate a host of other developmental breaches. In examining various trauma variables, childhood sexual abuse has historically and empirically been consistently identified as a non-specific risk factor for the development of BPD. In summarizing the research literature up through the mid 1990s, Pfeifer-Tarlowski (1997) concluded that there appears to be a relationship between childhood sexual abuse and borderline-like symptoms in adulthood. Even in the most recent empirical literature, childhood sexual abuse continues to demonstrate significant correlations with BPD symptomatology in adulthood (e.g., Bandelow et al., 2005; Bradley, Jenei, and Westen, 2005; Chaudhry, 2005; Goodman and Yehuda, 2002; Hexel, Wiesnagrotzki, and Sonneck, 2004; Katerndahl, Burge, and Kellogg, 2005; Mclean, 2001). As an example, in a large study of a nonclinical population of over 5,000 18-year-olds, Trull (2001a) confirmed a relationship between childhood physical and sexual abuses, and BPD psychopathology. However, like the historical literature in this area, not all recent studies support a relationship between childhood sexual abuse and the development of BPD (e.g., Bierer et al., 2003; Trull, 2001b). This seeming contradiction may be explained by the high rates of sexual

202

Randy A. Sansone and Lori A. Sansone

abuse in the general population. Specifically, given that childhood sexual abuse is unfortunately common in the general population, comparing nonclinical subjects with BPD subjects may not evidence statistical differences, unless the BPD population under study manifests very extreme or severe personality psychopathology (i.e., individuals from inpatient populations, extremely self-harming individuals, those with frequent suicide attempts). Even if there were no statistical differences between those with and without BPD, this mathematical finding would not necessarily exclude childhood sexual abuse as a contributory factor to BPD. This is because we know that, from a psychological perspective, some individuals fare reasonably well in the aftermath of trauma while others become psychologically dysfunctional. These varying outcomes are likely to be explained by the context of the childhood sexual abuse. What contextual factors might affect outcome? Hyde and Kaufman (1984) describe several influential factors that may affect psychological outcomes following sexual abuse, such as the age at which the molestation first began, the frequency and duration of the abuse, the relationship of the perpetrator to the victim, the methods used to contain the “secret,” the degree of isolation of the “secret,” and the manner in which the exposure of the secret is handled. Additional factors may include a greater number of perpetrators, the lack of parental/family support, a threat to one’s life or the life of a family member, and/or higher levels of aggression in conjunction with the sexual abuse (Sansone and Sansone, in press). We also suspect that the general psychological constitutions of the victims confer varying levels of resilience in the face of adversity.

OTHER TYPES OF CHILDHOOD ABUSES AND BPD We have emphasized the meaningful contributory role of sexual abuse to the development of BPD. However, in addition to sexual abuse, other childhood trauma variables appear to contribute to BPD as well, including physical abuse and emotional abuses.

Childhood Emotional Abuse While few in number, several recent studies have examined the relationship between emotional abuse in childhood and BPD in adulthood. In nonclinical populations, J. G. Johnson et al. (2001) found that verbal abuse was associated with a 3-fold risk of having BPD. In the Collaborative Longitudinal Personality Disorders Study, Battle et al. (2004) found that both emotional and verbal abuses in childhood were associated with BPD.

Childhood Physical Abuse Compared with other Axis II disorders, Golier et al. (2003) and Paris, Zweig-Frank, and Guzder (1994) found that those with BPD have a greater frequency of childhood physical abuse.

Childhood Sexual Abuse and Borderline Personality Disorder

203

Combinations of Childhood Abuses Contemporary investigators have recently examined the role of multiple types of abuses in childhood and their correlation with BPD symptoms in adulthood. In this regard, Renneberg, Weibb, Under, Fiedler, and Brunner (2003) found that 87% of female psychiatric inpatients with BPD reported various traumatic childhood experiences (i.e., sexual and physical abuses). In an inpatient psychiatric sample, Zanarini, Williams, et al. (1997) found that, compared to those without the disorder, those with BPD reported significantly more emotional and physical abuses by a caretaker during childhood. In another inpatient sample, Zanarini, Dubo, Lewis, and Williams (1997) found that over 90% of the patients with BPD reported childhood abuse and neglect, 80% emotional or verbal abuse, and 60% physical and sexual abuses. In a sample of hospitalized adolescent females, Atlas (1995) found that those with early histories of physical and/or sexual abuse were significantly more likely to be diagnosed with BPD. In addition to the preceding findings from psychiatric inpatient samples, several investigators have examined the relationship between childhood adversity and BPD symptoms in patients with various types of substance abuse. Ellason, Ross, Sainton, and Mayran (1996) examined inpatient substance abusers and found that, compared to those without histories of physical and/or sexual abuse, those with such histories had higher rates of BPD. In another sample of patients with substance abuse diagnoses, Ruggiero (1996) found that both physical and emotional abuses had diffuse relationships with most of the Axis II disorders under study, including BPD. Finally, Bierer et al. (2003) examined a sample of 182 outpatients with various personality disorders. They found that global trauma severity was predictive of Cluster B diagnoses (i.e., in the DSM-IV-TR, those Axis II disorders characterized by dramatic, emotional, and/or erratic clinical features), particularly borderline and antisocial personality disorders. In summary, these data indicate that childhood sexual abuse is but one of various types of abuses that may contribute to BPD. Other types include emotional and physical abuses. In addition, it appears that combinations of childhood abuse are apparent in many cases. The presence of various forms of childhood abuses in patients with BPD may suggest that: (a) the combination of abuse types are particularly predisposing to BPD and/or (b) a statistical “clustering” phenomenon is occurring. With regard to the latter, from a statistical perspective, clustering occurs when multiple variables are highly inter-related to each other. For example, in the case of BPD, it is unlikely that a single form of childhood abuse occurs in isolation from the others—i.e., various types naturally occur together (e.g., can one be physically abused without experiencing emotional abuse, as well?). Therefore, these types of variables are likely to cluster.

Non-Traumatic Pathways to BPD Throughout this chapter, we have emphasized the role of childhood sexual abuse and other types of childhood trauma in the development of BPD. However, there may be other pathways to BPD that do not entail malignant adversity in childhood. According to Graybar and Boutilier (2002), such cases may develop from high-risk genetics and/or inherited

204

Randy A. Sansone and Lori A. Sansone

temperaments, affective dysfunction, neurological deficits, and emotionality—all in the absence of childhood trauma. Many of these adjunctive predisposing factors will be discussed in the next section. The only caveat we offer to the proposal by Graybar and Boutilier is the role of impaired childhood recollections. What if it only appears that some victims do not have trauma histories because of their well-honed psychological defenses, which may effectively and totally obscure the recollection of these types of events?

OTHER CONTRIBUTORY FACTORS TO BPD While trauma appears to play a significant role in the majority of cases (Zanarini, Dubo, et al., 1997), other factors may also contribute to the development of BPD (i.e., BPD is a multi-determined disorder). These factors include: (a) genetic predisposition (Skodol et al., 2002); (b) parental psychopathology; and (c) family dysfunction.

Genetic Predisposition Genetics appear to play a role in the development of BPD. The possibility of genetic predisposition does not mean that the personality disorder, itself, is directly inherited. Rather, investigators (Skodol et al., 2002) suggest that temperamental characteristics may be inherited, such as a genetic impairment in the ability to self-regulate or a tendency towards affective lability. Under conducive circumstances, these temperamental characteristics might then heighten the overall risk for developing BPD.

Parental Psychopathology With regard to parental psychopathology, researchers describe a number of unhealthy patterns. These include parental neglect and a lack of empathy (Yatsko, 1996), “biparental failure” (Zanarini et al., 2000), and perceived low parental empathy and support (Fruzzetti, Shenk, and Hoffman, 2005). The overall theme of these studies is ineffectual parenting (Norden, Klein, Donaldson, Pepper, and Klein, 1995), although Paris and Zweig-Frank (1997) also describe separation from or loss of parents in early life.

Family Dysfunction In terms of family psychopathology, Fruzzeti et al. (2005) describe invalidating, conflictual, negative, and/or critical family interactions. In keeping with the preceding findings, Hogue (1999) emphasizes the overall level of family dysfunction.

Childhood Sexual Abuse and Borderline Personality Disorder

205

Triggering Events One final phenomenon may be of relevance in the ultimate manifestation of BPD symptoms—the role of triggering events. Zanarini and Frankenburg (1997) describe these events as acute psychosocial stressors that result in the abrupt precipitation and/or acute onset of BPD symptoms. We are not aware of extensive data regarding how frequently these triggering events occur among patients or the nature of the events, themselves. However, they are likely to be acute catalysts for chemical reactions that have been developing since childhood.

CONCLUSIONS BPD is an insidious psychiatric disorder that, in the majority of cases, appears to have its primal roots in childhood. The childhoods of these individuals seem to be riddled with maltreatment, adversity, and neglect. Sexual abuse is common as well as other forms of abuse including emotional and physical abuses. While there may be non-traumatic pathways to BPD, this seems infrequent, particularly given what we know about the defensive operations of children under stress and their ability to “erase” the violations they incur. In addition to childhood trauma, other priming substrates appear to be parental psychopathology and dysfunctional family environments. While at first glance, these phenomena may appear independent of each other, in practical terms, these contributory variables are likely to be highly inter-related. In other words, bad genes are likely to be associated with psychologically impaired parents who, in turn, propagate abusive experiences upon their young charges, who have no options but to exist in these chaotic households. Are there individuals with BPD who do not come from such backgrounds? If so, they are very infrequent in psychiatric treatment settings.

ABOUT THE AUTHORS Dr. R. Sansone is a Professor in the Departments of Psychiatry and Internal Medicine at Wright State University School of Medicine in Dayton, Ohio, and Director of Psychiatry Education at Kettering Medical Center in Kettering, Ohio. Dr. L. Sansone is a civilian family medicine physician at Wright-Patterson Air Force Base in Dayton, Ohio. The views expressed in this chapter are those of the authors and do not reflect the official policy or position of the US Air Force, Department of Defense, or US government. Please address all correspondence to: Randy A. Sansone, M.D., 2115 Leiter Road, Miamisburg, Ohio, 45342. Telephone: 937384-6850. FAX: 937-384-6938. E-mail: [email protected]

REFERENCES American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders, 4th edition, text revision. Washington, DC: American Psychiatric Press.

206

Randy A. Sansone and Lori A. Sansone

American Psychiatric Association. (2001). Practice guideline for the treatment of patients with borderline personality disorder. American Journal of Psychiatry, 158, S1-52. Atlas, J. A. (1995). Association between history of abuse and borderline personality disorder for hospitalized adolescent girls. Psychological Reports, 77, 1346. Bandelow, B., Krause, J., Wedekind, D., Broocks, A., Hajak, G., and Ruther, E. (2005). Early traumatic life events, parental attitudes, family history, and birth risk factors in patients with borderline personality disorder and healthy controls. Psychiatry Research, 134, 169179. Battle, C. L., Shea, M. T., Johnson, D. M., Yen, S., Zlotnick, C., Zanarini, M. C., et al. (2004). Childhood maltreatment associated with personality disorders: Findings from the Collaborative Longitudinal Personality Disorders Study. Journal of Personality Disorders, 18, 193-211. Bierer, L. M., Yehuda, R., Schmeidler, J., Mitropoulou, V., New, A. S., Silverman, J. M., et al. (2003). Abuse and neglect in childhood: Relationship to personality disorder diagnoses. CNS Spectrums, 8, 737-740, 749-754. Blum, N., Pfohl, B., St. John, D., Monahan, P., and Black, D. W. (2002). STEPPS: A cognitive-behavioral systems-based group treatment for outpatients with borderline personality—A preliminary report. Comprehensive Psychiatry, 43, 301-310. Bradley, R., Jenei, J., and Westen, D. (2005). Etiology of borderline personality disorder: Disentangling the contributions of intercorrelated antecedents. Journal of Nervous and Mental Disease, 193, 24-31. Chaudhry, B. R. (2005). Psychosocial risk factors associated with the development of borderline personality features. Dissertation Abstracts International, 65, 6700B. Chavira, D. A., Grilo, C. M., Shea, M. T., Yen, S., Gunderson, J. G., Morey, L. C., et al. (2003). Ethnicity and four personality disorders. Comprehensive Psychiatry, 44, 483-491. Ellason, J. W., Ross, C. A., Sainton, K., and Mayran, L. W. (1996). Bulletin of the Menninger Clinic, 60, 39-51. Ellison, J. M., and Shader, R. I. (2003). Pharmacologic treatment of personality disorders: A dimensional approach. In R. I. Shader (Ed.), Manual of psychiatric therapeutics (pp. 169183). Philadelphia: Lippincott, Williams, and Wilkins. Fruzzetti, A. E., Shenk, C., and Hoffman, P. D. (2005). Family interaction and the development of borderline personality disorder: A transactional model. Development and Psychopathology, 17, 1007-1030. Golier, J., Yehuda, R., Bierer, L. M., Mitropoulou, V., New, A. S., Schmeidler, J., et al. (2003). The relationship of borderline personality disorder to posttraumatic stress disorder and traumatic events. American Journal of Psychiatry, 160, 2018-2024. Goodman, M., and Yehuda, R. (2002). The relationship between psychological trauma and borderline personality disorder. Psychiatric Annals, 32, 337-345. Graybar, S. R., and Boutilier, L. R. (2002). Nontraumatic pathways to borderline personality disorder. Psychotherapy: Theory, Research, Practice, Training, 39, 152-162. Hexel, M., Wiesnagrotzki, S., and Sonneck, G. (2004). Psychiatric disorders and traumatic life events. German Journal of Psychiatry, 7, 28-34. Hogue, S. L. (1999). Relationship between family of origin history and personality pathology. Dissertation Abstracts International, 59, 6067B. Hyde, M. L., and Kaufman, P. A. (1984). Women molested as children: Therapeutic and legal issues in civil actions. American Journal of Forensic Psychiatry, 5, 147-157.

Childhood Sexual Abuse and Borderline Personality Disorder

207

Hyler, S. E. (1994). Personality Diagnostic Questionniare-4. New York: Author. Jackson, H. J., and Jovev, M. (2006). Personality disorder constructs and conceptualizations. In R. A. Sansone and J. L. Levitt (Eds.), Personality disorders and eating disorders: Exploring the frontier (3-20). New York: Routledge. Johnson, D. M., Shea, M. T., Yen, S., Battle, C. L., Zlotnick, C., Sanislow, C. A., et al. (2003). Gender differences in borderline personality disorder: Findings from the Collaborative Longitudinal Personality Disorders Study. Comprehensive Psychiatry, 44, 284-292. Johnson, J. G., Cohen, P., Smailes, E. M., Skodol, A. E., Brown, J., and Oldham, J. M. (2001). Childhood verbal abuse and risk for personality disorders during adolescence and early adulthood. Comprehensive Psychiatry, 42, 16-23. Katerndahl, D., Burge, S., and Kellogg, N. (2005). Predictors of development of adult psychopathology in female victims of childhood sexual abuse. Journal of Nervous and Mental Disease, 193, 258-264. Linehan, M. M. (1993). Cognitive-behavioral treatment of borderline personality disorder. New York: Guilford. Links, P. S., Heslegrave, R., and van Reekum, R. (1998). Prospective follow-up study of borderline personality disorder: Prognosis, prediction of outcome, and Axis II comorbidity. Canadian Journal of Psychiatry, 43, 265-270. Links, P. S., Heslegrave, R., and van Reekum, R. (1999). Impulsivity: Core aspect of borderline personality disorder. Journal of Personality Disorders, 13, 1-9. Loranger, A. W. (1988). Personality Disorder Examination Manual. Yonkers, New York: DV Communications. Mclean, L. M. (2001). The relationship between early childhood sexual abuse and the adult diagnoses of borderline personality disorder and complex posttraumatic stress disorder: Diagnostic implications. Dissertation Abstracts International, 62, 2069B. Mehlum, L., Friis, S., Vaglum, P., and Karterud, S. (1994). The longitudinal pattern of suicidal behaviour in borderline personality disorder: A prospective follow-up study. Acta Psychiatrica Scandanavica, 90, 124-130. Norden, K. A., Klein, D. N., Donaldson, S. K., Pepper, C. M., and Klein, L. M. (1995). Reports of the early home environment in DSM-III-R personality disorders. Journal of Personality Disorders, 9, 213-223. Paris, J. (2002). Implications of long-term outcome research for the management of patients with borderline personality disorder. Harvard Review of Psychiatry, 10, 315-323. Paris, J., and Zweig-Frank, H. (1997). Parameters of childhood sexual abuse in female patients. In M. C. Zanarini (Ed.), Role of sexual abuse in the etiology of borderline personality disorder (pp. 15-28). Washington, DC: American Psychiatric Association. Paris, J., Zweig-Frank, H., and Guzder, J. (1994). Psychological risk factors for borderline personality disorder in female patients. Comprehensive Psychiatry, 35, 301-305. Pfeifer-Tarkowski, V. J. (1997). The role of childhood sexual abuse and the development of borderline personality disorder: A critical review. Dissertation Abstracts International, 57, 4720B. Quigley, B. D. (2005). Diagnostic relapse in borderline personality: Risk and protective factors. Dissertation Abstracts International, 65, 3721B.

208

Randy A. Sansone and Lori A. Sansone

Renneberg, B., Weibb, M., Unger, J., Fiedler, P., and Brunner, R. (2003). Etiological factors in borderline personality disorder. Verhaltenstherapie and Verhaltensmedizin, 24, 347364. Ruggiero, J. S. (1996). The personality sequelae of child maltreatment in drug and alcohol dependent male veterans. Dissertation Abstracts International, 56, 4592B. Sansone, R. A., Gaither, G. A., and Songer, D. A. (2002). Self-harm behaviors across the life cycle: A pilot study of inpatients with borderline personality disorder. Comprehensive Psychiatry, 43, 215-218. Sansone, R. A., Rytwinski, D., and Gaither, G. A. (2003). Borderline personality and psychotropic medication prescription in an outpatient psychiatry clinic. Comprehensive Psychiatry, 44, 454-458. Sansone, R. A., and Sansone, L. A. (2006). Borderline personality and eating disorders : An eclectic approach to treatment. In R. A. Sansone and J. L. Levitt (Eds.), Personality disorders and eating disorders: Exploring the frontier (197-212). New York: Routledge. Sansone, R. A., and Sansone, L. A. (in press). Borderline personality in the medical setting: Unmasking and managing the difficult patient. Hauppauge, NY: Nova Science Publishers. Sansone, R. A., Songer, D. A., and Gaither, G. A. (2001). Diagnostic approaches to borderline personality and their relationship to self-harm behavior. International Journal of Psychiatry in Clinical Practice, 5, 273-277. Sansone, R. A., Wiederman, M. W., and Sansone, L. A. (1998). The Self-Harm Inventory (SHI): Development of a scale for identifying self-destructive behaviors and borderline personality disorder. Journal of Clinical Psychology, 54, 973-983. Skodol, A. E., and Bender, D. S. (2003). Why are women diagnosed borderline more than men? Psychiatric Quarterly, 74, 349-360. Skodol, A. E., Siever, L. J., Livesley, W. J., Gunderson, J. G., Pfohl, B., and Widiger, T. A. (2002). The borderline diagnosis II: Biology, genetics, and clinical course. Biological Psychiatry, 51, 951-963. Spitzer, R. L., Williams, J. B. W., Gibbon, M., and First, M. B. (1990). Structured Clinical Interview for DSM-III-R Personality Disorders (SCID-II). Washington, DC: American Psychiatric Press. Stern, A. (1938). Psychoanalytic investigation of therapy in the borderline group of neuroses. Psychoanalytic Quarterly, 7, 467-489. Stone, M. H. (1986). Borderline personality disorder. In R. Michels and J. O. Cavenar (Eds.), Psychiatry, 2nd edition (pp. 1-15). Philadelphia: Lippincott. Stone, M. H. (1993). Long-term outcome in personality disorders. British Journal of Psychiatry, 162, 299-313. Trull, T. J. (2001a). Structural relations between borderline personality disorder features and putative etiological correlates. Journal of Abnormal Psychology, 110, 471-481. Trull, T. J. (2001b). Relationships of borderline features to parental mental illness, childhood abuse, Axis I disorder, and current functioning. Journal of Personality Disorders, 15, 1932. Widiger, T. A., and Rogers, J. H. (1989). Prevalence and comorbidity of personality disorders. Psychiatric Annals, 19, 132-136. Yatsko, C. K. (1996). Etiological theories of borderline personality disorder: A comparative multivariate study. Dissertation Abstracts International, 56, 4628B.

Childhood Sexual Abuse and Borderline Personality Disorder

209

Zanarini, M. C., Dubo, E. D., Lewis, R. E., and Williams, A. A. (1997). Childhood factors associated with the development of borderline personality disorder. In M. C. Zanarini (Ed.), Role of sexual abuse in the etiology of borderline personality disorder (pp. 29-44). Washington, DC: American Psychiatric Press. Zanarini, M. C., and Frankenburg, F. R. (1997). Pathways to the development of borderline personality disorder. Journal of Personality Disorders, 11, 93-104. Zanarini, M. C., Frankenburg, F. R., Dubo, E. D., Sickel, A. E., Trikha, A., Levin, A., et al. (1998). Axis II comorbidity of borderline personality disorder. Comprehensive Psychiatry, 39, 296-302. Zanarini, M. C., Frankenburg, F. R., Hennen, J., Reich, D. B., and Silk, K. R. (2004). Axis I comorbidity in patients with borderline personality disorder: 6-year follow-up and prediction of time to remission. American Journal of Psychiatry, 161, 2108-2114. Zanarini, M. C., Frankenburg, F. R., Hennen, J., Reich, D. B., and Silk, K. R. (2006). Prediction of the 10-year course of borderline personality disorder. American Journal of Psychiatry, 163, 827-832. Zanarini, M. C., Frankenburg, F. R., Hennen, J., and Silk, K. R. (2003). The longitudinal course of borderline psychopathology: 6-year prospective follow-up of the phenomenology of borderline personality disorder. American Journal of Psychiatry, 160, 274-283. Zanarini, M. C., Frankenburg, F. R., Reich, D. B., Marino, M. F., Lewis, R. E., Williams, A. A., et al. (2000). Biparental failure in the childhood experiences of borderline patients. Journal of Personality Disorders, 14, 264-273. Zanarini, M. C., Frankenburg, F. R., Sickel, A. E., and Yong, L. (1996). The Diagnostic Interview for DSM-IV Personality Disorders (DIPD-IV). Belmont, MA: Authors. Zanarini, M. C., Gunderson, J. G., Frankenburg, F. R., and Chauncey, D. L. (1989). The revised Diagnostic Interview for Borderlines: Discriminating BPD from other Axis II disorders. Journal of Personality Disorders, 3, 10-18. Zanarini, M. C., Vujanovic, A. A., Parachini, E. A., Boulanger, J. L., Frankenburg, F. R., and Hennen, J. (2003). A screening measure for BPD: The McLean Screening Instrument for Borderline Personality Disorder (MSI-BPD). Journal of Personality Disorders, 17, 568-573. Zanarini, M. C., Williams, A. A., Lewis, R. E., Reich, R. B., Vera, S. C., Marino, M. F., et al. (1997). Reported pathological childhood experiences associated with the development of borderline personality disorder. American Journal of Psychiatry, 154, 1101-1106.

In: Advances in Psychology Research, Volume 57 Editor: Alexandra M. Columbus

ISBN 978-1-60456-897-4 © 2008 Nova Science Publishers, Inc.

Chapter 10

POST-PARTUM DEPRESSION: PREVALENCE AND DEMOGRAPHIC, OBSTETRIC AND PERINATAL RISK FACTORS Alexandre Faisal-Cury* a and Paulo Rossi Menezes a,b a

Epidemiology Section – University Hospital- University of São Paulo, Brasil b Departament of Preventive Medicine – University of São Paulo, Brasil

ABSTRACT Objectives: to estimate the prevalence and risk factors for postpartum depression (PPD), among post-partum women from a private clinic at Osasco, São Paulo. Methods: we performed a cross sectional study of 267 women from 8/28/00 to 5/15/03.The instruments used were the Beck Depression Inventory (BDI) and a questionnaire for socio-demographic and obstetric characteristics. Inclusion criteria were: women with no past or present history of depression, psychiatric treatment, alcohol or drug addiction, and whose child was alive. The prevalence of PPD, according to the BDI, and odds ratios for the associations between PPD and exposures variables were estimated. Hypothesis testing was done with x2 tests, or x2 tests for linear trend, when categories were ordered. A p value of < 0.05 was considered statistically significant. Results: the prevalence of PDD was 19.1% (95% IC: 14,3 a 23,8%). In the univariate analysis, only low birth weight was associated with PPD (OR 5.88, IC 95% 1.78-20.0, p<0,001). Conclusions: PPD was highly prevalent among women from this private setting and was associated with new-born low birth weigth.

Keywords: Postpartum depression, Prevalence, Screening, Low Birth Weigth.

*

Alexandre Faisal-Cury, Rua Dr Mário Ferraz 135/32, Jd Paulistano, 01453-010, São Paulo, Tel/Fax: 11 36838196, [email protected].

212

Alexandre Faisal-Cury and Paulo Rossi Menezes

INTRODUCTION Depression is one of the ten most important public health problems in the USA [36]. Many women present with a first depressive episode in puerperium [34]. Postpartum depression is important for several reasons. Usually, the born of a child is a motif of joy and happiness to all the family. PPD may end these feelings. PPD affects not only the women in the puerperium [28] but also the entire family [23]. A depressed woman may avoid social contact and can possibly have difficulties with her professional activities. Husbands and partners are more likely to develop depression in the postpartum period if their wives develop PPD. The marital relationship may be significantly affected by PPD, leading to deterioration in many areas of marriage. PPD can also have lasting effects on an infant’s development. Infant’s cognitive and social skills, attention and language may be adversely affected by PPD 31 . Regarding herself, a depressed women presents a higher risk of been depressed years after delivery, somatizations and even a risk of committing suicide. Depending on the diagnostic criteria used and the time period observed, the prevalence of PPD can be as high as 20% (Watson et al, 1984). In a meta-analysis of 59 studies, the mean 1year prevalence rate was 13% [25]. A recent study, with 296 women from 8 countries, confirms that there are significant differences in the prevalence of PPD between countries and has found an overall estimated 6-month prevalence of 12.3% (Gorman et al, 2004). Studying a low-income population in Brazil, we found a prevalence of depressive symptoms of 16% in the tenth day after delivery [11]. Even oriental countries like Twain and China, where mood disturbances were traditionally lower compared to ocidental societies, are experiencing an increase of the problem [22,38]. The American College Obstetricians and Gynecologists states that the obstetriciangynecologist should be cognizant of the various factors that influence the presentation, diagnosis, and treatment of depression in women [39]. This is possibly true for PPD. Unfortunately, a previous research with 437 current residents and recent graduates has shown that even if the newly trained ob-gyn are confident overall for recognizing depression, they are not as confident, as older physicians, to manage it (Dietrich et al, 2003). The literature depicts the importance of risk factors for PPD, such as personal and family history of depression, lack of social support, poor partner relationship, life events, anxiety and depression during pregnancy. There is some controversy about other factors, such as age, parity, breastfeeding, unplanned pregnancy and obstetric complications (Eberhard-Gran et al, 2002; Gale and Harlow, 2003). Most studies on PPD were done with postpartum women from public health services. Less is known about PPD in the private sector. It is possible that when compared to women from public health services, some different risk factors may play a role. The objectives of the present study were to estimate the prevalence of PPD and it is association with socio-demographic, obstetric and perinatal variables, among women attending a private clinic in Brazil.

Post-Partum Depression: Prevalence and Demographic…

213

METHOD Study Design We performed a cross-sectional study of women who attended a private gynecologic and obstetric clinic in Osasco, which is part of Greater Sao Paulo, in South Eastern Brazil, during the first year after delivery.

Subjects A sample of 265 post-partum women was recruited from appointments in a private clinic in Osasco, São Paulo, during the period of 08/28/2000 to 05/15/03. The clinic is attended mainly by middle-class patients with health insurance plans. Osasco has 700,000 habitants and its main activities are industry and commerce. It is the largest and most important city in the West area of Greater São Paulo. Inclusion criteria were: post-partum women from one to twelve months after delivery, with no past or present history of depression, psychiatric treatment, alcohol or drug abuse and whose new-born was alive. There were no refusals and all interviews were made by the same person (AFC).

Instruments Beck Depression Inventory (BDI) The BDI [4] was used to identify probable cases of depression. A cut-off point of 15 was used, according to a previous validation in the country [14]. The scale consists of 21 items including symptoms and attitudes with intensities ranging from neutral to a maximum level of severity, ranked from 0 to 3. This inventory has been used in several studies in different countries [11] (Teissedre et al, 2004; Chung et al, 2001). The BDI internal consistency for psychiatric patients and non-psychiatric patients were 0.86 and 0.81, respectively [5] . Additional Instruments A questionnaire was employed to elicit information on factors that could be associated to PPD. The socio-demographic questionnaire comprised couple’s information about age, religion, years of education, employment, personal and family income, ethnicity, and years of marriage. Maternal health information included past obstetric history, parity, number of children alive and miscarriage, type of delivery and complications during delivery or the postpartum period. New-born information included sex, weight, breast or bottle feeding (with duration in months) and complications during and after delivery. All variables were categorized. Regarding marital status, women not legally married but living with their partners were classified as married. Breast-feeding exclusively was considered when the child had received maternal milk with no other type of food. Low birth weight was considered when new-born had less then 2500 g. Sample size was estimated taking in account several studies that have shown a PPD prevalence of [25]. Considering a 95% confidence interval, wich results in limits from 9% to 17%, a sample of 271 women would be needed.

214

Alexandre Faisal-Cury and Paulo Rossi Menezes

PROCEDURES The research project was approved by the Ethics Committee of the private hospital where most deliveries were performed. Women who met the inclusion criteria were approached by the main investigator (AFC), during the post-partum appointments. They were then oriented about the research project. During the interview, the participants answered the questionnaire and the BDI.

Statistical Analysis All variables were categorized. The prevalence of PPD, according to BDI, was estimated with 95% CI. Odds ratios, and 95% confidence intervals, were used to examine the association between PPD and exposures variables. Hypothesis testing was done with x2 tests, or x2 tests for linear trend, when categories were ordered. Multivariate analysis was performed using a stepwise regression logistic procedure. Odds ratio and 95% confidence intervals were evaluated. A p value of < 0.05 was considered statistically significant. Statistical analysis was performed using STATA 8 software.

RESULTS Subjects Two hundred sixty five post-partum women, mainly white (84.3%), catholic (67.6%), married or living with their partners (95.4%), were included. Their mean age was 26.2 years (range: 14 to 44). Half were in their first pregnancy. The number of previous pregnancy varied from 1 to 6. The mean number of years married was 4.3 (range: 1 to 20). Eighteen percent had less than 8 years of education, while 14.5% had reached university. 96 of the women (42.3%) had no income, while 60 (26.4%) had a monthly income of less than 166 US dollars. The mean monthly income for couples was 600 US dollar. Forty four percent of women had had their deliveries less than 3 months prior to the interview. Two hundred and forty one women were breast-feeding (exclusively).

Prevalence of PPD The mean score of BDI was 9.65 (SE=7.6). Prevalence of PPD according to BDI was 19.1% (95%CI: 14.3 to 23.8). In the univariate analysis, only low birth weight was associated with PPD (OR 5.88, 95%CI:1.78 to 20.0, p<0.001). Comparing women whose babies had low birth weight against women whose babies weight more than 3500 g, the risk of PPD was almost 3 times higher (OR:3.12, 95%CI: 0.91-11.1, p=0.05)

Post-Partum Depression: Prevalence and Demographic…

215

Discussion Our study has some methodological limitations. The study was carried out in a single private clinic, which may limit generalization. However, the profile seen in the present sample regarding years of education and income suggest that the sample is similar to the population of women seen in such settings in Brazil. Exclusion of women with previous story of depression may have produced an underestimate of the prevalence of PPD. There was some missing data for certain explanatory variables. Finally, we used a self-report instrument, instead of more strict criteria, such as a psychiatric interview, to classify possible cases of PPD. Several studies have shown that PPD prevalence is lower with the utilization of psychiatric diagnosis given in a direct clinical interview [26]. There is also some controversy about the employmenty of BDI as a screening instrument for PPD. Harris et al [17] considered that BDI has too many somatic questions, such as insomnia, lost of energy and appetite, symptoms very commom in psychological and physical disturbances. In fact, it is difficult to assess these symptoms during the postpartum period. On the other hand, some authors defend that even depression screening instruments, which are not designed for postpartum women, may be used after delivery [20], except during the first few days of puerperium [21]. One of the most used intrument for postpartum women, the Edinburgh PosNatal Depression Scale (EPDS), [8] showed moderate agreement with BDI [2] . A better accuracy for the EPDS, compared to BDI, has been suggested [6]. Despite this controversy, BDI has been considered a usefull instrument in research on depression [19]. The prevalence of PPD was 15.9%, which is comparable with other studies that used the same instrument [24,27,35] or different ones (Pop, Essed et al, 1993; Georgiopoulos, Bryan et al. 1999; Sugawara, Sakamoto et al. 1999). Higher rates were found in other studies [29]. Glasser, Barell et al. (1998), studying a group of 288 Israeli women, at 6 weeks of postpartum, found an overall PPD prevalence of 22.6% [13]. Our results are also slightly higher than the results of a recent meta-analysis with 59 studies, which yielded a summary estimate of 13% [25], but is in agreement with studies that have used the same instrument (BDI). Pfost et al (1990) [27], in the USA, have studied prospectively 69 pregnant women up to 30 days after delivery and found a PPD prevalence of 17%. O`Hara et al (1991) [24], also in the USA, followed a cohort of 182 pregnant women, from the second trimester up to 9 weeks after delivery, and found a PPD prevalence of 10.2%. Gotlib et al (1989) 15 evaluated prospectively a heterogeneous group of Canadian women, until 30 days of puerperium. Using a cut-off of 10 with the BDI, they found 25% with depressive symptomatology. Alvarado et al (1993) 1 did a longitudinal cohort study with 125 Chilean pregnant women, evaluated at 24 weeks of pregnancy and 8 weeks in the puerperium, and found 22.4% of PPD. They used the same cut-off that we used in the present study. Stuart et al (1998) [35] have followed prospectively 107 pregnat women up to 14 and 30 weeks of puerperium, finding a PPD prevalence of 23.3% and 18.7%, respectively. A recent study found that 30.6% of postpartum women presented with symptoms of depression, and that the mean scores decreased significantly between 4-8 and 10-14 weeks of puerperium, but not between 10-14 weeks and two years after delivery [18]. A previous study carried out by our team in a tertiary public hospital in Brazil, with women of lower socio-economic level, found a PPD prevalence of 15.9% [11]. Regarding to the variables that could be associated to PPD, we have observed in the present study, that women whose babies had birth weight lower than 2500 g had a greater risk

216

Alexandre Faisal-Cury and Paulo Rossi Menezes

of being depressed than women whose babies had a birth weight between 2500 and 3500 g. Considering the mothers whose babies weight more than 3500 g, the diference was still statisticaly significant. In this case, low birth weight`s mothers had a 3 fold increased in the chance of being depressed. The socio-demographic characteristics of the sample may explain this finding. The homogenity of demographic profile in this group of women may enhance the importance of psychological aspects such as anxiety in the association with low birth weight. Association between low birth weight and PPD was also obeserved in a study with 217 postpartum women, evaluated with EPDS, five days and six weeks after delivery. In this study other variables associated to PPD were cesarean section, botlle feeding and delivery more complicated than expected [16]. Gennaro (1988)[ 12] observed that mothers whose babies were prematures were significantly more depressed than mothers whose babies were delivered at term. In other cross-sectional study with 1250 participants, at the fifth day after delivery, authors found 20% of women with depressive symptoms that are associated to low birth weight, complicated delivery and low socio-economic status [7]. Authors stressed that despite the association between low birth weight and cesarean, this type of delivery was not associated to PPD. In the present study, type of delivery was not associated to PPD. In fact, it is possible that in our sample, a cesarean may no be regarded by both, women and obstetrics, as a complication. This assumption is based in the high rates of cesarean deliveries in private clinics We could not confirm an association between PPD and other obstetrics and perinatal outcomes, as newborn sex, time of evaluation after delivery, medical complication during delivery, presence and duration of breast feeding. A review of the subject depicts the controversy among studies regarding to the association of PPD and several perinatal and obstetrics risk factors [26]. Nevertheless, a recent study found that clinical complications during pregnancy increase the risk of PPD [37]. It is really interesting to observe that, according to a meta-analysis, different psychological variables have been implicated in PPD: stressful life events, modd disturbances during or before pregnancy, lack of social support, conflictive marital relationship, low self estim and not planning the pregnancy [3]. Knowledge about prevalence and risk factors of PPD are an important part of pregnant women`s health care and helps obstetrics to deal with their patients emotional demands [10]. In fact there are few possible roles for the obstetricians dealing with PPD including to develop a new attitude starting during pre-natal appointments that includes discussion of psycho-social aspects (sexuality, marriage, social and professional life), to gain familiarity with screening tools, not relying just on clinical judgments, to gain familiarity with treatment options and to individualize attendance, especially during post partum period, offering close and carefully care or referral when indicated. Table 1. Characteristics of participants, number with Postpartum Depression (PPD), according to the BDI, Odds Ratios, 95% confidence intervals and p-values (n=267) Explanatory variable Age (years) 14 to 19 20 to 29

Total (n)

PPD cases (%)

34 151

9 (26.4) 31 (20.5)

OR

CI ( 95%)

P value 0,09*

1 0.71

0.30 : 1.69

Post-Partum Depression: Prevalence and Demographic…

217

Table 1. (Continued) Explanatory variable

Total (n)

New born birth weight (g) 30 to 40 80 Missing 2 Ethnic origin White 208 Others 56 Missing 3 Religion Catholic 161 Evangelic 64 Others 13 Missing 25 Women’s income (US$) 0 96 1 to 166 60 167 to 1000 71 Missing 40 Couple’s income (R$) Up to 450 141 451 to 2730 83 Missing 43 Marital status Married 252 Others 12 Missing 3 Length of marriage (years) <1 9 1 to 4 129 5 to 20 95 Missing 34 Number of children alive 1 139 2 to 5 106 Missing 22 Number of previous abortion 0 199 1 to 2 46 Missing 22 * chi-square of tendency.

PPD cases (%)

OR

CI ( 95%)

P value 0.003*

11 (13.7)

0.44

43 (20.6) 8 (14.3)

1 0.63

29 (18.0) 13 (20.3) 2 (15.3)

1 1.16 0.82

22 (22.9) 11 (18.3) 12 (16.9)

1 0.75 0.68

32 (22.7) 12 (14.4)

1 0.57

0.16 : 1.21 0.28 0.28 : 1.45 0.91 0.55 : 2.41 0.17 : 3.95 0.59 0.33 : 1.70 0.31 : 1.50 0.13 0.27 : 1.19 0.18

47 (18.6) 4 (33.3)

1 2.18

1 (11.1) 26 (20.1) 14 (14.7)

1 2.01 1.38

25 (18.0) 12 (19.8)

1 1.12

34 (17.1) 12 (26.1)

1 1.71

0.62 : 7.59 0.57 0.23 : 17.0 0.15 : 12.0 0.71 0.59 : 2.14 0.15 0.80 : 3.65

218

Alexandre Faisal-Cury and Paulo Rossi Menezes Table 1. (Continued)

Explanatory variable

Total (n)

New born birth weight (g) 1100 to 2500 14 2501 to 3500 186 3501 to 4600 66 Missing 1 New born sex Female 130 Male 137 Missing 0 Type of delivery Cesarean 169 Forceps 44 Vaginal 54 Missing 2 Medical complications after delivery No 226 Yes 41 Missing 0 Time since delivery (months) Up 3 117 4 a 12 150 Missing 0 Length of breast feeding (months) Up 3 161 4 a 12 95 Missing 11 Type of feeding Exclusively 241 Others 21 Missing 5

PPD cases (%)

OR

CI ( 95%)

P value 0.003*

7 (50.0) 28 (15.0) 16 (24.2)

1 0.17 0.40

27 (20.7) 24 (17.5)

1 0.81

33 (19.5) 8 (18.1) 10 (18.5)

1 0.91 0.93

41 (18.1) 10 (24.4)

1 1.45

22 (18.8) 29 (19.3)

1 1.03

29 (18.0) 21 (22.1)

1 1.29

47 (19.5) 4 (19.0)

1 0.97

0.05 : 0.56 0.09 : 1.09 0.49 0.43 : 1.49 0.97 0.38 : 2.15 0.42 : 2.05 0.34 0.65 : 3.21 0.91 0.55 : 1.91 0.42 0.68 : 2.42 1.00 0.31 : 3.02

* chi-square of tendency.

REFERENCES [1] [2] [3] [4]

Alvardo R, Vera AC, Rojas M, Olea E, Monardes J, Neves E, Perucca E. Eventos vitales, soporte social y depresión en el postparto. Rev Psiquiatr 1994;11:121-6. Affonso DD, DE AK, Horowitz JA, Mayberry LJ. An international study exploring levels of postpartum depressive symptomatology. J Psychosom Res 200;49:207-16. Beck CT. Predictors of postpartum depression: na update. Nurs Res 2001;50:275-5. Beck AT, Ward CH, Mendelson M, Mock J, Nerbaugh J. An inventory for measuring depression. Arch Gen Psychiatry 1961;4: 561-71.

Post-Partum Depression: Prevalence and Demographic… [5] [6]

[7] [8] [9] [10] [11]

[12] [13]

[14]

[15]

[16] [17] [18] [19] [20] [21] [22] [23]

219

Beck AT, Steer RA, Garbin MG. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clin Psychol Rev 1988;8:77-100. Beck CT, Garble RK. Comparative analysis of the performance of the Postpartum Depression Screening Scale with two other depression instruments. Nurs Res 2001;50:242-50. Bergant AM, Heim K, Ulmer H, Illmensee K. Early postnatal depressive mood: associations with obstetric and psychological factors. J Psychosom Res 1999;46:391-4. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of 10 item Edinburgh Pos-Natal Depression Scale. Br J Psychiatry 1987;150:782-6. Cruz EBS, Simões GL, Faisal-Cury. Rastreamento da depressão pós-parto em mulheres atendidas pelo Programa de Saúde da Família. RBGO 2005;27(4):181-8. Faisal-Cury A, Menezes PR. Depressão pós-parto: o papel do obstetra. FEMINA 2005; 33(2):135-40. Faisal-Cury A, Tedesco JJA, Kahhale S, Zugaib M, Menezes PR. Postpartm depression: in relation to life events and patterns of coping. Arch Womens Ment Health 2004;7:123-31. Gennaro S. Pospartal anxiety and depression in mothers of term and preterm infants. Nurs Res 1988;37:82-5. Glasser S, Barell V, Shoham A, et al. Prospective study of postpartum depression in an Israeli cohort: prevalence, incidence and demographic risk factors. J Psychosom Obstet Gynaecol 1998;19:155-64. Gorenstein C, Andrade L. Validation of Portuguese version of the Beck Depression Inventory and the state-Trait Anxiety Inventory in Brazilian subjects. Braz J Med Biol Res 1996;29:453-7. Gotlib IH, Whiffen VE, Mount JH, Milne K, Cordy NI. Prevalence rates and demographic characteristics associated with depression in pregnancy and the postpartum. J Consult Clin Psychol 1989;57:269-74. Hannah P, Adams D, Lee A, GloverR V, Sander M. Links between early-postpartum mood and postnatal depression. Br J Psychiatry 1992;160:777-80. Harris B, Huckle P, Thomas P, Johns S, Fung H. The use of rating scale to identify postnatal depression. Br J Psychiatry 1989;154:813-7. Horowitz JA, Goodman J. A longitudinal study of maternal postpartum depression symptoms. Res Theory Nurs Pract 2004;18:149-63. Kendall PC, Hollon SD, Beck AT, IngramM RE. Issues and recommendations regrading use of the Beck Depression Inventory. Cognit Therapy Res 1987;11:289-9. Lee DT, Yip AS, Chiu HF, Leungty, Chung TK. Screening for postnatal depression: are specific instruments mandatory ?. J Affect Disord 2001;63:233-8. Lee DT, Yip AS, Chan SS, Tsui MH, Wong WS, Chung TK. Postdelivery screening for postpartum depression. Psychosom Med 2003;65:357-61. Lee TS, Yip ASK, Chiu HFK, Leung TYS, Chung TKH. A psychiatric epidemiological study of postpartum chineses women. Am J Psychiatry 2001;158:220-6. Nettelbladt P, Uddenberg N, Englesson I. Marital disharmony four and half years postpartum. Effects on parent-child relationships and child development. Acta Pschiatr Scand 1978;58:201-212.

220

Alexandre Faisal-Cury and Paulo Rossi Menezes

[24] O'Hara MW, Schlechte JA, Lewis DA, Varner MW. Controlled prospective study of postpartum mood disorders: psychological, environmental, and hormonal variables. J Abnorm Psychol 1991;100:63-73. [25] O’Hara MW, Swain AM. Rates and risks of postpartum depression: a meta analysis. Int Rev Psychiat 1996,8:37-45. [26] O’Hara MW, Zekoski EM. Postpartum depression: a comprehensive review. In Motherhood and Mental Illness 2: Causes and consequences. Kumar and Brockington eds. Wright. London. 1988. [27] Pfost KS, Stevens MJ, Lum CU. The relationship of demographic variables, antepartum depression, and stress to postpartum depression. J Clin Psychol 1990;46:588-92 [28] Philipps LH, O’Hara MW. Prospective study of pospartum depression:41/2 year follow-up of women and children. J Affect Disord 1994;31:67-74. [29] Seguin L, Potvin L, St.Denis M, Loiselle J. Socio-environmental factors and postnatal depressive symptomatology: a longitudinal study. Women Health 1999;29:57-72). [30] postpartum among low socioeconomic status women. Birth 1999;26(3):157-62. [31] Silva VA, Moraes-Santos AR, Carvalho MS, Martins MLP, Teixeira NA. Prenatal and postnatal depression among low income Brazilian women. Braz J Med Biol Res 1998;3:799-804. [32] Sinclair D and Murray L. Effects of postnatal depression on children`s adjustment to school. Br J Psychiatry. 1998;172:58-63; Murray L and Cooper P. Effects of postnatal depression on infant development.Arch Dis Child 1997;77: 99-101. [33] Skazufka EV. Prevalência da depressão pós-parto e fatores associado sem mães que deram à luz em um hospital universitário do município de São Paulo. São Paulo, 2000. 66 p. Dissertação de Mestrado. Departamento de Medicina Preventiva da Faculdade de Medicina da USP. [34] Stata (1997). Stata User's guide. Release 5. Texas. [35] Stowe ZN and Nemeroff CB. Women at risk for postpartum-onset major depression. Am J Obstet Gynecol 1995;173:639-45. [36] Stuart S, Couser G, Schilder K, O’Hara MW, Gorman L. Postpartum anxiety and depression: onset and comorbidity in a community sample. J Nerv Ment Dis 1998;186:420-4. [37] US Department of Health and Human Services. Healthy People 2010. Vol II, 2nd ed. Mental Health and Mental Disorders. www.healthypeople.gov. Acessado em 29/06/05. [38] Verdoux H, Sutter AL, Glatigny-Dallay E, Minisin A . Obstetrical complications and the development of postpartum depressive symptoms: a prospective survey of the Matquid cohort. Acta Psychiat Scand 2002;106:212-9. [39] Wang SY, Jiang XY, Jan WC, Chen CH. A comparative study of postnatal depression and its predictors in Twain and China. Am J Obstet Gynecol 2003;189:1407-12. [40] Acog. American College of Obstetricians and Gynecologists. Depression in women. Acog.182. Washington, DC. 1993. [41] Watson JP, Elliott SA, Rugg AJ, BroughDI: Psychiatric disorder in pregnancy and the first postnatal year. Br J Psychiatry 1984;144:453-62 [42] Gorman LL, O’Hara MW, Figueiredo B, Hayes et al. Adaptation of the Struictured clinical Interview for DSM-IV Disorders for assessing depression in women during pregnancy and post-partum across countries and cultures. Brit J Psychiatry 2004; 184 (suppl.-46):17-23.

Post-Partum Depression: Prevalence and Demographic…

221

[43] Dietrich AJ, Williams JW, Ciotti MC, Schulkin J et al. Depression care attitudes and practices of newer obstetrician-gynecologists: A national survey. Am J Obstet Gynecol 2003;189:267-73. [44] Eberhard-Gran M, Eskild A, Tambs K et al. Depression in postpartum and nonpostpartum women: prevalence and risk factors. Acta Psychiatr Scand 2002:106:42633. [45] Gale S, Harlow BL. Postpartum mood disorders: a review of clinical and epidemiological factors. J Psychosom Obstet Gynecol 2003;24:257-66. [46] Teissedre F, Chabrol H. A study of the Edinburgh Pos-Natal Depression Scale (EPDS) in 859 mothers: detecton of mothers at risk for postpartum depression. Encephale 2004;30(4):376-81 [47] Glasser S, Barell V, Shoham A, Ziv A, Boyko V, Hart S. Prospective study of postpartum in an Israeli cohort: prevalence, incidence and demographic risk factors. J. Psychosom. Obstet. Gynecol.,1998;19:155-164. [48] Sugawara M, Sakamoto S, Kitamura T, Toda MA, Shima S. Structure of depressive symptoms in preganancy and the postpartum period. J. Affec.Disorders 1999; 54:161-9. [49] Pop VJM, Essed GGM, Geus CA, Son MMV, Komproe IH. Prevalence of postpartum depression-or is it post-puerperium depression?.Acta Obstet Gynecol Scand 1993;72:354-8. [50] Georgiopoulos AM, Bryan TL, Yawn BP, Houston MS, Rummans TA, Therneau TM. Population-based screening for postpartum depression. Obstet Gynecol 1999;93:653-7. [51] Chung TKH, Lau TK, Yip ASK , Chiu HFK, Lee DTS. Antepartum depressive symptomatology is associated with adverse obstetric and neonatal outcomes. Psychosom Med 2001;63:830-34.

INDEX A aberrant, 141 abnormalities, x, 39, 61, 67, 72, 141, 142, 152 abortion, 217 abstinence, 175, 177, 179, 183, 187, 188, 189, 190, 193, 194 abusive, 205 academic, x, 37, 75, 77, 79, 80, 87, 89, 91, 92, 103, 108 academic performance, 37, 79, 87 academic success, 79 access, 130, 140 acculturation, 14, 32, 37 accuracy, 34, 127, 132, 215 achievement, 89 acid, 41, 42, 44, 48, 55, 56, 57, 58, 59, 63, 64, 65, 66, 69, 70, 71, 72 activation, 52, 58, 131, 132, 137, 141, 142, 151, 152, 153, 160, 161 acute, 48, 58, 65, 145, 152, 161, 205 acute coronary syndrome, 48, 65 adaptation, 32, 37 addiction, 193 Addiction Severity Index (ASI), 178 adipose, 48, 65 adipose tissue, 48 adjustment, 33, 56, 169, 220 administration, 57, 70, 72, 78, 80, 94, 150, 151, 152, 160, 178, 199 adolescence, 11, 14, 28, 32, 33, 35, 37, 174, 207 adolescent female, 203 adolescent patients, 48 adolescents, 34, 37 adult, ix, 3, 9, 11, 15, 31, 32, 33, 35, 37, 41, 68, 133, 157, 169, 207 adult population, 41

adulthood, 11, 15, 28, 29, 32, 33, 34, 36, 38, 52, 58, 174, 200, 201, 202, 203, 207 adults, 3, 4, 7, 13, 25, 34, 37, 41, 49, 58, 60, 70, 71, 97, 133, 154, 156, 161 adverse event, 50 advertising, 131, 133 aetiology, 164, 165 affect, 79 affective disorder, 49, 68, 159, 160, 161 African American, 178 afternoon, 21 age, ix, 3, 4, 8, 13, 15, 16, 17, 24, 25, 28, 29, 34, 35, 39, 50, 56, 64, 78, 79, 82, 125, 126, 137, 139, 155, 156, 158, 159, 165, 178, 183, 200, 202, 212, 213, 214 ageing, 63, 64 agent(s), 54, 59, 151, 156, 159 age-related, 82 aggression, 61, 77, 78, 87, 89, 202 aggressive behavior, 55, 78, 79, 89 aging, 36, 131, 153 aging process, 153 agonist, 156 agoraphobia, 49 air, 94 Alaska, 44, 96, 99 Alaska Natives, 99 alcohol, xii, 40, 92, 177, 178, 180, 183, 208, 211, 213 alcohol abuse, 40 alcohol use, 178, 183 alcoholism, 192 alien, 23, 26, 136, 137 allele(s), 154, 156 alpha, 4, 16, 42, 52, 95, 181 alpha-linolenic acid, 42 alternative, 12, 52, 63, 136, 145, 171 alternative medicine, 52

224

Index

alternatives, 11, 21 alters, 157 Alzheimer, 56, 57, 68, 69, 70, 136, 146, 148, 155, 159 American Heart Association, 41, 42 American Indian(s), 96, 99, 130 American Psychiatric Association, 174, 192, 198, 200, 205, 206, 207 amino acid, 153 amphetamine(s), 152, 157, 158, 160, 183 amygdala, 160 amyloid, 56, 70 amyloid precursor protein, 56 analysis of variance, 173 anger, 199 animal models, 51, 58, 151, 156 animal studies, 151, 153, 156 animals, 47, 174 anisotropy, 146 anorexia nervosa, 7, 49, 66 ANOVA, 25, 95, 181, 184 anoxia, 56 antagonist, 156 antagonists, 156 antarctic, 50 antecedents, 206 anterior cingulate cortex, 152, 161 antibody, 151 anticonvulsants, 152 antidepressant, 50, 51, 151, 153, 157, 160 antidepressant medication, 50, 157 antidepressants, 52, 67, 150, 156 anti-inflammatory, 52 antioxidants, 54, 56, 67, 68, 69 antipsychotic drugs, 54 antipsychotics, 54, 150, 152 antisocial, xii, 68, 89, 145, 173, 174, 175, 191, 192, 193, 194, 198, 203 antisocial behaviour, 68 antisocial personality disorder (ASPD), xii, 173, 174, 175, 176, 177, 178, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 203 anxiety, 4, 6, 47, 51, 52, 66, 137, 138, 145, 164, 169, 171, 182, 212, 216, 219, 220 anxiety disorder, 164 anxiolytic, 55 apathy, 141, 145 aphasia, 136, 141, 142, 144, 145 apoptosis, 61, 70 appendix, 76, 77, 80, 81, 82, 83, 85, 86, 87, 88, 89, 94, 96 appetite, 215 apples, 138

application, 195 apraxia, 136, 137, 138, 141, 142, 144 arachidonic acid, 46, 48, 53, 58, 59, 60 archeology, 33 argument, xii, 35, 164, 165, 173, 189, 190 Aristotelian, 19 Aristotle, 17, 120 articulation, 137 artistic, 12 Asia, 64 Asian, 154, 155 assault, 77, 85, 86, 92, 93, 97, 101, 105 assaults, 85, 97 assessment, 132, 146, 166, 193, 197, 200, 201 assignment, 175, 178, 190 assimilation, 15 association, 174, 185 associations, xi, xii, 82, 135, 167, 211, 219 asthma, 58 astrocytes, 145 Athens, 34 Atlantic, 44 atmosphere, 6 ATPase, 62 atrophy, 137, 140 attacks, 85, 97 attention, x, 2, 20, 39, 52, 58, 60, 61, 70, 71, 72, 75, 120, 121, 129, 130, 136, 139, 144, 145, 146, 212 attention deficit hyperactivity disorder (ADHD), 58, 59, 60, 61, 64, 71, 72 attitudes, 2, 7, 8, 10, 213, 221 atypical, 54 Australia, 163, 165, 170 authenticity, 38 authority, 31, 174 autism, 58, 59, 60, 61, 70, 71, 161 autistic spectrum disorders, x, 39 autonomic, 136 autonomy, 35 autopsy, 136 availability, 42, 52, 92, 190 averaging, 4, 28 avoidance, x, 75, 77, 79, 87, 88, 91, 92, 193 avoidance behavior, x, 75, 77, 87, 88, 91, 92 awareness, 11, 13, 19, 59, 138, 143, 165

B babies, 4, 214, 215, 216 background information, 178 background noise, 125 barbiturates, 180 barrier, 62

Index basal ganglia, 136, 143, 144 battery, 15, 122, 137 Beck Depression Inventory (BDI), xii, 3, 211, 213, 214, 215, 216, 219 behavior, x, 10, 14, 18, 19, 32, 51, 59, 60, 71, 75, 78, 79, 81, 82, 87, 88, 89, 92, 132, 141, 174, 175, 176, 179, 192, 193, 194, 198, 199, 208 behavior therapy, 51 behavioral change, 192 belief systems, 26 beliefs, 10, 22, 32, 37, 52, 165, 189 beneficial effect, 40, 41, 194 benefits, 51, 55 benzodiazepine(s), 177, 180, 191 beta, 52, 58, 70 bias, 169, 198 bifurcation, 20 bilateral, 136 binding, x, 40, 52, 55, 67, 150, 160 biochemical, 40, 142 biological, 40, 61, 121, 153 biological processes, 61 biosynthesis, 49 bipolar, xi, 46, 49, 50, 59, 66, 68, 71, 149, 153, 154, 157, 158, 159, 160, 161 bipolar disorder, xi, 46, 50, 59, 66, 68, 71, 149, 153, 154, 157, 158, 159, 160, 161 bipolar illness, 161 birth, xii, 56, 163, 164, 206, 211, 213, 214, 215, 216, 217, 218 birth weight, xii, 211, 213, 214, 215, 216, 217, 218 black, 43, 201 Black students, 76, 81 Blacks, 198 bleeding, 42 blood, 48, 55, 60, 61, 65, 69, 124, 153 blood flow, 61 blood plasma, 69 blood pressure, 124 body dissatisfaction, 2, 3, 4, 7 body image, ix, 1, 3, 4, 6, 7 body mass index (BMI), 2, 5, 6 body schema, 143 body shape, ix, 1 body size, 2, 4, 6, 8 body temperature, 120, 124, 131 body weight, 55, 57 boils, 131 bone, 44 bonus, 179 borderline, xii, 50, 57, 66, 197, 198, 199, 200, 201, 203, 206, 207, 208, 209

225

borderline personality disorder, xii, 50, 66, 197, 199, 200, 206, 207, 208, 209 Boston, 33, 38 boys, 59, 71, 76, 78, 80, 81, 87 bradykinesia, 137 brain, x, xi, 39, 41, 46, 48, 49, 52, 53, 55, 57, 58, 59, 62, 63, 64, 66, 67, 68, 69, 70, 72, 121, 131, 135, 137, 142, 143, 146, 149, 150, 151, 153, 156, 157, 158, 159, 160, 161 brain-derived neurotrophic factor (BDNF), xi, 52, 67, 70, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161 brain development, 46, 68 brain functions, 142 brain growth, 46 brain structure, 66 Brazil, 212, 213, 215 Brazilian, 154, 219, 220 breaches, 201 breakdown, 49, 53, 55, 60, 68 breast, 213, 214, 216, 218 breast feeding, 212, 216, 218 Brief Psychiatric Rating Scale, 55 British, 117, 133, 171, 208 broad spectrum, ix buffer, 36 bulimia, 2, 7, 8 bullies, 82, 83, 89 bullying, x, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 93, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108 Bureau of the Census, 96 burglary, 92

C calcium, 55, 68 California, 36, 43, 177 cAMP, 153, 159, 160 Canada, 36, 37 Canberra, 64 candidates, 177 cannabinoids, 180 capacity, 58, 142 capsule, 50 carbohydrates, 138 carbon atoms, 44, 45 cardiovascular, x, 40, 41, 42, 48, 63 cardiovascular disease, 41, 42, 48 caregivers, 137, 138 caretaker, 203 case study, 49 caspase(s), 58, 70

226

Index

catalysts, 205 catholic, 214 Catholic, 217 causal inference, x, 75, 80, 84 causality, x, 75, 80, 89 causation, 40, 47 cell, x, 40, 51, 53, 55, 58, 62, 67, 70, 143, 145, 153, 157, 158, 182, 191 cell body, 62 cell line, 157, 158 cell membranes, 53 cell signaling, 55 cellular telephones, 125 Census, 92, 96 central city, 96 central nervous system (CNS), x, 39, 40, 51, 52, 62, 68, 160, 184, 185, 206 cerebellum, 143 cerebral cortex, 148 cerebrovascular diseases, 69 certainty, 31 certificate, 179 cesarean section, 216 chaos, 22 chaotic, 205 chemical, 205 chemical reactions, 205 chemicals, 52 chemokines, 67 Chicago, 35, 37, 38, 117 child development, 32, 219 child maltreatment, 208 childbirth, 47, 64 childhood, x, xii, 34, 58, 61, 73, 75, 78, 154, 157, 161, 174, 197, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209 childhood sexual abuse, xii, 197, 201, 202, 203, 207 children, 4, 7, 21, 22, 32, 37, 41, 58, 59, 60, 61, 63, 70, 71, 72, 73, 77, 78, 154, 158, 201, 205, 206, 213, 217, 220 China, 48, 64, 212, 220 Chinese, 154 cholesterol, x, 40, 48, 51, 55, 64, 67 chromosome, 136, 145, 153 chronic, 41, 55, 58, 67, 150, 152, 157, 160, 161, 198, 199 chronic disorders, 41 circadian, 132 circadian rhythms, 132 civil action, 206 classes, 21, 87, 88, 91, 123, 124, 165, 171 classification, 79, 85, 93, 167, 198 classified, 96, 213

clients, 175, 176, 178, 183, 191, 194 clinical, x, xii, 15, 40, 48, 49, 52, 54, 60, 61, 62, 65, 67, 136, 141, 142, 145, 146, 147, 148, 153, 156, 160, 178, 197, 199, 200, 203, 208, 215, 216, 220, 221 clinical diagnosis, 147 clinical judgment, 216 clinical presentation, 136, 146, 153, 199 clinical symptoms, 48, 65 clinical syndrome, 136 clinical trials, 60 clinically significant, 171 clinician, 146, 200 clinicians, 164, 170, 171, 176, 191, 197, 198, 201 clinicopathologic, 147 clinics, 177, 178, 216 cloning, 159 clozapine, 54 cluster, 92 clustering, 203 clusters, 92 cocaine, xii, 173, 174, 175, 176, 177, 178, 180, 181, 183, 184, 186, 187, 188, 189, 190, 191, 192, 193, 194 cocaine abuse, 176, 193 cocaine use, 173, 174, 175, 176, 177, 178, 181, 183, 186, 187, 188, 189, 190, 191, 192, 194 Cochrane, 55, 68 codes, 97 coding, 16, 153, 155, 156 cognition, ix, 9, 35, 36, 70, 141, 142, 161 cognitive, xii, 11, 13, 14, 28, 29, 31, 32, 33, 35, 36, 37, 38, 51, 56, 57, 59, 68, 69, 121, 122, 131, 136, 137, 141, 145, 146, 147, 155, 161, 173, 175, 176, 179, 193, 194, 200, 201, 206, 212 cognitive abilities, 28, 31, 131 cognitive ability, 13, 137 cognitive alterations, 59 cognitive behavioral treatment (CBT), 173, 176, 177, 178, 179, 180, 181, 182, 184, 187, 188, 189, 190 cognitive deficits, 59, 136 cognitive development, 11, 33, 35, 37 cognitive function, 57, 68, 131, 155 cognitive impairment, 56, 69, 137, 141, 147 cognitive performance, 155 cognitive research, 33 cognitive style, 201 cognitive tasks, 131 cognitive tool, 29 cognitive-behavioral therapies, 200 coherence, 10, 14, 17, 18 cohort, 47, 63, 73, 198, 215, 219, 220, 221 collisions, 14

Index Colorado, 117 colors, 97 Columbia University, 37 combined effect, 124 commerce, 213 communication, xi, 135, 142 communities, 175 community, 78, 194, 195, 198, 220 comorbidity, 207, 208, 209, 220 complement, xii, 123, 163 complementary, 52 complexity, ix, 9, 10, 11, 17, 25, 29, 31, 36, 38, 51 compliance, 54 complications, 212, 213, 216, 218, 220 components, 14, 20, 22, 26, 27, 28, 40, 46, 51, 59, 95, 120, 146, 200 composite, 145 composition, 55, 57, 65, 66, 69 comprehension, 37, 139, 140, 142 compulsion, 138 compulsive behavior, 142 computer(s), 124, 131, 200 concentration, 57, 89, 139, 150 conception, 10 conceptualization(s), 9, 11, 13, 14, 15, 16, 35, 78, 207 concrete, 13 conditioning, 176 conduct, 192 confabulation, 145 confidence, 168, 213, 214, 216 confidence interval(s), 213, 214, 216 conflict, 14, 20, 22, 34, 128, 129 confounders, 56 confrontation, 89 congruence, 14, 20 connectivity, 61 consciousness, 12, 35 consensus, 159 consent, 4, 142, 178 consilience, 38 construction, 11, 12, 14, 20, 26, 33, 37, 85, 93 consumers, 47 consumption, ix, 39, 40, 41, 46, 47, 55, 56, 57, 60, 62, 63, 64, 67, 73 contaminants, 42 content analysis, 16 context, 77, 78 context-dependent, 26 contingency, xii, 173, 175, 176, 193, 194 continuing, xi, 135 control, x, 18, 33, 50, 57, 60, 62, 64, 67, 69, 75, 80, 84, 124, 129, 130, 138, 139, 142, 144, 148, 150,

227

153, 154, 156, 158, 160, 173, 175, 176, 177, 180, 181, 184, 186, 187, 189, 190 control condition, 173, 175, 176, 177, 184, 186, 187, 189, 190 control group, 50, 60, 67, 138, 139, 175, 176, 186 controlled, 50, 51, 55, 61, 66, 67, 71, 72, 154, 171 controlled studies, 50 controlled trials, 55 conversion, 40, 41, 44, 48, 60 coping, 118, 163, 167 coping strategy, 164 corn, 40, 54, 63 coronary heart disease, 41, 42 corpus callosum, 143 correlation(s), 6, 24, 28, 29, 40, 46, 48, 49, 53, 60, 131, 158, 201, 203 correlation coefficient, 6 cortex, 55, 57, 58, 62, 142, 143, 144, 146, 147, 151, 152, 160 cortical, 136, 137, 142, 143, 146, 147, 148, 151, 152, 153, 158 cortical abnormalities, 136 cortical neurons, 151, 158 corticobasal degeneration (CBD), 135, 136, 137, 138, 141, 142, 144, 145, 146, 147 corticospinal, 143 Costa Rica, 160 counseling, 174, 175, 179 couples, 158, 165, 166, 214 covariate, 125, 126 craving, 138 CREB, 150, 152, 158, 160 credit, 3, 4, 123 Crete, 48, 65 crime(s), 77, 78, 80, 85, 86, 92, 93, 95, 97, 98, 101, 105, 174, 176, 192 criminal activity, 175 criminal behavior, 174, 176 criminal justice, 178 critical thinking, 34 critical value, 95 criticism, 26 cross-sectional, x, 29, 47, 75, 80, 87, 213, 216 cross-sectional study, 47, 213, 216 crying, 87, 138, 164 cues, 121, 133 cultural, 9, 10, 14, 15, 21, 22, 23, 25, 26, 29, 32, 33, 37, 47, 53, 171 cultural differences, 53 culture, ix, 9, 13, 14, 16, 21, 22, 25, 28, 31, 34 cyclic AMP, 150 cycling, 154 cytochrome, 62

228

Index

cytochrome oxidase, 62 cytokine(s), x, 40, 52, 61, 67, 72

D daily living, 139 data collection, 85, 115, 178, 180 data set, 82 death(s), 42, 48, 151 decisions, 92, 119, 120 deduction, 11 defects, 137, 144 defenses, 201, 204 deficiency, 51, 53, 58, 59, 61, 62, 65, 67, 72, 156 deficit(s), x, 39, 54, 56, 58, 59, 70, 71, 72, 136, 141, 145, 148, 156 definition, xi, xii, 3, 31, 78, 85, 93, 119, 191, 197, 199 degenerative disease, 156 degree, 11, 13, 14, 15, 17, 18, 20, 21, 22, 24, 28, 137, 168, 169, 191, 202 delivery, 168, 175, 179, 190, 212, 213, 215, 216, 218 delta, 44, 48 delusions, 52, 137, 138, 141, 150 demand, 165, 193 dementia, x, 39, 42, 56, 57, 68, 69, 136, 137, 141, 144, 145, 146, 147, 148 demographic, xii, 4, 6, 123, 125, 178, 181, 182, 183, 185, 211, 212, 213, 216, 219, 220, 221 demographic characteristics, 183, 216, 219 demographic data, 4, 125 demographics, 178 denial, 201 density, 62, 137, 157, 196, 205 Department of Education, 115, 116 Department of Health and Human Services, 193 Department of Justice, 81, 83, 84, 86, 88, 90, 91, 100, 101, 102, 103, 104, 105, 106, 107, 108, 116, 117 dependent variable, 125, 126, 127, 129, 130 depolarization, 153 depressed, 47, 48, 49, 50, 51, 64, 65, 67, 150, 151, 153, 157, 164, 168, 171, 172, 212, 216 depression, x, xii, 3, 7, 36, 40, 46, 47, 48, 49, 50, 51, 52, 61, 64, 65, 66, 71, 137, 138, 141, 145, 150, 151, 152, 157, 158, 160, 164, 165, 169, 170, 171, 172, 211, 212, 213, 215, 218, 219, 220, 221 depressive disorder, 62, 66 depressive symptomatology, 215, 218, 220, 221 depressive symptoms, 46, 48, 49, 50, 51, 52, 64, 67, 212, 216, 220, 221 deprivation, 61 derivatives, 41, 46, 55, 61

desipramine, 158 detection, 199 developed countries, 53 developing brain, 70 developing countries, ix, 39, 53 developmental change, 12 developmental disabilities, 71 developmental disorder, 72 developmental psychology, 32, 33 diabetes, 40, 55 diagnostic, xii, 51, 59, 163, 164, 165, 166, 169, 178, 191, 197, 198, 199, 212 Diagnostic and Statistical Manual of Mental Disorders, 174, 192, 198 diagnostic criteria, xii, 59, 163, 169, 199, 212 Dialectical-Deconstructive, ix, 9, 18, 22 diastolic blood pressure, 125 dichotomy, 78 diet(s), ix, 39, 41, 42, 44, 47, 48, 49, 52, 53, 54, 56, 58, 63, 70, 151 dietary, 40, 41, 47, 49, 55, 56, 57, 60, 61, 62, 64, 67, 69, 73, 138 dietary intake, 47, 55, 60, 64, 73 dietary supplementation, 60, 67 dieting, 2 differential diagnosis, 142, 148 differentiation, 14, 33 direct measure, 183 disability, 40, 70, 150 discharges, 144 discourse, 10, 26, 33, 140 disease model, 69 diseases, 42, 161 disequilibrium, 155, 158 disinhibition, 138, 141, 145 disorder, x, xii, 2, 6, 7, 39, 46, 54, 56, 58, 70, 71, 72, 122, 136, 145, 146, 149, 150, 154, 157, 159, 164, 173, 174, 176, 183, 191, 192, 193, 194, 197, 199, 203, 204, 207, 208, 220 disposition, 55 disruptive behaviours, 72 dissatisfaction, 2, 4, 7 distress, 164, 165, 169, 170, 171 distribution, 23, 24, 137, 154, 156, 181 diurnal, 122, 133 diversity, 25, 31, 156 division, 198 docosahexaenoic acid (DHA), 40, 41, 42, 44, 46, 47, 48, 49, 50, 51, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 66, 67, 68, 69, 70, 71, 72 dominance, 82 dopamine, 58, 62 dopaminergic, 142

Index dosage, 54 double bonds, 45 download, 95 drinking, 174 drug abuse, 174, 192, 193, 213 drug abusers, 192 drug addict, xii, 211 drug addiction, xii, 211 drug dependence, 40 drug treatment, xii, 160, 173, 178, 189, 190, 192 drug use, 175, 176, 178, 179, 182, 191, 194, 195 drug-related, 176 drugs, 46, 50, 54, 66, 92, 157, 191 dry, 43, 44, 46 DSM-II, 194, 199, 207, 208 DSM-III, 194, 199, 207, 208 DSM-IV, 164, 174, 177, 178, 191, 192, 198, 199, 203, 209, 220 dual task, 130 dualism, 11 duality, 23 duration, xi, xii, 55, 59, 119, 120, 121, 123, 128, 129, 130, 131, 132, 133, 152, 163, 165, 166, 167, 169, 170, 179, 202, 213, 216 dysarthria, 137 dysfunctional, 202, 205 dyskinesia, 54 dyslexia, x, 39, 58 dysmenorrhea, 66 dystonia, 136

E eating, ix, 1, 2, 6, 7, 49, 53, 150, 198, 199, 200, 207, 208 eating disorders, ix, 1, 2, 7, 198, 199, 200, 207, 208 ecological, 64 economic, 47, 215, 216 economic status, 216 eczema, 58 education, 5, 9, 13, 15, 21, 25, 34, 68, 95, 116, 130, 139, 165, 177, 181, 183, 185, 196, 205, 213, 214, 215 educational background, 15 educational settings, 131 educators, x, 75, 77, 79, 89, 91 efficacy, xii, 54, 173, 176, 183, 189, 192 ego, 10, 33, 36 eicosanoid, 46 eicosapentaenoic acid, 47, 50, 62, 65, 67 elaboration, 13, 142 elderly, 3, 48, 56, 57, 65 elderly population, 3

229

election, 190 electrical, 143 eligibility criteria, 178 elongation, 44, 45 embryogenesis, 156 emergence, 193 emotion(s), 13, 15, 34, 52 emotional, 14, 47, 52, 174, 200, 202, 203, 205, 216 emotional abuse, 202, 203 emotionality, 204 empathy, 138, 145, 204 employment, 83, 178, 183, 213 encoding, 136, 141, 144, 200 encouragement, 179 endocrine, 61 endogenous depression, 65 endothelial cells, 153 energy, 145, 150, 215 engagement, 198 England, 133 English, 43, 165 enrollment, 177, 183 enteric, 72 enterocolitis, 61 entorhinal cortex, 152 envelope, 166 environment, xi, 3, 14, 18, 59, 70, 119, 121, 125, 207 environmental, 11, 17, 47, 56, 59, 71, 122, 128, 170, 220 environmental conditions, 47 environmental context, 170 environmental factors, 17, 56, 59, 220 Environmental Protection Agency (EPA), 40, 41, 42, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 59, 60, 61, 62, 63, 66, 72 enzyme(s), 40, 55, 179 epidemiological, x, 40, 47, 49, 53, 59, 61, 62, 198, 219, 221 epidemiology, xii, 157, 197 epilepsy, 161 episodic, 129, 155 episodic memory, 129, 155 episteme(s), ix, 9, 10, 12, 13, 16, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31 epistemological, 9, 10, 11, 12, 13, 14, 15, 16, 22, 28, 29, 31, 32, 36, 38 epistemology, 9, 31, 32, 37 epithelial cells, 160 equilibrium, 20, 28 erythrocyte(s), 53, 54, 57, 65, 67, 69 erythrocyte membranes, 67, 69 escitalopram, 158 essential fatty acids, x, 40, 48, 52, 53, 54, 63, 68

230

Index

esters, 65 estimating, 121, 130 ethane, 60 ethical, 37 ethics, 14, 38 ethnic background, 154 ethnic groups, 32, 38 ethnicity, 78, 81, 104, 178, 183, 213 ethnocentrism, 38 etiology, 56, 59, 62, 207, 209 Europe, 41, 58, 63 European, 41, 44, 131, 154, 155 evening, xi, 119, 122, 123, 125, 126, 127, 128, 129, 131, 132, 133 evidence, 12, 14, 29, 36, 40, 52, 57, 58, 59, 62, 63, 67, 68, 71, 95, 121, 131, 133, 136, 137, 138, 141, 142, 143, 150, 153, 154, 157, 160, 177, 192, 201, 202 evolution, 32, 143, 144 exaggeration, 80 examinations, 136 excitotoxicity, 151, 158 exclusion, x, 75, 76, 78, 80 execution, 138, 142, 143, 144 exercise, 47, 52, 179 experimental condition, 175 experimental design, 80, 121, 129 expert(s), 41, 63, 73, 159, 174 exposure, 2, 21, 59, 62, 202 extracellular, 150, 158 extrapolation, 151 extrovert, 20 eye(s), 137, 139, 142, 143, 144, 147, 148 eye movement, 137, 139, 143, 144, 147

F fabric, 197 factorial, 126 failure, 204, 209 faith, 12, 33 false, 12, 21, 26, 52, 164, 169 familial, 150 family, x, xi, xii, 7, 22, 40, 52, 56, 60, 63, 82, 132, 146, 149, 150, 154, 155, 156, 159, 160, 163, 164, 165, 168, 169, 170, 196, 201, 202, 204, 205, 206, 212, 213 family environment, 7, 205 family history, 154, 155, 206, 212 family income, 213 family members, xii, 163, 168, 169 family support, 202 fat(s), 2, 47, 48, 53, 57, 68, 69, 121

fatherhood, 164, 171 fatigue, xii, 163 fatty acid(s), ix, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73 fax, 135 FDA, 72 fear, x, 2, 75, 77, 79, 87, 91, 92 fee, 178 feedback, 144 feeding, 166, 167, 168, 169, 213, 214, 216, 218 feelings, xi, 50, 87, 135, 150, 199, 201, 212 fees, 183 females, 121, 122, 123, 126, 129, 131, 132, 136, 137 feminist, 171 fetal, 62, 72 fetus, 48 fiber(s), 143, 152, 161 fibroblasts, 53, 67 first-time, 168 fish, ix, 39, 40, 41, 42, 46, 47, 50, 51, 56, 57, 61, 63, 69, 72 fish oil, x, 39, 40, 41, 46, 50, 51, 56, 61 fixation, 144 flexibility, 13 flow, 27 fluctuations, 128 fluid, 13, 138 focusing, xii, 85, 91, 163, 164, 169, 170 food, 41, 57, 60, 63, 69, 72, 138, 213 food intake, 138 Foucault, 10, 33 fragmentation, 22, 35 France, 57 freeze-dried, 43 frontal cortex, 62, 142, 144, 151, 152 frontal dementia, 145 frontal lobe, 136, 142 frontal-subcortical circuits, 141, 144 frontotemporal dementia, 136, 141 fruits, 57 fulfillment, 15

G G protein, 72 gait, 137 gangs, 76, 82, 91, 92, 97 gas, 57 gas chromatograph, 57 gastrointestinal, 61 gastrointestinal tract, 61

Index gender, xi, 13, 15, 16, 17, 25, 78, 119, 121, 123, 126, 128, 129, 131, 159, 183, 185 gender differences, 25, 121, 131 gender effects, 129 gender gap, 131 gene(s), 58, 59, 61, 70, 136, 150, 153, 154, 156, 159, 160, 161, 205 gene expression, 61, 150 generalization, 28, 31, 215 generation, 38 genetic, xi, 32, 49, 56, 59, 149, 154, 155, 156, 157, 158, 204 genetic alteration, 157 genetic factors, 49, 56 genetics, 150, 156, 203, 208 genome, 157, 160 genotype(s), 154, 155 geriatric, 7 girls, 76, 78, 80, 81, 121, 206 glial, 157 globus, 142, 145 glucocorticoids, 161 glucose, 55, 131 glucose metabolism, 131 glutamate, 151, 158 glutathione, 58 gnosis, 142 God, 22 gold standard, 142 goods and services, 175 government, 196, 205 grades, x, 75, 77, 78, 79, 80, 81, 89, 91, 93, 96, 98, 103, 108 grading, 146 graffiti, 92 Greenland, 47 group variance, 95 groups, 1, 4, 6, 10, 15, 16, 23, 24, 25, 28, 29, 35, 41, 51, 54, 69, 79, 92, 95, 125, 137, 153, 155, 170, 175, 179, 180, 184, 186, 187, 190, 191, 192 growth, 11, 12, 22, 29, 34, 35, 37, 52, 72, 150, 159 growth factor, 159 guidance, 116, 143, 147 guidelines, 14, 26, 159 guilt, 50 gynecologist(s), 212, 221 gyrus, 143

H habitat, 14 Haifa, 22 hallucinations, 52, 150

231

haplotype, 154, 156 haplotype analysis, 154 happiness, 172, 212 harassment, x, 75 harm, 88, 198, 199, 208 harmful, x, 75, 78, 156 Harvard, 2, 32, 33, 34, 35, 38, 50, 63, 124, 132, 207 hate, 92 health, 5, 41, 59, 71, 120, 124, 125, 126, 132, 165, 168, 169, 170, 176, 178, 190, 212, 213, 216 Health and Human Services, 193 health care, 216 health effects, 41 health information, 213 health insurance, 213 health problems, 59, 71 health services, 170, 212 health status, 178 hearing, 52, 139 heart disease, 42 heat, 44 height, 3, 139 helplessness, 150 hemisphere, 142 hemp, 40 heroin, 175, 181, 182, 183, 187, 188, 189, 190, 191 heterogeneity, 15, 156 heterogeneous, 14, 27, 215 heuristic, 32 high school, 21, 93, 183, 185 high-risk, 203 hippocampal, 68, 72, 151, 155, 157, 158 hippocampus, xi, 149, 151, 152, 156, 158, 159, 160, 161 Hispanic(s), 76, 81, 96, 99, 104, 178, 181, 183, 198 Hispanic origin, 96, 99 histological, 142 HIV, 193 homocysteine, 48, 65 homogeneity, 82 homogeneous, 21 hopelessness, 150 hormones, 121 Horne and Ostberg scale, xi, 119 hospital, 48, 138, 147, 165, 214, 215, 220 hospitalized, 203, 206 host, 201 hostility, 61 hot water, 180 household(s), xii, 78, 79, 82, 90, 92, 93, 94, 96, 99, 104, 163, 168, 201, 205 household income, 78, 82, 90, 94, 96, 99, 104 housing, 92

232

Index

human(s), x, 10, 12, 18, 33, 34, 35, 38, 39, 40, 41, 45, 48, 52, 56, 65, 72, 73, 120, 122, 131, 132, 142, 144, 148, 152, 153, 155, 156, 158, 159, 160, 161, 195, 201 human development, 33, 34, 35, 38 human sciences, 33 human subjects, 132 humanity, 22 hyperactivity, x, 39, 46, 58, 70, 71, 72, 152 hyperphosphorylated tau protein, 141 hyperphosphorylation, 58 hypothalamic-pituitary axis, 52 hypothalamus, 160 hypothesis, 10, 46, 56, 57, 67, 123, 128, 144, 151, 175, 184, 185, 190 hypothetico-deductive, 31

I identification, 37, 38 identity, xi, 10, 14, 15, 17, 18, 26, 27, 28, 36, 37, 38, 135, 199 illusion, 33, 133, 146, 198 images, xi, 7, 13, 135, 137 imaging, 49, 136 imbalances, 40 immigrants, 32 immigration, 171 immune function, 61 immunoreactivity, 151, 157 impairments, 141, 157 implementation, 64, 137, 141 impulsive, 55, 138, 139 impulsiveness, 145 impulsivity, 58, 132, 199, 200 in vitro, 58, 151 in vivo, 58 inactivation, 58, 148 inattention, 72 incentive(s), 13, 173, 174, 175, 176, 177, 178, 185, 189 incidence, ix, 39, 46, 47, 49, 53, 61, 97, 219, 221 inclusion, 214 income, 78, 82, 90, 94, 96, 99, 104, 214, 215, 217, 220 independence, 21 independent variable, 95, 185 India, 18 Indian(s), 67, 96, 99, 100 indicators, 82 Indicators of School Crime and Safety, 116 indirect effect, 52 individual differences, 121, 122, 132

induction, 56, 152 industry, 213 infancy, 9, 14, 33 infants, 42, 200 inferences, x, 75, 80, 84, 94 inflammation, 61 inflammatory, 52, 58 information processing, 34, 66, 120, 131 informed consent, 4, 178 ingestion, 47 inherited, 203, 204 inhibition, 131 inhibitor(s), 52, 151 inhibitory, 62 initiation, 179 injury(ies), 40, 70, 97 insight, 19, 138, 145, 174 insomnia, 49, 50, 215 instability, 199 instruments, xii, 211, 215, 219 insulin resistance, 56 insults, 56, 71 Integral-Inclusive, ix, 9, 17, 20, 22, 27, 29 integrated unit, 142 integration, 14, 15, 31, 36, 131 integrity, 62, 156 intellectual development, 37 intellectual functioning, 142 intelligence, 3, 37, 124, 133 intensity, 130, 131, 137 interaction(s), xi, 10, 11, 19, 22, 37, 59, 72, 78, 90, 119, 123, 126, 128, 130, 169, 184, 192, 206 interaction effect, 184 interest, x, 75, 80 interference, 48, 130, 132, 139 interferon, 52 interleukin, 52, 160 interleukin-1 (IL-1), 52 interleukin-8, 160 internal clock, 133 internal consistency, 18, 213 international, 53, 63, 218 interpretation, 13, 16, 18, 51, 80, 85, 93, 139 interrelationships, 8 interval, xi, 119, 125, 127, 129, 130 intervention, 1, 50, 57, 171, 175, 177, 180, 189, 190, 192 interview(s), ix, 9, 12, 13, 15, 16, 19, 25, 29, 76, 79, 92, 93, 164, 166, 168, 169, 178, 180, 187, 191, 199, 213, 214, 215 intimacy, 201 intravenous drug abusers, 192 introvert, 17

Index intuition, 12 investigations, 46 investigative, 59 ion channels, 61 ipsilateral, 143 irrationality, 27 irritability, 68, 141 ischaemic heart disease, 40 ischemic, 146 isolation, x, 75, 78, 164, 165, 202, 203 Israel, 9 Italy, 135

J Japan, ix, 39, 46, 72 Japanese, 48, 57, 65, 154, 155, 159, 160 Jerusalem, 36 Jews, 21 Judaism, 21, 22 judge, 120, 130 judgment, 34, 35, 131, 139 justice, 35, 178 justification, 12, 19, 34

K kappa, 160 kinase(s), xi, 58, 70, 149, 150, 157, 158, 159 knockout, 151 knowledge acquisition, 26 Korea, 46 krill, 50

L laboratory studies, 49 lack of confidence, xii, 163, 169 lactation, 41 laminar, 143 language, xi, 26, 33, 135, 138, 139, 140, 141, 142, 212 large-scale, 154 latency, 137, 143 late-onset, 56, 155, 159 laughing, 19 law(s), 14, 17, 18 lead, ix, 1, 2, 6, 19, 20, 62, 80, 87, 88, 93, 121, 136, 144 learning, 13, 21, 22, 41, 58, 59, 60, 66, 69, 70, 71, 72, 176 learning difficulties, 72

233

learning disabilities, 58, 60 legal issues, 206 legumes, 43 lens, 23 lesions, 136, 142, 144, 148 leukotrienes, 46 levodopa, 57, 58, 69, 136 Lewy bodies, 136 libido, 51 life cycle, 14, 208 life experiences, 13 lifestyle, 47 ligand, 156 likelihood, 169 limitation(s), x, 6, 12, 47, 75, 80, 93, 139, 169, 189, 191, 197, 215 linear, xii, 12, 29, 95, 211, 214 linguistic, 10, 138, 139, 140 linguistic task, 140 linguistically, 139 linkage, 153, 155 links, 33, 40, 61, 143, 145 linoleic acid, 56, 60 linolenic acid, 40, 41, 46, 59, 60 lipid(s), 51, 56, 58, 59, 63, 67, 69, 72 lipid metabolism, 59 lipoprotein, 56 literature, xii, 7, 11, 14, 78, 86, 120, 123, 129, 141, 166, 176, 177, 183, 192, 193, 197, 201, 212 lithium, 46, 150, 151, 152, 153, 155, 157, 158, 159, 161 Lithium, 151, 157, 158, 160 liver, 40 location, 4, 19, 26, 146 locus, 142, 153, 156, 157, 161 locus coeruleus, 142 London, 32, 146, 148, 171, 220 longitudinal study, 34, 35, 37, 219, 220 long-term, 53, 119, 120, 150, 151, 152, 161, 207 Los Angeles, 173, 177, 192, 193 losses, xi, 135, 164 love, 23 low power, 176 low-income, 212 lung cancer, 48, 65 lying, 174 lymphoblast, 159

M magnet, 137 maintenance, 66, 150, 156, 173, 174, 175, 176, 177, 178, 180, 190, 193, 194

234

Index

major depression, x, 39, 46, 48, 64, 66, 67, 72, 150, 220 major depressive disorder, 40, 48, 50, 51, 66, 150 males, 47, 48, 121, 122, 123, 129, 131, 132, 136, 198 malignant, 203 maltreatment, 205, 206 management, x, xii, 40, 41, 47, 62, 66, 133, 173, 175, 176, 193, 194, 207 mania, 46, 50, 150, 152, 156, 158, 161 manic, 50, 150, 153, 156, 157, 159 manic episode, 153, 157, 159 manic-depressive illness, 50 marijuana, 183 marital status, 213 marriage, 168, 212, 213, 216, 217 Maryland, 190 maternal, 66, 171, 213, 219 maternal mood, 171 mathematical, 202 matrices, 138, 139, 148 matrix, 14, 25, 55, 72 maturation, 11, 14, 153 meanings, 14, 20, 27, 28 measurement, 33, 48, 133, 191 measures, 2, 7, 51, 78, 79, 83, 92, 132, 175, 181, 191, 199 medical school, 132 medication, 50, 53, 54, 55, 66, 164, 178, 208 medications, xi, 3, 6, 51, 52, 54, 149 medicine, 52 membership, 6 membranes, x, 40, 46, 51, 65, 67, 68 memory, xi, 52, 58, 120, 122, 123, 128, 129, 130, 132, 133, 135, 136, 141, 142, 144, 145, 158 memory performance, 122 men, xii, 6, 47, 50, 56, 67, 68, 131, 150, 163, 164, 165, 166, 167, 168, 169, 198, 208 menstruation, 50 mental arithmetic, 140 mental development, 11, 41 mental disorder, 41, 46, 55, 160, 169, 205 mental health, 36, 40, 47, 63, 64, 169, 178, 198 mental health professionals, 63 mental illness, 40, 164, 208 mental life, xi, 135 mental retardation, 58, 60, 61, 71 mental state, 50 mercury, 72 messages, 158 messenger RNA, 159 messengers, x, 40, 52 meta-analysis, 55, 123, 131, 172, 212, 215, 216, 220 metabolic, 41, 44, 64

metabolism, 41, 44, 52, 53, 55, 60, 61, 68, 70, 71, 120, 148 metabolite(s), 177, 180 methamphetamine, 180 methodological dilemmas, 133 mice, 56, 151, 152, 158 microenvironment, 55 middle-aged, 4 mildly depressed, 49 milk, 47, 64, 213 milligrams, 180 Millon Clinical Multiaxial Inventory, 194 minerals, 68 Mini-Mental State Examination, 139 Minnesota, 70 minority, 37, 200 mirror, 201 miscarriage, 213 misinterpretation, 201 mitochondria, 62 modalities, 139 modality, 139, 190 models, 11, 12, 13, 21, 29, 33, 57, 95, 131, 133, 152 moderates, 191 modulation, x, 40, 158 money, 76, 79, 81, 83, 84, 86, 88, 90, 91, 96, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 168, 175 monitoring, 83 monkeys, 69, 142, 148 monoamine, 62 monocyte, 67 monolithic, 9 Monolithic-Monoformal, ix, 9, 16, 17, 21, 25 monotherapy, 51 Montana, 146 mood, xi, xii, 4, 40, 46, 47, 49, 50, 55, 61, 64, 149, 150, 151, 152, 154, 156, 157, 158, 159, 161, 163, 170, 171, 199, 212, 219, 220, 221 mood change, 46, 64 mood disorder, xi, xii, 40, 46, 55, 149, 151, 152, 154, 157, 158, 161, 163, 220, 221 mood states, 150 moral development, 35 moral reasoning, 10 morality, 36 morals, 34 morbidity, 40, 49, 178 morning, xi, 119, 122, 123, 125, 126, 128, 129, 131, 133 morphemes, 140 morphological, 140 mortality, 40, 49

Index motherhood, 171, 172 mothers, xii, 47, 63, 64, 72, 163, 164, 167, 170, 171, 216, 219, 221 motion, 26, 27, 28, 143, 144 motivation, 78, 145, 177, 178, 190 motor activity, 58 motor area, 143 motor coordination, 139 motor skills, 121 motor vehicle theft, 92, 97 mouse, 56, 58, 67, 69, 70, 161 mouse model, 56, 58, 69, 70 movement, 27, 54, 143, 144, 145, 147, 148 movement disorders, 148 MRI, 49, 137, 140 mRNA, 52, 56, 151, 152, 153, 156, 158, 159, 160 multicultural education, 38 multiculturalism, 15, 38 multidimensional, 7, 139 multiplicity, 22, 27 multivariate, 185, 208 muscle(s), 121, 143 muscle mass, 121 music, xi, 135 mutation, 136, 146 myelination, 59, 61 myoclonus, 136

N narcotic, 177 nation, 78, 89, 92, 190 national, 53, 64, 79, 91, 92, 221 National Center for Education Statistics (NCES), 75, 92, 95, 98, 116 National Crime Victimization Survey (NCVS), 75, 76, 78, 79, 81, 83, 84, 85, 86, 88, 90, 91, 92, 93, 94, 95, 96, 97, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 115 National Institutes of Health, 193 natural, 32 neck, 143 necrosis, 150 needs, 174, 178 neglect, 203, 204, 205, 206 neonatal, 221 nerve(s), x, 39, 62, 71, 157, 159 nerve growth factor, 157, 159 nervous system, xi, 59, 70, 135, 159, 161 network, 11, 141, 142 neurobehavioral, 59, 194 neurobiological, 150 neurobiology, 161

235

neuroblastoma, 158 neurodegenerative diseases, x, 40 neurodevelopmental, ix, 39, 56, 59, 61, 62, 63, 64, 68, 71, 73 neurogenesis, 61 neurological deficit, 204 neurological disorder, 68 neuronal death, 150 neuronal degeneration, 69 neuronal survival, 70, 150 neurons, x, 40, 52, 56, 58, 62, 72, 143, 145, 148, 151, 153 neuropathological, 141 neuroplasticity, 156 neuroprotection, 158 neuroprotective, 58, 151 neuropsychiatric, ix, 39, 62, 63 neuropsychiatric disorders, x, 39 Neuropsychiatric Inventory, 138 neuropsychology, 133 neuroses, 65, 208 neurotic, 198 neurotoxic, 71 neurotoxicity, 58 neurotoxins, 62 neurotransmission, 61, 68 neurotransmitter(s), x, xi, 40, 52, 55, 61, 149, 150, 156 neurotrophic, xi, 52, 67, 149, 150, 157, 158, 159, 160, 161 neurotrophic factors, 150, 157, 159 New England, 132 New Jersey, 193 New York, 32, 33, 34, 35, 36, 37, 38, 117, 131, 132, 133, 147, 148, 193, 194, 207, 208 New Zealand, 46, 171 NMDA receptors, 70 non-invasive, 60 non-linear, 12 non-random, 60 nonsmokers, 49 nonverbal, 78 normal, x, 47, 53, 54, 56, 58, 60, 75, 124, 138, 140, 153, 156 normal children, 58 normalization, 48, 64 norms, 14, 21 North America, 41, 63, 71 Notre Dame, 36 nuclear receptors, 58 nuclei, 71, 142, 143 nucleus accumbens, 62 nursing, 72

236

Index

nutrient(s), 40, 41, 62, 64, 69 nutrition, 40, 49, 63, 73 nuts, 43

O obese, ix, 1, 4 ob-gyn, 212 objectivity, 36 observations, 136 obstetricians, 216 occipital cortex, 152 odds ratio, xii, 47, 211 odds ratio, 216 Office of Justice Programs, 116, 117 Office of Juvenile Justice and Delinquency Prevention, 117 Ohio, 34, 196, 197, 205 oil(s), x, 39, 40, 41, 42, 44, 49, 50, 52, 54, 57, 60, 61, 62, 63, 72, 73 old age, 4 olfactory bulb, 62 oligodendroglia, 145 olive oil, 50 omega-3, ix, x, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73 omega-6, ix, 39, 40, 41, 45, 46, 47, 48, 56, 57, 60, 61, 63, 72, 73 online, 144 open-field, 158 operant conditioning, 176 opiates, 175, 180, 183 opioid, 174, 175 opposition, 25 optical, 146 oral, 140 orbitofrontal cortex, 66 organ, 10 organic, 164 organism, x, 39, 120 organization, 2, 30, 121, 144, 145 orientation, 16, 23 outpatient, 193, 208 outpatients, 54, 198, 203, 206 oxidative, 58, 60, 70, 71 oxidative damage, 60, 70 oxidative stress, 70, 71 oxygen, 148

P pacemaker, 120 pacemakers, 132 Pacific, 44, 96, 99, 100 Pacific Islanders, 96, 99 pain, 138, 164 pairing, 185 pap, 73 paper, 64, 151, 170, 179 paradox, 26, 27, 172 paradoxical, 12, 27 parameter, 53, 62, 94 parental attitudes, 206 parent-child, 219 parenthood, 165, 171 parenting, 204 parents, x, xi, xii, 75, 77, 91, 163, 165, 168, 170, 204, 205 parietal cortex, 142, 144, 146, 148, 152 parietal lobe(s), 142, 143, 144, 146, 147 Paris, 200, 202, 204, 207 Parkinson, x, 39, 57, 69, 142 parkinsonism, 58, 136 passive, 87 pathogenesis, xi, 149, 150, 151, 153, 155, 156, 157 pathology, 56, 69, 136, 145, 200, 206 pathophysiological, 141, 150 pathophysiological mechanisms, 150 pathophysiology, 68, 150, 160 pathways, xi, 46, 141, 142, 143, 145, 149, 150, 156, 203, 205, 206 patients, xi, xii, 48, 49, 50, 51, 53, 54, 55, 57, 58, 59, 61, 63, 65, 66, 67, 68, 69, 72, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 150, 151, 152, 153, 154, 155, 156, 157, 160, 161, 173, 174, 175, 176, 177, 178, 179, 180, 182, 183, 184, 185, 187, 188, 189, 190, 191, 192, 193, 194, 198, 199, 200, 201, 203, 205, 206, 207, 209, 213, 216 peer support, 177 peer(s), 77, 78, 81, 91, 177 pellagra, 65 Pennsylvania, 32 peptide, 160 per capita, 46 perception, xii, 121, 131, 132, 133, 142, 143, 173, 189, 190 perceptions, ix, 1, 7, 8, 52, 79, 92, 165 performance, 3, 5, 41, 79, 87, 122, 128, 132, 138, 139, 155, 161, 173, 177, 179, 184, 185, 187, 189, 190, 191, 219 perinatal, 212, 216 peripheral, 152

Index permit, 94 peroxide, 58 personal, ix, xi, 9, 10, 13, 14, 15, 25, 34, 37, 135, 139, 190, 201, 212, 213 personal histories, 37 personal identity, xi, 135 personal responsibility, 201 personality, xii, 14, 21, 32, 34, 38, 122, 128, 132, 138, 169, 173, 174, 190, 191, 192, 193, 194, 198, 199, 200, 202, 203, 204, 206, 207, 208, 209 personality disorder(s), xii, 173, 174, 193, 194, 198, 200, 203, 204, 206, 207, 208, 209 personality traits, 14, 38, 191 perturbations, 61 pharmacological, 153 pharmacotherapy, 51, 68, 193 phenomenology, 148, 209 phenotype(s), 136, 137, 138, 141, 145, 147, 150, 154, 155, 156, 158 Philadelphia, 32, 146, 147, 206, 208 philosophical, 10, 12 philosophy, 10, 165 phone, 135 phonological, 140 phospholipids, 48, 49, 50, 53, 55, 57, 60, 65, 67, 72 phosphorylation, 151 physical abuse, 202, 203, 205 physical aggression, 78 physical health, 168 physicians, 212 physiological, 120, 121, 122, 124, 156 Piagetian, 35 pilot study(ies), 50, 51, 65, 66, 67, 208 placebo, 49, 50, 51, 54, 55, 60, 61, 66, 67, 71, 72 planar, 146 planning, 144, 145, 216 plasma, 47, 48, 54, 57, 59, 60, 67, 153, 159 plasma levels, 48, 153 plasma membrane, 67 plasticity, 150, 156 platelet(s), 55, 68, 153, 159 play, x, xi, 39, 46, 47, 56, 59, 62, 121, 142, 143, 149, 154, 155, 156, 204, 212 pleasure, 201 plurality, 18, 22, 28 Poland, 39 polarity, 18, 19 police, 76, 79, 83, 91, 92, 97, 100, 105, 199 policymakers, 92 polymorphism(s), xi, 56, 149, 153, 154, 155, 156, 158, 159, 160, 161 polypeptide, 52

237

polyunsaturated fatty acid(s) (PUFA), x, 39, 40, 47, 53, 56, 57, 58, 59, 60, 63, 65, 69, 70, 71 pons, 143 poor, 3, 49, 58, 59, 89, 138, 139, 142, 145, 168, 200, 212 population, 1, 2, 7, 24, 40, 47, 49, 64, 65, 69, 92, 94, 146, 154, 155, 159, 180, 198, 201, 202, 212, 215 population size, 92 portfolio, 17, 20 positive correlation, 15, 153 positive reinforcement, 193 positron emission tomography, 148 posterior cortex, 142 postmortem, 147, 151, 152 postpartum depression (PPD), xii, 46, 47, 64, 66, 171, 172, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221 postpartum period, 212, 215, 221 post-traumatic stress, 198, 206, 207 posture, 136, 143 potassium, 62 power(s), 20, 78, 124, 131, 155, 156, 176, 191 pragmatic, 32 praxis, 32, 138, 142 precipitation, 205 prediction, 207, 209 predictors, 7, 185, 220 predisposing factors, 204 pre-existing, 181, 182, 185, 189 preference, 22, 146 pregnancy, 41, 47, 48, 49, 51, 59, 62, 64, 65, 73, 166, 170, 212, 214, 215, 216, 219, 220 pregnant, 62, 72, 168, 215, 216 premenstrual syndrome, 50, 66, 132 preparation, 66, 72 prepubertal, 158 presenilin 1, 70 pressure, 124 preterm infants, 219 prevention, x, 1, 7, 40, 41, 42, 66, 68, 165, 194 preventive, 92, 165 primacy, 35 primate, 57, 146 priming, 205 prisoners, 68 private, xii, xiii, 76, 82, 91, 211, 212, 213, 214, 215, 216 private sector, 212 probability, 29, 94, 95 problem behaviors, 77 problem-solving, 32, 33, 142 procedures, 4, 94, 124, 138, 165, 172, 178, 179

238

Index

production, 45, 52, 56, 116, 120, 123, 125, 129, 130, 137, 139, 141, 150, 160 professions, 15 program, 124, 131, 175, 176, 178, 183, 190 programming, 142, 144, 145 progressive, 12, 136, 137, 141, 143, 144, 145, 147 progressive supranuclear palsy, 136, 147 proinflammatory, 52, 67 promote, 183 property, 77, 81, 83, 84, 85, 86, 88, 90, 91, 93, 97, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108 prophylaxis, 155 prosocial behavior, 179 prostaglandins, 46 protection, 47, 63, 69, 77, 89, 90, 91, 103, 108, 151 protective factors, 207 protein(s), 51, 56, 58, 68, 150, 151, 152, 156, 157, 158, 159, 160 protocol, 180 provocation, 87 proximal, 143 psychiatric diagnosis, 215 psychiatric disorder(s), 49, 61, 183, 191, 198, 205 psychiatric patients, 38, 198, 213 psychiatrist, 54 psychiatry, 55, 64, 68, 208 psychological, 10, 12, 14, 28, 32, 33, 36, 38, 52, 77, 89, 116, 122, 128, 130, 131, 133, 176, 200, 201, 202, 204, 206, 215, 216, 219, 220 psychological development, 36 psychological phenomena, 10 psychological stress, 52 psychological variables, 216 psychology, ix, xi, 3, 4, 10, 32, 33, 34, 35, 36, 38, 119, 123, 124, 132, 193 psychometric properties, 3, 4, 169 psychopathology, 54, 55, 146, 201, 202, 204, 205, 207, 209 psychoses, 65 psychosis, 67, 145, 150, 198 psychosocial, xii, 59, 163, 205, 216 psychosocial stress, 205 psychotherapy, 174, 193, 195, 200 psychotic, 49, 52, 155 public, 21, 41, 76, 82, 91, 165, 176, 190, 212, 215 public health, 176, 212 public policy, 190 public schools, 82 puerperium, 212, 215, 221 pulses, 120 punishment, 179 pyramidal, 62, 136, 143 pyramidal cells, 143

Q qualifications, 136 qualitative research, 165, 172 quality of life, 58 quantitative research, 169 questioning, 13 questionnaire(s), xii, 4, 57, 79, 122, 124, 131, 132, 211, 213, 214

R race, 76, 78, 81, 96, 99, 104, 178, 183, 185 radical, 22, 33 rain, 157 random, 94, 175, 180 random assignment, 175 range, 3, 4, 15, 18, 20, 31, 41, 46, 59, 60, 79, 119, 124, 137, 138, 140, 153, 167, 176, 214 rape, 77, 85, 86, 92, 93, 101, 105 rapid-cycling, 154 rating scale, 6, 54, 219 ratings, 54, 131 rat(s), 56, 66, 69, 70, 132, 143, 151, 152, 153, 156, 157, 158, 159, 160, 161 reactive oxygen species, 58 reactivity, 199 reading, x, 58, 75, 80, 84, 138, 139, 140 reading comprehension, 140 reagent, 180 reality, 9, 13, 14, 17, 23, 27, 37, 52 reasoning, 10, 11, 13, 16, 19, 20, 33, 35, 36, 37, 137, 141 recall, 79, 80, 93, 122, 131 receptors, 51, 56, 58, 150, 157, 159 recognition, 164 recollection, 165, 204 reconcile, 20, 21, 27, 160 reconciliation, 14, 34 recurrence, 46 red blood cell(s), 48, 54, 59, 60, 64, 65, 67 reduction, xi, 26, 48, 49, 51, 54, 55, 135, 137, 138, 151, 178 reference frame, 144, 146 reflection, 17, 20, 23 refugees, 32 regional, 148, 157 regression(s), 47, 54, 174, 181, 185, 214 regression analysis, 47, 54 regular, 21, 27, 168, 170 regulation(s), 10, 46, 58, 61, 70, 150, 156, 201 reinforcement, 136, 175, 193, 194

Index rejection, 76, 78, 80, 87 relapse, 51, 61, 176, 177, 207 relapses, 72 relationship(s), x, xi, xii, 18, 22, 27, 29, 30, 34, 46, 47, 48, 75, 77, 78, 80, 82, 84, 95, 133, 149, 155, 164, 169, 174, 175, 176, 177, 192, 197, 199, 201, 202, 203, 206, 207, 208, 212, 216, 219, 220 relatives, 138 relativity, 31, 38 relevance, 61, 171, 179, 205 reliability, 3, 4, 16 religion(s), 22, 213 religious, 13, 22 religious beliefs, 13 remission, 65, 209 replication, 154, 160 repression, 201 reproduction, 120, 129, 130, 137, 138 research, ix, 1, 2, 4, 6, 7, 12, 13, 14, 15, 16, 25, 29, 31, 32, 37, 38, 40, 49, 52, 54, 56, 57, 60, 63, 64, 68, 77, 79, 80, 81, 82, 87, 89, 91, 121, 122, 123, 128, 129, 130, 150, 165, 166, 170, 174, 176, 177, 178, 189, 191, 192, 195, 199, 201, 207, 212, 214, 215 researchers, ix, x, 1, 14, 49, 50, 61, 75, 78, 82, 92, 164, 170, 204 residential, 82, 175 resilience, 35, 156, 202 resolution, 78 resources, 121, 131 responsiveness, 136, 175 restoration, 61 retaliate, 87 retaliation, 89 retardation, 71 retention, 175, 183, 193 retina, 41, 46, 70 Rett syndrome, 71 returns, 120 rhythms, 48 rights, 174 rigidity, 136 risk(s), x, xii, 1, 2, 6, 7, 39, 40, 41, 46, 47, 48, 49, 51, 52, 56, 57, 59, 64, 68, 69, 84, 88, 161, 172, 193, 201, 202, 204, 206, 207, 211, 212, 214, 215, 216, 219, 220, 221 risk assessment, 59 risk factors, xii, 40, 41, 206, 207, 211, 212, 216, 219, 221 Rita, 135 robberies, 97 robbery, 77, 85, 86, 92, 101, 105 rodent(s), xi, 149, 152, 158

239

Rosenberg Self-Esteem Scale, 2 rural, 82

S saccades, 143, 144 saccadic eye movement, 143 safety, 52, 97, 98 sample, xi, 15, 24, 79, 82, 85, 92, 94, 95, 96, 153, 154, 155, 156, 163, 164, 165, 166, 168, 169, 170, 175, 176, 177, 178, 179, 180, 182, 183, 189, 191, 192, 198, 203, 213, 215, 216, 220 sampling, 92, 94, 95, 198 sampling error, 94 Sao Paulo, 213 saturated fat, 52, 53, 57 savings, 179 Scalar, 132 schizophrenia, x, 39, 40, 42, 52, 53, 55, 56, 59, 61, 67, 68, 71, 72, 150, 155, 161 schizophrenic patients, 53, 54, 55, 67, 155 scholastic achievement, 10 school, x, 15, 21, 22, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 120, 178, 181, 183, 185, 220 school community, 78 School Crime Supplement (SCS), 76, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 100, 101, 102, 103, 104, 105, 106, 107, 108 science, 10, 121 scientific, 10, 12, 13, 35, 41, 49, 57 scientific knowledge, 10, 12 scientists, 49, 121, 122, 191 scores, 2, 3, 4, 16, 23, 24, 25, 28, 29, 51, 54, 57, 125, 126, 137, 141, 184, 215 scripts, 13 seafood, ix, 39, 46, 47, 62, 73 search, 15, 43, 44 seasonal affective disorder, 46, 47 seasonality, 48 secondary education, 95 secondary students, 37 secret, 202 secretion, 151, 153, 156, 158 security, x, 75, 76, 80, 83, 84, 91, 97, 100, 105 seed, x, 39, 43 segregation, 143 seizure(s), 157, 158, 160, 161 selective serotonin reuptake inhibitor, 150 selectivity, 131, 145

240

Index

self, 9, 13, 26, 32, 34, 36, 38, 79, 80, 85, 89, 92, 93, 103, 108, 116, 167, 174, 178, 182, 183, 190, 191, 192, 195, 199, 208 self-care, 49 self-concept, 14, 29, 33, 36, 201 self-control, 17 self-definition, 15 self-destructive behavior, 208 self-esteem, 2, 15, 37 self-identity, 33 self-knowledge, 36 self-mutilation, 199 self-rated health, 3, 6, 126 self-reflection, 14 self-regulation, 199 self-report(S), xii, 7, 15, 47, 64, 79, 80, 89, 126, 163, 168, 169, 170, 178, 183, 191, 195, 199, 215 self-understanding, 33 semantic, 122, 131, 140, 142, 148 semantic memory, 122, 131 semi-structured interviews, 199 sensation, 136 sensations, 9 sensitivity, 142, 158 sentences, 140 separation, 204 septum, 152, 159 sequelae, 208 series, 4, 6, 46, 49, 66, 80, 93, 94, 95, 125, 142, 174, 181, 185 serotonergic, 61, 65 serotonin, 52, 62, 67 serum, 48, 55, 59, 60, 65, 67, 71, 153, 156, 157, 161 services, xii, 163, 165, 170, 175, 178, 180, 212 severity, 48, 49, 52, 58, 67, 153, 159, 203, 213 sex, 3, 78, 90, 96, 99, 104, 131, 133, 199, 213, 216, 218 sex differences, 131, 133 sexual abuse, xii, 197, 200, 201, 202, 203, 207, 209 sexual assault, 77, 85, 86, 92, 93, 97, 101, 105 sexual behavior, 174 sexual contact, 97 sexual orientation, 201 sexuality, 216 shape, ix, 1, 4, 179 shares, 10, 121 shellfish, 47 shock, 159 short-term, 57, 119, 120 siblings, 155 side effects, 50, 55, 62 sign, 11 signal transduction, 68, 159

signaling, x, xi, 40, 52, 55, 58, 61, 68, 70, 72, 149, 150, 151, 153, 156, 158 signaling pathway, xi, 58, 149, 151, 158 signals, 87, 158 significance level, 95 signs, 27, 97, 136, 137, 138, 141, 145, 146, 174 similarity, 13, 25 single nucleotide polymorphism, 153 singular, 22, 26, 27, 28, 30 sites, 151 skills, 11, 13, 33, 35, 58, 138, 200 skills training, 200 skin, 67 sleep, 51, 60, 61, 120, 132, 150, 164, 168, 169, 170, 171 sleep deprivation, 132, 164 smokers, 47 smoking, 40, 49, 53 social, x, 6, 7, 13, 14, 18, 19, 20, 21, 32, 33, 34, 36, 38, 47, 49, 75, 76, 77, 78, 80, 82, 87, 89, 90, 122, 131, 137, 145, 176, 191, 192, 198, 199, 212, 216, 218 social behavior, 13 social cognition, 34 social control, 145 social development, 77 social environment, 18 social exclusion, 76, 78, 80 social factors, 47 social group, 6 social influence, 7 social influences, 7 social isolation, x, 75, 78 social learning, 176 social phobia, 49 social psychology, 32, 36 social relationships, 77 social roles, 33 social sciences, 34 social skills, 212 social structure, 82 social support, 212, 216 social theory, 36 social withdrawal, 137 socialization, 6 socially, 4, 6, 79, 87 society, 19, 38, 120 socioeconomic status, 82, 220 sociological, 121 Socrates, 120 sodium, 151 software, 94, 214 solutions, 139

Index somatomotor, 143 somatosensory, 143 sorority women, ix sorting, 56, 68 soybean, 42 spatial, 70, 132, 138, 139, 141, 143, 146 spatial frequency, 132 specialists, 146 species, 44, 47 specificity, 28 spectrum, 70, 71, 77 speech, 137, 140, 141, 144 speed, 120 spelling, 58 spiritual, 20, 35 sporadic, 68 spouse, 120 sprouting, 152, 161 St. Louis, 148 stability, 14, 17 stabilizers, 152, 156, 158 stabilizing drugs, 50 stages, 12, 15, 29, 33, 35, 37, 38, 77, 150 standard error, 81, 94, 95, 104, 105, 106, 107, 108 standards, 13 statistical analysis, 16 statistical inference, 182 statistics, 94, 95 staurosporine, 70 sterile, 137 stimulant, 179, 180 stimulus, 13, 15, 139, 143 stomach, 3, 4 storage, 62, 142, 144 strain(s), 152, 158, 164 strategies, xii, 7, 36, 63, 131, 137, 141, 174, 176, 193, 194, 197, 200 stratification, 155, 156 strength, 190, 191 stress, 15, 36, 40, 47, 52, 59, 78, 151, 169, 170, 199, 201, 205, 220 stressful life events, 216 stressors, xii, 122, 128, 163, 165, 166, 167, 168, 169, 170 striatum, 145, 152 student behavior, 79 student characteristics, x, 75, 99, 104 student populations, 8 students, x, xi, 38, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 119, 123 subgroups, 1, 95

241

subjective, 12, 26, 38, 121, 124, 131, 132, 133 subjective well-being, 38 subjectivity, 36 substance abuse, xii, 173, 174, 175, 176, 189, 190, 191, 192, 193, 194, 198, 199, 200, 203 substance use, 178, 183, 199 substantia nigra, 145 substitutes, 11 substrates, 205 suburban, 82 sucrose, 52 suffering, 42, 57, 145, 168, 171, 200 suicidal, 51, 150, 155, 158, 199, 207 suicidal behavior, 158 suicidal ideation, 51 suicide, 47, 48, 64, 65, 200, 202, 212 suicide attempts, 200, 202 summer, 48 sunflower, 40, 63 sunlight, 46 supervision, 42, 76, 83, 84, 91, 97, 100, 105 supervisor, 179 supplemental, 93 supplements, 42, 55, 60, 61, 62, 63 suppression, 201 surprise, 20 survey design, x, 75, 80 survival, xi, 52, 149, 150, 158 surviving, 143 survivors, 65 susceptibility, 154, 156, 157, 160 Sweden, 117 switching, 180 symbolic, 11 symbols, 9, 97 sympathy, 145 symptomology, 54 symptom(s), 3, 4, 7, 48, 49, 50, 52, 53, 58, 59, 60, 61, 65, 67, 72, 148, 150, 153, 156, 159, 174, 198, 199, 200, 201, 203, 205, 213, 215, 219 synaptic plasticity, xi, 149, 150 synaptic transmission, 61 syndrome, 50, 54, 60, 65, 71, 136, 137, 141, 145, 197, 201 syntactic, 17, 140 synthetic, 28 systematic, 10, 12, 31, 32, 143 systems, xi, 10, 11, 12, 14, 21, 22, 23, 26, 27, 30, 56, 61, 149, 150, 176, 206 systolic blood pressure, 125

242

Index

T Taiwan, 149 tardive dyskinesia, 54 target stimuli, 144 targets, 78, 143 task interference, 130 taste, 55 tau, 58, 70, 136, 146 tau pathology, 70 Taylor series, 94 technician, 179 technology, 49 teens, 32 Tel Aviv, 9 temperature, 124, 125, 180 temporal, 55, 120, 141, 144, 151 tension, xii, 19, 163, 165, 168, 169 tertiary education, 165 test procedure, 180 test-retest reliability, 169 Texas, 220 thalamus, 142, 143, 144, 145 thalidomide, 59 theft, 77, 85, 86, 92, 101, 105 theology, 38 theoretical, 29, 35 theory, 10, 11, 12, 13, 14, 28, 32, 33, 34, 35, 37, 38, 121, 130, 133, 158, 172, 192 therapeutic, 50, 66, 72, 151, 152, 155, 156, 175, 194 therapeutic agents, 151 therapeutic community, 194 therapeutics, 160, 206 therapists, 174 therapy, xi, 38, 50, 149, 152, 156, 174, 175, 176, 179, 189, 193, 194, 208 thinking, 11, 12, 32, 33, 34, 52, 150 threat(s), 87, 97, 199, 202 threatened, 80, 93 threatening, 83 thrombotic, 69 thromboxanes, 46 time, x, xi, xii, 2, 3, 4, 7, 14, 17, 19, 22, 26, 29, 55, 59, 62, 66, 75, 77, 78, 80, 87, 93, 95, 98, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 136, 137, 139, 140, 151, 154, 163, 164, 165, 169, 170, 179, 180, 181, 183, 186, 187, 188, 189, 190, 198, 200, 209, 212, 216 time frame, 169 time periods, xi, 119, 181, 186, 187, 188, 189, 190 timetable, 138 timing, 132 tissue, 48, 49

toddlers, 200 tolerance, 25 total cholesterol, 55 total energy, 41 toxic, 59 toxicology, 183 toxin, 69 training, 179 trait anxiety, 4 traits, 13, 14, 17, 18, 19, 20, 30, 37, 191, 198 trajectory, 11, 12, 29 transcription, 58, 70, 150 transcription factors, 58, 150 transduction, xi, 149, 150 transfer, 48, 144 transformation(s), 11, 14, 26, 27, 30, 144 transgenic mouse, 70 transition, 78, 82, 165, 171 trauma, xii, 197, 200, 201, 202, 203, 204, 205, 206 traumatic brain injury, 70 traumatic events, 206 travel, 18 treatment programs, 175, 177, 190, 192 treatment-resistant, 50, 65, 194 tremor, 136 trend, xii, 2, 55, 70, 95, 129, 151, 211, 214 trial, 50, 51, 61, 66, 71, 171, 183 triggers, 120 triglyceride(s), 42, 55 truancy, 87, 88 trucks, 121 tumor necrosis factor, 52 tumour, 150 turnover, 49, 66 two-way, 173 type II diabetes, 56 tyrosine, 58, 150, 157 tyrosine hydroxylase, 58

U UK, 54, 154, 158 uncertainty, 22 undergraduate, 15 undifferentiated, 26 unification, 144 unilateral, 136 United Nations, 73 United States, 41, 63, 82, 160 univariate, xii, 211, 214 urban, 78, 82, 90 urbanicity, 78, 82, 90 urinalysis, 180, 185, 187, 188, 189, 195

Index urinary, 136, 180 urine, 175, 176, 177, 179, 180, 183, 186, 187, 190 US Department of Health and Human Services, 72, 220 US dollar, 214 USDA, 43, 44 users, 179

vitamins, 67, 68 vocabulary, 3, 6, 124, 125 voice, 32, 34 vouchers, 175, 179, 185 vulnerability, 59 vulnerability to depression, 59 Vygotsky, 12, 28, 38

V validation, 7, 213 validity, 3, 4, 22, 26, 28, 166, 169, 195 valproic acid, 59 values, 4, 13, 14, 21, 22, 26, 41, 60, 95, 120, 140, 167, 168, 216 variability, 94, 146 variable(s), x, xi, xii, 4, 6, 75, 78, 80, 85, 93, 94, 95, 96, 97, 98, 119, 121, 127, 128, 129, 130, 141, 175, 185, 197, 201, 202, 203, 205, 211, 212, 213, 214, 215, 216, 217, 218, 220 variance, 95, 173, 190 variation, 38, 48, 64, 65, 94, 95, 154, 155, 158 vascular, 68, 146, 148, 153 vascular dementia, 68, 146, 148 vegetable oil, 63 vegetables, 57 vegetarians, 47 ventricle, 137 ventricular, 49 verbal abuse, 202, 203, 207 versatility, 26 vesicle, 62 veterans, 208 victimization, x, 75, 76, 77, 78, 79, 80, 83, 84, 85, 92, 93, 97 victims, 76, 77, 78, 79, 80, 81, 82, 83, 85, 86, 87, 88, 89, 90, 91, 92, 93, 201, 202, 204, 207 violence, 55, 68, 87, 92, 174, 176 violent, 48, 55, 64, 65, 77, 84, 85, 86, 91, 93, 97, 101, 105, 176 violent behavior, 91 violent crime(s), 77, 85, 86, 93, 97, 101, 105 vision, 142, 144 visual, 41, 68, 121, 139, 142, 143, 144, 147 visual acuity, 41 visual area, 143 visual attention, 144 visuospatial, 141 vitamin E, 54, 55, 60

243

W war, 34 Warsaw, 39 Washington, 35, 63, 73, 116, 117, 192, 205, 207, 208, 209, 220 watches, 125 water, 47, 180 weapons, 77, 89, 90, 92, 97, 103, 108 web, 28, 95, 98, 120 wellbeing, x, 64, 75, 77 Western countries, 46 Western societies, ix, 39 white matter, 137, 143 winter, 46, 48 Wisconsin, 138, 139, 155 wisdom, ix, 9, 31, 35 withdrawal, 138, 178 wives, 212 women, ix, xii, xiii, 1, 2, 3, 4, 5, 6, 7, 8, 34, 47, 50, 51, 62, 66, 72, 131, 132, 150, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 198, 208, 211, 212, 213, 214, 215, 216, 219, 220, 221 words, 92 work, 179 working memory, 120, 132, 141, 142, 145, 148 workload, 132 work-related stress, xii, 163, 167, 170 World Bank, 63 World Health Organization (WHO), 40, 63, 73 World Wide Web, 131 worldview, 10, 14 writing, 139 written tasks, 140

Y yield, 16 young adults, 3, 4, 34