Advances in Psychology Research, Volume 60 [1 ed.] 9781612098128, 9781607418535

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Advances in Psychology Research, Volume 60, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook Central,

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Advances in Psychology Research, Volume 60, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook Central,

Advances in Psychology Research Series

ADVANCES IN PSYCHOLOGY RESEARCH, VOLUME 60

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

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.

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ADVANCES IN PSYCHOLOGY RESEARCH SERIES Advances in Psychology Research, v. 63 Alexandra Columbus (Editor) ISBN 978-1-60876-050-3 Advances in Psychology Research, v. 62 Alexandra Columbus (Editor) ISBN 978-1-60741-076-8 Advances in Psychology Research, v. 61 Alexandra Columbus (Editor) ISBN 978-1-60741-551-0 Advances in Psychology Research, v. 60 Alexandra Columbus (Editor) ISBN 978-1-60741-835-5 Advances in Psychology Research, v. 59 Alexandra Columbus (Editor) ISBN 978-1-60692-571-3 Advances in Psychology Research, v. 58 Alexandra Columbus (Editor) ISBN 978-1-60456-910-0 Advances in Psychology Research, v. 57 Alexandra Columbus (Editor) ISBN 978-1-60456-897-4 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

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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 60, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook Central,

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Advances in Psychology Research, Volume 60, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook Central,

Advances in Psychology Research Series

ADVANCES IN PSYCHOLOGY RESEARCH, VOLUME 60

ALEXANDRA M. COLUMBUS

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Science Publishers, Inc. New York

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Copyright © 2009 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.

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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 upon request ISBN 978-1-61209-812-8 (eBook)

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CONTENTS

Preface Chapter 1

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Chapter 2

ix Proteomic Research in Psychopharmacology and Biological Psychiatry Yuji Odagaki and Christoph W. Turck Psychosocial Adjustment among Caregivers Raising Children with High-Functioning Autism Spectrum Disorders (HFASDs) – An Application of the Double ABCX Model Gloria K. Lee,, Christine Berry-Kaizmien, Martin A. Volker, Christopher Lopata, Robert E. Nida, Marcus L. Thomeer, Jonathan D. Rodgers

Chapter 3

Motivation, Ability, and Task Strategy Use in Skill Acquisition Janice Langan-Fox and Michael J. Sankey

Chapter 4

Neuropsychology of the Sense of Agency. Theoretical and Empirical Contributions Michela Balconi

Chapter 5

Caffeine Consumption and Changes in the Function of Dopaminergic Transmission: Evidence of a Hyperdopaminergic State in Rats Subchronically Treated with Caffeine Nicola Simola, Annalisa Pinna, Elisabetta Tronci, Philip Seeman and Micaela Morelli

Chapter 6

Personality Traits and Lay Conceptions of Intelligence Tomas Chamorro-Premuzic

Chapter 7

Regulating the Expression Patterns of Bizarre Behavior: A Therapeutic Option for Amphetamine-type Drug-induced Stereotypy? Junichi Kitanaka, Nobue Kitanaka, Tomohiro Tatsuta, Yoshio Morita, Hiroshi Kinoshita and Motohiko Takemura

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37

59

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107

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viii Chapter 8

Contents Weight and Metabolic Status of Children and Adolescents Admitted to a Psychiatric Hospital: A Prospective Study Humberto Quintana and Grant Butterbaugh

Chapter 9

Cognitions Related to the Performance of a Review Uwe Hentschel and Dan Pokorny

Chapter 10

Screening for Prodromal Symptoms in a High School Community Population in Mexico City Ana Fresan and Rogelio Apiquian

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Index

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155 167

177 187

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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. Chapter 1 - Over the past two decades genomic research in psychiatry has resulted in the identification of a number of candidate susceptibility genes and chromosomal loci associated with specific physiological and pathophysiological conditions. However, so far these data have not revealed much insight into mental disorder etiology. Likewise, no significant progress has been made in diagnostic and therapeutic procedures for these disorders. In order to better understand dynamic molecular processes in complex diseases like psychiatric disorders, the identification of pathways and signal transduction cascades holds great promise for unraveling functional networks pertinent to disease etiology. This information is best acquired on the protein level. Proteomics, the large-scale analysis of proteins with the help of high-throughput technologies like mass spectrometry, has become an important field of research in the medical sciences to gain information about the molecular mechanisms involved in the pathophysiology of diseases. At the same time, it holds great potential for new drug development in the post-genomic era. In contrast to proteomic efforts for somatic diseases including cancer and metabolic disorders, proteomics of the central nervous system is still in its infancy. Particularly in the area of psychiatric disorders only limited information has become available from neuroproteomics studies. In the present chapter, general aspects of proteomic approaches for psychopharmacology and psychiatry research are reviewed with regard to their strengths and limitations. Subsequently, neuroproteomics data that have been reported on “functional” mental disorders, such as schizophrenia and affective disorders, as well as effects of psychopharmacological medication will be reviewed. It is author belief that despite a number of limitations, the application of proteomic technologies will pave the way for a better understanding of mental and behavioral abnormalities, more accurate diagnosis and re-categorization of psychiatric disorders, and novel therapeutic approaches. Chapter 2 - This chapter investigated the psychosocial adjustment of caregivers of children with HFASDs, using the double ABCX model. Sixty-six caregivers completed a packet of survey that measured parenting stress, coping styles, resource availability, and psychosocial adjustment (depression, anxiety, and life satisfaction). Results indicated that 36% of the caregivers displayed clinical depression. Utilizing regression analysis, the three predictor variables (stress, support, and coping) accounted for 39.7% of the observed variance in depression. In addition, three percent of the caregivers experienced significant levels of

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Alexandra M. Columbus

anxiety, with stress as a significant predictor of anxiety, explaining 14.3% of the observed variance. Two of the three predictor variables were significant in predicting life satisfaction, with 28.4% of total variance in life satisfaction. Chapter 3 - Individual differences are fundamental to performance. Prior research has highlighted the importance of individual differences in skill acquisition through the use of ability-performance frameworks. However, studies in this area have largely neglected the influences of motivation and strategy use. The current chapter questioned the role of motivation, ability, and strategy in learning a new skill, and whether these variables interacted to influence performance. An existing model was used to test the relationships between ability, motivation and performance in skill acquisition, with effective strategy use proposed as a mediating variable. A sample comprising both students and employees was administered a number of ability measures and then performed an adapted text-editing task. Results offered support for an interaction between motivation and ability, with motivation found to be most beneficial to low-ability individuals. In addition, effective strategy use was found to play a mediating role in both motivation-performance and ability-performance relationships. Chapter 4 - The investigation of the sense of agency is an increasingly prominent field of research in psychology as well as cognitive neurosciences alike. How do author know that author am the person who is moving? The main question that the chapter tries to answer is about the causal explanation of action and about the mechanism of conscious control of action implicated on both normal and pathological cases. The neuroscience of action shows the existence of specific cognitive processes allowing the organism to refer the cause or origin of an action to its agent. This sense of agency has been defined as the sense that author am the one who is causing or generating an action or a certain thought in my stream of consciousness. As such, one can distinguish actions that are self-generated from those generated by others, giving rise to the experience of a self-other distinction in the domain of action and thus contributing to the subjective phenomenon of self-consciousness. Theoretical and empirical implications of the sense of agency for consciousness, self-consciousness and action will be considered in the present chapter. The predominant account on explaining the sense of agency of author own actions is the ‘‘central monitoring theory” or ‘‘comparator model” that postulate a monitoring of central and peripheral signals arising as a consequence of the execution of an action. This theory holds that the (central) efferent signals at the origin of an action are matched with those which result from its execution (the reafferent signals) and that this comparison provides cues about where and when the action originated. Moreover, recent conceptual developments distinguished between different levels of the sense of agency: separating an implicit level of ‘‘feeling of agency” as opposed to an explicit level of ‘‘judgment of agency”. The first level is thought to be characterized by lower-level, pre-reflective, sensorimotor processes, and the second level by higher-order, reflective or belief-like processes. Sensorimotor processes thought to be characteristic for the feeling level may run outside of consciousness (but may be available to awareness). This is supported by empirical evidence that, for example, minor ‘violations of intended actions or action consequences (i.e., brief temporal delays in sensory feedback) do not necessarily enter awareness, while neural signatures of such violations can be observed. New and prospective data from neuropsychological filed are proposed in the chapter, which allow for an integrated view on the sense of agency.

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Preface

xi

Chapter 5 - The existence of extensive interactions between the psychostimulant caffeine and the dopaminergic transmission has been clearly demonstrated by means of both neurochemical and behavioral experiments. In light of the fact that caffeine is widely consumed and considering the major role played by dopamine in mediating important physiological functions, such as movement, learning and emotional control, elucidating the features of such an interaction appears as an issue of great interest. This chapter summarizes evidence previously obtained in a rat model of subchronic caffeine administration demonstrating the capability of caffeine in triggering a hyperfunctional state involving the dopaminergic transmission in the corpus striatum which is manifested at both the behavioral and the neurochemical level. In particular, subchronic caffeine administration was found to promote the development of both sensitization to the motor stimulant effects of caffeine itself and cross-sensitization to those of amphetamine. Next to this, different neuroadaptive phenomena, which involve persistent changes in receptors’ density and affinity state as well as enduring modifications in immediate early gene expression, but not dopamine release, were observed in striatal regions of rats sensitized to caffeine. The relevance of these findings to the possible mechanisms underlying caffeinedopamine interactions is discussed. Chapter 6 - This study examined the relationship between lay conceptions of intelligence, personality traits, and subjectively-assessed intelligence (SAI). 160 (118 females) British and American University students completed the NEO-FFI and a 109 item lay conceptions of intelligence inventory. In addition, they estimated their scores on a number of different abilities (e.g., vocabulary, mathematical, verbal skills). Principal Components Analyses identified three major dimensions underlying people’s conceptions of the nature of intelligence, which were labelled academic IQ, social awareness and social intelligence. All personality dimensions were significantly and positively correlated with social awareness, and negatively with academic IQ. Social intelligence was significantly correlated with Extraversion, Openness, and Agreeableness (all positively), whilst academic IQ was significantly correlated with Extraversion, Openness, Agreeableness and Conscientiousness (all negatively). Results are discussed in terms of the theoretical conceptualization of the relationship of established personality traits with both lay conceptions and self-assessed intelligence. Chapter 7 - Amphetamine-type drug-induced positive symptoms, such as abnormal experiences (delusions and hallucinations) and bizarre behavior (hyperreactivity to both real and non-existent stimuli, locomotor hyperactivity, and stereotypy), are thought to lead to temporary or persistent psychosis, anti-social behavior, and criminal assaults. Therefore, the treatment of positive symptoms with medication is an important issue for individuals and society, but no effective treatment for amphetamine abuse has been established. In this chapter, author will review some of the evidence for a specific neuronal contribution to the alteration of the overall frequency and expression pattern of amphetamine-induced stereotypies in rodents and consider which agents are effective at treating amphetamine-type drug-induced positive symptoms in humans. Chapter 8 - These patients appear to be 3-4 times at greater risk of being overweight, obese and have concurrent metabolic abnormalities by the national rates using Centers of Disease Control and Prevention 2000 criteria. This places this group at a higher risk of morbidity and mortality. Therefore, physicians must provide appropriate treatments for these

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conditions by implementing appropriate dietary and exercise programs for this very high risk group. Chapter 9 - This chapter reports a study on the cognitive tactics of evaluating papers for a scientific journal of clinical psychology. For the analysis, 7 ratings of the journal’s evaluation form were used. They were pre-formulated by the editors of the journal and then used by the reviewers for almost every paper submitted to one of the editorial offices of the journal. Altogether the ratings for 670 papers—submissions or re-submissions—were used to build models of the cognitive activities of the reviewers. Two forms of model building were applied, a more or less intuitive one and one testing the respective connections. The results of both models were very similar, both are related to the probable cognitive activities of the reviewers, which could be linked to the form and the content of the respective submissions. There is an ongoing debate on the use of peer reviews for journal publications, but nobody to author knowledge until now has looked at the cognitions of the reviewers. Limits of the study and advantages and disadvantages of this real-life problem-solving tasks compared to experimental approaches are discussed. Chapter 10 - A combination of different risk indicators as well as a recent significant deterioration in global functioning are currently used as a preliminary definition of the initial prodromal state by many prospective studies of early psychosis. However, most of the referrals or these studies include prodromal patients with advanced symptoms who are at ultra-high-risk for transition to frank psychosis.

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Chapter 1

PROTEOMIC RESEARCH IN PSYCHOPHARMACOLOGY AND BIOLOGICAL PSYCHIATRY Yuji Odagaki1,* and Christoph W. Turck2 1

Department of Psychiatry, Faculty of Medicine, Saitama Medical University, Saitama, Japan 2 Proteomics and Biomarkers, Max Planck Institute of Psychiatry, Munich, Germany

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Over the past two decades genomic research in psychiatry has resulted in the identification of a number of candidate susceptibility genes and chromosomal loci associated with specific physiological and pathophysiological conditions. However, so far these data have not revealed much insight into mental disorder etiology. Likewise, no significant progress has been made in diagnostic and therapeutic procedures for these disorders. In order to better understand dynamic molecular processes in complex diseases like psychiatric disorders, the identification of pathways and signal transduction cascades holds great promise for unraveling functional networks pertinent to disease etiology. This information is best acquired on the protein level. Proteomics, the large-scale analysis of proteins with the help of high-throughput technologies like mass spectrometry, has become an important field of research in the medical sciences to gain information about the molecular mechanisms involved in the pathophysiology of diseases. At the same time, it holds great potential for new drug development in the post-genomic era. In contrast to proteomic efforts for somatic diseases including cancer and metabolic disorders, proteomics of the central nervous system is still in its infancy. Particularly in the area of psychiatric disorders only limited information has become available from neuroproteomics studies. In the present chapter, general aspects of proteomic approaches for psychopharmacology and psychiatry research are reviewed with regard to their *

Corresponding author. Department of Psychiatry, Faculty of Medicine, Saitama Medical University, 38 Morohongo, Moroyama-machi, Iruma-gun, Saitama 350-0495, Japan; Tel: +81 49-276-1214; Fax: +81-49276-1622; E-mail: [email protected]

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Yuji Odagaki and Christoph W. Turck strengths and limitations. Subsequently, neuroproteomics data that have been reported on “functional” mental disorders, such as schizophrenia and affective disorders, as well as effects of psychopharmacological medication will be reviewed. It is our belief that despite a number of limitations, the application of proteomic technologies will pave the way for a better understanding of mental and behavioral abnormalities, more accurate diagnosis and re-categorization of psychiatric disorders, and novel therapeutic approaches.

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1. INTRODUCTION In 2000 the completion of the sequencing of the human genome was announced and in the following year first drafts of the human genome sequence were published [International Human Genome Sequencing Consortium, 2001; Venter et al., 2001]. The reported number of approximately 30,000 protein-coding genes is far less than what had been widely anticipated [Claverie, 2001] since it is not much different from the numbers found in lower organisms. At the same time, however, the size of the human genome is about 30 and 200 times larger compared to the one in the fruit fly and baker’s yeast, respectively. This fact is largely attributable to the extensive contribution of noncoding and repetitive DNA sequences. Proteomic analyses have revealed that the average number of protein isoforms derived from one gene increases with the complexity of an organism, ranging from 1-2 proteins per gene in prokaryotes to more than 10 protein species per gene in Homo sapiens. This great divergence during transcription and subsequent translation processes greatly contributes to the complexity of higher organisms. In addition, a great variety of posttranslational protein modifications (e.g. phosphorylation, glycosylation) have been identified, yielding functional diversity in dynamic and spatial signaling networks and specific protein-protein interactions [Reinders and Sickmann, 2007]. In summary, the complexity of highly differentiated organs like the human brain results from the diverse repertoire of expressed proteins rather than a varied genome. Considerable effort has been made in molecular genetic studies with the hope of identifying the genes and chromosomal loci associated with psychiatric disorder susceptibility. However, despite such efforts linkage analysis for psychiatric disorders has so far failed to identify any single locus that can be replicated across multiple independent samples [Cowan et al., 2002; Burmeister et al., 2008]. Although the classical family, twin and adoption studies consistently indicate the high degree of heritability of psychiatric disorders such as schizophrenia and manic-depressive illnesses [Plomin et al., 1994], none of these mental disorders follows a simple Mendelian pattern of inheritance. This is presumably due to the involvement of multiple interacting genes and non-genetic environmental and/or psychosocial factors, that result in a lower risk of each individual allele with odds ratios less than 2. Traditional linkage methods are unlikely to have sufficient power to detect genes of such small effect size in complex multifactorial disorders [Risch and Merikangas, 1996]. As a consequence, the more powerful association analyses have been the focus of psychiatric genetic studies since the late 1990s [Burmeister et al., 2008]. Analyses have identified hundreds of candidate genes associated with susceptibility to major psychiatric disorders such as schizophrenia and affective disorders. In many cases, however, these findings have not been replicated in subsequent studies. Although a

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substantial number of interesting liability genes has been identified to be involved in bipolar affective disorders [Serretti and Mandelli, 2008], major depressive disorders [López-León et al., 2008], and schizophrenia [Riley and Kendler, 2006; Owen et al., 2005], recent genomewide association studies [Craddock et al., 2008a] failed to confirm previously reported associations in either bipolar [The Wellcome Trust Case Control Consortium, 2007; Baum et al., 2008; Sklar et al., 2008] or schizophrenic [Lencz et al., 2007; Sullivan et al., 2008] patients. While these high-throughput studies are powerful and have the potential to bear fruit when applied to larger sample sizes, molecular genetics-based approaches alone will in all likelihood be insufficient to disentangle the complicated and multi-etiological pathogenesis of psychiatric disorders. As for the analysis of mRNA levels, several techniques such as mRNA differential display [Liang and Pardee, 1992], subtractive hybridization [Sagerström et al., 1997], serial analysis of gene expression (SAGE) [Velculescu et al., 1995] and complementary DNA microarrays [Schena et al., 1995; Lockhart et al., 1996] have been used to analyze differential expression patterns between control and case samples. In particular, transcriptome profiling using DNA microarrays (transcriptomics) has been applied to psychiatric disorders as a highthroughput screening method of gene expression [Konradi, 2005; Mirnics et al., 2006]. However, precise molecular mechanisms underlying pathological processes of psychiatric disorders cannot be sufficiently derived from mRNA expression, because it has been shown that the correlation between transcriptional profiles and actual protein levels is poor [Anderson and Seilhamer, 1997; Gygi et al., 1997]. Based on the above we submit that, in addition to genes and mRNAs, proteins as the functional molecules of a cell must be analyzed under physiological and pathological conditions. Up until recently only limited and fragmentary information was gained from traditional approaches that examined one or a few proteins at a time in a small number of samples. In order to understand molecular processes comprehensively, it is necessary to get information about the ensemble of protein isoforms expressed in cells, body fluids, tissues or organisms. In order to improve this situation proteomics, the comprehensive analysis of proteins [Wasinger et al., 1995] has become feasible due to technical advances in recent years. Still, in contrast to other somatic diseases such as cancer and metabolic disorders, proteomics of the central nervous system (neuroproteomics) is in its infancy [Rohlff and Hollis, 2003; Freeman and Hemby, 2004; Kim et al., 2004; Vercauteren et al., 2004; Pennington et al., 2005]. Only limited information has become available from neuroproteomics studies in the area of psychiatric disorders. In the present chapter, general aspects of proteomic approaches in psychopharmacology and psychiatry are reviewed with regard to their strengths and limitations. Subsequently, neuroproteomics data that have been reported on “functional” mental disorders, such as schizophrenia and affective disorders, as well as effects of psychopharmacological medication will be discussed. We realize that our review is not comprehensive and apologize to everyone whose work is not included in our discussion.

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2. PROTEOMIC APPROACHES IN NEUROSCIENCE Although the concept of global protein analysis was proposed some time ago [Anderson et al., 2001], proteomics research only became feasible in the mid-1990s thanks to technological advances in mass spectrometry (MS). It became possible to analyze proteins with great sensitivity and in combination with bioinformatics tools to identify them from complex mixtures with high accuracy [Mann et al., 2001; Tannu and Hemby, 2006]. The two MS-based methods for protein identification that were developed and which are still used today are matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) MS and electrospray ionization (ESI)-tandem mass spectrometry (MS/MS). Fractionation of complex protein mixtures is carried out by either two dimensional gel electrophoresis (2DE) or, after enzymatic digestion, multi dimensional chromatography of the resulting peptides. Postmortem brain samples have been used in proteomic studies in an effort to identify the proteins differentially expressed in psychiatric patients compared with control subjects. Alternatively, cerebrospinal fluid (CSF) has been utilized [Maccarrone et al., 2004; Raedler and Wiedemann, 2006]. Animal brain tissues or neuronal cell lines also serve as materials in neuroproteomics to reveal altered protein expression in animal models of psychiatric disorders or in response to psychotropic drug treatments. Extensive sample preparation is necessary for a meaningful representation of the proteins of interest. For instance, in body fluids such as CSF and plasma, several high abundant proteins (albumin, immunoglobulins, etc) are dominant and repress the signals of the low abundant proteins [Fountoulakis et al., 2004; Yuan and Desiderio, 2005]. Thus, prefractionation of such samples to deplete the high abundant proteins is a prerequisite to enrich low abundant proteins potentially associated with the pathogenesis of psychiatric disorders. With regard to brain tissue samples, subcellular fractionation methods can be used to reduce the complexity of protein mixtures (e.g., endoplasmic reticulum, mitochondria, nucleus, cellular membrane, and cytosol) [Brunet et al., 2003; Yates et al., 2005]. Additional methods including selective prefractionation and chromatography can also be utilized to obtain a specific set of proteins from a complex mixture [Ahmed and Rice, 2005; Righetti et al., 2005]. For protein solubilization sample preparation is commonly carried out in buffers containing chaotropes (e.g., urea), detergents (e.g., CHAPS, Triton-X), reducing agents (e.g., dithiothreitol), and carrier ampholytes. Protease inhibitors are also frequently added. 2DE involves two electrophoretic steps. During the first dimension isoelectric focusing (IEF) proteins are separated based on their differences in net charge. In the second dimension, proteins are resolved by SDS-PAGE according to their molecular weight (MW). With 2DE it is now possible to separate up to several milligrams of protein, which is sufficient for further characterization of low abundant proteins. After 2DE separation proteins are visualized by staining with Coomassie Blue or a modified silver stain. In an alternative approach known as two-dimensional difference gel electrophoresis (2D-DIGE) [Marouga et al., 2005], proteins are first labeled with different fluorescent cyanine (Cy) dyes (Cy2, Cy3 and Cy5) followed by analysis with a fluorescence imager capable of detecting the DIGE dyes with their specific excitation wavelengths. The stained proteins are quantitatively and statistically analyzed with special image software packages [Marengo et al., 2005]. Subsequently, the protein spots of interest are excised and subjected to in-gel digestion with proteolytic enzymes, most commonly trypsin.

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Trypsin cleaves proteins at the C-terminal end of lysine and arginine residues and the resulting peptides are identified by MS or MS/MS. If needed, proteases with other specificities can also be employed. MALDI-TOF-MS can be used to identify proteins by peptide mass fingerprinting (PMF). MALDI is a soft ionization technique, utilizing a matrix consisting of crystallized molecules such as 3,5-dimethoxy-4-hydroxycinnamic acid (sinapinic acid) on a sample plate where peptides are embedded. The ionization is triggered by a laser beam, and ionized molecules are accelerated in an electric field. The individual mass-to-charge ratio (m/z) in TOF analyzers is deduced from the flight time the ionized peptide requires to travel through a tube of specific length under vacuum. The PMF data are compared to the theoretically expected tryptic peptide masses for each protein entry in the database. Candidate proteins are ranked according to the number of peptide matches and/or the level of confidence for the match. The workflow for 2DE followed by MALDI-TOF-MS techniques is depicted schematically in Fig. 1. If the identity of a protein cannot be unambiguously obtained by MALDI-TOF-MS, ESIMS/MS should be employed. Because MALDI-TOF-MS and ESI-MS/MS are based on different physicochemical principles and have different characteristics, they can provide analytical information complementary to each other. Typically, tryptic peptide mixtures are first separated by LC before peptide-sequence data are obtained by tandem MS followed by a database search using the peptide parent and fragment data. Proteomics research has many advantages. In contrast to transcriptomics, proteomics directly addresses the level of gene products present in a given cell state, thus providing invaluable information for protein-protein interactions and subcellular distributions. Hundreds to thousands of proteins can be resolved and analyzed simultaneously in a single experiment, each protein characterized by MS via PMF and/or product-ion spectra. Furthermore, posttranslationally modified proteins can be detected separately according to their differences in isoelectric point (pI) and/or MW [e.g., Ditzen et al., 2006]. Nevertheless, proteomics technologies are still under development to overcome limitations and drawbacks [BeranovaGiorgianni, 2003; Garbis et al., 2005]. It is still not possible to analyze a complete proteome, and low abundant proteins are often not detected by conventional methods. For instance, membrane-bound proteins that play important roles in various cellular processes including signal transduction, cell adhesion, ion transport, endocytosis and neural transmission are not easily detectable by standard methods [Santoni et al., 2000]. These proteins are of particular interest since they have been implicated in the pathogenesis of psychiatric disorders and molecular mechanisms of psychotropic drug treatment. In addition, most proteomic data have been of qualitative nature, not taking into account the dynamic nature of the mentioned processes. Even if quantitative data are obtained, the accuracy of protein quantification is compromised by the inherent problems associated with sample preparation, application of 2DE and protein staining procedures, resulting in unsatisfactory reproducibility. In order to overcome the shortcomings of conventional 2DE methods and to gain more accurate and reliable quantitative information, several new strategies have been developed in recent years [Ong and Mann, 2005; Bantscheff et al., 2007]. 2D-DIGE with multiplex fluorescent dyes (Cy2, Cy3 and Cy5) [Marouga et al., 2005] is one such method and has been used in neuroproteomics. Two or three samples are independently labeled with different fluorescent dyes, pooled and analyzed simultaneously using an internal standard as reference resulting in increased accuracy. Other quantitative methods are based on labeling proteins or peptides

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with stable isotopes. These include isotope-coded affinity tags (ICAT), stable isotope labeling of amino acids in culture (SILAC), metabolic labeling, and isobaric tag for relative and absolute quantitation (iTRAQ). These techniques enable peptides derived from two or more samples to be distinguished and identified by MS or MS/MS, providing accurate relative quantitation data. These methods have great potential in the neuroproteomic field.

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Figure 1. Workflow of proteomic analysis by 2DE followed by MALDI-TOF-MS.

Surface enhanced laser desorption/ionization time of flight mass spectrometry (SEFDITOF-MS) is another technology that provides quantitative protein expression information. It utilizes protein chip array technology to separate proteins from complex mixtures with high resolution. Proteins are selectively adsorbed to “chip” surfaces with different properties and subsequently analyzed by MS. Differences in the amplitude of spectral peaks are used to obtain a “fingerprint” or “signature” that can potentially distinguish disease from non-disease states.

3. PROTEOMIC RESEARCH USING POSTMORTEM BRAIN TISSUE The first proteomic study using postmortem brain tissue samples taken from patients with “functional” psychiatric disorders was reported by Edgar et al. [1999], who studied the hippocampal proteome of seven schizophrenic patients, seven Alzheimer’s disease patients and seven controls using 2DE of homogenized tissues (Table 1). Several proteins were significantly altered in schizophrenic patients, indicating that schizophrenia had a subtle neuropathological presentation in comparison with Alzheimer’s disease, which showed 35 decreased and 73 increased proteins. One commonly decreased protein in both diseases was identified to be diazepam-binding inhibitor protein, a regulator of the GABAA receptors. In a follow-up analysis by the same researchers [Edgar et al., 2000], three additional proteins altered in the hippocampus of the schizophrenic patients were identified as manganese

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superoxide dismutase, T-complex protein 1 and collapsin-response mediator protein 2 (also known as dihydropyrimidinase related protein-2). Johnston-Wilson et al. [2000] investigated the frontal cortex of 24 schizophrenic, 23 bipolar disorder, 19 major depressive disorder patients and 23 unaffected controls, using 2DE followed by ESI-MS/MS for protein identification. Four proteins, which were decreased in one or more psychiatric disorders, were identified as glial fibrillary acidic proteins. Ubiquinol cytochrome c reductase complex core protein 1 and carbonic anhydrase I were altered specifically in major depressive disorders, while dihydropyrimidinase-related protein 2 and fructose-bisphosphate aldolase were altered in all three disorders. Prabakaran et al. [2004] found that almost half of all altered proteins identified by proteomics in prefrontal cortex of schizophrenic patients were associated with mitochondrial function and oxidative stress responses. Together with transcriptomics and metabolomics data obtained from the same samples, the authors put forward the hypothesis that diverse genetic and/or epigenetic factors predispose and precipitate hypoxic events in a constitutively vulnerable prefrontal cortex and in turn lead to the acute and chronic deficits characteristic of schizophrenia, e.g., cellular dysfunction derived from an overproduction of reactive oxygen species. Anterior cingulated cortex (ACC, Brodmann area 24) is one of the cortical regions most predominantly implicated in the pathogenesis of major psychiatric disorders including schizophrenia. The proteome of this brain region was analyzed in order to identify diseasespecific or common protein changes in schizophrenia, bipolar disorder, and major depressive disorder [Beasley et al., 2006]. Thirty-five spots representing significantly altered protein expression in one or more of the three disorders in comparison with controls were detected. Of these, 26 spots were identified by MS, representing 19 different proteins. There was only one protein spot downregulated in all three major psychiatric disorders, but it was not identified. Since almost all of the identified altered proteins are cytoskeletal or mitochondrial, it has been concluded that the neuropathology of major psychiatric disorders may be associated with cytoskeletal and mitochondrial dysfunction. An Australian research group also explored the ACC proteome from 10 schizophrenic patients and 10 controls either in gray [Clark et al., 2006] and white matter [Clark et al., 2007]. In the gray matter, 42 protein spots were quantitatively altered in the schizophrenic cohort, 39 of which were identified and functionally classified as metabolic, oxidative stress, cytoskeletal, synaptic, signaling, trafficking and glial-specific groups. On the other hand, 32 protein spots of the white matter proteome were altered in schizophrenic patients, 30 of which were identified by MS. Four proteins were found to be altered commonly in both the grey and white matter of ACC. However, only one of these proteins, bisphosphate aldolase C, was downregulated in both structures whereas the other 3 proteins (citrate synthase, heat shock protein 70 kDa, and dihydropyrimidinase related protein-2) were altered in the opposite direction in gray and white matter of ACC. Dorsolateral prefrontal cortex (DLPFC, Brodmann area 46) is another brain region of interest that has been implicated in the pathophysiology of major psychiatric disorders, in particular, schizophrenia. Mei et al. [2006] performed SELDI-TOF-MS from DLPFC of 34 schizophrenic and 35 control subjects. Of 1597 protein peaks that were reproducibly observed, 173 (10.8%) and 45 (2.8%) were found to be significantly different between schizophrenia and controls with a probability of 80), assessed by psychologists, and no current significant language delay. There is an ongoing diagnostic debate regarding the inclusion of the three aforementioned diagnoses under the broader term of HFASDs (e.g., Klin, PcPartland, & Volkmar, 2005; Miller & Ozonoff, 2000). Often, the distinguishing feature of these children from others on the autism spectrum is their relative strengths in cognitive and language ability. These strengths often complicate differential diagnoses and qualification for services (Kasari & Rotheram-Fuller, 2005). Many researchers include children with all three diagnoses in their interventions (e.g., LeGoff, 2004; Solomon, Goodlin-Jones, & Anders, 2004) as a result of their shared communicative and social interaction characteristics. A multiple-gate screening procedure was used by the researchers to confirm the accuracy of the diagnosis in addition to the formal diagnosis and cognitive assessment (Lopata et al., 2007). The Autism Diagnostic Interview – Revised (ADI-R) was conducted to confirm the diagnosis. All screening and pre-treatment assessments were performed at least two weeks prior to the commencement of the summer camp. Caregivers who had been screened were then asked to participate in this study. If they agreed, research paperwork was given to them, which included two informed consent forms (one for the caregiver and one for the researcher to keep), a packet of surveys, and a selfaddressed, stamped envelope. Caregivers were asked to complete and return the packet of surveys within two weeks of the commencement of summer camp.

Measures The measures used for this study included seven different self-report surveys, which measured basic information and the four constructs under consideration. The collection included: a) a basic demographic sheet, providing information on the caregiver and the family; b) coping (Family Crisis Oriented Personal Evaluation [FCOPE]); c) social support (Family Inventory of Resources for Management [FIRM]); d) stress (Parenting Stress Inventory [PSI]) and e) psychosocial adjustment outcomes (Center for Epidemiologic Studies Depression Scale [CES-D], Beck Anxiety Inventory [BAI], and Subjective Life Satisfaction Scale [SLSS]).

Demographics The demographic sheet consisted of basic items to gather demographic information. Contents included gender, age, marital status, ethnicity, education, family income, and perceived socioeconomic status.

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Family Crisis Oriented Personal Evaluation (F-COPE) The F-COPE (McCubbin, Olson, & Larsen, 1981) is a 30-item, self-rating inventory that measures the problem-solving attitudes and behaviors which families use to respond to difficulties. Each item is rated based on a 5-point Likert scale, ranging from 1 “Strongly Disagree” to 5 “Strongly Agree.” There are five subscales and one total score. The subscales reflect different types of coping mechanisms. They include: Subscale 1: Acquiring Social Support; Subscale 2: Reframing; Subscale 3: Seeking Spiritual Support; Subscale 4: Mobilizing Family to Acquire and Accept Help; and Subscale 5: Passive Appraisal. The higher the score on a particular subscale, the more the individual adopts that particular type of coping mechanism when faced with a problem in life. All five subscales, except Passive Appraisal, are considered adaptive coping. McCubbin and colleagues (1981) reported reliability for the total score to be .77. Test-retest reliability of a five-week period was shown to be .71. Two additional samples were used to test the psychometrics of the scale. These samples indicated a similar factor structure to the original sample (McCubbin et al., 1981). Reliability of the current study is reported with Cronbach’s alpha of .45. Family Inventory of Resources for Management (FIRM) The FIRM (McCubbin, Comeau, & Harkins, 1981) is a 69-item, self-rating inventory that measures what social, psychological, community, and financial resources families believe they have available to them. Each item is rated based on a 4-point Likert scale, ranging from 0 “Not At All” to 3 “Very Well.” There are four subscales and a total score. The four subscales include: Subscale 1: Family Strengths I: Esteem and Communication; Subscale 2: Family Strengths II: Mastery and Health; Subscale 3: Extended Family Social Support; and Subscale 4: Financial Well-Being. McCubbin and colleagues (1981) reported internal consistency of the four subscales and the total score as .85, .85, .62, .85 and .89, respectively. In addition, concurrent validity was established when all subscales of the Family Environmental Scale were positively and significantly correlated with the four subscales of the FIRM. Discriminant analysis was used to confirm the discriminatory ability of family support between families of individuals with myelomeningocele and families of individuals with cerebral palsy (Nevin, McCubbin, Comeau, Cauble, Patterson, & Schoonmaker, 1981). Reliability of the current study is reported with Cronbach alpha of .92. Parenting Stress Inventory (PSI-Short Form) The PSI-SF (Abidin, 1995) is a 36-item self-report inventory that measures one’s perceived level of stress from parenting. Each item is rated on a 5-point Likert scale, ranging from 5 “Strongly Agree” to 1 “Strong Disagree.” The PSI consists of three subscales and one total score. The three subscales are: Subscale 1: Parental Distress; Subscale 2: Parent-Child Dysfunctional Interaction; and Subscale 3: Difficult Child. The total score is represented by the sum of the three subscales. Test-retest reliability over a six-month period ranged from .68 to .84, and internal consistency reportedly ranged from .80 to .91. Roggman, Moe, Hart, and Forthun (1994) reported internal consistency coefficients ranging from .78 to .90 for a sample of Head Start parents. The short form was found to correlate highly with the original form, with correlations ranging from .50 to .95. The PSI authors indicated that no independent studies have been conducted on the psychometric properties of the short form, “but because it is a direct derivative of the full-length PSI, it is likely that it will share in the validity of the full-length PSI” (p.61). The validity of the full-length PSI is supported in numerous studies

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Psychosocial Adjustment among Caregivers Raising Children …

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across different disability and illness groups (see manual for details). Reliability in the current study is reported with Cronbach alpha of .92.

Center for Epidemiologic Studies Depression Scale (CESD) The CESD (Radloff, 1977) is a 20-item, self-rating inventory that measures the existence of potential depressive symptomotology. Each item is rated based on a 4-point Likert scale, ranging from 0 “Rarely or None of the Time” to 3 “Most or All of the Time.” The minimum score for the CES-D is 0 and the maximum score is 60. A score of 16 or above is potentially indicative of clinically significant depression. Radloff (1977) reported internal consistency coefficients ranging from .84 to .90 in several applications. Reliability of the current study is reported with Cronbach alpha of .85.

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Beck Anxiety Inventory (BAI) The BAI (Beck & Steer, 1990) is a 21-item, self-rating inventory that measures the perceived level of anxiety symptoms. Each item is rated based on a 4-point Likert scale, ranging from 0 “Not At All” to 3 “Severely”. Internal consistency was shown to be high, with Cronbach alpha values of .92 (Beck et al., 1988) and .94 (Fydrick, Dowdall, & Chambless, 1990). Test-retest reliability over a one-week period was shown to be .75 (Beck et al., 1988). Concurrent validity was established, with r=.51 with the Hamilton Anxiety Rating-ScaleRevised (Riskind, Beck, Brown, & Steer, 1987), and with r’s=.58 and .47 with the Trait and State subscales of the State-Trait Anxiety Inventory (Fydrick et al., 1990). Reliability of the current study is reported with Cronbach alpha of .85. Subjective Life Satisfaction Scale (SLSS) The Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) is a fiveitem, self-rating inventory that measures an individual’s subjective well-being, which is a person’s evaluation of his/her life, happiness, fulfillment, and life satisfaction. Each item is rated on a 7-point Likert scale, ranging from 1 “Strongly Disagree” to 7 “Strongly Agree.” A series of three studies conducted by Diener and colleagues (1985) showed internal reliability of .87 and test-retest reliability of .82 over an eight-week period. Studies also demonstrated convergent and discriminant validity with other measures of well-being, and expected correlations with personality measures (Diener et al., 1985). Other studies have found support for validity and similar levels of internal reliability with various populations (e.g., Neto, 1993; Pavot, Diener, Colvin, & Sandvik, 1991). Reliability of the current study is reported with Cronbach alpha of .90.

RESULTS Demographics of Participants Table 1 reports the demographic variables.

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Table 1. Demographics of Parents with Children with High Functioning Autism Spectrum Disorders (HFASDs) Variables Age

Percentage 41.7 (6.4)

Gender

Female: 93.9% (n=62) Male: 6.1% (n=4)

Marital Status

Married: 81.8% (n=54) Separated: 6.1% (n=4) Never Married: 6.1% (n=4) Divorced: 4.5% (n=3) Widowed: 1.5% (n=1)

Education

Bachelor: 27.3% (n=18) Masters: 21.2% (n=14) Others: 18.2% (n=12) Vocational School: 13.6% (n=9) High School: 10.6% (n=7) Doctoral Degree: 7.6 (n=5) Missing: 1.5% (n=1)

Ethnicity

Caucasian: 93.9% (n=62) African Americans: 1.5% (n=1) Asian Americans: 1.5% (n=1) Missing: 1.5% (n=1) Other: 1.5% (n=1)

Family Income

US$70,000 and over: 53.0% (n=35) US$50,000 - 60,000: 12.1% (n=8) US$60,000 - 70,000: 7.6% (n=5) US$20,000 - 30,000: 7.6% (n=5) US$40,000 - 50,000: 6.1% (n=4) US$30,000 - 40,000: 4.5% (n=3) Under $10,000 : 4.5% (n=3) US$10,000 - 20,000: 3.0% (n=2) Missing: 1.5% (n=1)

SES

Middle Class: 59.1% (n=39) Upper Middle Class: 24.2% (n=16) Lower Middle Class: 9.1% (n=6) Below Poverty: 6.1% (n=4) Missing: 1.5% (n=1)

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Psychosocial Adjustment among Caregivers Raising Children … Parents’ Disability

Physical Disabilities: 10.7% (n=7) Psychological Disablities : 37.9% (n=25)

Parents’ Treatment

Counseling/Psychotherapy: 7.6% (n=5) Medical Treatment: 7.6% (n=5) Others: 1.5% (n=1)

Support Group For Children with Disability

Parent Groups: 22.7% (n=15) Educational/Informational Groups: 6.1% (n=4) Informal (family, relatives): 4.5% (n=3)

45

Gender of Children with a Disability Males: 81.8% (n=54) Females: 13.6% (n=9) Missing: 4.5% (n=3)

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Diagnoses of primary Children’s Disability

Asperger’s Syndrome: 66.7% (n=44) PDDNOS: 15.2% (n=10) High Functioning Autism: 6.1% (n=4) Autism: 3.0% (n=2) Missing: 9.1% (n=6)

Among the 66 caregivers participating, 93.9% were female primary caregivers, while 6.1% were male primary caregivers. The average age was 41.7 years (SD=6.5). A majority of participants reported being married (81.8%). A majority of the participants reported their ethnicity as “European descent” (93.9%). For educational level, most participants had a college degree (27.3%), 21.2% reported having a master’s degree and another 18.2% reported “others”. Slightly over half (53.0%) of participants reported having their family income as US$70,000 and above. Fifty-nine percent reported their perceived socio-economic status as “middle class”, and another 24.2% reported their SES as upper-middle class. Among the caregivers participating in this study, a total of 10.6% reported having a physical disability while 37.9% reported having psychological disabilities (anxiety, depression or substance abuse). Among those with a disability, 18.2% reported actively seeking treatment; of these, 7.6% reported receiving counseling/psychotherapy, another 7.6% reported receiving medical treatment. In terms of support, 34.8% reported receiving some kind of support: among which 22.7% reported attending a parent group as support, another 6.1% reported attending educational/informational support groups, and 4.5% reported having informal support groups (e.g. family, relatives). Two demographic characteristics of the children are worth reporting. First, 89% of the children were male. Second, a majority of the children had a formal diagnosis of Asperger’s Disorder (66.7%), with 15.2% PDDNOS and 6.1% high functioning autism.

Descriptive Statistics of Measures Table 2 reports the descriptive statistics on each of the studied variables. Advances in Psychology Research, Volume 60, Nova Science Publishers, Incorporated, 2009. ProQuest Ebook Central,

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Gloria K. Lee, Christine Berry-Kaizmien, Martin A. Volker et al. Table 2. Descriptive Statistics of the Studied Variables Studied Variables Outcomes: CESD

BAI

Mean

SD

Range

13.0 7.3 1-31 36.4% (n=24) scored 16+ (indicative of clinical depression) 6.3

5.5

0-22

95.5% (n=63) scored between 0-21 (indicative of low level of anxiety) 3.0% (n=2) scored between 22-35 (indicative of moderate level of anxiety)

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SWL Stress: PSI Total

24.1

6.9

7-35

94.8

19.0

52-140

Coping: FCOPE Total

96.8

11.9

67-125

Social and Resources: FIRM Total

189.4

35.7

107-267

The mean for the depression score was 13.0 (SD=7.3). Using the cut-off criteria of 16 for clinical depression, the average score for this sample did not fall into the diagnostic category of clinical depression. However, 36.4% of caregivers had a score of 16 or higher, which indicates that a significant proportion of participants fall into the clinically depressed range. For anxiety, the mean score was 13.0 (SD=5.5). Ninety-six percent of the sample indicated low levels of anxiety, while three percent scored at a clinically significant level. For satisfaction with life, there are no particular cut-off scores to indicate levels of satisfaction. Scores ranged from seven to 35, with higher scores indicative of better satisfaction with life. The average score on the SLSS in this sample was 24.1 (SD=6.9). Table 3 reports the correlations among the studied variables. Depression was moderately and significantly correlated with the other two outcome variables: anxiety (r=.50) and general life satisfaction (r=-.39). Depression and anxiety, which represent negative psychological distress, correlate positively, while both depression and anxiety have a negative correlation with positive life satisfaction.

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Table 3. Correlations of the Studied Variables

1. Depression 2. Anxiety 3. Life Satisfaction 4. Age 5. Age of Child 6. Gender 7. Gender of Child 8. Ethnicity 9. Education 10. Income 11. Perceived SES 12. PSI Total 13. FCOPE Total 14. FIRM Total ** p