Mental Health of College Students

MENTAL HEALTH OF COLLEGE STUDENTS

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MENTAL HEALTH OF COLLEGE STUDENTS

KATHERINE N. MORROW EDITOR

Nova Science Publishers, Inc. New York

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. 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 Mental health of college students / Katherine N. Morrow (editor). p. ; cm. Includes bibliographical references and index. ISBN 978-1-60876-333-7 (E-Book) 1. College students--Mental health. I. Morrow, Katherine N. [DNLM: 1. Stress, Psychological. 2. Adaptation, Psychological. 3. Mental Health. 4. Students-psychology. 5. Universities. WM 172 M5488 2008] RC451.4.S7M435 2008 616.8900835--dc22 2007051994 ISBN: 978-1-60456-394-8

Published by Nova Science Publishers, Inc.    New York

CONTENTS

Preface Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

vii Trait Anger, Anger Expression, and Themes of Anger Incidents in Contemporary Undergraduate Students Sandra P. Thomas

1

Social Anxiety in the College Student Population: The Role of Anxiety Sensitivity Angela Sailer and Holly Hazlett-Stevens

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Coping, Mental Health Status, and Current Life Regret in College Women Who Differ in their Lifetime Pregnancy Status: A Resilience Perspective Jennifer Langhinrichsen-Rohling, Theresa Rehm, Michelle Breland and Alexis Inabinet

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Sexual Behavioral Determinants and Risk Perception Related to HIV among College Students Su-I Hou and Joseph M. Wisenbaker

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The Impact of a Lecture Series on Alcohol and Tobacco Use in Pharmacy Students Arjun P. Dutta, Bisrat Hailemeskel, Monika N. Daftary, and Anthony Wutoh

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The Gould versus Heckhausen and Schulz Debate in the Light of Control Processes among Chinese Students Wan-chi Wong, Yin Li and Ji-liang Shen

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Writing your Way to Health? The Effects of Disclosure of Past Stressful Events in German Students Lisette Morris, Annedore Linkemann and Birgit Kröner-Herwig

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vi Chapter 8

Chapter 9

Chapter 10

Chapter 11

Index

Contents Test Anxiety and Its Consequences on Academic Performance among University Students Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock The Prevalence of Depression among Female University Students and Related Factors Fernando L. Vázquez, Ángela Torres, María López, Vanessa Blanco, and Patricia Otero

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Relationships between Mood, Coping and Stress Symptoms Among Students who Work in Schools Dafna Kariv and Tali Heiman

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Examining Anger Expression Reactions and Anger Control Behaviors of Turkish Students Ibrahim Kisac

217 233

PREFACE College students have always been subject to a massive input of stresses. These stresses include inside and outside pressures by the world to succeed, financial worries, concerns about uncertain future, social problems and opportunities since college is often the meeting place for future mates, and homework and tests in multiple and complex subjects requiring preparation and focus with often conflicting priorities. Unsuccessful coping often results in anxiety, heavy drinking, depression and a host of other mental health problems. The ready availability of weapons of all sorts has added a new dimension to the problem. This new book presents new analyses which detail the depth of the issues involved. Chapter 1 - Guided by Trait-State Anger Theory (Spielberger et al., 1983), trait anger, anger expression, and written narratives of anger incidents were examined in 305 undergraduate students. Fischer et al.’s (2004) coding scheme was used to assess reasons for anger, the relational context of the incident, methods of expressing anger, and outcomes. The chief provocateur for all students was a non-romantic intimate, but important differences were observed when comparing 3 subgroups: (1) students scoring high on angry temperament, (2) those scoring high on angry reaction, and (3) those scoring low on the entire trait anger scale. Interventions for dysfunctional anger are proposed. Chapter 2 - Most college students experience some degree of social anxiety on occasion. However, many suffer chronic anxiety across social situations coupled with a strong fear of negative evaluation. In addition to impaired occupational and social functioning, severe social anxiety or social phobia can carry profound consequences for college students. Social anxiety is a prominent motivation for college student drinking (Burke and Stephens, 1999). In addition to social isolation, social anxiety is associated with depressogenic cognitions, both of which leave socially anxious students at an increased risk for depression (Johnson et al., 1992). Anxiety sensitivity – fear of anxiety-related sensations due to perceived consequences of physical, mental, or social harm – might play an important role in the development of social anxiety (Hazen et al., 1995). Unlike panic disorder, in which individuals typically fear anxiety symptoms out of fear of physical harm or loss of mental control, socially anxious individuals fear perceived social consequences of others noticing their anxiety. Socially anxious college students also judge others who appear anxious more negatively than do college students without social anxiety (Purdon et al., 2001). Although panic disorder treatments target anxiety sensitivity directly with interoceptive exposure strategies, this approach is just beginning to receive attention for the treatment of social anxiety. After a brief review of the literature describing the nature of social anxiety among college students, this

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chapter will examine the specific role of anxiety sensitivity in its development and maintenance. Finally, results from a preliminary investigation comparing the effects of interoceptive exposure delivered in a social context to social context exposure without the interoceptive component will be presented and discussed. Chapter 3 - This study examined the current mental health status, coping strategies, and perceived life regret of three types of female college students (n = 277): those who had never been pregnant (67.9%, n= 188); those who became pregnant at or before age 18 who were a priori considered to be resilient (14.8%, n = 41); and those who had experienced a pregnancy after age 18 (17.3%, n = 48). Data were collected at a diverse urban public university in the Southeast. This university has a significant number of commuter and non-traditional students. Results indicated that college women who had experienced an adult pregnancy reported significantly fewer maladaptive coping strategies than never-pregnant college women and those who had experienced a teenage pregnancy. Surprisingly, both groups of ever pregnant college women expressed significantly more life regret than never pregnant college women. Among the college women who had experienced a teenage pregnancy, two groups were delineated: those who were “thriving” versus those who were “at-risk” with regards to their current symptoms of depression, hostility, and hopelessness. Women in the “at-risk” group were significantly less likely to be simultaneously parenting and attending college than those in the “thriving” group. One potential implication is that identifying and intervening with these potentially at-risk college women may help improve retention rates and student morale at universities with a diverse student body. Chapter 4 - Young adults such as college students are known to engage in frequent and unprotected sexual activities, the primary route for HIV transmission, yet their risk perception towards HIV infections have been low. This study aimed to examine the extent to which HIV risk perception among college students may be explained by behavioral factors (number of partners and condom use by type of sexual activity, and partner’s risk) and selected background variables (sexually transmitted infections history, sexual orientation, age, and gender). A web-survey was administered in a major university in the Southeastern U.S. (N=440). Study information with survey website address and login password were disseminated through flyers, colored mini-handouts, classroom announcements, student newspaper advertisements, and several e-mail listserv student organizations. Informed consent was obtained as part of the login process. The innovation of the study is to assess a comprehensive array of sexual behaviors and their relationships on risk perceptions via the Internet. Bivariate analyses were used to first examine the relationships between individual behavioral or background variables and students’ perceived HIV risk. Multiple logistic regressions were then performed to investigate how well the various behavioral determinants and background variables together distinguished between students with higher or lower perceived risk of HIV infection. Data showed that, after considering all the variables together, number of partners for oral (OR=1.293), vaginal (OR=1.255), and anal (OR=1.846) sex were the three variables which revealed significant predictions to perceived risk. Results support the use of the Intent in obtaining sensitive behavioral information and suggest that public health messages addressing multiple partners in conjunction with type of sexual activity can be important in influencing HIV risk perception among college students. Chapter 5 - Studies related to alcohol and drug use in healthcare students, namely nursing, pharmacy, and medicine suggest that drug and alcohol abuse continues to be a growing problem among health profession students. A review of the more recent literature

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involving pharmacy students, has noted higher levels of alcohol and drug use when compared to the undergraduate student population. Interestingly, the use and/or abuse of tobacco have largely been overlooked in studies involving substance abuse in pharmacy students. This study documented the current alcohol and tobacco use in pharmacy students and conducted a lecture series on the use and abuse of alcohol and tobacco. The lecture series was successful in increasing the awareness of the use and potential abuse of alcohol in the students. Attitudinal changes in students following the lecture series were also assessed. Chapter 6 - In response to the Gould versus Heckhausen and Schulz debate (1999) on the claim to universality of the life-span theory of control, the present study aims to examine the theoretical formulation of Heckhausen and Schulz in the context of contemporary China, with specific reference to the control processes applied by Chinese students in their academic pursuits. A new instrument, the OPS-Scales in the Domain of Academic Achievement (OPSAA), was constructed and examined in the pilot study. The main part of the research program consists of three studies. Study One and Study Two respectively investigated the control processes endorsed by Chinese students in the pre-deadline and post-deadline situations relating to two important public examinations, namely the University Entrance Examination and the Test of English as a Foreign Language (TOEFL). Study Three examined the application of control strategies among junior and senior high school students in a less critical situation (i.e., before an internal school examination). The results of the studies lend support to the thesis about the primacy of primary control. As predicted, the Chinese students made extensive use of selective primary control, selective secondary control, and compensatory primary control in the urgent pre-deadline situation. The control strategies applied in the post-deadline situation continued to be characterized by primary control striving in both the success and the failure conditions. Such primary control striving also demonstrated its adaptive value by significantly correlating to the positive affect subscale of the Positive and Negative Affect Schedule (PANAS). On the other hand, the endorsement of compensatory secondary control in the failure condition did not show its adaptive value. In integrating the results of Study One, Study Two and Study Three, differences were found across the compared age groups. The ascending slope in the application of compensatory secondary control was confirmed among the subjects who ranged from pre-adolescents through adolescents to young adults. For further development of the research program, it is suggested that Lakatos’s idea of sophisticated falsification would be worth considering. Attempts are made to define the “hard core” of the research program, and to propose new auxiliary hypotheses on the basis of the present study. Several lines for future research are also discussed. Chapter 7 - In 1986 Pennebaker and Beall published their renowned study on the longterm beneficial health effects of disclosing traumatic events in 4 brief sequential writing sessions. Their results have been confirmed in various studies, but conflicting results have also been reported. The intent of our study was to replicate the experiments from Pennebaker and Beall (1986), Pennebaker et al. (1988), and Greenberg and Stone (1992) using a German student sample. Additionally, essay variables that point to the emotional processing of events (e.g., depth of self-exploration, number of negative/positive emotions, intensity of emotional expression) were examined as potential mechanisms of action. Trait measures of personality which could moderate the personal consequences of disclosure (alexithymia, selfconcealment, worrying, social support) were also assessed. In a second study the experimental condition (disclosure) was varied by implementing “coping” vs. “helping”

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instructions as variations of the original condition. Under the coping condition participants were asked to elaborate on what they used to do, continue to do, or could do in the future to better cope with the event. Under the helping condition participants were asked to imagine themselves in the role of a adviser and elaborate on what they would recommend to persons also dealing with the trauma in order to better cope with the event. The expected beneficial effects of disclosure on long-term health (e.g., physician visits, physical symptoms, affectivity) could not be corroborated in either the first or the second study. None of the examined essay variables of emotional processing and only a single personality variable was able to explain significant variance in the health-related outcome variables influence. Nevertheless, substantial reductions in posttraumatic stress symptoms (e.g., intrusions, avoidance, arousal), were found in both experiments. These improvements were significantly related to essay variables of emotional expression and self-exploration and were particularly pronounced under the activation of a prosocial motivation (helping condition). Repeated, albeit brief, expressive writing about personally upsetting or traumatic events resulted in an immediate increase in negative mood but did not lead to long-term positive health consequences in a German student sample. It did, however, promote better processing of stressful or traumatic events, as evidenced by reductions in posttraumatic stress symptoms. The instruction to formulate recommendations for persons dealing with the same trauma seems more helpful than standard disclosure or focusing on one's own past, present, and future coping endeavours. Overall, expressive writing seems to be a successful method of improving trauma processing. Determining the appropriate setting (e.g., self-help vs. therapeutic context) for disclore can be seen as an objective of future research. Chapter 8 - Some educators have failed to acknowledge the prevalence of test anxiety and its effect on academic performance among university students. This study addresses this issue at the university level using data collected through the Revised Test Anxiety (RTA) instrument and Sarason’s four-factor model as a basis for measuring test anxiety. The study also investigates the effect of demographic factors on test anxiety. Findings reveal that test anxiety is significantly and negatively related to academic performance. Reasons for these findings are addressed. Chapter 9 - In many countries, university students now constitute a significant proportion of their age group. As in the general population, depression is relatively frequent in this group, and affects women more than men. In the study described here we evaluated the prevalence of depression, depressive symptoms and associated factors among 365 young women sampled randomly, with stratification by year and discipline, from among the 18,180 female students attending a Spanish university (65.9% of its total student roll). The prevalence of current major depressive episode was 10.4% (95% CI 7.5-14.0%). Among students with current depression, the commonest symptoms were depressed mood (86.5%) and alteration of sleep (78.9%). Some 52.6% of depressed students had suffered one or more previous depressive episodes (M = 1.2; SD = 1.5), and 13.2% had attempted suicide, but the existence of previous depressive episodes did not increase the risk of a current episode. Increased risk was associated with recent problems, which multiplied the odds of depression by 2.31 (95% CI 1.26-4.26), and with smoking in the past month, which multiplied the odds of depression by 2.01 (95% CI 1.09-3.89), but not with the use of alcohol, cannabis or cocaine in the past month. Nor was there any significant association between depression and declared social class, monthly family income, university course level, geographical

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background (urban or rural), persons lived with during term time (family, friends, etc.), whether all the previous year's exams had been passed, sports activity, or academic discipline. Chapter 10 - The study examined the mood states of 229 men and women who are simultaneously full-time students and school staff when coping with their dual-demanding stressful environments. A causal model was developed to demonstrate that the dualdemanding stressors that the respondents faced affected their moods; these moods are prebehavioral factors that affected their coping strategies. Results of multilevel analyses indicated that men and women differ in the magnitude of their experienced moods, but both genders experience vigorous moods as a prime emotional reaction to the dual-demanding environment. Moods were found to affect both male and female coping strategies, in all categories except social support. The genders differed in the coping strategies adopted, except for task-oriented strategies. In addition, the analyses revealed gender differences in expressing angry and depressed moods, where females reported experiencing higher levels. These results reinforce our assumption that coping with dual-demanding environments, especially by individuals who are employed in stressful occupations, reflects not only a gender-based tendency but also the mood states that derive from the stressors. Results revealed that men and women manifest identical patterns in coping with dual-demanding stressors, and that these patterns are related to their moods. Thus, coping strategies seem to depend on context rather than on gender. Chapter 11 - The aim of this research is to examine anger expression reactions and anger control behaviors with respect to gender and education levels of the students when they are angry. Subjects were recruited from Gazi University, Abidinpasa High School and Aksaray Anatolian Hotel and Tourism Vocational High School and consist of 466 students. Inventory was prepared by the researcher to collect data about demographic qualities and anger behaviors of the students. Data were analyzed by frequency, percent and chi-square techniques. Results indicated that when the students get angry, they “sulk or make sour face”(77%), “try to think that everybody does not have to behave as they want”(76%) and “think that they can handle with the situation which made them angry” (75%). According to gender variable, male students significantly “say nasty things to the others”, but “try to be more intelligent and indulgent”, “to be more coolheaded”, “more think that not being able to control anger is a weakness” and “more think that they will not let others make them angry” than female students. On the other hand, it was found that female students more “sulk or make sour face”, “feel helpless, feel cry” and “say sarcastic words to the person who made them angry” than male students when they are angry. According to educational status, it was determined that while female high school students significantly “yell or scream more”, “argue with the person who made them angry” and “say nasty things to the others” more than female university students, female university students “express their anger in a more suitable way”, “try to see pozitif sides of the case”, “try to convince themselves not to be angered” more and “think that everybody does not have to behave as they want” when they feel angry. It was seen that while male high school students “make fun of the person who made them angry” more, male university students “do nothing at all, quite; suppress their their anger” more, “sulk or make sour face” and “withdraw from the people”.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 1

TRAIT ANGER, ANGER EXPRESSION, AND THEMES OF ANGER INCIDENTS IN CONTEMPORARY UNDERGRADUATE STUDENTS Sandra P. Thomas University of Tennessee, Knoxville Knoxville, Tennessee, USA

ABSTRACT Guided by Trait-State Anger Theory (Spielberger et al., 1983), trait anger, anger expression, and written narratives of anger incidents were examined in 305 undergraduate students. Fischer et al.’s (2004) coding scheme was used to assess reasons for anger, the relational context of the incident, methods of expressing anger, and outcomes. The chief provocateur for all students was a non-romantic intimate, but important differences were observed when comparing 3 subgroups: (1) students scoring high on angry temperament, (2) those scoring high on angry reaction, and (3) those scoring low on the entire trait anger scale. Interventions for dysfunctional anger are proposed.

INTRODUCTION In the lively realm of emotion research in the early 21st century, investigations are ranging from the micro-level (neurons) to macro-levels (societies, cultures) and across several of the subspecialties of psychology (clinical, developmental, and health psychology, to name only a few) (Salovey, 2001). The emotion of anger is compelling increased attention from researchers because its dysfunctional manifestations surround us in our daily lives. As we travel, work, and play, we frequently encounter out-of-control anger behavior (publicized in the media as “air rage,” “desk rage,” and “road rage”). In addition to its social consequences, mismanaged anger has serious consequences for personal health. Deservedly, anger is

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occupying the attention of a number of health psychologists because of its effects on both physical and mental health. My own program of research on anger, now approaching the 20-year mark, began with an intense interest in women’s anger. Amazed at the void in research literature, despite seminal theoretical and clinical papers (e.g., Bernardez-Bonesatti, 1978; Miller, 1983; Lerner, 1977), I formed a research team of psychologists and nurses and undertook the Women’s Anger Study, which included both clinical and community samples (Thomas, 1993). Women’s anger was examined in relation to their self-esteem, stress levels, social support, and social role responsibilities as mothers, wives, and workers, as well as indicators of their physical health (such as blood pressure) and mental health (such as depression and substance abuse). During the first phase of the Women’s Anger Study, data were mainly quantitative, derived from well-established, valid and reliable instruments. However, women also were invited to write responses to open-ended questions about their stress and anger. These brief narratives were enlightening, but left us wanting to know more about the situational context in which anger episodes are embedded, and the deeper meaning of these experiences. A woman’s anger at her mother was not like anger at her husband or her teenage daughter. Hence, more recently, I (along with various members of my research team) have conducted phenomenological studies involving in-depth, face-to-face interviews with participants, including both men and women (e.g., duMont, Droppleman, Droppleman, & Thomas, 1999; Fields et al., 1998; Mozingo, Davis, Thomas, & Droppleman, 2002; Thomas, 2003; Thomas, Smucker, & Droppleman, 1998). I turned to existential phenomenology, using a procedural approach developed at the University of Tennessee (Pollio, Henley, & Thompson, 1997; Thomas & Pollio, 2002), because I wanted a way to grasp the meaning of participants’ anger, not merely its correlates. The phenomenological approach involves entrance into the participant’s world in a humble manner to obtain “a direct description of…experience as it is” (Merleau-Ponty, 1962, p. vii). Qualitative approaches have been slow to gain acceptance in psychology. In fact, Fischer (2006, p. xiv) contends that “among the social sciences, especially in North America, psychology has been slowest to veer from its natural science model to explore events as lived rather than as measured.” Only using the qualitative approach, however, did I learn how much painful inner conflict anger produces, for both men and women. Through the qualitative studies, I became convinced that very few people feel good about the way they manage their anger. Few study participants report ever having role models whose anger behavior they wanted to emulate. Regret, shame, and guilt are acknowledged by most. The primary impetus for my continuing work is my conviction that effective and health-promoting anger management modalities must be identified and then widely disseminated, especially to young people whose emotional habits are still in the formative stages. In this chapter, I report findings of a new study of college students, in which I continue to include a qualitative component (written narratives of anger incidents), while also employing well-known quantitative measures to permit comparability to previous college samples. Before proceeding to discuss the study design and findings, I review the literature documenting anger’s importance to health, the literature that lends urgency to my research agenda. Additionally, I review several theoretical perspectives on anger before introducing Trait-State Anger Theory (Spielberger, Jacobs, Russell, & Crane, 1983), which has guided much of my work, including the present study.

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ANGER’S CONNECTION TO DISEASE RISK AND DISEASE OUTCOMES Anger’s importance to physical and mental health has been demonstrated in numerous studies within health psychology and behavioral medicine over the past 30 years. Since anger arousal is a common occurrence in daily life, unlikely to be eradicated even if people attempted to do so, investigators have sought to identify which aspects of it are pathogenic. Complicating research efforts is the multidimensional nature of the anger construct, (i.e., cognitive, affective, and behavioral dimensions) presenting substantial measurement challenges. Further complicating matters for researchers is lack of clarity and specificity in definitions of anger, hostility, and aggression (terms that are often used interchangeably by researchers).

Issues Regarding Definitions of Anger-related Terms Spielberger and his colleagues, because of the overlap among anger, hostility, and aggression, decided to refer to the constructs collectively as the “AHA! Syndrome” (Spielberger, Johnson, Russell, Crane, Jacobs, & Worden, 1985). Although there is undoubtedly overlap and intercorrelation among anger, hostility, and aggression, a number of scholars (including Spielberger) have been trying to delineate distinctions among the terms. Presently, there is general agreement among psychologists that hostility refers to a characteristic attitude of cynicism and mistrust, an attitudinal set that predisposes a person to frequent bursts of anger. The hostile person could be said to approach the world with a chip on the shoulder, ready to be offended. Anger is the emotion that is felt when an offense takes place. Anger and hostility are correlated but not synonymous, because not all anger is fueled by hostile cognitions. Nor is all anger irrational, as Ellis (1973) and others have contended. Research by Thomas (1995, 2003) indicates that everyday anger can be a justifiable, healthy, and rational response to a violation (e.g., of one’s rights, values, or expectations of reciprocity in significant relationships). There is an old notion that there is an anger continuum, with aggression or violence as the endpoint after angry feelings continue to escalate. This is not supported by research, however. In nonclinical populations, most anger is relatively short-lived and does not involve hurtful actions toward others (Averill, 1982). Anger expression can even prevent aggression, because it may elicit a contrite apology from the other person (Izard, 1993). Aggression, on the other hand, involves verbal or physical actions designed to inflict harm on another; it can be “cold” (enacted in a premeditated fashion) or “hot,” enacted in a sudden rage.

Styles of Anger Expression Of critical importance to health is what a person characteristically does with anger once it has been aroused (often called the “anger expression style”). In early research on anger expression, a unidimensional conceptualization dominated, with low scores indicating that anger was kept inside (Anger-In) and high scores indicating anger directed outwardly (AngerOut) (Funkenstein, King, & Drolette, 1954). In subsequent studies, conducted with an anger

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expression instrument developed by Spielberger et al. (1983), Anger-In and Anger-Out proved to be independent dimensions; correlations between the two were essentially zero (Spielberger et al., 1985; Thomas & R.L. Williams, 1991). Furthermore, Anger-In and AngerOut are not the only choices available when anger has been provoked. Spielberger (1988), realizing that his Anger-In and Anger-Out scales did not capture all possible anger expression modes, developed an Anger Control scale that measures behaviors such as calming down quickly when anger is aroused and stopping oneself from losing one’s temper. Another possibility is discussion with the provocateur, or with a supportive confidant (termed AngerDiscuss in the research literature). Anger-Discuss was included in a research instrument for the first time in the Framingham Heart Study (Haynes, Levine, Scotch, Feinleib, & Kannel, 1978).

The Big Question: Which Anger Dimensions are Salient to Heath Outcomes? Which aspects of the complex AHA! phenomenon are risk factors for, or precursors of, deleterious health outcomes? Is a hostile attitudinal set the pathogenic predictor variable? Or is aggressive behavior the dangerous factor? If only some types of angry thoughts and behaviors are maladaptive, can these be identified by clinicians with confidence? Is the frequency of anger arousal a predominant concern? Or is the intensity or duration of a person’s response more important? What are the effects on health of venting anger in an outburst (Anger-Out) or seething silently (Anger-In) for hours after an altercation? Answers to these questions have been emerging from the behavioral medicine and health psychology studies, and we will review key findings shortly. Before examining this literature, I need to point out that I will use often use the generic term “anger” as I discuss the research findings. Unfortunately, researchers still fail to be precise in specifying whether they are investigating hostility, anger, and aggression. Even when they are purportedly studying anger, closer scrutiny reveals that they did not use an anger instrument (e.g., “anger” appears in the title of a journal article, but perusal of the instrumentation section reveals that the researchers used the Cook-Medley Hostility Scale [Cook & Medley, 1954]--a measure of cynical hostility, not anger). As Averill (1994) has noted, anger has become a synecdoche (common figure of speech) for all kinds of aggressive syndromes. Thus, readers should bear in mind that some of the cited studies actually focused more so on hostility or aggression than on anger, despite the use of the word anger in the title (or elsewhere). Seeking out the original research reports is strongly encouraged to examine the instrumentation more closely.

Anger and Cardiovascular Disease (CVD) Considerable attention has been devoted to anger’s effects on the cardiovascular system, because anger is known to evoke the greatest cardiovascular responses (i.e., heart rate, blood pressure) of any emotion, even greater than fear (Schwartz, Weinberger, & Singer,1981). Anger is associated with increases in both cardiac output and peripheral vascular resistance (Sinha, Lovallo, & Parsons, 1992). It logically follows that an emotion producing such a powerful physiological arousal could eventually contribute to disease processes,

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especially if it is experienced frequently, intensely, and for significant amounts of time during the work day and/or during the conflictual interactions of family and community life. Cardiovascular disease (CVD) is the leading cause of death in the United States (Anderson & Smith, 2005) and causes significant decrements in the quality of life for millions who live with the disease. Not surprisingly, psychologists have joined with our colleagues in medicine who seek to develop effective preventive and ameliorative interventions for CVD. The new field of psychocardiology was featured on the cover of the January 2007 issue of Monitor on Psychology, and several articles within the issue highlighted the efforts of researchers who are studying psychosocial risk factors for CVD, such as hostility and anger (Clay, 2007; Geipert, 2007; Meyers, 2007). While the etiology of cardiac disease is multifactorial, hostility is an established risk factor, independently and in combination with other factors such as obesity, smoking, and alcohol consumption (Bunde & Suls, 2006). Anger is an independent risk factor as well (e.g., J.E. Williams, Nieto, Sanford, & Tyroler, 2001). Particularly impressive are the prospective studies, in which initially healthy young people fill out anger questionnaire and disease outcomes are measured much later. As an example, consider the Precursors Study. Male medical students at Johns Hopkins from the graduating classes of 1948 to 1964 have been tracked for a median follow-up period of 36 years. Those who exhibited a high level of anger as students were significantly more likely at follow-up to have premature cardiovascular disease, particularly premature myocardial infarction (Chang, Ford, Meoni, Wang, & Klag, 2002). To briefly summarize other key research findings regarding anger, hostility, and CVD: •

•

•

•

•

A hostile, distrusting attitude toward other people has been linked to cardiovascular symptoms, such as chest pain, as well as structural changes in the blood vessels of the heart and the peripheral circulation, including coronary artery calcification and coronary atherosclerosis, and carotid atherosclerosis (Iribarren et al., 2000; Pollitt et al, 2005) A volatile, overt anger expression style is associated with coronary heart disease, myocardial ischemia in daily life, and myocardial infarction (Gabbay et al., 1996; Kawachi, Sparrow, Spiro, Vokonas, & Weiss, 1996; Krantz et al., 2006; Mittleman et al., 1995). In fact, a single explosive outburst of anger can be fatal to someone with advanced CVD (Mayne, 2001) Even re-living an anger incident at the request of an experimenter in the laboratory can cause significant reduction in left ventricular ejection fraction (an indicator of myocardial ischemia) in patients with coronary artery disease (Ironson et al., 1992) Habitual suppression is just as problematic as the tendency to have explosive outbursts. Actively suppressing emotion heightens the sympathetic activation of the cardiovascular system (Gross & Levenson, 1997). Anger that is felt but not overtly expressed is associated with higher blood pressures and with diagnosed hypertensive disease (Perini, Muller, & Buhler, 1991; Thomas, 1997a) and incident heart disease (Gallagher, Yarnell, Sweetnam, Elwood, & Stansfeld, 1999) Suppressed anger was an independent predictor of coronary heart disease at 8-year follow-up in the longitudinal Framingham Heart Study (Haynes, Feinleib, & Kannel, 1980)

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Anger and other Disease Conditions The same maladaptive anger patterns that are linked to CVD (i.e., hostility, excessive anger-out, excessive anger-in) appear to predispose individuals to other conditions as well. Anger affects many interacting organ systems. In the burgeoning empirical literature are studies implicating anger in conditions ranging in severity from the common cold to cancer: Among the studies are these: • •

•

•

• •

Hostility predicted not just CVD, but poorer general health and earlier mortality, in a meta-analytic review of research (Miller, Smith, Turner, Guijarro, & Hallet, 1996). Research by immunologists showed that intensely hostile interactions, such as arguments with an intimate partner, lower one’s immunocompetence (Kiecolt-Glaser et al., 1993). On the other hand, stifling anger and engaging in resentful rumination about grievances can be equally detrimental to health. Anger suppression has been linked to decreased function of the immune system (Petrie, Booth, & Pennebaker, 1998; Larson, Ader, & Moynihan, 2001) and to a variety of common illnesses or conditions (Forgays, Richards, Forgays, & Sujan, 1999). Extremely low anger scores have been noted in numerous studies of patients with cancer, suggesting suppression, repression, or restraint of anger. Although additional longitudinal studies are needed, suppressed anger is thought to be a factor both in development of cancer and in its progression after diagnosis (Temoshok, 1987; Thomas et al., 2000). Anger suppression was associated with early mortality in a 17-year prospective study conducted by Harburg, Julius, Kaciroti, Gleiberman, and Schork (2003). Anger suppression and depression were associated with increased death rates in elderly clergy studied over a 4-year period (independent of age, sex, education, smoking, alcohol use, and obesity (Wilson, Bienias, Mendes de Leon, Evans, & Bennett, 2003).

It is beyond the scope of this chapter to elucidate the explanatory mechanisms of these anger-disease linkages; in fact, researchers are still identifying contributing and mediating factors, such as catecholamine levels, lipid levels, serotonin levels, and platelet physiology (see discussions by Iribarren et al., 2000; Lovallo & Gerin, 2003; Pert, 2002; Sloan et al., 2001; J.E. Williams et al., 2000; R.B. Williams, 1994). In addition to the direct effects of anger on health through physiological arousal and immune system inhibition, anger impacts health indirectly through cognitions and behaviors (Mayne, 2001). Behaviors that are often used to alleviate or diminish angry emotion are overeating, smoking, drinking, and using drugs (including over-the-counter, prescription, and illicit drugs) (Arnow, Kenardy, & Agras, 1995; Everson et al., 1997; Grover & Thomas, 1993; Scherwitz & Rugulies, 1992). Further research is necessary to fully delineate the complex relationships among a host of variables. Moreover, there are gaps in the extant literature. Women were excluded from many of the pioneering studies (e.g., an Israeli study of anger and blood pressure in 10,000 male civil service workers [Kahn, Medalie, Neufeld, Riss, & Goldbourt, 1972]; the Western Collaborative Group Study of coronary heart disease [Rosenman, Brand, Jenkins, Friedman,

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Strauss, & Wurm, 1975]). Recently, studies are revealing gender differences that deserve further examination (e.g., Hogan and Linden’s [2005] finding of curvilinear relationships of expressed anger and blood pressure in women but not in men; Suarez’s [2006] finding of associations between depressive symptoms, hostility, anger expression, and insulin resistance in women but not in men). Despite some gaps in the literature, the aggregated evidence is strong that dysfunctional anger can negatively impact physical health. What about anger’s effects on mental health?

ANGER’S RELEVANCE TO MENTAL HEALTH AND INTERPERSONAL RELATIONSHIPS Anger and Mental Health Beyond anger’s significance for physical health, it has obvious relevance to mental health. Poorly regulated anger is characteristic of several personality disorders (e.g., borderline, paranoid), and, when coupled with impulsivity, is known to increase the risk of suicide (Plutchik, Van Praag, Conte, & Picard, 1989). Anger’s link to depressive illness is well known, although it is not clear whether maladaptive anger is a precursor or a byproduct of depression (e.g., Koh, Kim, & Park, 2002).

Anger and Interpersonal Relationships Individuals exhibiting greater anger and hostility are known to have greater frequency and severity of daily hassles and less social support (Siegler et al., 2003; Smith & Frohm, 1985; Thomas, 1993). During the course of a typical day, hostile people have more tense, angry, and confrontational interactions with other people than nonhostile people do (Brondolo, Rieppi, Erickson, Sloan, & Bagiella, 2002). Understandably, chronically angry people have more occupational problems (Caspi, Elder, & Bem, 1987). High anger participants (in comparison to low anger participants) change jobs more frequently, report more conflict at work, and say they are less satisfied with their current jobs (Lench, 2004). Further, studies show that high anger individuals report more conflict with friends (Lench, 2004) and higher rates of divorce (Caspi et al., 1987). Lest the reader conclude that anger should be suppressed to preserve harmony in relationships, (a belief expressed by many women), there is evidence that suppressed anger is significantly correlated with a number of negative consequences, including damaged friendships and feeling dumb, embarrassed, ashamed, or depressed (Deffenbacher, Oetting, Lynch, & Morris, 1996; Thomas et al., 1998; Thomas, 2003).

Summary In summary, what does the health psychology literature tell us? On the one hand, explosive anger is deleterious to health. On the other hand, suppression and rumination are

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detrimental as well. Clearly, achieving more effective management of anger is necessary for optimal health and satisfying relationships. Is there any indication in the research literature of a type of anger behavior that could be health-promoting rather than health-damaging? In 1979, Harburg, Blakelock, and Roeper described a reflective anger coping style that was associated with lower blood pressure. Around the same time, the anger expression style called Anger-Discuss was identified as a better option for cardiac health than Anger-In or AngerOut in the Framingham Heart Study (Haynes, Feinleib, & Kannel, 1980). Subsequent research has shown that Anger-Discuss is correlated with better general health and lower blood pressure levels, as well as greater self-efficacy and optimism (Davidson, et al., 1999; Hogan & Linden, 2004; Thomas, 1997b). Discussing anger can be useful in sorting out what happened during the confusion of a heated exchange. Additionally, it facilitates the formulation of ideas to solve problems. Used constructively, anger can alert intimate partners that something needs to be corrected and can mobilize social activism to combat injustices such as racism and sexism. In situations where anger cannot be expressed (because of power imbalance, social disapproval), vigorous physical exercise or calming procedures are efficacious. But many people have not mastered the skills of anger diffusion or constructive anger expression. In fact, people have fewer strategies for managing anger than for any other emotion (Tice & Baumeister, 1993), and some people formed very unhealthy anger patterns during childhood and adolescence. In the next section, we will explore how unhealthy anger patterns form.

HOW UNHEALTHY ANGER PATTERNS FORM Although developmental and psychodynamic theories offer richly detailed postulations about early childhood influences on emotional development, many theories are not buttressed by empirical evidence, nor are they applicable specifically to the emotion of anger. Only in recent years has a small cadre of researchers turned to the study of anger in young children. While some researchers focus on the child’s temperament, others focus more on the child’s interactions with significant others.

Nature versus Nurture? We have known since the 1960s, from landmark studies by Chess, Thomas, and Birch (1965) and others, that babies have unique temperaments from birth, with a genetic basis. Both reactivity and self-regulation are dimensions of temperament (Rothbart, 1994). A child’s basic temperament displays considerable stability over time (Caspi & Silva, 1995) and is obviously influential in his or her emotional tendencies (Zawadzki, Strelau, Oniszcenko, Riemann, & Angleitner, 2001). An irritable toddler is likely to be a moody teenager. However, basic temperament can be modified by interactions with parents, teachers, and peers. Rewards and punishments, as well as the anger management style of admired role models, help to shape the growing child’s repertoire of anger behaviors. Several anger-related studies have highlighted the importance of the infant having secure attachment to the mother. “Difficult” children are less likely than children perceived as “easy”

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to become securely attached (Calkins & Fox, 1992; Fox & Calkins, 1993). Observational studies suggest that children who do not form secure attachments to their mothers tend to “develop an internal view of the world…as threatening and hostile, [in which] other people are seen as unavailable” (Grunbaum, Vernon, & Clasen, 1997, p. 187). These children tend to exhibit angry behavior; their targets may respond angrily and/or punitively, thus perpetuating their perception of a hostile world. Woodall and Matthews (1989) broadened the focus beyond the maternal-infant relationship to the family environment (as measured by the Moos and Moos [1981] Family Environment Scales). Anger of schoolchildren in grades 2-12 was assessed by several scales, including the Spielberger Trait Anger Scale (Spielberger, Jacobs, Russell, & Crane, 1983). In familial environments characterized by low supportiveness and cohesiveness, children were more chronically and openly angry. Parental conflict can be quite distressful and frightening to children, especially when disputes are handled by yelling and cursing (Cummings & Davies, 1994). Further, children cannot always remain bystanders when parents fight: they can be recruited into parental conflicts, serving as allies or scapegoats. Divorce of parents does not necessarily terminate family conflicts, which may continue for years over financial settlements, child custody, and visitation arrangements. In one study, high expressed anger of the custodial parent (mother, in this case) was related to poorer adjustment of adolescent children (Dreman, 1995). Notably, the mothers had been divorced for an average of 9 years by the time of Dreman’s data collection. Harsh physical punishments are known to foster the development of aggressive behavior in children (W. McCord, J. McCord, & Howard, 1961; Miller, 1980; Olweus, 1980). Physical assault was the number one precipitant of anger in a study of children from first, third, fifth, and seventh grades (Rotenberg, 1983). Parents, siblings, and peers were the main provocateurs, with siblings topping the list. Sibling interactions, which may be as important as transactions with parents, have not received adequate attention from the researchers who are trying to understand anger in children and adolescents (Ewart, 1991). Peer interactions have been extensively studied by Dodge and colleagues (e.g., Dodge & Coie, 1987). In brief, angry behavior may accrue rewards from peers in the short-term, but continued angry, aggressive behavior leads to peer disapproval and rejection (Lemerise & Dodge, 1993). Facility with language is a determinant of children’s anger behavior. Children who learn to verbalize “I’m angry” are less likely to engage in physical aggression (hitting, biting) (Brody & Hall, 1993). Level of exposure to media violence is another factor. A steady stream of aggressive role models in American television, movies, and videogames depict explosive anger behavior that is rewarded, not punished. Many of these role models are greatly admired and emulated. The greater the exposure to media violence, the greater the aggressive behavior in children and adolescents (Bushman & Anderson, 2001). There is some evidence that anger coping styles are becoming routinized as early as middle school or high school. For example, one longitudinal study measured students as high school freshmen and then as seniors using Siegel’s (1984) multidimensional Anger Index; there was no change in anger scores over time (Kollar, Groer, Thomas, & Cunningham, 1991). Faulty emotion regulation habits developed as children may continue through adolescence and adulthood, unless modified by education or counseling. College may be an optimal time for delivery of psychoeducational anger management interventions. Upon entrance, college students are still adolescents (Elliott & Feldman, 1990), and their

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personalities can change markedly during their years at college. Longitudinal studies show that personality is more fluid in adolescents and young adults (Roberts & DelVecchio, 2000). What is presently known about anger in college students? Let us turn to the extant research.

Anger in College Students There is actually quite a lot of research on anger in college students, perhaps because they comprise such convenient samples for their professors to study. However, a great deal of this research is conducted in the artificial environment of the laboratory. Study participants may be asked to keep their hands in painfully cold water as they administer rewards and punishments to their fellow students (e.g., Berkowitz, 1990). This body of anger research is not reviewed here because it fails to inform about emotional experience in the real world. Descriptive research on college student anger began in 1926. Two very early studies elucidated causes of anger in Barnard College women, who were asked to record anger incidents for a week (Anastasi, Cohen, & Spatz, 1948; Gates, 1926). The average number of incidents ranged from 3 per week to 16 per week (with some women reporting as many as 42 incidents). People, not things, provoked anger in the majority of cases (45.8% in Anastasi et al., 79.3% in Gates). The primary cause of anger in both studies was termed thwarting (of self-assertion in the Gates study, of plans in the Anastasi study). The women in the Gates sample reported the most violent reactions to “domineering attitude of other persons” (1926, p. 332). It should be noted that the word “violence” is not used in the way we use it today, because shaking or slapping a provocateur was only reported in 3 of 145 anger incidents. Violence apparently referred to verbal behaviors (i.e.,“excited talking or making an angry exclamation”) that would be considered mild today. The women admitted, however, to impulses to slap, pinch, scratch, and choke their provocateurs, as well as making verbal responses. Shame, irritability, and weariness often followed anger incidents (Gates, 1926). This line of research lagged for a number of years, in part because there was little research of any kind being conducted on emotions. Lazarus (1991, p. 4) has commented on the “perplexing resistance to emotion in mainstream academic psychology until the 1960s,” noting that only an occasional monograph on emotion appeared in the literature between 1920 and 1960. In a revelatory emotion study of the 1980s designed to identify the prototypical features of all the basic emotions, Shaver, Schwartz, Kirson, and O’Connor (1987) asked 120 psychology students to write accounts of emotional experiences. For each emotion, coders identified antecedents, responses, and self-control procedures. The anger prototype of the college students included features of attack, such as “Loud voice, yelling, screaming, shouting,” “Attacking something other than the cause of anger, e.g., pounding on something, throwing things,” and “Incoherent, out-of-control, highly emotional behavior” (p. 1078). In 95% of the students’ written accounts of their anger, a judgment had been made that “the frustration, interruption, power reversal, or harm is illegitimate” (p. 1077). Anger caused a narrowing of attention, such that the students reported they could think of nothing else but the injustice that occurred. Self-control procedures included attempts to redefine the situation or “view it in such a way that anger is no longer appropriate” (p. 1078). Other important studies of college students during the 1980s and 1990s, conducted by Averill (1982), Deffenbacher (1992), Scherer (1997), and others, will be discussed, in detail, a bit later in the paper.

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Is the Current Generation Angrier? There is speculation that contemporary college students are angrier than those of previous generations. Several writers have described the sense of “specialness” or entitlement displayed by the children of the baby boomer generation who populate college classrooms today. A 1998 article in The Chronicle of Higher Education revealed concerns of professors across the nation about student incivility, insubordination, and intimidation of faculty (Schneider, 1998). The following examples were cited: “When a chemistry professor at Virginia Tech asked his class how to solve an equation, a student in the back of the room shouted, ‘Who gives a s---?’ When a scholar at Utah State University refused to change a grade, a student screamed at her, ‘Well, you goddamned bitch, I’m going to the department head, and he’ll straighten you out!’ …A historian at Washington State University was challenged to a fight when a student disliked the grade he’d received” (Schneider, 1998, p. A 12).

Because this literature suggests higher levels of anger (and more overtly expressed anger) in today’s college students, one of the aims of the present study is to compare the present sample to previous samples of students. One basis of comparison will be scores on trait anger, a construct from Trait-State Anger Theory (Spielberger et al., 1983), the theory that is perhaps the most widely used by health psychologists. Before elaborating on this theory, a brief overview of other prominent theories is presented.

CONCEPTUALIZATIONS OF ANGER IN THE PSYCHOLOGICAL LITERATURE Theory comes from a Greek word meaning “I behold;” therefore, the purpose of theory is to enlarge our observation (Coles, 1989). Anger research has been framed within several emotion theories, each illuminating a particular aspect of the anger experience, while failing to shed light on other aspects. Evolutionary theories of emotion emphasize biology; other theories emphasize cognitive appraisals or the situational context in which anger is provoked. There is not much evidence that the theorists aligned in different camps read each other’s works, although cross-fertilization would appear to be fruitful. Only those theories that have been used in major anger studies are reviewed in the following pages.

Anger from the Perspective of Evolutionary Theories In 1872, Darwin proposed that (a) humans are genetically programmed with certain emotions; (b) these emotions, having evolved because of selection factors in the species, have adaptive value for survival; and (c) emotions are universal, not culture-specific. Darwin conducted observational studies that supported these propositions. Several contemporary researchers tested various tenets of evolutionary theory, including Ekman (1972), Izard

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(1971), Plutchik (1980), and Tomkins (1963, 1980, 1991). Plutchik (1980) built upon Darwin’s idea of the emotions as adaptive for survival of the species. For each of the 8 emotions he deemed “primary,” he proposed its origin and function. The origin of anger was said to be meeting an obstacle viewed as enemy; its function, destruction of that enemy. Because blood goes to the hands in anger, the autonomic nervous system is preparing the individual for fighting (Ekman, 1994). Supportive of Darwin’s assertion that emotions are universal are studies such as Ekman’s (1972), in which people in both Eastern and Western cultures—even preliterate cultures such as New Guinea—could correctly identify all of the primary emotions (anger, fear, sadness, surprise, disgust, and joy) in photographs of faces. Considerable attention continues to be devoted to facial expressions. The role of facial muscle movement in activating and regulating emotional experience has been a central focus in Izard’s (1980) emotion theory, which is tested using electromyography. Coding systems designate the facial muscles involved in each emotion, and electrodes are placed accordingly. According to Izard (1990), substantial evidence has accumulated regarding congruence among facial, behavior, physiological function, and individuals’ self-reports of emotion experiences. Facial muscle movements do appear to elicit or alter feeling states. Another scholar within the Darwinian tradition, Tomkins, views the skin of the face as more essential than its musculature in providing feedback for emotions. Among his research methods over the years is high-speed photography of the face. Tomkins’s (1980) propositions include the following: (1) affects are muscular and glandular responses triggered by innate mechanisms; (2) affect is primarily facial behavior; (3) when people become aware of their facial (or visceral) responses, they are aware of their affects; (4) people learn to generate from memory images of these responses; (5) affect amplifies not only its activator but also the response to the activator and to itself. Tomkins considered anger among the 9 innate affects, readily evident to observers by a red face, frown, and clenched jaw. Further, he considered anger the most urgent of all affects and the most problematic in human interaction (Tomkins, 1991).

Anger from the Social Constructivist Perspective Quite different from the evolutionary theories is the social constructivist point of view. Constructivism refers to the “imposition of meaning or structure on events…This imposed meaning or structure can come from social, cultural, or biological forces. However, the social constructivist position suggests that feelings are more social than biological constructions” (Kassinove, 1995, pp. 21-22). The social constructivist perspective is exemplified by Averill (1982), who conducted an oft-cited and comprehensive study of anger in college students and community-dwelling adults. Averill used a diary method to collect descriptions of anger as it occurred in everyday life, discovering that most anger was provoked within intimate relationships, by misdeeds that were potentially avoidable. The most frequent responses during anger episodes were calming activities and talking over the incident. Direct physical aggression against another person was very rare. Averill’s research demonstrated that anger is a highly interpersonal emotion that cannot be understood without consideration of the social context.

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Anger from the Perspective of Appraisal Theorists The basic premise of appraisal theories of emotion is that emotions are generated by a person’s subjective appraisal of a situation; the appraisal involves cognitive processing of the significance of the event (Scherer, 1997). Put simply, an event could evoke anger in one individual (who perceives an insult) and laughter in another (who perceives a harmless practical joke). Magda Arnold (1960) is considered the first modern theorist to propose that appraisals determine the particular emotion that a person will experience. In her conceptualization, anger is generated when a harmful object is present and appraised as difficult to overcome. Newer theories have been posited by Scherer (1982), Roseman (1984), Lazarus (1991),and others, and tested in both laboratory and questionnaire studies. In most of the appraisal theories, anger is said to occur when an incident of injustice is caused by an external agent, providing the aggrieved individual with impetus to attack. Discrepant in some respects from the other theories is the theoretical model developed by Berkowitz (1990). The Berkowitz model (termed cognitive-neoassociationistic) integrates automatic arousal processes and higher-order cognitive concepts such as appraisals. He described a series of stages in the formation of anger. First, primitive associative processes are dominant and then more complicated cognitive processes become involved. There is an initial rudimentary angry reaction, and then the person makes causal attributions and considers alternative courses of action. The person could decide that the provocation is too trivial for anger, thereby moderating the arousal. Another possibility is evaluating the provocation in a way that escalates or prolongs the initial arousal. Berkowitz acknowledged a limitation in the model, in that it has “nothing to say about the kinds of interpersonal relationships that give rise to angry feelings, even though these interpersonal relationships are the source of much of the anger that occurs in everyday life” (Berkowitz, 1990, p. 494). According to Berkowitz, an external agent (such as another person) is not necessary for anger to be generated; internal physical discomforts such as headaches--or general unpleasantness-can evoke anger. In his most recent writing, he reiterates that the crucial determinant of anger is unpleasantness (Berkowitz & Harmon-Jones, 2004a). In response to Berkowitz and Harmon-Jones (2004a), Roseman (2004) has vigorously asserted that appraisals, not unpleasantness, are the primary determinants of anger. In Roseman’s own study of anger, subjects wrote narratives about emotional experiences that had actually occurred, then responded to researcher questions about their appraisals at the time of the events. Key elements in experiences of anger were: (1) situations that were unwanted, (2) caused by someone else, (3) characterized by low power, and (4) beliefs that one deserved a more positive outcome (Roseman, Spindel, & Jose, 1990). Scherer (1997) contends that the appraisal mechanism is universal across cultures, with different emotions being elicited by differentiated appraisals. Because Scherer’s 37-study is perhaps the most extensive cross-cultural study of emotions ever attempted, it deserves closer attention. The Intercultural Study on Emotional Antecedents and Reactions (ISEAR) involved 2,921 university students (55% women, 45% men, mean age 21.8). For reasons of comparability, data were always collected during classes at universities located in major cities. Over an 8-year period, data were collected in industrialized and affluent countries such as France, Japan, Australia, and the Netherlands, as well as less affluent, developing countries in Africa and Latin America. Anger was one of the 7 emotions studied. For each emotion, participants were asked to freely describe an incident in which they had most recently

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experienced that emotion. After completion of this portion of the task, participants were asked specific questions about appraisals, physiological symptoms, expressive reactions, and other aspects of the incident. Generally consistent with the findings of Roseman et al. (1990), anger was generated by appraisals of situation as unexpected, unfair, obstructive of goals, and caused by other people. Germane to the present paper is a secondary analysis of the ISEAR data conducted by Fischer, Rodriguez Mosquera, van Vianen, and Manstead (2004). A coding scheme was developed for the above-mentioned written descriptions of anger incidents. Only those situation descriptions which could be translated by a native speaker to English were used in the analysis. 1,028 student anger stories (representing 16 countries) were translated and coded. The coders identified the target toward whom anger was directed (intimates, strangers, or no specific target) and the reason for the anger (relational, attack on one’s status, personal or general injustice, or minor frustration). Several gender differences were found (e.g., men targeting anger at strangers more so than women), but the number one reason for anger (personal or general injustice) was constant across gender and countries. Gender and culture can have profound impact on appraisals (and subsequent behaviors), and a sizeable body of literature has accumulated on gender and cultural differences in anger. For example, many studies show men are more likely than women to exhibit cynical hostility and aggressive behavior (Stoney & Engebretson, 1994), and individualistic Westerners are more likely to overtly express anger than Easterners in collectivistic cultures valuing interdependence and harmony (Thomas, 2006). This literature, while interesting and important, is not reviewed here, for two reasons: (1) it was not an aim of the present study to explore gender differences; and (2) the cultural homogeneity of the college student sample prevented any examination of cultural differences. See Shields (2002) for delineation of differences between men and women in anger experience and expression; also see Thomas (2006) for an extensive review of the literature on cultural and gender differences as they relate to the assessment and treatment of anger disorders.

Anger from the Perspective of a Personality Trait Theory (Trait-State Anger Theory) A trait is defined as “a characteristic or quality distinguishing a person…, especially a more or less consistent pattern of behavior that a person possessing the characteristic would be likely to display in relevant circumstances” (Colman, 2001, p. 750). Gordon Allport (1937) studied traits for his doctoral dissertation and spurred tremendous interest in these enduring predispositions to behavior. Lines of research developed around trait anxiety, trait curiosity, and trait hope, among others (e.g., Ellsworth & Smith, 1988; Spielberger, 1998). Although traits were attacked during the hegemony of behaviorism, they are receiving fresh attention because of the personality-health associations discovered in recent years. It is clear that personality traits affect both health and longevity (Caspi, Roberts, & Shiner, 2005; Leclerc, Rahn, & Linden, 2006). Theorizing that anger is both a personality trait and a transient emotional state, Spielberger and colleagues (Spielberger et al., 1983; Spielberger, et al., 1985) developed the first questionnaire to measure both, the State-Trait Anger Scale (STAS), (later expanded to become the STAXI, which included the anger expression modes, i.e., Anger-In, Anger-Out,

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Anger Control). Trait anger refers to an individual’s overall propensity to become aroused to anger, a stable aspect of the personality over the long term. Spielberger et al. (1983, p. 169) hypothesized that persons scoring high on the trait anger questions of the STAS (T-anger scale) tended “to perceive a wide range of situations as anger-provoking (e.g., annoying, irritating, frustrating), and to respond to such situations with elevations in state anger.” Moreover, it was hypothesized that these individuals would experience more intense anger arousal than persons scoring low on the scale. Examples of T-anger scale items are “I have a fiery temper” and “I am a hot-headed person.” State anger refers to emotional experience at a particular moment, consisting of “subjective feelings of tension, annoyance, irritation, fury, and rage, with concomitant activation or arousal of the autonomic nervous system” (Spielberger et al., 1983, pp. 168169). Examples of items in the State Anger subscale of the STAS (S-anger) are: “I am furious” and “I am burned up.” The S-anger scale proved especially useful in measuring angry responses of participants in laboratory experiments. Commonly, these studies involved various anger-provoking stimuli, such as harassment by the experimenter while completing a frustrating task. Thousands of college students, military recruits, junior and senior high school students, and working adults were tested during the initial psychometric evaluations of the new StateTrait Anger Scale. As expected, the trait anger subscale was highly correlated with hostility measures such as the Cook-Medley Hostility scale (Cook & Medley, 1954) and the BussDurkee Hostility Inventory (Buss & Durkee, 1957). Factor analysis revealed a two-factor solution for the 10-item Trait Anger Scale: a 4-item factor labeled Angry Temperament, a 4item factor called Angry Reaction, and two other items. We will elaborate on the importance of these two components of trait anger a bit later. First, we discuss empirical evaluation of Trait-State Anger Theory by several research teams. Our discussion emphasizes Trait Anger because of its relevance to the present study. Deffenbacher, with various colleagues, conducted a series of studies during the 1980s and 1990s designed to test Trait-State Anger Theory (Deffenbacher, 1992). Typically, the subjects were college students who completed the STAS along with other self-report tools, including daily anger logs; subsequently, comparisons of high T-anger and low T-anger students were made. Findings strongly supported Trait-State Anger Theory and identified correlates of trait anger, such as lower self-esteem. To wit, Deffenbacher (1992) found that people scoring high in trait anger exhibit: •

• • • • • •

Greater anger responsiveness to a wide range of provocations, more frequent and intense daily anger reactions, and more severe physiological arousal and somatic symptoms (clenched jaw, shakiness) Tendency toward irrational beliefs (e.g., need for perfection) Lower self-esteem Tendency to be more tense, high-strung, irritable Poorer coping with chronic stressors Higher trait anxiety Strong tendency to express anger in maladaptive ways (i.e., outwardly in an antagonistic, less constructive manner, or inwardly)

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Later, Deffenbacher and colleagues (2003) adapted Trait-State Anger Theory to the specific situation of driving while angry, again recruiting a college student sample. Predictions derived from the theory were generally supported: higher anger drivers (compared to low anger drivers) scored significantly higher on Spielberger’s (1999) Trait Anger Scale and reported more risky and aggressive driving behavior, traffic tickets, and minor accidents. The tendency of persons high in trait anger to make risky choices was also shown in a series of studies conducted by Lerner and Keltner (2001). Faulty appraisals regarding degree of risk and personal vulnerability influenced respondents’ proclivity for making risky choices. Other research teams have provided further support for Trait-State Anger Theory and the construct validity of the Trait Anger Scale. High Trait Anger (HTA) subjects in a nonclinical adult sample surveyed by Tafrate, Kassinove, and Dundin (2002) were significantly more prone to exaggeration of the triggering event and cognitive distortions about it, as compared to Low Trait Anger (LTA) individuals. Consistent with earlier studies, HTA adults reported more frequent and more intense anger episodes than did LTA adults. They were more likely to vent their anger through verbal and/or physical aggression and to medicate it by misusing chemical substances. Furthermore, they were four times more likely than low LTAs to experience negative consequences in their interpersonal relationships. Strong correlations were found between Trait Anger scores and scores on Cognitive and Somatic Anger scales (Contrada, Hill, Krantz, Durel, & Wright, 1986) in Thomas’s (1993) study. Women scoring high on trait anger in Thomas’s study acknowledged faulty cognitions (e.g., “they are deliberately provoking me”) and difficulty letting go of anger (“I keep thinking about what happened over and over again”) as well as numerous somatic symptoms of anger, such as headaches, a tight knotted feeling in stomach, and faster respirations. As in Deffenbacher’s (1992) study, higher trait anger was associated with lower self-esteem.

Component Analysis: A Gap in the Literature What is missing in this growing body of trait anger research is teasing apart the temperament component and the reaction component. Some people who score high on trait anger truly have an angry temperament; they are hyperresponsive to a multitude of diverse stimuli, even trivial provocations. The Angry Temperament subscale of the STAS appears to measure a genetic propensity to be a “hot reactor.” Other people may react strongly to particular situations of criticism and injustice (i.e., score high on Angry Reaction), although they are not customarily so anger-prone (i.e., they do not score high on Angry Temperament). Carefully examining the two components of trait anger has implications for achieving greater conceptual clarity as well as for tailoring anger management interventions. One early study alerting researchers to the importance of component analysis was conducted by Crane (1981). Hypertensive patients were compared to medical patients who had no history of hypertension. As predicted, hypertensives scored higher than the comparison group on trait anger. Interestingly, differences in Trait Anger scores between the two groups were not because they differed in angry temperament but because the hypertensive patients scored high on angry reaction (i.e., the items assessing anger in situations of criticism by other people). Crane also found that the hypertensives suppressed their strong feelings about unfair criticism, rather than expressing them overtly to the other parties involved in the interactions.

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Another study suggesting there is value in looking at angry temperament and angry reaction separately was that of J.E.Williams and colleagues (2000), who examined the development of cardiac disease over a period of 6 years in a large sample (n=12,990) of initially healthy men and women. Those with higher levels of trait anger (measured by Spielberger et al.’s [1983] scale) were more likely to ultimately suffer heart attacks and sudden death than those with lower trait anger. Closer scrutiny of the data in 2001 revealed that it was the angry temperament component of trait anger, not angry reaction to criticism or unfair treatment, that predicted heart disease risk. In the new analysis, the association between each trait anger component and coronary heart disease was determined by Cox proportional hazards regression. Having a high score on angry temperament conferred more than twice the risk of cardiac events (compared to low angry temperament). Results of the proportional hazards regression analysis for angry reaction were not statistically significant (J.E. Williams, Nieto, Sanford, & Tyroler, 2001). Despite the foregoing evidence that it is valuable to examine the components of trait anger, few researchers have done so. Further, few trait anger researchers have invited study participants to describe their anger episodes in detail, including situational precipitants, relational context, behaviors, and outcomes. To understand an emotion, we must understand what it is about (Sartre, 1939/1948). What are contemporary college students angry about?

PURPOSE OF THE STUDY The purposes of this descriptive study were to (1) survey levels of trait anger and styles of anger expression in contemporary undergraduate students; (2) analyze their written narratives of anger incidents, with regard to situational precipitants, relational context, behaviors, and outcomes; and (3) contribute to Trait-State Anger Theory by identifying any differences between anger narratives of high scorers on angry temperament, high scorers on angry reaction (but not temperament), and low scorers on the entire trait anger scale. The study method was modeled after Averill (1982), Roseman et al. (1990), and Scherer (1997), who pointed out that cognitive appraisals of emotion situations and subjective feeling states are accessible only through self-report. Despite the disadvantages of self-report data, Scherer and Wallbott (1994, p. 312) argued that “Rather than not studying emotion episodes in real life at all, it is preferable to have access to real, and often intimate, emotions through verbal report on recalled emotion experiences in anonymous questionnaires (even though some of the reports might be biased).”

METHOD Participants Study participants were 305 undergraduate students at a large southeastern university (126 males, 175 females, 4 not reporting sex). Racial composition of the sample was 88% white, 7.5% black, 5% other (e.g., Asian, Hispanic, Native American). Mean age was 19.6 (range 18-24 years). There were 135 sophomores, 91 juniors, 40 freshmen, 28 seniors, and 5

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fifth-year seniors (missing data for 6 students).

Instruments Spielberger Trait Anger Scale The Trait Anger portion of the Spielberger Trait Anger Scale (STAS) includes 10 angerrelated statements, with a 4-point scale of response options, ranging from almost never (1) to almost always (4). Respondents are instructed to “rate yourself according to how you generally feel.” Sum of all responses is the trait anger score indicating an individual’s general proneness to become angry (possible range 10-40). 4 of the 10 items comprise the Angry Temperament subscale (range of scores 4-16), and another 4 items comprise the Angry Reaction subscale (range of scores 4-16). The Angry Temperament subscale measures “a general propensity to experience and express anger without specific provocation,” while the Angry Reaction subscale assesses “the disposition to express anger when criticized or treated unfairly by other individuals” (Spielberger, 1991, p. 1). As noted previously, the two-factor solution (Angry Temperament and Angry Reaction) of the Trait Anger Scale was established during initial development and validation of the tool (Spielberger et al., 1983). Subsequent factor analytic work has supported the 2-factor structure (e.g., Van der Ploeg, 1988). Concurrent, convergent, and discriminant validity of the STAS, as well as internal consistency reliability, have been well established. Cronbach’s alpha was.70 when the Trait Anger Scale was administered to the normative sample of college students (Spielberger, 1991) and.85 for a college sample tested by Thomas and R.L.Williams (1991). Test-retest reliabilities have ranged from.70 to.77 in various published reports. Demographic Data Form A simple demographic data form requested participants to report their age, year of college, gender, and preferred racial/ethnic designation. Description of Anger Incidents Students were asked to recall an experience of anger and describe it in writing on a blank sheet of paper included in the instrument packet. As in Scherer’s (1997) 37-country study, respondents freely chose the events they reported. Instructions were as follows: “Think of a time when you became angry. Describe this experience in as much detail as you can. Where were you and what happened? Include your thoughts and actions as well as any after-effects of the incident (e.g., how you felt, how your relationship with another person was affected). When speaking about other people you interacted with while angry, be sure to give them pseudonyms. Type your story or write legibly. Add other pages if necessary.”

Procedure 310 instrument packets were distributed by 31 undergraduate students in the university honors program to classmates who were at least 18 years of age and enrolled in undergraduate

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course work. Data collectors returned the completed instrument packets to the researcher at regular class meetings during the semester. Five packets were erroneously distributed to graduate students or students who were not yet 18; these were discarded before data analysis.

Protection of Human Subjects This study was approved by the university IRB. Potential participants were given full study information to permit informed consent on a cover sheet attached to the questionnaire packet. To preserve anonymity, however, no signature was required on the form. Participants were told that completion of the instruments would take about 30 minutes and conferred neither risks nor benefits. Returning questionnaires to the data collectors (in the sealed envelopes provided) signified their consent to participate.

RESULTS Analysis of Quantitative Data Comparison of Anger Scores to Previous Samples of College Students Overall, the data suggested no trend toward an increasingly angry college population. The full range of possible scores on the Trait Anger Scale (i.e., 10 to 40) was observed in this sample of 305 college students, indicating heterogeneity in anger proneness. The mean Trait Anger score was 19.087 (SD=5.61), slightly less than the mean of 20.53 (SD=5.89) obtained for a large college sample 15 years ago by Thomas and R.L.Williams (1991), but virtually identical to scores obtained in other recent studies using college samples (e.g., O’Neil & Emery, 2002). There was no gender difference in this sample (M = 19.4 for men, 19 for women), consistent with previous studies by Deffenbacher (1992) and Kopper and Epperson (1991). Gender-specific means were slightly less than those reported for the college sample tested by Spielberger (1991) (M = 20.08 for men, 20.35 for women).

Comparison of Anger Scores to Samples in Health-related Studies While the present sample scored similarly to other college samples, scores diverged considerably from those reported for the middle-aged sample participating in the prospective study of cardiovascular disease by J.E. Williams et al. (2000). Williams and her colleagues used cut-points to divide trait anger scores of the participants into 3 levels: high trait anger (scores of 22 to 40); moderate (scores of 15 to 21); and low (scores of 10 to 14). Only 7.7% of the Williams et al. sample scored at the highest level, compared to 29% of the present college sample. Thus, a much greater proportion of the college students scored at a level shown by Williams et al. to confer coronary heart disease risk. Compared to the middle-aged sample, fewer college students scored in the moderate range (49.5% vs. 55.2%) or low range (22% vs. 37.1%) on trait anger.

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Analysis of Qualitative Data A broad-brush preliminary analysis of some of the student anger stories took place during meetings of the honors class over the semester of data collection. Students were provided guidelines for thematizing the stories, and worked in small groups to do so. This phase of the analysis was focused more on student learning than on rigorous data analysis, but proved useful with regard to evaluation of the anger stories by young men and women who were in the same age cohort as the study participants and familiar with pop-culture references in the stories (e.g., names of rappers, athletes, videogames, bars). Notes of the student analysis teams were collected at the conclusion of class and saved for later review. A much more rigorous and systematic analysis of the narrative data took place the following semester, with assistance of two honors students who elected to work with the data more intensively. For the purposes of this paper, we compared the anger narratives of 3 groups of students, categorized according to the percentiles for Spielberger’s (1991) normative sample of college students: (1) subjects scoring high on Angry Temperament, i.e., scores of 10 or above, which are 91st percentile for both men and women (n=35); (2) subjects scoring high on Angry Reaction but not high on Angry Temperament, i.e., scoring 12 and above on Angry Reaction (80th percentile for females, 89th percentile for males), but not scoring at 10 or above on Angry Temperament (n=32); and (3) subjects scoring low on the entire Trait Anger Scale, i.e., less than 13, which is 6th percentile for men, 5th percentile for women (n=41). One student in the latter group did not provide an anger story, stating “Personally, I cannot recall the last time that I got angry at anyone or anything,” leaving 40 stories of the Low Anger group for analysis.

The Coding Scheme Copies of the anger stories were divided among the principal investigator and the student coders, to be coded using forms devised by the PI. As suggested by Waltz, Strickland, and Lenz (2005), existing categorical schemes developed by other anger researchers were evaluated for their applicability to the present project. Ultimately, the coding scheme of Fischer et al. (2004) was used to examine the students’ reasons for anger and the relational context of the incident (i.e., whether the provocateur was an intimate or a stranger). Additionally, coders recorded methods of expressing anger and outcomes of the anger episode on the researcher-developed coding sheet. Throughout the analysis, narratives were examined for emergent categories and themes, using standard content analysis procedures (Waltz et al., 2005). While Fischer et al.’s coding scheme was adequate for categorizing reasons for anger and relational context, the coding sheet for methods of expressing anger and outcomes required expansion to include several new categories. For example, originally 5 methods of expressing anger (derived from literature review) were listed on the coding sheet: (1) kept anger to self; (2) vented anger verbally (yelling, cursing); (3) vented anger by physical act (punching wall); (4) vented anger by hitting another person; (5) talked to the provocateur or a supportive listener about the anger. Space was provided to record “other” expression methods. Among the “other” responses mentioned by participants were withdrawing from the other person for a period of time, taking revenge, and distracting self from anger (playing music, going for a drive). Outcomes of the anger episodes were also more diverse than those listed on the original

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coding sheet. Four possibilities were originally listed: (1) worked things out successfully with the other person(s); (2) let go of the anger, even though no resolution of the issue; (3) still angry at other person; and (4) still angry at self. In addition to these options, participants mentioned alteration or termination of the relationship. Blinded to previous coding, the team members re-coded all of the stories using the expanded form. To ensure intercoder reliability, not only did each student re-code the narratives analyzed by the other student, but the PI also performed frequent random checks of the students’ work. Ambiguities and discrepancies were resolved by discussion among coders at weekly meetings. Notes from these discussions were an important component in the audit trail for the project (Rodgers & Cowles, 1993).

Brief Overview of Findings from the Content Analysis For all of the college students, relational issues were highly salient, and the number one anger provocateur was a non-romantic intimate (e.g., roommate or friend). This finding is consistent with Deffenbacher’s (1992) report that 53% of college student anger situations involved their roommates and friends. However, that study did not involve comparisons between subgroups of the sample. In the present study, important differences were evident when comparing stories of the 3 subgroups (high angry temperament, high angry reaction, and low anger) (See Table 1). Reason for Anger The number one triggering event for the high angry temperament (HT) group was a minor frustration, whereas more substantive violations (injustices, such as betrayal by a significant other) were likely to trigger the ire of the high angry reaction (HR) and low anger (LA) groups. Compared to the other two groups, a higher percentage of HT students were angered by treatment that they perceived as disrespectful. Methods of Anger Expression and Outcomes of Anger Episodes The experience of the anger incident, and the behavior enacted, varied considerably among the 3 groups of students. Both the HT and HR subjects reported that their anger arousal in the moment was intense, and the HT individuals almost always vented their anger verbally or physically (via assault or property destruction). In contrast, HR subjects were more likely to suppress their anger or withdraw from the situation. Little or no verbal or physical aggression was reported by the LA group. The predominant response of LA subjects was constructive anger verbalization, and the most frequently reported outcome was working things out successfully with the other person. LA subjects were more than twice as likely to work things out than were HT subjects and three times as likely to work things out, when compared to HR subjects. Unlike HT and HR individuals, who often remained angry at the other party, only 7.5% of LA subjects held on to their anger after the episode was over.

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Sandra P. Thomas Table 1. Comparison of Three Groups of College Students on Anger Episodes High Angry Temperament (n=33) Anger Provocateur Stranger Authority Non-romantic Intimate Romantic Intimate Other (e.g., videotape) Reason for Anger Minor Frustration Relational Issue Disrespectful Treatment/attack on status Injustice (betrayal, lied to) Other (e.g., unsafe driving) Method of Expressing Anger Vented Verbally, Negatively Suppression Expressed Constructively Took Time-out/Withdrew Vented Physically (breaking object) Vented by Assault of Person Distracted Self (music) Took Revenge on Other Outcome of Anger Episode Worked Things Out With Other Let Go, But No Resolution Still Angry at Other Still Angry at Self Relationship Altered, But Not Ended Relationship Terminated

High Angry Reaction (n=32)

Low Anger (n=40)

15% 6% 42% 18% 18%

19% 22% 31% 16% 19%

7.5% 20% 47.5% 10% 12.5%

33% 30% 24% 18% 3%

19% 28% 9% 50% 16%

15% 32.5% 15% 32.5% 5%

36% 21% 18% 3% 24% 18% 0% 12%

25% 34% 22% 12.5% 12.5% 9% 0% 0%

20% 22.5% 45% 7.5% 2.5% 0% 2.5% 0%

21% 33% 30% 3% 15% 3%

16% 22% 28% 0% 16% 16%

47.5% 25% 7.5% 0% 10% 12.5%

Note. In some instances, percentage totals exceed 100% because a behavior merited two codes (e.g., vented verbally and took revenge).

The heaviest toll on interpersonal relationships was seen in the HR group (i.e., 32% of their relationships were altered or terminated after the anger incident).

Thematic Elements of the Narratives Understanding of these findings deepens when examining thematic elements of the narratives written by the 3 groups of students (See Table 2). Patton’s (2002) approach was used when re-reading the anger stories, searching for recurring patterns or features in their descriptions of the incidents (i.e., themes). Although we used phenomenological analysis in our interview studies (e.g., Thomas et al., 1998; Thomas, 2003), the brevity of these student narratives did not permit phenomenological analysis. A few stories exceeded the one page provided in the instrument packet, but most were a page or less. Nonetheless, the stories were very enlightening. The students were quite candid, readily acknowledging thoughts and behaviors that could be judged as reprehensible, such as shoving one’s mother or driving recklessly. The anonymity afforded by the elicitation of written narratives could have

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decreased the need to give socially desirable responses about anger behaviors. In the following sections, verbatim quotations are used to illustrate each theme. The quotes were chosen to represent the voices of as many participants as possible. Participant identification numbers appear in parentheses after the excerpts from the narratives. Table 2. Thematic Elements of Narratives of Three Groups of Students

1.

2. 3. 4. 5.

High Angry Temperament (n=35) Exaggerated response to provocation: provocation often trivial. Display of physical and/or verbal aggression. Pejorative depiction of the other. Relationships adversely affected by the anger. Little remorse or lessons learned from the incident.

1.

2. 3. 4. 5.

High Angry Reaction (n=32) Exaggerated response to provocation: provocation substantive. Suppression, withdrawal, and rumination. Pejorative depiction of the other. Relationships adversely affected by the anger. Little remorse or lessons learned from the incident.

Low Trait Anger (n=40) 1. Slow to be provoked to anger.

2. Constructive anger verbalization. 3. Ability to see the other side of the issue or conflict. 4. Relationships maintained. 5. Remorse expressed/lessons learned.

Narratives of Subjects Scoring High on Angry Temperament Five themes were identified in the narratives of subjects scoring high on angry temperament: (1) exaggerated response to provocation; (2) display of physical and/or verbal aggression; (3) pejorative depiction of the other; (4) relationships adversely affected; and (5) little remorse or lessons learned from the incident. Theme 1. Exaggerated Response to Provocation, often a somewhat Trivial Provocation HT participants described their response to provocation in colorful terms: “I was boiling hot” (#85); “I was enraged, livid, furious, pissed off” (#184). Given that they were responding to a minor frustration in many cases (e.g., unable to score well on a videogame, recipe wasn’t working out, didn’t like room temperature set by roommate), the volatility of the response does not seem proportionate to the situational context. In the following account, it is unclear why the participant interpreted the other fellow’s behavior as so offensive. The anger escalates rapidly: “I was at a party and a guy complimented my shirt. He put his hand up to give me a five, and I put mine down to receive it. A few seconds passed and he began to take his hand down. I immediately slapped his hand and said ‘Fuck you!’ I was extremely angry and we had a verbal altercation full of curse words. This continued until several of his friends pulled him away. I wanted to kick his ass, but didn’t get to. I don’t take people making fun of me lightly.” (#56)

In the next vignette, the participant views a friend’s behavior as disrespectful, although an observer might come to a somewhat different conclusion: “It was a Friday night, and I had plans to spend an evening with a friend I was just getting to know. We hadn’t known each other for very long…I was in the middle of changing [clothes] to go out when she called. A friend from out of town had called her and wanted to spend time

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Sandra P. Thomas with her that evening. Without even thinking, she told her friend ‘yes’ and told me ‘I’ll talk to you later. Have a good night.’…Immediately I was infuriated that she would disrespect my time.” (# 237)

While disappointment would be a rational response to the canceled plan, and perhaps the cancellation was not handled in the most tactful manner, the participant’s resultant fury seems extreme. She reports crying, using “bitter sarcasm,” and later forcefully confronting the offender about violating the “previous plans honor code.” She accuses her friend of being thoughtless --acting “without even thinking” -- and fails to consider alternative explanations (perhaps the visitor from out of town was a valued old friend who rarely visits). In the final exemplar of this theme of exaggerated response, the participant describes an incident which rapidly escalated from yelling to pushing, although it had started “over nothing”: “I was in an argument with my father. It was over nothing important…I started yelling, then he started yelling. I tried to walk away, but that just made my dad angrier. He stopped me and I pushed him. He pushed me back. Then when I tried to walk past him, he hit me in the shoulder. I came very close to punching him in the face.” (#310)

Theme 2. Display of Physical and/or Verbal Aggression Aggressive acts described in HT narratives ranged from destroying objects (telephone, gameboy console) to road rage (running someone off the road) to engaging in verbal and physical fights (e.g., “I just lost it and raged, picked him up off the couch and threw him out of the house” [#27]). Often a combination of verbal and physical aggression occurred, as in these examples: “I cursed and blasphemed, punched a hole in the wall, threw it [a necklace] in her face” (#90); “I hung up the phone, then threw it against the wall [which] knocked a hanging picture off my wall, which landed on and broke a cologne bottle” (#300). Pride was evident in many accounts when describing aggressive acts. The following narrative is illustrative: “I asked my girlfriend to go to a party with me and she said no. I got so angry because it meant that I had to go alone. I showed up and she was talking to two other guys. They were touching her arms and hugging her and didn’t stop when I walked up. I pulled her over to the side of the house and screamed, ‘You fucking whore, why do you do this to me?” It felt good…I pushed her into the wall. She was crying a little. I think she was impressed with my newfound confidence. I smacked her and told her ‘Shut the fuck up!’ A few guys came around and broke it up. They tried to be tough with me, but she told them to stop. They did and we left together. We are happier now than ever.” (#289)

Theme 3. Pejorative Depiction of the Other Narratives of the HT group contained a strong “I’m right/they’re wrong” flavor. For example, the narrator in the above-cited story seems to believe that he is justified in his physically abusive behavior because his girlfriend was acting like a “whore.” There is no empathy evident for his girlfriend, who must have experienced humiliation when being shoved and hit at a social event. Pejorative terms were often used by other study participants to describe the anger provocateur: “She was jealous” (#85); “He wasn’t a person possessed of many social skills” (#133); “Her reasons were stupid” (#52); “She is a very fake person” (#306); “I hate that bitch” (#184).

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Theme 4. Relationships Adversely Affected by the Anger As depicted in Table 1, only 21% of the anger incidents reported by HT subjects culminated in working things out successfully. In many cases, considerable anger remains (“Up to this moment, the sight of her sickens me and incites intense fury” [#85]); “I still, to this day, have not talked in person to the girl” [#90]). One participant admitted that despite his roommate’s apology (for a minor violation of his hygiene standards) “I am still a little mad about it” (#225). Theme 5. Little Remorse or Lessons Learned from the Incident HT individuals sometimes recognized that they did not manage their anger well (e.g., “My decisions are not always good when I’m angry;” “I get very angry when I don’t get my way;” “I realized I overreacted”). However, they did not tend to express remorse regarding their behavior, nor did they speak in terms of any lessons learned. One participant broke his hand punching a wall after a passing motorist splashed him with puddled rain water, but ended his narrative by saying, “If I see that person again, I still won’t hesitate to punch him” (#177). Another participant who reported destroying a videogame in anger admitted destroying another one since the original incident (#240). Narratives of Subjects Scoring High on Angry Reaction but not Temperament Five themes were identified, exemplifying both commonalities with, and differences from, the high angry temperament subjects. Like the HT narratives, there was (1) an exaggerated response to provocation, but the provocation was quite serious in many cases (not about videogames or minor slights). Aggression was sometimes displayed in property destruction (throwing clock, trying to break door) or by using profanity, but HR subjects did not commonly talk about their angry feelings to others, or find much relief from doing so. Therefore, theme 2 was titled “suppression, withdrawal, and rumination.” The remaining themes were consistent with the HT group: (3) pejorative description of the other; (4) relationships adversely affected; and (5) little remorse or lessons learned from the incident. Theme 1. Exaggerated Response to Provocation Intense bodily arousal was described by HR participants, in vivid language comparable to that of the HT students. Participant 131’s account is richly descriptive: “The first thing I usually feel is a rush, I guess, adrenaline, that floods my skin. Sometimes, if the antagonizer is still in site and being antagonizing, well, I feel dizzy for a second, light-headed, and my jaw clenches.” Other HR participants reported typical cardiovascular symptoms: “blood rushing to my face, heart pounding madly in fury” (#163) and “my heart always races and I get really fidgety” (#254). In contrast to the minor frustrations characteristic of many HT narratives, injustice was the major trigger of the intense anger response in HR stories. The students told stories of being cheated, lied to, betrayed, and unfairly criticized. The following exemplars are illustrative: “My girlfriend told me she was breaking up with me, not only because of me, but for her engineering teacher. AND not only that, she had cheated on me with him.” (#113)

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Sandra P. Thomas “I had to do all the work for a group presentation. I did all the research, all the analyzing, all the writing. When all was said and done, I got the same grade as everyone else. I was pissed off beyond belief.” (#304) “I become quite angry on a fairly regular basis. I suffer from a disease called muscular dystrophy…I have to take the elevator because of having MD. I understand that people don’t know that I have something wrong with me, but they don’t have to yell at me. I literally get yelled at because I use up a few seconds of their time…I personally feel extremely angry because having MD is not my fault and I can’t do anything about it…I would take the stairs if I could.” (#58)

Theme 2. Suppression, Withdrawal, and Rumination Individuals in the HR group seemed to lack skill in assertive anger expression and problem-solving. Despite strong physiological arousal, they apparently took no action in many of the aforementioned situations of unjust treatment. Their anger was suppressed and/or they withdrew from the conflict. Recall the young man with muscular dystrophy. Twice in his narrative he stated that “people don’t know my situation.” Presumably, he has not spoken up to inform his classmates of his physical condition. So they continue to yell at him, and he continues to silently seethe. In the next example, the participant apparently could summon no defense when her grandfather made a hurtful comment, and she was left feeling worthless and “very small”: “One day, my family and I stopped by my grandfather’s house…We started talking about school and he asked me what I was majoring in. I told him accounting, but I wasn’t absolutely positive if that was what I wanted to do. In the most hateful way, he told me that it was absolutely pointless for me to be going to college if I didn’t know what I wanted to be. It made me feel pretty worthless and very small.” (#143) As in the HT group, a sizeable percentage of the HR group admitted that their anger at the provocateur has not abated. Their narratives depict rumination about the grievance, often for a prolonged period. Although a specific temporal referent was not included in all narratives, some HR participants emphasized that they had retained anger about the incident for 6 months or longer. For example, the student (#143) whose grandfather thought it “pointless” for her to be in college stated that she didn’t talk to him for 6 months following their interaction and holds “even more of a grudge towards him since then.” Another student (#267) reported that she did not talk to her sister for about 6 months after her sister called her a whore. For one male student, residual anger about an incident with his roommate resulted in “a very rocky relationship that persisted throughout the entire first year [of college]” (#163). Another participant said, “I feel that in some ways I will never get over this” (#254). There is little evidence in the HR narratives that comfort was sought in ventilating to supportive confidants after the interaction with the provocateur was over. The present data do not indicate whether these participants lacked supportive confidants or simply chose not to avail themselves of opportunities to talk about the incidents. Perhaps some of them shared the view of participant 131, who did not find it helpful to talk and did not want to be questioned: “When others question me about the situation, I usually have to cut them short. Talking about such incidents, especially at length and in detail, often makes me relapse into that anger state.” (#131)

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Theme 3. Pejorative Depiction of the Other As in the HT narratives, the anger provocateur is described in a pejorative way: the professor was “idiotic” (#315); the coworker was a “jerk” (#204); the roommates was “uptight, screaming for no reason” (#134); the customers were “rude, disrespectful” (#148). In the following story, the narrator perceived her mother to be “snooping” in her room, although her mother explained that she had opened a little pouch because she thought it contained jewelry. The reader cannot know if the mother really was prying, but the narrator’s aggressive response is clearly inappropriate in any case (and undoubtedly hurtful to the mother): “As I turned the corner and walked in my room, I immediately saw her standing there holding my bowl. She looked right at me and asked, ‘So this means you’re smoking pot again, doesn’t it?’ I never answered her question; instead, I grabbed the bowl from her and started irrationally asking her why she had been going through my stuff, and to get out of my room. Of course, my temper was flaring and my language was not appropriate…I was pissed because she had violated my privacy…She wouldn’t get out of my room when I told her to, then demanded her to, so I used force to get her out of my room. When I finally got her out the door, I locked it and pounded my hand against it for emphasis…I left the next day to come back to school, instead of 5 days later like I had planned on doing.” (#50) Theme 4. Relationships Adversely Affected by the Anger Within the HR group, the desirable outcome “worked things out with the other” occurred in only 16% of anger episodes, the lowest percentage of the 3 groups. Relationships were usually significantly altered or terminated. Participants reported quitting a job, changing roommates, withdrawing from significant others for long periods, and never speaking again to a person who had lied to them. Theme 5. Little Remorse or Lessons Learned from the Incident Although one student in this group acknowledged the “stupidity” of a road rage incident and two students said they turned their anger into determination to succeed in their studies or sports, the majority neither expressed remorse for anger behavior nor reported any lessons learned. To return to the story of the study participant (#50) who pushed her mother out of her bedroom, there was no remorse for possessing drug paraphernalia nor recognition that she does not have an absolute right to privacy within the home of her parents. Narratives of Subjects Scoring Low on the Entire Trait Anger Scale Five themes were identified in the narratives of subjects scoring low on trait anger: (1) slow to be provoked to anger; (2) constructive anger verbalization; (3) ability to see the other side of the issue or conflict; (4) relationships maintained; and (5) remorse expressed/lessons learned. Theme 1. Slow to be Provoked to Anger Consistent with Trait Anger Theory, students scoring low on the trait anger instrument used self-descriptors such as “not easily angered” and “very laid back.” Students in this group were the least likely of the 3 groups to become angered by minor frustrations. When they did become angry, it was because of a relational issue or injustice (e.g., accused of being on a

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porn site on uncle’s computer; best friend lied and asked someone else to lie to cover his own lie; boyfriend or girlfriend broke off relationship precipitously).

Theme 2. Constructive Anger Verbalization Although there was a fair amount of unexpressed anger within the LA group, constructive anger verbalization occurred in nearly half the narratives. As noted earlier, constructive verbalization can mean talking over an incident with a sympathetic listener or talking directly to the person who provoked it. In the first set of exemplars, anger was expressed directly to the provocateur: (Describing anger verbalization to driver whose recklessness frightened her): “B____ was being completely irresponsible, especially considering 3 of the people in his back seat were not buckled up, since we had one extra person in the car. It made me really mad that he was playing around with the lives of the friends in his car. We stopped for lunch and he asked if I was okay. I said I was not okay, I was mad because of the way he had driven. He apologized…Two days later he came up to me again and said he was really sorry. I normally do not get mad at people, but he really did scare me.” (#238) (Describing assertive action after being lied to and taken advantage of by her friend A____, which deprived her of valuable study time): “I value my time, to study any chance I get…A couple of days later [after she caught A___ in the lie], when I had some free time, I went to A’s [residence] to discuss the issue because it bothered me.” (#8) (Describing resolution of estrangement from friends for a week because of a practical joke): “Our relationship has become a lot better, and [this] brought us closer, after talking about it and telling each other how we felt. Now we are able to respect each other’s feelings and know what we should not do.” (#103) In the following excerpts from the data, anger was not expressed to the provocateur but was shared with confidants, who provided a listening ear and/or advice: “My ex-boyfriend acted completely inappropriate to me in front of a large group at a party…afterwards I talked to two friends about it” (#192). “My friends were going behind my back in a certain situation involving a guy. They knew that I was interested in him, but they were trying to set one of our other friends up with him. I did not confront them…But I did talk to my other friends about it and got advice.” (#264)

Theme 3. Ability to See the Other Side of the Issue or Conflict In contrast to the “I’m right/they’re wrong” stance often taken by high scorers on angry temperament and angry reaction, LA individuals were more likely to see the other side of the issue or conflict. For example, one student (#271) was angry at his roommate’s “rudeness” and “hatefulness,” but realized that this behavior was related to depression about the ending of a significant relationship. Therefore, he resolved to strive for greater tolerance of the roommate’s hateful behavior during this difficult period. Another student became angry about her father’s unwillingness to help with her large auto repair bill. She could take her father’s

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perspective, however. Despite her anger, she admitted, “I understand his thoughts and feelings, but that doesn’t mean I liked them…My dad just wanted to make sure I learned a lesson” (#51).

Theme 4. Relationships Maintained It was important to LA participants that relationships be preserved. As noted previously, the most frequently reported outcome of anger incidents for the LA students was “working things out successfully with the other person.” Rather than let angry feelings fester, these students took action promptly. For example, participant 71, whose anger was provoked by her best friend lying, “confronted him immediately. I let him know I was mad, but I was still controlled.” The students expressed their opinions honestly, even in trying circumstances. Participant 321’s father attempted suicide, which produced mixed emotions of anger, worry, and sadness. While she was visiting her father in the hospital after his overdose, he asked her what she thought “about everything.” She admitted to him that she thought his suicide attempt was selfish, “but I also told him how much I love him…I felt better talking about it.” Narratives frequently concluded with statements like, “our relationship was not hurt,” “everything is fine,” or “we are still friends.” Theme 5. Remorse Expressed/lessons Learned Echoing the words of participant 51 that were cited earlier (see theme 3), narratives of the LA group often included a statement about a lesson learned from the anger incident. Participants wrote about learning to compromise, discuss grievances calmly, and maintain control and dignity in handling distressing situations. An account by participant # 277 is illustrative: “One day, one of my roommates was making a lot of noise when I was trying to sleep. I had repeatedly asked her to stop, but she did not. In this situation, I was very angry…We eventually talked about it. I found out it was better to take naps at other times when she isn’t there. Thankfully, it didn’t really affect the friendship, but we did learn to talk things out.” Participant 153 was blindsided at dinner in a restaurant by her fiance’s sudden request to break their engagement. Despite her hurt and anger, she was able to respond with dignity: “I didn’t say anything mean to him, didn’t insult him, or say anything that I would regret. In the end, I feel that I am a stronger individual for the way that I handled it.” When a situation was not handled well (i.e., sharp language or profanity was used), remorse was evident. Participant 15 became angry when a customer service representative refused to replace a malfunctioning cell phone. His angry comments did not produce a satisfactory outcome, and he said, “I felt kind of bad about the way I handled the situation.” Participant 100 was angry because his parents had not called frequently since he went away to college. So he called to tell them how he felt, and displayed more anger than he had intended: “I think my words were a little too sharp…My eyes teared up as my frustration came out” Although regretting the sharpness of his words, the participant reported that he did feel better “once it was off my chest.” And before hanging up the phone, he assured his father that he loved him.

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CONCLUSION In 1983, Averill asserted that “we know surprisingly little about anger, even in a descriptive sense” (p. 1158). More than 20 years later, DiGiuseppe (2006) contends that we still know much less about anger than we do about anxiety and depression, and “as of yet, we have no clear paradigm in the treatment of dysfunctional anger” (p. xxiii). The cadre of anger researchers within psychology is small, and there are many unanswered questions. Averill (1982) pioneered examination of everyday anger, eliciting written accounts. Unfortunately, only a few psychologists have adopted this approach during the intervening years (most preferring to conduct laboratory experiments). Self-report research has been disparaged, as typified in this criticism from Berkowitz and Harmon-Jones (2004b): “Self-reports and anecdotes are…highly susceptible to distortions…the conclusions drawn from…self-report studies are generally equivocal at best” (pp. 154-155). Lazarus (1991), on the other hand, argued that “if we can’t depend to some extent on what humans tell us, we lose important information about emotions, because behavior alone is not easy to interpret” (p. 29). The present study extends Averill’s work, providing a vivid description of study participants’ thoughts, feelings, and behaviors during episodes of anger occurring in natural settings. The written accounts reveal important elements of the provocation, the response, and nuances of the situational context that are obscured in questionnaire research. Contrary to some literature during the past decade deploring the angry children of the baby boomers, there was no evidence in this study that today’s college students are angrier than those assessed in the 1920s, 1940s, or 1980s and 90s, nor were their provocations substantively different from earlier cohorts. As in the past, college students were mainly angered during interactions with significant others (roommates, friends). Congruent with Averill’s (1982) findings, anger in this college sample was a highly interpersonal emotion. Many of the triggering events were typical of those experienced by people learning to live communally in dormitories or apartments. Of great concern, however, is the subgroup of the sample scoring high on Trait Anger, who may be at risk for cardiovascular disease or other organic pathology. Recall that 29% of the sample scored at a level shown by J.E. Williams et al. (2001) to confer cardiac risk. Consistent with Trait Anger Theory, the HT and HR study participants were markedly different from students scoring low on the trait anger scale. For example, only the HT and HR groups displayed the egocentric “I’m right/they’re wrong” blaming of the provocateur that has been noted in previous research (e.g., Shaver et al., 1987). This stance was not evident in the narratives of the low anger students, who were able to take the perspective of the other and even empathize with the other. The anger of the HT and HR students was clearly maladaptive, both in its intensity and in its duration. Recall that these students often held onto their anger at the provocateur, in contrast to the small percentage (7.5%) of Low Anger participants who did so. Neither HT nor HR study participants were likely to report any lessons learned from conflictual interactions, heightening the probability that they will repeat behaviors that alienate significant others and contribute to occupational problems, as shown in previous research. The study has considerable pragmatic validity (Kvale, 1995), in that implications for appropriate interventions can be readily drawn from the narrative data. The words of the students themselves convey so much more to clinicians than mere test scores do. For example, the tendency of high HT and HR participants to label disputants “bitches” and

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“jerks” obviously calls for an intervention encouraging a more nuanced and benign view of their offenders. As is the case in all research, some limitations must be acknowledged. Narratives of the students tended to be relatively brief, rather concrete, accounts of their anger incidents, containing limited reflection on their own behavior. They told what happened but sometimes ended their stories abruptly, leaving the data coders with questions. Most narratives did not provide the richness of contextual detail that would be available in narratives obtained via interview methodology. For example, an interviewer could have explored the duration and quality of an intimate relationship prior to the angry altercation that ended it. The pre-existing relationship was important in understanding face-to-face conflict in a recent phenomenological study by Graves (2006). Despite its limitations, this study contributes to the psychology of anger. It is perhaps the first study to expand our understanding of the components of trait anger. Important differences were delineated between high scorers on angry temperament and high scorers on angry reaction, both in the provocations that trigger their anger and in their coping responses, suggesting that anger management interventions be tailored accordingly. Different interventions are required for individuals with a volatile outward anger expression style and those with a predominantly suppressive/ruminative style. As shown in the review of health psychology research literature, both volatile outward anger expression and suppression/rumination are deleterious to health. In the following sections of the chapter, I will make suggestions regarding acquisition of specific anger management skills for students with these unhealthy anger expression styles, drawing from my own clinical experience and from the literature.

Interventions for Students with Volatile Anger First, we address the volatile anger of high scorers on the Angry Temperament component of Trait Anger. Despite their innate propensity to be “hot reactors,” anger management (AM), a psychoeducational intervention, could reduce their maladaptive anger behavior, and perhaps, ultimately, their risk of cardiovascular disease. While anger reduction research is said to be in its infancy (Deffenbacher, 2006), and the efficacy of interventions for the primary prevention of CVD has not been established (J.E. Williams et al, 2001), several researchers have reported successful interventions with individuals who already have CVD (Davidson, 2000; Lavie & Milani, 1999). To cite just one example, individuals with diagnosed myocardial infarction or unstable angina pectoris participated in an 8-week cognitive-behavioral treatment program designed to modify their hostility. As hostile, cynical thoughts decreased, constructive anger verbalization increased, which in turn was associated with decreases in blood pressure (Davidson, MacGregor, Stuhr, & Gidron, 1999). Positive outcomes of anger management programs also have been reported for groups as diverse as delinquent adolescents (Feindler, 1995), New York City traffic agents (Brondolo, Hough, & Rabinowitz, 2000), combat veterans (Gerlock, 1994), and incarcerated women (Smith, Smith, and Beckner, 1994) and men (Ireland, 2004). These findings are encouraging, especially considering that AM was mandated, not voluntary, in some of these studies, such as those conducted with incarcerated women and men. Group work is customary in anger management programs because participants need to

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practice new behaviors in an interpersonal context that offers feedback and support. Most AM programs are highly structured, with a balance of didactic and experiential components. The leader of an AM group functions as a teacher and coach, not a therapist. Therefore, screening should take place before enrolling participants, so that referrals can be made for individual psychotherapy when anger is related to extensive abuse or trauma. Other exclusion criteria include paranoia, organic disorders, and severe personality disorders (Thomas, 2001). Candidates for AM should have some motivation to enlarge their behavioral repertoire. Motivation to become involved in anger management training is a significant issue, because (as shown in our data), many individuals with volatile anger do not see themselves as having a problem and do not experience much remorse after their explosive outbursts. Notes Novaco (1996), anger management might be viewed negatively as an attempt to stifle their personality or their sense of mastery and control. Given the heavy toll on relationships reported by the study participants, they may eventually become motivated to engage in AM interventions to preserve significant adult relationships (e.g., marriage, collegial associations in the workplace). Among the skills to be acquired by high angry temperament individuals, both for relationship preservation, and for personal health, are: •

• •

•

•

•

•

•

Calming. Diminishing the strong physiological arousal is the most important initial skill. Becoming less reactive to provocations can be achieved by breathing techniques, relaxation training, meditation, or imagery. Progressive relaxation (Jacobson, 1974) is effective for many people. Learning to use words, not fists. Individuals who express anger through property destruction or fighting must learn to put words to their feelings instead. Lowering the volume and rate of anger verbalization.. Speaking more softly and slowly when angry decreases not only the angry feelings but also the CV arousal (Siegman, Anderson, & Berger, 1990) Linguistic shading (i.e., toning down inflammatory language). For example, one might shade anger by saying “there is tension between us” (McNamee & Gergen, 1999) Thinking differently about power. Having been rewarded, at least at times, for verbal or physical aggression, high HT individuals must learn that controlling their anger means they will actually become more powerful, not less powerful (Novaco, 1996) Differentiating between demands and personal preferences. High HT individuals often demand attention to their needs from other people. They have a right to state their preferences, but others have no obligation to comply. Skills in negotiation and compromise are mandatory for successful communal living and working. Making a greater effort to understand the other person’s point of view or motives. Respectful listening can be quite enlightening and may foster development of empathy. Developing empathy for the intended target of an anger outburst is an inhibitor of that outburst (Knafo & Moscovitz, 2006). Acquiring skill in problem-solving. High anger individuals should avail themselves of problem-solving training. Such training shows how to take discrete steps to address anger-producing situations (e.g., identifying resources and solutions), and the training has proven to be effective with college students (Moon & Eisler, 1983)

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Interventions for Students with the Suppressive/ruminative Anger Coping Style Most AM programs have targeted the overt explosive anger typical of the coronary-prone individual. Less frequently addressed is the suppressive/ruminative anger coping style that is associated more so with the development of diseases such as hypertension and cancer, rather than cardiovascular disease. This suppressive style was observed in a substantial proportion of high scorers on Angry Reaction in the present college sample. These students engaged in avoidant coping when faced with situations of interpersonal conflict; they stopped speaking to the other party or nursed a grudged for a prolonged period (sometimes 6 months, a year, or longer). In addition to the negative consequences for physical health of this long-festering anger, suppressing anger is known to produce sadness and hopelessness (Greenberg & Safran, 1987) as well as intensification of the anger itself (Mao, Bardwell, Major, & Dimsdale, 2003). Rumination about interpersonal transgressions is receiving considerable attention in current health psychology literature because there is some evidence that it is associated with higher blood pressure and adversely affects general health (Hogan & Linden, 2004; Rusting & Nolen-Hoeksema, 1998; Thomsen et al., 2004). Persons who ruminate mentally replay the anger scenario over and over, thinking about what occurred and what they wished they had said or done during the altercation. The outcome, of course, is always the same because no action has been taken. Problems with significant others cannot be solved when they are never verbalized. Although some offenses may be viewed as unforgivable (e.g., infidelity of an intimate partner), many relationships of the students in this sample may have been terminated unnecessarily. Research shows that anger provocateurs often do not even know that they have committed an egregious offense (Baumeister, Stillwell, & Wotman, 1990). Therefore, they have no opportunity to recognize their own faults, to apologize or to make amends. In Averill’s classic 1982 study, 76% of those who were on the receiving end of someone else’s anger reported that they recognized their own faults as a result of the anger incident. Further, they perceived the relationship with the angry person to be strengthened, not weakened. Students who display a suppressive/ruminative anger coping style are not well suited for traditional anger management programs designed to down-regulate explosive anger. Instead, they need an intervention that teaches skills such as assertiveness. They need to effectively utilize the energy that anger provides to take action instead of withdrawing. Skills that anger suppressors should acquire include: •

•

•

Taking constructive action to address injustices and grievances wherever possible rather than passively stewing about them or holding grudges. Barriers to constructive action must be identified, such as high anxiety, low self-confidence, or perhaps early inculcation of notions that anger expression is sinful or selfish Learning to verbalize anger in a tactful, assertive manner at the time it is provoked (habitual suppressors may need to role-play and practice assertive anger statements in a supportive group setting) Realizing that expressing one’s anger to significant others will not have catastrophic consequences. Both men and women sometimes fear hurting the other person or relationship termination if they express angry feelings. But targets of anger often gained rather than lost respect for the angry person in Averill’s (1982) study.

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Interventions Applicable to All Students Some strategies have general applicability, regardless of one’s customary anger “titer” and preferred expression style. Most everyone could benefit from careful scrutiny of residual issues and patterns from the family of origin that are hampering effectiveness in anger regulation. Many conflictual interactions could be avoided by recognizing times of one’s own vulnerability to excessive angry emotionality, such as when one is highly stressed, hungry, tired, or sleepless. Discussions of substantive interpersonal issues should be postponed until a more opportune time. Self-assessment may also reveal a need to simply avoid or limit interactions with certain individuals who have irritating characteristics or values discrepant from one’s own. In situations when contact with these individuals cannot be avoided, and anger is rising, distraction is a possible strategy. Research shows that distraction after anger provocation can accelerate physiological recovery (Schwartz, Gerin, Christenfeld, Glynn, Davidson, & Pickering, 2000). Distraction can be accomplished by engaging in activities that are absorbing and entertaining (e.g., Zillmann, 1988) or by finding humorous elements of anger-provoking situations, a tactic which is known to decrease angry emotion (Baron, 1976). Another strategy that may be useful in a variety of situations is undoing negative emotion by deliberately generating positive emotion. In experiments by Fredrickson and colleagues, positive emotions (such as joy) down-regulated the undesirable cardiovascular aftereffects of negative emotions (Fredrickson, Mancuso, Branigan, & Tugade, 2000). Subsequently, Fredrickson suggested interventions to cultivate positive emotions in daily life to optimize health and well-being. Along these lines, a treatment (Coping Effectiveness Training) delivered to persons living with HIV/AIDS and cancer involved tallying positive events at the end of the day, describing these positive events to others, and identifying how the events were meaningful with regard to their values and goals. Outcomes included decreased stress, greater coping efficacy, positive states of mind, and personal growth (Chesney, Darbes, Hoerster, Taylor, Chambers, & Anderson, 2005). At this writing, it is not known if any existing anger management programs have included a comparable emphasis on positive events. It is logical to assume, however, that deliberately keeping track of the positive events of a day could reduce rumination about the negative interactions that occurred. This approach could be particularly useful to individuals with cynical hostility, who may fail overlook good things in their perpetual focusing on snubs and slights. There was scant mention of forgiving provocateurs in this set of college student narratives. The topic of forgiveness is receiving much current attention within health psychology, with nearly 200 studies on the topic being published in the past decade (Harris et al., 2006). Research shows that forgiveness reduces trait anger (Harris et al, 2006) and has salutary effects on health (Lawler, Younger, Piferi, Jobe, Edmondson, & Jones, 2005). Students who lack tools in changing a grievance narrative could benefit from a psychoeducational program like the one conducted at Stanford. Participants in the 6-week Stanford Forgiveness Project reported interpersonal transgressions similar to those reported by college students in the present study (being cheated, lied to, betrayed). Compared to a no-treatment control group, the treatment group reduced their negative thoughts and feelings about the grievance 2 to 3 times more effectively.

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Of specific relevance to the present study, trait anger (measured with the Spielberger tool) was significantly reduced. See Wade, Worthington, and Meyer (2005) for a recent metaanalysis of group interventions to promote forgiveness.

Interventions for Individuals who Merit the Diagnosis of an Anger Disorder Some individuals may need more intensive intervention than a psychoeducational program, especially those who experienced adverse childhood circumstances, such as harsh discipline or parental divorce, and those who cannot control their aggressive impulses. At present, there is only one anger-related disorder listed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) (American Psychiatric Association, 2000): Intermittent Explosive Disorder (IED). Once thought to be rare, Intermittent Explosive Disorder is reported to affect 16 million Americans, only 28% of whom ever receive any treatment for their anger (Kessler, 2006). To establish a diagnosis of IED, the clinician should be alert for descriptions of aggressive episodes as “spells” or “attacks,” during which there is inability to resist aggressive impulses that result in serious assault or property damage. The critical criterion is the degree of aggressiveness during the “attacks,” which is “grossly out of proportion to any precipitating psychosocial stressors” (American Psychiatric Association, 2000, p. 667). The clinician must also ascertain that the aggressive episodes are not accounted for by another mental disorder (such as antisocial personality disorder, borderline personality disorder, or psychotic states) or caused by drug abuse, head trauma, or other organic pathology. Scholars (Eckhardt & Deffenbacher, 1995) have proposed inclusion of additional anger disorders in the DSM: (1) adjustment disorder with angry mood; (2) situational anger disorder without aggression; (3) situational anger disorder with aggression; (4) general anger disorder; and (5) general anger disorder with aggression. These additional diagnoses would be useful, because anger is the primary affective disruption for some clients who undertake therapy; they are not concurrently depressed, nor do they meet the criteria for a personality disorder. For example, a clinician could apply a diagnosis of “situational anger disorder without aggression” when anger is not a chronic problem, but generated by an acutely painful situation (e.g., impending divorce, job loss). Feindler’s (2006) volume is an excellent compendium of therapies for individuals whose anger merits the diagnosis of an anger disorder. Among the therapies included in this volume are psychoanalytic, cognitive-behavioral, emotion-focused, Adlerian, Buddhist, and dialectical behavior therapy. Length of recommended treatment for an anger disorder is variable, sometimes as long as two to four years (e.g., Knafo & Markowitz, 2006)..

Evidence for Efficacy of Psychological Interventions for Maladaptive Anger Do psychological interventions for maladaptive anger work? Longitudinal studies such as the Precursors Study (Chang et al., 2002) and the North Carolina Alumni Study (Siegler et al., 2003), showing that anger/hostility in young adulthood persists over time, beg the question, “Can trait anger really be modified?” Yes, there is evidence that trait anger—although a relatively stable aspect of the personality—can be modified. For example, Deffenbacher,

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Story, Stark, Hogg, and Brandon (1987) recruited college students who scored in the upper 25% of the Trait Anger Scale (Spielberger et al., 1983) for a comparison of the efficacy of two treatments (cognitive-relaxation therapy and social skills training) versus a no-treatment control condition. Both treatments, delivered in small groups for 8 weeks, reduced Trait Anger scores. The above-cited forgiveness intervention delivered by Harris et al. (2006) produced a decrease in trait anger from 72nd percentile to 55th percentile at 4-month followup. Given research findings such as these, perhaps we should begin to view trait anger as a bias or predisposition to behave in a certain way, but susceptible to modification through learning. A characteristic way of responding is not an immutable way of responding. Four meta-analytic reviews have shown that anger treatments are superior to no-treatment control conditions, and that treatment recipients show moderate to strong improvement (Tafrate & Kassinove, 2006). To date, cognitive and cognitive-behavioral therapies have the most extensive empirical evidence of efficacy (Deffenbacher, 2006), but interventions based on other theoretical models have not been sufficiently investigated. In a recent critique of the state of the science with regard to psychological interventions for anger, Deffenbacher (2006) pointed out that there is little research comparing individual and group interventions. He also urged assessment of the need for relapse prevention strategies (i.e., do clients need booster sessions to maintain their healthier anger behaviors?) Based on the present study findings, I recommend evaluation of the effectiveness of delivering anger management interventions differently to the volatile high scorers on Angry Temperament and those with the suppressive/ruminative style more characteristic of high scorers on Angry Reaction.

A Final Thought about Emotional Development in Young Adulthood Might not some of college students’ youthful volatility naturally decline over time, even without treatment? It does appear that some of the intense anger of youth naturally begins to decline as individuals move from late adolescence into adulthood. Spielberger (1999) has reported that the frequency with which anger is experienced and expressed decreases, and the control of anger increases, as people grow older. Caspi, Roberts, and Shiner (2005) assert that most people become more agreeable and emotionally stable over the life course. Further, they assert that the majority of personality change occurs in young adulthood. A recent study by Galambos, Barker, and Krahn (2006) offers some support for these assertions. Galambos et al. followed 920 students from the senior year of high school until age 25, reassessing selfesteem, depression, and anger. Their anger measure focused on overtly expressed anger (losing temper, yelling, and fighting). On average, anger and depression decreased across the 5 waves of data collection, while self-esteem increased. (Individual trajectories varied, depending on variables such as unemployment, family conflict, and marital status). In sum, at 25, the young adults exhibited greater psychological well-being. Psychology now recognizes that emotional development continues throughout life (Malatesta & Izard, 1984). People learn about themselves (and about themselves in relation to others) in each new situational context. Changes in partners, jobs, and geographic residence, revisions in values or spiritual orientations, and life crises involving illness and loss, all help to bring about personal growth and transformation. Thus, there is reason for optimism that the dysfunctional anger observed in a subsample of these American college students will diminish, so that their lives may be happier and healthier.

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REFERENCES Allport, G. (1937). Personality: A psychological interpretation. New York: Holt. American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders, 4th edition, text revision (DSM-IV-TR). Washington, DC: American Psychiatric Association. Anastasi, A., Cohen, N., & Spatz, D. (1948). A study of fear and anger in college students through the controlled diary method. The Journal of Genetic Psychology, 73, 243-249. Anderson, R.N., & Smith, B.L. (2005). Deaths: Leading causes for 2002. National vital statistics reports (Vol. 53, no. 17). Hyattsville, MD: National Center for Health Statistics. Arnow, B., Kenardy, J., & Agras, W.C. (1995). The Emotional Eating Scale: The development of a measure to assess coping with negative affect by eating. International Journal of Eating Disorders, 18, 79-90. Averill, J.R. (1982). Anger and aggression: An essay on emotion. New York: SpringerVerlag/ Averill, J.R. (1983). Studies on anger and aggression: Implications for theories of emotion. American Psychologist, 38, 1145-1160. Averill, J.R. (1984). The acquisition of emotions during adulthood. In C. Malatesta and C. Izard (Eds.), Emotion in adult development (pp. 23-43). Beverly Hills: Sage. Baron, R.A. (1976). The reduction of human aggression: A field study of the influence of incompatible reactions. Journal of Applied Social Psychology, 6, 260-274. Baumeister,R.F., Stillwell, A., & Wotman, S.R. (1990). Victim and perpetrator accounts of interpersonal conflict: Autobiographical narratives about anger. Journal of Personality and Social Psychology, 59, 994-1005. Berkowitz, L. (1990). On the formation and regulation of anger and aggression: A cognitiveneoassociationistic analysis. American Psychologist, 45, 494-503. Berkowitz, L., & Harmon-Jones, E. (2004a). Toward an understanding of the determinants of anger. Emotion, 4, 107-130. Berkowitz, L., & Harmon-Jones, E. (2004b). More thoughts about anger determinants. Emotion, 4, 151-155. Bernardez-Bonesatti, T. (1978). Women and anger: Conflicts with aggression in contemporary women. Journal of the American Medical Women’s Association, 33, 215219. Brody, L.R., & Hall, J.A. (1993). Gender and emotion. In M. Lewis & J.M. Haviland (Eds.), Handbook of emotions (pp. 447-460). New York: Guilford. Brondolo, E., Hough, P., & Rabinowitz, D. (2000, April). Conflict resolution for traffic agents. Paper presented at the Society of Behavioral Medicine, Nashville, TN. Brondolo, E., Rieppi, R., Erickson, S., Sloan, R., & Bagiella, E. (2002, April). Hostility and ambulatory diary measures of mood and interpersonal interactions. Poster presented at the meeting of the Society of Behavioral Medicine, Washington, DC. Bunde, J., & Suls, J. (2006). A quantitative analysis of the relationship between the CookMedley Hostility Scale and traditional coronary artery disease risk factors. Health Psychology, 25, 493-500. Bushman, B.J., & Anderson, C.A. (2001). Media violence and the American public. American Psychologist, 56, 477-479.

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Thomas, S.P., & Pollio, H.R. (2002). Listening to Patients. New York: Springer. Thomas, S.P., Smucker, C., & Droppleman, P. (1998). “It hurts most around the heart:” A phenomenological exploration of women’s anger. Journal of Advanced Nursing, 28, 311322. Thomas, S.P., & R.L. Williams (1991). Perceived stress, trait anger, modes of anger expression, and health status of college men and women. Nursing Research, 40, 303-307. Thomsen, D.K., Mehlsen, M.Y., Olesen, F., Hokland, M,. Viidik, A., Avlund, K., & Zachariae, R. (2004). Is there an association between rumination and self- reported health? Journal of Behavioral Medicine, 27, 215-231. Tice, D.M., & Baumeister, R.F. (1993). Controlling anger: Self-induced emotion change. In D.M. Wegnder & J.W. Pennebaker (Eds.), Handbook of mental control (pp. 393-409). Englewood Cliffs, NJ: Prentice Hall. Tomkins, S.S. (1963). Affect, imagery, and consciousness. New York: Springer. Tomkins, S.S. (1980). Affect as amplification: Some modifications in theory. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience Vol. 1, Theories of emotion (pp. 141-164). New York: Academic Press. Tomkins, S.S. (1991). Affect, imagery, and consciousness, Vol.3 The negative affects, Anger and fear. New York: Springer. Van der Ploeg, H.M. (1988). The factor structure of the State-Trait Anger Scale. Psychological Reports, 63, 978. Wade, N.G., Worthington, E.L., Jr., & Meyer, J.E. (2005). But do they work? A metaanalysis of group interventions to promote forgiveness. In E.L. Worthington (Ed.), Handbook of forgiveness (pp. 423-440). New York: Routledge. Waltz, C., Strickland, O., & Lenz, E. (2003). Measurement in nursing and health research. New York: Springer. Williams, J.E., Nieto, F.J., Sanford, C.P., & Tyroler, H.A. (2001). Effects of an Angry temperament on coronary heart disease risk: The Atherosclerosis Risk in Communities Study. American Journal of Epidemiology, 154, 230-235. Williams, J.E., Paton, C.C., Siegler, I.C., Eigenbrodt, M.L., Nieto, F.J., & Tyroler, H.A. (2000). Anger proneness predicts coronary heart disease risk: Prospective analysis from the Atherosclerosis Risk in Communities (ARIC) Study. Circulation, 101, 2034-2039. Williams, R.B., Jr. (1994). Basic biological mechanisms. In A.W. Siegman & T.W. Smith (Eds.), Anger, hostility, and the heart (pp. 117-125). Hillsdale, NJ: Erlbaum. Wilson, R.S., Bienias, J.L., Mendes de Leon, C.F., Evans, D.A., & Bennett, D.A. (2003). Negative affect and mortality in older persons. American Journal of Epidemiology, 158, 827-835. Woodall, K.L., & Matthews, K.A. (1989). Familial environment associated with Type A Behaviors and psychophysiological responses to stress in children. Health Psychology, 8, 403-426. Zawadzki, B., Strelau, J., Oniszcenko, W., Riemann, R., & Angleitner, A. (2001). Genetic and environmental influences on temperament. European Psychologist, 6, 272-286. Zillmann, D. (1988). Mood management: Using entertainment to full advantage. In L. Donohew, H.E. Sypher, & E.T. Higgins (Eds.), Communication, Social cognition, and affect (pp. 147-171). Hillsdale, NJ: Erlbaum.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 2

SOCIAL ANXIETY IN THE COLLEGE STUDENT POPULATION: THE ROLE OF ANXIETY SENSITIVITY Angela Sailer and Holly Hazlett-Stevens* University of Nevada, Reno Nevada, USA

ABSTRACT Most college students experience some degree of social anxiety on occasion. However, many suffer chronic anxiety across social situations coupled with a strong fear of negative evaluation. In addition to impaired occupational and social functioning, severe social anxiety or social phobia can carry profound consequences for college students. Social anxiety is a prominent motivation for college student drinking (Burke and Stephens, 1999). In addition to social isolation, social anxiety is associated with depressogenic cognitions, both of which leave socially anxious students at an increased risk for depression (Johnson et al., 1992). Anxiety sensitivity – fear of anxiety-related sensations due to perceived consequences of physical, mental, or social harm – might play an important role in the development of social anxiety (Hazen et al., 1995). Unlike panic disorder, in which individuals typically fear anxiety symptoms out of fear of physical harm or loss of mental control, socially anxious individuals fear perceived social consequences of others noticing their anxiety. Socially anxious college students also judge others who appear anxious more negatively than do college students without social anxiety (Purdon et al., 2001). Although panic disorder treatments target anxiety sensitivity directly with interoceptive exposure strategies, this approach is just beginning to receive attention for the treatment of social anxiety. After a brief review of the literature describing the nature of social anxiety among college students, this chapter will examine the specific role of anxiety sensitivity in its development and maintenance. Finally, results from a preliminary investigation comparing the effects of interoceptive exposure delivered in a social context to social context exposure without the interoceptive component will be presented and discussed. *

Correspondence concerning this article should be addressed to Holly Hazlett-Stevens, University of Nevada, Department of Psychology/298 Reno, NV 89557, or the author can be reached via email at: [email protected]

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INTRODUCTION Many college students find interpersonal relationships stressful (Santiago-Rivera, Gard, and Bernstein, 1999) and anywhere from twenty to fifty percent of college students report shyness (Durand and Barlow, 2006). A smaller percentage of students suffer from a more serious clinical condition known as social phobia. Lifetime prevalence estimates for this anxiety disorder are as high as 13.3% in the general population (Kessler et al., 1994). Diagnostic criteria for social phobia, generalized type (also known as social anxiety disorder) include a “marked and persistent fear” of social situations in which the individual fears acting in a way that will be humiliating or embarrassing (DSM-IV-TR; American Psychiatric Association, 2000). Exposure to feared social situations almost always provokes an anxiety response. These situations are either endured with intense discomfort or avoided altogether, resulting in significant functional impairment and/or distress. Social anxiety is maintained by unreasonably high standards for social performance coupled with views that others perceive oneself as inadequate and that such perceptions are valid (Clark and Wells, 1995; Rapee and Heimberg, 1997). Individuals with social phobia also tend to rely heavily upon internal cues as an indication of whether or not a social situation is going well (Clark and Wells, 1995). Thus, individuals assume that if they feel anxious in a social interaction, this is indicative of poor performance. When compared to control samples, individuals with social anxiety disorder experience higher negative affect and judge their quality of life lower (Davidson, Hughes, George, and Blazer, 1994; Safren, Heimberg, Brown, and Holle, 1997). Ineffective coping strategies such as drinking and social isolation may be especially problematic in the college setting. We begin this chapter with a literature review examining the nature and impact of social anxiety among college students. We then turn to an important construct in the anxiety disorders literature, anxiety sensitivity, which may play an important role in the development and maintenance of social phobia. An original research investigation comparing two different exposure approaches for socially anxious college students will be described, and suggestions for treatment and future research will be discussed.

LITERATURE REVIEW Social Anxiety among College Students Purdon, Antony, Monteiro, and Swinson (1999) investigated the nature of social anxiety in the college student population. In addition to the frequency of social anxiety symptoms experienced, they examined how the perception of anxiety in others influences immediate impressions of personal characteristics such as attractiveness and intelligence. A total of 81 undergraduate college students completed self-report measures of social anxiety and social desirability and rated how much their impressions of others are influenced when the other person appears anxious. Of the 81 college students surveyed, 15 reported elevated levels of social anxiety on clinical social phobia scales. Thirteen percent of the student participants experienced all 24 social anxiety symptoms listed on the Social Anxiety Symptoms Scale at least “rarely.” In addition, a substantial majority of students experienced many of these

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anxiety symptoms in social situations at least once. Stomach “butterflies,” general tension, desire to avoid the situation, trouble expressing oneself, and blushing were the most frequently reported social anxiety symptoms. When asked about specific personal characteristics of those appearing anxious, most students indicated that if they noticed someone was anxious, their perception of the other’s attractiveness, intelligence, compassion, ambition, reliability, and mental health would not be influenced. Over half the student participants did, however, indicate that their perception of an individual’s leadership abilities and strength of character would be negatively influenced if the person in question was visibly anxious. Interestingly, the students reporting elevated social anxiety themselves were more likely to perceive others who show signs of anxiety as having less strength of character and as less attractive. Students with high levels of social anxiety also indicated that other individuals appearing anxious would be more compassionate than individuals who did not appear anxious. Overall, results from this investigation suggested that most college students experience social anxiety symptoms now and then and that negative attitudes towards those with social anxiety are prevalent, even among socially anxious individuals (Purdon et al., 1999). These authors also noted that individuals who are highly socially anxious may underestimate how often others become anxious as well as how visible the signs of anxiety are in others. Another self-report study of social anxiety in college students was conducted by LesureLester (2001). Questionnaire measures of social anxiety, dating competence, and social assertion were collected from 217 college students from different ethnic groups (African American, Asian American, European American, Mexican American, and multiracial). Relationships between dating competence, social assertion, and social anxiety as well as ethnic differences in these constructs were examined. Measures included the Dating and Assertion Questionnaire (DAQ; Levenson and Gottman, 1978), the Social Anxiety Thoughts Questionnaire (SAT; Hartman, 1984), and the Social Avoidance and Distress Scale (SAD; Watson and Friend, 1969). College students reporting greater competence at dating also reported a tendency to be more assertive in social situations and less socially anxious. No differences in reported dating competence and dating assertion were found among the various ethnic groups. Although these results suggested that low levels of social anxiety were associated with improved social assertiveness and competence, the relationship between social anxiety and actual social performance was not addressed with behavioral measures. Nevertheless, these results are consistent with previous research finding a negative relationship between self-reported social anxiety and self-reported assertiveness among college students (Chambless, Hunter, and Jackson, 1982). It is important to note that Chambless et al. also found that this observed relationship was weaker in their college student sample than their clinical social phobic sample. Kashdan and Roberts (2004) investigated the impact of self-focused attention on affective, cognitive, and motivational disturbances during a reciprocal self-disclosure task. College students reporting either high or low levels of social anxiety were included to determine if high levels of self-focused attention and social threat would have more detrimental effects for students with high levels of social anxiety than for students reporting low levels of social anxiety. Ninety-one college students completed social anxiety measures prior to their participation in a reciprocal self-disclosure social interaction task. Participants were required to answer personal questions with a video camera pointed at them as well as to ask such questions while the camera pointed at a confederate. Results indicated that students

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reporting high levels of social anxiety experienced more negative and less positive affect than students with low social anxiety during both phases of the task. These group differences were greater when the camera was pointed at the participant. These findings suggested that the level of social threat as well as the degree of self-focused attention may contribute to the cognitive and affective difficulties reported by so many socially anxious individuals (Kashdan and Roberts, 2004). The nature of “irrational” anxiety-provoking thoughts about social situations was examined with a small sample of socially anxious (n = 8) and nonanxious control (n = 15) undergraduate college students (Davison and Zighelboim, 1987). Socially anxious students articulated more irrational thoughts during a simulated social situation task than during a neutral task, and these students articulated more irrational thoughts than control participants during the experiment. Social anxiety among college students may also be associated with more general cognitive distortions. Johnson, Johnson, and Petzel (1992) collected self-report measures of social anxiety as well as the Cognitive Distortion Questionnaire (CDQ; Krantz and Hammen, 1979) from 114 undergraduate psychology students. Results indicated that students reporting high levels of social anxiety endorsed more distressed-distorted responses than less socially anxious students even after depression and trait anxiety measures were used as covariates. Thus, cognitive disturbances for socially anxious college students may not be limited to the domain of social performance and interpersonal relationships. Depressed thinking about other areas of one’s life, such as achievement, also appears to be elevated for these students. Not surprisingly, Johnson et al. concluded that social anxiety among young college students may be an important risk factor for the later development of clinical depression. Results from these studies suggest that while most college students experience some symptoms of social anxiety from time to time, socially anxious college students exhibit negative beliefs about social situations and their social performance to a greater degree than their less socially anxious peers. Although it is unclear to what degree these beliefs reflect actual social performance deficits, socially anxious students may also hold more general negative beliefs about themselves and others. These students may be vulnerable to depression, not only because of the social isolation resulting from avoidance of social situations but also due to elevated general cognitive distortions associated with the development of depression. One additional consequence of social anxiety may be particularly problematic for the college student population. In their review of the literature on social anxiety and drinking among college students, Burke and Stephens (1999) found that social anxiety is indeed a prominent motivation for college student heavy drinking. This relationship appears to be moderated by cognitive variables such as alcohol expectancies and social situation selfefficacy. As a result, these authors outlined a social cognitive model of college student drinking in which expectations about the effects of alcohol and beliefs in one’s ability to avoid heavy drinking in the face of anxiety-provoking social situations are central. This model also suggests that social anxiety treatments may be crucial to the prevention and reduction of excessive drinking on college campuses. In this next section, we discuss an important construct in anxiety disorders research known as anxiety sensitivity. A widely used self-report measure of this construct, the Anxiety Sensitivity Index (ASI; Reiss, Peterson, Gursky, and McNally, 1986), will be described. Anxiety sensitivity has received the most attention in panic disorder research. However, anxiety sensitivity may play a pivotal role in other anxiety disorders as well, including social

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anxiety disorder. We therefore review empirical investigations of anxiety sensitivity and social anxiety among college students before presenting our own empirical investigation.

Anxiety Sensitivity Anxiety sensitivity – fear of anxiety-related sensations due to perceived consequences of physical, mental, or social harm – is considered an imperative factor in the maintenance and development of anxiety disorders (Reiss and McNally, 1985). This construct is much more specific than the previously proposed anxiety-related construct of trait anxiety. There is much variability in how prone people are to experience anxiety. Some individuals experience anxiety when minimally provoked, and others require much more stressful circumstances. Individual differences in how prone one is to experience anxiety is considered trait anxiety (Taylor, 1999). The tendency to see the world as dangerous or threatening or the tendency to become anxious across situations sums up the broad definition of trait anxiety (Beck and Emery, 1985). A more sophisticated conceptualization was offered in a hierarchical model of trait anxiety (Lilienfeld, Turner, and Jacob, 1993). In this model, anxiety consists of one higher-order factor, the general concept of trait anxiety, and three lower-order factors: anxiety sensitivity, fear of negative evaluation, and fear of illness or injury sensitivity. This model later received empirical support (Taylor, 1995). Anxiety sensitivity is conceptually different from trait anxiety in that anxiety sensitivity represents the tendency to fear or respond anxiously to arousal symptoms whereas trait anxiety refers to the tendency to have an anxious response to any stressor or stressors in general (Holloway and McNally, 1987). In sum, the development and severity of a variety of anxiety conditions is determined by three fundamental fears: negative evaluation, fear of injury or death, and anxiety sensitivity (Reiss and McNally, 1985; Reiss, 1991). According to the sensitivity theory of motivation, anxiety sensitivity is a genetically based aversion to anxiety that is combined with beliefs about the negative consequences of anxiety (Reiss and Havercamp, 1996). Similar to how individuals vary in their proneness to experience anxiety, there is also variability in their fear of experiencing these symptoms. The construct of anxiety sensitivity represents the individual differences associated with the fear of anxiety (Reiss and McNally, 1985). Anxiety sensitivity is considered a predisposition that is a stable and trait-like characteristic (Taylor, 1999). Anxiety sensitivity refers to a fear of anxiety-related symptoms resulting from distressing thoughts or beliefs about the possible negative consequences of experiencing anxious sensations (Scott, Heimberg, and MacAndrew, 2000). For example, an individual with high anxiety sensitivity may view heart palpitations as an indication that he or she is having a heart attack, while an individual with low anxiety sensitivity would consider such an experience to be just uncomfortable or unpleasant (Taylor, 1999). In addition to fearing anxiety-related sensations because of feared imminent physical or mental complications, other individuals may fear these sensations out of social evaluative concerns.

Anxiety Sensitivity Index The Anxiety Sensitivity Index (ASI; Reiss, Peterson, Gursky, and McNally, 1986; Peterson and Reiss, 1992) was developed to measure and test the theory of anxiety sensitivity.

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The ASI consists of 16-items asking about the degree to which an individual finds anxiety sensations fearful or catastrophic in outcome (Peterson and Reiss, 1992). Individuals respond to each question on a five-point Likert scale ranging from 0 (“very little”) to 4 (“very much”). A recent psychometric analysis of the ASI was conducted by Zinbarg, Barlow, and Brown (1997). They found that the ASI is made up of a hierarchy of subscales. The lowest first-order factors assess three areas: physical concerns, mental incapacitation concerns, and social concerns. Most of the items on the ASI address the fear of physical harm resulting from anxious sensations, as reflected in the first factor. Examples of items targeting an individual’s beliefs about mental incapacitation include “When I cannot keep my mind on a task, I worry that I might be going crazy” and “When I am nervous, I worry that I am mentally ill.” Finally, items measuring the feared social consequences of anxiety sensations include “Other people notice when I feel shaky” and “It is important to me not to appear nervous.” Taylor (1995) expressed concern that this third lower-order social concerns ASI factor may be conceptualized more appropriately as negative evaluation sensitivity than anxiety sensitivity. However, Zinbarg, Mohlman, and Hong (1999) argued that the social concern items of the ASI are conceptually different from negative evaluation sensitivity. These authors proposed that the construct of anxiety sensitivity taps into negative evaluation concerns resulting from publicly displaying observable symptoms of anxiety whereas negative evaluation sensitivity refers to fears of negative evaluation resulting from a wide variety of other behaviors. The question of where the social concerns component of the ASI belongs was investigated by McWilliams, Stewart, and MacPherson (2000). An exploratory factor-analytic approach was used to determine if this third ASI component would be better conceptualized in the domain of negative evaluation sensitivity or in the domain of anxiety sensitivity. Factors were obtained that represented the construct of negative evaluation sensitivity as well as the three lower-order constructs that make up the ASI (i.e., physical, psychological, and social concerns). Subscales derived from these four factors were positively correlated with one another within the ASI and the Brief Fear of Negative Evaluation scale (BFNE; Leary, 1983). Contrary to the speculation that ASI social concerns belong to a higher-order anxiety sensitivity factor that is separate from a higher-order negative evaluation sensitivity factor, anxiety sensitivity and negative evaluation sensitivity were positively and significantly correlated with a single higher-order factor labeled Threat Sensitivity. Thus, the social concerns component of the ASI does appear distinct from the other two components of anxiety sensitivity (i.e., physical and psychological) as well as from negative evaluation sensitivity. However, results from correlation and higher-order principal components analyses suggested that the ASI social concerns factor represents a blend of anxiety sensitivity and negative evaluation sensitivity in addition to something unique and separate from global negative evaluation sensitivity and anxiety sensitivity constructs (McWilliams et al., 2000). The ASI has been used to study a range of anxiety disorders, including the development of panic attacks and anxiety. Anxiety sensitivity as measured by the ASI is elevated in individuals with anxiety disorders when compared to normal control groups (Reiss et al., 1986; Taylor, Koch, and Crockett, 1991). Furthermore, ASI scores are often elevated among individuals with panic disorder compared to individuals with other anxiety disorders (Taylor, Koch, and McNally, 1992). For this reason, anxiety sensitivity has received the most attention in panic disorder research.

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Anxiety Sensitivity and Panic Disorder Anxiety sensitivity appears to predispose individuals to panic disorder. Lilienfeld (1997) found that anxiety sensitivity predicts a history of panic attacks above and beyond indicators of more general trait anxiety or negative affect. Anxiety sensitivity measures differentiated individuals who experience panic attacks but do not have panic disorder from those who have never had a panic attack (Norton, Cox, and Malan, 1992). Individuals high in anxiety sensitivity are considered to be at greater risk to experience panic attacks and develop panic disorder than individuals with low levels of anxiety sensitivity. Anxiety sensitivity may develop from direct experience with aversive events such as serious illness or injury. Alternatively, exposure to the serious illness or death of a family member or the influence of an overprotective parent may also contribute to an individual’s vulnerability to anxiety sensitivity (Craske, 1999). Anxiety sensitivity is associated with a heightened level of attention paid to internal physical cues. Individuals who experience panic appear to have an elevated awareness or an increased ability to identify and detect bodily sensations associated with arousal. This increased ability to detect physical cues may predispose an individual for the development of panic disorder (Craske, 1999). Initial panic attacks occur in a variety of settings. These locations are often outside of the home (Craske, Miller, Rotunda, and Barlow, 1990), such as while at work or school, while driving, on a plane or bus, in public in general, or in a situation that is socially evaluative (Craske, 1999). Craske and Rowe (1997) proposed that initial panic attacks are most likely to occur in situations where feared physical sensations are perceived as especially threatening because of possible impairment. Examples include driving, fear of being trapped, fear of negative evaluation, or fear of being in an unfamiliar location. Certain situations or contexts are more likely to be linked with negative personal consequences of experiencing anxiety (Craske, 1999). An intense fear of specific bodily sensations related to panic attacks often develops after an individual experiences the initial panic attack. Following a panic attack, this “fear of fear” is considered a sensitization of the individual’s predisposing trait of anxiety sensitivity. Reiss (1991) described a vicious cycle in which anxiety sensitivity increases the risk of panic attacks and panic attacks increase the levels of anxiety sensitivity. There is considerable evidence demonstrating that panic disordered individuals hold powerful beliefs and fears of mental or physical harm occurring from bodily sensations associated with panic attacks (Craske, 1999). One study looked specifically at anxiety sensitivity as a predictor of panic attacks. Struzik, Vermani, Duffin, and Katzman (2004) reasoned that if anxiety sensitivity is an intrinsic and independent factor in panic development as opposed to a learned fear of earlier panic (Goldstein and Chambless, 1978), then anxiety sensitivity should be a predictor of panic that is both provoked and unprovoked. Struzik et al. tested the predictive value of the ASI when panic was induced in the laboratory. Participants with panic disorder as well as healthy nonanxious volunteers were included. Only two items on the ASI (“It is important to me not to appear nervous” and “It is important to me to stay in control of my emotions”) correlated with panic attacks experienced by the group with panic disorder. Total ASI scores as well as subscale scores and individual ASI item scores were not effective in predicting the elicitation of panic in either population. Thus, the hypothesis that anxiety sensitivity plays a causal role in the elicitation of panic attacks was not supported by Struzik et al. Nevertheless,

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anxiety sensitivity appears to predict a number of process variables involved in both physiological and psychological panic symptoms (Brown, Smits, Powers, and Telch, 2003; Perna, Romano, Caldirola, Cucchi, and Bellodi, 2003; Shipherd, Beck, and Ohtake, 2001; Rassovsky, Kushner, Schwarze, and Wangensteen, 2000). Holloway and McNally (1987) examined the effects of anxiety sensitivity on the response to hyperventilation. They predicted that anxiety sensitivity would increase responses to the biological challenge of hyperventilation. Individuals with low and high anxiety sensitivity were selected for participation. Results indicated that participants with high anxiety sensitivity reported more frequent and intense hyperventilation and anxiety sensations in response to the hyperventilation challenge than those with low anxiety sensitivity. Interestingly, individuals with high anxiety sensitivity also reported a greater number of other sensations not related to the physiological effects of hyperventilation. These results suggested that anxiety sensitivity may intensify the anxious responses of individuals who experience panic during biological challenge tests (Holloway and McNally, 1987).

Anxiety Sensitivity and Other Anxiety Disorders The role of anxiety sensitivity has been in examined in other anxiety disorders, particularly social anxiety. However, anxiety sensitivity appears to play a different role in the maintenance of social anxiety disorder than it does in panic. Different anxiety disorders are associated with different patterns of responding on the ASI. For example, Hazen, Walker, and Stein (1995) compared ASI scores of individuals with social phobia to those of individuals with panic disorder. Results suggested a different manner of responding between the two groups, with the social phobia group having significantly higher scores than the panic disorder group on three items (“Other people notice when I am shaky”, “It is important to me not to appear nervous”, and “It embarrasses me when my stomach growls”), all of which reflect concern for social consequences. Along similar lines, Taylor et al. (1992) examined how anxiety sensitivity varies across anxiety disorders. A total of 313 patients recruited from a medical school and hospital completed the ASI. All participants received an anxiety disorder diagnosis according to DSM-III-R criteria (American Psychiatric Association, 1987). Diagnostic groups consisted of panic disorder (PD), post-traumatic stress disorder (PTSD), generalized anxiety disorder (GAD), obsessive compulsive disorder (OCD), social phobia, and simple phobia. As expected, ASI scores were elevated for all anxiety disorder groups when compared to normal controls with the exception of simple phobia. Taylor et al. noted that simple phobia participants may not have shown elevated levels of anxiety sensitivity because their panic was situationally bound and thus more predictable. ASI scores were significantly higher for individuals with PD than those of all other anxiety disorders with the exception of PTSD. There was a nonsignificant trend in which the PD group had higher scores than the PTSD group. The PD group also scored significantly higher than the PTSD group on 7 out of 16 items assessing fears of fainting, heart palpitations, unusual body sensations, and the subjective experience of anxiety. There were no differences between the groups on items targeting fears of difficulty concentrating or trembling. Taylor et al. (1992) conducted further analyses by grouping together the remaining anxiety disorders for comparison with panic disorder patients. The PD group had higher ASI

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item scores than the other anxiety disorder patients except for two items, suggesting that PD is characterized by greater anxiety sensitivity than the other anxiety disorders. However, this difference may simply reflect the amount of distress associated with each anxiety disorder (Taylor et al., 1992). The direction of the relationship between anxiety sensitivity and anxiety disorder symptoms is not entirely clear. Anxiety sensitivity is viewed by some as a risk factor for panic disorder as well as other anxiety disorders. This causal interpretation of the data was articulated by Reiss and McNally (1985; Reiss, 1991). In contrast, earlier views of a related construct known as “fear of fear” proposed that a fear of anxious bodily sensations resulted from panic attacks through the process of interoceptive conditioning (Goldstein and Chambless, 1978). Indeed, Donnell and McNally (1990) found that individuals with high anxiety sensitivity were more likely to report both a personal and a family history of panic when compared to individuals with low anxiety sensitivity. However, they also found that two thirds of the individuals with high anxiety sensitivity had never experienced a panic attack. Thus, anxiety sensitivity is not only a consequence of panic but also precedes the onset of panic attacks in a number of cases (Donnell and McNally, 1990).

Anxiety Sensitivity and Social Anxiety in College Students Given that anxiety sensitivity was elevated in individuals with social anxiety (Taylor et al., 1992), researchers have begun to examine anxiety sensitivity and social anxiety in the college student population. Gore, Carter, and Parker (2002) collected self-report measures including the Social Interaction Anxiety Scale and the Social Phobia Scale (SIAS and SPS; Mattick and Clarke, 1998), Anxiety Sensitivity Index-Physical Scale (ASI; Peterson and Reiss, 1992), and the State-Trait Anxiety Inventory (STAI-T; Speilberger, Gorsuch, and Lushene, 1970) from 37 university students enrolled in psychology courses. All participants were also presented with a laboratory social challenge task instructing them to ask an “aloof” confederate on a date. Gore et al. (2002) found that while trait anxiety significantly predicted anxiety responses to the social challenge task, social anxiety measures were better predictors than either the ASI-physical subscale or the STAI-T. Thus, the SIAS and SPS combined accounted for more variance than either the STAI-T or the ASI-physical scale when predicting all social challenge task-related state measures. In addition, the higher the individual’s social anxiety measure scores, the greater the state social anxiety as well as physical symptoms reported after interacting in the social challenge. In regards to anxiety sensitivity, individuals with higher ASI-physical scores did report greater fear during the social challenge. A surprising finding noted by Gore et al. was that the ASI-physical scale was nearly as good at predicting anxiety response as the SIAS and SPS combined. The ASIphysical scale significantly predicted all dependent measures, including the Beck Anxiety Inventory (BAI; Beck, Brown, Epstein, and Steer, 1988), the Fear of Physical Sensations Questionnaire (FPSQ) which is a modified version of the Agoraphobic Cognitions Questionnaire (ACQ; Chambless, Caputo, Bright, and Gallagher, 1984), and Social State (SocS) which is a state measure adapted from a version of the Fear of Negative Evaluation scale (Watson and Friend, 1969). Roth, Coles, and Heimberg (2002) investigated the relationship between memories for childhood teasing and anxiety and depression in college students. These researchers examined

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the impact of childhood teasing on later social anxiety exhibited during the college years, whereas most of the previous research on “bullying” examined immediate effects on depressive symptoms and social anxiety among children. This line of research has found that children experiencing higher levels of victimization by their peers displayed higher levels of social anxiety (Craig, 1998; Walter and Inderbitzen, 1998) and depression (Callaghan and Joseph, 1995), as well as lower levels of social acceptance (Callaghan and Joseph) than children with lower levels of victimization. Victimized children may learn to perceive the world as a dangerous place in which they always need to be on alert, thereby leading to problems with anxiety, especially in social situations. Direct experience with such situations reinforces the perception that social situations are dangerous and are expected to end in failure, a well-known characteristic of social anxiety (Clark and Wells, 1995; Rapee and Heimberg, 1997). Avoidance of social situations often results and prevents individuals from having experiences that disconfirm their beliefs (Francis and Radka, 1995). Roth et al. (2002) measured social anxiety, worry, and anxiety sensitivity in a college student sample to investigate the relationship between memory for teasing in childhood and levels of depression and anxiety in early adulthood. A Teasing Questionnaire was developed to measure the extent to which participants remembered having been teased about 20 different topics during childhood. Positive correlations between scores on the Teasing Questionnaire and anxiety and depression measures were predicted. In addition, social anxiety was expected to have the strongest relationship with memories of teasing. Finally, the authors predicted that the stronger the memories of teasing as a child, the higher the levels of anxiety and depression as an adult. As expected, statistically significant and positive correlations were found between the Teasing Questionnaire and all of the anxiety and depression measures. Anxiety sensitivity and social anxiety were more strongly related to a reported history of childhood teasing than was worry. The authors noted surprise that the strength of the link between childhood teasing and social anxiety did not differ from the strength of association between teasing and anxiety sensitivity. A couple of research studies have examined relationships between social anxiety, anxiety sensitivity, and alcohol consumption in the college setting. Consistent with the tension reduction hypothesis, Lewis and Vogeltanz-Holm (2002) proposed that individuals often consume or abuse alcohol out of an expectation that drinking will reduce unpleasant sensations and cognitions, thus serving as a way to self-medicate anxious feelings. This view is consistent with the Burke and Stephens (1999) model described above and is supported by research showing that socially anxious individuals are more likely to report alcohol-related problems than nonanxious individuals (Kessler, Crum, Warner, Nelson, Schulenberg, and Anthony, 1997; Kushner, Sher, and Beitman, 1990) and that both placebo and alcoholic drinks reduced speech anxiety in a diagnosed social phobia sample (Himle, Abelson, Haghightgou, Hill, Nesse, and Curtis, 1999). Lewis and Vogeltanz-Holm (2002) also suggested that this tension-reduction effect of alcohol differs among individuals with varying levels of anxiety sensitivity. Lewis and Vogeltanz-Holm examined the interaction between anxiety sensitivity, social anxiety, and the effects of alcohol by measuring subjective and physiological responses to a social stressor. ASI (Peterson and Reiss, 1992) scores were obtained from a sample of college women who were subsequently separated into groups of low or moderate anxiety sensitivity. All participants performed a “body image speech” social stressor task in which they presented a speech about what they liked and disliked about their bodies in front of a mirror. Results

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indicated that participants in the moderate anxiety sensitivity group who consumed alcohol experienced a greater dampening of heart rate compared to participants who did not consume alcohol during the anticipatory phase. This result suggested that individuals with elevated levels of anxiety sensitivity are highly responsive to the stress-reduction effects of alcohol when anticipating a stressor. Results from this Lewis and Vogeltanz-Holm study were consistent with a previous investigation in which a burst of loud noise served as the stressor (Stewart and Pihl, 1994). Stewart and Pihl assigned female college students to low, moderate, and high anxiety sensitivity groups based on their Anxiety Sensitivity Index scores (ASI; Peterson and Reiss, 1992). All participants were presented with the loud burst of noise when they were sober and again after they had consumed alcohol. All experienced lower anxiety levels when intoxicated than when sober. Greater anxiety reductions were displayed by the participants in the high anxiety sensitivity group when compared to the low anxiety sensitivity group (Stewart and Pihl, 1994). Thus, anxiety sensitivity may heighten the tensionreducing effects of alcohol in both social and nonsocial stressful situations. Anxiety sensitivity, particularly the fear of negative social consequences resulting from anxiety sensations, appears to be an important component of social anxiety. However, social anxiety treatments rarely address this facet directly. In this next section, we describe original research investigating whether an additional interoceptive exposure component provides any additional clinical benefit over social situation exposure alone.

RESEARCH INVESTIGATION Effects of Interoceptive Exposure on Social Anxiety Interoceptive exposure was originally developed to treat the fears of anxious bodily sensations seen in panic disorder. This treatment involves repeated exposure to feared bodily sensations (Barlow, Craske, Cerny, and Klosko, 1989) and effectively reduced the number of panic attacks as well as the fear of bodily sensations when delivered as a sole treatment (Beck and Shipherd, 1997; Beck, Shipherd, and Zebb, 1997). As discussed above, panic disorder individuals typically fear anxiety-related sensations because they misinterpret these sensations as signs of imminent physical or mental complications. However, individuals may also fear these sensations based on concerns of negative social evaluation. Indeed, socially anxious people tend to report high anxiety sensitivity due to feared social consequences rather than perceived physical harm such as a heart attack (Hazen et al., 1995). Individuals with social phobia interpret the same anxiety-related sensations as a sign of embarrassment or social rejection. For example, a socially anxious individual with high anxiety sensitivity might consider sensations of feeling hot or flushed dangerous because others will see that he or she is anxious and therefore judge them negatively. In contrast, an individual with low anxiety sensitivity would not interpret these sensations as problematic. This conceptualization of social anxiety has led clinical researchers to study interventions that target feared bodily sensations directly. A couple clinical studies have investigated exposure to bodily sensations as a treatment component for social phobia. For example, socially anxious participants exposed to somatic symptoms in a paradoxical treatment showed improvement (Mersch, Hidlebrand, Lavy et al.,

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1992). However, it was unclear whether improvements resulted from exposure to feared physiological sensations or other treatment factors. Similarly, Plotkin (2002, unpublished dissertation) investigated the effects of interoceptive exposure on public speaking anxiety compared to guided imagery relaxation in a sample of socially anxious college students. While some empirical support for the efficacy of interoceptive exposure was found, again it was not clear if exposure to physiological sensations was the active treatment component responsible for decreases in anxiety. Alternatively, some other component of the intervention, such as social exposure to the group setting, may have accounted for treatment effects. The current study investigated whether interoceptive exposure effectively reduced speech anxiety for college students reporting general social phobia. Unlike these previous studies, we controlled for exposure to the group setting by including a control treatment in which participants performed tasks that did not directly induce specific physiological sensations. We predicted that socially anxious students receiving a group session of interoceptive exposure would display greater reductions in distress during a public speaking behavioral assessment test than socially anxious students receiving only social situation exposure. We also expected that students randomized to the interoceptive exposure condition would experience greater reductions in self-report measures of anxiety sensitivity and fear of bodily sensations than students randomized to the social exposure only condition.

Method Approximately 600 undergraduate college students completed the Anxiety Sensitivity Index (ASI; Reiss et al., 1986) and the Social Phobia Diagnostic Questionnaire (SPDQ; Newman et al., 2003) during a mass screening session conducted in their psychology courses. The SPDQ is a 15 item self-report diagnostic questionnaire of social phobia according to DSM-IV criteria. Participants also rated their fear of giving a speech and their fear of anxiety symptoms during a speech. Students endorsing DSM-IV diagnostic criteria for generalized social phobia on the SPDQ, reporting moderate to extreme fear of giving a speech as well as of their heart racing, sweating, shaking, or some other physical sign of anxiety during a speech were eligible for participation. A total of 41 eligible students agreed to participate in the two-hour experimental session for extra credit in their psychology class. Students were randomly assigned to either the interoceptive exposure (IE) condition or the social exposure only condition. In order to ensure that these randomly assigned groups were equivalent on a number of measures before the exposure intervention, all participants completed the following measures both beforehand and afterward: the Anxiety Sensitivity Index (ASI; Reiss et al., 1986), the Body Sensations Questionnaire (BSQ; Chambless et al., 1984), the Social Avoidance and Distress Scale (SADS; Watson and Friend, 1969), the Brief Fear of Negative Evaluation ( BFNE; Leary, 1983), and the Personal Report of Confidence as a Speaker Personal Report of Confidence as a Speaker (PRCS; Paul, 1966). These measures were administered at the beginning of the experimental session prior to the intervention and immediately following the intervention at the end of the experimental session. In addition to these self-report measures, all participants completed a behavioral assessment test (BAT) of speech anxiety before and after the exposure intervention. Participants were instructed to speak for one minute in front of two other participants and a

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video camera, choosing from one of three topics: “Your favorite foods and restaurants”; “How you would like to spend your next vacation”; or “What you like to do for fun when you are not studying”. Subjective units of distress (SUDS; 0-100) were recorded immediately before and after this public speaking BAT task. Participants randomized to the interoceptive exposure (IE) condition were led through three interoceptive exposure exercises conducted in small groups. The interoceptive exposure treatment exercises of overbreathing (i.e., hyperventilation), running in place, and muscle tension were conducted as described by Barlow and Craske (2000). Next, these participants selected the interoceptive exposure exercise that was most anxiety provoking for them and most similar to what they typically experience in feared social situations. IE participants then repeated the selected exercise until habituation occurred, operationally defined as a SUDS rating of 25 or less on two consecutive trials. All of these interoceptive exposure exercises were performed in front of the other group members as well as in front of a video camera. The second condition involved tasks not designed to directly induce physiological arousal. To control for the performance of novel physical tasks in front of a group seen in the IE condition (e.g., hyperventilating and running in place), similar tasks not expected to induce sensations of physiological arousal were developed for this control condition. Specifically, students randomized to this control condition were instructed to stick out their tongue, say ahhh, and stand awkwardly in lieu of the interoceptive exposure exercises performed by IE participants. Following the same procedure as the IE condition, participants chose which task was most anxiety provoking for them and performed this exercise repeatedly until habituation occurred. These tasks were also performed in the presence of the other group members as well as a video camera. For both conditions, participants rated how willing they were to perform each exercise immediately after the exercise was described. After the participants performed each exercise, a SUDS rating, two state measures, and two social anxiety ratings were collected. State measures consisted of autonomic arousal scale items from the Mood and Anxiety Symptom Questionnaire-Anxious Arousal Scale (MASQ-AA; Watson and Clark, 1991) and an abbreviated state version of the State-Trait Anxiety Inventory (STAI-S; Marteau and Bekker, 1992) consisting of 6 statements reflecting one’s level of anxiety “at the moment.” The first social anxiety rating was collected in response to the question “How embarrassed were you during this task?” Level of embarrassment was rated from 0 (“not embarrassed at all”) to 8 (“extremely embarrassed”). The second social anxiety rating was collected in response to the question “How self-conscious did you feel during this task?” Participants rated how selfconscious they felt on a scale of 0-8, with 0 indicating “not at all self-conscious” and 8 indicating “extremely self-conscious.”

Results A one-way MANOVA including all pre-experimental measures yielded no significant group differences before the exposure intervention (all univariate p’s greater than .22), suggesting that random assignment was successful. A series of between-group repeated measures ANOVAs were then conducted on each of the outcome measures. Means and standard deviations for SUDS ratings collected during each BAT as well as for ASI, BSQ,

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and BFNE scores collected at baseline and following the exposure intervention are presented in Table 1. Table 1. Means and Standard Deviations for Measures Collected Pre and Post Exposure Intervention Measure

BAT SUDS ASI BSQ BFNE

Interoceptive Exposure Condition

Pre 58.45 (34.64) 21.30 (11.44) 43.15 (13.74) 39.40 (8.93)

Post 43.55 (30.28) 21.10 (11.11) 44.90 (15.47) 41.25 (8.55)

Social Exposure Only Condition

Pre 72.01 (31.54) 21.38 (12.23) 42.05 (14.75) 38.40 (12.00)

Post 57.18 (41.53) 18.48 (10.71) 37.76 (14.50) 26.75 (11.63)

A between-group repeated measures ANOVA was conducted on SUDS ratings collected during the baseline BAT performed before the exposure intervention and on SUDS ratings collected during the post-intervention BAT performed after the exposure intervention. A main effect for time reflected that BAT SUDS ratings decreased after the exposure intervention for the participants overall, F(1, 39) = 10.87, p < .01. No main effect for group F(1, 39) = 1.89, ns, or interaction effect F(1, 39) = 0, ns was found. A between-group repeated measures ANOVA was also conducted on total ASI scores collected at baseline and after the exposure intervention. A main effect for time showed that total ASI scores reduced for the sample as a whole, F(1, 39) = 5.09, p < .05, but no main effect for group, F(1, 39) = .13, ns was found. An interaction effect approached significance, F(1, 39) = 3.86, p = .057, reflecting a greater decrease in ASI scores for the social exposure only group than the IE group. A between-group repeated measures ANOVA was then conducted on pre and post exposure intervention BSQ scores. A significant interaction effect was found F(1, 39) = 3.86, p < .01, in which only the social exposure control group exhibited a decrease. No main effects of time F(1, 39) = 1.47, ns, or of group F(1, 39) = .86, ns were found. A between-group repeated measures ANOVA conducted on pre and post exposure intervention BFNE scores also yielded a significant interaction effect F(1, 38) = 10.05, p < .01, in which only the social exposure control group showed a decrease. No main effect of time F(1, 38) = .03, ns, or of group F(1, 38) = .72, ns were found. Between-group repeated measures ANOVAs conducted with SADS and PRCS scores yielded no significant main or interaction effects for either measure. Given the unexpected nature of these results, we conducted a series of post-hoc group comparisons. Independent samples t-tests between the two groups were performed on three task variables. No significant group differences were found for ratings of how embarrassing the tasks were, t(39) = .30, p < .76, or for ratings of how self-conscious participants felt while performing the tasks, t(39) = -.53. p < .60. The MASQ-AA, our self-report measure of physiological arousal, was significantly higher for the IE group than the social exposure only control group t(36) = 3.27, p <.01. As intended, the IE group reported more physiological arousal during their exposure tasks than the control group.

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Discussion As expected, both exposure groups experienced reductions in social anxiety following the exposure intervention as measured by subjective distress ratings (SUDS) during a public speaking behavioral assessment task. However, this reduction was not more pronounced for the IE group than the social exposure only group. Both groups also reported reductions in anxiety sensitivity following the exposure intervention, but interoceptive exposure did not lead to greater reductions in anxiety sensitivity than social exposure alone. Perhaps most surprising was our finding that only the social exposure control group exhibited reductions in a related construct measured by the Body Sensations Questionnaire. In contrast, the interoceptive exposure group failed to show decreases on this measure. Fears of negative evaluation also reduced for the social exposure only control group but not for the IE group. Thus, the addition of interoceptive exposure exercises designed to elicit specific feared bodily sensations does not appear necessary in the treatment of college student social anxiety. Follow up data analysis suggested that feared physiological symptoms were effectively induced during interoceptive exposure, as interoceptive exposure produced greater selfreported physiological arousal than the social exposure only tasks. However, participants in the social exposure only condition appeared to benefit more from this experimental control intervention on a couple of outcome measures when compared to participants in the interoceptive exposure intervention. There were no differences between groups on the ratings of embarrassment and self-consciousness experienced during the exposure tasks. Thus, it does not appear that participants in the social exposure only condition received more intensive social situation exposure than participants in the IE condition. However, IE participants may have been distracted from the social context in which the tasks were performed more so than control participants, given the focus of interoceptive task instructions on the induction of specific bodily sensations. The students who performed the social exposure only tasks may have had more attentional resources available for the social exposure component of that intervention.

CONCLUSION Social anxiety is a common clinical problem across college campuses. Socially anxious college students report reduced assertiveness and feelings of competence in social situations, particularly in dating relationships (Chambless et al., 1982; Lesure-Lester, 2001). In addition to common physical symptoms such as “butterflies” in the stomach, general tension, and blushing (Purdon et al., 1999), social anxiety among college students can lead to behavioral avoidance, social isolation, and depression (Johnson et al., 1992). Excessive drinking to selfmedicate anxiety and tension in social situations appears to be a particularly problematic coping strategy for these students (Burke and Stephens, 1999). Ironically, socially anxious students are more likely than nonanxious students to judge visible signs of anxiety in others negatively (Purdon et al., 1999). For this reason, experiencing anxious sensations in the presence of others may be especially threatening for the socially anxious. Indeed, socially anxious individuals report elevated levels of anxiety sensitivity, or fear of anxious bodily sensations, due to perceived threatening social

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consequences of such sensations (Hazen et al., 1995). Available research suggests that anxiety sensitivity plays an integral role in the development and maintenance of social anxiety among college students (Gore et al., 2002), possibly interacting with other important factors such as a history of childhood teasing (Roth et al., 2002). Furthermore, anxiety sensitivity may augment a socially anxious individual’s response to the stress-reduction effects of alcohol (Lewis and Vogeltanz-Holm, 2002). Social anxiety researchers have begun to investigate the possible clinical benefit of interoceptive exposure, the direct induction of feared physiological sensations first developed for panic disorder treatment. Although promising, previous research (Mersch et al., 1992; Plotkin, 2002) did not control for the social situation exposure inherent in conducting interoceptive exposure exercises in front of others. In our own original research investigation, we randomly assigned socially anxious college students to receive a session of either group interoceptive exposure or group social exposure only. Results indicated that interoceptive sensations were effectively produced for interoceptive exposure participants and that both treatments were largely beneficial. However, the social exposure only group showed additional improvements not exhibited by the interoceptive exposure group. Thus, inducing physiological sensations did not seem to have any clinical benefit above and beyond mere exposure to a social situation. Given that no group differences were found on task-related measures of embarrassment and self-consciousness, the nature of the specific tasks conducted in the social exposure only condition do not seem to account for these results. The question of whether or not socially anxious individuals would benefit from induction of physiological sensations remains. Limitations of the current study include a small sample size, use of a brief single session intervention, and lack of direct physiological arousal measures. Future research is needed to develop relevant interoceptive exposure exercises that effectively target the fears of socially anxious individuals before this approach can be recommended for the treatment of social phobia. The traditional cognitive-behavioral exposure approach, such as Cognitive-Behavioral Group Therapy developed by Heimberg and colleagues (Turk, Heimberg, and Hope, 2001), is still the psychological treatment of choice for social anxiety disorder.

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In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 3

COPING, MENTAL HEALTH STATUS, AND CURRENT LIFE REGRET IN COLLEGE WOMEN WHO DIFFER IN THEIR LIFETIME PREGNANCY STATUS: A RESILIENCE PERSPECTIVE *

Jennifer Langhinrichsen-Rohling†, Theresa Rehm, Michelle Breland and Alexis Inabinet University of South Alabama, Mobile, Alabama USA

ABSTRACT This study examined the current mental health status, coping strategies, and perceived life regret of three types of female college students (n = 277): those who had never been pregnant (67.9%, n= 188); those who became pregnant at or before age 18 who were a priori considered to be resilient (14.8%, n = 41); and those who had experienced a pregnancy after age 18 (17.3%, n = 48). Data were collected at a diverse urban public university in the Southeast. This university has a significant number of commuter and non-traditional students. Results indicated that college women who had experienced an adult pregnancy reported significantly fewer maladaptive coping strategies than never-pregnant college women and those who had experienced a teenage pregnancy. Surprisingly, both groups of ever pregnant college women expressed significantly more life regret than never pregnant college women. Among the college women who had experienced a teenage pregnancy, two groups were delineated: those who were “thriving” versus those who were “at-risk” with regards to their current *

This project was supported by Grant No. 2001-SI-FX-0006 awarded by the Office of Juvenile Justice and Delinquency Prevention, Office of Justice Programs, U.S. Department of Justice. Points of view or opinions in this document are those of the author and do not necessarily represent the official position or policies of the U.S. Department of Justice. † Correspondence concerning this article should be addressed to Jennifer Langhinrichsen-Rohling, 385 Life Sciences Building, Psychology Department, University of South Alabama, Mobile, AL., 36688-0002, or the author can be reached via email at [email protected].

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Jennifer Langhinrichsen-Rohling, Theresa Rehm, Michelle Breland et al. symptoms of depression, hostility, and hopelessness. Women in the “at-risk” group were significantly less likely to be simultaneously parenting and attending college than those in the “thriving” group. One potential implication is that identifying and intervening with these potentially at-risk college women may help improve retention rates and student morale at universities with a diverse student body.

INTRODUCTION Individual differences in successful adaptation to stressful life events have prompted investigations of a construct termed resilience. Many different definitions of resilience have been used across studies (Luthar, Cicchetti, & Becker, 2000). Resilience requires an individual both to experience a precipitating adversity and subsequently to exhibit successful adaptation to the event. It is necessary to clearly operationally define both of these components in order to study the construct of resilience. For example, definitions of what constitutes a precipitating adversity have ranged from a single stressful experience to exposure to various levels of cumulative negative events (Luthar et al., 2000). Methods of identifying individuals who have successfully adapted, or who are exhibiting resilience in response to adversity, have also varied. Carver (1998) suggested that resilient individuals are those who return to their prior level of functioning after experiencing adversity. Others have required that resilient individuals excel in one category, while maintaining at least average performance in other areas (Luthar, Doernberger, & Zigler, 1993). Still others have divided resilient individuals into distinct categories. For example, Masten (1994) specified three resilient outcomes: (1) the individual experiences a better-thanexpected outcome, (2) positive adaptation is maintained despite the continued occurrence of stress, or (3) there is good recovery from trauma. Carver (1998) also argued that benefits could occur through adversity. He describes this as “thriving”, and argues that thriving is a conceptually distinct construct from resilience. The psychological components or mechanisms underlying resilience have also been delineated in diverse ways. According to Luthar and colleagues (2000), early explorations of resilience were centered on identifying children’s pre-existing character traits, such as high self-esteem or resourcefulness (Masten & Garmezy, 1985; Moran & Eckenrode, 1992). More recently, researchers have argued the importance of conceptualizing resilience as a dynamic and multi-faceted process (Luther et al., 2000). This led to the inclusion of external in addition to internal factors when studying resilience. In 1992, Werner and Smith delineated three disparate factors that influence the development of resilience. They are: (1) attributes of the individual, (2) aspects of the person’s families, and (3) characteristics of the individual’s wider social environment. Bickart and Wolin (1997) have expanded this conceptualization by articulating seven essential attributes of the individual (i.e., insight, independence, relationships, initiative, creativity, humor, and morality). They also noted that the expression of these attributes interacts with environmental factors, which may or may not be related to the precipitating stressor, and may be expressed unevenly across time. Consistent with this line of reasoning, in the current study, it is assumed that individuals who display resilience to one significant life event (i.e., teenage pregnancy) are more likely to demonstrate certain adaptive coping strategies and to possess particular individual attributes. These characteristics, such as high levels of personal competence and/or hopefulness, are

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likely to have contributed to their resilience. However, it is still plausible that some of these resilient individuals might simultaneously display some characteristics that would place them at risk for continued life difficulties; perhaps because of on-going mental health concerns or stress related to the life event, trauma related symptoms, and/or continued life regret over the initial adversity. Thus, resilient individuals may differ in the degree to which they can be considered to be “thriving”, particularly if they are exposed to additional stressors over time. Within the resilience literature, researchers have focused on a number of different adversities from which successful adaptation is difficult. For example, studies have examined resilience from family adversity (Fergusson & Lynskey, 1996), childhood sexual abuse (Himelein & McElrath, 1996; Wilcox, Richards, & O’Keeffe, 2004), growing up with alcoholic parents (Carle & Chassin, 2004; Statham, 2004), being exposed to the battering of their mothers (Humphreys, 2001), coping with a mentally ill parent (Polkki, Ervast, & Huupponen, 2004), and triumphing over a generally high level of stress and numerous life events (Burton, 2004; Carver & Scheier, 1989; Charney, 2004; Compas, 1987; Fergusson & Lynskey, 1996; Lazarus, 1993). In many of these studies, resilience has been studied by observing positively adjusted individuals who have already experienced the specific stressor or the general adversity. These individuals, termed resilient, are then compared to similar groups of individuals who did not experience the stressor to determine which factors of resilience contributed to the successful adaptation of the resilient individuals. Relevant to the current study, and an important event to which relatively large numbers of young women must cope, is teenage pregnancy. It is well established that teenage pregnancy and childbearing is a significant problem in the United States (for reviews, see Adams, Adams-Taylor, & Pittman, 1989; Clemmens, 2002; Furstenberg, 1991; Hudson, Elek, & Campbell-Grossman, 2000; and Kivisto, 2001). Pregnancy is a unique adverse event in which to study resilience in that it often impacts individuals for the rest of their lives, particularly if they make the transition from pregnancy to parenthood. Furthermore, although pregnancy and childbearing are not typically viewed as negative events, the early timing, the emotional and physical requirements it places on an adolescent, and the increased likelihood that the event was unplanned for and/or unwanted, make it a significant stressor in a teenager’s life (Adams et al, 1989). Even for older moms, pregnancy, childbearing, and subsequent parenting can be stressful, limiting women’s available educational and career opportunities. The consequences of teenage pregnancy have been shown to be even more detrimental. According to Adams et al. (1989) more than half of teenage mothers and a third of teenage fathers drop out of high school. This is significant because without a high school diploma, these adolescents are almost certain to live in poverty. The added expenses of raising a child, including large daycare costs, exacerbate this problem. In addition, adolescent mothers have been shown to have higher rates of depression and experience more stress in the parenting role than older mothers (Hudson et al., 2000). Being forced to take on the adult role of parenting before completing their own adult developmental tasks can make things especially difficult. At a time when their peers are enjoying social outings and other egocentric activities, becoming a teenage parent can compromise the development of self-identity and limit mate-selection (Leitch, 1998). Finally, concern over body image and the need for peer acceptance can cause self-esteem problems for teenage mothers (Hudson et al., 2000). In spite of these circumstances, researchers have noted that pregnancy and parenting do not affect all individuals in the same way. Just as some abused children find the strength to

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succeed in spite of all odds, some adolescent mothers continue their education in spite of parenting demands begun during their teenage years. In the current study, we are defining these college women as resilient. Consistent with the literature, we assert that it is likely that both internal factors, or personality traits, and external factors, or situational conditions, contributed to their resilient status. The degree to which a subset of these women can be considered to be thriving versus being at continued risk in the college environment is the primary focus of the current study. To date, the literature has been largely silent about whether there are current mental health characteristics or coping factors that differentiate college women who differ in terms of whether they experienced a teenage pregnancy, never experienced a pregnancy, or experienced a pregnancy after they were teenagers. Therefore, the present study was designed to investigate three areas of particular importance to understanding resilience and subsequent thriving: current mental health status (levels of hostility, hopelessness, and depression), perceived life regret, and continued use of adaptive versus maladaptive coping skills. A priori, the following hypotheses were developed. First, because of the resilience demonstrated by matriculation, college women who experienced a teenage pregnancy were expected to demonstrate thriving in the academic environment as evidenced by fewer feelings of hopelessness and hostility, less current depression and perceived life regret, and increased use of adaptive coping strategies in comparison to both other groups of college women (never pregnant and adult pregnant). However, we expected considerable variability among these women such that a subset of college women who had experienced a teenage pregnancy could still be identified as “at-risk” with regards to their mental health functioning and coping skills. Second, it was hypothesized that college women who experienced an unwed pregnancy will differ significantly from those who experienced a pregnancy while married, regardless of their age at the time of the pregnancy. To our knowledge, no preexisting research has compared these two groups of college women. However, exploratory hypotheses were generated such that college women who were unmarried when they became pregnant will exhibit more current hopelessness, hostility, depression, and life regret, as well as fewer adaptive coping strategies than college women who were married when they became pregnant. This is expected because of the greater stressors and reduced social support associated with unwed motherhood. Finally, it is hypothesized that current college women who had a teenage pregnancy, but who are not currently parenting (because of abortion, adoption, miscarriage), will differ significantly from college women who experienced a teenage pregnancy and are simultaneously parenting a child while pursuing their education. These final analyses were exploratory in nature, and no a priori hypotheses were offered.

METHOD Participants Participants included 277 female college students who were enrolled in Introductory Psychology classes at an urban university located in the Southeastern part of the United States. The races of the participants were as follows: Caucasian (61%), African American

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(26%), Asian American (2.2%), Hispanic (1.8%), and Native American (0.4%). Twenty-three participants (8.3%) reported their race to be “other” and one participant (0.4%) did not report her race. The ages of the participants ranged from 19 to 54 years old, with a mean age of 23 years. The majority of the participants indicated that they were freshmen (59.2%). The sample also included sophomores (25.6%), juniors (9.4%), and seniors (4.7%). The grade point average (GPA) reported by the participants varied from 1.4 to 4.0, with a mean GPA of 3.1. These demographics are consistent with the demographics of the university’s college women, excluding the high proportion of freshmen in the sample. However, this was to be expected given that these data were collected from female students taking an introductory class in Psychology.

Instruments Participants were administered a 252-item questionnaire composed of several different scales. Questions on the survey were used to determine participant status according to the independent variables of teenage pregnancy status, marital status at time of pregnancy, and current motherhood status. Teenage pregnancy status was defined as the experience of a pregnancy at or before the age of 18. This was determined by participant answers on two questionnaire questions. The first question determined whether or not the college woman had ever experienced a pregnancy. A follow-up question determined the participant’s age at the time of pregnancy, if a pregnancy had occurred. Marital status at the time of pregnancy was defined as being married at the time of conception, and was determined by one question. Finally, current motherhood status was defined as completing the pregnancy and currently parenting one or more children while attending college. The dependent variables of interest were mental health status (current depression, hostility, and hopelessness), use of adaptive versus maladaptive coping strategies, and perceptions of current life regret. These three categories, within which the following scales were utilized, are described below.

Mental Health Status Depressive Symptoms. Symptoms of depression were assessed with 10 items from the Center for Epidemiological Studies-Depression Scale (CES-D; Radloff, 1977). On this scale, participants rate how frequently they have experienced each of 10 symptoms related to depression over the past seven days. Each items is rated on a four-point scale (rarely or never = 0, some or little of the time = 1, occasionally or a moderate amount of time = 2, most or all of the time = 3). Higher scores represent greater levels of depression by indicating a higher number of symptoms and/or symptoms that are more frequent. This scale has been used successfully in college samples, showing good reliability and internal consistency (e.g., Langhinrichsen-Rohling, Arata, Bowers, O’Brien, & Morgan, 2004). The current sample had a coefficient alpha of 0.82 for this scale. Hostility Hostility was measured with six items adopted from the Symptom Checklist-90 (SLC-90; Derogatis, 1994). These six items were used to gauge respondents’ current level of anger and

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irritation by asking them to rate how well each item pertains to them. Responses range from "not at all" to "extremely". Higher scores represent greater levels of hostility. In the current sample, these six items had a coefficient alpha of 0.84.

Hopelessnes Hopelessness was evaluated by six items designed to assess participants' negative expectations about themselves and their future. Five of the items were adopted from Kazdin's Hopelessness Scale for Children (HSC; Kazdin, French, Unis, Esveldt-Dawson, & Sherick, 1983). These five items, along with another item ("I don't expect to live a very long life"), were utilized successfully in previous research with both adolescents and college students by the primary author (Langhinrichsen-Rohling et al., 2004). Respondents are asked to rate how well they agree with each statement, with responses ranging from "strongly agree" to "strongly disagree". The coefficient alpha for the current sample was 0.72 for these six items, with higher scores indicating greater levels of hopelessness. Adaptive Verses Maladaptive Coping Strategies Coping. Coping was assessed with thirty items derived from the Adolescent Coping Orientation for Problem Experiences (A-COPE; Patterson & McCubbin, 1987). The A-COPE is a 54-item self-report questionnaire designed to measure adolescents' coping behaviors. Respondents are asked to rate how often they engage in each behavior when facing difficulties. Responses are based on a five-point scale ranging from "never" to "most of the time". The current study had a coefficient alpha of 0.83 for the thirty items taken from the ACOPE. Several researchers, including the authors of this instrument, have performed factor analysis on the A-COPE scale (e.g., Patterson & McCubbin, 1987; Copeland & Hess, 1995; Langhinrichsen-Rohling, O'Brien, Klibert, Arata, & Bowers, 2006). The numbers of factors contained within the scale have varied and differing amounts of subscales have been used, ranging from 6 to 13 different subgroups of coping strategies. Likewise, researchers have utilized a variety of different names for the subscales, which, in turn have included different items. Thus, the current study chose to investigate coping more broadly, by only separating the items into two subscales. Specifically, the thirty items from the A-COPE were divided into adaptive and maladaptive coping strategies for the current study; these two subscales were confirmed via factor analysis. The first subscale included 20 items and was labeled Adaptive Coping (alpha=0.88). Items on this subscale included activities such as apologizing, getting more involved in school and extracurricular activities, compromising, engaging in self improvement, optimistic thinking, joking, or organizing your life, seeking help from others, and/or talking with friends/ family about the problem. The second subscale contained 10 items and was labeled Maladaptive Coping (alpha=0.60). Items on this subscale included activities such as staying away from home, using drugs or alcohol, swearing, becoming aggressive, blaming others, and avoiding the problem. Perceptions of Current Life Regret Current life regret. Current life regret was assessed by one question on the questionnaire. Respondents were asked to indicate how much they agreed with the statement: "As I look

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back on my life, I am fairly well satisfied". Scores on this scale ranged from one to seven, with higher scores indicating more life regret.

Procedures After obtaining IRB approval, participants were obtained from the Introductory Psychology Course Human Subject Pool. Participants volunteered for the study in order to fulfill a research requirement. Data were collected over three consecutive semesters. During the first two semesters, data were collected in person. To be eligible for participation, the student had to be female and over the age of 18. Eligible participants were given an appointment time, and were then given the anonymous, self-report survey in a small group setting. However, during the third semester the survey was put on-line on the Psychology Department research participation website. Participants remained anonymous via the webbased procedure. All ethical procedures were followed, such as obtaining informed consent and providing appropriate debriefing procedures. At the conclusion of the survey, participants were also given the opportunity to indicate whether they were willing to participate in a follow-up interview if eligible. The results presented in this chapter represent only the data gathered from the self-report packets.

RESULTS The majority of the sample of college women had never experienced a pregnancy (n = 188; 67.9%). Of the 89 participants who had experienced a pregnancy, 41 were at or below the age of 18 at the time of conception (teenage pregnancy) and 48 were over the age of 18 when they became pregnant (adult pregnancy). The majority of participants reporting a pregnancy were also unmarried at the time of conception (n = 60; 68.2%). Of the 41 college women who experienced a teenage pregnancy, 25 (61.0%) were parenting at least one child while they were attending school. Fifteen of the women (36.6%) were not living with a child or parenting a child from their teenage pregnancy. Data for one of the teenage pregnant women were missing. Of the 48 college women who experienced a pregnancy as an adult, 35 (72.9%) completed the pregnancy and were currently parenting. Thirteen of the women (27.1%) were not currently parenting. To test the first hypothesis, a three group (Never Pregnant, Teenage Pregnancy, and Adult Pregnancy) MANOVA was conducted with the three mental health measures as the dependent variables. Contrary to expectation, this analysis failed to reveal a significant main effect for group, Roy’s Largest Root (3, 271) = .012, p = .36. As shown in Table 1, there were no significant between-group differences for current levels of hostility, depression, or hopelessness. However, on all three variables, the largest standard deviations were obtained for the teenage pregnancy group, indicating that, as anticipated, there may be considerable heterogeneity within this group of college women.

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Jennifer Langhinrichsen-Rohling, Theresa Rehm, Michelle Breland et al. Table 1. Differences in Current Mental Health, Coping, and Perceived Life Regret among Never Pregnant, Teenage Pregnant, and Adult Pregnant College Women

Measure Hostility M SD Depression M SD Hopelessness M SD Adaptive Coping M SD Maladaptive Coping M SD Life Regret M SD

Never Pregnant (n=188)

Teenage Pregnancy (n=41)

Adult Pregnancy (n=48)

3.01 3.52

3.66 3.95

3.17 3.46

7.99 5.97

8.29 6.02

7.78 4.66

0.34 0.85

0.56 1.28

0.28 0.74

66.64 13.06

62.34 13.95

22.67a 5.10 2.22a 0.98

F

p

ETA2

<1

0.58

.00

<1

0.92

.00

1.25

0.29

.01

63.62 11.42

2.43

0.09

.02

23.11a 5.07

20.61b 4.76

3.70

<.05

.03

2.59b 0.89

2.65b 1.06

5.04

<.01

.04

Female College Students (n = 277) Note: N’s vary slightly across analyses due to missing data. Post Hoc comparisons were conducted with Least Significant Differences tests. Means with different superscripts are significantly different from one another.

A three group (Never Pregnant, Teenage Pregnancy, and Adult Pregnancy) MANOVA with the adaptive and maladaptive coping subscales as the dependent variables was then conducted. As expected, this analysis did reveal an overall significant main effect for group, Roy’s Largest Root (2, 271) = .030, p < .05. As shown in Table 1, follow-up univariate ANOVA’s revealed significant between-group differences for reports of engagement in maladaptive coping strategies and a trend for group differences in reports of engagement in adaptive coping strategies. Follow-up LSD comparisons of the significant main effect for maladaptive coping strategies indicated that college women who reported experiencing an adult pregnancy engaged in significantly fewer maladaptive coping strategies than college women who had experienced a teenage pregnancy or college women who had never been pregnant. Significant between-group differences were also obtained for perceptions of life regret, F (2, 274) = 5.04, p < .01, ETA2 = .04. Post-hoc analyses of the means indicated that both groups of college women who reported a pregnancy, regardless of their age at the time of conception, expressed significantly more life regret than college women who reported never being pregnant. To test the degree to which marital status at the time of the pregnancy was associated with improved mental health functioning, greater adaptive and less maladaptive coping, and reduced life regret, a similar series of analyses were conducted comparing three groups of

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college women: Never Pregnant (n = 188), Unwed Pregnancy (n = 60), and Wed Pregnancy (n = 28). Because older women were more likely to be in the wed pregnancy group, age was included as a covariate in all of these analyses. Contrary to expectation, and according to a three group MANOVA with the three mental health scores as the dependent variables, there were no significant differences among the three groups in their reports of current symptoms of mental distress, Roy’s Largest Root (3, 270) = .021, p = .14. Age did emerge as a significant co-variate in this analysis. Follow-up univariate analyses of the age effect revealed that college women’s reports of feelings of hostility diminished with age, F (1, 271) = 5.96, p < .05, ETA2 = .02. A second three group (Never pregnant, Unwed Pregnant, and Wed Pregnant) MANOVA with the adaptive and maladaptive coping subscales as the dependent variables also failed to reveal a main effect for group, Roy’s Largest Root (2, 272) = .012, p = .21. Moreover, age did not emerge as a significant co-variate in this analysis, Roy’s Largest Root (2, 271) = .016, p = .12. Finally, an ANOVA did reveal a significant main effect for group in terms of their reports of life regret, F (2, 274) = 5.18, p < .01, ETA2 = .04. However, LSD post-hoc comparisons indicated that this effect was due to the reduced life regret reported by the never pregnant college women (M = 2.22, SD = .98) in comparison to the two groups of ever pregnant college women. Contrary to expectation, the mean life regret scores of the unwed pregnant college women (M = 2.62, SD = .98) did not significantly differ from the mean life regret scores of the college women who were married at the time of their pregnancy (M = 2.62, SD = 1.03). To consider the degree to which current parenting status impacted the mental health, coping behaviors, and life regret perceptions of college women who had experienced a teenage pregnancy, a third series of analyses were conducted. As shown in Table 2, a three group (Never Pregnant, Teenage Pregnancy Not Parenting, Teenage Pregnancy and Parenting) MANOVA with three mental health scores as the dependent variables revealed a significant overall main effect for group, Roy’s Largest Root (3, 223) = .079, p = .001. Follow-up univariate ANOVA’s revealed that the significant group effect held for symptoms of depression, F (2, 224) = 3.44, p < .05, ETA2 = .03; hopelessness, F (2, 224) = 6.55, p < .05, ETA2 = .04; and hostility, F (2, 224) = 3.45, p < .05, ETA2 = .03. As shown in Table 3, the same pattern of mean differences were obtained for all three variables such that college women who had experienced a teenage pregnancy yet were not parenting were currently reporting higher levels of depression, greater feelings of hostility, and more hopelessness about the future than were either never pregnant college women or college women who had a teenage pregnancy but who were currently parenting. Similarly, a three group MANOVA with the two coping subscales as dependent variables revealed a main effect for group, Roy’s Largest Root (2, 224) = .041, p = .01. Follow-up univariate ANOVA’s revealed that there were significant group differences in reports of maladaptive coping strategies utilized, F (2, 224) = 3.31, p < .05, ETA2 = .03. There was also a trend for group differences in terms of reports of the utilization of adaptive coping strategies, F (2, 224) = 2.44, p = .09, ETA2 = .02. LSD comparisons revealed the same pattern of mean differences such that college women reporting a teen pregnancy but no current parenting indicated that they were engaging in significantly more maladaptive coping strategies than either the never pregnant college women or the teenage pregnant college women who were parenting while attending college.

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Jennifer Langhinrichsen-Rohling, Theresa Rehm, Michelle Breland et al. Table 2. Differences in Current Mental Health, Coping, and Perceived Life Regret among Never Pregnant, Teenage Pregnant and Parenting, and Teenage Pregnant and Not Parenting Women

Measure

Hostility M SD Depression M SD Hopelessness M SD Adaptive Coping M SD Maladaptive Coping M SD Life Regret M SD

Never Pregnant (n=188)

Teenage Pregnant and Not Parenting (n=15)

Teenage Pregnant and Parenting (n=25)

3.01a 3.52

5.40b 4.55

2.56a 3.27

7.99a 5.97

11.40b 6.53

0.34a 0.85

F

p

ETA2

3.45

<.05

.03

6.36a 5.05

3.44

<.05

.03

1.20b 1.90

0.20a 0.50

6.55

<.01

.06

66.64 13.06

59.90 13.81

62.97 13.75

2.44

0.09

.02

22.67a 5.10

25.67b 5.75

21.47a 4.05

3.31

<.05

.03

2.22a 0.98

2.47ab 0.74

2.68b 0.99

2.79

=.06

.02

Note: N’s vary slightly across analyses due to missing data. Post Hoc comparisons were conducted with Least Significant Differences tests. Means with different superscripts are significantly different from one another. Table 3. Differences in Adaptive and Maladaptive Coping, and Perceived Life Regret among Thriving versus At-risk College Women who had experienced a teenage pregnancy

Measure Adaptive Coping M SD Maladaptive Coping M SD Life Regret M SD

Teenage Pregnancy in Thriving Cluster (n=29)

Teenage Pregnancy in At-risk Cluster (n=11)

62.45 13.52

F

p

ETA2

60.09 14.57

<1

0.63

.01

21.91b 4.01

26.06a 6.57

5.81

<.05

.14

2.45 0.95

3.00 0.63

3.16

=.08

.08

Note: N’s vary slightly across analyses due to missing data.

A trend was found of group differences on reports of perceptions of life regret, F (2, 225) = 2.79, p = .06, ETA2 = .02. In this analysis, significantly higher life regret scores were obtained by the teenage pregnant college women who were parenting (M = 2.68, SD = .99) than by never pregnant college women (M = 2.22, SD = .98). The mean life regret scores of the college women who had experienced a teenage pregnancy but were not parenting (M =

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2.47, SD = .74) was in-between the means of the two other groups, and not significantly different from either one. Lastly, due to the greater variability obtained in the mental health scores of college women who reported experiencing a teenage pregnancy in comparison to the never pregnant and adult pregnant college women, a set of post-hoc analyses were conducted. Specifically, we sought to distinguish among the teenage pregnancy group, those who were “thriving” from those who were “at risk”. To determine this, a K-means cluster analysis was conducted with the 40 women in the teenage pregnancy group who had complete scores on the hostility, depression, and hopelessness measures. Clusters were derived in three iterations. The final distance between cluster centers was 12.75. Twenty-nine women were placed in cluster one and 11 women were placed in cluster two. Women in cluster one had lower scores on hostility (cluster center = 2), depression (cluster center = 5), and hopelessness (cluster center = 0) than did women in cluster two. Women in cluster two had higher scores on hostility (cluster center = 8), depression (cluster center = 16), and hopelessness (cluster center = 1). In keeping with Carver’s (1998) theory, college women who had experienced a teenage pregnancy who were classified into cluster one could be considered to be “thriving”, while those placed into cluster two might be considered to be still “at-risk” in spite of their resilience in continuing their education. Not unexpectedly, there was a significant association between cluster membership and current parenting status, X2 (1) = 4.42, p < .05. Only four of the 25 college women (16%) who had experienced a teenage pregnancy and were currently parenting were placed into the “atrisk” cluster, whereas seven of the 15 college women (47%) who had experienced a teenage pregnancy but who were not parenting a child were placed into the “at-risk” cluster. As shown in Table 3, in spite of relatively low power, additional analyses indicated that college women in the “at-risk” cluster also reported engaging in more maladaptive coping behaviors in response to stressors than did college women in the “thriving” cluster, F (1, 39) = 5.81, p < .05, ETA2 = .14. Group membership accounted for 14 percent of the variance in scores on the maladaptive coping subscale. No significant differences in reports of engaging in adaptive coping strategies were obtained between the two clusters (F < 1). However, there was a trend for the two groups to differ in terms of their expression of life regret, F (1, 38) = 3.16, p = .08, ETA2 = .08, with less life regret reported by those women in the “thriving” cluster (M = 2.45, SD = .95) than in the “at-risk” cluster (M = 3.00, SD = .63).

DISCUSSION In the current study, college women who had experienced a teenage pregnancy and yet were continuing to advance their education were operationally defined to be displaying resilience. About one-third of our sample of college women indicated that they had been pregnant at some time in the past; with approximately 45% of these women indicating the pregnancy occurred when they were 18 years old or younger. These women represent a sizable minority of the sample, suggesting that this is an important subgroup of students to consider when planning activities within a large diverse urban university. Analyses were then conducted to determine if resilient teenage pregnant college women could be differentiated from never pregnant college women or from adult pregnant college

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women in terms of their current mental health status, utilization of coping strategies, or perceptions of life regret. Results suggested few, if any, group differences that were specific to the college women who had experienced a teenage pregnancy, making these findings consistent with definitions of resilience which have focused on individuals’ return to their prior level of functioning after experiencing adversity as a central concept (Carver, 1998). Unlike similar studies which have considered resilience in relation to a number of other life events primarily by studying individuals who have achieved a relatively unlikely positive outcome in relation to the stressor they have withstood (e.g., Carle & Chassin, 2004; Himelein & McElrath, 1996; Humphreys, 2001; Milgram & Palti, 1993; Statham, 2004; Wilcox et al., 2004), no particular adaptive coping strategies or lack of maladaptive coping strategies were identified in the current study that could be considered to be potential mechanisms underlying these teenage pregnant college women’s educational resilience. This may be because of the diversity of outcomes associated with teenage pregnancy (i.e., abortion, miscarriage, adoption, delivery of a premature baby, single parenthood, continued involvement of grandparents during the mother’s individuation process, early marriage, divorce or abuse, and subsequent children). As a result, resilient women in this group may have quite heterogeneous on-going experiences impacting them as they attend college. Or it may be that the variables included in the current study did not capture the key components of these women’s mechanisms for resilience. Therefore, additional research will be needed to understand the mechanisms of resilience utilized by college women who experienced a teenage pregnancy, perhaps by utilizing an indepth qualitative interview as was done by Himelein and McElrath, 1996. Potential mechanisms to consider might include higher IQ and lower affiliation with delinquent peers post-pregnancy (Fergusson & Lynskey, 1996), as well as higher pre-existing educational aspirations (Tiet et al., 1998). The field is also likely to be advanced if a large enough sample of college women with a teenage pregnancy history is studied so that researchers can consider the associations between current functioning and particular choices, existing environmental factors, and/or outcomes associated with the stressful or traumatic event. One between-group finding did emerge when comparing teenage pregnant, adult pregnant, and never pregnant college women. Specifically, both groups of college women who had experienced a pregnancy, regardless of their age at the time of conception, expressed greater life regret than the never pregnant group of college women. Qualitative research is necessary to determine definitive reasons; however, it is possible that these results could be explained by the greater demands placed on college students who are simultaneously parenting. These findings might also be driven by the nonparenting women within the pregnant groups whose greater life regret might be related to pregnancy loss (for reviews, see Brier, 2004; Neugebauer, 2003). Furthermore, an unexpected finding emerged among the three groups such that the fewest maladaptive coping strategies were endorsed by college women who had become pregnant as adults. There are several possible explanations for this result including pre-existing factors associated with adult pregnancy prior to attending college (e.g., these women might have been more family oriented, more relationship oriented, or less sensation seeking than never pregnant or teenage pregnant college women). These findings might also relate to current situational or environmental factors that are more likely to occur for the adult pregnant college women (e.g., these women may be older, more financial stable, and/or have more role responsibilities as mother, student, wife, wage earner that serve as protective factors from

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engaging in some types of maladaptive coping strategies). Additional research is needed to confirm these results. Theoretically, we expected one group of college women who had experienced a teenage pregnancy to be “thriving” while a second group could continue to be considered “at-risk” in spite of their initial resilience to the teenage pregnancy (Carver, 1998). A priori, we also chose to consider two potential situational factors that may impact the ever pregnant college woman’s ability to thrive differently. They were: marital status at the time of conception and whether the previously pregnant woman is concurrently parenting while she is attending college. Results indicated that there were few findings associated with marital status at the time of conception; however, teenage pregnant college women who were not concurrently parenting differed significantly from teenage pregnant college women who were parenting and educating themselves simultaneously. Specifically, the non-parenting teenage pregnant women were more depressed, hostile, and hopeless. They also utilized more maladaptive coping strategies than never pregnant or teenage pregnant and parenting college women. There are numerous possible explanations for these findings. One possibility is that raising a baby, even when it is conceived during adolescence, may be protective for college women. Another possibility is that pre-existing characteristics are associated both with a teenage pregnancy that doesn’t lead to parenting and with increased symptoms of mental distress and increased use of maladaptive coping strategies during college. Unfortunately, the cross-sectional nature of these findings precludes a determination of when and how these relationships might have developed. Another limitation of the current study is that the survey we utilized did not directly assess the outcome of the teenage pregnancy (i.e., keeping the baby, abortion, miscarriage, adoption); making it impossible to consider whether particular choices were more or less associated with particular outcomes during college. It is possible, however, that the increased mental health symptoms expressed by this subgroup of pregnant women are differentially associated with choices made by the woman with regards to her adolescent pregnancy. Future research will be needed to determine this directly. Finally, in a series of exploratory analyses, the mental health variables were used to create two clusters of women who had experienced a teenage pregnancy. Results garnered from cluster analysis indicated that 72.5% of the teenage pregnant college women could be considered to be “thriving” as they reported fewer symptoms of depression, and low hostility and hopelessness. In contrast, 27.5% of the teenage pregnant women could be considered “atrisk” because of their elevated reports of depressive symptoms, and higher levels of hopelessness and hostility. While there were a significantly higher proportion of nonparenting teenage pregnant women in the “at-risk” group than in the “thriving” group; there was not complete agreement between these two constructs. These findings suggest that a significant subgroup of college women who have experienced a teenage pregnancy may require additional services to facilitate their educational advancement and retention in the college environment. These women could be identified by mental health screening procedures.

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REFERENCES Adams, G., Adams-Taylor, S., & Pittman, K. (1989). Adolescent pregnancy and parenthood: A review of the problems, solutions, and resources. Family Relations, 38(2), 223-229. Bickart, T. S., & Wolin, S. (1997). Practicing resilience in the elementary classroom. Principal Magazine, November 1997, 1-3. Brier, N. (2004). Anxiety after miscarriage: A review of the empirical literature and implications for clinical practice. Birth, 31 (2), 138-142. Burton, K. B. (2004). Resilience in the face of psychological trauma. Psychiatry, 67(3), 231234. Carle, A. C., & Chassin, L. (2004). Resilience in a community sample of children of alcoholics: Its prevalence and relation to internalizing symptomatology and positive affect. Applied Developmental Psychology, 25, 577-595. Carver, C. S. (1998). Resilience and thriving: Issues, models, and linkages. Journal of Social Issues, 54(2), 245-266. Carver, C. S., & Scheier, M. F. (1989). Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56(2), 267-283. Charney, D. S. (2004). Psychobiological mechanisms of resilience and vulnerability: Implications for successful adaptation to extreme stress. American Journal of Psychiatry, 161(2), 195-216. Clemmens, D. A. (2002). Adolescent mothers’ depression after the birth of their babies: Weathering the storm. Adolescence, 37(147), 551-565. Compas, B. E. (1987). Stress and life events during childhood and adolescence. Clinical Psychology Review, 7, 275-302. Copeland, E. P., & Hess, R. S. (1995). Differences in young adolescents' coping strategies based on gender and ethnicity. Journal of Early Adolescence, 15(2), 203-219. Derogatis, L. R. (1994). Symptom Checklist-90-R: Administration, scoring, and procedures manual. Minneapolis, MN: National Computer Systems, Inc. Fergusson, D. M., & Lynskey, M. T. (1996). Adolescent resiliency to family adversity. Journal of Child Psychology and Psychiatry, 37(3), 281-292. Furstenberg, F. F. Jr. (1991). As the pendulum swings: Teenage childbearing and social concern. Family Relations, 40(2), 127-138. Himelein, M. J., & McElrath, J. V. (1996). Resilient child sexual abuse survivors: Cognitive coping and illusion. Child Abuse and Neglect, 20(8), 747-758. Hudson, D., Elek, S., & Campbell-Grossman, C. (2000). Depression, self-esteem, loneliness, and social support among adolescent mothers participating in the New Parents Project. Adolescence, 35(139), 445-453. Humphreys, J. C. (2001). Turnings and adaptations in resilient daughters of battered women. Journal of Nursing Scholarship, 33(3), 245-251. Kazdin, A. E., French, N. H., Unis, A. S., Esveldt-Dawson, K. & Sherick, R. B. (1983). Hopelessness, depression, and suicidal intent among psychiatrically disturbed children. Journal of Consulting and Clinical Psychology, 51, 504-510. Kivisto, P. (2001). Teenagers, pregnancy, and childbearing in a risk society: How do highrisk teens differ from their age peers? Journal of Family Issues, 22(8), 1044-1065.

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Langhinrichsen-Rohling, J., Arata, C., Bowers, D., O’Brien, N., & Morgan, A. (2004). Suicidal behavior, negative affect, gender, and self-reported delinquency in college students. Suicide and Life-Threatening Behavior, 34 (3), 255-266. Langhinrichsen-Rohling, J., O’Brien, N., Klibert, J., Arata, C., & Bowers, D. (2006). Gender specific associations among suicide proneness and coping strategies in college men and women. College Students: Stress, Depression, and Mental Health (pp. 12.1 – 12.14). Nova Science Publishers, Inc. Lazarus, R. S. (1993). From psychological stress to the emotions: A history of changing outlooks. Annual Review Psychology, 44, 1-21. Leitch, M. L. (1998). Contextual issues in teen pregnancy and parenting: Refining our scope of inquiry. Family Relations, 47(2), 145-148. Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The construct of resilience: A critical evaluation and guidelines for future work. Child Development, 71(3), 543-562. Luthar, S. S., Doernberger, C. H., & Zigler, E. (1993). Resilience is not a unidimensional construct: Insights from a prospective study on inner-city adolescents. Development and Psychopathology, 5, 703-717. Masten, A. S. (1994). Resilience in individual development: Successful adaptation despite risk and adversity. In M. C. Wang & E. W. Gordon (Eds.), Educational resilience in inner- city America: Challenges and prospects (pp. 3-25). Hillsdale, NJ: Erlbaum. Masten, A. S., & Garmezy, N. (1985). Risk, vulnerability, and protective factors in developmental psychopathology. In B. Lahey & A. Kazdin (Eds.), Advances in Clinical Child Psychology (Vol. 8, pp. 1-52). New York: Plenum Press. Milgram, N. A., & Palti, G. (1993). Psychosocial characteristics of resilient children. Journal of Research in Personality, 27, 207-221. Moran, P. B., & Eckenrode, J. (1992). Protective personality characteristics among adolescent victims of maltreatment. Child Abuse and Neglect, 16, 743-754. Neugebaur, R. (2003). Depressive symptoms at two months after miscarriage: Interpreting study findings from an epidemiological versus clinical perspective. Depression and Anxiety, 17, 152-161. Patterson, J.M., & McCubbin, H.I. (1987). Adolescent coping styles and behaviors: Conceptualization and measurement. Journal of Adolescence, 10, 163.186. Polkki, P. Ervast, S., & Huupponen, M. (2004). Coping and resilience of children of a mentally ill parent. Social Work Visions from around the Globe: Citizens, Methods, and Approaches, 39, 151-163. Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385-401. Statham, J. (2004). Effective services to support children in special circumstances. Child: Care, Health & Development, 30(6), 589-598. Tiet, Q. Q., Bird, H. R., Davies, M., Hoven, C., Cohen, P., Jensen, P., & Goodman, S. (1998). Adverse life events and resilience. Journal of the American Journal of Child and Adolescent Psychiatry, 37(11), 1191-1201. Werner, E. E., & Smith, R. S. (Eds.). (1992). Overcoming the odds: High risk children from birth to adulthood. Ithaca, NY: Cornell University Press. Wilcox, D. T., Richards, F., & O’Keeffe, Z. C. (2004). Resilience and risk factors associated with experiencing childhood sexual abuse. Child Abuse Review, 13, 338-352.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 4

SEXUAL BEHAVIORAL DETERMINANTS AND RISK PERCEPTION RELATED TO HIV AMONG COLLEGE STUDENTS Su-I Hou∗ and Joseph M. Wisenbaker** *

Department of Health Promotion Behavior, College of Public Health, The University of Georgia, USA ** Department of Education Psychology and Instructional Technology, The University of Georgia, USA

ABSTRACT Young adults such as college students are known to engage in frequent and unprotected sexual activities, the primary route for HIV transmission, yet their risk perception towards HIV infections have been low. This study aimed to examine the extent to which HIV risk perception among college students may be explained by behavioral factors (number of partners and condom use by type of sexual activity, and partner’s risk) and selected background variables (sexually transmitted infections history, sexual orientation, age, and gender). A web-survey was administered in a major university in the Southeastern U.S. (N=440). Study information with survey website address and login password were disseminated through flyers, colored mini-handouts, classroom announcements, student newspaper advertisements, and several e-mail listserv student organizations. Informed consent was obtained as part of the login process. The innovation of the study is to assess a comprehensive array of sexual behaviors and their relationships on risk perceptions via the Internet. Bivariate analyses were used to first examine the relationships between individual behavioral or background variables and students’ perceived HIV risk. Multiple logistic regressions were then performed to investigate how well the various behavioral determinants and background variables ∗

Requests for reprints should be addressed to: Su-I Hou, DrPH, RN, CHES; Department of Health Promotion and Behavior, College of Public Health, The University of Georgia, 309 Ramsey Center, 300 River Road, Athens, GA 30602. Phone: 706-542-8206; Fax: 706-542-4956. Email: [email protected]

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Su-I Hou and Joseph M. Wisenbaker together distinguished between students with higher or lower perceived risk of HIV infection. Data showed that, after considering all the variables together, number of partners for oral (OR=1.293), vaginal (OR=1.255), and anal (OR=1.846) sex were the three variables which revealed significant predictions to perceived risk. Results support the use of the Intent in obtaining sensitive behavioral information and suggest that public health messages addressing multiple partners in conjunction with type of sexual activity can be important in influencing HIV risk perception among college students.

Keywords: HIV, perceived risk, behavioral determinants, web-based survey, college students.

INTRODUCTION College students in the U.S. are known to engage in frequent and unprotected sexual activities, the primary route for HIV and other STI transmission (CDC, 2002). Results from a national survey conducted among college students in the U.S. showed that about 80% of college students (aged 18-24 years) reported having had sexual intercourse. About one in four reported six or more lifetime sex partners, while the condom use rate was low (CDC, 1997). The overall perception of HIV risk among college students was, however, very low despite the prevalence of risky behaviors for HIV infection. Brown (1998) assessed college students’ AIDS risk perception and found that some students reporting high-risk behaviors perceived their AIDS risk as “nil” or “small”. In a review of empirical studies dealing with the psychosocial correlates of HIV risk among heterosexual college students, studies found that students who engaged in the most risky behaviors, such as non-exclusive (Baldwin and Baldwin, 1988) or unprotected sex (Mahoney, Thombs, and Ford, 1995), accurately perceived themselves to be at highest HIV risk. Higher risk perception has been shown to be critical in influencing intentions towards HIV risk reduction behaviors in some studies. Such behaviors include seeking HIV testing (Hou and Wisenbaker, 2005; Irwin, Valdiserri, and Holmber, 1996; Memon, 1990), using condoms (Goodman and Cohall, 1989; Freimuth, Hammond, Edgar, McDonald, Pink, 1992), and remaining abstinent (Goodman and Cohall, 1989; MacDonald, et al., 1990). Nevertheless, studies among college students are consistent with research findings in other populations demonstrating an inconsistent relationship between perceived vulnerability for contracting HIV/AIDS and risk reduction behaviors (Roberts and Kennedy 2006; Yep, 1993; Gray and Saracino, 1989). Existing reviews support the hypothesis that current and recent behaviors, both risky and precautionary behaviors with regard to HIV, influence how one estimates his/her own vulnerability (perceived risk) towards HIV infection. Further investigations on how one reflects his/her own vulnerability towards HIV infection based on current or recent sexual behaviors have been suggested due to the moderating effects found (Gerrard, Gibbons, and Bushman, 1996). Weinhardt examined HIV risk sensitization following a detailed sexual behavior interview among a small sample of college students (Weinhardt, Carey, and Carey, 2000). Sexually active students, those with multiple partners, or who engaged in penile/vaginal sex, were more likely to experience HIV risk sensitization during the

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interview, compared to sexually inactive, single partner, or those who had only engaged in oral sex. Their findings indicated that detailed sexual behavior assessments influenced students’ motivation to reduce their risky behaviors. The purpose of our study was to look at the extent to which HIV risk perception among college students may be explained by behavioral factors (number of partners by type of sexual activity, partner types, condom use by type of sexual activity), and background variables (sexually transmitted infections history, sexual orientation, age, and gender). Since risk perception may motivate some behavioral changes but not others, a combination of various sexual behaviors were measured in this study to capture the complex relationships. Previous studies have suggested that indexes with combined multiple measures of risk and precautionary behaviors are the best predictors of perceived risk (Gerrad, et al, 1996). This study is among the first utilizing a web-based survey to assess detailed and specific sexual behaviors and examine their relationships to HIV risk perception among college students. Understanding these relationships may play a critical role in developing effective HIV prevention and education programs.

METHODS A web-based survey was offered during spring 2003 in one major university in the Southeastern U.S. A total of 440 students participated. The survey website address and a login password were announced through various channels. These included: (1) using an email listserv of student organizations to send out the recruiting message; (2) publishing a weeklong survey recruiting announcement in the student newspaper, and (3) posting flyers at several high traffic locations around the campus. Both the email listserv and student newspaper were the most common communication channels at the participating university. Colorful mini-flyers were also handed out around noon during the recruitment period at the student activity center where a large number of students gather for lunch and other activities. The password was used to ensure that respondents who participated in the survey were reached through the various recruitment efforts, thus eliminating the possibility that someone would accidentally encounter the web site on the Internet and access the survey. Further details on the recruitment process and strategies are documented elsewhere (Hou, 2004). This research was conducted with the approval of the Institutional Review Board for the Protection of Human Subjects at the University (No. H2003-10245).

Participants The majority of people participating in the web-survey were young, white heterosexual students (total N=440). The study sample was comparable to the overall university student profile in terms of age distribution and proportion of ethnic racial membership. Mean age of the sample was 21 years (SD=2.48; age range between 18-24 years), over 80% identified themselves as white, and 88% identified as heterosexual. Females were disproportionately represented in the sample (75% vs. 58% at this university). About 9% of the participating students reported that they have had sexually transmitted infections (STIs).

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Measures Behavioral determinants used in this study included lifetime partner numbers by the three types of sexual activity (oral, vaginal, and anal sex), risk of partner (i.e. someone who uses injectable drugs, someone who has sex with multiple partners, and someone is paid for sex), as well as condom use by type of sexual activity. The exact survey questions are described below.

Perceived Risk of HIV Infection A three-item five point Likert scale was used to measure perceived risk of HIV infection. The three perceived risk questions asked were: (1) “I am not at risk for an HIV” (reverse coded); (2) “It is likely that I might be infected with HIV in my lifetime”; and (3) “Compared with other people my age, my chance of getting HIV is higher”. Higher scores indicated higher perceived risk to HIV infection. These items were adapted from previous studies (Stein and Nyamathi, 2000; Aspinwall, et al., 1991) and revised with input from focus groups conducted during the development of the web survey. The Cronbach’s alpha coefficient showed these items to have moderate internal consistency (α=0.67). After examining the distribution of perceived risk, we found the majority of the student perceived low or very low risk of HIV infection. The perceived risk scale was not normally distributed; therefore it was recoded into a dichotomous variable. Students were classified into two groups based on their risk perception (low versus high), using the scale mean as the cut-off point (scale mean =6.40). About 44% students were placed into the higher perceived risk group. Number of Partners by Type of Sexual Activity Separate questions on oral, vaginal, and anal sex were asked about number of people students have had sex with during their lifetime. Response categories were zero, one, two, three, and more than three. Partner’s Risk Three questions were asked about partner’s risk. Participants were asked “Have you ever had sex (oral, vaginal, or anal) with someone who (1) has ever used injectable drugs, (2) has more than one sex partners, and (3) was paid for sex; with response categories of “yes”, “no”, or “don’t know”. Since less than 3% of the students reported having sex with someone who use injetable drugs or was paid for sex, it made sense to analyze only whether participants had had sex with someone who had more than one partner. About 56.1% of the participants indicated their partners had had sex with someone else. Condom Use by Type of Sexual Activity Similarly, condom use behaviors were assessed separately for oral, vaginal, and anal sex. Participants were asked “How often do you or your partner use a condom when you have (1) oral, (2) vaginal, or (3) anal sex”. A five point scale was used to measure condom use frequencies, from “never” (coded as one) to “(almost) always” (coded as five).

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Background Variables Previous reviews suggest that characteristics of the participants could moderate the relation between HIV preventive behavior and risk perception (Gerrad, et al, 1996). Therefore, in addition to the various HIV risk behaviors, the analysis also included several background variables, such as age, gender, sexual orientation, and sexually transmitted infections (STIs) history. Sexual orientation was grouped into two categories: heterosexual and others or GLBTQ (i.e. gay/lesbian, bi-sexual, trans-gendered, or questioning / not sure); as the numbers in GLBTQ groups were small. It should be noted, however, that they are different groups and these different orientations have different types and levels of risk. STIs history was coded as a dichotomous variable (yes or no). Data collected were screened to identify missing data and outliers. Residual analysis was conducted to evaluate the fulfillment of the test assumptions. A preliminary multiple regression analysis showed that tolerance for all predicting variables was greater than .10, indicating that multicollinearity was not a major issue. Bivariate analyses were used to first examine each individual behavioral or background variable and its relationship with students’ perceived HIV risk. Multiple logistic regressions were then performed to investigate how well the various behavioral determinants together distinguished between students with higher or lower perceived risk of HIV infection. The various behavioral determinants, along with background characteristic variables, were entered simultaneously in the multiple regression analyses.

RESULTS Data showed that participating college students engaged in the various kinds of sexual activities frequently. Nearly 80% of the students had oral sex experience, two thirds had engaged in penile/vaginal sex, and about one fourth had engaged in anal sex. Number of lifetime sexual partners was highest for oral sex, then vaginal sex, followed by anal sex (Table 1). Condom use frequencies, assessed only among sexually experienced students, also varied depending on the type of sexual activity involved. Among students who had engaged in oral sex, less than 4% reported using a condom “often or always” during oral sex. Nearly half of those who had engaged in penile/vaginal sex did not always (or often) use condoms. Among students who had reported engaging in anal sex, about 64% did not often or always use condoms (Table 1). Bivariate analyses of each individual behavioral determinant showed that number of partners for oral, vaginal, and anal sex, as well as having had sex with someone who had more than one partner, were all individually significantly associated with perceived risk of HIV. Condom use variables, regardless the type of sexual activity involved, however, did not reveal any significant relationship. Except gender, all of the background variables, including age, sexual orientations, and history of STIs, showed positive individual relationships with perceived risk of HIV infection. Preliminary regression models with all of the predictors entered simultaneously revealed similar results. The three condom use variables, after

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adjusting for all other behavioral and demographic variables, still showed no predictive advantages. Therefore, the full model was analyzed without the condom use variables. Table 1. Number of partners and condom use frequencies among students participating in the web-survey Number of Partners a (Num_Partner) Zero One Two Three More than three Total c Condom Use b (CU) Never Seldom Sometimes Often (almost) Always Total c

N

Oral Sex %

N

Vaginal Sex %

N

Anal Sex %

71 83 60 52 144

17.3% 20.2% 14.6% 12.7% 35.1%

143 84 51 30 102

34.9% 20.5% 12.4% 7.3% 24.9%

317 64 20 7 6

76.6% 15.5% 4.8% 1.7% 1.4%

410

100.0%

410

100.0%

414

100.0%

N 291 18 3 2 9 323

Oral Sex % 90.1% 5.6% 0.9% 0.6% 2.8% 100.0%

Vaginal Sex N % 47 17.9% 42 16.0% 32 12.2% 32 12.2% 109 41.6%

N 39 14 4 5 27

262

89

100.0%

Anal Sex % 43.8% 15.7% 4.5% 5.6% 30.3% 100.0%

Notes: a Number of partners was assessed among all students. b Condom use was assessed only among sexually experienced students. c Students who did not respond to the selected variables were not included. Therefore, the total of students represented in each variable varied accordingly.

Results from using the full model (n=366) with the remaining predictors, including four behavioral and four background variables revealed adequate fit (-2 Log Likelihood=418.321; Hosmer-Lemeshow Goodness-of-Fit p>.05) with model classification rate of 71.6% (see Table 2). Three variables, number of oral sex partners (OR=1.293), number of vaginal sex partners (OR=1.255), and number of anal sex partners (OR=1.846), revealed significant predictions of perceived risk of HIV infection. Other variables, such as having had sex with someone who had more than one partner, age, gender, sexual orientation, or having had STI, did not reveal significant coefficients (Table 2). Analysis of a reduced model which included only the three variables as predictors also revealed adequate fit (-2 Log Likelihood=467.880; Hosmer-Lemeshow Goodness-of-Fit p>.05) with similar model classification rate (70.0%). All of the three variables in the reduced model, number of oral sex partners (OR=1.378), number of vaginal sex partners (OR=1.292), and number of anal sex partners (OR=1.820), still revealed significant predictions to perceived risk of HIV infection (Table 3).

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Table 2. (Full model) Coefficients for multiple logistic regression model variables (n=366)

Num_Partner (Oral sex) Num_Partner (Vaginal sex) Num_Partner (Anal sex) Partner Type

B

S.E.

Wald

df

p-value

Odds Ratio (OR)

95.0% C.I. for OR Lower Upper

.257

.110

5.438

1

.020

1.293

1.042

1.605

.227

.102

4.954

1

.026

1.255

1.027

1.532

.613

.211

8.433

1

.004

1.846

1.220

2.791

.308

.303

1.033

1

.309

1.361

.751

2.464

STI History

.225

.423

.282

1

.595

1.252

.546

2.869

Sex_Orient

.405

.440

.849

1

.357

1.500

.633

3.552

Age

-.030

.054

.295

1

.587

.971

.873

1.080

Gender

-.199 -1.728

.281

.502

1

.479

.819

.472

1.422

1.381

1.566

1

.211

.178

Constant

Notes:-2 Log Likelihood=418.321; Hosmer-Lemeshow Goodness-of-Fit p>.05; X2 (8) =79.832, p<.001.

Table 3. (Reduced model) Coefficients for multiple logistic regression model variables (n=404)

Num_Partner (Oral sex) Num_Partner (Vaginal sex) Num_Partner (Anal sex) Constant

B

S.E.

Wald

df

p-value

Odds Ratio (OR)

95.0% C.I. for OR Lower Upper

.320

.097

11.014

1

.001

1.378

1.140

1.665

.256

.087

8.675

1

.003

1.292

1.089

1.531

.599

.181

10.897

1

.001

1.820

1.275

2.598

-1.636

.221

54.834

1

.000

.195

Notes: -2 Log Likelihood=467.880; Hosmer-Lemeshow Goodness-of-Fit p>.05; X2 (3) =86.934, p<.001.

DISCUSSION Despite having engaged in various high risky sexual activities, these students perceived low personal HIV risk levels. This finding is consistent with existing evidence that perceptions of HIV risk are not necessarily consistent with college students’ self-reported sexual behaviors (Brown, 1998). The level of sexual activity reported through the present web-based survey was also consistent with those published from the CDC, (1997). Results in the current study showed that, after adjusting all the background variables (STI history, sexual orientation, age, and gender), the numbers of partner by the three types of sexual activity were significant predictors of HIV risk perception. On the other hand, condom use, regardless of the type of sexual activity, did not reveal any significant relationship.

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Although multiple lifetime partners has been found in previous research to be a significant predictor for higher perceived risk for HIV infection among women seeking HIV testing (Stringer, et al, 2004) as well as sexual contact with drug users (Leukefeld, et al, 2001), previous studies did not break down partner number by different types of sexual activity. In our study, students who reported having oral, penile/vaginal, or anal sex with more partners perceived a higher risk of HIV infection. Among these, current results showed that the number of anal sex partners was the strongest predictor of perceived HIV risk (OR=1.8). It was interesting to note that condom use (or lack of it) was not found to be a significant predictor of students’ perceived risk, either in the bivariate analyses or multiple regressions. Data showed that students’ unprotected sexual behaviors were not associated with an increase in their perceived risk of HIV. Previous studies have also revealed no consistent patterns between perceived HIV risk and protective sexual behavior (Roberts and Kennedy, 2006; Yep, 1993; Freimuth, et al., 1992; MacDonald, et al; 1990). In addition, our data also indicated that after adjusting all the potential confounding variables, condom use still did not reveal any significant prediction to perceived risk. One possible explanation of the nonsignificant relationship could be the lack of variation. In other words, because the overall risk perception was low, the dichotomous split of high versus low risk was a separation of a sample with low risk perception. However, on the other hand, it was also possible that there could be no association between lack of condom use with higher risk perception because people perceived themselves to be having sex without a condom with a partner they “felt” they knew enough about or with whom they had been tested for HIV. One of our concerns involved the possibility of needing interaction terms related to the number of partners and condom use in our analysis. One could argue that the number of partners someone is involved with could influence condom use frequencies (Bazargan, Kelly, Stein, Husaini, and Bazargan, 2000), and this potential interaction might have some impact on students’ risk perception. Students who use condoms more often could more likely be those who practice riskier behaviors, yet feel less susceptible to HIV due to the use of protection. On the other hand, some young people may find certain behaviors attractive BECAUSE they see them as risky (just the opposite of what someone with a public health perspective might be thinking). For those people, not using condoms may be more arousing due to the added elements of risk OR because using condoms implies prior planning and intent, or being perceived as a symbol of infidelity, and they give themselves permission to do certain things only if they can pretend that these things sort of just happened (Bowleg, Lucas, and Tschann, 2004). However, a detailed examination of perceived risk examining those relevant subgroups suggested no need for more complex interaction effects in the model. No significant interactions on perceived risk between number of partners and condom use were found (data not shown). In other words, there were no consistent patterns of student’s risk perceptions towards the number of partners they had in various sexual activities and their associated condom use frequencies. Lack of evidence of significant interactions insured that the main effects of each factor examined could be more reliably interpreted (Mertler and Vannatta, 2002). One limitation of the current study was its cross-sectional design. One could argue that instead of viewing perceived risk as reflective of risk of precautionary sexual behaviors (e.g. avoidance of risky behavior or initiation of precautionary behavior); it was also possible that perceived risk influences subsequent precautionary behavior. Although most theories of

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health behaviors assume that precautionary behavior is related to perceived risk, the applicability of this assumption to HIV preventive behavior has recently been called into question (Gerrard, et al., 1996). Gerrard and colleagues reviewed the few existing prospective studies (Aspinwall et al, 1991; Joseph, et al, 1987, Boyd and Wandersman, 1991, van der Velde, et al, 1992) and commented that no support was found for the hypothesis that perceived vulnerability motivates subsequent precautionary sexual behavior. On the other hand, based upon the 26 cross-sectional studies reviewed, Gerrard et al pointed to the conclusion that estimates of vulnerability to HIV infection are, in fact, reflective of risk and precautionary sexual behaviors. Our results showed that number of partners in conjunction with the various types of sexual activity may be important in predicting students’ perceived risk of HIV infection. Therefore, public health messages addressing multiple partner issues (especially in anal sexual activities) could be important to increasing risk perception. Although partner’s risk and background characteristics, such as STIs history, nonheterosexual orientation, and increased age, individually showed significant prediction to HIV risk perception, they did not uniquely add to the ability to predict students in higher versus lower risk perception groups once all other variables were taken into consideration. Only behaviors involving multiple partners in oral, vaginal, and anal sexual activities showed significant predictions in our models. Current results showed that the correct classification was similar when using the eightfactor full model (71.6%) versus the three-factor model (70.0%). Risky sexual behaviors clearly provide some explanatory power on risk perception, even though they do not account for all the variance. Additional factors related to risk perception need to be investigated in order to provide more information on how to better educate and influence the public. This study suggests that increasing perceptions of what constitute personal risk behaviors may need special emphasis when prevention programs are delivered. In summary, the current study provides information on incremental risk perceptions of HIV infection with reputed HIV risky behaviors. There is a great need for preventive interventions for late adolescents and young adults, such as college populations (Lewis, et al., 1997). The significance of multiple partners in conjunction with the various sexual activities sheds light on potentially effective intervention messages which might help increase risk perception for this population. Better educational programs focusing on the benefits of condom use in reducing actual HIV risk seem justified. The degree to which HIV risk estimates are based on sexual behaviors is worthy of further investigation among different groups. Such knowledge will provide useful information regarding the correlates of risk estimates and may suggest additional strategies for public health efforts.

REFERENCES Aspinwall, L.G., Kemeny, M. E., Taylor, S.E., Schneider, S.G., and Dudley, J.P. (1991). Psychosocial predictors of gay men’s AIDS risk-reduction behavior. Healthy Psychology, 10, 432-444. Baldwin, J.D., and Baldwin, J.I. (1988). Factors affecting AIDS-related sexual risk-taking behavior among college students. Journal of Sex Research, 25, 181-196.

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Bazargan, M., Kelly, E.M., Stein, J.A., Husaini, B.A., and Bazargan, S.H. (2000). Correlates of HIV risk-taking behaviors among African-American college students: The effect of HIV knowledge, motivation and behavioral skills. Journal of the National Medical Association, 92, 391-404. Boyd, B., and Wandersman, A. (1991). Predicting undergraduate condom use with the Fishbein and Ajzen and the Triandis attitude behavior models: Implications for public health intervention. Journal of Applied Social Psychology, 21, 1810-1830. Bowleg, L., Lucas, K. J., and Tschann, J. M. (2004). "The ball was always in his court": An exploratory analysis of relationship scripts, sexual scripts, and condom use among African American women. Psychology of Women Quarterly, 28, 70-82. Brown, E. J. (1998). College students' AIDS risk perception. Journal of Psychosocial Nursing Mental Health Services, 36(9), 25-30. Center for Disease Control and Prevention. (1997). Youth Risk Behavior Surveillance: National College Health Risk Behavior Survey -- United States, 1995. MMWR, 46 (SS6), 1-54. Center for Disease Control and Prevention. (2002). YRBSS 2001 information and results: Youth 2001 online. Retrieved from World Wide Web on Aug. 24, 2002. http://www.cdc.gov/nccdphp/dash/yrbs/youth01online.htm Freimuth VS, Hammond SL, Edgar T, McDonald DA, and Pink EL. (1992). Factors explaining intent, discussion and use of condoms in first-time sexual encounters. Health Education Research, 7, 203-215. Gerrard, M., Gibbons, F. X., and Bushman, B. J. (1996). Relation between perceived vulnerability to HIV and precautionary sexual behavior. Psychology Bullet, 119(3), 390409. Goodman, E., and Cohall, A.T. (1989). Acquired Immunodeficiency Syndrome and adolescents: Knowledge, attitudes, beliefs, and behaviors in a New York City adolescent minority population. Pediatrics, 84 (1), 36-42. Gray LA, and Saracino M. (1989). AIDS on campus: A preliminary study of students' knowledge and behaviors. Journal of Counseling and Development, 68, 199-202. Hou, S. (2004). Objective and subjective knowledge and HIV testing among college students. American Journal of Health Education, 35 (6), 328-335. Hou, S. and Wisenbaker, J. (2005). Using a web survey to assess correlates of intention towards HIV testing among never-been-tested but sexually experienced college students. AIDS Care, 17(3), 329-334. Irwin, K.L., Valdiserri, R.O., and Holmberg, S.D. (1996). The acceptability of voluntary HIV antibody testing in the United States: a decade of lessons learned. AIDS, 10, 1707-1717. Joseph, J.G., Montgomery, S.B., Emmons, C., Kirscht, J.P., Kessler, R.C., Ostrow, D.G., Wortman, C.B., and O’Brien, K. (1987). Perceived risk of AIDS: Assessing the behavioral and psychological consequences in a cohort of gay men. Journal of Applied social Psychology, 17, 231-250. Leukefeld, C.G., Farabee, D., McDermeitt, M., Dennis, M., Wechsberg, W., Inciardi, J.A., et al., (2001). Real and perceived HIV risk by county population density: An exploratory examination. Journal of Drug Issues, 31 (4), 889-900. Lewis, J. E., Malow, R. M., and Ireland, S. J. (1997). HIV/AIDS risk in heterosexual college students. A review of a decade of literature. J. of American College Health, 45(4), 147158.

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MacDonald, N.E., Wells, G.A., Fisher, W.A., Warren, W.K., King, M.A., Doherty, J.A., and Bowie, W.R. (1990). High-risk STD/HIV behavior among college students. JAMA, 263 (23), 3155-3159. Mahoney, C.A., Thombs, D.L., and Ford, O.L. (1995). Health belief and self-efficacy models: Their utility in explaining college student condom use. AIDS Education and Prevention, 7, 32-49. Memon, A. (1990). Young people’s knowledge, beliefs, and attitudes about HIV/AIDS: a review of research. Health Education Research: Theory and Practice, 5 (3), 327-335. Mertler, C.A., and Vannatta, R.A. (2002). Advanced and multivariate statistical methods (2nd Ed.). Los Angeles, CA: Pyrczak Publishing. Roberts, S.T., and Kennedy, B.L. (2006). Why are young college women not using condoms? Their perceived risk, drug use, and developmental vulnerability may provide important clues to sexual risk. Archives of Psychiatric Nursing, 20(1), 32-40. Stein, J.A., and Nyamathi, A. (2000). Gender differences in behavioral and psychosocial predictors of HIV testing and return for test results in a high-risk population. AIDS Care, 12(3), 343-356. Stringer, E.M., Sinkala, M., Kumwenda, R., Chapman, V., Mwale, A., Vermund, S.H., Goldenberg, R.L., and Stringer, J.S. (2004). Personal risk perception, HIV knowledge and risk avoidance behavior, and their relationships to actual HIV serostatus in an urban African obstetric population. Journal of Acquired Immune Deficiency Syndromes, 35 (1), 60-66. Van der Velde, F.W., Hooykaas, C., and van der Pligt, J. (1992). Risk perception and behavior: Pessimism, realism, and optimism about AIDS-related health behavior. Psychology and Health, 6, 23-28. Weinhardt, L. S., Carey, K. B., and Carey, M. P. (2000). HIV risk sensitization following a detailed sexual behavior interview: a preliminary investigation. Journal of Behavior Medicine, 23(4), 393-398. Yep GA. (1993). HIV prevention among Asian-American college students: Does the health belief model work? Journal of American College Health, 41, 199-205.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 5

THE IMPACT OF A LECTURE SERIES ON ALCOHOL AND TOBACCO USE IN PHARMACY STUDENTS Arjun P. Dutta,∗ Bisrat Hailemeskel,† Monika N. Daftary,‡ and Anthony Wutoh§ Howard University, College of Pharmacy, Nursing and Allied Health Sciences, School of Pharmacy, Washington, DC USA

ABSTRACT Studies related to alcohol and drug use in healthcare students, namely nursing, pharmacy, and medicine suggest that drug and alcohol abuse continues to be a growing problem among health profession students. A review of the more recent literature involving pharmacy students, has noted higher levels of alcohol and drug use when compared to the undergraduate student population. Interestingly, the use and/or abuse of tobacco have largely been overlooked in studies involving substance abuse in pharmacy students. This study documented the current alcohol and tobacco use in pharmacy students and conducted a lecture series on the use and abuse of alcohol and tobacco. The lecture series was successful in increasing the awareness of the use and potential abuse of alcohol in the students. Attitudinal changes in students following the lecture series were also assessed.

Key Words: health professions students, abuse, alcohol use, tobacco use

∗

† ‡ §

Office: 503-352-7281; Fax: 202-806-4478; Email: [email protected]; The author is currently the Assistant Dean for Academic Affairs at Pacific University, School of Pharamcy, Forest Grove, OR. Office: 202-806-4210; Email: [email protected] Office: 202-806-4206; Email: [email protected] Office: 202-806-4209; Email: [email protected]

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INTRODUCTION Studies related to alcohol and drug use in healthcare students, namely nursing, pharmacy, and medicine suggest that drug and alcohol abuse continues to be a growing problem among health care professional students [1-11]. A study conducted by Coleman and colleagues found that about ten percent of practicing nurses were chemically dependent, and for many of these nurses the abuse began during nursing school [12]. Some of these studies not only examined trends in use, but have also identified precursors of alcohol abuse that are unique to students in health professions. Causal factors that have been identified include burnout, role strain, peer pressure, socializing, self-medication, and a history of parental alcoholism or drug addiction [11,13-16]. Previous studies (prior to 1990) regarding alcohol and drug abuse in health professions students reported that the level of alcohol and drug use in pharmacy students was similar to the general college population [5-8, 11]. A review of the more recent literature (post 1990) involving pharmacy students, has however noted higher levels of alcohol and drug use when compared to the undergraduate student population [11, 17-19]. Interestingly, the use and/or abuse of tobacco have largely been overlooked in studies involving substance abuse in pharmacy students. Given the increasing nature of this problem, recent studies have examined the impact of educational intervention programs in the health profession student. One such study assessed substance abuse in health profession students and the efficacy of educational interventions in this group. The investigators found that focusing on drug and alcohol education can influence use [12]. The impact of substance abuse (alcohol/drugs/tobacco) educational programs in pharmacy students has also been documented. [20,21] This is particularly important in light of the fact that healthcare training institutions have recently been among those affected by the Drug Free Schools and Communities Act of 1989. This Act mandates that institutions of higher education that receive federal funds establish drug prevention programs. The US Department of Education's Fund for the Improvement of Post-Secondary Education (FIPSE) annually awards grants to college-level drug prevention programs. Colleges and universities have developed prevention programs that have contributed greatly to the existing knowledge about the impact of educational programs on prevention of substance abuse. Although the vast majority of this existing knowledge has been applicable to undergraduate students, not much has been reported in terms of educational programs or its effect on pharmacy students [11]. In this study we have reported the alcohol and tobacco use patterns in pharmacy students and the impact of a lecture series (3 classes of 1.5 hours each in duration) in changing pharmacy students’ attitudes towards the use of alcohol and tobacco. The lecture series was designed to disseminate information on the use and abuse of alcohol and tobacco, the pharmacological action of such substance use, the consequences of alcohol and tobacco use, the related side effects, and results of long-term use.

METHODS The survey population consisted of first year (P-1) professional students (N = 81) at Howard University, School of Pharmacy. We compiled a 20-item survey by an iterative process with input from faculty and the Howard University Student Counseling Center. The

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survey was pilot-tested by faculty members and students and was approved by the university's Institutional Review Board for the Protection of Human Subjects. The final study sample consisted of 67 students (83% response rate). All students completed an IRB-approved informed consent form prior to completing the survey, and were told that their participation was voluntary and that the survey responses would be kept anonymous. The survey was administered to pharmacy students at our institution prior to the initiation of the lecture series to document the pattern of alcohol and tobacco use. The students were then re-administered a post survey at the conclusion of the lecture series to assess changes in student attitudes regarding alcohol and tobacco use.

RESULTS Of those surveyed, 67 students responded to the pre-survey, with an overall response rate of 83%. Of those who responded, students were predominantly female (61%), and largely in the 21-26 age group (61%). Most of the students ascribed to the Christian faith (30%) and were predominantly of African origin (70%). Table 1 provides data on the number of participants, gender, race, and their religious belief or practice. Regarding the survey, thirtynine percent of the respondents reported the use of alcohol at least once during the previous month. Among them, 7% reported using alcohol 10 times or more during the past month. Another 26% reported on having used alcohol at least once during the previous year. Thirtyfive percent students however, said that they had never consumed alcohol in their life. In terms of the quantity of alcohol consumed at one sitting, 59% reported having at least two drinks but not more than four. Binge drinking or drinking more than four drinks at one sitting was reported by five percent of the respondents. There was a significant difference (p<0.004) in gender in relation to the number of times a respondent drank, with males reported drinking more frequently than females. Moreover, binge drinking was more common among males than females. There was also a positive correlation (p<0.02) between socializing with friends and frequency of alcohol use. The longer a respondent spent in terms of socializing with friends the more he/she drank. However, females drank less than males even if they socialized for the same length of time. Such findings are ironic given that 69% of the students believed alcohol consumption to be dangerous to their health. Furthermore, students agreed that peer pressure would often force them to drink more than they intended, as a majority of students felt that participating in parties was important to them socially. The results of this survey seem to be consistence with previous findings in the literature [11, 16-18]. Interestingly, religious belief was correlated to alcohol use as well. Students, who felt that adhering to their religious beliefs and customs was important, drank less often or in fewer quantity than those for whom the practice of one’s religion was not as important. This is important in light of the fact that certain religions (e.g. Muslim religion) specifically prohibit the consumption of alcohol. In terms of using tobacco, only 8% students reported smoking during the past month. Among the respondents who smoked (8%), the rate of smoking ranged from 10 cigarettes to about two packs for the entire month. An overwhelming 88% of the students felt that using tobacco was dangerous to their health. This belief seems consistent with the pattern of tobacco use in health profession students. Interestingly, the belief that alcohol is dangerous (69%) was however, not consistent with usage pattern of alcohol (65%). This may be because

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students drink despite knowing that alcohol may be deleterious to their health in an effort to blend in with their peers. It is also possible that these students do not consider alcohol use to be as detrimental as smoking. Table 1. Summary of Respondents (Please add numbers) Category Age 18-20 21-26 27-35 >35 Gender Males Females Race African-American** Asian Caucasian Faith Christian Muslim Other

N*= 67 (%) 7 (11) 39 (61) 15 (23) 3 (5) 26 (39) 41 (61) 47 (70) 15 (22) 5 (1) 20 (30) 11 (15) 36 (55)

* The N for each category/ subcategory represents the number of respondents for that particular category. The total number of responses was 67. ** Includes immigrant students from Africa as well

The post-survey following the lecture series inquired about potential changes student’s attitudes towards drinking and tobacco use in the future. A total of 67 students responded to the post survey as well. The results of the post-survey indicated an increased awareness of the use and potential abuse of alcohol. In general, respondents (58%) indicated that they would like to reduce alcohol consumption in parties and social gatherings. Moreover, a majority of students (81%) felt that binge drinking should be avoided and that peer pressure should not compel them to drink more. A significantly higher percentage (95%) of students (p<0.004) felt that alcohol consumption was detrimental to them following the lecture series as compared to the previous 69%. Students’ attitude towards the use of tobacco was not significantly different following the post-survey. This is probably because there were a very small percentage (8%) of students using tobacco in the first place. Following the lecture series however, only two percent of students indicated that they would probably continue smoking. Thus, the lecture series was at least successful in promoting an awareness of the risks of alcohol and tobacco use together with instilling a desire in the students to reduce their consumption rates. Although, the post-survey indicated an attitude change towards the use and misuse of alcohol and tobacco products, it is of paramount importance to continue such educational programs throughout the length of the Doctor of Pharmacy curriculum. A constant reminder

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about the potential dangers of such substance abuse will definitely help students to perform better in pharmacy school.

IMPLICATIONS FOR BEHAVIORAL HEALTH SERVICES Pharmacists are an integral part of health services delivery and research. Given the proximity and frequency of contact with patients, pharmacists are in a unique position to influence and impact health policy and services delivery as well as research. In this study, the authors have reported the alcohol and tobacco use patterns in pharmacy students at their home institution and the impact of a lecture series (3 classes of 1.5 hours each in duration) in changing pharmacy students' attitudes towards the use/abuse of alcohol and tobacco. The lecture series was also designed to disseminate information on the use and abuse of alcohol and tobacco, the pharmacological action of such substance use, consequences of alcohol use, related side effects, and results of long-term use. We, the authors believe that an educational program such as the one mentioned above, is important for future pharmacists/ pharmacy residents as they will go on to provide health services to patients. In terms of the journal itself, we feel that our submitted manuscript addresses questions raised in the literature about the lack of mention of alcohol and tobacco use in studies involving substance abuse by pharmacy students. This study assesses alcohol and tobacco use in pharmacy students and also reports potential change in attitude of such use in the study population. This endeavor, in the authors' opinion will definitely go a long way in producing better pharmacists capable of handling the growing need for addressing alcohol and tobacco use in particular, and other substances abuse in general.

REFERENCES [1] [2]

[3]

[4] [5]

[6]

Kory WP, Crandall LA. Nonmedical drug use patterns among medical students. International Journal of Addiction. 1984; 19(8): 871-884. Conard S, Hughes P, Baldwin DC, Achenbach KE, Sheehan DV. Substance use by fourth-year students at 13 US medical schools. Journal of Medical Education. 1988; 63:747-758. Borkman T, Rosenberg N. What do we know about medical students' use and abuse of alcohol and other drugs? A constructive critique. Alcohol Health Research World. 1986; 10: 54-59. Haack MR, Harford T. Drinking patterns among student nurses. International Journal of Addiction. 1984; 19(5): 577-583. Miller CJ, Banahan BF. A comparison of alcohol and illicit drug use between pharmacy students and the general college population. American Journal of Pharmaceutical Education. 1990;54:27-30. McAuliffe WE, Santangelo SL, Gingras J, Rohman M, Sobol A, Magnuson E. Use and abuse of controlled substances by pharmacists and pharmacy students. American Journal of Hospital Pharmacy. 1987; 44:311-317.

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[9] [10]

[11]

[12]

[13] [14]

[15] [16] [17] [18]

[19]

[20]

[21]

Arjun P. Dutta, Bisrat Hailemeskel, and Monika N. Daftary et al. Normarck JW, Eckel FM, Pfifferling JH, Cocolas G. Impairment risk in North Carolina pharmacy students. American Pharmacist. 1985; 25:60-62. Tucker DR, Gurnee MC, Sylvestri MF, Baldwin JN, Roche EB. Psychoactive drug use and impairment markers in pharmacy students. American Journal of Pharmaceutical Education. 1988;52:42-47. Haack M. Alcohol use and burnout among student nurses. Nursing and Health. 1987;8(4):239-242. Baldwin DC, Hughes PH, Conard SE, Storr CL, Sheehan DV. Substance use among senior medical students: A survey of 23 medical schools. Journal of the American Pharmaceutical Association. 1986; 255(14): 1913-1920. 11. Kriegler KA, Baldwin JN, Scott DM. A survey of alcohol and other drug use behaviors and risk factors in health profession students. Journal of American College Health. 1994: 42(6): 259-66. Coleman EA, Honeycutt G, Ogden B, McMillan DE et al. Assessing substance abuse among health care students and the efficacy of educational interventions. Journal of Professional Nursing. 1997; 13(1):28-37. Dawson DA, Harford TC, Grant BF. Family history as a predictor of alcohol dependence. Alcohol Clinical Experience Research. 1992; 16(3):572-575. McCaul ME, Turkkan JS, Svikis DS, Bigelow GE, Cromwell CC. Alcohol and drug use by college males as a function of family alcoholism history. Alcohol Clinical Experience Research. 1990; 14(3):467-471. Fillmore KM. Drinking and problem drinking in early adulthood and middle age: An exploratory 20-year follow-up study. Journal of the Study of Alcohol. 1974;35:819-840. Brown SA. Expectancies versus background in the prediction of college drinking patterns. Journal of Consulting Clinical Psychology. 1985;53(l):123-130. Murawski M., Jeurgens, J. Analysis of longitudinal pharmacy student alcohol and other drug use survey data. American Journal of Pharmaceutical Education. 2001:65:20-9. Noormohammed S., Ferguson K., Baghaie A., and Cohen, L. Alcohol drug use, and sexual activity among pharmacy students at three institutions. Journal of the American Pharmaceutical Association. 1998:38(5):609-13. Miller C., Banahan, B., and Borne R. Comparison of illicit drug use between pharmacy students and the general college population. American Journal of Pharmaceutical Education. 1990:54:27-30. McAuley, J., Akers, A., and Mott, D. Assessing the impact of a substance abuse educational program on pharmacy student’s knowledge base. American Journal of Pharmaceutical Education. 1999:63:309-14. Corelli, R., Hudmon, K., Kroon, L. et al., Development of tobacco cessation curriculum for pharmacy students. AACP Annual Meeting, Jul. 2000, vol.101, pg.50. International Pharmaceutical Abstracts, Accession Number: 38-02011

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 6

THE GOULD VERSUS HECKHAUSEN AND SCHULZ DEBATE IN THE LIGHT OF CONTROL PROCESSES AMONG CHINESE STUDENTS Wan-chi Wong1∗, Yin Li2 and Ji-liang Shen3 1

Chinese University of Hong Kong 2 Peking University 3 Beijing Normal University

ABSTRACT In response to the Gould versus Heckhausen and Schulz debate (1999) on the claim to universality of the life-span theory of control, the present study aims to examine the theoretical formulation of Heckhausen and Schulz in the context of contemporary China, with specific reference to the control processes applied by Chinese students in their academic pursuits. A new instrument, the OPS-Scales in the Domain of Academic Achievement (OPSAA), was constructed and examined in the pilot study. The main part of the research program consists of three studies. Study One and Study Two respectively investigated the control processes endorsed by Chinese students in the pre-deadline and post-deadline situations relating to two important public examinations, namely the University Entrance Examination and the Test of English as a Foreign Language (TOEFL). Study Three examined the application of control strategies among junior and senior high school students in a less critical situation (i.e., before an internal school examination). The results of the studies lend support to the thesis about the primacy of primary control. As predicted, the Chinese students made extensive use of selective primary control, selective secondary control, and compensatory primary control in the urgent pre-deadline situation. The control strategies applied in the post-deadline situation continued to be characterized by primary control striving in both the success and the ∗

Correspondence concerning this article should be addressed to Wan-chi Wong, Department of Educational Psychology, Chinese University of Hong Kong, Shatin, NT, Hong Kong, China. E-mail: [email protected].

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Wan-chi Wong, Yin Li and Ji-Liang Shen failure conditions. Such primary control striving also demonstrated its adaptive value by significantly correlating to the positive affect subscale of the Positive and Negative Affect Schedule (PANAS). On the other hand, the endorsement of compensatory secondary control in the failure condition did not show its adaptive value. In integrating the results of Study One, Study Two and Study Three, differences were found across the compared age groups. The ascending slope in the application of compensatory secondary control was confirmed among the subjects who ranged from pre-adolescents through adolescents to young adults. For further development of the research program, it is suggested that Lakatos’s idea of sophisticated falsification would be worth considering. Attempts are made to define the “hard core” of the research program, and to propose new auxiliary hypotheses on the basis of the present study. Several lines for future research are also discussed.

Keywords: Life-span theory of control, primary control, secondary control, academic achievement, subjective well-being

INTRODUCTION The dynamics of control processes has been recognized as a highly significant area of study in human functioning. Different theoretical formulations for explaining control-related human behavior have been proposed in recent decades (e.g., Rothbaum, Weisz, and Snyder, 1982; Folkman, Lazarus, Dunkel-Schetter, DeLongis and Gruen, 1986; Holahan, Moos, and Schaefer, 1996). In this context, Heckhausen and Schulz (1993, 1995) developed the life-span theory of control and specified a model of optimization in primary and secondary control (OPS model) to account for individuals’ attempts to regulate their development. In essence, the OPS model conceptualizes developmental regulation as an interaction of two orthogonal dimensions: primary and secondary control on the one hand, and selectivity and compensation on the other. The key proposition of the model is that individuals strive to control their (immediate) environment and self (internal processes including motivation, emotion, and mental representation) in their development across the life span. The former, referred to as primary control, is regarded as having primacy over the latter, which is referred to as secondary control. The postulation that primary control has primacy means that such a type of control “is both preferred and has a greater adaptive value to the individual” (Heckhausen and Schulz, 1995, p.286). It is hypothesized that the employment of primary control forms an inverted U shape over the life-span, whereas the application of secondary control follows an ascending slope from childhood through adulthood to old age (Heckhausen and Schulz, 1995; Heckhausen, 1999). Another underlying principle of the OPS model lies in the proposition that selectivity and compensation are fundamental requirements of human behavior and development (Heckhausen, 1999). Selectivity, in the sense of selection of goals and the focused investment of resources in goal attainment, is needed to achieve successful behavior-event contingencies. On the other hand, compensation is needed to protect a person’s motivational resources when facing experiences of failure, loss, threat, and decline, which are inevitable and frequent in human life. Based on the interaction of the above key propositions, four types of control strategies are identified in this two-dimensional model, namely selective primary control (e.g., investing

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effort and time, learning new skills), compensatory primary control (e.g., recruiting the advice and help of others, using technical aids), selective secondary control (e.g., enhancing goal value, anticipating the positive consequences of goal attainment), and compensatory secondary control (e.g., goal disengagement, self-protective interpretations). It is further postulated that the effective use of these four control strategies is regulated by a higher-order process known as optimization, which guides goal selection in terms of optimizing the longterm potential for primary control. A further aspect of theoretical advancement lies in the integration of the life-span theory of control with the Rubicon model of action-phases (H. Heckhausen and Kuhl, 1985; H. Heckhausen, 1987a, 1987b, 1991). Figure 1 illustrates the extended model of action-phases that contains three levels: critical transition points; functions and challenges of the sequential action phases (pre-decisional, non-urgent and urgent pre-deadline, and post-deadline); and adaptive control strategies to meet these phase-specific challenges (Heckhausen, 1999; Heckhausen, Wrosch, and Fleeson, 2001; Wrosch and Heckhausen, 1999).

Figure 1. Action-phase model of developmental regulation.

“Deadline”, newly inserted as a critical transition point in the motivational process (in addition to the Rubicon of intention formation), represents a central component of the extended model of action-phases. It denotes a change from greater and richer opportunities to lesser and poorer opportunities for goal attainment. If the concept of developmental deadline is applied, the deadline refers to age-normative constraints for attaining developmental goals, which involves deteriorating opportunity structures and calls for a shift from goal striving to goal disengagement. It should be noted that in the pre-deadline actional-phase there is a further distinction made between a non-urgent and an urgent situation. In a non-urgent situation, it is proposed that selective primary and selective secondary control would be employed. In an urgent situation, it is expected that there would be greater use of selective primary control and selective secondary control, as well as a supplementary application of compensatory primary control. The above employed control processes are adaptive in the sense that they are directed toward meeting the challenge of goal attainment defined by the

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situation. A different situation arises when the deadline is passed and thus opportunities for goal attainment are no longer present or lessened. If the goal is not achieved when the deadline is passed, it is hypothesized that a radical shift would be made to apply compensatory secondary control. Those individuals who attain their goals before the deadline would continue the process of primary control striving. In parallel with the theoretical development in control processes, Heckhausen, Schulz and their associates have developed a research program to penetrate the varied fields of human activity related to developmental regulation. For instance, a large-scale empirical study was carried out among East and Western Berliners to examine the primary and secondary control of aging-related and socio-historical challenges (Heckhausen, 1994, 1997; Heckhausen and Schulz, 1998). Control strategies in specific domains such as managing health and financial stress were further studied across adulthood (Wrosch, Heckhausen and Lachman, 2000; Wrosch, Schulz and Heckhausen, 2002). Also noteworthy are the empirical investigations into control processes in pre-deadline and post-deadline situations. Research has focused on important developmental deadlines such as partnership realization (Wrosch and Heckhausen, 1999), and childbearing (Heckhausen, Wrosch and Fleeson, 2001). The findings of the research projects converge in confirming the hypothesis that adults adjust their control striving to the opportunities in their respective developmental ecologies. Before the deadline is passed, individuals invest in primary control striving toward attaining the life goal. However, once the deadline is passed people shift to goal disengagement and self-protection. In the study on partnership realization, it was found that an age-adapted application of control processes is related to the improvement of subjective well-being over time (Wrosch and Heckhausen, 1999). Results of studies on the “biological clock” of childbearing also lend support to the action-phase model of developmental regulation regarding the hypothesized patterns of control strategies before and after the deadline. Furthermore, phase congruent goal engagement versus goal disengagement was found to be associated with a higher level of subjective well-being (Heckhausen, Wrosch and Fleeson, 2001). The issue of commonalities and variations between different cultural groups has been an ongoing concern in psychology. In response to Heckhausen and Schulz’s formulation of the life-span theory of control, Gould (1999) questioned its claim to universality. Drawing on empirical studies in Asian societies, Gould suggested that secondary control has primacy in this part of the world. He perceived Heckhausen and Schulz’s theoretical explication as another example of the “imposed etic” perspective, which reflects the typical error of Western interpretation of non-Western cultures. Heckhausen and Schulz (1999) replied to Gould’s critique by making two essential clarifications. (1) The fundamental characteristics of the human motivation system, which constitute the heart of the life-span theory of control, are proposed to be historically and culturally invariant. (2) The role of secondary control is neither that of master nor of slave in relation to primary control. Rather, the apt metaphor for the relation of secondary control to primary control would be that of a confederate. In his analysis, Gould confounded other psychological constructs (e.g., independent self and interdependent self; individualistic and collectivistic orientations) with primary and secondary control. The mixing up of the empirical level of Asian cultures with their ideological level can also be observed in Gould’s discussion. Probably influenced by a stereotypic understanding of Asian cultures and peoples, Gould has not fully considered alternative interpretations concerning certain selected results of culture-comparative research. To capture the fine points of psychological reality, it is important to distance oneself from both an “imposed etic”

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perspective and a stereotypic understanding of an indigenous culture. Joining the discourse on the primacy of primary control or secondary control, Yamaguchi (2001) remarked that empirical research on this issue is scarce. According to his review of existing literature, the claim that East Asians use less primary control compared to Westerners is not well supported. Nonetheless, he suggested that secondary control could contribute to subjective well-being among East Asians on the basis of his conceptual analysis. When considering the Gould versus Heckhausen and Schulz debate, as well as Yamaguchi’s perspective, a critical test of the extended OPS model in an Asian society, which could reveal the subtle commonalities and variations of control processes in different samples, seems particularly promising. The theoretical advancement in control processes offers rich possibilities for generating empirical studies in diversified domains of human life. In the light of the current state of knowledge, and of the debate about the claim to universality of the life-span theory of control, the present study aims to examine the control processes in the academic pursuits of Chinese students, with special emphasis on the developmental regulation before and after a deadline. It is well known that academic achievement is highly prized in Chinese communities. In mainland China, the University Entrance Examination and the Test of English as a Foreign Language (TOEFL) are generally regarded as critical life events among adolescents and young adults respectively. More specifically, a place in a good university constitutes a developmental goal of enormous importance for Chinese adolescents. If a student were to fail to enter a good university, he/she would be in a less advantageous position in his/her pursuit of further goals. Among young adults, a satisfactory result in the TOEFL further serves as a prerequisite for the life-dream of going abroad for postgraduate study. Unsatisfactory results in the TOEFL would diminish their chances of getting an offer from their targeted universities in foreign countries. Given these circumstances, the University Entrance Examination and the TOEFL constitute developmental deadlines: the transition into better educational chances and advanced careers. Passing such a deadline without success marks the change from greater and richer opportunities to lesser and poorer ones in the attainment of developmental goal(s). Therefore, an investigation of Chinese students’ control processes before and after the deadline of these public examinations would be of great theoretical and practical interest. In brief, the present study is designed to serve three main objectives: (1) to empirically put to test the “primacy-of-primary-control” proposition argued in the Gould versus Heckhausen and Schulz debate; (2) to examine Heckhausen’s theoretical formulation about patterns of control processes before and after an important deadline of developmental goal(s); and (3) to investigate in greater detail control processes and their adaptive value among Chinese adolescents and young adults in the domain of academic achievement. When investigating the control processes involved in the academic behavior of Chinese students, the construction of an instrument for this specific domain is a prerequisite. A pilot study is thus required to examine the newly constructed instrument (OPS-Scales in the Domain of Academic Achievement, OPSAA) for any necessary revision. The main research program consists of three studies. Study One focused on investigating the control processes of Chinese students in the pre-deadline and post-deadline situations of the University Entrance Examination, which is generally regarded as the most important public examination in mainland China. Chinese students’ control processes before and after the TOEFL constituted the focus of Study Two. The subjects involved were undergraduate and postgraduate students who voluntarily took the TOEFL. Study Three, being implemented in a less critical situation (i.e., before an internal school examination rather than an important public examination),

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serves the purpose of comparison with the candidates of the public examinations. The participants in Study Three included all levels of junior and senior high school students (except for those taking the public examination) from a middle tier high school. In this way Chinese students, from pre-adolescents through adolescents to young adults, were involved in the present study of control processes. Based on the theoretical framework of the extended OPS model (Heckhausen and Schulz, 1995; Heckhausen, 1999), three sets of predictions are made in the present study. (1) The primacy of primary control in all Chinese samples across all situations (except the postdeadline failure condition) is expected. (2) In the urgent pre-deadline situation, it is expected that the control processes of Chinese students would be characterized by extensive employment of selective primary control and selective secondary control, as well as compensatory primary control. An increased application of compensatory secondary control is expected in the post-deadline failure condition, whereas a continuing exercise of primary control is predicted in the success condition. (3) Differences in the endorsement of primary and secondary control are expected among the different age groups of Chinese students ranging from pre-adolescents through adolescents to young adults. Specifically, it is expected that older students in this age range would apply both primary and secondary control more frequently.

THE PILOT STUDY Subjects and Procedure In the pilot study, the newly constructed OPSAA (OPS-Scales in the Domain of Academic Achievement) was distributed to the final year students of two high schools in Beijing (n=293; male=119, female=174). This group of subjects, who took the University Entrance Examination in July 2001, joined the pilot study in March 2001 on a voluntary basis. Their ages ranged from 16 to 20 years (mean=17.84, SD=0.53).

The Development of the OPSAA (OPS-Scales in the Domain of Academic Achievement) The main instrument of the present research project, namely the OPS-Scales in the Domain of Academic Achievement (OPSAA), has been adapted from the general OPS-Scales (Heckhausen and Schulz, 1998; Heckhausen, Schulz and Wrosch, 1998). The newly constructed OPSAA used in the pilot study was composed of six main subscales (general optimization, optimization in the domain of academic achievement, selective primary control, selective secondary control, compensatory primary control, and compensatory secondary control), each containing five items. Prior to its application in the pilot study, the OPSAA underwent a back-translation process with the help of a bilingual (Chinese-English) academic 1 trained in psychology . 1

We are grateful to Dr. Shu-chen Li at the Max-Planck-Institute for Human Development (Berlin) for her help in the back-translation of the OPSAA.

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After the necessary modifications had been made following the back-translation process, the 30-item OPSAA was used in the pilot study. Each item portrays a kind of optimization or control strategy in the form of an act or a thought. The respondents were instructed to review their own state, and to report the frequency of occurrence of the stated strategies using a fivepoint Likert scale (ranging from never true “1” to almost always true “5”). Apart from responding to the 30 items, the subjects were also requested to answer two open-ended questions about the clarity and relevance/personal meaning of the items. They were invited to list all items that they considered to be unclear and irrelevant/not meaningful, and to provide a brief explanation why. Table 1. The prototypical item content of the OPSAA control subscales (1) Selective primary control (SPC) prototypical item content: investing effort, time, and/or energy in academic goal attainment; developing essential skills and abilities to achieve a learning goal; fighting difficulties in the realization of an academic goal αs : ranging from 0.71 to 0.81 (2) Selective secondary control (SSC) prototypical item content: enhancing the value of academic goals or devaluing competing goals; enhancing perception of control in a learning goal; anticipating positive consequences of academic goal attainment αs: ranging from 0.57 to 0.74 (3) Compensatory primary control: Sub-category A (CPCa) prototypical item content: recruiting help or advice from others in different situations of academic pursuits αs: ranging from 0.74 to 0.79 (4) Compensatory primary control: Sub-category B (CPCb) prototypical item content: trying new, unfamiliar or unusual ways to overcome academic setbacks; taking reference of others’ methods; learning more effective ways of solving academic difficulties αs: ranging from 0.65 to 0.80 (5) Compensatory secondary control: Sub-category A (CSCa) prototypical item content: self-protective interpretations for academic setbacks: external attribution, self-protective social comparison, and self-protective intra-individualized comparison αs: ranging from 0.58 to 0.72 (6) Compensatory secondary control: Sub-category B (CSCb) prototypical item content: goal disengagement or goal adjustment following academic failure αs: ranging from 0.53 to 0.65 Note: αs = standardized alpha

On the basis of reliability analyses, exploratory factor analysis, and the responses to the open-ended questions, we worked on the revision of the OPSAA. The major revision involved the subscales “compensatory primary control (CPC)” and “compensatory secondary

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control (CSC)”. In the pilot study, we found that items of the CPC fell neatly onto two separate factors: one factor concerned recruiting help or advice from other people, the other concerned seeking new ways or unusual methods. Furthermore, CSC items addressing selfprotection and goal disengagement also appeared as two distinguishable components. Accordingly, we decided to differentiate the subscales CPC and CSC into finer sub-categories (CPCa, CPCb, CSCa and CSCb), and to construct new items according to the meaning of the new sub-categories, each new sub-category containing five items.2 The revised OPSAA consists of 40 items (five items x eight subscales, see Appendix A). Excluding the 10 items on optimization, 30 items are related to control strategies (five items x six subscales). Table 1 below shows the prototypical item content of the OPSAA control subscales. The range of reliabilities (αs: standardized alpha) of these subscales revealed in various studies of the present project is also reported. As shown in Table 1, acceptable/satisfactory internal consistencies for the subscales on control strategies were found despite the small number of items (n=5) in these subscales. Combining the sub-categories, the αs of CPC (no. of items=10) ranged from 0.76 to 0.84 whereas the αs of CSC (no. of items=10) ranged from 0.72 to 0.78.

STUDY ONE Method Subjects and Procedure Study One covers both the pre-deadline and post-deadline situations of the University Entrance Examination. Subjects involved were high school students taking this public examination. In early April 2001 (three months before the University Entrance Examination), a questionnaire containing the OPSAA was distributed to the graduating classes of three high schools in Beijing (n=666; male=312, female=354). Teachers in the participating schools helped to distribute the questionnaire in class, gave clear instructions and explanations, and drew attention to the voluntary nature of the response. Students filled in the questionnaire in their free time and returned the materials to their class teacher. Each of the participating schools belongs to one of the three different tiers applying in China. The first tier covers schools recognized as outstanding at the city level. Schools that are recognized as good within a district fall into the second tier. The remaining average schools are categorized as third tier. The detailed breakdown of the number of subjects is as follows: 157 students from the first tier, 276 students from the second tier, and 233 students from the third tier. Similar to the

2

In addition to the above mentioned major changes, reliability analyses and exploratory factor analysis also indicated the need for some minor revisions in the subscales of “general optimization”, “optimization in the domain of academic achievement”, and “selective secondary control”. Specifically, one item of each of the above-mentioned subscales was reconstructed. It should be noted that only a few subjects expressed doubts about the clarity and/or relevance of a very limited number of items. We examined carefully all such doubts and made minor modifications to four items. On the other hand, quite a large number of students stated explicitly that they found the items clear and/or meaningful. The reaction expressed by a female student is perhaps worth mentioning: “All items in this questionnaire are very meaningful to me. Some of them stimulate me to think about my learning goals and my daily behavior. This is a very good inventory for self-reflection”.

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sample in the pilot study, the mean age of the subjects was 17.94 (SD=0.49, minimum=16, maximum=20). High school subjects who filled in the questionnaire in the pre-deadline situation were further invited to join the follow-up study in the post-deadline situation. Two weeks after they had received their results, the participants had to respond to a questionnaire including the OPSAA and the PANAS (Positive and Negative Affect Schedule, Watson, Clark and Tellegen, 1988). A total of 305 high schools students (male=125, female=180) joined the post-deadline study. After completing the questionnaire in mid-August 2001, the subjects were asked to return the materials using envelopes provided by us.

Materials The Questionnaire Applied in the Pre-deadline (Pre-examination) Situation of Study One In the pre-deadline situation, an open-ended question on developmental goals for the next 5 to 10 years was raised at the beginning. Subjects were requested to identify five important goals and to specify the expected time of attainment. For each of the nominated goals, the significance and probability of their attainment as well as the perceived degree of personal control were also recorded using a five-point Likert scale. Prior to responding to the OPSAA, subjects were asked to indicate the significance of the approaching University Entrance Examination using a five-point Likert scale (ranging from extremely unimportant “1” to extremely important “5”). The 40-item OPSAA constituted the main component of the questionnaire. Participants had to review their own state in the previous two weeks, and to report the frequency of their application of certain optimization and control strategies reflected in the items. Such a frequency report was expressed using the five-point Likert scale ranging from never true “1” to almost always true “5”. The Questionnaire Applied in the Post-deadline (Post-examination) Situation of Study One In the post-examination situation, subjects were first asked to respond to a 20-item PANAS (Positive and Negative Affect Schedule, Watson, Clark and Tellegen, 1988). The PANAS, a widely applied instrument for assessing subjective well-being, was included in the present study to reflect the level of adaptivity. Good psychometric properties of the PANAS, including high inter-item reliabilities, high convergence in factor structures, and high discriminant validity, have been demonstrated (Watson, 1988; Watson, Clark and Tellege, 1988). The PANAS consists of two 10-item (each in the form of an adjective) self-report scales designed to assess positive and negative affect respectively. Specifically, the 10 items of positive affect are: interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive, and active. Items of negative affect are: distressed, upset, guilty, scared, hostile, irritable, ashamed, nervous, jittery, and afraid. A back-translation of the PANAS was undertaken with the help of two bilingual (Chinese-English) academics trained in psychology and philosophy respectively.3 In applying PANAS to the present study, subjects were instructed to report how they had experienced positive and negative affect in the previous two

3

We would like to express our sincere thanks to Dr. Jenny Yau and Dr. Si-wai Man for their help in backtranslating the PANAS.

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weeks using a five-point Likert scale (ranging from very slightly or not at all “1” to extremely “5”). In the second part of the questionnaire, the subjects had to respond to the OPSAA. The instruction was the same as for the pre-deadline situation. Based on the design of the present study, the two weeks on which the subjects were asked to review their acts and thoughts should coincide with the two weeks immediately after they received their results. All items of the OPSAA were randomly re-arranged so that the ordering of the items was totally different from the scale used in the pre-deadline study. As the data had to be collected anonymously, we were not in a position to compare within subjects across a longitudinal span. In the last section of the questionnaire, the participants were further asked about their perceived success or failure in the examination. They were also requested to analyze the causes of this success or failure, and to identify the most important cause(s).

Results and Discussion Pre-deadline (Pre-examination) Situation of Study One As a precedent to the analysis of the endorsement of control strategies, it should be noted that the subjects of the study regarded the public examination as a highly significant event. Using a five-point Likert scale on which “5” means “extremely important”, the mean score among the candidates for the University Entrance Examination (n=666) is 4.68 (SD=0.64). The Endorsement of Control Strategies before the Deadline (i.e., a Highly Significant Public Examination) Three months before the University Entrance Examination, the patterns of the control strategies employed by the candidates were elicited. Figure 2 illustrates the mean ratings of the OPSAA control subscales among them in this pre-deadline situation. From Figure 2, we can observe the pattern of control processes before the deadline: Selective primary control (SPC) and selective secondary control (SSC) were extensively endorsed, and compensatory primary control (CPC) slightly less so. The application of compensatory secondary control (CSC) was relatively infrequent. The Factor Structure of the Control Processes In order to uncover the underlying structure of control strategies, exploratory factor analysis was employed in the present study on the 30 items of OPSAA control subscales. Principal components analysis with promax rotation was applied. In this sample of candidates preparing for the University Entrance Examination, five substantial factors were extracted (eigenvalues = 4.97, 3.47, 1.95, 1.63, and 1.37). These factors help to explain 44.61% of the total variance. Upon close examination of the items that loaded heavily (>0.50) on each extracted factor, we found that these five factors are highly interpretative, and define them as follows: Factor 1: Readiness to seek advice and help from others in varied situations of academic pursuits (explaining 16.57% of the total variance)

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5 4.5 4

Candidates for the University Entrance Examination

3.5 3 2.5 2 1.5 1 0.5 0 SPC

SSC

CPCa

CPCb

CSCa

CSCb

Figure 2. The mean ratings (per item) of the OPSAA control subscales among candidates for the University Entrance Examination (n=666) in the pre-deadline situation

Factor 2: Mobilization of resources such as time and effort (selective primary and selective secondary control inclusive) (explaining 11.56% of the total variance) Factor 3: Consoling oneself by social comparison, intra-individualized comparison, and inter- domain comparison (explaining 6.51% of the total variance) Factor 4: Finding new and/or effective ways of learning, and developing one’s abilities and skills (explaining 5.42% of the total variance) Factor 5: Goal disengagement, and self-protective external attribution of the difficulty level of the unfulfilled goal (explaining 4.56% of the total variance) [The factor loadings and the mean scores of the response items are presented in Appendix B] Factor 1, Factor 2 and Factor 4 reflect the hypothesized adaptive control strategies in a pre-deadline situation. The high mean scores of the items that loaded heavily on these factors imply that these adaptive control strategies were frequently endorsed by the present sample. Both Factor 3 and Factor 5 fell into the category of compensatory secondary control. The mean scores of the items loading on these two factors are relatively low (in particular for Factor 5 which highlights goal disengagement), reflecting an infrequent endorsement of such types of control processes in the pre-examination situation. The five extracted factors were further subjected to a second order factor analysis (with principal component analysis using promax rotation). It yielded two higher-order factors that explained 60.57% of the total variance (eigenvalues = 1.73 and 1.30). Table 2 below illustrates the loadings of the extracted factors on the higher-order factors:

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Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Higher-order Factor one 0.73 0.71

Higher-order Factor two

0.81 0.76 0.88

A clear two-factor structure is revealed in Table 2. With Factors 1, 2 and 4 falling substantially onto the first higher-order factor, and Factors 3 and 5 substantially onto the second one, we can define the former as “Engaging”, and the latter as “Disengaging and selfprotective”. Noteworthy is the negative significant correlaton between the two higher-order factors (r= -0.12).

Group Differences in the Endorsement of Control Strategies In order to assess group differences among the students graduating from the three different tiers of high schools, one-way ANOVA was applied to the factor scores (pertaining to individual subjects) of the five extracted factors on control processes. It is noteworthy that no significant difference was found, despite the fact that students from different tiers had varied academic backgrounds. They would probably have different results in the forthcoming University Entrance Examination. By means of a t test, significant gender differences were found among the candidates for the University Entrance Examination in Factor 1 [ t (451.39) = -6.61, p<0.001 ] and Factor 2 [ t (495.20) = -3.44, p=0.001 ]. Specifically, these results indicated that female students were more ready to seek advice and help from others, and to mobilize resources such as time and effort. Post-deadline (Post-examination) Situation of Study One Perception of Success or Failure in the Examination Among the high school students who joined the post-deadline study (n=305) two weeks after receiving the examination results, 53.44% rated their results as a failure (choosing 1 to 3 on the six-point Likert scale), whereas 44.26% rated their results as a success (choosing 4 to 6 on the six-point Likert scale). Subjective Well-being of the Examination Candidates The subjective well-being of the examination candidates in the post-deadline situation was assessed using the 20-item PANAS (Positive and Negative Affect Schedule). The internal consistencies of the subscales were high in Study One (PA: αs=0.78; NA: αs=0.90). Among the candidates for the University Entrance Examination, a significant negative correlation was found between PA and NA (r= -0.28, p<0.001). As there were significant differences in the mean scores of PA and NA between the success and failure conditions, we

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analyzed these conditions separately. The results of the candidates for the University Entrance Examination are presented in the Table 3 below: From Table 3, we can observe a marked difference in emotional experience between the success and the failure conditions among the candidates for the University Entrance Examination, particularly in the case of negative affect.

The Endorsement of Control Strategies after the Deadline Among the candidates for the University Entrance Examination, no significant difference was found between the success and failure conditions in relation to the mean ratings of the control subscales. It is thus not necessary to report these results separately. Figure 3 below presents the mean ratings of the OPSAA control subscales among the candidates in the postdeadline situation. Table 3. Positive and negative affect of the candidates in the post-deadline success (n=135) and failure (n=163) conditions of the University Entrance Examination

Positive affect (PA) Success condition Failure condition Negative affect (NA) Success condition Failure condition

Mean

Mean per Item

SD

29.20

2.92

6.75

23.36

2.34

5.82

15.15

1.52

4.40

25.40

2.54

8.16

5 4.5 4 Candidates for the University Entrance Examination (n=305)

3.5 3 2.5 2 1.5 1 0.5 0 SPC

SSC CPCa CPCb CSCa CSCb

Figure 3. The mean ratings (per item) of the OPSAA control subscales among candidates for the University Entrance Examination in the post-deadline situation

We can observe from Figure 3 that the patterns of control strategies in the post-deadline situation are highly similar to the patterns found in the pre-deadline situation. Selective primary control (SPC) and selective secondary control (SSC) were most frequently applied, followed by compensatory primary control (CPCa and CPCb). Contrary to the expectation, in the failure condition, there is no increased endorsement of compensatory secondary control (CSCa and CSCb).

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The Factor Structure of the Control Processes Among the candidates for the University Entrance Examination, the factor structure of the control processes found in the post-deadline situation was highly similar to that of the predeadline situation. A principal component analysis with promax rotation yielded five highly interpretative factors (eigenvalues = 5.75, 3.56, 2.28, 1.70 and 1.40), explaining 48.95% of the total variance: Factor 1: Mobilization of resources including time, effort, energy and abilities (selective primary and selective secondary control inclusive)(explaining 19.15% of the total variance) Factor 2: Readiness to seek advice and help from others in varied situations of academic pursuits (explaining 11.86% of the total variance) Factor 3: Finding new, unusual, unfamiliar and/or effective ways of learning, and developing one’s abilities and skills (explaining 7.61% of the total variance) Factor 4: Applying self-protective mechanisms including external attribution, social comparison, and intra-individualized comparison (explaining 5.67% of the total variance) Factor 5: Goal disengagement, and self-protective external attribution of the difficulty level of the unfulfilled goal (explaining 4.67% of the total variance) [Appendix C presents the factor loadings and the mean scores of the response items.] Table 4. Second order factor analysis of the control processes among the candidates for the University Entrance Examination in the post-deadline situation (n=305)

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Higher-order Factor one 0.77 0.73 0.68

Higher-order Factor two

0.78 0.82

A second order factor analysis further yielded two higher-order factors that explained 58.78% of the total variance (eigenvalues = 1.64 and 1.30). As was the case in the predeadline situation, we can also define the first higher-order factor as “Engaging”, and the second one as “Disengaging and self-protective”. Nonetheless, a subtle difference was observed regarding the relation between the two higher-order factors. These two factors were not significantly correlated in the post-deadline situation, whereas a negative significant correlation existed between them (r= -0.12) in the pre-deadline situation. Table 4 above shows how the extracted factors loaded on the higher-order factors.

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The Relationship between the Endorsement of Control Strategies and Subjective Wellbeing To assess the relationship between the endorsement of control strategies and subjective well-being in the post-deadline situation, the correlation coefficients between the factor scores of the control subscales and the PANAS subscales were computed. Among the candidates for the University Entrance Examination who perceived their results as successful (n=135), no significant relationship was found between the five extracted factors of control processes and the two subscales of positive and negative affect. For those who regarded their results as a failure (n=163), significant correlations were found between PA (10 items of positive affect) and Factor 1 [Mobilization of resources including time, effort, energy and abilities](r=0.25, p<0.01), as well as between PA and Factor 3 [Finding new, unusual, unfamiliar and/or effective ways of learning, and developing one’s abilities and skills] (r=0.26, p<0.01). It is interesting to note that compensatory secondary control did not have a significant relationship with the emotional experience of Chinese students in the post-deadline failure condition. Among the Chinese examination candidates, the selection of an “engaging” style of control processes appeared to be more adaptive in such a condition. Group Differences in the Endorsement of Control Strategies In the post-deadline situation, no significant difference was found in the factor scores of the OPSAA control subscales between the examination candidates from different tiers of high schools. This finding is the same as that in the pre-deadline situation. Gender differences were found among this sample (n=305) in Factor 1 [Readiness to seek advice and help from others in varied situations of academic pursuits] [ t (223.23) = -2.22, p<0.05 ] and Factor 3 [Finding new, unusual, unfamiliar and/or effective ways of learning, and developing one’s abilities and skills] [ t (257.73) = 2.09, p<0.05 ]. Specifically, female students scored higher on Factor 1 whereas male students scored higher on Factor 3 in the post-deadline situation.

STUDY TWO Method Subjects and Procedure Concerning the TOEFL subjects involved in the pre-examination situation (n=219), the majority came from two of the best universities in China (78 from Peking University, 62 from Tsinghua University). Another 70 came from other universities in Beijing, and 12 came from universities in other cities. All of the subjects participated on a voluntary basis in response to an advertisement posted on the notice boards of the major universities in Beijing. The advertisement was also sent to the internal websites of the Peking University and the Tsinghua University. As an incentive, a small monetary reward (50 yuan, equivalent to about 6.4 US dollars) was offered for participation. Only students intending to take the TOEFL in May 2001 were qualified as subjects for our study. These qualified volunteers were requested to enroll in our study with the help of our research assistant. A questionnaire containing the OPSAA was sent to the recruited subjects in mid-April 2001 (one month before the TOEFL). The ages of the participants ranged from 19 to 28 years (Mean=22.16, SD=1.73). They were either undergraduate or postgraduate students.

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Like the case in Study One, the TOEFL candidates who filled in the questionnaire in the pre-deadline situation were further invited to join the follow-up study in the post-deadline situation. Two weeks after they had received their results, the participants had to respond to a questionnaire including the OPSAA and the PANAS. A total of 157 TOEFL subjects (male=64, female=93) joined the post-deadline study. Among them, 85 were undergraduates, and 72 were postgraduates. After completing the questionnaire in early August 2001, the TOEFL candidates were asked to return the materials using envelopes provided by us.

Materials The questionnaires used in both the pre-examination and post-examination situations were exactly the same as those used in Study One.

Results and Discussion Pre-deadline (Pre-examination) Situation of Study Two Among the undergraduate and postgraduate students preparing to take the TOEFL (n=219), the mean score for the significance of the examination is 4.01 (SD=0.79) (“5” means “extremely important”). The Endorsement of Control Strategies before the TOEFL One month before the TOEFL, the patterns of the control strategies employed by the candidates were elicited. Figure 4 illustrates the mean ratings of the OPSAA control subscales among these candidates in this pre-deadline situation. 5 4.5 4 3.5

TOEFL Candidates

3 2.5 2 1.5 1 0.5 0 SPC

SSC

CPCa CPCb CSCa CSCb

Figure 4. The mean ratings (per item) of the OPSAA control subscales among TOEFL candidates (n=219) in the pre-deadline situation

Similar to the pattern of control strategies employed by the candidates for the University Entrance Examination, selective primary control (SPC) and selective secondary control (SSC) were extensively endorsed by the TOEFL candidates, with compensatory primary control

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(CPC) slightly less so. The application of compensatory secondary control (CSC) appeared to be relatively infrequent. When applying t tests to the mean scores of the OPSAA subscales of the two groups of candidates, significant differences were found in all control subscales except SSC (p<0.001 in the case of SPC, CPCb, CSCa and CSCb; p<0.01 in the case of CPCa). As compared to the candidates of the University Entrance Examination, the TOEFL candidates reported more frequent employment of all the strategies of primary and secondary control that showed a significant difference between the two groups.

The Factor Structure of the Control Processes Employing principal components analysis with promax rotation on the 30 items of OPSAA control subscales, five substantial factors (eigenvalues = 5.66, 3.07, 2.12, 1.76, and 1.42) were extracted among the TOEFL candidates, explaining 46.7% of the total variance. These factors were found to be highly interpretative. Integrating the meanings of the items that loaded heavily (>0.50) on each factor, we define the five factors as follows: Factor 1: Readiness to seek advice and help from others in varied situations of academic pursuits (explaining 18.87% of the total variance) Factor 2: Mobilization of internal resources such as abilities and effort (selective primary and selective secondary control inclusive) (explaining 10.24% of the total variance) Factor 3: Highlighting the value of a certain goal, giving it priority, and learning effective methods (explaining 7.07% of the total variance) Factor 4: Self-protective external attributions (including luck, difficulty level of the unfulfilled goal, etc.), and goal disengagement (explaining 5.88% of the total variance) Factor 5: Consoling oneself by social comparison and intra-individualized comparison (explaining 4.73% of the total variance)

[Appendix D summarizes the factor loadings and the mean scores of the response items.] The mean scores of the items that loaded heavily on Factor 2 are particularly high, followed by Factor 3 and Factor 1 (see also Appendix D). It should be noted that all of these three factors reflect the hypothesized adaptive control strategies in a pre-deadline situation, with Factor 2 portraying the mobilization of internal resources such as abilities and effort. The high mean scores imply that these control strategies were frequently employed by the subjects. The items that loaded heavily on Factor 4 and Factor 5, both portraying compensatory secondary control, had relatively low mean scores, particularly in the case of Factor 4 (self-protective external attribution and goal disengagement). As in the case of the candidates for the University Entrance Examination, the application of a second order factor analysis to the five extracted factors yielded two higher-order factors. Table 5 shows the loadings of the extracted factors on these two higher-order factors (eigenvalues=1.64 and 1.30, explaining 58.76% of the total variance):

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Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Higher-order Factor one 0.56 0.72 0.78 -0.44

Higher-order Factor two 0.52

0.84 0.55

Table 5 shows that Factors 1, 2 and 3 loaded substantially on Higher-order Factor one (with Factor 1 loading less heavily). It also reveals that Factors 1, 4 and 5 fell substantially onto Higher-order Factor two (with Factor 4 loading most heavily). It should be further noted that Factor 5 (consoling oneself) loaded negatively on Higher-order Factor one in a substantial way. Taking account of the structure of the second order factor analysis, we define the first higher-order factor as “Engaging”, and the second one as “Compensatory”. To summarize, exploratory factor analysis revealed a similar pattern of control processes among the two groups of our samples, namely those preparing for the University Entrance Examination and for the TOEFL. Noteworthy is the observation that selective primary control and selective secondary control loaded on a single factor in both samples that can be interpreted as goal engagement (see also Heckhausen, Wrosch and Fleeson, 2001; Wrosch and Heckhausen, 1999; Wrosch, Schulz and Heckhausen, 2002). Despite the apparent similarity found between the two samples by means of the exploratory factor analysis, the application of a second order factor analysis helps to reveal the subtle differences in the underlying structure of the control processes.

Post-deadline (Post-examination) Situation of Study Two Perception of Success or Failure in the Examination In the post-examination situation, 63.69% of our TOEFL participants (n=157) rated their results as a failure (choosing 1 to 3 on the six-point Likert scale), and 35.67% rated their results as a success (choosing 4 to 5 on the six-point Likert scale). No students chose point “6” (“extremely successful”). The Subjective Well-being of the Examination Candidates The internal consistencies of the subscales of PANAS were high in Study Two. (PA: αs=0.84; NA: αs=0.88). No significant correlation was found between PA (positive affect) and NA (negative affect) among the TOEFL candidates. Significant differences were found in the mean scores of PA and NA between the success and failure conditions. We thus analyzed these conditions separately. The emotional experience of the TOEFL candidates in the success condition was similar to that of the graduating high school students. It is interesting to observe that even in the failure condition the experience of positive affect was more intense than that of negative affect. Table 6 summarizes the results of the emotional experience in both conditions among the TOEFL candidates:

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Table 6. Positive and negative affect of the TOEFL candidates in the post-deadline success (n=56) and failure (n=100) conditions

Positive affect (PA) Success condition Failure condition Negative affect (NA) Success condition Failure condition

Mean

Mean per Item

SD

27.09 23.31

2.71 2.34

7.12 6.44

14.32 20.69

1.43 2.07

5.46 6.51

The Endorsement of Control Strategies after the TOEFL Figure 5 below presents the mean ratings of the OPSAA control subscales among the TOEFL candidates in the post-deadline situation (significant difference between the success and failure conditions was only found in subscale SPC [p<0.05]). 5 4.5 4 3.5

TOEFL Candidates

3 2.5 2 1.5 1 0.5 0 SPC

SSC CPCa CPCb CSCa CSCb

Figure 5. The mean ratings (per item) of the OPSAA control subscales among TOEFL candidates (n=156) in the post-deadline situation

We can observe from Figure 5 that the patterns of control strategies in the post-deadline situation are highly similar to the patterns found in the pre-deadline situation. Selective primary control (SPC) and selective secondary control (SSC) were most frequently applied, followed by compensatory primary control (CPCa and CPCb). Contrary to the expectation, in the failure condition, there is no increased endorsement of compensatory secondary control (CSCa and CSCb). ]

The Factor Structure of the Control Processes The application of principal component analysis with promax rotation to the OPSAA control subscales yielded six highly interpretative factors (eigenvalues = 6.82, 3.75, 2.21, 1.63, 1.56 and 1.25). They explained 57.38% of the total variance. Despite the great similarity of the factor structure in the pre-deadline and post-deadline situations, one subtle difference is observed. There is a clear emergence of a factor on selective secondary control (i.e., Factor 5), which is not the case in the pre-deadline situation. The six extracted factors are named as follows:

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Wan-chi Wong, Yin Li and Ji-Liang Shen Factor 1: Readiness to seek advice and help from others in varied situations of academic pursuits (explaining 22.75% of the total variance) Factor 2: Mobilization of internal and external resources including time, efforts, energy, abilities, new methods, and others’ methods (explaining 12.50% of the total variance) Factor 3: Finding new, unusual, unfamiliar and/or effective ways of learning, and developing one’s abilities and skills (explaining 7.36% of the total variance) Factor 4: Applying self-protective mechanisms including external attributions, social comparison, intra-individualized comparison, and relaxation from academic goal pursuit (explaining 5.42% of the total variance) Factor 5: Enhancing the value of academic goals, and anticipating positive consequences of academic goal attainment (explaining 5.19% of the total variance) Factor 6: Goal disengagement, and self-protective external attribution of the difficulty level of the unfulfilled goal (explaining 4.16% of the total variance) [Appendix E summarizes the factor loadings and mean scores of the response items.]

By way of a second order factor analysis on the above six extracted factors, we obtained two higher-order factors that explained 59.09% of the total variance (eigenvalues = 2.35 and 1.20). Undertaking a careful examination of the loadings, we defined the two higher-order factors as “Engaging” and “Compensatory” respectively, as in the case of the pre-deadline situation. Table 7 below shows the loadings of the extracted factors on these two higher-order factors: Table 7. Second order factor analysis of the control processes among the TOEFL candidates in the post-deadline situation (n=157)

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

Higher-order Factor one 0.67 0.83 0.80

Higher-order Factor two 0.38

0.74 0.64 0.79

From Table 7, we can observe that factors reflecting selective primary control, compensatory primary control, and selective secondary control loaded substantially on Higher-order Factor one. It is further observed that factors of compensatory secondary control loaded substantially on Higher-order Factor two, whereas the factor reflecting compensatory primary control also loaded moderately on the same higher-order factor. Although the meanings of the higher-order factors are highly similar in both the pre-deadline and postdeadline situations among the TOEFL candidates, there is a noteworthy difference concerning their relationship. Whereas these two factors (“Engaging” and “Compensatory”) were not significantly related in the pre-deadline situation, they showed a positive significant correlation in the post-deadline situation (r=0.23).

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The Relationship between the Endorsement of Control Strategies and Subjective wellbeing Among the TOEFL candidates who defined their results as successful (n=56), PA (Positive Affect) was found to be significantly related to Factor 1 [Readiness to seek advice and help from others in varied situations of academic pursuits](r=0.33, p<0.05), and Factor 2 [Mobilization of internal and external resources including time, efforts, energy, abilities, new methods, and other people’s methods] (r=0.31, p<0.05). In the failure condition (n=100), significant correlations were found between PA and Factor 5 [Enhancing the value of academic goals, and anticipating positive consequences of academic goal attainment] (r=0.26, p<0.05). Interestingly, in the post-deadline failure condition, it was selective secondary control but not compensatory secondary control that had a significant relationship with the positive affect of the TOEFL candidates. Among these candidates, the selection of an “engaging” style of control processes appeared to be more adaptive after an important deadline in both the success and failure conditions.

STUDY THREE Method Subjects and Procedure The subjects of Study Three were high school students of all levels (except the two forms taking a public examination) from a school of the second tier. The graduating classes of this school had already participated into Study One of the present project. With the support of the headmaster, a questionnaire containing the OPSAA was distributed to all classes in junior one, junior two, senior one, and senior two. The response to the questionnaire was on a voluntary basis. In total 1085 students (male=498, female=586, unreported=1) filled in the questionnaire in their free time and then returned the materials to their class teachers in June 2001 (about one month before the internal school examination). The ages of the participants ranged from 12 to 18 years (M=14.88, SD=1.68). Materials The questionnaire used in Study Three is basically the same as the set distributed in the pre-deadline situation of Study One and Study Two. The only difference is that the subjects were asked to indicate the significance of the approaching internal school examination instead of the public examinations.

Results and Discussion It should be noted that the mean score of this group of high school students concerning the significance of the internal school examination is 4.28 (SD=0.99) (“5” meaning “extremely important”). Since the students perceived the internal school examination to be an important event, the situation at the time that they participated in our study can also be considered as a pre-deadline one, even though an internal school examination could be

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considered less important than a public examination such as the University Entrance Examination. In the context of mainland China, results of an internal school examination may affect the chance of getting a place in an “elite class” within one’s school, or of transferring to a more prestigious school in one’s city.

The Endorsement of Control Strategies before the Internal School Examination The pattern of control strategies among the different levels of high school students was similar to that of the candidates for the University Entrance Examination and the TOEFL candidates in the pre-deadline situations of Study One and Study Two. Figure 6 illustrates the mean ratings of the OPSAA control subscales among these three groups. We can observe from the mean ratings that selective primary control and selective secondary control were the most frequently applied control processes, followed by primary compensatory control. Compensatory secondary control was the least frequently endorsed strategy. 5 4.5

High school students

4 Candidates for the University Entrance Examination

3.5 3

TOEFL candidates

2.5 2 1.5 1 0.5 0 SPC

SSC

CPCa

CPCb

CSCa

CSCb

Figure 6. The mean ratings (per item) of the OPSAA control subscales among high school students (n=1085) in the pre-deadline situation [comparing and contrasting with the candidates for the University Entrance Examination (n=666) and the TOEFL candidates (n=216)]

The Factor Structure of the Control Processes Applying principal component analysis (with promax rotation) to the OPSAA control subscales, five highly interpretative factors were extracted from the responses of the high school students (eigenvalues = 5.90, 3.86, 1.72, 1.41 and 1.17; total variance explained = 46.89%): Factor 1: Mobilization of resources including time, effort, energy, abilities and motivation (selective primary and selective secondary control inclusive) (explaining 19.68% of the total variance)

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Factor 2: Readiness to seek advice and help from others in varied situations of academic pursuits (explaining 12.87% of the total variance) Factor 3: Applying self-protective mechanisms including social comparison, intraindividualized comparison, and external attribution (explaining 5.74% of the total variance) Factor 4: Goal disengagement, and self-protective external attribution of the difficulty level of the unfulfilled goal (explaining 4.69% of the total variance) Factor 5: Finding unusual, unfamiliar and effective ways of learning, and taking reference of others’ methods (explaining 3.91% of the total variance) [Appendix F shows the factor loadings and the mean scores of the response items.] From Appendix F, we can observe that Factor 1 is a very substantial factor concerning the mobilization of resources. In this factor, selective primary control and selective secondary control are intricately related. We shall use the phrase “selective primary and secondary control” to characterize this factor in our subsequent discussion. The factor structure of control processes among the high school students is seen to be highly similar to that of the candidates preparing for the University Entrance Examination in Study One. We then proceeded to a higher-order factor analysis that yielded two factors (eigenvalues= 1.82 and 1.37; total variance explained=63.74%). Table 8 shows how the extracted factors loaded on the higher-order factors: Table 8. Second order factor analysis of the control processes among the high school students (n=1085)

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Higher-order Factor one 0.80 0.73

Higher-order Factor two -0.40 0.71 0.81

0.74

Table 8 reveals the substantial loading of Factor 1, Factor 2, and Factor 5 on Higherorder Factor one, and the substantial loading of Factor 3 and Factor 4 on Higher-order Factor two. A moderately negative loading of Factor 1 (mobilization of resources) on Higher-order Factor two was also observed. We can define Higher-order Factor one as “Engaging” and Higher-order Factor two as “Disengaging and self-protective”. No significant correlation was found between these two higher-order factors. The subtle difference in higher-order factor structure between these high school students and the candidates for the University Entrance Examination in the pre-deadline situation should be noted. Among the candidates for the University Entrance Examination, there existed a negative significant correlation between the two similar higher-order factors (i.e., “Engaging” and “Disengaging and Self-protective”). Group Differences in the Endorsement of Control Strategies Among the high school students, we were interested in the gender difference and the level difference (junior versus senior) in the endorsement of the control strategies. Significant

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gender differences were found in Factor 1 [Mobilization of resources including time, effort, energy, abilities and motivation] [ t (706.80) = -2.02, p<0.05 ] and Factor 2 [Readiness to seek advice and help from others in varied situations of academic pursuit] [ t (676.14) = -3.01, p<0.01 ]. Female students scored higher on both Factors 1 and 2, meaning that they applied more frequently selective primary and secondary control, and compensatory primary control. Significant differences between the junior and senior high school students were found in Factor 1 [ t (763) = 2.81, p<0.01 ] and Factor 3 [Applying self-protective mechanisms including social comparison, intra-individualized comparison, and external attributions] [ t (789.62) = -5.24, p<0.001 ]. It is noteworthy that junior students scored higher on Factor 1 whereas senior students scored higher on Factor 3. Such a pattern implies that junior students more frequently applied selective primary and secondary control, whereas senior students more frequently employed compensatory secondary control.

GENERAL DISCUSSION The present research project aims at examining the control processes applied in the academic pursuits of Chinese students. The highly interpretable factor structures of the control subscales, found across different samples, lend support to the applicability of the control theory. Specifically, we have proposed three sets of predictions on the basis of the extended OPS model (Heckhausen and Schulz, 1995; Heckhausen, 1999), namely in relation to the primacy of primary control, the control processes in the pre- and post-deadline situations, and the differences across the age groups in the endorsement of control strategies. Taking the results of the studies together, we can now proceed to an integrative discussion. The thesis of the primacy of primary control is well supported by the findings of the present study across all samples in all situations. In both the urgent pre-deadline and the postdeadline situation (including success and failure conditions), primary control was preferred. Specifically, selective primary control, selective secondary control, as well as compensatory primary control were extensively employed. The factor structures of the control subscales further revealed a close relationship between selective primary control and selective secondary control. The adaptive value of primary control for subjective well-being was also demonstrated in the post-deadline situation. Among the candidates for the University Entrance Examination, positive affect was significantly correlated with two factors in the failure condition, namely (1) Mobilization of resources including time, effort, energy and abilities, and (2) Finding new, unusual, unfamiliar and/or effective ways of learning, and developing one’s abilities and skills. Among the TOEFL candidates who perceived their results as a success, positive affect was significantly related to one factor comprising seeking advice and help from others, and another, mobilization of internal and external resources. In the failure condition, it is noteworthy that positive affect was significantly correlated with the factor concerning selective secondary control. It should be noted that compensatory secondary control has played no adaptive role in the subjective well-being among Chinese students in the failure condition. In responding to the Gould versus Heckhausen and Schulz debate, we should note the fact that China is entering a phase of drastic societal transformation. Elder is perceptive in reminding us that such societal transformation could enhance the chances of gains and the

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risks of losses (Elder, 1974; Elder and Caspi, 1990). Living with this environmental demand, it is understandable that people would be more motivated to control their own life and development (Heckhausen, 1997). Evidence has been found for this in a research project launched among East and West Berliners after the unification of Germany (Heckhausen, 1994, 1998). Specifically, it was detected that the East Berliners, being confronted with radical sociopolitical change, endorsed selective primary control and selective secondary control more frequently than the West Berliners. Another noteworthy finding is provided by Seginer, Trommsdorff, and Essau (1993). In their study, Malaysian students showed stronger belief in primary as well as secondary control than their German counterparts. We should note that Malaysia is an Asian society undergoing transition to modernity whereas Germany is a typical modern society. In asserting that secondary control has primacy in Asian societies, Gould might have relied too much on certain stereotypic ideas of Asian societies and overlooked the environmental demands of a drastically changing social ecology. Nonetheless, we should bear in mind that the application of control strategies may be domain specific. Even though our data clearly suggest the primacy of primary control among Chinese students in the domain of academic achievement, the refutation of Gould’s thesis cannot be generalized to other domains without the support of further substantial empirical findings. Regarding the control processes in the pre-deadline situation, we can observe a highly consistent pattern across all samples, including the candidates for the University Entrance Examination and the TOEFL, and the high school students of different levels. As predicted, the Chinese students made extensive use of selective primary control, of selective secondary control, and of compensatory primary control in an urgent pre-deadline situation (i.e., before a public examination or an internal school examination). Concerning the post-deadline situation that we examined in Study One and Study Two, a continuous endorsement of primary control as well as selective secondary control was found in both the success and failure conditions. Contrary to the prediction, an increase in the employment of compensatory secondary control in the failure condition was not observed among the examination candidates. A better understanding of the characteristics of the subjects would probably throw light on this finding. As reported above, a majority of the candidates (including those for the University Entrance Examination and the TOEFL) perceived their results as a failure. Nonetheless, we learned from the information they provided that their results could be regarded as satisfactory/ acceptable from a factual point of view. This information, provided voluntarily by a relatively high number of subjects, included the total marks and/or specific marks obtained in the examinations, and the confirmation of a place in a certain university. Noteworthy is also the fact that many students provided attributions of failure when they rated their results as “relatively successful” or “very successful”, thus showing that they probably set themselves a very high standard of excellence, and viewed their results as a sort of failure to reach their ideal. Among students with such a high level of achievement motivation, it is understandable that they would not prefer disengagement or adjustment of academic goals in a subjectively defined failure condition. Further, students with these characteristics might not feel the need for a self-protective mechanism. The attributional explanations they provided for “failure” were largely related to effort (an internal, unstable, and controllable factor). Viewed through the lens of Higgins’s (1996) conceptualization of promotion focus vs. prevention focus in regulation, the prevalence of promotion focus among the Chinese samples in all examined situations is apparent.

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Concerning the differences across the age groups in the endorsement of control strategies, the results were largely convergent with the hypothesis of the life-span theory of control. Comparing the pre-deadline situation of Study One and Study Two, the TOEFL candidates (mean age = 22.16) rated significantly higher on the subscales of selective primary control, compensatory primary control, and compensatory secondary control than did the candidates for the University Entrance Examination (mean age=17.94). In Study Three, significant differences were found between the junior and senior high school students (mean age = 13.40 and 16.50 respectively) on the factors concerning selective primary and secondary control, and compensatory secondary control. Whereas the junior students rated selective primary and secondary control higher, the senior students rated compensatory secondary control higher. Integrating the results of Study One, Study Two and Study Three, the ascending slope in the application of compensatory secondary control from pre-adolescent through adolescent to young adults is clearly confirmed. This ascending slope in the use of compensatory secondary control strategies may be due to the development of social cognitive abilities in adolescence during which these secondary control strategies become more elaborate (see Heckhausen and Schulz, 1995; Weisz, 1983, 1986). The finding that junior students applied selective primary and secondary control more extensively calls for an explanation. One possible explanation is that the junior students rated the internal school examination as being more important than did the senior students (M=4.63 versus M=3.91), and they were thus more highly motivated to mobilize resources for the attainment of their academic goals. Summarizing the results, there are major convergences and minor inconsistencies with the theoretical claims of the extended OPS model. In discussing the dialectic between theory and empirical facts, and the development of the research program concerning control processes, it is worthwhile to incorporate Lakatos’s ideas on sophisticated falsification (Lakatos, 1970/1999; 1973/1999). Methodologically, Lakatos suggested the negative heuristic to specify the “hard core” of a research program, and the positive heuristic to articulate or invent auxiliary hypotheses. Whereas the “hard core” should be made immune against refutation within a certain range of time, the auxiliary hypotheses, which serve as a protective belt, should be subject to readjustment or even replacement. This methodology originated from the recognition that “theories are born in an ocean of anomalies and inconsistencies” (Lakatos, 1973/1999, p. 95). These anomalies and inconsistencies should not act as obstacles to genuine scientific development as expressed in the emergence of novel facts, novel auxiliary theories, and progressive problem-shifts. Despite Lakatos’s emphasis on heuristic power and the bracketing of anomalies, he continuously highlighted the need to acknowledge inconsistencies as well as the state of degeneration of the theory. In the spirit of Lakatos, we may consider the primacy of primary control, the theoretical formulation around a deadline, and the hypothesized differences in control processes across the age groups as the hard core of the extended OPS model. After implementing the present study, we are in a position to suggest three new auxiliary hypotheses. First, the primacy of primary control becomes even more salient in a drastically transforming social ecology. Second, compensatory secondary control is neither important nor adaptive for young people with high achievement motivation in a subjectively defined failure condition. Third, younger subjects apply selective primary and secondary control more extensively than their older counterparts when a certain goal appears to be very important for them. In future developments of the research program, several lines of research are worth pursuing. With regard to the control processes of students in their academic pursuits, it would

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be worthwhile to launch empirical studies in different Chinese communities (including provincial areas and overseas) on the one hand, and to implement cross-cultural studies on the other. Another valuable focus of inquiry would be to examine how teachers in different cultural backgrounds and social ecologies apply control processes in their pedagogical activities. With respect to the examination of control processes operating around a loss or a failure, indigenous or cross-cultural research on subjects experiencing job loss, retirement, and chronic disease or disability would also be revealing. Further effort should be made to integrate qualitative methods into the currently applied quantitative measure, so that the integration and dynamic of control processes can be further uncovered. In the process of cross-cultural study, it would also be worthwhile to re-examine and enrich the prototypical content of primary and secondary control on the conceptual level.

ACKNOWLEDGMENTS This project was supported by the Mainline Research Scheme of the Chinese University of Hong Kong (44M2010). We are grateful to Jutta Heckhausen for her valuable advices in various phases of the research process, and for her helpful comments on previous versions of this article. We would also like to extend our sincere thanks to Yan-li Cui and Iris Tsang for their help in data collection and data analyses respectively.

APPENDIX A. OPS-Scales for the Domain of Academic Achievement4 SPC (Selective Primary Control) 5. To achieve a learning goal, I work hard in developing the essential skills and abilities. 10. I invest as much time and energy as possible for higher academic achievement. 16. Having set my mind on good academic results, I put it before everything else. 19. When I really want further study, I work hard to achieve it. 33. In tackling an academic goal that is more difficult than expected, I try harder to achieve it.

CPCa (Compensatory Primary Control: Sub-category A) 4. When I get stuck on an academic task, I don't hesitate to ask others for advice. 12. To strive for better academic results, I don't mind taking the initiative to get help from others. 20. With a view to attaining higher excellence in academic study, I am willing to seek advice from others. 4

The item numbers stated in this appendix correspond to those of the questionnaire applied in the pre-deadline situation of the present study.

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Wan-chi Wong, Yin Li and Ji-Liang Shen 27. I ask others for help when I can not solve an academic problem by myself. 39. When my pursuit of further study is obstructed, I try to get help from others.

CPCb (Compensatory Primary Control: Sub-category B) 2. When I can no longer make progress in my academic study, I look for new ways to reach my goal. 15. When I can no longer make any progress in my academic study, I take reference of others' methods in attaining my goal. 22. When I am dissatisfied with my academic progress, I try to learn about more effective ways of studying. 29. When I am not able to solve an academic problem, I rely on any possible ways, even if they are unfamiliar to me. 31. When I encounter difficulties in my academic pursuit, I try to think of other ways of reaching my goal, even if they are unusual.

SSC (Selective Secondary Control) 8. Once I have decided on achieving good academic results, I remind myself to avoid anything that could distract me. 13. Having decided on an academic goal, I keep in mind its benefits. 21. Having set an academic goal, I remind myself that it was the right decision. 26. Having set a learning goal for myself, I keep in mind that I have the abilities to achieve it. 35. For academic goals that are difficult to achieve, I keep in mind how proud I will feel when I reach them.

CSCa (Compensatory Secondary Control: Sub-category A) 9. When things don't work out for me in my academic study, I tell myself that it was just bad luck. 18. When I get unsatisfactory examination results, I console myself by thinking about other areas where I had more success. 25. When I get into a difficult situation in my academic study, I remind myself that I am better off than other people in many ways. 32. When I fail to attain a learning goal, I tell myself that the goal was too difficult to achieve. 36. When I fall through on my academic study, I tell myself that it wasn't my fault.

CSCb (Compensatory Secondary Control: Sub-category B) 3. When I fall through on academic pursuit, I remind myself that academic achievement is not everything there is in life. 11. When my pursuit of further study is obstructed, I will aim for a career which does not require a success in the examination.

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23. When I know that it is impossible to reach an academic goal, I can let go of it. 30. When the academic pursuit becomes too difficult, I can put it out of my thoughts. 37. When I fail to attain an academic goal, I try to set an academic or vocational goal that is less difficult to achieve.

OG (General Optimization) 1. Knowledge and skills that I can use in different areas are more useful than those I can solely use in a specific area. 7. It is important for me to be active in not just one area of life, but in several different ones. 17. I always need to have something to fall back on in case what I am working on falls through. 28. I don't waste my time struggling with problems if it uses up energy I need for more important things. 40. I avoid becoming too narrow in my interests, so that I can switch to something else if I need to.

OA (Optimization in the Domain of Academic Achievement) 6. It is important for me that a new academic goal can be pursued in the long run. 14. I adjust my goal for the sake of academic development. 24. At the present stage, I put as much effort as possible to achieve good academic results. 34. I pursue new academic goals when the time is right for me. 38. I invest my time in developing skills that can be used in different academic arenas.

APPENDIX B The Factor Structure of Control Strategies among the Candidates for the University Entrance Examination in the Pre-deadline Situation (n=666)

Factor Loadings Response Items Q5 SPC Q10 SPC Q16 SPC Q19 SPC Q33 SPC Q8 SSC

Factor 1

Factor 2

Factor 3

Factor 4

0.66 0.74 0.72 0.52 0.57 0.73

Factor 5

Mean per Item 3.89 3.67 3.88 4.49 3.69 3.68

SD

0.97 1.01 1.04 0.72 0.92 1.08

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Wan-chi Wong, Yin Li and Ji-Liang Shen Appendix B (Continued)

Factor Loadings Response Factor 1 Items Q13 SSC Q21 SSC Q26 SSC Q35 SSC Q4 CPCa 0.58 Q12 CPCa 0.71 Q20 CPCa 0.72 Q27 CPCa 0.78 Q39 CPCa 0.61 Q2 CPCb Q15 CPCb Q22 CPCb Q29 CPCb Q31 CPCb Q9 CSCa Q18 CSCa Q25 CSCa Q32 CSCa Q36 CSCa Q3 CSCb Q11 CSCb Q23 CSCb Q30 CSCb Q37 CSCb

Factor 2

Factor 3

Mean per Item

SD

0.65

3.04 4.04 4.29 3.94 3.35 3.61

1.15 1.01 0.87 0.96 1.12 1.00

0.74

3.72

0.98

3.05 2.80 2.57

1.16 1.14 1.10

3.02

1.27

2.97 2.77

1.20 1.14

Factor 4

Factor 5

0.76 0.74 0.66 0.64

Note: Factor loadings greater than 0.50 are reported here.

0.64 0.62

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APPENDIX C The Factor Structure of Control Strategies among the Candidates for the University Entrance Examination in the Post-deadline Situation (n=305) Factor Loadings Response Items Q6 SPC Q13 SPC Q22 SPC Q29 SPC Q34 SPC Q4 SSC Q10 SSC Q18 SSC Q26 SSC Q33 SSC Q2 CPCa Q16 CPCa Q23 CPCa Q32 CPCa Q39 CPCa Q7 CPCb Q14 CPCb Q19 CPCb Q28 CPCb Q36 CPCb Q3 CSCa Q15 CSCa Q21 CSCa Q30 CSCa Q40 CSCa Q8 CSCb Q11 CSCb Q17 CSCb Q25 CSCb Q37 CSCb

0.73 0.71 0.71 0.73 0.59

Mean per Item 3.78 3.79 3.60 3.60 4.30 3.76

0.96 0.99 0.93 0.95 0.80 1.00

0.51

4.04

0.89

3.54 3.86 3.14

1.03 1.01 1.01

3.69 4.01 3.34

0.98 0.90 0.92

0.57 0.83

3.21 3.61 3.23 2.22 2.24 2.88 2.78 2.55

0.99 0.90 0.93 0.85 0.98 1.05 1.03 0.92

0.67

2.89

1.07

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

0.70

0.64 0.65 0.72 0.83 0.83 0.72 0.61 0.74 0.61

Note: Factor loadings greater than 0.50 are reported here.

0.77 0.68 0.67 0.57

SD

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APPENDIX D The Factor Structure of Control Strategies among the TOEFL Candidates in the Predeadline Situation (n=219)

Factor Loadings Response Items Q5 SPC Q10 SPC Q16 SPC Q19 SPC Q33 SPC Q8 SSC Q13 SSC Q21 SSC Q26 SSC Q35 SSC Q4 CPCa Q12 CPCa Q20 CPCa Q27 CPCa Q39 CPCa Q2 CPCb Q15 CPCb Q22 CPCb Q29 CPCb Q31 CPCb Q9 CSCa Q18 CSCa Q25 CSCa Q32 CSCa Q36 CSCa Q3 CSCb Q11 CSCb Q23 CSCb Q30 CSCb Q37 CSCb

Factor 1

Factor 2

Mean per Item 4.24

0.80

0.74

3.95 4.47 3.88

1.05 0.69 0.82

0.79 0.69

3.84 3.99 4.27

1.04 0.93 0.76

3.45 4.04 4.31 4.08 3.59

1.06 0.86 0.73 0.80 1.07

3.88

0.89

2.42 3.32 3.15 2.67 2.49

1.01 1.18 1.04 0.99 1.01

2.95 2.78 2.93

1.16 0.99 0.98

Factor 3

Factor 4

Factor 5

0.58

0.74 0.59

0.73 0.58 0.68 0.79 0.73 0.60

0.52

Note: Factor loadings greater than 0.50 are reported here.

0.63 0.76 0.66 0.69 0.61

0.62 0.61 0.53

SD

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APPENDIX E The Factor Structure of Control Strategies among the TOEFL Candidates in the Postdeadline Situation (n=157)

Factor Loadings Response Items Q6 SPC Q13 SPC Q22 SPC Q29 SPC Q34 SPC Q4 SSC Q10 SSC Q18 SSC Q26 SSC Q33 SSC Q2 CPCa Q16 CPCa Q23 CPCa Q32 CPCa Q39 CPCa Q7 CPCb Q14 CPCb Q19 CPCb Q28 CPCb Q36 CPCb Q3 CSCa Q15 CSCa Q21 CSCa Q30 CSCa Q40 CSCa Q8 CSCb Q11 CSCb Q17 CSCb Q25 CSCb Q37 CSCb

Mean per Item 4.04 4.04 4.06 3.87 4.38 3.89 3.89 4.09 4.01 3.68 3.89 3.33

0.78 0.91 0.84 0.86 0.67 0.97 0.93 0.74 0.83 0.89 0.85 0.97

3.76 4.02 3.72 3.66 3.45 3.78 3.49

0.84 0.86 0.74 0.96 0.96 0.73 0.90

0.78

2.50 3.17 3.13 2.66

0.90 0.98 1.04 0.87

0.64 0.52

2.84 2.92 2.94 3.22

0.99 1.05 0.96 0.99

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6

0.57 0.77 0.82 0.75 0.68

0.61

0.57 0.74 0.70 0.61 0.76 0.63

0.53 0.77 0.75 0.89 0.81 0.54

0.55 0.53

0.71 0.57 0.77 0.66 0.80 0.61 0.59 0.72

0.56 0.74 0.67

Note: Factor loadings greater than 0.50 are reported here.

SD

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APPENDIX F The Factor Structure of Control Strategies among the High School Students (n=1085)

Factor Loadings Response Items Q5 SPC Q10 SPC Q16 SPC Q19 SPC Q33 SPC Q8 SSC Q13 SSC Q21 SSC Q26 SSC Q35 SSC Q4 CPCa Q12 CPCa Q20 CPCa Q27 CPCa Q39 CPCa Q2 CPCb Q15 CPCb Q22 CPCb Q29 CPCb Q31 CPCb Q9 CSCa Q18 CSCa Q25 CSCa Q32 CSCa Q36 CSCa Q3 CSCb Q11 CSCb Q23 CSCb Q30 CSCb Q37 CSCb

Factor 1

Factor 2

Factor 3

Mean per Item 3.86 3.74 3.94 4.43 3.78 3.68

1.02 1.00 1.02 0.81 0.97 1.15

4.05 4.14 4.04 3.16 3.93 4.11 3.74 3.38

0.97 0.93 1.07 1.16 1.09 1.01 1.08 1.16

3.23 3.64 3.24 3.15 2.44 3.03 2.79 2.46 2.39

1.13 1.02 1.14 1.09 1.18 1.23 1.19 1.08 1.15

0.56

2.12

1.21

0.68

2.46

1.14

Factor 4

Factor 5

0.56 0.67 0.71 0.66 0.73 0.57 0.61 0.56 0.52

0.52

0.63 0.70 0.73 0.78 0.65 0.52

0.54 0.57 0.79 0.80

0.58

0.57 0.71 0.73 0.70 0.61

Note: Factor loadings greater than 0.50 are reported here.

SD

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REFERENCES Elder, G.H., Jr. (1974). Children of the Great Depression. Chicago, IL: University of Chicago Press. Elder, G.H., Jr., and Caspi, A. (1990). Studying lives in a changing society: Sociological and personological explorations. In A. Rabin, R. Zucker, R. Emmons, and S. Frank (Eds.), Studying persons and lives (pp. 201-247). New York, NY: Springer. Folkman, S., Lazarus, R.S., Dunkel-Schetter, C., DeLongis, A., and Gruen, R. (1986). The dynamics of stressful encounter: Cognitive appraisal, coping, and encounter outcomes. Journal of Personality and Social Psychology, 50(5), 992-1003. Gould, S.J. (1999). A critique of Heckhausen and Schulz’s (1995) life-span theory of control from a cross-cultural perspective. Psychological Review, 106(3), 597-604. Heckhausen, H. (1987a). Bruchstrueke fuer eine vorlaeufige Intentions- und Volitionstheorie [Fragments towards a preliminary theory of intention and volition]. Unpublished manuscript, Max-Planck-Institut fuer psychologische Forschung, Munich, Germany. Heckhausen, H. (1987b). Wuenschen, Waehlen, Wollen [Wish, choice, intention]. In H. Heckhausen and P.M. Gollwitzer (Eds.), Jenseits des Rubikon: Der Wille in den Humanwissenschaften (pp. 3-9). Berlin, Germany: Springer. Heckhausen, H. (1989). Motivation und Handeln [Motivation and action] (2nd ed.). Berlin, Germany: Springer. Heckhausen, H., and Kuhl, J. (1985). From wishes to action: The dead ends and short cuts on the long way to action. In M. Frese and J. Sabini (Eds.), Goal directed behavior: The concept of action in psychology (pp. 134-159). Hillsdale, NJ: Lawrence Erlbaum Associates. Heckhausen, J. (1994). Entwicklungsziele und Kontrollueberzeungen Ost- und Westberliner Erwachsener [Developmental goals and control beliefs of East and West Berliners]. In G. Trommsdorff (Ed.), Psychologische Aspekte des sozio-politischen Wandels in Ostdeutschland [Psychological aspects of sociopolitical change in East Germany] (pp. 124-133). Berlin, Germany: de Gruyter. Heckhausen, J. (1997). Developmental regulation across adulthood: Primary and secondary control of age-related challenges. Developmental Psychology, 33(1), 176-187. Heckhausen, J. (1999). Developmental regulation in adulthood. Age-normative and sociostructural constraints as adaptive challenge. Cambridge, UK: Cambridge University Press. Heckhausen, J., and Schulz, R. (1993). Optimization by selection and compensation: Balancing primary and secondary control in life-span development. International Journal of Behavioral Development, 16(2), 287-303. Heckhausen, J., and Schulz, R. (1995). A life-span theory of control. Psychological Review, 102(2), 284-304. Heckhausen, J., and Schulz, R. (1998). Developmental regulation in adulthood: Selection and compensation via primary and secondary control. In J. Heckhausen and C.S. Dweck (Eds.), Motivation and self-regulation across the life span (pp. 50-77). New York, NY: Cambridge University Press.

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Heckhausen, J., and Schulz, R. (1999). The primacy of primary control is a human universal: A reply to Gould’s (1999) critique of life-span theory of control. Psychological Review, 106(3), 605-609. Heckhausen, J., Schulz, R., and Wrosch, C. (1998). Developmental regulation in adulthood: Optimization in primary and secondary control – a multiscale questionnaire. Technical Report, Max-Planck Institute for Human Development and Education, Berlin, Germany. Heckhausen, J., Wrosch, C, and Fleeson, W. (2001). Developmental regulation before and after a developmental deadline: The sample case of “biological clock” for child-bearing. Psychology and Aging, 16(3), 400-413. Higgins, E.T. (1996). The “Self digest”: Self-knowledge serving self-regulatory functions. Journal of Personality and Social Psychology, 71(6), 1062-1083. Holahan, C.J., Moos, R.H., and Schaefer, J.A. (1996). Coping, stress resistance, and growth: Conceptualizing adaptive functioning. In M. Zeidner and N.S. Endler (Eds.), Handbook of coping. Theory, research, applications (pp. 24-43). New York, NY: John Wiley and Sons. Lakatos, I. (1973/1999). Lectures on scientific method. In M. Motterlini (Ed.), For and against method (pp. 19-112). Chicago, IL: The University of Chicago Press. Lakatos, I. (1970/1999). Falsification and the methodology of scientific research programmes. In J. Worrall and G. Currie (Eds.), The methodology of scientific research programmes (pp. 8-101). Cambridge, UK: Cambridge University Press. Rothbaum, F., Weisz, J.R., and Snyder, S.S. (1982). Changing the world and changing the self: A two-process model of perceived control. Journal of Personality and Social Psychology, 42(1), 5-37. Seginer, R., Trommsdorff, G., and Essau, C. (1993). Adolescent control beliefs: Crosscultural variations of primary and secondary orientations. International Journal of Behavioral Development, 16(2), 243-260. Watson, D. (1988). The vicissitudes of mood measurement: Effects of varying descriptors, time frames, and response formats on measure of positive and negative affect. Journal of Personality and Social Psychology, 55(1), 128-141. Watson, D., Clark, L.A., and Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. Weisz, J.R. (1983). Can I control it? The pursuit of veridical answers across the life span. In P.B. Baltes and O.G. Brim, Jr. (Eds.), Life-span development and behavior (pp. 233-300). New York, NY: Academic Press. Weisz, J.R. (1986). Understanding the developing understanding of control. In M. Perlmutter (Ed.), Cognitive perspectives on children’s social and behavioral development. The Minnesota symposia on child psychology, Volume 18 (pp. 219-278). Hillsdale, NJ: Lawrence Erlbaum Associates. Wrosch, C., and Heckhausen, J. (1999). Control processes before and after passing a developmental deadline: Activation and deactivation of intimate relationship goals. Journal of Personality and Social Psychology, 77(2), 415-427. Wrosch, C., Heckhausen, J., and Lachman, M.E. (2000). Primary and secondary control strategies for managing health and financial stress across adulthood. Psychology and Aging, 15(3), 387-399.

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Wrosch, C., Schulz, R., and Heckhausen, J. (2002). Health stresses and depressive symptomatology in the elderly: The importance of health engagement control strategies. Health Psychology, 21(4), 340-348. Yamaguchi, S. (2001). Culture and control orientation. In D. Matsumoto (Ed.), The handbook of culture and psychology (pp. 223-243). Oxford, UK: Oxford University Press.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 7

WRITING YOUR WAY TO HEALTH? THE EFFECTS OF DISCLOSURE OF PAST STRESSFUL EVENTS IN GERMAN STUDENTS Lisette Morris, Annedore Linkemann and Birgit Kröner-Herwig* Clinical Psychology and Psychotherapy University of Göttingen, Germany

ABSTRACT In 1986 Pennebaker and Beall published their renowned study on the long-term beneficial health effects of disclosing traumatic events in 4 brief sequential writing sessions. Their results have been confirmed in various studies, but conflicting results have also been reported. The intent of our study was to replicate the experiments from Pennebaker and Beall (1986), Pennebaker et al. (1988), and Greenberg and Stone (1992) using a German student sample. Additionally, essay variables that point to the emotional processing of events (e.g., depth of self-exploration, number of negative/positive emotions, intensity of emotional expression) were examined as potential mechanisms of action. Trait measures of personality which could moderate the personal consequences of disclosure (alexithymia, self-concealment, worrying, social support) were also assessed. In a second study the experimental condition (disclosure) was varied by implementing “coping” vs. “helping” instructions as variations of the original condition. Under the coping condition participants were asked to elaborate on what they used to do, continue to do, or could do in the future to better cope with the event. Under the helping condition participants were asked to imagine themselves in the role of a adviser and elaborate on what they would recommend to persons also dealing with the trauma in order to better cope with the event. The expected beneficial effects of disclosure on long-term health (e.g., physician visits, physical symptoms, affectivity) could not be corroborated in either the first or the second study. None of the examined essay variables of emotional *

Prof. Dr. B. Kroener-Herwig; Georg-Elias-Mueller-Institut für Psychologie; Dep. Clinical Psychology and Psychotherapy; Gosslerstr. 14; D - 37073 Goettingen; Email: [email protected]

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Lisette Morris, Annedore Linkemann and Birgit Kröner-Herwig processing and only a single personality variable was able to explain significant variance in the health-related outcome variables influence. Nevertheless, substantial reductions in posttraumatic stress symptoms (e.g., intrusions, avoidance, arousal), were found in both experiments. These improvements were significantly related to essay variables of emotional expression and self-exploration and were particularly pronounced under the activation of a prosocial motivation (helping condition). Repeated, albeit brief, expressive writing about personally upsetting or traumatic events resulted in an immediate increase in negative mood but did not lead to long-term positive health consequences in a German student sample. It did, however, promote better processing of stressful or traumatic events, as evidenced by reductions in posttraumatic stress symptoms. The instruction to formulate recommendations for persons dealing with the same trauma seems more helpful than standard disclosure or focusing on one's own past, present, and future coping endeavours. Overall, expressive writing seems to be a successful method of improving trauma processing. Determining the appropriate setting (e.g., self-help vs. therapeutic context) for disclore can be seen as an objective of future research.

INTRODUCTION Pennebaker & Beall’s (1986) study published under the title “Confronting a traumatic event: Towards an understanding of inhibition and disease” caused quite a sensation among clinical psychologists and incited numerous replication studies, primarily in the USA. In their original study, the authors asked students to write about personally upsetting or traumatic experiences from one of the following three perspectives: emphasising feelings without describing the actual experience (trauma-emotion condition), emphasising factual aspects of the experience without mentioning feelings (trauma-fact condition), or describing both the experience and the associated feelings (trauma-combination condition). In a control condition, students were instructed to write in an factual manner about different trivial topics (e.g., their living room, the shoes they were wearing). In all four conditions, writing took place on 4 consecutive days for a period of 15 minutes per day. The physical symptoms and mood of the students were assessed directly prior to and following writing and a number of health-related variables were assessed at follow-up 4 to 6 months later. Short-term effects of writing were not found for physical symptoms, but significant effects were found, as expected, for mood. Ss in all three trauma conditions reported a deterioration of mood subsequent to writing, whereas controls reported improved mood. The most important effect, however, was the significantly better health status found in the trauma-combination condition at follow-up. Ss in both the trauma-emotion and traumacombination conditions reported significant reductions of health problems (4-month) relative to the other conditions, while significantly fewer days with illness-related restriction of activity (4-month) and fewer visits to the university health care centre (6-month follow-up) were found only in the trauma-combination condition. The authors concluded that written disclosure of traumatic or stressful experiences in a manner that combines emotional expression and factual description is beneficial to health, at least in a sample of young students. Thus, it seemed that with the disclosure paradigm a

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simple intervention capable of enhancing physical, and perhaps even psychological, health had been found. Numerous replication studies conducted by Pennebaker and associates as well as by independent researchers followed and various modifications were made to the original paradigm. In some studies Ss were asked to write about specific events like job loss (Spera et al, 1994), entering college (Pennebaker et al., 1990; Pennebaker & Francis, 1996) or suffering from rheumatic disease (Kelly et al, 1997). In some of the studies disclosure took place not through writing but by oral report (e.g., Pennebaker et al. 1987; Donnelly & Murray, 1991; Esterling et al, 1994) or bodily expression (Krantz & Pennebaker, 1996). Additionally, the length of writing sessions was varied (e.g., up to 45 minutes by Schoutrop et al, 1996), as was the number of sessions (1 session by Greenberg et al, 1996; 5 sessions by Spera et al, 1994). Nearly all early studies corroborated the negative short-term effect of expressive writing on mood (e.g., Petrie et al, 1995; Francis & Pennebaker, 1992, Greenberg et al, 1996) and many further studies found the postulated short-term increase in physical symptoms (e.g., Pennebaker et al, 1988; Greenberg & Stone, 1992; Booth et al, 1997). The long-term beneficial effects on physical health were supported by numerous studies which documented improvements ranging from reductions in health care utilization (e.g., Pennebaker et al, 1990, Pennebaker & Francis, 1996, Pennebaker et al, 1988) to improved immunological parameters (e.g., Esterling et al, 1994; Pennebaker et al, 1988; Lutgendorf et al, 1994; Petrie et al, 1995). In other studies, however, expressive writing did not positively affect subjective health measures (e.g., Petrie et al, 1995; Spera et al, 1994; Murray & Segal, 1994). Results concerning the long-term effect of disclosure on psychological well-being were also contradictory. Pennebaker et al’s (1988) results as well as the findings from Schoutrop et al (1996) pointed to long-term improvements of mood following writing. No effect, however, was seen by Greenberg and Stone (1992) and an unexpected long-term increase in negative affect was reported by Greenberg et al (1996). Overall, however, the studies seemed to support the theoretical model formulated by Pennebaker (1988, 1989) on inhibition and confrontation. Based on the tenet that people have an innate desire to express their feelings and to communicate significant experiences, Pennebaker postulated that hindered interpersonal expression, due to feelings of guilt or shame or feared negative response of others, leads to negative physical and psychological consequences. Inhibition was defined by Pennebaker (1989) as the process of consciously holding back or otherwise suppressing thoughts, feelings and behaviours. It entails physiological work and leads to an activation of the autonomic nervous system. In the long run, it places cumulative stress on the body, increasing the likelihood of stress-related physical and psychological symptoms or illness. Confrontation is seen as the opposite of inhibition. It is the process of actively facing significant personal experiences, while acknowledging and dealing with the associated feelings and thoughts. Confronting significant experiences makes the physiological work of suppressing associated thoughts and feelings obsolete and can, via reductions in overall stress level, negate the long-term effects of inhibition on physical health and psychological well-being. Later the focus of attention was shifted more to the cognitive level (Francis & Pennebaker, 1992; Pennebaker et al., 1997). From this perspective, inhibition is seen as an impediment to the emotional processing of traumatic experiences, a hindrance to their assimilation and resolution. The inadequately processed experiences maintain their

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distressfulness as they resurface in the form of rumination or associated cognitive symptoms. Written or verbal confrontation, which entails the translation of traumatic memory into language, negates inhibition and works to promote the understanding and assimilation of the experiences, thereby facilitating their closure. The relevance of the reorganisation of traumatic memory and its integration into the autobiographical memory and self-concept echoes back to Horowitz (1976) and coincides with current models of the processes underlying confrontation therapy in posttraumatic stress disorder (Ehlers, 2000). As the vast majority of the early studies were conducted in the USA and Canada, Petrie et al (1995), Paez et al. (1999), and Schoutrop et al (1996) are several exceptions, we were interested in the effect of disclosure on a German sample. The intent of our experiment was to replicate the studies from Pennebaker and Beall (1986), Pennebaker et al (1988) and Greenberg and Stone (1992) in order to find out whether we would achieve effects of disclosure comparable to those in the USA. Furthermore, we intended to study the disclosure process more closely by assessing relevant essay characteristics (e.g., frequency of positive and negative emotional expressions) and examining their influence on the short- and longterm effects of disclosure. A number of personality variables were also examined as potential moderators of the effects of disclosure. Two studies were conducted, each on a different sample of students. In the first study, standard disclosure and control conditions were implemented. In the second study, two new variations of expressive writing were examined, one instructing the Ss to focus on coping endeavours and a second emphasising a “helping” perspective (see Methods: Study II).

STUDY I: METHODS The design was based on the studies from Pennebaker and Beall (1986), Pennebaker et al (1988), and Greenberg and Stone (1992) and employed analogous assessment instruments. A two factorial control group design with repeated measures was implemented in accordance with Pennebaker et al (1988). In the disclosure condition, Ss were instructed to write about a very upsetting or traumatic personal experience in their past and to emphasise revealing their deepest thoughts and feelings in their essays, while control Ss were asked to write about their daily routine and time management in an detailed and factual manner. A total of 3 writing sessions were held, each lasting 20 minutes. Long-term effects of disclosure were assessed 6 weeks after writing in accordance with Pennebaker et al, (1988). The sample consisted of 61 students, who were randomly assigned to one of the two conditions. Because of our focus on variables which could potentially moderate disclosure effects, a greater number of Ss were assigned to the experimental condition (40 vs. 21 in the control condition). The following instruments, commonly employed in disclosure research, were used (in German translation) to assess the short-term effects of expressive writing (pre - post comparison): • •

Pennebaker Physical Symptom Scale (PPSS) Pennebaker Negative Mood Scale (PNMS)

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Long-term effects (pre - 6-week follow-up comparison) were assessed using the following common instruments / measures: • Pennebaker Inventory of Limbic Languidness (PILL) • self-reported number of illness days • self-reported number of days with illness-related activity restriction • self-reported number of illness-related physician visits • Positive and Negative Affect Schedule (PANAS, Watson, Clark & Telegen, 1988) • subjective rating of the long-term effect of writing. As an additional measure of long-term outcome, the self-report version of the PTSD Symptom Scale (PSS-SR, Foa et al, 1993) was administered to the Ss of the disclosure group. The following essays characteristics, posited as potential mechanisms of action, were assessed in the disclosure condition: • • •

relative frequency of negative emotional expressions (Negative Affect Scale, Westbrook, 1976) relative frequency of positive emotional expressions (Positive Affect Scale) relative frequency of emotional expressions on the whole.

Additionally, the intensity of both positive and negative emotional expression in the essays was rated by independent judges on a 6-point scale (scale anchors taken from SchmidtAtzert, 1981). The judges also rated the depth of self-exploration exhibited in the essays, yielding the variables average depth of self-exploration and change in self-exploration from day 1 to day 3. Self-exploration, which has proven its relevance for the course and efficacy of client-centred therapy (German Scale: Tausch, 1970), seemed a fitting construct for disclosure research. Finally, Ss in both conditions were asked to rate how emotionally revealing and personal their essays were. Four personality variables were selected for examination as potential moderators of the short- and long-term effects of disclosure on the basis of their theoretical fit with Pennebaker’s theory of inhibition and confrontation. The following instruments were employed for their assessment in the German version: • • • •

Self-Concealment Scale (SCS, Larson & Chastain, 1990) Toronto Alexithymia Scale (TAS, Taylor et al, 1985) Penn State Worry Questionnaire (PSWQ, Meyer et al, 1990) Social Support Questionnaire (F-SozU, Fydrich et al, 1987)

Finally, Ss in the disclosure group were requested to rate the extent to which the experience was personally upsetting at the time of its occurrence and on the first day of writing. The participants were recruited via placards and handouts distributed in university facilities that provided information about the research project and its aim of tapping “physiological responses to writing about personal experiences” (Blood pressure and other physiological parameters were assessed during the experiment, but will not be reported here). Ss received a postpaid monetary incentive or partial course credit for participation in the

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study. Anonymity of personal data and essays was assured and enforced through strict adherence to data protection procedures. An offer of free counseling was made for any participants who felt emotionally shaken or upset after writing.

STUDY I: RESULTS A total of 39 female and 22 male Ss with a mean age of 23 years participated in the study (see tab. 1). Half of the Ss were psychology majors. Under the predetermined quota of 2:1 in favour of the experimental group, Ss were randomly assigned to the conditions. The Ss in the two conditions did not differ significantly with regard to sex or age. Table 1. Characteristics of study I sample Condition

Variable

Disclosure (n=40*) 23.9 (4.1)

Control (n=21) 23.3 (4.0)

23 (57.5%)

16 (76%)

Psychology

47,5%

52%

Business/ Economics

32.5%

23.8%

5%

14.3%

15.5%

9.9%

Age (m,sd) Sex (n, % female) Major

Social sciences Other * 1 drop-out at follow-up

As a manipulation check subjects were asked to rate how personal and how emotionally revealing their essays were. Ss in the disclosure group gave significantly higher ratings with regard to both aspects (personal: mdisclosure = 5.71 (1.12), mcontrol = 2.79 (1.03), p < .001; emotionally revealing: mdisclosure = 5.25 (0.95), mcontrol = 1.86 (.85), p < .001). Analysis of the essay contents in the disclosure group corroborated the personal nature of the essays and revealed that Ss wrote about a broad spectrum of life events (tab. 2). The Ss rated the experiences described in their essays as quite upsetting at the time they occurred (m=5.8, sd=1.5, scale 1-7), though somewhat less so at the time of writing (m=4.0, sd=1.4). Nevertheless, the latter rating indicates that Ss wrote about experiences that continued to have a negative impact in their lives. Inspection of the essays of the control group revealed compliance with the writing instructions. The first hypothesis tested relates to short-term effects of writing. The disclosure group was expected to show an increase in negative mood and physical symptoms following writing (see tab. 3, mean of all sessions). The hypothesis was statistically supported for negative mood, but not for physical symptoms.

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Table 2. Contents of essays in study I disclosure group Problems with boyfriend / girlfriend Severe illness or death of family member or close friend Own severe illness or deformity Problems with friends or peers Problems with family members Separation or divorce of parents Sexual or physical abuse Stressful events (not interpersonal) Major personal failure Other

15% 15% 12% 12% 10% 7% 7% 7% 5% 10%

Table 3. Short-term effects of writing (study I): Item means (m), standard deviation (sd), and results from analysis of variance (interaction terms*) Short-term effects Variables 1. PPSS (m,sd) α = 0.59+ 2. PNMS (m,sd) α = 0.81 VA(1)*: F (1,59) = 0.62, p > .10 VA(2)*: F (1,59) = 12.70, p= .001

Period pre post pre post

Condition Disclosure Control 1.63 (.40) 1.58 (.39) 1.65 (.43) 1.54 (.56) 1.87 (.64) 1.93 (.88) 2.05 (.74) 1.73 (.79)

+

Cronbach's alpha * period x condition

The second hypothesis related to long-term effects and postulated an improvement in physical health in the disclosure group. Results did not confirm the hypothesis. Ss in disclosure group failed to show a significant improvement relative to the control group in any of the health-related variables (see tab. 4). On the contrary, inspection of means revealed deteriorations in 2 of the 4 health-related variables, albeit in both the disclosure and control condition. The third set of hypotheses relates to the expected long-term improvement of psychological well-being in the disclosure group, predicting more positive and less negative affectivity relative to the controls, and also predicting a reduction of posttraumatic stress symptoms within the disclosure group. The hypothesis cannot be confirmed regarding affectivity. However, significant reductions in PSS-SR scales indicate a decreased presence of maladaptive processing 6 weeks after writing. Both re-experiencing and autonomic arousal are reduced (effect sizes d = .72 and .54, respectively), as are posttraumatic stress symptoms on the whole (d = .56) Asked about long-term positive and negative effects of writing at follow-up, Ss in the disclosure group rate both effects to be stronger than the controls (positive: mdisclosure = 2.43 (1.32), mcontrol = 1.57 (.98), t-test: p = 0.006; negative mdisclosure = 1.55 (1.09), mcontrol =1.0 (1.0); t-test: p = 0.003).

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Table 4. Long-term effects of writing (study I): Item means (m), standard deviation (sd), and results from analysis of variance (interaction terms*) and t-tests

pre follow-up pre follow-up pre follow-up pre follow-up

Condition Disclosure Control 1.03 (0.46) 1.11 (0.37) 0.99 (0.51) 1.07 (0.44) 0.43 (0.90) 0.48 (1.25) 0.40 (1.08) 0.52 (0.98) 2.63 (3.83) 2.55 (3.67) 5.75 (17.27) 3.00 (6.60) 2.30 (3.31) 1.93 (2.67) 4.03 (9.42) 3.86 (7.02)

pre follow-up pre follow-up

2.05 (0.73) 1.90 (0.66) 3.37 (0.56) 3.15 (0.56)

pre

0.92(0.64)

follow-up pre follow-up pre follow-up pre follow-up

0.54 (0.45) 0.81 (0.69) 0.70 (0.65) 0.78 (0.58) 0.54 (0.56) 0.83 (0.55) 0.61 (0.53)

Health 1. PILL (m,sd) α = 0.91 2. Illness-related visits to physician+ (m,sd) 3. Days with illness-related restriction of activity+ (m,sd) 4. Illness days+ (m,sd) Affectivity 5. PANAS: negative (m,sd) α = 0.89 6. PANAS: positive (m,sd) α = 0.82 VA(1) *: F (1,59) = .00, p > .10 VA(2) *: F (1,59) = .04, p > .10 VA(3) *: F (1,59) = .48, p > .10 VA(4) *: F (1,59) = .01, p > .10 VA(5) *: F (1,59) = .47, p > .10 VA(6) *: F (1,59) = 1.87, p > .10 PSS-SR § 7. Re-experiencing (m, sd)

8. Avoidance (m, sd) 9. Arousal (m, sd) 10. Total severity score

Period

1.78 (0.65) 1.75 (0.67) 3.17 (0.61) 3.14 (0.71)

Statistics df=38 t=4.52 p=.000** t=1.16 p=.127 t=3.38 p=.001** t=3.50 p=.001**

* Period x condition + Mean frequency § Only assessed in disclosure group

All essay variables were examined for their influence on short- or long-term outcome. Only 4 of the 108 correlations examined reached significance (p < .001, see tab. 5). The results indicate that autonomic arousal is reduced to a larger extent when essays include more positive emotions and when the positive emotions are of greater intensity. Reductions in avoidance and total posttraumatic stress symptoms are greater, when self-exploration increases from day 1 to day 3. The moderating effect of personality variables on short- and long-term outcome was also examined. Of the 48 correlation coefficients, only one reached significance (tab. 5): The long-

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term reduction of physical symptoms was more attenuated, the greater the extent of selfconcealment. In a last step of analysis, the influence of personality variables on the manner of writing, as assessed with the essay variables, was examined. The only personality variable that correlated significantly with the examined essay characteristics was “worrying”. Essays written by habitual worriers contained relatively more emotional expressions on the whole (r = .435, p = .005) and more negative emotional expressions in particular (r = .511, p = .001) than non-worriers’ essays. Also, the stronger the tendency to worry, the deeper the selfexploration exhibited in the essays (r = .378, p = .016) Table 5. Significant correlations (p ≤ 0.01) between moderator variables (essay or personality variables) and outcome variables (short- and long-term) in the disclosure group (study I) Moderator variable Frequency of positive emotions in essay Intensity of positive emotions in essay Increasing self-exploration day 1 to day 3

Increasing self-exploration day 1 to day 3 Self-Concealment

Outcome Reduced arousal (PSS-SR) Reduced arousal (PSS-SR) Reduced posttraumatic stress symptoms (PSS-SR) Reduced avoidance (PSS-SR) Physical symptoms (PILL)

Correlation: r .452 (p = .002) .421 (p = .004) .424 (p = .004)

.376 (p = .009) -.366 (p = .01)

STUDY II: METHOD Because of the unexpected negative outcome regarding the postulated long-term beneficial effect of expressive writing on physical health, a second study was conducted to examine whether disclosure instructions modified to promote self-efficacy and coping would produce more positive effects. Therefore, in addition to the standard disclosure condition, two further experimental conditions, “coping” and “helping”, were implemented, in which modifications were made to the writing instructions given on day 3. In the “coping” condition, Ss were instructed on to reflect upon what they have done in the past, continue to do, or could do in future to better cope with the traumatic experience they wrote about during the first 2 sessions. This instruction aimed at increasing Ss’ awareness of their past, present, and future coping behaviour and thereby at increasing their sense of self-efficacy in dealing with the traumatic experience. It was postulated that the instruction could elicit a constructive reappraisal of the experience which would, in turn, facilitate emotional resolution (see Murray et al, 1989). In the “helping” condition, Ss were asked to imagine themselves in the role of an adviser and to elaborate on what they would recommend to persons dealing with the same trauma they experienced in order to better cope with the event. Midlarsky & Kahana (1994) as well as Berking (1998) have presented data indicating that adopting a prosocial role can

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have positive cognitive and emotional consequences. A control condition analogous to study I was also implemented, in which Ss were asked to write about their daily routine and time management in a detailed and factual manner. 22 Ss were randomly assigned to each of the four conditions. This time a different set of instruments, selected based on the psychometric quality of the validated German versions, was used for the assessment of long-term effects. The circumstance that the study I instruments were, for the most part, translations of questionnaires originally developed for Anglo-American samples and not yet psychometrically evaluated for German samples was seen as a limitation worthy of amelioration in study II. Physical symptoms (prior PILL) were assessed via the Complaints Schedule (Beschwerden-Liste, von Zerssen, 1976), affectivity (prior PANAS) through a validated German version of the Profile of Mood States (McNair et al, 1971), and PTSD symptoms via the tested German version of the Impact of Event Scale (Horowitz et al, 1979). The individual health-related items from study I (e.g., illness days) were implemented, as was a questionnaire scale tapping satisfaction with one's health (Fahrenberg et al, 1986). To assess the effect of writing on mood regulation, which is posited as one of the mechanisms underlying health improvement, the questionnaire “Generalized Expectancy for Negative Mood Regulation” (Catanzaro & Mearns, 1990, Catanzaro & Greenwod, 1994) was administered. Furthermore, an item assessing self-efficacy regarding coping with the critical event was added. The conductance of study II was similar to study I in all other aspects.

STUDY II: RESULTS The sample comprised a total of 84 Ss, the majority of which were female and whose average age varied in the four conditions between 21 and 24 years (see tab. 6). Four Ss dropped out of the study (i.e., did not return follow-up data). Like in study I, most of the participants were students majoring in psychology. No significant differences between groups were found with regard to sociodemographic variables. Analysis of the essay contents in the three experimental conditions (disclosure, coping, helping) indicates that Ss wrote about experiences similar to those in study I. Problems with boyfriend / girlfriend were, however, more frequently written about in study II, while problems with friends and peers, and own severe illness or deformity were less frequent than in study I. Two two-factorial analyses of variance (condition x period) on the short-term effects of writing showed significant differences between groups regarding physical symptoms (PPSS) and negative mood (PNMS, see tab. 7). A post-hoc Scheffé test revealed that this effect can be attributed to differences between the disclosure and control conditions: The disclosure group reported more physical symptoms and greater negative mood directly after writing. The postulated long-term effect of improvements in physical health could not be corroborated in this study. None of the analyses of variance on the health-related variables yielded significant interaction effects, reflecting the absence of health differences between the controls and the three experimental groups, in which the Ss had written in an emotionally expressive manner about traumatic experiences (see tab. 8).

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Table 6. Characteristics of study II sample

Age (m,sd)

Disclosure n = 20* 24.1 (5.7)

Condition Coping Helping n = 21 n = 22 21.8 (2.4) 22.2 (3.2)

Control n = 21 21.2 (2.6)

Sex (n, % female)

13 (65%)

14 (67%)

15 (64%)

14 (67%)

Psychology

50%

76.2%

45.5%

57.1%

Law

5%

4.8%

13.6%

19%

Other

35%

19.0%

40.9%

19.0%

Non-students

10%

Variable

Major

4.8%

* deviation from n = 22: drop-outs at follow-up

Table 7. Short-term effects of writing in study II: Item means (m), standard deviations (sd), and results from analysis of variance (interaction terms) and post-hoc Scheffé-tests

Variables

Period

Condition

1. PPSS (m,sd)

pre post

Disclosure 1.41 (.40) 1.64 (.40)

2. PNMS (m,sd)

pre post

1.56 (.64) 1.98 (1.05)

Coping 1.36 (.32) 1.35 (.37)

Helping 1.49 (.39) 1.54 (.39)

Control 1.60 (.57) 1.42 (.33)

1.67 (.97) 1.79 (1.16)

1.65 (.70) 1.72 (.78)

1.51 (.58) 1.41 (.48)

VA (1)* F (3,80)= 3.75, p = .014 VA (2)* F (3,80) = 4.16, p = .009 Post-hoc Scheffé (1): control / disclosure, p = .016 Post-hoc Scheffé (2): control / disclosure, p = .010

Analyses of variance conducted on the long-term effects of writing on affectivity and yielded significant differences between groups regarding depression, fatigue and vigour. A post-hoc Scheffé test revealed that this interaction reflects differences between the helping and coping conditions: Ss in the coping condition reported feeling less vigorous and more fatigued than Ss in the helping group. Analysis of variance of PTSD symptoms (IES) revealed a significant interaction effect for intrusion and a marginally significant interaction effect for avoidance. These effects can be attributed to the expected lack of change in the control group and reductions in intrusions and avoidance found in the disclosure and helping conditions, respectively. The post-hoc Scheffé test supported this interpretation (see tab. 8). Overall, the highest average effect on symptoms of posttraumatic stress was found in the helping group (d = .71), while the other experimental conditions yielded somewhat attenuated effects (disclosure: d = .52, coping: d = .43) and no change occurred in controls (d = .07).

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Table 8. Long-term effects of writing in study II: Means (m), standard deviations (sd), and results from analysis of variance (interaction terms) and post-hoc Scheffé-tests Variable

Period

Disclosure

Condition Coping Helping

Control

Health 1. Symptoms

2. Satisfaction with health 3. Visits to physician+ 4. Activity restriction+ 5. Illness days+

pre follow-up pre follow-up pre follow-up pre follow-up pre follow-up

0.77 (.43) 0.80 (.36) 2.91 (1.12) 2.89 (1.01) 0.05 (.22) 0.40 (1.57) 1.75 (3.16) 3.16 (6.83) 2.05 (4.57) 2.65 (6.47)

0.78 (.33) 0.77 (.49) 2.92 (1.23) 3.29 (1.29) 0.05 (.22) 0.10 (.44) 1.11 (1.70) 1.53 (2.32) 1.43 (2.01) 1.95 (4.77)

0.78 (.33) 0.65 (.39) 3.13 (.97) 3.24 (1.02) 0.14 (.35) 0.05 (.21) 0.77 (2.19) 0.86 (1.49) 1.45 (2.46) 0.77 (1.60)

0.84 (.42) 0.76 (.35) 3.02 (.96) 2.82 (.70) 0.33 (.73) 0.00 (.00) 1.19 (2.32) 0.91 (1.76) 2.19 (6.49) 0.71 (1.68)

pre follow-up pre follow-up pre follow-up prä follow-up

0.89 (.85) 0.81 (.63) 1.22 (.88) 1.36 (.80) (1.09) 1.10 (.96) 1.86 (.83) 1.47 (.79)

(.69) 1.23 (1.21) 1.07 (.67) 1.68 (.65) 0.94 (.71) 1.05 (.87) 1.85 (.70) 1.24 (.71)

0.86 (.69) 0.55 (.45) 1.22 (.72) 1.10 (.70) 0.77 (.51) 0.72 (.57) 1.49 (.79) 1.70 (.81)

1.10 (.65) 0.90 (.68) 1.25 (.79) 1.37 (.58) 0.94 (.72) 1.20 (.85) 1.61 (.76) 1.63 (.90)

Affectivity: POMS 6. Depression α = 0.92*

7. Fatigue α = 0.89 8. Anger α = 0.90 9. Vigor α = 0.90 IES (scale 0 - 3) 10. Intrusion pre 1.36 (.76) 1.24 (.82) 1.22 (.73) 0.99 (.60) follow-up .79 (.63) 1.00 (.91) 0.69 (.68) 0.92 (.75) α = 0.82 11. Avoidance pre 1.06 (.70) 0.84 (.59) 1.08 (.66) 0.92 (.60) follow-up 0.89 (.61) 0.63 (.50) 0.65 (.61) 0.93 (.63) α = 0.75 VA (1)* F (3, 80) = 1.22 p > .10 VA (2)* F (3, 80) = 2.56 p = .061 VA (3)* F (3, 80) = .58 p > .10 VA (4)* F (3, 80) = .65 p > .10 VA (5)* F (3, 80) = 2.02 p > .10 VA (6)* F (3, 80) = 2.91 p = .04 VA (7)* F (3, 80) = 5.40 p = .002 VA (8)* F (3, 80) = .51 p > .10 VA (9)* F (3, 80) = 5.56 p = .002 VA (10)* F (3, 80) = 3.23 p = .027 VA (11)* F (3, 80) = 2.29 p = .084 Post-hoc Scheffé: (2) control / helping, p = .071 Post-hoc Scheffé: (6) helping / coping, p = .055 Post-hoc Scheffé: (7) control / coping, p=.083; helping / coping, p = .003 Post-hoc Scheffé: (9) control / coping, p=.060; disclosure / helping p=.082; helping / coping, p = .005 Post-hoc Scheffé: (10) control / disclosure, p = .076 Post-hoc Scheffé: (11) control / helping, p = .086 * Cronbach's Alpha + Mean frequencies

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While analysis of variance yielded no significant long-term effects of expressive writing on mood regulation (assessed with the NMR), a significant interaction effect (period x condition) was found for Ss’ perceived coping self-efficacy. On the descriptive level, the increase in self-efficacy was most pronounced in the helping condition followed by the coping condition. Inquired as to the positive and negative long-term effects of writing, Ss in the helping group reported significantly more positive consequences than controls. No other differences were found. Table 9. Mood regulation and coping competency in study II: Item means (m), standard deviation (sd), and results of analysis variance (interaction terms*) Variables 1.

Mood regulation (m,sd) α = 0.85+ Coping competency (m,sd) α = 0.82+

Period

pre follow-up 2. pre post§ follow-up VA (1)* F (3,80) = 1.14, p > .10 VA (2pre - post)* F (3,80) = 1.79, p > .10 VA (2pre - follow-up)* F (3,80) = 2.71, p = .05

Disclosure 3.40 (.40) 3.52 (.40) 1.70 (.73) 1.85 (.99) 1.75 (1.07)

Condition Coping Helping 3.31 (.43) 3.41 (.42) 3.31 (.50) 3.59 (.48) 1.55 (1.06) 1.74 (.87) 2.09 (.68) 2.16 (.96) 2.10 (1.02) 2.10 (1.07)

Control 3.35 (.39) 3.43 (.47) 1.81 (1.08) 1.76 (.83) 1.81 (.93)

+

Cronbachs Alpha After 3rd writing session *period x condition §

STUDY I: DISCUSSION In many studies a relative increase in negative mood directly after writing about upsetting events has been observed, an effect which Pennebaker (1993) has postulated as being a prerequisite for the long-term positive effects of disclosure. This negative effect on mood was corroborated in our study, though inspection of means revealed the effect to be attributable to an improvement of mood in the control group and a comparable deterioration of mood in the disclosure group. It is important to emphasise that the disclosure Ss wrote about truly upsetting and traumatic events, as shown by the analysis of essay contents and the self-rating of the extent to which the experience was troubling at occurrence and now. The expected short-term increase in physical symptoms due to the emotional impact of expressive writing, which has been observed at least in some prior studies, was not shown in our data. This may be due to inadequacies of the German version of the PPSS, an interpretation supported by the relatively low internal consistency of the scale (α = .59 vs. α = .75 reported by Pennebaker, 1982). Data of the second study should decide on this interpretation. The positive long-term effect of expressive writing on physical health could not be found at 6-week follow-up for any of the health-related variables assessed in the study. Thus, the beneficial effects of disclosure on physical health reported by Pennebaker and colleagues

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(1986, 1988) could not be replicated in our German sample. In fact, increases in both illness days and days with illness-related restriction of activity were found in the disclosure condition at follow-up. Such increases, however, were also observed in the control group and seem quite likely due to the seasonal influence of follow-up taking place during winter. The very high variance within Ss (see e.g. “illness-related restriction of activities”) indicates the presence of heterogeneous health trajectories, especially in the disclosure group. It should be pointed out that all health-related variables in our study were of a subjective nature. Unlike American universities, Germany universities do not operate student health care centres, a source from which objective health data was obtained in prior studies. Though possible that health improvement not apparent in subjective measures might be found in objective health data, the likelihood of such a divergence of health measures is small. Furthermore, it bears attention that our study was not unique in being unable to corroborate health improvement: Significant health-related differences between conditions were also absent in other studies (Greenberg & Stone, 1992; Murray et al, 1989; Murray & Segal, 1994; Gidron et al, 1996). The results concerning long-term effects of expressive writing on psychological wellbeing are contradictory. Though no improvement relative to controls was found for positive or negative affectivity, significant reductions were found in maladaptive processing 6 weeks after writing: Re-experiencing, autonomic arousal and posttraumatic stress symptoms on the whole occurred less frequently. The study also focussed on potential mechanisms of written disclosure by examining the relationship between a number of essay variables and the postulated short- and long-term effects of disclosure. The essay characteristics were assessed by self-report (e.g., rating of extent to which the essay was emotionally revealing) as well as by independent judges’ rating (e.g., depth of self-exploration). Despite the overall lack of significant long-term effects of disclosure on health status and affectivity, meaningful correlations between essay characteristics and outcome variables could have been found that would lend support to Pennebaker’s theory of inhibition and confrontation. However, only 4 out of 108 calculated correlations reached significant and the few significant correlations were all related to the domain of posttraumatic stress symptoms, the only outcome variables for which significant effects were found. Interestingly, the significant correlations were not exclusive to the scales for which long-term effects were found: Re-experiencing, though significantly reduced at follow-up, was not associated with any of the examined essay characteristics, while avoidance, though not significantly changed following disclosure, was. Associations were found between the more frequent and intense expression of positive emotions in essays and a higher the reduction in arousal. This effect, though not predicted by inhibition theory, seems quite plausible in light of Lazarus' stress coping model, in which positive reappraisal reduces the stress response. Associations were also found between increasing self-exploration (day 1 to day 3) and reductions in avoidance as well as posttraumatic stress symptoms on the whole. Surprisingly, the assessed personality variables were of little to no relevance for shortand long-term consequences of disclosure. The constructs of personality variables like alexithymia (lack of ability to perceive and express emotions) and self-concealment (conscious inhibition of expressing emotions to others) made the hypothesis of their influence on the disclosure process and its outcome highly probable. Nevertheless, only one significant correlation was found regarding self-concealment and long-term change of physical

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symptoms. The unexpected absence of these theoretically highly plausible associations may be indicative of a weakness in the theory of inhibition and confrontation.

STUDY II: DISCUSSION The second study was conducted to determine whether the negative results of study I might be due, in part, to inadequacies in the German versions of the selected assessment instruments. More importantly, however, was the study’s aim of examining whether modified disclosure instructions promoting self-efficacy and coping would be more successful in producing the postulated positive effects on physical health and psychological well-being. Negative short-term effects of expressive writing were found in study II for both mood and physical symptoms. Interestingly, the increases in both were most pronounced in the disclosure condition, which differed significantly from the control condition. The coping and helping conditions, on the other hand, evidenced only slight, if any, increases in physical symptoms and negative mood. As in study I, positive long-term effects of writing on physical health were conspicuously absent. Not only were there no effects with regard to the Complaints Schedule, an instrument specifically validated for German samples, none of the subjective health measures indicated a beneficial effect of expressive writing on physical health. The observed long-term effects on mood were unexpectedly attributable to differences between the helping and coping conditions, controls were not involved. Nevertheless, the deterioration of mood in the coping Ss, relative to the helping Ss, merits comment. The only predicted long-term improvements of psychological well-being were found with the Impact of Event Scale. A marginally significant interaction effect was revealed for “avoidance” and a significant interaction effect for “intrusion”. Altogether the helping group showed the largest reduction in posttraumatic stress symptoms, The newly explored variable “expectancy of negative mood regulation” did not respond to expressive writing, either in its standard or modified form. Self-rated coping competency did, however, as evidenced by the significant interaction effect in the analysis of variance on follow-up data. Though the post-hoc Scheffé-test did not reveal any significant pairwise differences, inspection of means showed that the largest increase in perceived coping competency was found in the helping condition, marginal increases were found in the other experimental groups, while the controls evidenced no change. Regarding global estimate of positive effects of writing by the Ss, the helping group gives the highest rating and the control the lowest.

SUMMARY In both of our studies, the main assumption made by Pennebaker that confronting personally upsetting experiences via a brief writing intervention, can lead to positive longterm health consequences could not be corroborated. The vision of being able to achieve improvements in physical health and psychological well-being by writing in an emotionally expressive way about negative experiences does not seem to be warranted by the results of

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the present study. Thus, our findings contradict not only the early disclosure studies but also the results of a metaanalysis from Smyth (1998), in which medium effect sizes were reported for both physical health (d = .42) and psychological well-being (d = .66). We want to point, however, that the effects reported in some studies did not reflect improvement in the disclosure condition, but rather a deterioration of health in the control group (Pennebaker & Beall, 1986; Pennebaker & Francis, 1996; Greenberg et al, 1996). Taken together with our negative results on health improvement and the lack of substantial correlations between theoretically fitting personality constructs and outcome variables, a more sceptical view of disclosure seems warranted. On the other hand, however, we found substantial changes in symptoms of post traumatic stress. In the first experiment re-experiencing and autonomic arousal were reduced after disclosure and a decrease in posttraumatic stress symptoms on the whole was found. In the second experiment, the positive effect of disclosure on these symptoms could be replicated using an instrument that was psychometrically validated for German samples. A significant reduction in intrusions was found as well as a marginally significant reduction of avoidance. These effects (reduction of symptoms) were most pronounced in the helping group. It seems that taking on the role of an adviser and recommending coping strategies to others dealing with the same experience can increase perceived coping competency and thereby facilitate improved emotional processing. Contrary to our expectations, the coping instruction was not as effective. It is plausible that the coping instruction may have reactivated the memory of unsuccessful coping endeavours in some of the Ss. On the other hand Cameron & Nicholls (1998) found positive effects in their somewhat different coping intervention. Thus, disclosure had a positive long-term effect on the processing of traumatic experiences but not on physical health or mood. Perhaps the effects on trauma processing, which are of medium size in the helping and disclosure group were not strong enough to have consequences for general health. Conclusions from our studies are that writing about upsetting or traumatic events can be useful as a self-help strategy to improve coping with the trauma but it can not replace more comprehensive professional interventions when the negative impact of the stressful event on the individual is strong. Is there any explanation for the discrepancy between our results and the beneficial health effects reported in the early studies from Pennebaker and Beall (1986) and others? Our samples do not differ from the others with regard to Ss’ status and age. The marginal gender difference between conditions in study I cannot explain the discrepancies, as gender had no moderating effect on outcome. The experiences the Ss wrote about are similar to the essay contents reported by Pennebaker and Beall (1986) or Pennebaker et al (1988). The healthrelated assessment measures and instruments were analogous, with the exception of a lack of objective health data. It seems highly unlikely, however, that self-report measures of health should be less sensitive to change than objective parameters. It could be argued that our follow-up assessment was premature, the time span of 6 weeks being too short for the beneficial effects on health to occur. This argument, however, loses its strength in view of the health improvements reported by Pennebaker et al (1988), who implemented a follow-up of the same length, and found reductions in health centre visits and increased immunocompetence 6 weeks after writing. Improvements in health have even been reported for as short a time span as 4 weeks after writing (Greenberg et al, 1996). It cannot be ruled out that sociocultural factors may play a role in the discrepant results as nearly all supporting

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findings originate from the USA and Canada. What factors these might be, however, is far from clear. Interest in the theory of inhibition and confrontation has not waned over the years: Since the first wave of research in the late eighties and the nineties, numerous new studies using the disclosure paradigm have been conducted. The study samples have grown more diverse ranging from prisoners (Tromp, 1998; Richards et al, 2000), individuals in mourning (Eddins, 1999, Ströbe et al, 2002), persons afflicted with cervical dysplasia (Cook, 2001) and prostate cancer (Rosenberg et al, 2002[prostate cancer]), to patients presenting with somatisation (Schilte et al, 2001), fibromyalgia (Gillis, 2002) and major depression (Hitt, 2001). College students were examined by Marlo & Wagner (1999) and Kloss & Lisman (2002), school children (8-13 years) by Reynolds et al (2000), and Klapow et al (2001) tested the disclosure hypothesis on a sample of primary care patients of an older age (66 years or older). Beneficial effects of disclosure are reported in some of the studies, e.g. by Gillis et al (2002), who found functional improvement in patients with fibromyalgia as well as better sleep quality. Rosenberg et al (2002) reported reductions of physical symptoms and health care utilisation in prostate cancer patients, though no effect was found on psychological variables or disease-related parameters of immunocompetence. Richards et al’s (2000) psychiatric prisoners showed a reduction in postwriting infirmary visits. Reduced health care utilisation was also found in older primary health care patients, though somatic symptoms and distress remained unchanged (Klapow et al, 2001). Whether Tromp's report (1998) of increased mental health care utilization in prisoners points to a positive effect (more sensitivity to psychological symptoms) or a negative effect (more symptoms) remains unclear. In other studies, however, disclosure was less successful in promoting psychological or physical health (Wilson, 2000; Marlo & Wagner, 1999; Schilte et al, 2001; Ströbe et al, 2002; Reynolds et al, 2000; Kloss & Lisman, 2002). Thus, evidence seems to be accumulating that the effects of disclosure are less positive and less dramatic than assumed after the first studies. Unfortunately, outcome variables indicative of the dysfunctional processing of traumatic events were rarely assessed, so that further support for the results of our studies is lacking. Furthermore, the variables mediating and moderating the effect of disclosure are far from clear. Additional research is needed to systematically analyse relevant variables and elucidate the mechanisms of action. The current focus of disclosure research on health-related variables and the neglect of psychological processing seems adversarial to the clarification of the potential utility of written disclosure as a means of self-help or in conjunction with psychotherapy.

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Paez, D., Velasco, C. & Gonzalez, J.L. (1999). Expressive writing and the role of alexithymia as a dispositional deficit in self-disclosure and psychological health. Journal of Personality & Social Psychology, 77, 630-641. Pennebaker, J.W. & Beall, S.K. (1986). Confronting a traumatic event: Toward an understanding of inhibition and disease. Journal of Abnormal Psychology, 95, 274-281. Pennebaker, J.W., Hughes, C.F. & O’Heeron, R.C. (1987). The psychophysiology of confession: Linking inhibitory and psychosomatic processes. Journal of Personality and Social Psychology, 52. 781-793. Pennebaker, J.W., Kiecolt-Glaser, J.K. & Glaser, R. (1988). Disclosure of traumas and immune function: Health implications for psychotherapy. Journal of Consulting and Clinical Psychology, 56, 239-244. Pennebaker, J.W. (1988). Confiding traumatic experiences and health. In S. Fisher & J. Reason (Eds.), Handbook of life stress, cognition and health. Chichester: John Wiley & Sons. Pennebaker, J.W. (1989). Confession, inhibition, and disease. In L. Berkowitz (Ed.), Advances in Experimental and Social Psychology, 22, 211-244. New York: Academic Press. Pennebaker, J.W., Colder, M. & Sharp, L.K. (1990). Accelerating the coping process. Journal of Personality and Social Psychology, 58, 528-537. Pennebaker, J.W. & Francis, M.E. (1996). Cognitive, emotional, and language processes in disclosure. Cognition and Emotion, 10, 601-626. Pennebaker, J.W., Mayne, T. & Francis, M. (1997). Linguistic predictors of adaptive bereavement. Journal of Personality and Social Psychology, 52, 863-871. Petrie, K.J., Booth, R.J., Pennebaker, J.W., Davison, K.P. & Thomas, M.G. (1995). Disclosure of trauma and immune response to a hepatitis B vaccination program. Journal of Consulting and Clinical Psychology, 63, 787-792. Reynolds, M., Brewin, C. R. & Saxton, M. (2000). Emotional disclosure in school children. Journal of Child Psychology and Psychiatry and Allied Disciplines, 41, 151-9. Richards, J.M., Beal, W.E. & Seagal, J.D. (2000). Effects of disclosure of traumatic events on illness behavior among psychiatric prison inmates. Journal of Abnormal Psychology, 109, 156-160. Rosenberg, H.J., Rosenberg, S.D. & Ernstoff, M.S. (2002). Expressive disclosure and health outcomes in a prostate cancer population. International Journal of Psychiatry in Medicine, 32, 37-53. Schilte, A. F., Portegijs, P., Blankenstein, A.H., van der Horst, H.E. & Latour, M. B. (2001). Randomised controlled trial of disclosure of emotionally important events in somatisation in primary care. British Medical Journal, 323, 86-89. Schmidt-Atzert, L. (1981). Die verbale Kommunikation von Emotionen: Eine Bedingungsanalyse unter besonderer Berücksichtigung physiologischer Prozesse. (Verbal communication of emotions: an analysis with regard to physiological processing). Unpublished PhD thesis. Justus-Liebig-University, Giessen. Schoutrop, M.J.A., Lange, A., Davidovich, U. & Salomon, H.B. (1996). The effects of writing assignments in traumatised individuals: An experimental study. Psychosomatic Medicine, 58, 64. Smyth, J.M. (1998). Written emotional expression: Effect sizes, outcome types, and moderating variables. Journal of Consulting and Clinical Psychology, 66, 174-184.

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In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 8

TEST ANXIETY AND ITS CONSEQUENCES ON ACADEMIC PERFORMANCE AMONG UNIVERSITY STUDENTS Mohd Ariff Bin Kassim1, Siti Rosmaini Bt. Mohd Hanafi2 and Dawson R. Hancock*3 1

Universiti Tenaga Nasional; 26700 Muadzam Shah; Pahang, Malaysia; Electronic Mail – [email protected]; Telephone – 012-6097503 2 Universiti Tenaga Nasional; 26700 Muadzam Shah; Pahang, Malaysia; Electronic Mail – [email protected]; Telephone – 09-4552043 3 University of North Carolina at Charlotte; 9201 University City Boulevard; Charlotte, North Carolina, U.S.A.; Electronic Mail – DHancock@ uncc.edu Telephone – (704)687-8863

ABSTRACT Some educators have failed to acknowledge the prevalence of test anxiety and its effect on academic performance among university students. This study addresses this issue at the university level using data collected through the Revised Test Anxiety (RTA) instrument and Sarason’s four-factor model as a basis for measuring test anxiety. The study also investigates the effect of demographic factors on test anxiety. Findings reveal that test anxiety is significantly and negatively related to academic performance. Reasons for these findings are addressed.

Although testing is an important and widely used means for evaluating ability and achievement of individuals, many motivated and talented college students suffer from test *

Address for Correspondence: Dawson R. Hancock, Ph.D. University of North Carolina at Charlotte; 9201 University City Boulevard; Charlotte, North Carolina, U.S.A. 28223; Electronic Mail – DHancock@ uncc.edu; Telephone – (704)687-8863

162 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock anxiety (Austin and Patridge, 1995). Students often experience increased testing as they progress from primary school to post-secondary levels. Although most students experience normal nervousness during tests, others experience severe anxiety. Obviously, test anxiety can be considered an important factor in relation to academic performance. It has been proposed that test anxiety is one of the most disruptive factors associated with underachievement of students. Sarason (1984) stated that test anxiety is a debilitating factor at all academic levels. Because of its strong influence on academic achievement, test anxiety has been identified as one of the variables in the motivation and learning strategies model proposed by Pintrich (Paulsen and Gentry, 1995).

RESEARCH PROBLEM Test anxiety is a serious problem for many students. It has been described as the most powerful impediment to learning in an educational setting (Matthew, Tracy and Scott, 2000). Test anxiety has been linked to fears of negative evaluation, dislike of testing, and less effective study skills (Hambree, 1988) and has been identified as one of the factors that impairs academic performance (Everson and Millsap, 1991 and Tobias, 1980; Gregory, 1999). Many educators are disturbed over the trauma experienced by students during test taking time. This study was conducted to examine this issue in college students with the goal of helping students seek appropriate strategies to overcome debilitative test anxiety.

LITERATURE REVIEW The Definition of Anxiety Anxiety is a complex concept and this complexity is illustrated by the various definitions of anxiety in the literature. Anxiety describes cognitive, affective, and behavioral responses that will result in poor performance and possibly failure in an evaluative situation (Ian and Owens, 1996). According to Spielberger (1966), anxiety stems from an individual’s feeling of guilt from committing wrongful acts. Anxiety can also be described as an unpleasant state of tension arising from disapproval in interpersonal relations (Eady, 1999). Anxiety actually arises due to direct threat to some value considered important to an individual’s existence as a personality (Spielberger, 1966). Furthermore, anxiety can be considered as a sense or feeling of discomfort and worry about undefined threat. The threat can be physical or psychological in nature and may involve the anticipation of bodily injury, damage to self-esteem, or harm to personal welfare.

The Definition of Test Anxiety Anxiety is also considered to have an important relation to academic performance, particularly in the form of test anxiety. In this context, test anxiety is viewed as a special part of general anxiety. Test anxiety is a universal phenomenon and has been studied in many

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different cultures (e.g., Morris, Davis and Hutchings, 1981, Spielberger, 1980 and Zeidner, 1992). Test anxiety is an extreme fear of performing poorly on examinations and it is a common form of anxiety among students. Such anxiety arises during evaluation situations or events. It can be explained as an affect or feeling of apprehension or fear and discomfort together with cognitive difficulties (Isaac and Orit, 1997). Test anxiety is closely related to negative emotions. It is because when one’s performances are being evaluated, an emotional reaction will appear. Therefore, during the evaluation, one may feel uneasiness, distress, or fear if one is not prepared and not confident with his or her abilities to perform well. However, if one is well prepared and very confident with himself or herself, the opposite feeling will arise (McDonald, 2001). On the other hand, Sarason and Stoops (1978) view that test anxiety is related to time whereby an individual may develop anxiety a long time prior to the examination. This implies that the preparation for the examination can also be affected. Therefore, such fear of tests may contribute to ineffective preparation for the test. Test anxiety also arises when the evaluative situation is interpreted as threatening (Mwamwenda, 1994).

Test Anxiety and Academic Performance Test anxiety is a major educational problem affecting millions of students in schools and colleges (Everson and Millsap, 1991). It is also widely recognized as a significant contributor to academic performance (Gregory, 1999). Many empirical studies have shown that test anxiety is a major debilitating factor on all academic levels, from the elementary level to the university level (Sarason, 1984). This view is also supported by the finding of Tobias (1980), who reported that test anxiety is one of the variables that are most commonly related to poor performance among students. Test anxiety is found to be negatively related to college students’ performance (Pintrich and Garcia, 1991 and Pintrich and De Groot, 1990). According to Ian and Owens (1996), approximately twenty percent of students consistently suffer from poor performance due to high test anxiety. The effects of test anxiety on academic performance have been thoroughly investigated by many researchers. Generally, the study of the relationship between test anxiety and academic achievement began in the early 1900’s (McDonald, 2001). The comprehensive reviews by Hambree (1988) on the Meta analysis of 562 studies showed that test anxiety caused poor performance. It implied that test anxiety had a negative relationship with students’ performance, where high test anxious students tended to score lower than low test anxious students. This result was supported by the findings of various studies (McDonald, 2001). High test anxiety students may view the testing situation differently compared to their low test anxiety counterparts. Such differing views may be expressed conceptually by variations in the features of the situation that students recognized as important and by the emphasis they replaced on those features (Schutz, Davis and Schwaneflugel, 2002). Studies conducted by Sarason in 1980 show that highly test anxious students perform relatively poor under an evaluative situation and that their performance is hindered by excessive selfpreoccupation with concern about failures and its consequences. Sarason also reported that the influence of test anxiety is most pronounced in those situations when the testing situation is competitive.

164 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock The study of test anxiety was also conducted involving an Arab population. The results showed that Arab students experienced higher test anxiety compared to American students. It was interpreted that Arab students experienced higher levels of test anxiety due to consequences of extreme importance of the test to students in their society (El-Zahhar and Hocevar, 1991). Similarly, it has been reported that college students in Egypt, Turkey and Mexico scored higher on test anxiety than students in America. In addition, test anxiety may also benefit the students in relation to their performance. This is because without any fear of failure, the students may make inadequate preparation for an examination that may lead to poor performance. However, if the level of test anxiety is above optimum level, it may disrupt preparation and create distress during the test and will result in an impairment of students’ performance. Even worse, there are students who resort to an avoidance approach to testing by not sitting for an examination due to extreme fear (McDonald, 2001).

Theoretical Framework In the test anxiety literature, several theories or models measure the test anxiety construct and in explain the effects of test anxiety on academic performance. Among the models suggested are the two-factor model by Spielberger (1980) and the four-factor model proposed by Sarason (1984). In addition, the two most common models used in explaining the effect of test anxiety on academic performance are the Interference and Deficits models. Detailed explanations of the models are discussed in this section.

Dimensionality of Test Anxiety It has been theorised that the construct of test anxiety is multidimensional. Among the various conceptualisations of test anxiety, Spielberger’s (1980) two-factor model (i.e., Worry and Emotionality) and Sarason’s (1984) four-factor model (i.e., Worry, Tension, Test Irrelevant Thinking and Bodily Symptoms) have been discussed widely in many empirical studies (e.g., Benson and Bandalos, 1992; David, et al., 2000; Hodapp and Benson, 1996; Hong, 1998 and Nasser, Takahashi and Benson, 1997). Initially, Liebert and Morris (1967) proposed that test anxiety consisted of Worry (Cognitive) and Emotionality components. Then, Spielberger, Gonzales, Taylor, Algaze and Anton (1978) developed the Test Anxiety Inventory (TAI) that followed the lead of Liebert and Morris (1967) and sought to refine a two-dimensional measure of test anxiety (i.e., twofactor model). Cognitive components refer to the mental activity that revolve around during test situations and will give an impact to the individual. In this two-factor model, Worry is the cognitive activity that accompanies the test anxiety. In contrast, Emotionality components are the psychological components of test anxiety and refer to tension, high heart rate, sweating, feeling sick and shaking (McDonald, 2001). On the other hand, Sarason (1984) and Wine (1982) suggested that test anxiety is consisted of cognitive, emotionality, behavioural and bodily reaction components. This occurs because test anxiety is a multidimensional constructs the separation of cognitive and emotionality should be addressed properly. Mainly due to this reason, Sarason (1984) subsequently categorised test anxiety construct into four components which are Tension,

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Worry, Bodily Symptoms and Test Irrelevant Thinking (i.e., four-factor model). Worry and Test Irrelevant Thinking are considered Cognitive components whereby Tension and Bodily Symptoms are grouped into Emotionality components. For the purpose of the present study, the Sarason (1984) four-factor model will be adopted in assessing test anxiety construct using the Revised Test Anxiety scale (RTA) developed by Benson and El-Zahhar (1994).

The Association between Cognitive Components with Academic Performance Cognition is claimed to be the most consistently and strongly related (i.e., negatively) to academic performance (David et al., 2000). This result was supported by other studies such as Kin and Roklin, 1994; O’Neil and Abedi, 1992; Zeidner and Nevo, 1991 and Liebert and Morris, 1967 (as cited in Hong, 1999). The cognitive test anxiety is hypothesised to have a debilitating effect on academic achievement because it may produce self-depreciating thoughts that will distract a student from thinking about relevant academic problems and cause her to focus on irrelevant thought (Ho, 2000). Worry is described as the unwanted and uncontrollable cognitive activity that relates with negative thoughts that result in emotional discomfort to the individual. Examples of negative thoughts include expecting to perform poorly on a test compared to other students, not being confident or feeling doubtful of one’s ability and the consequences of failing the test. Between the two cognitive components, Worry has a strong inverse relationship with academic performance (Hong, 1998 and 1999; Morris et al., 1981 and Sarason, 1984). The second element of Cognitive component is Test Irrelevant Thinking. This refers to intrusive, distracting and non-evaluative thoughts during the examination. For example, a student thinks of matters unrelated to the questions being asked in the examination. David et al (2000), who conducted a study involving Irish undergraduate students by using the RTA, found that Test Irrelevant Thinking is the strongest predictor of examination performance. This result is actually contradictory with those obtained by Hong (1998; 1999), Morris et al. (1981), and Sarason (1984).

The Association between Emotionality Components with Academic Performance The Emotionality component of test anxiety is comprised of Bodily Symptoms and Tension. The Emotionality component of test anxiety is not too debilitating to students’ performance (David et al. 2000). The above result is supported by Worth, Glazeski, Kirkland, Jones and Van Norman (1979) cited by David et al.(2000) which reported that the main difference between the low and high test anxious student is based on their cognitive reaction but not on physiological arousal (i.e., Emotionality) during the test. It is in line with the study conducted by David et al. (2000) who found that both Emotionality components are less negatively related to student performance as compared to the Cognitive component. Bodily Symptoms refer to the student’s physical reaction before and during test taking such as having a headache, tightening of the muscles and experiencing difficulty in breathing.

166 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock David et al. (2000) found that Bodily Symptoms have less of a negative impact on performance. Tension is the second element of Emotionality in test anxiety model. It refers to the student feeling tense during testing and feeling uneasy just before getting test results. Study indicated that Tension has slightly more negative impact towards student performance as compared to Bodily Symptoms (David et al., 2000).

Academic Performance This study uses students’ marks from final examinations in three courses – Cost Accounting (ACCD 213), Company Accounts II (ACCD 313), and Business Accounting II (ACCF 063) – offered to undergraduates at the Universiti Tenaga Nasional (UNITEN). The maximum mark that a student may achieve is 100 while the lowest is 0.

Test Anxiety Models Among the models that have been suggested for explaining the effect of test anxiety on academic performance are the Interference and Deficit models.

Interference Model The Interference Model describes test anxious student who know or sufficiently understand the content of course material but who went blank during the examination. In such a situation, the particular student is unable to recall prior learning or course materials (Wine, 1980). This model also indicated that students with high levels of test anxiety tend to divide their attention between the task demand (i.e., examination) and personal concerns, particularly negative self-preoccupation. However, students with low levels of test anxiety may devote most of their attention to task demands (Wine, 1980). This implies that the Interference model stresses the detrimental effect of task irrelevant thought during the test taking situation. A study conducted by Morris et al. (1981) supported this model. In addition, the high test anxious students may be involved in more negative thinking which perhaps interferes with the task demand (i.e., focusing on exam) when the students are under evaluative threat (Mwamwenda, 1994). The decline in academic performance caused by high test anxiety is a reflection of self doubt rather than lack of ability (Sarason and Stoops, 1978). The concept of the Interference model of test anxiety was supported by the majority of test anxiety researchers (David et al., 2000). For example, Hambree (1988) supporting the Interference model, concluded from a meta-analysis of 562 studies that test anxiety interferes with students’ recall of prior learning. Deficit Model In the Deficit model two types of factors were taken into consideration which caused poor academic performance due to high test anxiety experienced by students: study skills and test taking skills. Study skills describe student’s behaviours during meaningful learning that are intended to improve the acquisition, retention and retrieval of new knowledge (Tobias, 1985). This model assumes that student performance is reduced due to less initial acquisition

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or storage of the course materials contents rather than interference in retrieving course materials previously learned. According to Jochen and Arndt (1999) high test anxious students had less effective study skills than their low anxious counterparts. Therefore they have less knowledge of the relevant course materials. The model also assumes that poor academic performance is caused by deficiencies in students’ test taking skills. Elevation in test anxiety during testing presumably is caused by students’ awareness of doing poorly. Tobias (1985) stated that test taking skills significantly affected performance on essay and multiple-choice examinations but had a less important effect on calculation (i.e., mathematics examinations). In order to clarify the differences between the Interference and Deficit models in explaining the effect of test anxiety on academic performance, the diagram in figure 1 is referred to. The diagram is composed of three components, which are input, processing and output. Input refers to the presentation of instructional material to student. Processing represents the operations performed by students to encode, organise and store the input (i.e., study skills) and output denotes the performance of students on evaluative measures. Test anxiety affects all three components (Tobias, 1985). Test anxiety at the input stage refers to the apprehension that students experience when they are presented with new learning material. The level of test anxiety depends on the student’s ability to attend to, concentrate on and encode information. Anxiety experienced at this stage may reduce the effectiveness of input by limiting the anxious student’s ability to attend to material presented by the instructor and reducing the student’s ability to represent input internally (Bailey, Ongwuegbuzie and Daley, 2000). Students with high levels of test anxiety at this stage may ask their lecturer to repeat sentences or explain more often than do their low anxious counterparts. Anxiety at the processing stage refers to the apprehension students’ experience when performing cognitive operation on new information. The amount of test anxiety during processing depends on the complexity of the information, the extent to which memory is realised, and the level of organisation of the presented material (Tobias, 1985). At this stage, anxiety can impede learning by reducing the efficiency with which memory processes are used to solve problems. Moreover, high levels of anxiety at the processing stage may reduce a student’s ability to understand messages or to learn new material (Bailey et al., 2000). Finally, anxiety at the output stage involved the apprehension students experienced when required to demonstrate their ability to use previously learned material. Particularly, anxiety at this stage involved interference that appears after processing had been completed, but before it had been reproduced effectively as output. High level of anxiety at this stage might hinder students’ ability to reproduce the learned material when it is required. Bailey et al. (2000) noted that the three stages of test anxiety are interdependent. Each stage depends on the successful completion of the previous one. The major difference between Interference and Deficit can be seen clearly in the post processing. At this point, the Interference model assumes that learning had occurred; however, the evaluative threat posed by the examination situation interferes with the students’ ability to retrieve information. The students are said to “go blank” during examination and therefore are unable to recall prior knowledge. On the other hand, the Deficit model of test anxiety seems to affect the input and processing components. The inadequate initial preparation or poor test taking skills among the students may account for the reduced academic performance (Tobias, 1985). For the purpose of this study, the Interference model is

168 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock the preferred test anxiety model in explaining its effects on students’ performance. This model is adopted as the majority of researchers have supported this concept (e.g., Deffenbecher, 1980; Hambree, 1988; Morris et al., 1981; Mwamwenda, 1994 and Sarason and Stoops, 1978).

Interference Model

Deficit Model

Input

Processing of input to store, retrieve or transfer information

Output

Test Anxiety Figure 1 Theoretical Model of the Current Study. Independent Variables

1

Dependent Variable

Test Anxiety

W orry

Test Irrelevant Thinking

Academic Performance

Bodily Symptoms

Tension

Figure 2. Schematic Diagram.

1

Source: Tobias S. (1985). “Test Anxiety: Interference, Defective Skills and Cognitive Capacity”. Educational Psychologist, 20(3), 135-142.

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Schematic Diagram The schematic diagram in figure 2 summarizes the theoretical framework of the present study. There are four components of test anxiety (i.e., Worry, Test Irrelevant Thinking, Bodily Symptoms and Tension) that serve as independent variables. Performance is the dependent variable in the study, which refers to student’s final examination marks of accounting courses.

RESEARCH DESIGN This section discusses the research questions, type of study, data collection method, and the sample as well as the instrument and its validity. In addition, this chapter also discusses the data analyses, data types, and statistical analyses using Factor Analysis, K-S test, Correlation, One-way ANOVA, and Independent sample T-tests.

Research Questions There are three main research questions that will be addressed in the present study. [1] How do test anxiety variables relate to the academic performance of students? [2] Does the level of test anxiety among students vary between three groups of students? [3] Does the level of test anxiety among the students vary in different demographic and environmental situation?

Data Collection In this study, data were collected using self-reported questionnaires at the end of the semester for each courses offered at UNITEN. The data collection was approximately one month before the final examination. The study involved all the population of students that enrolled in the three courses i.e., Cost Accounting (DBS), Company Accounts II (DIA) and Business Accounting II (Business Foundation). As data were gathered only once, this current study can be considered a cross-sectional study. However, the students’ academic performances (i.e., final examination marks) were obtained from the academic records of the students.

Instrument The students responded to a self-reported questionnaire called the Revised Test Anxiety (RTA) developed and verified by Benson and El-Zahhar (1994). The instrument was developed based on the combination of Test Anxiety Inventory (TAI), created by Spielberger, Gonzalez, Taylor, Algaze and Anton (1978) and Reaction To Test scale (RTT) proposed by

170 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock Sarason (1984). From the combination of 60 items (20 items from TAI and 40 items from RTT), a process of item deletion resulted in 20 items of RTA consisting of the four dimensions of Worry, Test Irrelevant Thinking, Bodily Symptoms and Tension. The RTA is based on the theoretical four-factor dimensionality proposed by Sarason (1994). The goal of RTA is to incorporate the best qualities of each scale, to maintain multiple dimensions as theorised by Sarason, to provide a scale with acceptable precision and to develop valid measure of test anxiety for multinational samples. The instrument consists of 20 questions or items based on a 4-point Likert scale. The scales are 1 = almost never, 2 = sometimes, 3 = often and 4 = almost always. Higher scores reflects higher test anxiety. RTA can be divided into two broad components; Cognitive and Emotionality. The Cognitive component comprises Worry and Test Irrelevant Thinking, while the Emotionality component comprises Tension and Bodily Symptoms. The twenty items in the RTA are distributed among the four components as follows: Worry (6 items), Test Irrelevant Thinking (4 items), Tension (5 items) and Bodily Symptoms (5 items). Benson and El-Zahhar (1994) have demonstrated the stability of the dimensionality estimates of 20 items RTA scale by cross-validation among American and Egyptian samples. In addition, David et al (2000), who conducted a study to validate the RTA by using a sample of Irish students, found that the RTA is a useful cross cultural instrument to measure test anxiety. Therefore, the instrument used in this study is reliable and valid in measuring test anxiety among the UNITEN students in Malaysia.

Analysis In conducting the statistical analysis, SPSS version 12 was used. This section explains the data analysis process.

Data Types Initially, it is important to identify the types of data gathered whether they are ordinal, ratio, nominal or interval. In this study, the data were obtained through self-reported questionnaires received from the students using 4-point Likert scale. According to Keller and Warrack (2000), if data can be ordered or ranked preferentially, those data are considered as ranked data and are said to have an ordinal scale. The responses using a 4-point Likert scale are considered non-quantitative data because the data are ranked based on preferences. In addition, Mason, Lind and Marchal (1999) suggested that we are not able to differentiate the magnitude of the differences between the ranks. For instance, is the difference between “almost never” and “sometimes” the same as the difference between “almost always” and “often?” We can only conclude that rating 1 is better than rating 2 or 3 or 4 but we cannot determine how much better. Thus, it is clear that the data obtained are ordinal data (Keller and Warrack, 2000; Mason et al., 1999).

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Statistical Analysis When the data are ranked, average is not the appropriate measure. Keller and Warrack (2000) proposed the use of non-parametric statistical tests for ranked data. However, this present study utilised factor scores for further analysis as it is considered as ratio data. Hair et al. (1992) recommended the use of factor scores if the instrument used to collect the original data is well constructed, valid and reliable. As the RTA is a reliable and valid instrument to measure test anxiety, factor scores are utilised for analysis involving test anxiety variables. In addition, we can use parametric test if the data are normally distributed. In this study the confidence level of statistical tests is 95%. All the statistical analysis with p-values of 0.05 or less are considered as significant to reject the null hypothesis.

Normality Kolmogorov-Smirnov Test (K-S Test) was used to test the normality of data, which comprise the four test anxiety factors; Tension, Test Irrelevant Thinking, Bodily Symptoms and Worry. Parametric tests are appropriate for normally distributed data and non-parametric are appropriate for data that are not normally distributed. Factor Analysis The study utilised a well-established research instrument (RTA). However, because the data are collected from very different groups of students, factor analysis was performed. In order to determine the number of factors to be extracted from the variables, the common rule was the eigenvalue of more than 1. Correlation With regards to the first research question on the association between test anxiety and academic performance, the bivariate correlation was performed. Pearson correlation is an appropriate measure for normally distributed data and Spearman correlation for data that are not normally distributed. One-Way ANOVA The second research question is to measure the differences in the level of test anxiety among students. ANOVA tests are performed for data that are normally distributed. ANOVA tests were also performed to answer the third research question regarding the effect of demographic factors which involved comparison between more than two groups (i.e., age, reasons for enrolment and study habit). Independent Sample T-Test The study also investigated the effect of demographic factors on the test anxiety level which involved comparison between two groups. Demographic factors include student gender, hometown, secondary school profile and exposure to accounting subjects during SPM. For the test anxiety variables that are normally distributed, independent sample t-tests were performed.

172 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock

RESULTS, INTERPRETATION, AND DISCUSSION Factor Analysis Factor Analysis is a data reduction technique used to reduce a large number of variables to a smaller set of underlying factors, which summarise the important information contained in the variables. The following are the results for the factor analysis test.

Kaiser-Meyer-Olkin (KMO) and Bartlett’s Test In performing factor analysis, the KMO and Bartlett’s Tests were used. These tests measure sampling adequacy. The results of KMO is 0.820 and a good measure should be greater than 0.6. Thus, it indicated good sampling adequacy. In addition, the Bartlett’s test of sphericity was significant with a p-value of 0.000. The anti-image correlation matrices revealed all the measure of sampling adequacy are well above acceptable level of 0.5. The Rotated Factor Matrix Based on the rotated factor matrix table (see table 1), which employed the Varimax rotation method, the results indicate five factors from the total of 20 variables or items used to measure test anxiety. The results are quite inconsistent with the study conducted by Benson and El-Zahhar (1994). All the factors are named accordingly based on their items. The existing four factors are retained with the addition of one new factor. The first factor known as Bodily Symptoms comprises 6 items with factor loading ranging from 0.349 to 0.597. These items assess how much students experienced Bodily Symptoms before taking tests. Such bodily symptoms include headache, trembling, muscle tightening and difficulty in breathing. An example of Bodily Symptoms would be getting a headache during an important test. The second factor, Test Irrelevant Thinking, measures the students’ judgement on how relevant an examination is to them. An example can be seen in the following statement: “During tests I find myself thinking of things unrelated to the material being tested.” There are 4 items that were grouped into this factor with factor loadings ranging from 0.532 to 0.656. The result was consistent with Benson and El-Zahhar (1994). The third factor, Tension, comprises 5 items and the results are slightly inconsistent with what was found by Benson and El-Zahhar (1994). The factor loadings of the 5 items ranged from 0.336 to 0.551. The factor assesses the level of tension experienced by the students before and during testing or examination. An example of this is the statement, “I start feeling very uneasy just before getting a test paper back.” The forth factors, termed as self defeat, measures students’ negative perceptions during testing. The factor comprises two items and loadings range from 0.447 to 0.589. An example of this is the statement, “I seem to defeat myself while taking important tests”. The last factor in test anxiety construct is Worry. It has 2 items that are used to assess the level of worry among students. The factor load ranged from 0.449 to 0.498. An example of Worry can be seen in the statement, “Thinking about my grade in a program interferes with my work on tests.” All of the five factors will be the basis to form further analysis in relation to test anxiety. Item 8 from the RTA was dropped due to a correlation of less than 0.30.

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Table 1. Rotated Factor Matrix Factor 1 .597

Item 16 Item 15

2

3

4

5

.569

Item 18 Item 17 item 10

.520 .497

item 6

.349

.313

.361

item 9 item 14 item 7

.656 .626

item 13

.532

.591

item 5 item 4 item 20

.551 .539 .484

item 12 item 11 item 8 item 3

.339

.360 .336 .327

item 2 item 19 item 1

.589 .447 .498 .366

.449

Extraction Method: Principal Axis Factoring. Rotation Method: Varimax with Kaiser Normalization.

Normality Test The study utilised K-S tests in order to test the normality of variables. There are five main variables in relation to the test anxiety construct; Bodily Symptoms, Test Irrelevant Thinking, Tension, Self-Defeat and Worry. The results illustrated in table 2 indicated that all test anxiety variables were normally distributed. Bodily Symptoms (p-value = 0.130), Test Irrelevant Thinking, (p-value = 0.649), Tension (p-value = 0.320), Self-Defeat (p-value = 0.140) and Worry, (p-value = 0.846). With regards to academic performance (i.e., final examination marks for accounting courses) the results indicated a normal distribution. Table 2. One-Sample Kolmogorov-Smirnov Test

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

Exam Marks

N

308

308

308

308

308

345

Std. Deviation

.81260873

.83818322

.76977603

.72612033

.71086918

14.109

1.169

.737

.956

1.154

.614

1.003

.130

.649

.320

.140

.846

.266

KolmogorovSmirnov Z Asymp. Sig. (2-tailed)

174 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock

The Association between Test Anxiety and Academic Performance The primary research objective is to measure and determine the associations between test anxiety and academic performance of the DIA, DBS and Business Foundation students. It was hypothesised that the test anxiety construct is inversely related to academic performance. Therefore, it is important to test such relationships as previous studies demonstrated inverse relationships between test anxiety and academic performance. For instance, Hambree (1988) found that test anxiety had negative relationships with academic performance where high test anxiety students tended to score lower than low test anxiety students. The above relationship was tested using the Pearson correlation. The results indicate that Self-defeat was found to have a significant relationship with academic performance (p-value =0.039 and r = - 0.119) for all programs. In relation to individual programs, DIA and Business Foundation programs reported a significant relationship with academic performance. DBS programs showed no significant result. For DIA programs, the result revealed that only the Worry variable was found to be negatively associated with performance (p-value = 0.006 and r = - 0.363). For Business Foundation, Self-defeat (p-value = 0.019 and r = -0.365) and Worry (p-value = 0.006 and r = -0.418) results showed a negative association with academic performance. The other variables indicated no significant result.

Comparison of Test Anxiety Level between Groups The second research objective has been divided into two parts which compare the test anxiety levels among the three cohorts of DBS students (i.e., students from semester 2, 2003/2004, semester 1, 2004/2005 and semester 2, 2004/2005) and compare the test anxiety levels among DIA, DBS and Business Foundation students. Both objectives were tested using one-way ANOVA. For the first objective, it was hypothesised that there was a significant difference in the level of test anxiety construct among the three cohorts of DBS students. The present study involved 117 students from semester 2, 2003/2004, 114 students from semester 1, 2004/2005 and 120 students from semester 2, 2004/2005. Based on the results obtained, there is sufficient evidence to infer that there is a significant different in the level of Worry (p-value = 0.013) among these three groups. The students from semester 2, 2004/2005 experienced the highest level of Worry (mean 0.199) compared to their counterparts from semester 2, 2003/2004 and semester 1, 2004/2005. The other variables showed no significant differences. For the second part of this objective, it was hypothesised that the level of test anxiety between DIA, DBS and Business Foundation students was significantly different. Based on analysis performed, three variables were found to have significant results as presented in table 3. Table 3 shows that the Business Foundation students exhibit lower levels of Bodily symptoms (mean –0.410) while the DBS students exhibit the highest score (mean 0.114). In relation to the Self-defeat variable, the same result is applied. Surprisingly, the Business Foundation students were found to experience the highest level of Tension (mean 0.276) as compared to their counterparts.

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Table 3. Differences in test anxiety level Factor P-value DIA (mean) DBS (mean) B. Foundation (mean)

B. Symptom 0.000 -0.135 0.114 -0.410

Tension 0.012 -0.192 -0.003 0.276

Self-defeat 0.048 -0.102 0.065 -0.203

The Effect of Demographic and Environmental Factors on Test Anxiety The third research objective concerns the effect of demographic and environmental factors towards test anxiety level. Among the demographic factors are the students’ gender, hometown, exposure to accounting subjects during SPM, age, reasons for enrollment and students' study behaviour (i.e., preferred study format, study time, study hours per week and study before test). The above demographic factors were hypothesised to have significant effects on test anxiety level. The results indicated that only student’s study behaviour such as preferred study hours per week and study before test showed the significant effect to the level of test anxiety. The other demographic factors exhibited no significant result. A preferred study hour refers to the amount of hours allocated for reviewing the course material. The three choices given were: more than 10 hours, 5 to 9 hours and less than 4 hours. It was found that only Test irrelevant thinking (p-value = 0.019) did support the hypothesis. The others showed no significant result. It revealed that the students who study less than 4 hours per week experienced high levels of Test irrelevant thinking (mean 1.160). The students who study more than 10 hours per week exhibited the opposite result (mean –0.336). The respondents were asked about their study attitude before they sat for any tests. The three choices given were “consistent study”, “when I feel like it” and “last minute study”. The result reported that Bodily symptom (p-value = 0.023) and Worry (p-value = 0.042) variables have sufficient evidence to infer the hypothesis. It was found that the students who have a consistent study behavior exhibited the highest score (mean 0.094). Surprisingly, the students who studied last minute, indicated the lowest score (mean –0.107). Unlike the Bodily symptom variable, the students who had a consistent study pattern experienced the lowest level of Worry (mean –0.152) while the students who had a last minutes study pattern experienced the highest level of Worry (mean 0.094).

Discussion of the Results This section discusses the association between test anxiety and academic performance as well as the comparison of test anxiety level among the DBS students from different cohorts and students from various programs. It also discusses the effect of demographic and environmental factors towards test anxiety.

176 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock

The Association between Test Anxiety and Academic Performance On the basis of research viewed earlier, it has been reported that there are negative relationships between the levels of test anxiety and academic performance. Those who score high in test anxiety generally performed less well academically than those who have a low level of test anxiety (Hambree, 1988). In the present study, the same pattern of results was replicated. From the findings, Self-defeat was found to have an inverse relationship with academic performance for all programs. Business Foundation students reported a similar pattern of results with the additional Worry variable. The DIA program also indicated a negative relationship between Worry and academic performance. For the current study, Worry was found to have a strong association with academic performance particularly with the students enrolled in the Business Foundation program. Worry refers to uncontrollable cognitive activity that relates to negative thought that results in emotional discomfort to an individual. Examples of negative thought include expecting to perform poorly on test, not being confident or being doubtful of one’s ability and thinking extensively about the consequences of failing the test. Therefore, the students who score high in level of Worry are more likely to have lower academic results. This result was consistent with the study found by Sarason (1984) indicating that Worry is more strongly related to poor performance. In addition, Wine (1980 and 1971) reported that the impairment of performance is due to the cognitive component and Worry is one of the elements in the cognitive component. The results of the present study indicated that Worry is strongly and negatively associated with performance. Thus, it supports the Interference model such as when high anxious students are under evaluative situations, they engage more on cognitive activity (i.e., Worry) that may interfere with their task accomplishment (i.e., answering the examination questions). This result is supported by Mwamwenda (1994). Clearly, the Interference model seems relevant in the present study. Thus, the accounting lecturers in particular have to implement the appropriate test anxiety treatments which focus on reducing the test anxiety that inhibits students from retrieving course contents during examinations.

Comparison of Test Anxiety Level among the Students between Uitm Campuses The current study revealed that the Worry variable showed a significant difference in terms of level of test anxiety among the three cohorts of DBS students. The result suggests that the students from semester 2, 2004/2005 were more likely to be exposed to the negative thought which might have resulted in emotional discomfort as compared to their counterparts. In comparing the level of test anxiety among the DIA, DBS and Business Foundation students, the present study reported that Bodily symptom, Tension and Self-defeat showed a significant difference in the level of test anxiety among these groups of student. The Business Foundation students were found to have the lowest level of Bodily symptoms and Self- defeat while DBS students exhibited the highest score for both variables. Therefore we can infer that DBS students were more anxious and more likely to experience headache, stomachache and shaking during test taking. However, Business Foundation students feel more tension during the test and feel uneasy just before they receive their test paper back.

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The Effect of Demographic and Environmental Factors Towards Test Anxiety Some research suggests that test anxiety can be situationally specific and thus may vary depending on the environmental or demographic factors (Bruce, 1994). There are several environmental and demographic factors considered in this study in order to serve the third research objective. They include student’s gender, hometown, exposure to accounting subjects during SPM, age, reasons for enrollment and student’s study behaviour. This section highlights the significance of the results. The students may relate test anxiety to the preparation done before exams or their study behaviour. Normally, less preparation would seem to lead to higher test anxiety due to the greater chance of poor performance. The result of the present study revealed the relationship between the level of test anxiety and level of preparation (i.e., student’s study behavior). In relation to preferred study hours, the finding suggests that the students should engage in their study for more than 4 hours per week. It is proven that those who studied less than 4 hours per week were more likely to be less prepared, thus more anxious for the tests, particularly for the courses concerned. Unexpectedly, the current findings reported that the students who studied consistently before their tests indicated the highest level of Bodily symptoms and the opposite result was found. However, the students who studied consistently exhibited the lowest score for level of Worry and those who studied last minute experienced high levels of Worry. This finding implies that students should engage in their studies consistently. It is proven that those who study consistently are more likely to be well prepared, thus less anxious for the test. The present study was inconsistent with the result obtained by David (2004) who reported no significant difference in the level of test anxiety and study behaviour.

CONCLUSIONS, RECOMMENDATIONS, AND FUTURE RESEARCH The four-factor model of test anxiety in the RTA scale established by Benson and El Zahhar (1994) can be used as a basis for describing data in the present study. The factorial invariance across diverse population suggests that the RTA scale is potentially a useful crosscultural instrument. In line with previous research, the present study demonstrates an inverse relationship between test anxiety and academic performance. The Cognitive factor (i.e., Worry) has emerged as the strongest predictor of academic performance among the factors. This result suggests that students may be able to reduce test anxiety by addressing the problem of distracting thought during examinations. In examining levels of test anxiety among DIA, DBS and Business Foundation students from UNITEN, the DBS students reported the highest score in the most significant variables. Furthermore, the level of test anxiety varies depending on environmental and demographic factors. Most of the demographic factors exhibit no significant results. From the theoretical standpoint, the effect of test anxiety on academic performance can be explained within the Interference and Deficit models. The current results support the

178 Mohd Ariff Bin Kassim, Siti Rosmaini Bt. Mohd Hanafi and Dawson R. Hancock Interference model which stresses the detrimental effect of negative thoughts during test taking situations. The two models used in explaining the effect of test anxiety on academic performance have been conceptualised by some researchers as being mutually exclusive (Jochen and Arndt, 1999). However, some of the researchers proposed that both Interference and Deficit were complementary rather than contradictory (Naveh-Benjamin, McKeachie and Lin 1981). This implies that lower test score of anxious students can occur either by lack of study skills or interference in the retrieval of prior learning or by the combination of both. This assumption sets the stage for further investigation to test whether both models are contradictory or complementary. In addition, research is also encouraged to investigate the effect of test anxiety on performance with the inclusion of intervening variables such as selfefficacy, personality and learning strategies.

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In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 9

THE PREVALENCE OF DEPRESSION AMONG FEMALE UNIVERSITY STUDENTS AND RELATED FACTORS Fernando L. Vázquez∗a, Ángela Torresb, María Lópeza, Vanessa Blancoa, and Patricia Oteroa a

Faculty of Psychology b Faculty of Medicine, University of Santiago de Compostela, Spain

ABSTRACT In many countries, university students now constitute a significant proportion of their age group. As in the general population, depression is relatively frequent in this group, and affects women more than men. In the study described here we evaluated the prevalence of depression, depressive symptoms and associated factors among 365 young women sampled randomly, with stratification by year and discipline, from among the 18,180 female students attending a Spanish university (65.9% of its total student roll). The prevalence of current major depressive episode was 10.4% (95% CI 7.5-14.0%). Among students with current depression, the commonest symptoms were depressed mood (86.5%) and alteration of sleep (78.9%). Some 52.6% of depressed students had suffered one or more previous depressive episodes (M = 1.2; SD = 1.5), and 13.2% had attempted suicide, but the existence of previous depressive episodes did not increase the risk of a current episode. Increased risk was associated with recent problems, which multiplied the odds of depression by 2.31 (95% CI 1.26-4.26), and with smoking in the past month, which multiplied the odds of depression by 2.01 (95% CI 1.09-3.89), but not with the use of alcohol, cannabis or cocaine in the past month. Nor was there any significant association between depression and declared social class, monthly family income, university course level, geographical background (urban or rural), persons lived

∗

Corresponding author. Universidad de Santiago de Compostela, Facultad de Psicología, Departamento de Psicología Clínica y Psicobiología, Campus Universitario Sur, 15782 Santiago de Compostela, Galicia, Spain. E-mail: [email protected]

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Keywords: depressive disorder, prevalence, epidemiology, students, cross-sectional study.

INTRODUCTION Depression is one of the commonest psychiatric disorders in the general population, with an estimated prevalence of around 16% (Kessler et al., 2003). It is currently responsible for some 5% of the all-cause burden of disease (Hyman, Chisholm, Kessler, Patel, and Whiteford, 2006), which makes it the leading cause of non-fatal burden and the fourth leading cause overall (Ustün, Ayuso-Mateos, Chatterji, Mathers and Murray, 2004); it is predicted that it will be the overall leading cause of disability and death by the year 2030 (Mathers and Loncar, 2006). It not only affects those who suffer it directly, but also causes great suffering to their families and disrupts everyday activity and productivity; it often complicates the evolution of physical disorders, and increases the risk of suicide (Wang and Kessler, 2006). Women are about twice as likely as men to suffer depression (Marcus et al., 2005). Among adolescents and young adults, the risk of depression is also greater for females than males: about one in three young women have at some time in their lives suffered depression, as against one in five young men (Kessler and Walters, 1998). University students, who in many countries now constitute a considerable proportion of their age-group, share this general trend: depression is a frequent disorder in this population, especially among women (Adewuya, Ola, Aloba, Mapayi, and Oginni, 2006; Allgöwer, Wardle, and Steptoe, 2001; Apfel, 2004; Clark, Salazar-Grueso, Grabler, and Fawcett, 1984; Dahlin, Joneborg, and Runeson, 2005; Eller, Aluoja, Vasar, and Veldi, 2006; Rimmer, Halikas, Schuckit, and McClure, 1978; Schuckit, 1982; Tomoda, Mori, Kimura, Takahashi, and Kitamura, 2000; Vázquez and Blanco, 2006). The risk of emotional disorders increases under stress, and university students can be put under stress not only by accommodation, finance and social problems, but also by academic difficulties (demands and deadlines, exams, grades and competition, uncertainty about career and future success) and by their awareness that they must at this stage make some of the most important decisions in their lives. Such pressures can trigger the onset of depressive episodes in susceptible students and, in turn, depression can negatively affect academic performance by altering memory function and other learning processes (Dyrbye, Thomas, and Shanafelt, 2006; Hysenbegasi, Hass, and Rowland, 2005; Murphy and Archer, 1996). The university has been described as a critical context for studying mental health in youth (Weitzman, 2004). In spite of the evidence of the vulnerability of university students to depression, and the plausibility of the above reasons, the phenomenology of depression in this population has been insufficiently investigated, especially as regards any distinctive characteristics of depression among female university students. In particular, only two studies have been published in which the object of study has been clearly defined by the use of the DSM-IV criteria of depression: a study of first-year students in Japan (Tomoda et al., 2000), and a study of Swedish medical students (Dahlin et al., 2005). There is therefore a need for broader

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studies of well-defined depression among university students, especially considering that depressive episodes can not only disrupt a student’s life during this period that is critical for his or her future, but can also, as in the case of adolescents (Lewinsohn, Clarke, Seeley, and Rohde, 1994), predispose towards further episodes (Franko et al., 2005); hopefully, such studies would help orient the design of preventive strategies. In view of the apparently greater prevalence of depression among female students, and the possibility that depression among female students may have specific characteristics relevant to the design of preventive strategies, the need for studies of female students is particularly urgent. The objectives of the present study of a random sample of female university students stratified by course year and discipline were to determine the prevalence of DSM-IV major depressive episodes (MDEs) among female university students, to characterize the typical symptom profile, and to identify associated factors.

METHOD From among the 18,180 female students on the roll of the University of Santiago de Compostela, Spain (65.9% of all students enrolled in this institution), a sample of 368 was randomly selected, with stratification by course year and discipline. Each student in the sample was personally contacted and invited to participate in the study; its nature, objectives, risks and benefits were explained, confidentiality and anonymity were assured, and any questions they might have about it were answered. Participation was totally voluntary, and no economic, academic or other kind of incentive was offered. Three of the initial sample declined the invitation to participate, leaving a final sample of 365 students who gave written consent prior to participation. The study was reviewed and approved by the Ethics Committee of the University of Santiago de Compostela. Data on depressive symptoms, diagnoses of depression, personal relationships, academic performance and sociodemographic background were obtained from each participant in a 20– 30—minute personal interview with one of three psychologists given specific training for this study. During this interview, Muñoz’s Mood Screener (Miller and Muñoz, 2005; Muñoz, 1998) was administered to determine whether the participant was currently suffering, or had ever suffered, an MDE; these screening results were subsequently used to estimate the prevalence of MDE in the sample. The Mood Screener essentially comprises eighteen items designed to evaluate the nine positive DSM-IV symptoms of MDE (nine items for current MDE and nine for sometime MDE), plus two more to assess satisfaction of the DSM-IV requirement that these symptoms significantly interfere with the subject's life or activities. A positive result for sometime MDE consists in the subject reporting having experienced, over some two-week period during his or her life, at least five of the nine symptoms, including one of the first two (depressed mood and anhedonia), together with satisfaction of the interference requirement. The criterion for current MDE is the same, except that the items now refer to the 2 weeks preceding completion of the Screener. The values of kappa for concordance of the Mood Screener with the Primary Care Evaluation of Mental Disorders scale (PRIME-MD) and with the Structured Clinical Interview for DSM-IV Axis I Disorders - Clinical Version (SCID-CV) have been reported as respectively 0.75 (Muñoz, McQuaid, González, Dimas, and Rosales, 1999) and

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0.758 (Vázquez, Muñoz, Blanco, and López, in press). The sensitivity and specificity of the Mood Screener for detection of MDE in a non-clinical population are 0.969 and 0.967, respectively (Vázquez et al., in press). The interviewers were trained for this study by a psychologist with 14 years’ experience of clinical evaluation who had himself been trained in the use of the Mood Screener by its author. Training consisted of two 90-minute “theoretical” sessions, followed by practice sessions in which the interviewers applied the instrument to subjects similar to those taking part in the main study, but who did not themselves actually participate in the main study. The theoretical sessions involved explanation of the instrument, role play, and practice in the diagnosis of depressive disorders by consideration of 10 cases. Videotapes of the practical sessions were used by the instructor to evaluate deviation from the interview protocol, and to correct the interviewers accordingly until performance was satisfactory; in all, 18 subjects took part in these practice sessions. Statistical analyses were performed using SPSS software (version 14.0). Data are presented as percentages for categorical variables, and as means, standard deviations and medians for continuous variables. The relationship between current MDE and other variables was evaluated using logistic regression (both with and without adjustment for age), for which purpose two age groups were defined (< 20 years and ≥ 20 years) and “number of friends” was split in three groups (0-2, 3-9 and > 9). Since weighting did not significantly influence the estimated odds ratios (ORs), only the results of unweighted analyses are presented. Confidence intervals (CIs) for the values of parameters in the population from which the sample was drawn were estimated by calculation of exact binomial probabilities.

RESULTS Mean student age was 21.9 years (SD = 2.4 years) (see Table 1). Some 99.3% of the sample were single, 40.3% were from families with a monthly income of 960-1,920 €, 74.5% described themselves as middle-class, and 67.9% came from urban localities. 67.4% were studying social sciences, law or humanities, and 66.3% were in the third or subsequent years of their undergraduate course. 47.0% lived with their parents during term time, 58.7% had failed one or more of the subjects taken the previous year, and 57.8% did not take part in regular sports activity. The mean number of friends declared was 8.2 (SD = 10.2). 61.4% of participants had not recently had personal, social or other problems. In the 30 days preceding the interview, the legal psychoactive substance most commonly consumed was alcohol (76.2%), and the illegal substance most commonly consumed was cannabis (19.7%) (see Table 2). The prevalence of current MDE was 10.4% (95% CI 7.5-14.0%). Among students with current depression, the commonest symptoms were depressed mood (86.5%) and alteration of sleep (78.9%) (see Table 3).

The Prevalence of Depression among Female University Students… Table 1. Sociodemographic and academic profile of the final sample (N = 365) Characteristic Age (years) M SD Declared social class Upper Middle Lower NR/NS Monthly family income < 960 € 960-1920 € > 1920 € NR/NS* Geographical background Rural Urban University course level Years 1-2 3rd and subsequent years Kind of discipline Social sciences and humanities Health sciences Natural sciences and mathematics Passed all previous year’s subjects Yes NO NR/NS* Persons lived with during term Parents Friends Others Sports activity Yes No NR/NS* Number of friends M SD Recent problems? Yes No NR/NS* Note. (*) No response or not sure.

n

%

21.9 2.4 52 272 34 7

14.2 74.5 9.3 1.9

35 147 98 85

9.6 40.3 26.8 23.3

117 248

32.1 67.9

123 242

33.7 66.3

216 63 56

67.4 17.3 15.3

145 214 6

39.7 58.7 1.6

171 142 52 145 211 9

47.0 38.7 14.3 39.7 57.8 2.5

8.2 10.2 136 224 5

37.3 61.4 1.3

187

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Fernando L. Vazquez, Angela Torres, and Maria Lopez, et al. Table 2. Substance use in the past 30 days

Substance Tobacco Yes No NR/NS* Alcohol Yes No NR/NS* Cannabis Yes No NR/NS* Cocaine Yes No

n

%

202 162 1

55.3 44.4 0.3

278 86 1

76.2 23.6 0.2

72 291 2

19.7 79.7 0.6

6 359

1.6 98.4

Note. (*) No response or not sure.

Table 3. Frequencies of DSM-IV diagnostic symptoms among the 38 female students who screened positive for MDE

Depressed mood Anhedonia Weight loss or altered appetite Alteration of sleep Psychomotor agitation or retardation Fatigue or loss of energy Feelings of worthlessness or of excessive or inappropriate guilt Impaired concentration Thoughts of death

n 33 20 20 30 20 22 15

% 86.5 52.6 52.6 78.9 52.6 57.9 39.5

23 8

60.5 21.1

Some 52.6% of depressed students had suffered one or more previous depressive episodes (M = 1.2; SD = 1.5), and 13.2% had attempted suicide, but the existence of previous depressive episodes did not increase the risk of a current episode. Reported age at occurrence of the first episode was on average 17.3 years (SD = 3.4 years); 50.7% of students with current MDE had had their first episode at age 17 years or younger, and the average number of years that had elapsed since the first episode was 4.6 (SD = 3.4). Increased risk was associated with recent problems, which multiplied the odds of depression by 2.31 (95% CI 1.26-4.26), and with smoking in the past month, which multiplied the odds of depression by 2.01 (95% CI 1.09-3.89), but not with the use of alcohol, cannabis or cocaine in the past month. Nor was there any significant association between depression and declared social class, monthly family income, university course level,

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geographical background (urban or rural), persons lived with during term time (family, friends, etc.), whether all the previous year's exams had been passed, sports activity, or academic discipline.

CONCLUSION In this study a substantial proportion of female university students, more than 10%, were currently suffering an MDE. This rate is somewhat higher than the 1-month prevalence among US women (5.8%) (Ohayon, 2007), the average for European women (7.9%) (AyusoMateos et al., 2001), and the 12-month prevalence among young women in a representative nationwide sample of adolescent and young adult Finns (8.1%) (Haarasilta, Marttunen, Kaprio, and Aro, 2001). It is much higher than the average among Spanish women in general (1.8%) (Ayuso-Mateos et al., 2001). However, it is lower than depression prevalences reported in other studies of university students: 11.9% among female Nigerian university students (Adewuya et al., 2006) (although this figure included minor depressive disorder); 12.9% among Swedish female medical students (Dahlin et al., 2005); and 28.4% among firstyear female students in Japan (Tomoda et al., 2000). It therefore seems unlikely to be an overestimated, especially since only 14.2% of the sample were in their first year (when students are probably most vulnerable) and all interviews were carried out at a time of year when there were no exams to cause stress. Furthermore, a positive Mood Screener result requires a positive answer to the question on interference with life or activity; failure to evaluate this or other indications of clinical significance has been pointed to as a significant cause of overestimation by other instruments (Narrow, Rae, Robins, and Regier, 2002). It is well known that women are more prone to depression than men, regardless of whether the criterion employed is the level of depressive symptoms or a diagnosis of unipolar depressive disorder (Kessler et al., 2003; Mazure, Keita, and Blehar, 2002). The prevalence observed in the present study is twice that observed among male students at the same university (Vázquez and Blanco, in press). Similar differences between men and women have been observed in other studies of depression among university students (Adewuya et al., 2006; Dahlin et al., 2005; Tomoda et al., 2000). The typical symptom profile observed in this study among participants who screened positive for MDE was similar to that reported by Haarasilta et al. (2001) for young adult women in that, in both studies, depressed mood and impaired concentration are among the three most prevalent symptoms, and thoughts of death are among the least. Anhedonia, thoughts of death, and weight loss or altered appetite were all more prevalent in Haarasilta et al.’s study, and alteration of sleep in ours, but both studies suggest that physical symptoms of depression (fatigue, alteration of sleep, alteration of appetite) are common in major depressive episodes. A considerable proportion of the participants with current MDE in this study, 52.6%, had suffered previous episodes. This finding is in keeping with those of longitudinal studies in which the peak of first episodes has occurred soon after puberty (Lewinsohn et al., 1994; Newman et al., 1996: Oldenhinkel, Wittchen, and Schuster, 1999). However, the average number of previous episodes, 1.2, was fewer than the figure of about 10 observed in the U.S. National Comorbidity Survey (Kessler, Zhao, Blazer, and Swartz, 1997); average age at the

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time of the first episode, 17.3 years, was younger than figures in the 20s observed in studies of the general female population (Andrade et al., 2003; Marcus et al., 2005; Weissman et al., 1996); and the time elapsed since the first episode was shorter than the 15.5 years reported in one of these latter studies (Marcus et al., 2005). All these differences are of course probably attributable to the youth of our sample. Furthermore, this characteristic of our sample – or, more specifically, the consequent low value of the number of episodes suffered by anyone with sometime MDE (1.3) - also probably explains why we did not find that past MDE significantly increased the probability of current MDE, since the risk of MDE is known to increase with the number of previous episodes (Depression Guideline Panel, 1993). It is striking that five of the 38 participants who screened positive for current MDE, 13.2%, had attempted suicide. This is a very large proportion in comparison with the 2.7% reported by Dahlin et al. (2005) for Swedish medical students of both sexes, but is compatible with reports of 6-13% among adolescents (Garland and Zigler, 1993; Ruangkanchanasetr, Plitponkarnpim, Hetrakul, and Kongsakon, 2005) and less than the 19.7% observed by Marcus et al. (2005) among adult outpatients with depression. Personal problems in the previous 6 months significantly increased the risk of current MDE in this study. This is in keeping with the results of studies that clearly show the relevance of serious adverse personal experiences to the commencement of depression (see, for example, Kendler, Neale, Kessler, Heath, and Eaves, 1993; and Mazure, Bruce, Maciejewski, and Jacobs, 2000). Maciejewski, Prigerson, and Mazure (2001) reported that women are three times more likely than men to suffer depression in response to stressful events. The observed relationship between smoking and depression in this study was not unexpected. It is well known that nicotine is one of the substances related to depression, and similar associations have been observed in a number of other studies of university students and other young people (Adewuya et al., 2006; Allgöwer et al., 2001; Haarasilta et al., 2001). The relationship is two-way: smoking can increase the risk of depression, and vice versa (Choi, Patten, Gillin, Kaplan, and Pierce, 1997; Rao, Daley, and Hammen, 2000). It may be pointed out that because the target population of this study consisted of university students, comparison of its results with those of similar studies carried out in other societies may possibly be more meaningful than for studies of the general population: it has been suggested that cross-cultural comparison of results on depression is more transparent when they concern undergraduate students than when it is necessary to control for confounding factors such as type of job, job-related stress, and marital stress (Iwata and Buka, 2002). The findings of this study suggest that therapeutic resources and preventive measures should target female university students as a population at relatively high risk of major depression, a disorder with possible life-long consequences. Teachers, educational authorities and students themselves should be made more aware of the threat of depression, and measures should be taken to minimize this threat, including measures to promote awareness of depression as a disorder and not a stigma.

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ACKNOWLEDGMENTS This study was supported by grant PGIDT05PXIA21101PR from the Directorate General for Research and Development (Counsellery of Innovation, Industry and Trade) of the Xunta de Galicia (Spain).

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In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 10

RELATIONSHIPS BETWEEN MOOD, COPING AND STRESS SYMPTOMS AMONG STUDENTS WHO WORK IN SCHOOLS Dafna Kariv1a and Tali Heiman2b 1

School of Business Administration, The College of Management, Israel 2 Department of Education and Psychology, The Open University of Israel, Israel

ABSTRACT The study examined the mood states of 229 men and women who are simultaneously full-time students and school staff when coping with their dual-demanding stressful environments. A causal model was developed to demonstrate that the dual-demanding stressors that the respondents faced affected their moods; these moods are pre-behavioral factors that affected their coping strategies. Results of multilevel analyses indicated that men and women differ in the magnitude of their experienced moods, but both genders experience vigorous moods as a prime emotional reaction to the dual-demanding environment. Moods were found to affect both male and female coping strategies, in all categories except social support. The genders differed in the coping strategies adopted, except for task-oriented strategies. In addition, the analyses revealed gender differences in expressing angry and depressed moods, where females reported experiencing higher levels. These results reinforce our assumption that coping with dual-demanding environments, especially by individuals who are employed in stressful occupations, reflects not only a gender-based tendency but also the mood states that derive from the stressors. Results revealed that men and women manifest identical patterns in coping with dual-demanding stressors, and that these patterns are related to their moods. Thus, coping strategies seem to depend on context rather than on gender. a b

E-mail address: [email protected]. Address: Yizhak Rabin Boulevard, Rishon Le Zion, Israel E-mail address: [email protected]. Address: 108 Ravutski Street., Ranana, 43107, Israel

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Key words: students; school staff; genders; coping; stress; mood. Working-students who are employed as school staff (teachers and principals), probably face higher levels of stress than 'regular' students as teaching is considered one of the most stressful jobs; excessive workload, pressures of school inspections and disruptive pupil behavior are only a partial list of key causes of teachers' stress; in the process of school management, school principals encounter specific stressors such as unnecessary bureaucracy, providing cover for teacher shortages and absences (Brouwers & Tomic, 2000; Griffith, Steptoe & Cropley, 1999; Morton, Vesco, Williams & Awender, 1997). Functioning as a teacher or principal simultaneously with being a full-time student (TP-S) requires coping with such demanding environments by controlling, adjusting, seeking assistance and fighting the variety of stressors encountered. The suggestion that women choose emotion-oriented coping strategies or avoidance, and that men opt for task-oriented strategies (Billings & Moos, 1981; Stein & Nyamathi, 1999) "because of their gender" implies that both women and men expose themselves to risk in the dual-demanding environments by avoiding or minimizing the use of the most potentially beneficial coping strategies for eliminating the stress – or stressors – they face. In this study we propose that male and female TP-Ss cope differently with the variety of stressors they encounter in their dual-demanding environment due to differences in mood states developed among each gender group; moods which are cultivated by the environment's stressors and in turn influence the coping behavior related to these stressors.

Gender and Moods Moods are generally defined as diffuse and long-lasting emotional states that influence rather than interrupt behavior. Moods are assessed through negative mood states of anger, confusion, depression, fatigue, tension (Russel, 2003; Terry, Lane, Lane, & Keohane 1999; Terry, Lane & Fogarty, 2003), as well as positive mood dimensions, such as vigor, happiness, well-being and calmness (Hanin, 2000). Studies of gender and emotionality indicate that among adult samples, men are generally less emotional and tend to lower mood intensiveness than women (Brody, 1997; Manstead, 1992). Moreover, women are usually more selfdisclosing than men (Winstead, Derlega & Wong, 1984), while men are less willing than women to reveal information about their expressive, interpersonal behaviors as well as behavior that may indicate the weaknesses or threats they face in their jobs. Thus, women are more likely to report their moods as affected by stressors they face, while men are less likely to do so, which may result in a certain amount of imprecision in each gender's self-assessment of performance (Snell, 2001) Yet an examination of the specific mood states shows that relationships between moods and gender are inconsistent among college students. While most studies in the area of gender and moods demonstrate that men report less frequent mental distress than women in college (Jones & Cochrane, 1981; Federal Centers for Disease Control and Prevention CDC6, Student

6

U.S. Department of Health, Education and Welfare, Public Health Service, National Center for Health Statistics (1977), A concurrent validation study of NCHS general well-being schedule, series 2, number, 73.

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Mental Health Planning, Guidance and Training Manual7; Shaikh, Kahloon, Kazmi, Khalid, 2004; Surtees, Wainwright, & Pharoah, 2002), as well as stress and fatigue at work (Kariv, Offer, Notzer & Dolev, 2005); others show that male students are more likely than female students to be depressed (Grant, Marsh, Syniar, Williams, et al., 2002), and express more anger; anger is often viewed as "masculine", especially when it involves acting the anger out physically (Thomas, 2003). Other studies report no significant gender differences in mood states of college students (Butler & Nolen-Hoeksema, 1994; Scarbrough & Hicks, 1998); in gender differences regarding expressions of anger at work (Gianakos, 2002); or in experiencing anxiety or fear (Humphrey, Yow & Bowden, 2000). While these findings focus on negative moods of anger, depression and tension (Katz & Bertelson, 1993; Wilson, Pritchard & Revalee, 2005), the exploration of positive moods as manifested by the genders is limited in the research, especially in the context of TP-S. This is probably due to the fact that in the academic world, the result of negative moods is costly for both the students and the college management, as it is related to student dropouts, low academic achievement or students' violent, abusive or suicidal behavior. However, the field of positive psychology (Seligman & Csikszentmihalyi, 2000; Shirom, 2003) does provide evidence that vigorous moods allow individuals to effectively cope with work-related demands (Luthans, 2002), as these moods tend to promote goal-directed behavior likely to increase individuals' personal resources (Hobfoll, 1999). Because positive affective states are indicators of subjective well-being (Katwyk et al., 2000), gender differences that emerge in well-being (Diener, Suh, & Oishi, 1997) may indicate gender differences in experiencing vigorous moods. In this case, women are more likely than men to report on higher positiverelated emotions such as vigor, energy, joy, etc. We postulate that dual-demanding academic and work stressors (Daniels, Brough, Guppy, Peters-Bean & Weatherstone, 1997; Kahn & Byosiere, 1992) elicit moods, both positive and negative, that could be the bridging link between the dual-demanding stressors and the performative aspect: coping strategies employed by male and female TP-Ss.

Coping and Moods Coping is the response that serves to alter the environment to reduce demands or to increase personal resources to address demands (Hobfoll, Dunahoo, Ben-Porath, & Monnier, 1994; Lazarus & Folkman, 1984). Coping strategies that create a positive affect are considered effective and adaptive and may include reframing, problem solving, and infusing events with positive meaning (Folkman & Moskowitz, 2000; Diener, et al., 1997). The choice of coping strategies when facing stressors has been found to relate to individuals' assessment of the demanding situations in terms of controllable or uncontrollable (Folkman & Lazarus, 1985): emotion-oriented coping is more likely in uncontrollable than in controllable situations, and task-oriented coping is more likely in controllable than in uncontrollable situations. In general, the fact that students prefer to chose task-oriented coping strategies, perceiving them as helpful and adaptive relative to the stressors they encounter (Holahan, Moos & Schaefer, 1996) implies that they believe their college lives to be controllable. Yet, the degree of emotional distress reported by students (Butler & Nolen-Hoeksema, 1994; Monk, 2004) 7

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suggests that many students are insufficiently equipped to cope with situations they perceive as demanding. Previous studies found a positive relationship between negative moods and task-oriented coping strategies among samples of college students (Catanzaro & Greenwood, 1994; Kirsch, Mearns & Catanzaro, 1990), while others found positive associations between negative moods and avoidance, and between negative moods and help-seeking strategies (Gellis & Kim, 2005) among students. Different mood categories are related to different coping choices. For example, emotional distress and depressed moods have a strong impact on college students' use of emotionfocused coping and avoidance, and were found negatively related to the use of problemfocused coping (Chang & Strunk, 1999; Coyne, Aldwin & Lazarus 1981); no such evidence is found for anxiety and tension (Edwards & Endler, 1989). Tense individuals seem overall to use more strategies to cope with daily stress (Raffety, Smith, & Ptacek, 1997) as compared to depressed students who are more rigid and more likely to use limited coping strategies. Most of the strategies adopted by tense students were not of the active coping kind (such as planning, taking direct action, or screening out other activities), but rather inactive (such as sleeping, leisure pursuit and relaxation). Angry moods which include expressions of anger including physical assaults on people and objects, verbal assaults and arguing, and other negative behaviors, as well as tension were negatively related to task-oriented coping and to social support (Lane, 2001; Lane & Terry, 2000; Monnier, Stone, Hobfoll & Johnson, 1998; Whatley, Foreman & Richards, 1998), probably because anger and tension increase through frustration with the failure to attain selfset performance goals. Fatigue was found to be related to greater social support as well as to indirect coping, such as sleeping, recreation and leisure time (Shaikh, et al., 2004). Some studies found that people who experience higher levels of stress, anxiety, or depression use more maladaptive coping (Aldwin & Revenson, 1987; Folkman & Lazarus, 1985), suggesting that such mood states influence the choice of irrelevant or inappropriate coping strategies in managing the stressful situations they face. Positive moods, a relatively neglected aspect in research, were found to be related to active coping, less denial, less avoidance and more social support (Brissette, Scheier & Carver, 2002), as well as with more task-oriented coping strategies among undergraduate students (Park, Armeli & Tennen, 2004). Other studies strengthen the findings on positive moods and optimism and their association with avoidance (Martin & Stoner, 1996).

Coping, Moods and Gender Gender differences in use of coping strategies have been reported in a number of studies. Findings suggest that females appear to favor social support, emotion-focused, and avoidant coping strategies relative to males (Billings & Moos, 1981; Ptacek, Smith, & Zanas, 1994; Stein & Nyamathi, 1999), whereas males appear to favor stress release through other activities and tend more often to turn to drugs or alcohol, relative to females (Bird & Harris, 1990; Stein & Nyamathi, 1999). There are inconsistent findings regarding gender differences in the use of problem-focused or active coping strategies. While most studies suggest that males use problem-focused strategies more often than women (Stone & Neale, 1984), others

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indicate that women use them more than men (Billings & Moos, 1981; Ptacek, et al., 1994); while still others find no differences (Hamilton & Fagot, 1988). Depressed moods were found to relate to gender: women report on depressed moods more frequently than men (Murakumi, 2002); and were diagnosed with depression symptoms twice as often as men (Blazer, Kessler, McGonagle & Swartz, 1994; Nolen-Hoeksema, 1994). Women were also more likely to report on tense moods, and their tension was found to increase over time when facing stressful situations, while men's tension remained the same over time (Tobar & Morgan, 2002). Sleep loss intensified negative emotions and fatigue among both men and women, while emotion-oriented strategies were mitigated (Zohar Tzischinsky, Epstein & Lavie, 2005), and vigor and optimism were more likely to relate to social support and emotional well-being perceptions among women in a study that did not assess men’s perceptions (Sumi, 1997). Among college students, female students who reported depressed moods tended more to reach for social support and adopt emotion-oriented strategies as compared to male students (Hammen & Peters, 1978; Heiman & Kariv, 2004). Male students who use task-oriented coping techniques reported experiencing less distress (Higgins & Endler, 1995), while the use of emotion-oriented coping strategies was a significantly positive predictor of distress in both men and women. Certain levels of social support are used by both genders (Wilson & Multon, 2001); with more female students applying for social support than male students (Kariv & Heiman, 2004). Teachers and school principals were found to manifest fatigue moods (Gaziel, 1993), a feeling of ambiguity and tense moods, but their coping enhanced their effectiveness (Chen & Miller, 1997). Other studies showed that teachers generally used more avoidance in coping with stressors (Lazarus & Folkman, 1984), or 'uncontrolled aggression', but these were assessed as negative coping strategies while pro-active-oriented coping was considered an effective way of coping (Austin & Muncer, 2005). School principals and educational executives are increasingly faced with more pressure, aggression, change, and conflict than ever before (Cooper, Sieverding & Muth, 1988; Gmelch, 1983). Studies on a sample of academic institutional executives revealed that females experienced higher levels of work-related stress but appeared to be happier in their jobs (Wolverton, Wolverton & Gmelch, 1998). Other studies showed that executives reporting on high stress that originated from their responsibilities favored the use of problemfocused coping in managing the stressors (Gianakos, 2002; Latack, 1986). The present study proposes an integrative causal model (see Model 1) which shows that stressors of dual-demanding environments (work and college studies) and personal attributes impact TP-Ss’ moods. These moods then engender corresponding coping strategies: taskoriented strategies, emotion-oriented strategies, avoidance and social support.

Hypotheses In our review of the literature dealing with gender and coping strategies, we have shown that empirical research scarcely explored the question of whether men and women TP-Ss develop different experienced moods derived from their dual-demanding environment. Moreover, the results gathered on college students show that 'gender matters', but inconsistent results on gender differences in moods emerge. Therefore, our first hypothesis is:

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Stressors of dual demanding environments a. Conflicting demands, derived from work and academics; b. Limited time for leisure due to overloads at work and/or at the college; c. Limited time dedicate to academic studies inside and/or outside the college hours; d. Long and erratic hours spent at work/college

Personal Attributes Gender Age Being Married

Task-oriented coping strategy

Moods Angry Confused Depressed Fatigue (exhausted) Tense Vigor

Emotion-oriented coping strategy

Avoidance

Social support Family Friends Significant others

Model 1. Stressors of dual-demanding environments (work and academic) and the relationship to moods and coping strategies among men and women.

Hypothesis 1: Male and female TP-Ss differ in their self-reported mood states derived from their dual-demanding environment. The literature shows that moods have an impact on actions, thus on coping strategies, however each mood category affects different coping strategies, differentiated by gender. According to the literature, gender differences are shown in negative moods and positive moods and their effect on the employment of specific coping strategies. Hypothesis 2: Negative moods (depression, fatigue, anger, confusion and tension) of TP-Ss have an impact on avoidance, with depressed moods affecting the use of emotion-oriented coping, and fatigue effecting social support. Positive moods cause TP-Ss to adopt taskoriented coping strategies and social support. The next hypothesis examines indicators that predict the choice of coping strategies among male and female TP-Ss. In order to decipher the significant indicators of coping strategies, we have included stressors of the dual-demanding environment, personal attributes and moods. Hypothesis 3: Emotion-oriented coping strategies are influenced by women's negative moods; task-oriented strategies are influenced by men and women's positive moods and avoidance – by men's and women's negative moods. Social support is more likely to appear among women and in depressed as well as vigorous moods.

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METHOD Participants The target population consisted of students in three Israeli academic institutions, two universities and a college, studying in continuing education programs. Only students who reported that they worked full-time as school staff, i.e., teachers or principals, were included in the study. T-tests and Chi squares show no significant differences between the students of the three academic institutions in terms of gender or age distribution; nor between the teachers versus the principals. Continuing programs in education are graduate programs developed to meet the express needs of teachers and school executives by fostering academic, practical, and professional development. These programs respond to the unique educational requirements of working adults in schools or in other educational areas, who seek to pursue professional and personal development through academic studies. These programs provide high quality relevant content, an advanced level of professional knowledge, and relevant skills for ambitious teachers who wish to be leaders in their schools, communities, and fields.

Participants The sample consisted of 229 students, 133 (58.1%) male and 96 (41.9%) female. The average age of the respondents was 38.72 (S.D. = 10.36); the average age of men was 39.96 (S.D. = 11.09) and women, 37.06 (S.D. = 9.33). Frequencies revealed that 173 (73.6%) were married, of them 57% were men and 43% were women; most of the respondents were parents to 1-3 children. 141 respondents were teachers, of these 71 (53.8%) were male and 70 (72.9%) were female. The rest, 88 (38.4%), reported holding managerial positions in schools.

Measures A four-part questionnaire was employed in this study composed of: (1) Stressors: only stressors representing the combination of work and academic loads in dual-demanding environments (Kariv & Heiman, 2005) were assessed. Our main interest was the focus on the combination of two demanding environments in respondents' lives rather than identifying each stressor as it related to the work or the college environment. Four variables were included: conflicting demands derived from work and academics; limited time for leisure due to overloads at work and/or at the college; limited time dedicated to academic studies within and/or outside of college hours; long and erratic hours spent at work/college; (2) Mood scale: Mood was assessed using the 24-item Brunel Mood Scale (BRUMS) (Terry, et al., 1999). The BRUMS assesses six subscales of anger, confusion, depression, fatigue, tension, and vigor with each containing four items. This scale serves as a brief measure of mood states among adolescent and adult populations, based on mood descriptors on which respondents indicate whether they have experienced such feelings on a 5-point scale. When responses from the four items in each subscale are summed up, a subscale score in the range of 0-16 is obtained.

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The BRUMS was initially developed for use with adolescents, and it is equally valid for use with adults. Terry, Lane & Fogarty (2003) provide evidence of content validity and confirmatory factor analysis results that lend support to a 24-item six-factor structure. The subscales of BRUMS include the following mood descriptors: anger, confusion, depression, fatigue, tension and vigor items. Items are rated on a 5-point scale ranging from 0 ("not at all") to 4 ("extremely"). In this study we classified the mood categories into dichotomous variables in order to sharpen the differences in moods: responses of 3 and 4 were represented by 1, while the other responses (0-2) were represented by 0; (3) Coping strategies were measured using Endler & Parker's (1999) Coping Inventory for Stressful Situations (CISS). This is a 53-item measure of coping styles composed of three factors: (a) Task-oriented coping, (b) Emotion-oriented coping and (c) Avoidance. In this study only the task- and emotion-oriented strategies were examined since most of the literature on managers and coping addresses active (task- and emotion-oriented) rather than a passive (avoidance) coping reactions to stressors they face. The 1–5 scale for these two coping strategies ranges from 1 (seldom used) to 5 (always used). The Cronbach alpha coefficients obtained for the entire scale of coping strategies were: task-oriented, α = 0.89 and emotion-oriented, α = 0.87, indicating that the coping strategies questionnaire is a reliable measure of adult coping orientations for a high-level educated population. A principal components analysis was performed on the items of the CISS. In support of Endler and Parker (1990a), three large components were identified, accounting for 46.9% of the total variance. Most of the items for the task-oriented coping factor had loadings of .60 or greater; and most of the items of the emotion-oriented coping factor resulted in loadings of .50 or greater; and the (4) Social support scale was assessed using the Multidimensional Scale for Social Support (Zimet, Dahlem, Zimet & Parley, 1988). This is a social network support scale focusing on a person’s social network and is broken down into: (1) friends; (2) family; and (3) significant others. The scale for this coping strategy ranges from 1 (never used) to 7 (always used). The Cronbach alpha coefficients obtained for this strategy were: for the social support factor as a whole, α = 0.92; for family, α = 0.91; for friends, α = 0.99; and for significant others, α = 0.90. Additional questions on personal and demographic characteristics (gender, age, and family status) were included as well.

Procedure First, we administered the questionnaires to the entire student population in graduate education programs in each of the three academic institutions. Research assistants distributed the questionnaire through the students' academic e-mail; the response rate was 12%. In light of the low response rate, we turned to a second stage of sampling, based on network sampling. Research assistants contacted the respondents who had completed the questionnaires, by e-mail or telephone, and obtained names of TP-Ss from these respondents, then additional subjects from the second set, and so on. The questionnaires were distributed both by e-mail and face-to-face meetings at the second stage.

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RESULTS Means and standard deviations and graphic representations are shown in Table 1, Figures 1 and 2. The data show that the highest mean self-reported mood categories (anger, confusion, depression, fatigue, tension, vigor) measured dichotomously (0,1) was vigor with a mean of .827 (S.D. = 0.38) for men and .865 (S.D. = 0.34) for women. The findings show that women are higher than men in each mood category, positive and negative. 1 0.8 0.6 0.4 0.2 0 Men angry

confused

Wom en depressed

fatigue

tensed

vigor

Figure 1. Mooods within Each gender group.

M en

vigor

tense

fatigue

depressed*

confused

0 0 0 0

1 ,8 ,6 ,4 ,2 0

angry*

The data also illustrate that in most categories men and women report the same categories of moods and almost in the same order, though to a different extent (Figure 2); the highest mean among both genders is vigor followed by confusion. Among the men, the next category is depression, followed by anger, while among the women, these two moods have the same mean with anger having higher variance (S.D. = .45) as compared to depression (S.D. = .33).

W o m en

Figure 2. Moods categories of men versus women.

To determine if male and female working-students significantly differ in their moods a oneway Anova was conducted for each of the variables of moods and gender; the F and p are shown in Table 1. The purpose of this procedure was to assess whether the means of male and female's self-reported moods were statistically different from each other. The analysis revealed that the differences were statistically significant for anger and depression.

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Table 1. Means, standard deviations, F and p scores of moods and gender Men (n=133) Women (n=96) Variables Means S.D. Means S.D. F (df=1) Angry

.20

.40

.28

.45

2.33*

Confused

.39

.49

.45

.50

.556

Depressed

.23

.39

.28

.33

2.29*

Fatigue

.07

.25

.08

.28

.20

Tense

.19

.39

.21

.41

.145

Vigor

.83

.38

.86

.34

.59

* p<.05

The next step, hypothesis 2, was to explore the effects of moods on coping strategies adopted by the respondents by identifying the role of gender in such relationships. For this purpose a multivariate analysis (MANOVA) was conducted using mood categories as dependent variables and coping strategies (task-oriented; emotion-oriented; avoidance; social support – applying to family, friends and significant others) and gender as independent variables (Table 2). The overall F test in the MANOVA tests the null hypothesis that there is no difference in the means of the dependent variables, i.e., coping strategies for the different groups formed by categories of the independent variables, mood states and gender. The overall F of the analysis was significant for the following moods categories: confusion (Wilks λ = 0.943), depression (Wilks λ = 0.812), fatigue (Wilks λ = 0.771) and vigor (Wilks λ = 0.923); as well as for gender (Wilks λ = 0.876), with the smallest lambda in fatigue, meaning the greater differences between coping strategies appear while experiencing fatigue. The use of task-oriented coping is likely to occur in vigor, while employing emotionoriented coping is more likely to occur in depressed and vigorous moods. Avoidance is more probable while confused, depressed and fatigued. An examination of social support strategies (use of family, friends and significant others) showed disappointing results, as only use of family support appeared as a significant variable in this analysis, and it is more likely when in a vigorous mood. However, except for task-oriented coping strategy all coping strategies emerged as significant in relation to gender; indicating that the significant coping strategies are more likely to be employed by women than by men. Table 2. Means, Standard Deviations and F scores of coping by moods categories Variables Mean S.D. F (1,228) Confusion 2.165* Task-oriented coping Emotion-oriented coping Avoidance Family-used as social support Friends-used as social support Significant others-used as social support

3.963 2.288 2.116 5.342 5.020 5.172

.472 .640 .660 1.436 1.936 1.474

.609 .996 11.508** .555 2.494 3.137*

Relationships between Mood, Coping and Stress Systems… Depression

205 8.245**

Task-oriented coping Emotion-oriented coping Avoidance Family-used as social support Friends-used as social support Significant others-used as social support Fatigue

3.981 2.934 2.614 5.604 5.507 5.243

.470 .753 .715 1.214 3.584 1.582

.415 40.789** 12.743** .984 2.751 .034 10.570**

Task-oriented coping Emotion-oriented coping Avoidance Family-used as social support Friends-used as social support Significant others-used as social support Vigor

3.986 2.494 3.115 4.922 5.360 5.422

.420 .476 .611 1.400 1.187 1.428

.262 .096 46.384** 1.880 .442 .335 2.980*

Task-oriented coping Emotion-oriented coping Avoidance Family-used as social support Friends-used as social support Significant others-used as social support Gender

3.937 2.328 2.157 5.247 4.980 5.154

.433 .640 .659 1.470 2.031 1.468

3.187* 3.203* 3.138 5.807* .787 .967 5.046**

Task-oriented coping Emotion-oriented coping Avoidance Family-used as social support Friends-used as social support Significant others-used as social support

.286 7.021* 7.103* 11.074** 25.597** 7.35*

Note: * p < 0.05; ** < 0.01

To predict whether gender-related moods, work and academic stressors and personal attributes prompt male and female TP-Ss to adopt different coping strategies, as hypothesized in our third hypothesis, six multiple regression analyses were used for each of the social support strategies (Table 3). Table 3. Regression analyses for men of coping strategies by stressors, moods and personal attributes Variables B β T (p) Task-orientation Stressors Number of conflicting assignments -.02 -.04 -.36 Limited time for leisure .07 .13 1.03 Limited time dedicate to academic studies .09 .06 1.74 Long and erratic hours spent at work -.01 .05 -.15

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Dafna Kariv and Tali Heiman Table 3. (Continued) B

β

T (p)

.07 .07 .21 -.09 .17 -.01

.06 .07 .16 -.05 .14 -.01

.51 .76 1.95* -.59 1.34 -.12

.01 .04

.22 .04

2.3* .42

Emotion-orientation B Stressors Number of conflicting assignments -.09 Limited time for leisure -.25 Limited time dedicate to academic studies .13 Long and erratic hours spent at work .02 Moods Anger -.12 Confusion .65 Depression .24 Fatigue .16 Tense .19 Vigor -.47 Personal attributes Age -.03 Being married .04 R = .48; R 2 = .37; Adj R 2 = .34; F (13, 121) = 26.82; p < .00**.

β

T (p)

-.06 -.16 .08 .01

-.45 -1.11 .63 .08

-.03 .21 .06 .03 .05 -.12

-.23 2.2* .61 .30 .44 -1.23

-.19 .01

-1.2* .11

Avoidance B Stressors Number of conflicting assignments .01 Limited time for leisure -.13 Limited time dedicate to academic studies .07 Long and erratic hours spent at work .03 Moods Anger -.31 Confusion .31 Depression .47 Fatigue .86 Tense -.13 Vigor .08 Personal attributes Age -.01 Being married -.02 R = .68; R 2 = .46; Adj R 2 = .32; F (13, 121) = 7.10; p < .00**

β

T (p)

.01 -.20 .11 .05

.12 -1.8* 1.11 .57

-.23 .25 .29 .37 -.09 .05

-2.13* 3.25** 3.73** 5.03** -.94 .64

-.04 -.02

-.53 -.18

Variables Moods Anger Confusion Depression Fatigue Tense Vigor Personal attributes Age Being married

R = .56; R 2 = .31; Adj R 2 = .223; F (13, 121) = 3.65; p < .00**

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Equations representing coping strategies were significant, while those representing use of social support showed disappointing results, except for applying to friends for female TP-Ss. The included independent variables explained 22.3% of the total variance of task-oriented coping among males, and 13.2% among females. The strongest predictors of this coping strategy among men were depression and age; being in a depressed mood significantly and positively affected the use of this strategy. Age also significantly and positively influenced males to adopt a task-oriented strategy. Dual-demanding stressors encountered affected female TP-Ss’ use of task-oriented coping strategies; specifically limited time dedicated to academic studies within and/or outside of college hours significantly and positively affected women’s use of task-oriented strategies, while limited time for leisure due to overloads at work and/or at college significantly and negatively affected women’s use of these strategies. Depression among women, unlike men, significantly and negatively influenced their use of task-oriented coping. Adjusted R2 illustrates that 33.7% of the total variance of emotion-oriented coping is explained for male TP-Ss and 32.1% for female TP-Ss. The strongest predictors for men are confusion, which significantly and positively affects the use of this strategy; and age, which significantly and negatively affects the adoption of emotion-oriented coping among men. For women, depression significantly and positively affects the use of emotion-oriented strategies while being married significantly and negatively affects the use of this coping strategy. Approximately 32% of the total variance of avoidance is explained by the included independent variables for men and 31% for women. For men, most of the mood categories, except for tension and vigor emerged as significant; confusion, depression and fatigue significantly and positively influenced adopting avoidance as a coping strategy while anger emerged as significantly and negatively affecting avoidance as coping strategy. The stressor limited time for leisure due to overloads at work and/or at the college, significantly and negatively predicted avoidance as a coping strategy among men. Among women, as shown in Table 4, results indicate that moods of anger and fatigue both significantly and positively influence the use of avoidance as a coping strategy. Social support equations were insignificant except in the case of applying to friends, in which only 2.5% of the total variance is explained by the included independent variables, and only among women. Depression significantly and positively affected women to adopt this support strategy while being married significantly and negatively affected them in applying to friends for social support. Table 4. Regression analyses for women of coping strategies by stressors, moods and personal attributes Variables Task-orientation Stressors Number of conflicting assignments Limited time for leisure Limited time dedicate to academic studies Long and erratic hours spent at work

B

.07 -.20 .14 .06

β

.14 -.39 .26 .12

T (p)

.97 -2.38* 1.99* .82

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Dafna Kariv and Tali Heiman Table 4. Continued

Variables B Moods Anger .18 Confusion -.094 Depression -.36 Fatigue .29 Tense -.01 Vigor -.17 Personal attributes Age .03 Being married -.01 Women: R = .52; R 2 = .27; Adj R 2 = .13; F (13,84) = 1.97; p > .05* Emotion-orientation B Stressors Number of conflicting assignments .03 Limited time for leisure .06 Limited time dedicate to academic studies .31 Long and erratic hours spent at work .07 Moods Anger .44 Confusion .31 Depression 2.03 Fatigue 1.01 Tense -.33 Vigor -.58 Personal attributes Age -.021 Being married -1.157 Women: R = .43; R2 = .38; Adj R 2 = .32; F (13,84) = 11.45; p > .00**. Avoidance B Stressors Number of conflicting assignments -.09 Limited time for leisure -.01 Limited time dedicate to academic studies .10 long and erratic hours spent at work -.05 Moods Anger .380 Confusion .140 Depression .056 Fatigue 1.26 Tense -.06 Vigor .23 Personal attributes Age -.01 Being married -.19 Women: R = .65; R 2 = .42; Adj R 2 = .31; F (13,84) = 3.85; p > .00**

β

T (p)

.17 .096 -.24 .15 -.01 -.12

1.23 -.82 -2.09* 1.24 -.05 -1.06

.04 -.06

.54 -.08

β

T (p)

.01 .02 .12 .02

.07 .12 .83 .16

.08 .06 .26 .10 -.06 -.08

.55 .51 2.16* .75 -.40 -.68

-.072 -.217

-.59 -1.80*

β

T (p)

-.13 -.01 .14 -.07

-.98 -.07 1.18 -.06

.255 .103 .03 .48 -.04 .13

2.13* .99 .27 4.54** -.34 1.16

-.14 -.13

-1.4 -1.26

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209

Table 4. Continued Social support – applying to Friends B Stressors Number of conflicting assignments .03 Limited time for leisure .06 Limited time dedicate to academic studies .32 Long and erratic hours spent at work .07 Moods Anger .44 Confusion .31 Depression 2.03 Fatigue 1.01 Tense -.33 Vigor -.58 Personal attributes Age -.02 Being married -1.16 Women: R = .37; R 2 = .14; Adj R 2 = .03; F (13,84) = 1.92; p > .05.

β

T (p)

.01 .02 .12 .02

.07 .12 .83 .16

.08 .06 .27 .097 -.06 .-08

.54 .51 2.16* .75 -.40 -.68

-.07 -.22

-.59 -2.0*

DISCUSSION The purpose of this study was to determine what prompts men and women TP-Ss to cope differently with their dual-demanding environment, i.e., work and academic studies, or, specifically, whether the moods shaped through the stressors they encounter differ and, consequently, their coping strategies. Adopting a relevant coping response, that is, employing coping strategies that deal with and manage the dual-demanding environmental stressors will produce different coping behaviors if the stressors themselves are differently experienced and 'translated' into different mood states by each gender. More importantly, full-time students who are employed in stressful and demanding occupations, such as teachers and school principals, face extended levels of conflicting demands from both academic and work environments as compared to non-working students; non-studying employees or workingstudents in less stressful occupations. Descriptive statistics show that women report higher mood states in each mood category as compared to men, supporting previous findings on gender differences in moods, both negative and positive (Hankin & Abramson, 1999; Diener, & et al., 1997; Manstead, 1992). Vigor emerges in our results as the highest-ranked mood state among both men and women, suggesting that working adults who 'go back to school', though they encounter academicrelated stressors, experience positive emotions (Kariv & Heiman, 2005). Fatigue appears to be the loweest-ranked mood state among both men and women in our study, supporting the supposition above as fatigue is negatively related to energy, joy or vigor. The first step in this study was to explore whether moods are differentiated by gender among TP-Ss. The analyses revealed gender differences in angry and depressed moods, where females reported experiencing higher levels. These results support previous findings on female students’ depressed moods (Shaikh, et al., 2004; Surtees, et al., 2002), while contradicting others (Grant et al., 2002). Though inconsistent findings have emerged to date

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in studies on these topics, these studies also indicate that anger is experienced more strongly by female TP-Ss. The present results showed that in dual-demanding and stressful situations, women TP-Ss experience more anger than men are of great importance. These results may imply women's self-disclosure more than men's. Additionally, while facing stressors derived from dual-demanding situations, and in contrast with our empirical knowledge on genderrelated anger moods, female TP-Ss do develop anger. If so, this finding is very relevant to both educational research and practice regarding teachers and executives who are involved in academic studies, in terms of providing the relevant supportive as well as guidance aimed at reducing women's anger in school. The multivariate analysis showed significant differences in coping strategy appearing in each mood state, showing that mood categories have an impact on specific coping strategies. More importantly in the analysis, gender appeared to be significant in differentiating among coping strategies, with the exception of task-oriented strategies and applying to significant others, in which no significant differences appear between men and women TP-Ss. Previous studies showed inconsistencies regarding gender differences in the use of taskoriented strategies (Billings & Moos, 1981; Hamilton & Fagot, 1988; Stone & Neale, 1984), which may explain the insignificance of gender effect on task-oriented coping choices revealed in our findings. Other findings that were partly support applied to a significant other social support which did not emerge as significant among TP-Ss. Insofar, gender-related coping strategies also showed that moods affect coping strategies regardless of gender. The next assumption that moods will affect coping strategies, when incorporating stressors that TP-Ss encounter and their personal attributes to the equations, was confirmed, both among men and women. The analyses revealed specific significant mood states that influenced each gender's coping strategies. Task-oriented coping, which appeared inconsistent in relation to gender in previous studies, was found significantly and positively related to depressed moods among male TP-Ss, but significantly and negatively related to depressed moods among female TP-Ss. Emotion-oriented coping, a strategy found in previous research more likely among women than among men (Billings & Moos, 1981; Stein & Nyamathi, 1999) was significantly and positively related to confused moods among male TP-Ss, and significantly and positively related to depressed moods among female TP-Ss. Avoidance, a typically female-oriented coping strategy (Winstead, et al., 1984) appeared significant in men in specific mood states, i.e., confusion, depression and fatigue, while among women it appeared significant in other mood states. These results reinforce our conception that coping with a dual-demanding environment, especially by individuals who are employed in stressful occupations, reflects not only a gender-based tendency but also the mood states derived from the stressors by each gender group.

Implications and Limitations First, the findings suggest that male and female TP-Ss manifest similar patterns in coping with their dual-demanding environment by adopting a range of coping strategies rather than employing one main gender-related coping strategy for managing most of the stressors encountered, and that the strategies used are determined largely by the moods developed by the stressors. The differences in coping behaviors are thus not a consequence of the different

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211

tendencies of male and female TP-Ss towards one or another coping strategy but, rather, are the result of proclivities emanating from the different moods developed by the stressors. Secondly, positive mood states, a neglected topic in the higher education and gender research were found here to be a concept associated to task- and emotion-oriented strategies and the use of family as social support. Future efforts should be addressed toward increasing our understanding of gender differences in positive moods. Third, deciphering TP-Ss’ mood reactions to dual-demanding stressors constitutes a significant contribution to both academic research and to stress and coping intervention programs, at work and in academic institutions. Finally, from a gender-related perspective, the findings suggested that male and female TP-Ss cope similarly with stressors, with both manifesting adaptive patterns, may moderate previous inferences as to gender-related coping behaviors. Concluding that female TP-Ss are more likely to implement emotion-oriented coping strategies in encountering academic- and workrelated stressors means categorizing them as less effective, especially in dealing with negative stressful situations, and as managing their emotional reactions rather than coping with the situation. From this perspective, presenting male TP-Ss as favoring task-oriented coping strategies may be seen as neglecting or suppressing their stressor-derived emotional reactions. The results of this study suggested that both men and women’s coping behaviors are seen to be an outcome of the context in which they emerge rather than of gender. The findings of this study have significant potential benefit for higher education and academic institutions in developing institutional stress reduction and anger management programs and in-house supportive and research centers. In understanding some basic differences between the genders in their "translation" of stressors into moods and coping, this input may contribute to the validation and to the relevance of intervention programs in academic institutions for improving male and female students' ability to cope with academic load and stress, especially where working-students are concerned; as well as assisting teachers and educational executives in managing their dual demanding stressors. Reducing students' stress through generic institutional interventions may be effective/ineffective for students, men or women, who developed specific mood states as a result of the stressors they face. For example, programs designed to develop a positive attitude among stressed students or to establish support groups may suit male students who experience confused moods or female students who experience depressed moods. This certainly implies that in the attempt of higher education institutions to develop stress reduction programs designated for working-students, a primary diagnosis should be executed in order to map the mood states as well as other emotional reactions and to assess the role of gender in the relationship between moods and the institutional programs.

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Russel, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110, 145-172. Scarbrough, A., & Hicks, C. (1998). Student gender and the probability of referral for counseling in a college of further education. British Journal of Guidance & Counseling, 26(2), 225-237. Shaikh, B. T., Kahloon, A., Kazmi, M., & Khalid, H. (2004). Students, Stress and Coping Strategies: A Case of Pakistani Medical School. Education for Health: Change in Learning & Practice, 17(3), 346 – 353. Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive Psychology: An Introduction. American Psychologist 55(1), 5-14. Shirom, A. (2003). Feeling vigorous at work? The construct of vigor and the study of positive affect in organizations. In D. Ganster & P. L. Perrewe (Eds.). Research in organizational stress and well-being. (Vol. 3, pp. 135-165). Greenwich, CN: JAI Press. Snell, W. E. (2001). Women's and men's willingness to self-disclose to therapists and friends: The moderating influence of instrumental, expressive, masculine, and feminine topics. In W. E. Snell, Jr. (Ed.), New Directions in the Psychology of Gender Roles: Research and Theory. Cape Girardeau, MO: Snell Publications. Stein, J. A., & Nyamathi, A. (1999). Gender differences in relationships among stress, coping, and health risk behaviors in impoverished minority populations. Personality and Individual Differences, 26, 141-157. Stone, A. A., & Neale, J. M. (1984). New measure of daily coping: Development and preliminary results. Journal of Personality and Social Psychology, 46, 892-906. Sumi, K. (1997). Optimism, social support, stress, and physical and psychological well-being in Japanese women. Psychological Reports, 81(1), 299-306 Surtees, P. G., Wainwright, N. W. J., & Pharoah, P. D. P. (2002). Psychosocial factors and sex differences in high academic attainment at Cambridge University. Oxford Review of Education, 28(1), 21-38. Thomas, S. (2003). Anger across the gender divide Researchers strive to understand how men and women experience and express anger. Monitor on Psychology, 34(3), 52. Terry, P. C., Lane, A. M., Lane, H. J., & Keohane, L. (1999). Development and validation of a mood measure for adolescents. Journal of Sports Sciences, 17, 861 -872. Terry, P. C., Lane, A. M., & Fogarty, G. (2003). Construct validity of the profile of mood states-A for use with adults. Psychology of Sport and Exercise, 4, 125-139. Tobar, D. A., & Morgan, W. P. (2002). Gender, trait anxiety and mood state responses to overtraining in college swimmers. Medicine & Science in Sports & Exercise, 34(5), 161. Whatley, S.L., Foreman, A.C., & Richards, S. (1998). The relationship of coping style to dysphoria, anxiety, and anger. Psychological Reports, 83, 783-791. Wilson, K. S. & Multon, K. D. (2001, August). The impact of stress on health outcomes among law students. Poster session presented at the annual convention of the American Psychological Association, San Francisco, CA. Wilson, G. S., Pritchard, M. E., & Revalee, B. (2005). Individual differences in adolescent health symptoms: the effects of gender and coping. Journal of Adolescence, 28(3), 369-381. Winstead, B. A., Derlega, V. J., & Wong, P. T. P. (1984). Effects of sex-role orientation on behavioral self-disclosure. Journal of Research in Personality, 18, 541-553.

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Wolverton, M., Wolverton, M. L,. & Gmelch, W. H. (1998, April). The interconnections between job satisfaction and work-related stress in academic deans. Paper presentation at AERA Conference: San Diego, CA. Zimet, G. D, Dahlem, M. W, Zimet, S. G., & Parley, G. K. (1988). The Multidimensional Scale for Perceived Social Support. Journal of Personality Assessment, 52, 30-41. Zohar, D., Tzischinsky, O., Epstein, R., & Lavie, P. (2005). The effects of sleep loss on medical residents' emotional reactions to work events: a cognitive-energy model. Sleep, 28(1), 47-54.

In: Mental Health of College Students Ed: Katherine N. Morrow

ISBN: 978-60456-394-8 ©2009 Nova Science Publishers, Inc.

Chapter 11

EXAMINING ANGER EXPRESSION REACTIONS AND ANGER CONTROL BEHAVIORS OF TURKISH STUDENTS Ibrahim Kisac* Gazi University, Ankara / Turkey

ABSTRACT The aim of this research is to examine anger expression reactions and anger control behaviors with respect to gender and education levels of the students when they are angry. Subjects were recruited from Gazi University, Abidinpasa High School and Aksaray Anatolian Hotel and Tourism Vocational High School and consist of 466 students. Inventory was prepared by the researcher to collect data about demographic qualities and anger behaviors of the students. Data were analyzed by frequency, percent and chi-square techniques. Results indicated that when the students get angry, they “sulk or make sour face”(77%), “try to think that everybody does not have to behave as they want”(76%) and “think that they can handle with the situation which made them angry” (75%). According to gender variable, male students significantly “say nasty things to the others”, but “try to be more intelligent and indulgent”, “to be more coolheaded”, “more think that not being able to control anger is a weakness” and “more think that they will not let others make them angry” than female students. On the other hand, it was found that female students more “sulk or make sour face”, “feel helpless, feel cry” and “say sarcastic words to the person who made them angry” than male students when they are angry. According to educational status, it was determined that while female high school students significantly “yell or scream more”, “argue with the person who made them angry” and “say nasty things to the others” more than female university students, female university students *

Gazi University, Vocational Education Faculty, Department of Educational Sciences, 06500 Besevler – Ankara / Turkey, [email protected]

218

Ibrahim Kisac “express their anger in a more suitable way”, “try to see pozitif sides of the case”, “try to convince themselves not to be angered” more and “think that everybody does not have to behave as they want” when they feel angry. It was seen that while male high school students “make fun of the person who made them angry” more, male university students “do nothing at all, quite; suppress their their anger” more, “sulk or make sour face” and “withdraw from the people”.

Keywords: anger expression, anger control, gender, educational status

INTRODUCTION Anger is one of the most experienced emotions in daily life. When stresses and troubles of daily life are regarded, anger is an unavoidably experienced emotion. However, when it gets out of control, it can lead to many problems in personal relationship, at work and in other aspects of life. Anger is commonly destructive of social relationships (Kennedy, 1992). Moreover, anger is associated with a variety of psychological and social problems in adolescents and adults. High general anger individuals experience considerable distress and problems, with some of the anger significantly impacting their physical, social, educational and vocational well-being (Deffenbacher, Lynch, Oetting and Kemper, 1996; Vecchio and O’Leary, 2004; Phillips, Henry, Hosie and Milne, 2005; Dahlen and Martin, 2005; Dahlen and Martin, 2006). The individuals who have greater intensities and frequencies of anger reactivity usually cope less well with anger and express themselves in less positive and constructive ways (Deffenbacher et al., 1996). Consequently, anger control frequently appears as a primary or secondary problem for some people (Deffenbacher, 1988). Anger control is directly related to better psychological and physical health. At the same time, anger control is associated with lower psychological distress and less physical illness. Diong et al.’s (2005) study showed that individuals who can easily control their angry feelings create a more favorable interpersonal environment compared to those individuals who have difficulty in anger control. Therefore, what is anger control or how can anger be controlled? There are some approaches about controlling anger. One of them was the catharsis of anger. This opinion was based on the view that suppressing anger may cause several problems. Squelching or suppressing anger does not get an individual anywhere and unexpressed rage will do far more harm (Ellis, 1992). Suppressing anger costs too much (Tavris, 1982), or has many unpleasant side-effects for the people (Walters, 1983). So, anger should be released. However, Green, Stonner and Shope (1975) found that a catharsis lead to an increase in anger rather than a decrease (Cited in Lewis and Bucher, 1992). Ebbesen et al. (1975) showed that the catharsis of anger is ineffective at reducing it, and may very well increase it (Cited in Lewis and Bucher, 1992). Anger feeds anger. Rage which is not restrained by intelligence will turn into violence (Goleman, 1998). As a result, “the expression of anger leads to increased anger; the anger response is reinforced rather than drained” (Lewis and Bucher, 1992). Tice points out that vomiting anger is one of the worst ways to calm down. Rage bursts strongly arouse the brain, and make the individual angrier (Cited in Goleman, 1998).

Examining Anger Expression Reactions and Anger Control Behaviors…

219

The second approach is suppressing anger. This happens by holding in anger. The aim of this is to inhibit anger. The danger of this approach is that if anger is not allowed outward expression, it can turn inward. Anger turned inward may cause stomach ulcers, high blood pressure, hypertension, depression, (Ellis, 1992; Sharkin, 1996) or pathological expression of anger such as passive-aggressive behavior, sarcastic behavior or making fun of people. The third approach about anger control is to calm down first, then to express it in a constructive way so that resolve the conflict by confronting the other person. This opinion is consistent with Asian and East cultures. One of the anger management techniques is “being silent” in these cultures. It is advised that “if one of you gets angry, let him be silent” (Beshir and Beshir). People are born with the potential to feel and to express anger. However, the things that make people angry, how they feel angry and what people do when they are angry are not the same for all people (Rubin, 1969). “Anger and its expression are result of biology and culture, mind and body” (Tavris, 1982). Individual’s thoughts, beliefs remain extremely important factors in determining both individual’s feelings and responses to any given situation (Berkowitz, 1990; Ellis, 1992). There is not enough study about socio-cultural context of anger. Anger is a highly interpersonal emotion. It can not be fully understood apart from the social context in which it occurs (Averill, 1983, Kassinova and Shuckhudolsky, 1995). It is fact that anger is a universal experience, but the experience and expression of anger may be influenced by one’s cultural heritage and world view. Culture may not only influence what are considered appropriate and inappropriate forms of anger expression, but also what makes people angry, what is perceived as anger and how people feel about their own anger (Sharkin, 1996). In another term, social constraints on the expression of anger are very effective (Kennedy, 1992). Few studies have investigated socio-cultural differences (such as race, ethnicity, and religion) in expressing and controlling anger (Ohbuchi, et al., 2004; Marby and Kiecolt, 2005; Bishop, Pek and Ngau, 2005). This research tries to find out the anger expression and control behaviors of the students in Turkish culture. The aim of this research is to examine anger expression reactions and anger control behaviors of the students with respect to gender and education levels when they are angry. In this study, it is attempted to define how the students react or express their anger, and what they do to control their anger.

METHOD Subjects were recruited from Gazi University (n=268), Abidinpasa High School (n=130) and Aksaray Anatolian Hotel and Tourism Vocational High School (n=68) and consist of 466 students. Sample contains 334 female and 132 male students. Anger Description Form was prepared by the researcher to collect data about demographic qualities and anger expression reactions, and anger control behaviors of the students. To develop that form, theories and studies in related literature were investigated. Anger Description form consisted of five sections. The first section is about demographic qualities of the participants such as gender, school type. The second section aims to collect data about which situations get individuals angry. The third section is about what individuals do when they are angry. The fourth section reveals experienced physical clues or reactions of

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220

the individuals when they are angry. Finally, the last section is examining to whom the people are expressing their anger. The form consists of “yes and no” statements. SPSS 13.0 was used to analyze findings. Data were analyzed by frequency, percent and chi-square techniques. The least significant level was considered p<0.05.

RESULTS In this section, the findings about negative anger reactions and anger control behaviors of all students will be given. Then, findings will be examined with respect to gender and educational levels of the students. Also, it will be investigated whether there are any significant differences among anger reactions and anger control behaviors of the students according to gender and educational status. Table 1. Negative anger expression reactions and anger control behaviors Anger reactions and control behaviors 1. I do nothing at all; suppress my anger 2. I yell or scream 3. I bang on doors, furniture 4. I say sarcastic words to the person who made me angry 5. I make fun of the person who made me angry 6. I argue with the person who made me angry 7. I say nasty things to the others 8. I internally become very angry, but I do not reveal it 9. I sulk or make sour face 10. I withdraw from the people 11. I feel helpless, feel cry

n 150 248 136 317 113 347 117 149 358 237 198

Yes % 32.8 53.3 29.3 68.0 24.2 74.5 25.2 32.2 76.8 51.1 43.7

n 307 217 328 149 353 119 348 314 108 227 255

No % 67.2 46.7 70.7 32.0 75.8 25.5 74.8 67.8 23.2 48.9 56.3

n 457 465 464 466 466 466 465 463 466 464 453

Total % 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

As it is seen in Table 1, the most exhibited negative anger reactions of the students are, in order, “sulking or making sour face”(76.8%), “argue with the person who made them angry” (74.5%) and “saying sarcastic words to the person who made them angry (68%). On the other hand, the least exhibited anger behaviors are “making fun of the person who made them angry” (24.2%), “saying nasty things to the others” (25.2%), and “banging on doors, furniture” (29.3%). Table 2 indicates that the most exhibited positive behaviors in participant students when they want to control their anger are “trying to think that everybody does not have to behave as they want”(75.5%), “thinking that they can handle with the situation which made them angry” (74.7%), “expressing their anger in a suitable way” (74.0%), and “trying to calm down and take a few deep breaths” (69.5%). The least shown anger control behaviors of the students are “thinking that not being able to control anger is a weakness” (47.2%) and “standing up and walking around if they are sitting, or sitting down if they are standing” (50.4%). In Table 3, negative anger reactions of the students with respect to gender were shown. It is seen that the most shown negative anger reactions of the female students are “sulking or making sour face” (83.5%) and “arguing with the person who made them angry” (74.0%).

Examining Anger Expression Reactions and Anger Control Behaviors…

221

Male students, too, mostly “argue with the person who made them angry” (75.8%), and “sulking or making sour face” (59.8%). Table 2. Positive anger expression reactions and anger control behaviors Anger reactions and control behaviors

Yes

1. I try to be more intelligent and indulgent 2. I express my anger in a suitable way 3. If I am sitting, I stand up and walk around, or if I am standing, I sit down 4. I try to calm down and take a few deep breaths 5. I try to see positive sides of case 6. I try to convince myself not to be angered 7. I try to keep being coolheaded or calm down inside 8. I think that not being able to control anger is a weakness 9. I try to think that this is a weakness of the other guy 10. I try to think that everybody does not have to behave as I want 11. I think that he/she is trying to make me angry, but I will not let him/her 12. I think that I can handle with the situation which made me angry 13. I try to think that what others said is not important for me

No

Total

n

%

n

%

n

%

250 341 234

54.0 74.0 50.4

213 120 230

46.0 26.0 49.6

463 461 464

100.0 100.0 100.0

322 241 292 235 219 247 345 270

69.5 52.1 63.6 51.2 47.2 55.1 75.5 58.7

141 222 167 224 245 201 112 190

30.5 47.9 36.4 4889 52.8 44.9 24.5 41.3

463 463 459 459 464 448 457 460

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

340

74.7

115

25.3

455

100.0

238

51.4

225

48.6

463

100.0

Table 3. Negative anger expression reactions and anger control behaviors by gender Anger reactions and control behaviors

Female students Yes

1. I do nothing at all, suppress my anger 2. I yell or scream 3. I bang on doors, furniture 4. I say sarcastic words to the person who made me angry 5. I make fun of the person who made me angry 6. I argue with the person who made me angry 7. I say nasty things to the others 8. I internally become very angry, but I do not reveal it 9. I sulk or make sour face 10. I withdraw from the people 11. I feel helpless, feel cry

*: p<.05, ***: p<.001.

Male students

No

Yes

Pearson

No

P

Chi-square

n 104

% 31.9

n 222

% 68.1

n 46

% 35.1

n 85

% 64.9

.43

.511

183 95 244

55.0 28.6 73.1

150 237 90

45.0 71.4 26.9

65 41 73

49.2 31.1 55.3

67 91 59

50.8 68.9 44.7

1.23 .27 13.70***

.303 .651 .000

74

22.2

260

77.8

39

29.5

93

70.5

2.81

.119

247

74.0

87

26.0

100

75.8

32

24.2

.16

.721

74

22.2

259

77.8

43

32.6

89

67.4

5.38*

.024

99

29.8

233

70.2

50

38.2

81

61.8

3.00

.098

279 177 172

83.5 53.3 52.9

55 155 153

16.5 46.7 47.1

79 60 26

59.8 45.5 20.3

53 72 102

40.2 54.5 79.7

29.80*** 2.33 39.69***

.000 .150 .000

Ibrahim Kisac

222

The least exhibited negative anger reactions of the girls are “saying nasty things to the others” (22.2%), “making fun of the person who made them angry” (22.2%) and “banging on doors, furniture” (28.6%). The least shown anger reactions of the male students are also “feeling helpless, feeling cry” (20.3%), “making fun of the person who made them angry” (29.5%), and “banging on doors, furniture” (31.1%). Chi-square analyze was performed to determine whether a significant difference between female and male students’ anger reactions. Obtained chi-square values indicated that male students significantly “say nasty things to the others” (p<.05) more than female students. On the other hand, female students more “say sarcastic words to the person who made them angry” (p<.001), “sulk or make sour face” (p<.001), and “feel helpless, feel cry” (p<.001) than male students do. Table 4. Positive anger expression reactions and anger control behaviors by gender Anger reactions and control behaviors

Female students Yes

1. I try to be more intelligent and indulgent 2. I express my anger in a suitable way 3. If I am sitting, I stand up and walk around, or if I am standing, I sit down 4. I try to calm down and take a few deep breaths 5. I try to see positive sides of case 6. I try to convince myself not to be angered 7. I try to keep being coolheaded or calm down inside 8. I think that not being able to control anger is a weakness 9. I try to think that this is a weakness of the other guy 10. I try to think that everybody does not have to behave as I want 11. I think that he/she is trying to make me angry, but I will not let him/her 12. I think that I can handle with the situation which made me angry 13. I try to think that what others said is not important for me

**: p<.01, ***: p<.001.

Male students

No

Yes

No

Pear son Chisquare

P

n 159

% 47.9

n 173

% 52.1

n 91

% 69.5

n 40

% 30.5

17.60***

.000

249

75.7

80

24.3

92

69.7

40

30.3

1.75

.198

164

49.4

168

50.6

70

53.0

62

47.0

.49

.537

231

69.6

101

30.4

91

69.5

40

30.5

.01

.981

167

50.3

165

49.7

74

56.5

57

43.5

1.44

.256

203

61.9

125

38.1

89

67.9

42

32.1

1.48

.133

147

44.8

181

55.2

88

67.2

43

32.8

18.73***

.000

144

43.2

189

56.8

75

57.3

56

42.7

7.40**

.007

183

57.0

138

43.0

64

50.4

63

49.6

1.61

.208

254

77.2

75

22.8

91

71.1

37

28.9

1.85

.184

178

54.1

151

45.9

92

70.2

39

29.8

10.04**

.002

248

76.3

77

23.7

92

70.8

38

29.2

1.50

.233

173

52.1

159

47.9

65

49.6

66

50.4

.23

.680

Examining Anger Expression Reactions and Anger Control Behaviors…

223

When looking at the positive anger control of the participants the first three behaviors of the female students, are “trying to think that everybody does not have to behave as they want” (77.2%), “thinking that they can handle with the situation which made them angry” (76.3%) and “expressing their anger in a suitable way” (75.7%). Male students reported the same behaviors when they want to control their anger. These behaviors are “trying to think that everybody does not have to behave as they want” (71.1%), “thinking that they can handle with the situation which made them angry” (70.8%) and “thinking that he/she is trying to make them angry, but they will not let him/her” (70.2%). The least exhibited anger control behaviors are “thinking that not being able to control anger is a weakness” (43.2%) and “trying to keep being coolheaded or calm down inside” (44.8%) for the female students, and “trying to think that what others said is not important for them” (49.6%) and “trying to think that this is a weakness of the other guy” (50.4%) for the male students. Chi-square analysis showed that male students significantly “try to be more intelligent and indulgent” (p<.001), more “try to keep being coolheaded or calm down inside” (p<.001), “think that not being able to control anger is a weakness” (p<.01) and “think that he/she is trying to make them angry, but they will not let him/her” than female students. Table 5. Negative anger expression reactions and anger control behaviors of female students by educational levels Anger reactions and control behaviors

High School Yes

1. I do nothing at all, suppress my anger 2. I yell or scream 3. I bang on doors, furniture 4. I say sarcastic words to the person who made me angry 5. I make fun of the person who made me angry 6. I argue with the person who made me angry 7. I say nasty things to the others 8. I internally become very angry, but I do not reveal it 9. I sulk or make sour face 10. I withdraw from the people 11. I feel helpless, feel cry

University

No

Yes

No

Pear son Chisquare

P

n 24

% 22.4

n 83

% 77.6

n 80

% 36.5

n 139

% 63.5

78 34 85

73.6 32.1 79.4

28 72 22

26.4 67.9 20.6

105 61 159

46.3 27.0 70.0

122 165 68

53.7 21.80*** 73.0 .91 30.0 3.26

.000 .363 .086

28

26.2

79

73.8

46

20.3

181

79.7

1.47

.259

89

83.2

18

16.8

158

69.6

69

30.4

6.95*

.011

36

34.0

70

66.0

38

16.7

189

83.3

29

27.1

78

72.9

70

31.1

155

68.9

87 43 54

81.3 40.2 51.9

20 64 50

18.7 59.8 48.1

192 134 118

84.6 59.6 53.4

35 91 103

15.4 40.4 46.6

6.57*

.011

12.40*** .001 .55

.521

.56 .527 10.92*** .001 .06 .813

*: p<.05, ***: p<.001

Any significant difference on negative anger reactions of the female students with respect to their educational status is displayed in Table 5. The most stated anger reactions of female high school students were found “arguing with the person who made them angry” (83.2%), “sulking or making sour face” (81.3%), and “saying sarcastic words to the person who made them angry” (79.4%). University students also stated same anger reactions, “sulking or

Ibrahim Kisac

224

making sour face” (84.6%), and “saying sarcastic words to the person who made them angry” (70.0%). Female high school students reported that they less “do nothing at all, they quite; suppress their anger” (22.4%), “make fun of the person who made them angry” (26.2%) and “internally become very angry, but they do not reveal it” (27.1%) when they are angry. The least preferred negative anger reactions of the university students are “saying nasty things to the others” (16.7%), “making fun of the person who made them angry” (20.3%) and “banging on doors, furniture” (27.0%). Table 6. Positive anger expression reactions and anger control behaviors of female students by educational levels Anger reactions and control behaviors

High School Yes

1. I try to be more intelligent and indulgent 2. I express my anger in a suitable way 3. If I am sitting, I stand up and walk around, or if I am standing, I sit down 4. I try to calm down and take a few deep breaths 5. I try to see positive sides of case 6. I try to convince myself not to be angered 7. I try to keep being coolheaded or calm down inside 8. I think that not being able to control anger is a weakness 9. I try to think that this is a weakness of the other guy 10. I try to think that everybody does not have to behave as I want 11. I think that he/she is trying to make me angry, but I will not let him/her 12. I think that I can handle with the situation which made me angry 13. I try to think that what others said is not important for me

*: p<.05, **: p<.01, ***: p<.001.

No

University Yes

No

Pear son Chisquare

P

n 45

% 42.1

n 62

% 57.9

n 114

% 50.2

n 111

% 49.3

2.15

.159

70

66.0

36

34.0

179

80.3

44

19.7

7.90**

.006

47

43.9

60

56.1

117

52.0

108

48.0

1.89

.197

71

67.0

35

33.0

160

70.8

66

29.2

.49

.523

44

41.1

63

58.9

123

54.7

102

45.3

5.32*

.026

51

47.7

56

52.3

152

68.8

69

31.2 13.62***

.000

39

37.1

66

62.9

108

48.4

115

51.6

3.67

.058

40

37.4

67

62.6

104

46.0

122

54.0

2.20

.156

49

49.0

51

51.0

134

60.4

87

39.4

3.80

.053

69

64.5

38

35.5

185

83.3

37

16.7

14.57***

.000

63

59.4

43

40.6

115

51.6

108

48.4

1.79

.194

78

73.6

28

26.4

170

77.6

49

22.4

.64

.487

62

57.9

45

42.1

111

49.3

114

50.7

2.15

.159

Examining Anger Expression Reactions and Anger Control Behaviors…

225

Whether there is any significant difference among anger reactions of the female students according to education levels was tested by chi-square analysis. When high school students are angry, they significantly more “yell or scream” (p<.001) “argue with the person who made them angry” (p<.05) and “say nasty things to the others” (p<.001) than university students. On the other hand, university students more “do nothing at all, they quite; suppress their anger” (p<.05) and “withdraw from the people” (p<.001) than high school students. As in Table 6, the three most seen anger control behaviors of the female high school student are “thinking that they can handle with the situation which made them anger” (73.6%), “trying to calm down and taking a few deep breaths” (67.0%) and “expressing anger in a suitable way” (66.0%). Likely, the most stated anger control behaviors of the female university students are “trying to think that everybody does not have to behave as they want” (83.3%), “expressing their anger in a suitable way” (80.3%) and “thinking that they can handle with the situation which made them angry” (77.6%). For the least expressed anger control behaviors of the female students, high school students less “try to keep being coolheaded or calm down inside” (37.1%) and “think that not being able to control anger is a weakness” (37.4%). For university students’ the least anger control behavior is “thinking that not being able to control anger is a weakness” (46.0%) and “trying to keep being coolheaded or calm down inside” (48.4%). However, female university students demonstrate the both behaviors more than female high school students. It was found that there are some significant differences about anger control behaviors between high school and university students. Obtained chi-square values indicated that university students behave more sensitive on “expressing their anger in a suitable way” (p<.01), “trying to see positive sides of case” (p<.05), “trying to convince themselves not to be angered” (p<.001) and “trying to think that everybody does not have to behave as they want” (p<.001) than high school students. In Table 7, when negative anger reactions of the male students are looked at, according to educational levels, like in female students, there are some differences among the male anger reactions too, as there are in female students. While male high school students mostly “argue with the person who made them angry” (73.6%), male university students “argue with the person who made them angry” (80.5%) “sulk or make sour face” (75.6%), and “say sarcastic words to the person who made them angry” (68.3%). The least expressed anger reactions of the male high school students are “feeling helpless, feeling cry” (16.9%), “saying nasty things to the others” (28.6%), “banging on doors, furniture” (28.6%) and “doing nothing at all, being quite; suppressing their anger” (28.6%). Male university students expressed their least exhibited anger reactions as “making fun of the person who made them angry” (17.1%) and “feeling helpless, feeling cry” (28.2%). Any significant differences among the male students’ negative anger reactions with respect to educational status was tested by chi-square. It was found that male university students “do nothing at all, be quite; suppress their anger” (p<.05), “withdraw from the people” (p<.05) and “sulk or make sour face” (p<.01) more than the male high school students do. However, high school students more “make fun of the person who make them angry” (p<.05) than male university students do.

Ibrahim Kisac

226

Table 7. Negative anger expression reactions and anger control behaviors of male students by educational levels Anger reactions and control behaviors

High School

Yes

1. I do nothing at all, suppress my anger 2. I yell or scream 3. I bang on doors, furniture 4. I say sarcastic words to the person who made me angry 5. I make fun of the person who made me angry 6. I argue with the person who made me angry 7. I say nasty things to the others 8. I internally become very angry, but I do not reveal it 9. I sulk or make sour face 10. I withdraw from the people 11. I feel helpless, feel cry

University

No

Yes

No

P

Pea rso n Chisquare

n 26

% 28.6

n 65

% 71.4

n 20

% 50.0

n 20

% 50.0

5.60*

.028

46 26 45

50.5 28.6 49.5

45 65 46

49.5 71.4 50.5

19 15 28

46.3 36.6 68.3

22 26 13

53.7 63.4 31.7

.20 .84 4.06

.709 .418 .058

32

35.2

59

64.8

7

17.1

34

82.9

4.44*

.040

67

73.6

24

26.4

33

80.5

8

19.5

.72

.511

26

28.6

65

71.4

17

41.5

24

58.5

2.13

.163

35

38.5

56

61.5

15

37.5

25

62.5

.01

.917

48 33

52.7 36.3

43 58

47.3 63.7

31 27

75.6 65.9

10 14

24.4 34.1

6.14* 9.98**

.014 .002

15

16.9

74

83.1

11

28.2

28

71.8

2.15

.157

*: p<.05, **: p<.01.

Table 8 shows that the most expressed anger control behaviors of the male high school students are “thinking that he/she is trying to make them angry, but they will not let him/her” (73.6), “trying to keep being coolheaded or calm down inside” (72.2%), “expressing their anger in a suitable way” (70.3%) and “thinking that they can handle with the situation which made them angry” (70.0%). On the other hand, the most expressed anger control behaviors of the university students are “trying to think that everybody does not have to behave as they want” (78.0%), “trying to calm down and taking a few deep breaths” (78.0%), “trying to be more intelligent and indulgent” (73.2%) and “thinking that they can handle with the situation which made them angry” (72.5%). Table 8 indicates that while the least anger control behavior of high school students is “trying to think that what others said is not important for them” (47.8%), the least preferred anger control behaviors of university students is “trying to think that this is a weakness of the other guy” (48.7%). The significant difference among anger control behaviors of the male students with respect to their educational levels was tested. There was not found any significant difference on positive anger reactions and anger control behaviors of the male students.

Examining Anger Expression Reactions and Anger Control Behaviors…

227

Table 8. Positive anger expression reactions and anger control behaviors of male students by educational levels Anger reactions and control behaviors

1. I try to be more intelligent and indulgent 2. I express my anger in a suitable way 3. If I am sitting, I stand up and walk around, or if I am standing, I sit down 4. I try to calm down and take a few deep breaths 5. I try to see positive sides of case 6. I try to convince myself not to be angered 7. I try to keep being coolheaded or calm down inside 8. I think that not being able to control anger is a weakness 9. I try to think that this is a weakness of the other guy 10. I try to think that everybody does not have to behave as I want 11. I think that he/she is trying to make me angry, but I will not let him/her 12. I think that I can handle with the situation which made me angry 13. I try to think that what others said is not important for me

High School

University

No

No

Pearson

P

n 61

Yes % 67.8

n 29

% 32.2

n 30

Yes % 73.2

n 11

% 26.8

.38

.683

64

70.3

27

29.7

28

68.3

13

31.7

.05

.840

49

53.8

42

46.2

21

51.2

20

48.8

.07

.851

59

65.6

31

3454

32

78.0

9

22.0

2.07

.219

48

53.3

42

46.7

26

63.4

15

36.6

1.16

.343

62

68.9

28

31.1

27

65.9

14

34.1

.11

.840

65

72.2

25

27.8

23

56.1

18

43.9

3.32

.075

50

54.9

41

45.1

25

62.5

15

37.5

.64

.449

45

51.1

43

48.9

19

48.7

20

51.3

.06

.849

59

67.8

28

32.2

32

78.0

9

22.0

1.42

.298

67

73.6

24

26.4

25

62.5

15

37.5

1.64

.218

63

70.0

27

30.0

29

72.5

11

27.5

.08

.837

43

47.8

47

52.2

22

53.7

19

46.3

.39

.575

Chi-square

CONCLUSION Results indicated that most of the students passively sulking or making sour face, or try to think that everybody does not have to behave as they want or argue with the person who made them angry. This may be somewhat consistent with the other results in the literature. In terms of anger expression style, high anger participants reported greater tendencies to both suppress anger and negatively express anger (Deffenbacher et al., 1996). High-anger individuals engage in more verbally and physically intimidating expressions of anger, present

228

Ibrahim Kisac

less effective interpersonal communication skills, and have less controlled and more negative anger expression styles (Deffenbacher, Lynch, Oetting and Kemper, 1996). That is not consistent with the other results. Because one of the least exhibited anger expression reactions is “saying nasty things to the others”. Also, another negative reaction is “banging on doors, furniture”. These results point out that the students do not engage in verbally and physically anger expression reactions. They prefer to passively express their anger such as sulking or making sour face. The reason of this reaction could be not leaving the catharsis or expressing anger verbally or physically in Turkish culture. In many Asian cultures, display of angry emotions is not socially approved (Diong et al., 2005). Individuals are supposed to deal with their anger. There is an expression about managing anger. That is a “strong man as the one who controls himself when he is angry, and not the one who wrestles others” (Beshir and Beshir 2003). Instead of negatively expressing anger verbally and physically, the students try to control their anger by thinking that everybody does not have to behave as they want or expressing their anger in a suitable way or taking a few breaths to calm down. When the difference between the sexes is examined, female students mostly sulk or make sour face. The second anger expression reaction, that females stated, was to argue with the person who made them angry. The most expressed anger reaction of the male students is to argue with the person who made them angry, too. This indicates that while female students mostly prefer passive anger reactions, male students mostly express their anger in aggressive ways. This result is similar in Milovchevich, Howells, Drew and Day’s (2001) study. They found that whether males are more likely to engage in a violent response and females a verbal response is not clear. The source of this difference could be that boys are culturally encouraged to behave more assertive and aggressive (Tavris, 1982; Erdentug, 1982; Koknel, 1986; Kisac, 1997; Kisac,2000). At the same time, anger expressions create the impression that the expresser is strong (Tiedens, 2001). This can be a probable reason of the male students’ anger expression reactions. It was found that there is a significant difference between female and male students at expressing anger reactions. While male students say more nasty thing to the others, female students sulk and make sour face, feel helpless, feel cry and say sarcastic words to the person who made them angry more when they are angry. As it is expected, these reactions also show that female students prefer to act passively when they are angry. To control anger, both female and male students try to think that everybody does not have to behave as they want and express their anger in a suitable way. When the difference between female and male students’ anger control behaviors was tested, it was found that male students significantly try to be more intelligent, indulgent and to keep being coolheaded than female students. Moreover, male students more think that not being able to control anger is a weakness and someone is trying to make them angry, but I will not let him/her than female students do. This can be related that men are more coolheaded in some unusual events, and behave more intelligent and indulgent. This result is consistent with some other results. Kisac (1997, 2000) found that male students control their anger more than female students do. Anger expression reactions is another searched variable in the study between the differences of female high school students and female university students. It is seen that the first two reactions of both high school and university students are sulking or making sour face and arguing with the person who made them angry. Meanwhile, when the significant difference is tested, it was found that high school student yell or scream more, argue with the

Examining Anger Expression Reactions and Anger Control Behaviors…

229

person who made them angry and say nasty thing to the others than university students. On the contrary, female university students prefer expressing their anger in a suitable way, trying to see positive side of the case, trying to convince themselves not to be angered and thinking that everybody does not have to behave as they wish. This can be interpreted as university students being more successful to control their behavior than female high school students. Also, male high school students and male university students’ anger expressing reactions were investigated. While the most expressed anger reaction of male high school students is to argue with the person who made them angry, male university students’ common reactions are to sulk or make sour face, to argue with the person and to say sarcastic words to the person who made them angry. Therefore, high school students significantly sulk less or make sour face than university students. Also, high school students withdraw less from people and say less sarcastic words to provoker when they are angry than university students do. This result can be explained that high school students prefer to be open when they are angry. However, male university students usually indirectly express their angry feelings such as saying sarcastic words or sulking or withdrawing. In other terms, male university students usually prefer being quite and suppressing their angry feelings. Therefore, as pointed out by Palfai and Hart (1997), anger-in may lead to social withdrawal. The high school students mostly prefer to think that he/she is trying to make them angry, but they will not let him/her, to keep being coolheaded and to express their anger in a suitable way for controlling their anger. On the other hand, university students’ anger control behaviors are to take a few breaths to calm down, to think that everybody does not have to behave as they want, and to be more intelligent, indulgent. In conclusion, most of the students have constructive ways to express their angry feelings. They usually prefer passively sulking. Especially, female students prefer to passively express their anger because of the cultural effect. This is highly related to “be silent” approaches. Also, many of the students, when they want to control their anger, behave rational by thinking that everybody acts in their own way, and express their anger in a suitable way. They try to more intelligent and indulgent when they feel angry. Particularly, university students prefer seeing positive side of the case and tryin to to think that everybody does not have to behave as they wish.

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Dahlen, E. R. and Martin, R. C. (2006). Refining the anger consequences questionnaire. Personality and Individual Differences, 41, 1021-1031. Deffenbacher, J. L. (1988). Cognitive relaxation and social skills treatments of anger: A year later. Journal of Counseling Psychology, 35 (3), 234-236. Deffenbacher, J .L., Lynch, R. S., Oetting, E. R. and Kemper, C. C. (1996). Anger reduction in early adolescents. Journal of Counseling Psychology, 43 (2), 149-157. Deffenbacher, J. L., Oetting, E. R., Thwaites, G. A., Lynch, R. S., Baker, D. A. Star, R. S., Thacker, S. and Eiswert-Cox, L. (1996). State-trait anger theory and the utility of the trait anger scale. Journal of Counseling Psychology, 43 (2), 131-148. Diong, S. M., Bishop, G. D., Enkelmann, H. C., Tong, E. M. W., Why, Y. P., Ang, J. C. H. and Khader, M. (2005). Anger, stress, coping, social support and health: Modelling the relationships. Psychology and Health, 20 (4), 467-495. Ellis, A. (1992). How to live with and without it. NewYork: Carol Publishing Company. Erdentug, S. A. (1982). Turkiye, Iran ve Pakistan’da geleneksel koy ailesinin ozellikleri [Features of traditional village family in Turkey, Iran and Pakistan]. Antropoloji Dergisi, 10, 63-73. Goleman, D. (1998). Duygusal Zeka [Emotional Intelligence], (Translated by Banu Seckin Yuksel), Istanbul: Varlik Yayinlari. Kassinove, H. and Sukhodolsky, D. G. (1995). Anger disorders: Basic science and practice issues. In H. Kassinove (Ed.), Anger disorders: Definition, diagnosis, and treatment (pp. 1-26). Washington: Taylor and Francis. Kennedy, H. G. (1992). Anger and irritability. British Journal of Psychiatry, 161, 145-153. Kisac, I. (1997). Universite ogrencilerinin surekli ofke ve ofke ifade duzeylerinin bazi degiskenler acisindan incelenmesi [Investigating of state trade anger expression levels of the university students with respect to some variables]. Unpublished Doctoral Dissertation. Ankara: Hacettepe University, Social Sciences Institute. Kisac, I. (2000). Universite ogrencilerinin surekli ofke ve ofke ifade bicimleri ve cinsiyet [Gender and state trate anger expressions of the university students]. Turkish Journal of Social Research, 4, (1), 129-144. Koknel, O. (1986). Kaygidan mutluluga kisilik. Istanbul: Altin Kitaplar Yayinlari. Lewis, W. A. and Butcher, A. M. (1992). Anger, catharsis, the reformulated frustrationaggression hypothesis, and health consequences. Psychotherapy, 29 (3), 385-392. Marby, J. B. and Kiecolt, K. J. (2005). Anger in black and white: Race, alienation, and anger. Journal of Health and Social Behavior, 46, 85-101. Milovchevich, D., Howells, K., Drew, N. and Day, A. (2001). Sex and gender role differences in anger: An Australian community study. Personality and Individual Differences, 31, 117-127. Ohbuchi, K., Tamura, T., Quigley, B. M., Tedeschi, J. T., Madi, N., Bond, M. H. and Mummendey, A. (2004). Anger, blame, and dimensions of perceived norm violations: Culture, gender, and relationships. Journal of Applied Social Psychology, 34, (8), 15871603. Palfai, T. P. and Hart, K. E. (1997). Anger coping styles and perceived social support. The Journal of Social Psychology, 137, 405-411. Phillips, L. H., Henry, J. D., Hosie, J. A. and Milne, A. B. (2006). Age, anger regulation and well being. Age & Mental Health, 10 (3), 250-256. Rubin, T. I. (1969). The angry book. London: The McMillan Company.

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Sharkin, B. S. (1996). Understanding anger: Comment on Deffenbacher, Oettingi et al. (1996), Deffenbacher, Lynch, et al. (1996) and Kopper and Epperson (1996). Journal of Counseling Psychology, 43 (2), 166-169. Tavris, C. (1982). The misunderstood emotion. New York: Simon and Schuster Press. Tiedens, L. (2001). Anger and advancement versus sadness and subjugation: The effect of negative emotion expressions on social status conferral. Journal of Personality and Social Psychology, 80 (1), 86-94. Walters, R. P. (1983). Anger: What to do about it. Leicester, UK: Inter-Varsity Press. Vecchio, T. D. and O’Leary, K. D. (2004). Effectiveness of anger treatments for specific problems: A meta-analytic review. Clinical Psychology Review, 24, 15-34.

INDEX

A abortion, 70, 78, 79 abusive, 24, 197 academic, ix, x, xi, 10, 70, 101, 102, 105, 106, 107, 108, 110, 112, 114, 115, 117, 120, 121, 123, 124, 125, 126, 127, 128, 129, 161, 162, 163, 164, 165, 166, 167, 169, 171, 173, 174, 175, 176, 177, 178, 180, 184, 185, 187, 189, 192, 197, 199, 200, 201, 202, 205, 206, 207, 208, 209, 210, 211, 215, 216 academic development, 129 academic difficulties, 107, 184 academic performance, x, 161, 162, 163, 164, 165, 166, 167, 169, 171, 173, 174, 175, 176, 177, 178, 180, 184, 185 academic problems, 165 academic progress, 128 academics, 109, 201 acceptance, 69 access, 17, 85 accidents, 16 accommodation, 184 accounting, 26, 169, 171, 173, 175, 176, 177, 202 achievement, 50, 66, 102, 105, 106, 108, 125, 126, 127, 128, 161, 162, 163, 165, 180, 197 Acquired Immune Deficiency Syndrome, 93 activation, x, 5, 15, 140, 141 activism, 8 acute, 39, 40, 41, 42 adaptation, 41, 68, 69, 80, 81 adaptive control, 103, 111, 117 adaptive functioning, 136, 213 addiction, 96 adjustment, 9, 35, 39, 107, 125, 156, 159, 186, 212 administration, 66 administrators, 213

adolescence, 8, 9, 36, 79, 80, 126, 214 adolescent boys, 43 adolescents, ix, 9, 31, 39, 40, 63, 66, 69, 72, 81, 91, 92, 102, 105, 106, 184, 185, 190, 191, 192, 193, 202, 215, 218, 230 adrenaline, 25 adult, viii, 16, 32, 37, 42, 56, 67, 69, 70, 73, 74, 77, 78, 189, 190, 196, 201, 202 adult population, 201 adulthood, 9, 35, 36, 37, 38, 40, 56, 66, 81, 100, 102, 104, 135, 136, 193 adults, viii, ix, 10, 12, 15, 16, 36, 41, 45, 78, 83, 91, 102, 104, 105, 106, 126, 184, 192, 193, 194, 201, 202, 209, 215, 218 adverse event, 69 advertisement, 115 advertisements, viii, 83 affect, ix, 48, 50, 53, 64, 69, 80, 81, 102, 109, 113, 115, 118, 119, 121, 122, 124, 136, 141, 159 affective disorder, 193 affective states, 197 Africa, 13, 98 African American, 39, 49, 70, 92 African American women, 39, 92 African-American, 92, 98 age, viii, ix, x, 6, 13, 17, 18, 20, 36, 38, 43, 67, 70, 71, 73, 74, 75, 78, 80, 83, 85, 86, 87, 88, 89, 91, 97, 100, 102, 103, 104, 106, 109, 124, 126, 135, 144, 148, 154, 155, 171, 175, 177, 183, 184, 186, 188, 189, 201, 202, 207 agent, 13 agents, 31, 37 age-related, 135 aggression, 3, 4, 9, 12, 16, 21, 23, 24, 32, 35, 37, 38, 39, 40, 41, 42, 43, 63, 199, 229, 230 aggressive behavior, 4, 9, 14, 43, 219 aggressiveness, 35

234

Index

aging, 104 agoraphobia, 64 aid, 27, 53 AIDS, 34, 84, 91, 92, 93 air, 1 Alabama, 67 alcohol, viii, x, 5, 6, 50, 56, 62, 64, 66, 72, 95, 96, 97, 98, 99, 100, 183, 186, 188, 194, 198, 214 alcohol abuse, viii, 64, 95, 96 alcohol consumption, 5, 56, 97, 98, 194 alcohol dependence, 100 alcohol problems, 64 alcohol use, 6, 95, 97, 99, 214 alcoholics, 80 alcoholism, 96, 100 alexithymia, ix, 139, 152, 158, 159 alienation, 230 allies, 9 alpha, 18, 71, 72, 86, 107, 108, 145, 202 alternative, 13, 24, 104 ambiguity, 199 amelioration, 148 American Educational Research Association, 179 American Psychiatric Association, 35, 37, 48, 54, 62 American Psychological Association, 38, 44, 192, 215 analyses of variance, 148 analysis of variance, 145, 146, 149, 150, 151, 153 anger, vii, xi, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 71, 196, 197, 198, 200, 201, 202, 203, 207, 210, 211, 213, 215, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231 anger management, 2, 8, 9, 16, 31, 32, 33, 34, 36, 38, 40, 44, 45, 211, 219 angina, 31 anhedonia, 185 animals, 38 ANOVA, 60, 75, 112, 169, 171, 174 antagonistic, 15 antecedents, 10 antibody, 92, 156, 157 antidepressant, 192 antisocial, 35, 214 antisocial personality, 35 antisocial personality disorder, 35

anxiety, vii, x, 14, 15, 30, 33, 38, 41, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 80, 81, 156, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 191, 192, 198, 214, 215 anxiety disorders, 156 anxiousness, 64 appendix, 127 appetite, 188, 189 application, ix, 101, 102, 103, 104, 106, 109, 110, 117, 118, 119, 125, 126 appraisals, 11, 13, 14, 16, 17, 212 argument, 24, 154 ARIC, 46 arousal, x, 3, 4, 6, 13, 15, 21, 25, 26, 32, 51, 53, 59, 60, 61, 62, 140, 145, 146, 147, 152, 154, 165 artery, 5, 37, 41 arthritis, 157 artificial, 10 ASI, 50, 51, 52, 53, 54, 55, 56, 58, 59, 60, 63 Asia, 192 Asian, 17, 49, 71, 93, 98, 104, 125, 219, 228 Asian American, 49, 71 Asian cultures, 104, 228 assault, 9, 21, 35 assaults, 198 assertiveness, 33, 49, 61, 63 assessment, 14, 34, 36, 38, 58, 61, 63, 64, 142, 143, 148, 153, 154, 156, 197, 212 assignment, 59 assimilation, 141 association, 56, 77, 90 associations, 7, 14, 32, 78, 81, 153, 174, 190, 194, 198 assumptions, 87 Athens, 83 atherosclerosis, 5, 43 Atherosclerosis Risk in Communities, 46 athletes, 20 attachment, 8, 40 attacks, 17, 35, 52, 53, 55, 57, 63, 64, 66 attention, vii, 1, 4, 9, 10, 12, 13, 14, 32, 33, 34, 47, 49, 50, 52, 53, 108, 141, 152, 166 attitudes, 49, 92, 93, 96, 97, 98, 99, 213 attractiveness, 48, 49 attribution, 107, 111, 114, 117, 120, 123 Australia, 13, 39 authority, 40 autobiographical memory, 142 autonomic, 12, 15, 44, 59, 141, 145, 146, 152, 154 autonomic nervous system, 12, 15, 141 autonomy, 66 availability, vii

Index aversion, 51 avoidance, x, 50, 61, 90, 93, 140, 146, 147, 149, 152, 153, 154, 164, 196, 198, 199, 200, 202, 204, 207 avoidance behavior, 93 avoidant, 33, 198 awareness, ix, 53, 95, 98, 147, 167, 184, 190

B babies, 8, 80 baby boom, 11, 30 baby boomers, 30 battered women, 80 behavior, 1, 2, 4, 8, 9, 10, 12, 14, 16, 21, 22, 23, 24, 25, 27, 28, 30, 31, 35, 38, 41, 43, 63, 65, 72, 81, 83, 84, 87, 90, 91, 92, 93, 102, 105, 108, 135, 136, 158, 175, 177, 193, 196, 212, 219, 225, 226, 229 behavior therapy, 35, 65 behavioral assessment, 58, 61 behavioral change, 85 behavioral dimension, 3 behavioral disorders, 45 behavioral medicine, 3, 4 behaviorism, 14 behaviours, 141, 166 Beijing, 106, 108, 115 beliefs, 13, 15, 50, 51, 52, 53, 56, 63, 92, 93, 97, 135, 136, 219 beneficial effect, x, 139, 141, 147, 151, 153, 154 benefits, 19, 68, 91, 128, 185 benign, 31 bereavement, 156, 158, 159 betrayal, 21, 22 bias, 36, 64 bilingual, 106, 109 binge drinking, 97, 98 biological, 12, 46, 54, 104, 136 biology, 11, 219 bipolar, 193 bipolar disorder, 193 birth, 8, 38, 80, 81, 193 black, 17, 191, 230 blame, 230 blaming, 30, 72 blood, 2, 4, 5, 6, 8, 12, 25, 31, 33, 40, 41, 42, 44, 45, 219, 229 blood pressure, 2, 4, 5, 6, 8, 31, 33, 40, 41, 42, 44, 45, 143, 219, 229 blood vessels, 5 bodily injury, 162 body, viii, 54, 56, 68, 69, 141 body image, 56, 69

235

boiling, 23 borderline, 7, 35 borderline personality disorder, 35 Boston, 38, 179 boys, 43, 228 brain, 218 Brazil, 179 breakdown, 108 breast, 157 breast cancer, 157 breathing, 32, 165, 172 British, 65, 157, 158, 179, 180, 191, 193, 213, 214, 215, 230 broad spectrum, 144 Buddhist, 35 bullying, 56, 63 bureaucracy, 196 burnout, 96, 100, 212

C calcification, 5, 41 California, 157 Canada, 142, 155 cancer, 6, 33, 34, 45, 155, 156, 157, 158 candidates, 106, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126 cannabis, x, 183, 186, 188 capacity, 168, 181 carbon, 65 carbon dioxide, 65 cardiac output, 4 cardiac risk, 30 cardiovascular, 4, 5, 19, 25, 30, 31, 33, 34, 38, 42, 44, 45 cardiovascular disease, 5, 19, 30, 31, 33, 38, 42 Cardiovascular disease (CVD), 4, 5 case study, 63 catecholamine, 6 category a, 200, 209 catharsis, 218, 228, 230 Caucasian, 70, 98, 213 causal attribution, 13 causal interpretation, 55 causal model, xi, 195, 199 cell, 29 Center for Disease Control and Prevention, 92 Centers for Disease Control (CDC), 84, 89, 196 cervical, 155, 156 cervical cancer, 156 cervical dysplasia, 155 CES, 71, 81 channels, 85

236 chemical, 16 chemistry, 11 Chi square, 201 Chicago, 41, 135, 136 childbearing, 69, 80, 104 childbirth, 43 childhood, 8, 35, 40, 43, 55, 56, 62, 66, 69, 80, 81, 102 childhood sexual abuse, 69, 81 children, 8, 9, 11, 30, 38, 39, 40, 42, 46, 56, 63, 69, 71, 78, 80, 81, 155, 158, 201 China, ix, 101, 105, 108, 115, 122, 124 Chinese, ix, 101, 105, 106, 109, 115, 124, 125, 127 Chi-square, 221, 222, 223, 224, 226, 227 chronic, vii, 15, 35, 39, 47, 127, 155 chronic disease, 127 chronic pain, 155 chronic stress, 15 cigarettes, 97 circulation, 5, 156 civil service, 6 classes, 5, 13, 70, 96, 99, 108, 121 classification, 88, 91 classified, 77, 86, 202 classroom, viii, 80, 83, 212 classroom management, 212 classrooms, 11, 44 clients, 35, 36 clinical, 1, 2, 31, 48, 49, 50, 57, 61, 62, 63, 80, 81, 140, 186, 189, 193 clinical depression, 50 clinician, 35 clinicians, 4, 30 closure, 142 cluster analysis, 77, 79 clusters, 77, 79 cocaine, x, 183, 188 codes, 22 coding, vii, 1, 14, 20, 21 cognition, 40, 46, 158 cognitive, 3, 11, 13, 16, 17, 31, 35, 36, 37, 38, 45, 49, 50, 62, 63, 64, 65, 126, 141, 148, 156, 157, 162, 163, 164, 165, 167, 176, 192, 216 cognitive abilities, 126 cognitive activity, 164, 165, 176 cognitive level, 141 cognitive process, 13 cognitive processing, 13 cognitive reaction, 165 cognitive test, 165 cognitive variables, 50 cognitive-behavioral therapies, 36 cohesiveness, 9

Index cohort, 20, 38, 92, 193 college campuses, 50, 61 college students, vii, viii, 2, 9, 10, 11, 12, 15, 17, 18, 19, 20, 21, 30, 32, 34, 36, 37, 43, 47, 48, 49, 50, 51, 55, 57, 58, 61, 62, 63, 64, 65, 66, 67, 70, 72, 78, 81, 83, 84, 85, 87, 89, 91, 92, 93, 156, 161, 162, 163, 164, 193, 196, 198, 199, 212, 213, 214 colleges, 163 combat, 8, 31 common rule, 171 communication, 85, 158, 228 communication skills, 228 communities, 105, 127, 201 community, 2, 5, 12, 45, 80, 192, 193, 212, 213, 230 comorbidity, 64, 191, 192, 193 comparative research, 104 compassion, 49 compensation, 102, 135 competence, 49, 61, 64, 68 competency, 151, 153, 154 competition, 184 complementary, 178 complexity, 162, 167 compliance, 144 complications, 51, 57 components, 15, 16, 17, 31, 32, 52, 64, 68, 78, 108, 110, 117, 164, 165, 167, 169, 170, 202 composition, 17 computer, 28 concealment, ix, 139, 147, 152, 157 concentration, 188, 189 conception, 71, 73, 74, 78, 79, 210 conceptualization, 3, 13, 51, 57, 68, 125 concordance, 185 concrete, 31 conditioning, 55 condom, viii, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93 condoms, 84, 87, 90, 92, 93 conductance, 148 confession, 158 confidence, 4, 24, 33, 171 confidence intervals, 186 confidentiality, 185 confirmatory factor analysis, 178, 179, 180, 202 conflict, 2, 7, 9, 23, 26, 27, 28, 31, 33, 36, 37, 38, 40, 41, 199, 219 confounding variables, 90 confrontation, 141, 142, 143, 152, 153, 155 confusion, 8, 196, 200, 201, 202, 203, 204, 207, 210 congruence, 12 consciousness, 46, 61, 62 consent, viii, 19, 73, 83, 97, 185

Index consequences, ix, x, 139, 140, 141, 148, 151, 152, 153, 154 constraints, 103, 135, 219 construct validity, 16 construction, 42, 105, 215 constructivist, 12 consumption, 5, 56, 97, 98, 194 consumption rates, 98 content analysis, 20, 159 context, ix, x, 101, 102, 122, 140 continuing, 2, 77, 106, 201 control, vii, ix, xi, 1, 10, 29, 32, 34, 35, 36, 42, 44, 46, 47, 48, 50, 52, 53, 58, 59, 60, 61, 62, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 135, 136, 137, 140, 142, 144, 145, 148, 149, 150, 151, 152, 153, 154, 190, 192, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229 control condition, 36, 59, 140, 142, 145, 148, 153 control group, 34, 52, 60, 61, 142, 144, 145, 149, 151, 152, 154 controlled, 29, 37, 38, 58, 99, 158, 218, 228 controlled substance, 99 controlled substances, 99 convergence, 109 conviction, 2 coping, viii, ix, x, 33, 34, 42, 48, 61, 67, 68, 69, 70, 71, 72, 74, 75, 76, 77, 78, 79, 80, 81, 135, 136, 139, 140, 142, 147, 148, 149, 150, 151, 152, 153, 154, 156, 157, 158, 159, 179, 180, 195, 197, 198, 202, 212, 213, 214, 215 coping model, 152 coping strategies, viii, xi, 48, 67, 68, 70, 71, 72, 74, 75, 77, 78, 79, 80, 81, 154, 156, 157, 195, 196, 197, 198, 199, 200, 202, 204, 205, 207, 209, 210, 211, 213 coping strategy, 61, 202, 204, 207, 210 coronary artery disease, 5, 37, 41 coronary heart disease, 5, 6, 17, 19, 40, 41, 43, 45, 46 correlation, 52, 97, 112, 114, 115, 118, 120, 123, 146, 152, 171, 172, 174 correlation coefficient, 115, 146 correlation coefficients, 146 correlations, 4, 16, 56, 63, 115, 121, 146, 147, 152, 154 costs, 69, 218 counseling, 9, 144, 213, 215 course content, 176 course work, 19 covariate, 75 CPC, 107, 108, 110, 117

237

creativity, 68 credit, 58, 143 criticism, 16, 17, 30 cross-cultural, 13, 127, 135, 177, 190, 192, 212 cross-cultural comparison, 190 cross-fertilization, 11 cross-sectional, 79, 90, 169, 184, 191 cross-sectional study, 169, 184, 191 cross-validation, 170 crying, 24 cues, 48, 53, 63 cultural, 12, 14, 39, 44, 104, 127, 136, 170, 219, 229 cultural differences, 14, 39, 219 cultural heritage, 219 culture, 11, 14, 20, 39, 44, 104, 137, 213, 219, 228 cumulative, 141 curiosity, 14, 64 curriculum, 98, 100 customers, 27 CVD, 4, 5, 6, 31 cynicism, 3

D danger, 219 data analysis, 19, 20, 61, 170 data collection, 9, 20, 36, 127, 169 dating, 49, 61 death, 5, 6, 17, 51, 53, 145, 184, 188, 189 death rate, 6 decisions, 25, 184 defense, 26 deficit, 158 deficits, 50 definition, 51 degree, vii, 16, 35, 47, 50, 52, 69, 70, 74, 75, 91, 109, 197 delinquency, 81 delinquent adolescents, 31 delivery, 9, 78, 99 delta, 213 demand, 32, 125, 166, 213 demographic, x, xi, 18, 88, 161, 169, 171, 175, 177, 202, 217, 219 demographic characteristics, 202 demographic data, 18 demographic factors, x, 161, 171, 175, 177 demographics, 71 denial, 198 density, 92 Department of Education, 83, 96, 101, 217 Department of Health and Human Services, 191 Department of Justice, 67

238

Index

dependent variable, 71, 73, 74, 75, 169, 204 depressed, x, xi, 7, 35, 79, 183, 185, 186, 188, 189, 195, 197, 198, 199, 200, 204, 207, 209, 210, 211, 212, 213, 214 depression, vii, viii, x, 2, 6, 7, 28, 30, 36, 47, 50, 55, 56, 61, 63, 64, 66, 68, 69, 70, 71, 73, 75, 77, 79, 80, 81, 149, 155, 157, 183, 184, 185, 186, 188, 189, 190, 191, 192, 193, 194, 196, 197, 198, 199, 200, 201, 202, 203, 204, 207, 210, 213, 214, 219 depressive disorder, 41, 184, 186, 189, 191, 192, 193 depressive symptomatology, 137 depressive symptoms, x, 7, 42, 45, 56, 79, 183, 185, 189, 191, 192 desensitization, 65 desire, 49, 98, 141 destruction, 12, 21, 25, 32 detection, 186, 191 developing countries, 13, 192 developmental psychopathology, 81 deviation, 145, 146, 149, 151, 186 diagnostic, 58, 65, 188 Diagnostic and Statistical Manual of Mental Disorders, 35 diagnostic criteria, 58 differences, 148, 149, 151, 152, 153 differentiation, 44 diffusion, 8 dignity, 29 dimensionality, 170 direct action, 198 disability, 127, 184 disappointment, 24 discipline, x, 35, 183, 185, 187, 189 disclosure, ix, x, 49, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 210, 215 discomfort, 48, 162, 163, 165, 176 discourse, 105 discrete emotions, 41, 43 disease, 140, 141, 155, 158 diseases, 33 disorder, vii, 35, 47, 48, 51, 52, 53, 54, 55, 57, 62, 63, 64, 65, 66, 142, 156, 184, 189, 190, 191, 192, 193 disposition, 18 disputes, 9 disseminate, 96, 99 distortions, 16, 30, 50 distraction, 34, 44 distress, 48, 55, 58, 59, 61, 75, 79, 155, 163, 164, 191, 196, 199, 213, 218 distribution, 85, 86, 173, 201, 212 divergence, 152

diversity, 78 divorce, 7, 35, 39, 78, 145 domain, 50, 52, 65, 105, 106, 108, 111, 125, 152 doors, 220, 221, 222, 223, 224, 225, 226, 228 down-regulation, 41 dream, 105 drinking, vii, 6, 47, 48, 50, 56, 61, 63, 97, 98, 100, 192 drinking pattern, 100 drinking patterns, 100 dropouts, 197 drug abuse, 35, 96 drug addict, 96 drug addiction, 96 drug use, viii, 90, 93, 95, 96, 99, 100 drugs, 6, 72, 86, 96, 99, 198 DSM, 35, 37, 48, 54, 58, 64, 184, 185, 188, 192, 193 DSM-III, 54, 64, 192 DSM-IV, 35, 37, 48, 58, 184, 185, 188, 193 duration, 4, 30, 31, 96, 99, 192 dysfunctional, vii, 1, 7, 30, 36, 155 dysphoria, 156, 212, 214, 215 dysplasia, 155

E East Asia, 105, 192 East Germany, 135 eating, 37 ecology, 125, 126 economic, 185 education, xi, 11, 6, 9, 44, 70, 77, 83, 85, 92, 93, 96, 99, 100, 136, 179, 180, 181, 191, 195, 196, 201, 215, 217, 219, 225 educational programs, 91, 96, 98 educational research, 210 educators, x, 161, 162 effective, 154 efficacy, 8, 31, 34, 36, 50, 58, 64, 93, 96, 100, 143, 147, 148, 151, 153, 178 Egypt, 164, 179 Egyptian, 170 eigenvalue, 171 eigenvalues, 110, 111, 114, 117, 119, 120, 122, 123 elderly, 6, 137 election, 135 electrodes, 12 electromyography, 12 elementary school, 63 e-mail, 47, 67, 85 emergence, 119, 126 emotion, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 17, 30, 34, 35, 37, 39, 40, 41, 43, 44, 45, 46, 102, 140, 192,

Index 196, 197, 198, 199, 200, 202, 204, 207, 211, 212, 213, 214, 215, 218, 219, 229, 231 emotion regulation, 9, 192 emotional, ix, xi, 2, 8, 10, 12, 13, 14, 15, 36, 66, 69, 113, 115, 118, 139, 140, 141, 142, 143, 147, 151, 154, 156, 157, 158, 159, 163, 165, 176, 184, 195, 196, 197, 198, 199, 211, 216 emotional disorder, 184 emotional distress, 197, 198 emotional experience, 10, 12, 13, 15, 113, 115, 118 emotional intelligence, 230 emotional reactions, 211, 216 emotional responses, 66 emotional state, 14, 196 emotional well-being, 156, 199 emotionality, 34, 164, 196 emotions, ix, 10, 11, 12, 13, 17, 29, 30, 34, 37, 38, 39, 40, 41, 42, 43, 44, 53, 81, 139, 146, 147, 152, 158, 159, 163, 197, 218, 228 empathy, 24, 32 employees, 209 employment, 102, 106, 117, 125, 200 energy, 33, 107, 114, 115, 120, 121, 122, 124, 127, 129, 188, 197, 209, 216 engagement, 29, 74, 104, 118, 137 engineering, 25 English, ix, 14, 101, 105, 106, 109, 193 enrollment, 175, 177 entertainment, 46 environment, xi, 9, 10, 46, 68, 70, 79, 102, 195, 196, 197, 199, 200, 201, 209, 210, 218 environmental, 46, 68, 78, 125, 169, 175, 177, 209 environmental factors, 68, 78, 175 environmental influences, 46 epidemiological, 81 epidemiology, 184, 191, 192, 193 ERIC, 212 ester, 29 estrangement, 28 ethical, 73 ethnic groups, 49 ethnicity, 80, 192, 219 etiology, 5, 64 Europe, 191 European, 46, 49, 189, 193, 213 evaluative thought, 165 evening, 23 evidence, 7, 8, 9, 11, 12, 17, 26, 30, 33, 35, 36, 38, 53, 89, 90, 155, 174, 175, 184, 197, 198, 202 evolution, 184 evolutionary, 11, 12 exaggeration, 16

239

examinations, ix, 101, 105, 106, 121, 125, 163, 166, 167, 176, 177 exclusion, 32 exercise, 8, 42, 44, 59, 106 expectations, 50, 72, 154 experiment, 142, 143, 154, 157 experimental condition, ix, 139, 142, 147, 148, 149 expert, 155 explosive, 5, 7, 9, 32, 33, 38 exposure, vii, 9, 47, 48, 53, 57, 58, 59, 60, 61, 62, 63, 65, 68, 157, 171, 175, 177 expression, ix, 68, 77, 139, 140, 141, 143, 152, 157, 158, 159 eyes, 29

F facial expression, 12, 39 facial muscles, 12 factor analysis, 72, 107, 108, 110, 111, 112, 114, 117, 118, 120, 123, 171, 172 factorial, 142, 148, 177 factors, 154 failure, ix, 56, 102, 106, 107, 110, 112, 113, 115, 118, 119, 121, 124, 125, 126, 127, 145, 162, 164, 189, 198 fainting, 54 faith, 97 familial, 9 family, x, 5, 9, 26, 34, 36, 43, 53, 55, 69, 72, 78, 80, 100, 145, 183, 187, 188, 202, 204, 211, 230 family conflict, 9, 36 family environment, 9 family history, 43, 55 family income, x, 183, 187, 188 family members, 145 family support, 204 fatigue, 149, 189, 196, 197, 199, 200, 201, 202, 203, 204, 207, 209, 210 faults, 33 fear, vii, 4, 12, 33, 37, 44, 46, 47, 48, 51, 52, 53, 55, 57, 58, 61, 63, 65, 66, 163, 164, 197 fears, 48, 51, 52, 53, 54, 57, 62, 162 federal funds, 96 feedback, 12, 32 feelings, 3, 12, 13, 15, 16, 25, 28, 29, 30, 32, 33, 34, 40, 56, 61, 70, 75, 140, 141, 142, 157, 201, 218, 219, 229 female, 144, 148, 149 females, xi, 17, 20, 97, 184, 195, 198, 199, 207, 209, 228 fertilization, 11 fibromyalgia, 155, 156

Index

240 finance, 184 Finns, 189 first-time, 92 flavor, 24 fluid, 10 focus group, 86 focus groups, 86 focusing, x, 34, 91, 96, 140, 166, 202 forgiveness, 34, 35, 36, 40, 42, 46 France, 13 frequency, 142, 143, 146 friends, 72, 97, 145, 148 friendship, 29 frustration, 10, 14, 21, 23, 29, 198, 230 frustration-aggression hypothesis, 230 fulfillment, 87 functional, 155 funds, 96 furniture, 220, 221, 222, 223, 224, 225, 226, 228

G gauge, 71 gay men, 91, 92 gender, viii, xi, 7, 14, 18, 19, 40, 44, 45, 80, 81, 83, 85, 87, 88, 89, 97, 112, 123, 154, 171, 175, 177, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 209, 210, 211, 213, 214, 215, 217, 218, 219, 220, 221, 222, 230 gender differences, xi, 7, 14, 112, 124, 195, 197, 198, 199, 200, 209, 210, 211, 213, 214 gender role, 213, 230 generalized anxiety disorder, 54 generation, 11 genes, 39 genetic, 8, 16 Georgia, 83 Germany, 125, 135, 136, 139, 152 girls, 222 glucose, 45 glucose metabolism, 45 goal attainment, 102, 103, 107, 120, 121 goal-directed, 197 goal-directed behavior, 197 goals, 14, 34, 102, 104, 105, 107, 108, 109, 120, 121, 125, 126, 128, 129, 135, 136, 198, 214 GPA, 71 grades, 9, 184 graduate education, 202 graduate students, 19 grandparents, 78 grants, 96 Great Depression, 135

greed, 58 grouping, 54 groups, viii, ix, 16, 20, 21, 22, 27, 30, 31, 36, 38, 39, 49, 52, 54, 56, 58, 59, 60, 61, 67, 69, 70, 74, 75, 77, 78, 86, 87, 90, 91, 102, 104, 106, 117, 118, 122, 124, 126, 148, 149, 153, 169, 171, 174, 176, 186, 204, 211 growth, 34, 36, 136, 213 guidance, 210 guidelines, 20, 81 guilt, 2, 141, 162, 188 guilty, 109 Guinea, 12

H habituation, 59, 63 handling, 29, 99 hands, 10, 12 hanging, 24, 29 happiness, 44, 196 harassment, 15 harm, vii, 3, 7, 10, 14, 47, 51, 52, 53, 57, 162, 194, 218 harmful, 13 harmony, 7, 14 hate, 24 hazards, 17 head, 11, 35 head trauma, 35 headache, 165, 172, 176 health, viii, ix, x, 1, 2, 3, 4, 6, 7, 11, 14, 31, 32, 33, 34, 42, 44, 46, 49, 67, 69, 70, 71, 73, 75, 77, 78, 79, 84, 90, 91, 92, 93, 95, 96, 97, 99, 100, 104, 136, 137, 139, 140, 141, 145, 147, 148, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 184, 191, 194, 213, 215, 218, 230 Health and Human Services, 191 health care, 96, 100, 140, 141, 152, 155 health effects, ix, 139, 154 health problems, 140 health psychology, 1, 3, 4, 7, 31, 33, 34 health services, 99 health status, viii, 46, 67, 70, 71, 78, 140, 152 healthcare, viii, 95, 96 heart, 4, 5, 6, 8, 17, 19, 25, 38, 40, 41, 42, 43, 44, 45, 46, 51, 54, 57, 58, 104, 164 heart attack, 17, 51, 57 heart disease, 5, 6, 17, 19, 40, 41, 43, 45, 46 heart rate, 4, 57, 164 heavy drinking, vii, 50 hegemony, 14 height, 30

Index hepatitis, 158 hepatitis B, 158 heritability, 192 heterogeneity, 19, 73 heterogeneous, 78, 152 heuristic, 126 high blood pressure, 219 high risk, 89, 190 high school, ix, xi, 9, 15, 36, 69, 101, 106, 108, 109, 112, 115, 118, 121, 122, 123, 125, 126, 217, 223, 224, 225, 226, 228, 229 high scores, 3 higher education, 96, 211, 213 high-level, 202 high-risk, 44, 80, 84, 93 high-speed, 12 hip, 49, 163 hips, 174 Hispanic, 17, 71 HIV, v, viii, 34, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93 HIV infection, viii, 83, 84, 86, 87, 88, 90, 91 HIV test, 84, 90, 92, 93 HIV/AIDS, 34, 84, 92, 93 homework, vii homogeneity, 14 Hong Kong, 101, 127 hopelessness, viii, 33, 43, 68, 70, 71, 72, 73, 75, 77, 79 hospital, 29, 54, 214 host, vii, 6 hostility, viii, 3, 4, 5, 6, 7, 14, 15, 31, 34, 35, 38, 40, 41, 42, 43, 44, 45, 46, 68, 70, 71, 72, 73, 75, 77, 79 HSC, 72 human, 12, 37, 102, 104, 105, 136 human activity, 104 human behavior, 102 human kinetics, 213 human motivation, 104 humans, 11, 30 humiliation, 24 humorous, 34 husband, 2 hygiene, 25 hypertension, 16, 33, 38, 39, 43, 219 hypertensive, 5, 16 hyperventilation, 54, 59, 63, 64 hypothesis, 53, 56, 73, 84, 91, 104, 126, 144, 145, 152, 155, 165, 171, 174, 175, 199, 200, 204, 205, 213, 230 hypothesis test, 144

241

I ice, 8 id, 31, 75, 153 ideas, 125, 126 identification, 23 identity, 69 IES, 149, 150 illusion, 80 imagery, 32, 44, 46, 58 images, 12 immune function, 158 immune response, 158 immune system, 6 immunocompetence, 6, 154, 155 immunological, 41, 43, 141 impulsivity, 7 in situ, 16, 53 inactive, 85, 198 incentive, 115, 143, 185 incidence, 40, 193 Incidents, v, 1, 18 inclusion, 35, 68, 178 income, x, 183, 186, 187, 188 independence, 68 independent variable, 71, 169, 204, 207 India, 39 Indian, 212 indication, 8, 48, 51 indicators, 2, 53, 191, 197, 200 indices, 45 indigenous, 105, 127 individual development, 81 individual differences, 51, 214 induction, 61, 62, 157 industrial, 213 infancy, 31 infarction, 5, 31, 39, 42 infection, viii, 84, 86, 87, 88, 90, 91 infections, viii, 83, 85, 87 inferences, 211 inflammatory, 32 influence, x, 140, 142, 146, 147, 152, 157 informed consent, 19, 73, 97 inhalation, 66 inhibition, 6, 38, 40, 140, 141, 143, 152, 155, 158 inhibitor, 32 inhibitory, 158 initiation, 90, 97 injury, 51, 53 injustice, 10, 13, 14, 16, 25, 27 inmates, 44, 158 innovation, viii, 83, 191

242

Index

input, 86, 96, 167 insight, 68 inspection, 144, 145, 151, 153 inspections, 196 institutions, 96, 100, 201, 202, 211 institutions of higher education, 96 instruction, x, 110, 140, 147, 154 instruments, 2, 19, 142, 143, 148, 153, 154, 189 insulin, 7 insulin resistance, 7 integration, 103, 127, 142 intelligence, 48, 49, 218 intensity, ix, 4, 30, 139, 143, 146 intent, ix, 80, 139, 142 intentions, 84 interaction, 12, 26, 48, 49, 55, 56, 60, 63, 64, 65, 90, 102, 145, 146, 148, 149, 150, 151, 153 interaction effect, 60, 90, 148, 149, 151, 153 interaction effects, 60, 90, 148 interactions, 5, 6, 7, 8, 9, 16, 30, 34, 37, 42, 90 interdependence, 14 interest, 71, 105 interference, 167, 178, 185, 189 internal consistency, 18, 71, 86, 151 internal processes, 102 internalizing, 80 internet, viii, 83, 85 internship, 191 interpersonal communication, 228 interpersonal conflict, 33, 37 interpersonal interactions, 37 interpersonal relations, 13, 16, 22, 48, 50, 162 interpersonal relationships, 13, 16, 22, 48, 50 interpretation, 37, 55, 104, 149, 151 interval, 170 intervention, 31, 33, 35, 36, 38, 40, 58, 59, 60, 61, 62, 91, 92, 96, 141, 153, 154, 159, 211 interventions, 154 interview, 22, 31, 73, 78, 84, 93, 185, 186 interview methodology, 31 interviews, 2, 156, 189 intimacy, 66 intimidating, 227 intimidation, 11, 44 intrinsic, 53 intrusions, x, 140, 149, 154 investment, 102 invitation to participate, 185 IQ, 78 Iran, 230 Ireland, 31, 41, 92 irritability, 10, 230 irritation, 15, 72

ischemia, 5, 40 Islamic, 229 isolation, vii, 47, 48, 50, 61 Israel, 181, 195

J JAMA, 93 Japan, 13, 184, 189, 193 Japanese, 215 Japanese women, 215 jewelry, 27 job loss, 35, 127, 141, 159 job satisfaction, 216 jobs, 7, 36, 196, 199 judge, vii, 47, 48, 57, 61 judges, 143 judgment, 10

K kappa, 185 knowledge, 70, 91, 92, 93, 96, 100, 105, 136 Korean, 213

L labeling, 213 lambda, 204 language, 9, 25, 27, 29, 32, 142, 158, 193 large-scale, 104 later life, 157 Latin America, 13 laughter, 13 law, 186, 215 lead, x, 61, 79, 140, 153, 164, 177, 218, 229 leadership, 49 leadership abilities, 49 learning, 20, 29, 30, 36, 103, 107, 108, 111, 114, 115, 117, 120, 123, 124, 127, 128, 162, 166, 167, 178, 184 learning process, 184 left ventricular, 5 leisure, 198, 201, 205, 206, 207, 208, 209 leisure time, 198 lens, 125 life course, 36 life satisfaction, 156 life span, 102, 135, 136 lifetime, 84, 86, 87, 90, 192 light, 152 likelihood, 69, 141, 152

Index Likert scale, 52, 86, 107, 109, 110, 112, 118, 170 limitation, 13, 79, 90, 148 limitations, 31 links, 40 lipid, 6 listening, 28, 32 literature, vii, viii, 2, 4, 6, 7, 10, 11, 14, 20, 30, 31, 33, 47, 48, 50, 69, 70, 80, 92, 95, 96, 97, 99, 105, 162, 164, 199, 200, 202, 219, 227 location, 53 London, 38, 42, 230 loneliness, 80 long period, 27 long run, 129, 141 longevity, 14 longitudinal studies, 6, 43, 189 longitudinal study, 9, 212 long-term, ix, x, 96, 99, 103, 139, 140, 141, 142, 143, 145, 146, 147, 148, 149, 151, 152, 153, 154 Los Angeles, 93 losses, 125 love, 29 low power, 13, 77 low risk, 86, 90 LSD, 74, 75 LTA, 16 lying, 29 lymphocyte, 156

M mainstream, 10 maintenance, viii, 47, 48, 51, 54, 62 major cities, 13 major depression, 155, 157, 190, 192, 193, 212 major depressive disorder, 191, 192 maladaptive, viii, 4, 6, 7, 15, 30, 31, 35, 67, 70, 71, 72, 74, 75, 77, 78, 79, 145, 152, 198 Malaysia, 125, 161, 170 male, 144 males, 17, 20, 97, 100, 184, 198, 207, 228 maltreatment, 81 management, 2, 8, 9, 16, 31, 32, 33, 34, 36, 38, 40, 41, 42, 44, 45, 46, 142, 148, 157, 197, 212, 214, 219 mandates, 96 manipulation, 144, 156 MANOVA, 59, 73, 74, 75, 204 marital conflict, 38, 41 marital status, 36, 71, 74, 79 marriage, 32, 78 mass, 58 mastery, 32

243

mathematics, 167, 180, 187 matrix, 172 mean, 144 meanings, 117, 120 measurement, 3, 81, 136, 157, 178, 214 measures, ix, 2, 4, 15, 18, 37, 48, 49, 50, 53, 55, 56, 58, 59, 60, 61, 62, 65, 73, 77, 85, 136, 139, 141, 142, 143, 152, 153, 154, 156, 167, 172, 190, 212, 214 media, 1, 9 median, 5 mediators, 45 medical school, 54, 99, 100 medical student, 5, 99, 100, 184, 189, 190, 191 medication, 96 medicine, viii, 3, 4, 5, 95, 96 meditation, 32 membership, 77, 85 memory, 12, 56, 142, 154, 167, 184 memory processes, 167 men, x, xi, 2, 7, 13, 14, 17, 19, 20, 31, 33, 38, 41, 42, 44, 45, 46, 81, 92, 183, 184, 189, 190, 191, 193, 195, 196, 197, 199, 200, 201, 203, 204, 205, 207, 209, 210, 211, 213, 214, 215, 228 mental activity, 164 mental disorder, 35, 37, 62, 193 mental health, vii, viii, 2, 3, 7, 49, 67, 69, 70, 71, 73, 74, 75, 77, 78, 79, 155, 184, 194, 211, 214 mental illness, 213 mental representation, 102 Merleau-Ponty, 2, 42 messages, viii, 84, 91, 167 meta-analysis, 35, 166 metabolism, 45 metaphor, 104 methodology, 126, 136 Mexican, 49 Mexico, 164 middle-aged, 19, 212 midlife, 44, 156 military, 15 Minnesota, 136 minority, 77, 92, 215 mirror, 56 miscarriage, 70, 78, 79, 80, 81 mixing, 104 modalities, 2 models, 2, 8, 9, 36, 80, 87, 91, 92, 93, 142, 164, 166, 167, 177, 178 moderators, 142, 143 modern society, 125 modernity, 125 monograph, 10

Index

244

mood, x, xi, 35, 37, 44, 136, 140, 141, 144, 148, 151, 153, 154, 156, 183, 185, 186, 188, 189, 193, 195, 196, 198, 200, 201, 202, 203, 204, 207, 209, 210, 211, 212, 214, 215 mood disorder, 193 mood states, xi, 195, 196, 198, 200, 201, 204, 209, 210, 211 morale, viii, 68 morality, 68 mortality, 6, 39, 40, 46, 192 motherhood, 70, 71 mothers, 2, 9, 39, 69, 70, 80 motivation, vii, x, 32, 47, 50, 51, 65, 85, 92, 102, 104, 122, 124, 125, 126, 140, 155, 162 motives, 32 movement, 12 multidimensional, 3, 9, 164 multiple regression, 87, 90, 205 multiple regression analyses, 87, 205 multiple regression analysis, 87 multivariate, 93, 204, 210 muscle, 12, 43, 59, 172 muscles, 12, 165 muscular dystrophy, 26 music, 20, 22 Muslim, 97, 98 myocardial infarction, 5, 31, 39, 42 myocardial ischemia, 5, 40

N narratives, vii, 1, 2, 13, 17, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 34, 37 nation, 11 national community, 212 Native American, 17, 71 natural, 2, 30 natural science, 2 NCS, 192 Nebraska, 39 negative affectivity, 145, 152 negative attitudes, 49 negative consequences, 7, 16, 33, 51 negative coping, 199 negative emotions, 34, 40, 163, 199 negative experiences, 153 negative mood, x, 140, 144, 148, 151, 153, 156, 196, 197, 198, 200, 212 negative relation, 49, 163, 174, 176 neglect, 155 negotiation, 32 nervous system, 12, 15, 141 nervousness, 162

Netherlands, 13 network, 202 neuroendocrine, 41 neurons, 1 Nevada, 47 new, vii, ix, 2, 5, 15, 17, 20, 32, 36, 65, 101, 103, 107, 108, 111, 114, 115, 120, 121, 124, 126, 128, 129, 142, 155, 159, 166, 167, 172, 193 New York, 31, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 62, 63, 66, 81, 92, 135, 136, 158, 178, 179, 181, 192, 213, 214, 231 Newton, 41 nicotine, 190 NMR, 151 NO, 187 noise, 29, 57 non-clinical, 186, 193 non-clinical population, 186 normal, 52, 54, 162, 173 normal distribution, 173 North America, 2 North Carolina, 35, 100, 161 null hypothesis, 171, 204 nurses, 2, 96, 99, 100 nursing, viii, 46, 95, 96

O obesity, 5, 6 obligation, 32 obsolete, 141 occupational, vii, 7, 30, 47, 212 OCD, 54 odds ratio, 186 offenders, 31, 41 Office of Justice Programs, 67 Office of Juvenile Justice and Delinquency Prevention, 67 Ohio, 179 old age, 43, 102 online, 92 on-line, 73 optimal health, 8 optimism, 8, 36, 93, 198, 199, 212 optimists, 156 optimization, 102, 103, 106, 107, 108, 109 oral, viii, 84, 85, 86, 87, 88, 90, 91, 141 ordinal data, 170 organ, 6 organic, 30, 32, 35 organizational behavior, 214 organizational stress, 215 organizations, viii, 83, 85, 213, 215

Index orientation, viii, 83, 85, 87, 88, 89, 91, 137, 205, 206, 207, 208, 215 outliers, 87 outpatients, 190 output, 167 overeating, 6 over-the-counter, 6 overtraining, 215

P Pacific, 63, 95 packets, 18, 73 pain, 5, 155 Pakistan, 230 Pakistani, 215 palpitations, 51, 54 panic attack, 52, 53, 55, 57, 63, 64, 66 panic disorder, vii, 47, 50, 52, 53, 54, 55, 57, 62, 63, 64, 65 panic symptoms, 54 paper, 10, 14, 18, 20, 37, 38, 172, 176, 179, 214, 216 paradoxical, 57, 65 paranoia, 32 parenthood, 69, 78, 80 parenting, viii, 68, 69, 70, 71, 73, 75, 76, 77, 78, 79, 81, 229 parents, 8, 9, 27, 29, 69, 145, 186, 201 partnership, 104 passive, 202, 219, 228 passive-aggressive, 219 password, viii, 83, 85 path model, 42 pathogenic, 3, 4 pathology, 30, 35 pathways, 42 patients, 5, 6, 16, 38, 40, 42, 54, 63, 65, 99, 155, 156, 157 patterning, 44 pedagogical, 127 pedagogy, 214 peer, 9, 39, 63, 66, 69, 96, 97, 98 peer group, 39 peers, 8, 9, 50, 56, 69, 78, 80, 98, 145, 148 pendulum, 80 perceived control, 136 perceived self-efficacy, 212 percentile, 20, 36 perception, viii, 9, 42, 48, 49, 56, 83, 84, 85, 86, 87, 89, 90, 91, 92, 93, 107 perceptions, viii, 48, 71, 74, 75, 76, 78, 83, 89, 90, 91, 172, 199, 214

245

performance, x, 48, 50, 59, 68, 161, 162, 163, 164, 165, 166, 167, 169, 171, 173, 174, 175, 176, 177, 178, 180, 184, 185, 186, 196, 198, 214 permit, 2, 19, 22 personal, ix, 1, 14, 16, 32, 34, 36, 48, 49, 53, 55, 68, 89, 91, 107, 109, 139, 141, 142, 143, 144, 145, 162, 166, 185, 190, 191, 197, 199, 200, 201, 202, 205, 207, 210, 218 personal control, 109 personal relations, 185, 218 personal relationship, 185, 218 personal welfare, 162 personality, ix, 7, 10, 14, 32, 35, 36, 38, 42, 43, 44, 64, 70, 81, 139, 142, 143, 146, 147, 152, 154, 162, 178, 192, 212 personality characteristics, 81, 192 personality constructs, 154 personality dimensions, 64 personality disorder, 7, 32, 35 personality traits, 14, 38, 43, 70 personality type, 212 perspective, 81, 90, 104, 135, 141, 142 pessimists, 156 pharmacists, 99 Pharmacists, 99 pharmacological, 96, 99 phenomenology, 2, 42, 43, 184 philosophy, 109, 213 phobia, vii, 47, 48, 54, 56, 57, 58, 62, 63, 64, 65, 66 phobic anxiety, 64 phone, 24, 29 photographs, 12 physical abuse, 145 physical aggression, 9, 12, 16, 21, 24, 32 physical exercise, 8 physical health, 2, 7, 33, 42, 141, 145, 147, 148, 151, 153, 154, 155, 157, 218 physicians, 214 physiological, 4, 6, 12, 14, 15, 26, 32, 34, 54, 56, 58, 59, 60, 61, 62, 64, 65, 141, 143, 156, 158, 165, 212 physiological arousal, 4, 6, 15, 26, 32, 59, 60, 61, 62, 165 physiology, 6 pilot study, ix, 101, 105, 106, 107, 108, 109 placebo, 56 planning, 77, 90, 198 platelet, 6 plausibility, 184 play, vii, 1, 33, 47, 48, 50, 54, 85, 154, 186 POMS, 150 poor, 48, 162, 163, 164, 166, 167, 176, 177 poor performance, 48, 162, 163, 164, 176, 177

246

Index

population, ix, x, 19, 48, 50, 53, 55, 63, 64, 81, 91, 92, 93, 95, 96, 99, 100, 158, 164, 169, 177, 183, 184, 186, 190, 193, 202 population density, 92 Positive and Negative Affect Schedule, ix, 102, 109, 112, 143 positive behaviors, 220 positive correlation, 56, 97 positive emotions, ix, 34, 40, 139, 146, 147, 152, 209 positive mood, 196, 197, 198, 200, 211 positive relation, 198 positive relationship, 198 postgraduate study, 105 posttraumatic stress, x, 140, 142, 145, 146, 147, 149, 152, 153, 154, 156 post-traumatic stress, 54 post-traumatic stress, 156 posttraumatic stress disorder, 142, 156 post-traumatic stress disorder, 54 post-traumatic stress disorder (PTSD), 54, 143, 148, 149, 156 poverty, 69 power, 8, 10, 13, 32, 77, 91, 126 pragmatic, 30 pre-adolescents, ix, 102, 106 prediction, 65, 90, 91, 100, 125, 192 predictors, 55, 65, 85, 87, 88, 89, 91, 93, 158, 207 pre-existing, 31, 68, 78, 79 pregnancy, viii, 67, 68, 69, 70, 71, 73, 74, 75, 76, 77, 78, 79, 80, 81 pregnant, viii, 67, 70, 73, 74, 75, 76, 77, 78, 79 pregnant women, 73, 79 preparation, iv, vii, 163, 164, 167, 177 pressure, 2, 4, 7, 8, 31, 33, 40, 41, 42, 44, 45, 96, 97, 98, 143, 199, 219, 229 prevention, 31, 36, 50, 85, 91, 93, 96, 125, 191 preventive, 5, 87, 91, 185, 190 primacy, ix, 101, 102, 104, 105, 106, 124, 125, 126, 136 primary care, 155, 157, 158, 191 primary school, 162 principal component analysis, 111, 114, 119, 122 principle, 102 prior knowledge, 167 priorities, vii, 192 prisoners, 155 privacy, 27 probability, 30, 109, 190, 215 problem drinking, 100 problem solving, 197 problem-focused coping, 198, 199 problem-solving, 26, 32 procedures, 8, 10, 20, 73, 79, 80, 144

productivity, 184, 192 profanity, 25, 29 profession, viii, 95, 96, 97, 100 professional development, 201 professions, 95, 96 profile of mood states, 148, 157, 215 program, ix, 2, 18, 31, 34, 35, 99, 100, 101, 104, 105, 126, 158, 172, 176 progressive, 126 promax rotation, 110, 111, 114, 117, 119, 122 promote, x, 35, 46, 140, 142, 147, 190, 197 property, 21, 25, 32, 35 proposition, 102, 105 prosocial, x, 140, 147 prostate, 155, 158 prostate cancer, 155, 158 protection, 90, 104, 108, 144 protective factors, 78, 81 protective mechanisms, 114, 120, 123, 124 protocol, 157, 186 prototype, 10, 44 provocation, 13, 18, 23, 25, 30, 34 PSS, 143, 145, 146, 147, 148 psychiatric disorder, 64, 184 psychiatric disorders, 64, 184 psychiatric illness, 193 psychoactive, 186 psychoeducational intervention, 31 psychoeducational program, 34, 35 psychological, 35, 36, 37, 52, 54, 62, 66, 68, 80, 81, 92, 104, 141, 145, 152, 153, 155, 157, 158, 159, 162, 164, 191, 212, 213, 215, 218 psychological distress, 191, 218 psychological health, 158 psychological stress, 81 psychological variables, 155 psychological well-being, 36, 141, 145, 152, 153, 157, 215 psychologist, 186 psychologists, 2, 3, 5, 11, 30, 39, 140, 185 psychology, 1, 2, 3, 4, 7, 10, 30, 31, 33, 34, 38, 43, 45, 50, 55, 58, 63, 104, 106, 109, 135, 136, 137, 144, 148, 197, 213 psychometric properties, 62, 109 psychometric quality, 148 psychopathology, 65, 81 psychophysiological, 46, 66, 156 psychophysiology, 157, 158 psychosocial, 5, 35, 40, 41, 45, 84, 93 psychosocial factors, 40, 41 psychosocial stress, 35 Psychosomatic, 40, 41, 42, 44, 65, 157, 158 psychotherapy, 32, 39, 40, 65, 155, 157, 158

Index psychotic, 35 psychotic states, 35 puberty, 189 public, viii, ix, 37, 53, 58, 59, 61, 65, 67, 84, 90, 91, 92, 101, 105, 108, 110, 121, 122, 125, 213 public health, viii, 84, 90, 91, 92 Public Health Service, 191, 196 pupil, 196 P-value, 175

Q qualitative research, 41, 43 quality of life, 5, 48, 66 questioning, 87 questionnaire, 5, 13, 14, 19, 30, 58, 65, 71, 72, 108, 109, 110, 115, 116, 121, 127, 136, 148, 169, 201, 202, 230 questionnaires, 17, 19, 116, 148, 169, 170, 202

R race, 71, 97, 219 racism, 8 radical, 104, 125 rain, 25 random, 21, 59, 185 random assignment, 59 range, 15, 17, 18, 19, 52, 72, 85, 106, 108, 126, 172, 201, 210 ratings, 59, 60, 61, 110, 111, 113, 116, 119, 122, 144 reactivity, 8, 41, 42, 44, 65, 218 reading, 22 realism, 93 reality, 104 reasoning, 68 recall, 18, 20, 44, 166, 167 receptors, 43 reciprocity, 3 recognition, 27, 126, 193 recovery, 34, 44, 68, 159 recreation, 198 recruiting, 16, 85, 103, 107, 108 recurrence, 192 reduction, 5, 31, 37, 50, 56, 61, 62, 84, 91, 145, 147, 152, 153, 154, 155, 172, 211, 230 reflection, 31, 108, 166 regression, 17, 87, 89, 186 regression analysis, 17, 87 regressions, viii, 83, 87, 90 regular, 19, 26, 186

247

regulation, 8, 9, 34, 37, 40, 41, 44, 102, 103, 104, 105, 125, 135, 136, 148, 151, 153, 156, 157, 192, 212, 214, 229, 230 rehabilitation, 42 rejection, 9, 57 relapse, 26, 36 relationship, 9, 18, 21, 26, 28, 29, 31, 32, 33, 37, 40, 41, 49, 50, 55, 56, 63, 66, 78, 84, 87, 89, 90, 92, 115, 120, 121, 124, 136, 152, 163, 165, 174, 176, 177, 186, 190, 200, 211, 215, 218 relationships, viii, 3, 6, 7, 8, 12, 13, 16, 22, 23, 25, 27, 29, 32, 33, 41, 48, 50, 56, 61, 68, 79, 83, 85, 87, 93, 174, 176, 185, 196, 204, 215, 218, 230 relaxation, 32, 36, 38, 41, 58, 120, 198, 230 relevance, 7, 15, 35, 107, 108, 142, 143, 152, 190, 211 reliability, 18, 21, 49, 71, 107, 108, 156, 192 religion, 97, 219 religions, 97 religious, 97 religious belief, 97 religious beliefs, 97 repair, 28 replacement, 126 replication, 140, 141 repression, 6 research, ix, x, xi, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 14, 15, 16, 26, 30, 31, 36, 39, 40, 41, 42, 43, 46, 48, 49, 50, 52, 56, 57, 62, 63, 66, 70, 72, 73, 78, 79, 81, 84, 85, 90, 93, 99, 101, 104, 105, 106, 115, 124, 125, 126, 127, 136, 140, 142, 143, 155, 169, 171, 174, 175, 176, 177, 178, 191, 197, 198, 199, 210, 211, 213, 217, 219 Research and Development, 191 researchers, 1, 3, 4, 5, 6, 8, 9, 11, 16, 17, 20, 30, 31, 55, 57, 62, 68, 69, 72, 78, 141, 163, 166, 168, 178 reservation, 32 resilience, 68, 69, 70, 77, 78, 79, 80, 81 resistance, 4, 7, 10, 136, 213 resolution, 21, 28, 37, 141, 147 resources, 32, 61, 80, 102, 111, 112, 114, 115, 117, 120, 121, 122, 123, 124, 126, 190, 197 response, 141, 152, 157, 158 response format, 136 responsibilities, 2, 78, 199 responsiveness, 15, 63 restaurant, 29 restaurants, 59 retardation, 188 retention, viii, 68, 79, 166 retirement, 127 Revised Test Anxiety (RTA), x, 161, 165, 169, 170, 171, 172, 177, 178

Index

248

rewards, 9, 10 rheumatic, 141 risk, vii, viii, x, 4, 5, 7, 16, 17, 19, 30, 31, 37, 39, 40, 41, 42, 43, 44, 46, 47, 50, 53, 55, 67, 69, 70, 76, 77, 79, 80, 81, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 100, 156, 183, 184, 188, 190, 192, 193, 196, 215 risk behaviors, 87, 91, 215 risk factors, 4, 5, 37, 39, 40, 41, 81, 100 risk perception, viii, 83, 84, 85, 86, 87, 89, 90, 91, 92, 93 risk society, 80 risks, 19, 98, 125, 185 risk-taking, 91, 92 rivers, 16 rocky, 26 room temperature, 23 RTT, 169 rumination, 6, 7, 23, 25, 26, 31, 34, 44, 46, 142 rural, xi, 183, 189

S SAD, 49 sadness, 12, 29, 33, 44, 231 sample, ix, x, 10, 11, 14, 16, 17, 18, 19, 20, 21, 30, 33, 39, 45, 49, 50, 56, 58, 60, 62, 71, 72, 73, 77, 78, 80, 84, 85, 90, 97, 109, 110, 111, 115, 136, 139, 140, 142, 144, 148, 149, 152, 155, 159, 169, 170, 171, 185, 186, 187, 189, 190, 191, 192, 193, 194, 199, 201, 212 sample survey, 16 sampling, 172, 202 sarcasm, 24 satisfaction, 148, 156, 185 saturation, 66 school, ix, xi, 9, 15, 26, 27, 36, 53, 54, 63, 69, 72, 73, 96, 99, 100, 101, 105, 106, 108, 109, 112, 115, 118, 121, 122, 123, 124, 125, 126, 155, 158, 162, 163, 171, 179, 195, 196, 199, 201, 209, 210, 213, 218, 219, 223, 224, 225, 226, 228, 229 school management, 196 science, 2, 36, 230 scientific, 126, 136 scientific method, 136 scores, 3, 6, 9, 11, 16, 18, 19, 20, 30, 36, 52, 53, 54, 55, 56, 60, 71, 72, 73, 75, 76, 77, 86, 111, 112, 114, 115, 117, 118, 120, 123, 170, 171, 204 scripts, 92 SCS, 143 searching, 22 security, 38 selectivity, 102

self, ix, x, 10, 22, 30, 34, 46, 48, 49, 50, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 68, 69, 72, 73, 80, 81, 89, 93, 96, 102, 103, 104, 107, 108, 109, 111, 112, 114, 117, 120, 123, 124, 125, 135, 136, 139, 140, 142, 143, 146, 147, 148, 151, 152, 153, 154, 155, 156, 157, 158, 159, 173, 174, 175, 176, 178, 179, 180 self-assessment, 196 self-concept, 142 self-confidence, 33 self-consciousness, 61, 62 self-control, 10 self-efficacy, 8, 50, 64, 93, 147, 148, 151, 153, 178 self-esteem, 2, 15, 16, 36, 40, 68, 69, 80, 162 self-help, x, 140, 154, 155 self-identity, 69 self-reflection, 108 self-regulation, 8, 135, 156, 157, 214 self-report, 12, 15, 17, 30, 48, 49, 50, 55, 58, 60, 61, 65, 72, 73, 81, 89, 109, 143, 152, 154, 156, 159, 169, 170, 200, 203 self-report data, 17 self-reports, 12 sensation, 78, 140 sensation seeking, 78 sensations, vii, 47, 51, 52, 53, 54, 55, 56, 57, 58, 59, 61, 62 sensitivity, vii, 47, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58, 61, 63, 64, 65, 66, 155, 186 sensitization, 53, 84, 93 sentences, 167 separation, 90, 164 series, ix, 13, 15, 16, 59, 60, 74, 75, 79, 95, 96, 97, 98, 99, 196 serotonin, 6 services, 79, 81, 99 settlements, 9 severity, 6, 7, 51, 146, 156 sex, viii, 6, 17, 41, 84, 86, 87, 88, 89, 90, 144, 215, 229 sex differences, 215 sexism, 8 sexual abuse, 69, 80, 81 sexual activities, viii, 83, 84, 87, 89, 90, 91 sexual activity, viii, 83, 85, 86, 87, 89, 90, 91, 100 sexual behavior, viii, 83, 84, 85, 89, 90, 91, 92, 93 sexual contact, 90 sexual intercourse, 84 sexual orientation, viii, 83, 85, 87, 88, 89 sexually transmitted infections, viii, 83, 85, 87 shade, 32 shame, 2, 141 shape, 8, 102

Index short-term, 9, 140, 141, 142, 144, 145, 148, 149, 151, 153 shoulder, 3, 24 shyness, 40, 48 siblings, 9 side effects, 96, 99 sign, 57, 58 signs, 49, 57, 61 similarity, 118, 119 skills, 8, 24, 31, 32, 33, 36, 38, 70, 92, 103, 107, 111, 114, 115, 120, 124, 127, 129, 162, 166, 167, 178, 201, 228, 230 skills training, 36 skin, 12, 25 sleep, x, 29, 155, 183, 186, 188, 189, 191, 214, 216 smoking, x, 5, 6, 27, 40, 97, 98, 183, 188, 190, 191 social, vii, ix, x, xi, 1, 2, 7, 8, 12, 24, 36, 38, 40, 43, 44, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 80, 92, 98, 107, 111, 114, 117, 120, 123, 124, 125, 126, 127, 136, 139, 156, 183, 184, 186, 187, 188, 191, 195, 198, 199, 200, 202, 204, 205, 207, 210, 211, 212, 215, 218, 219, 229, 230, 231 social acceptance, 56 social anxiety, vii, 47, 48, 49, 50, 51, 54, 55, 56, 57, 59, 61, 62, 63, 64 social behavior, 63 social class, x, 183, 187, 188 social cognitive model, 50 social comparison, 107, 111, 114, 117, 120, 123, 124 social competence, 64 social construct, 12 social context, viii, 12, 47, 61, 219 social desirability, 48 social environment, 68 social evaluation, 57 social isolation, vii, 47, 48, 50, 61 social network, 202, 212 social performance, 48, 49, 50 social phobia, vii, 47, 48, 54, 55, 56, 57, 58, 62, 63, 64, 65, 66 social policy, 191 social problems, vii, 184, 218 social psychology, 43 social relations, 218 social relationships, 218 social sciences, 2, 186 social situations, vii, 47, 48, 49, 50, 56, 59, 61 social skills, 24, 36, 38, 230 social skills training, 36 social status, 231 social stress, 56, 64

249

social support, ix, xi, 2, 7, 70, 80, 139, 156, 191, 195, 198, 199, 200, 202, 204, 205, 207, 210, 211, 215, 229, 230 social withdrawal, 40, 229 socially, vii, 23, 47, 48, 49, 50, 53, 56, 57, 58, 61, 62, 97, 228 society, 80, 105, 125, 135, 164 sociocultural, 154 software, 186 solutions, 32, 80 somatic symptoms, 15, 16, 57, 155 sorting, 8 South Africa, 180 South America, 192 Spain, 183, 185, 191 species, 11 specificity, 3, 186 spectrum, 144 speculation, 11, 52 speech, 4, 56, 58 speed, 12 spiritual, 36 sports, xi, 27, 184, 186, 189 SPSS, 170, 186, 220 stability, 8, 170 stages, 2, 13, 167, 178, 212 STAI, 55, 59, 65 standard deviation, 59, 73, 145, 146, 149, 150, 151, 186, 203, 204 standards, 25, 48 statistical analysis, 170, 171 statistics, 37, 209 STD, 93 stereotypes, 212 STI, 84, 89 stigma, 190 STIs, 85, 87, 91 stomach, 16, 54, 61, 219 stomach ulcer, 219 storage, 167 strain, 96 strategies, vii, viii, ix, xi, 8, 34, 36, 42, 47, 48, 67, 68, 70, 71, 72, 74, 75, 77, 78, 79, 80, 81, 85, 91, 101, 102, 103, 104, 107, 108, 109, 110, 111, 113, 115, 116, 117, 119, 122, 123, 124, 125, 126, 136, 137, 154, 156, 157, 162, 178, 185, 195, 196, 197, 198, 199, 200, 202, 204, 205, 207, 209, 210 stratification, x, 183, 185 strength, 49, 56, 69, 154 stress, x, 2, 34, 40, 44, 46, 57, 62, 68, 69, 80, 81, 104, 136, 140, 141, 142, 145, 146, 147, 149, 152, 153, 154, 156, 157, 158, 184, 189, 190, 196, 197, 198, 199, 211, 212, 213, 214, 215, 230

Index

250

stress level, 2, 141 stressful events, 190 stressful life events, 68, 212 stressor, 157 stressors, xi, 15, 35, 51, 69, 70, 77, 195, 196, 197, 199, 200, 201, 202, 205, 207, 209, 210, 211 stress-related, 141 structural changes, 5 structural equation modeling, 178 subgroups, vii, 1, 21, 72 subjective, 13, 15, 17, 54, 56, 61, 63, 64, 66, 92, 102, 104, 105, 109, 112, 115, 124, 141, 143, 152, 153, 157, 197, 212, 214 subjective experience, 54 subjective stress, 157 subjective well-being, 102, 104, 105, 109, 112, 115, 124, 197, 212 substance abuse, ix, 2, 95, 96, 99, 100 substance use, 96, 99, 193 substances, 16, 99, 190 SUDS, 59, 60, 61 suffering, 141, 184, 185, 189 suicidal, 80, 197 suicidal behavior, 197 suicide, x, 7, 29, 43, 81, 183, 184, 188, 190, 191 suppression, 5, 6, 7, 25, 31, 43, 45 suppressors, 33 surprise, 12, 56 survival, 11 survivors, 80 swimmers, 215 sympathetic, 5, 28 symptom, 175, 176, 185, 189 symptoms, vii, viii, x, 5, 7, 14, 15, 16, 25, 41, 42, 45, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 61, 65, 68, 69, 71, 75, 79, 81, 139, 140, 141, 142, 144, 145, 146, 147, 148, 149, 151, 152, 153, 154, 155, 172, 174, 176, 177, 183, 185, 186, 188, 189, 191, 192, 199, 215 syndrome, 156 systematic, 20, 193 systems, 6, 12

T target population, 190, 201 targets, 9, 33 task demands, 166 teachers, 8, 121, 127, 178, 196, 199, 201, 209, 210, 211, 212, 213 teaching, 196 team members, 21 teenagers, 70

teens, 80 telephone, 24, 202 television, 9 temperament, vii, 1, 8, 16, 17, 21, 23, 25, 28, 31, 32, 38, 40, 44, 46 temperature, 23 temporal, 26 Tennessee, 1, 2, 40 tension, 15, 32, 49, 56, 59, 61, 162, 164, 172, 176, 196, 197, 198, 199, 200, 201, 202, 203, 207 test anxiety, x, 161, 162, 163, 164, 165, 166, 167, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178 Test of English as a Foreign Language, ix, 101, 105 test scores, 30 test taking skills, 166, 167 Thailand, 193 theoretical, ix, 2, 13, 36, 65, 66, 101, 102, 103, 104, 105, 106, 126, 141, 143, 169, 170, 177, 186, 214 theory, ix, 11, 12, 16, 43, 44, 46, 51, 63, 65, 77, 101, 102, 103, 104, 105, 124, 126, 135, 136, 143, 152, 153, 155, 230 therapeutic, x, 140, 190 therapists, 215 therapy, 35, 36, 41, 65, 142, 143, 156, 157, 159 thinking, 16, 24, 33, 50, 72, 90, 128, 165, 166, 172, 175, 176, 220, 223, 225, 226, 228, 229 threat, 49, 64, 102, 162, 166, 167, 190 threatening, 9, 51, 53, 61, 163 threats, 38, 196 threshold, 39, 63 time frame, 136 timing, 69 title, 4, 140 tobacco, ix, 95, 96, 97, 98, 99, 100 TOEFL, ix, 101, 105, 115, 116, 117, 118, 119, 120, 121, 122, 124, 125, 126, 132, 133 tolerance, 28, 87 trade, 230 tradition, 12 traffic, 16, 31, 37, 85 training, 32, 36, 42, 96, 185 training programs, 42 trait anxiety, 14, 15, 50, 51, 53, 55, 66, 214, 215 traits, 14, 38, 43, 68, 70 transactions, 9 transformation, 36, 124 transition, 69, 103, 105, 125, 193, 212 transition to adulthood, 193 translation, 106, 107, 109, 142, 211 transmission, viii, 39, 83, 84 transparent, 190 trauma, x, 32, 35, 68, 69, 80, 139, 140, 147, 154, 156, 158, 159, 162

Index traumatic events, ix, x, 139, 140, 151, 154, 155, 158 traumatic experiences, 140, 141, 148, 154, 157, 158 travel, 1 trend, 19, 54, 74, 75, 76, 77, 184 trial, 158 T-test, 169, 201 Turkey, 164, 217, 230 two-dimensional, 102, 164 two-way, 190

U UK, 135, 136, 137, 231 uncertainty, 184 undergraduate, vii, ix, 1, 17, 18, 48, 50, 58, 92, 95, 96, 105, 115, 116, 165, 186, 190, 198 undergraduates, 116, 166, 213 unemployment, 36 unification, 125 United States, 5, 39, 64, 69, 70, 92, 178, 179, 193 univariate, 59, 74, 75 universality, ix, 44, 101, 104, 105 universities, viii, 13, 68, 96, 105, 115, 152, 201 university students, x, xi, 13, 39, 55, 161, 183, 184, 185, 189, 190, 191, 192, 193, 217, 224, 225, 226, 228, 229, 230 unstable angina, 31 urban, viii, xi, 67, 70, 77, 93, 183, 186, 189 US dollar, 115 users, 90 Utah, 11

V vacation, 59 vaccination, 158 vaginal, viii, 84, 86, 87, 88, 90, 91 validation, 18, 45, 65, 136, 157, 170, 196, 211, 215 validity, 16, 18, 30, 109, 156, 169, 202, 215 values, 3, 34, 36, 171, 185, 186, 222, 225 variability, 51, 70, 77 variable, x, xi, 4, 35, 86, 87, 88, 140, 147, 153, 169, 174, 175, 176, 204, 217, 228 variables, viii, ix, 6, 36, 50, 54, 60, 71, 73, 74, 75, 78, 79, 83, 85, 87, 88, 89, 90, 91, 139, 140, 142, 143, 145, 146, 147, 148, 151, 152, 154, 155, 158, 162, 163, 169, 171, 172, 173, 174, 175, 176, 177, 178, 186, 201, 202, 203, 230 variance, x, 55, 77, 91, 110, 111, 114, 117, 119, 120, 122, 123, 140, 145, 146, 148, 149, 150, 151, 152, 153, 202, 203, 207 variation, 44, 90

251

vascular, 4, 38 vascular disease, 38 vessels, 5 veterans, 31 victimization, 56, 63 victims, 81 video, 49, 59 videotape, 22 vignette, 23 village, 230 violence, 3, 9, 10, 37, 42, 43, 218 violent, 10, 197, 228 Virginia, 11 virus, 156 visible, 49, 61 vision, 153 vocational, 129, 218 voice, 10, 44, 193 volatility, 23, 36 vomiting, 218 vulnerability, 16, 34, 43, 53, 80, 81, 84, 91, 92, 93, 184

W walking, 220 Washington, 11, 37, 38, 39, 44, 45, 62, 63, 95, 181, 192, 193, 230 waste, 129 water, 10, 25 weakness, xi, 153, 217, 220, 221, 222, 223, 224, 225, 226, 227, 228 weapons, vii web, viii, 73, 83, 84, 85, 86, 88, 89, 92 web-based, 73, 84, 85, 89 websites, 115 weight loss, 189 welfare, 162 well-being, 34, 36, 102, 104, 105, 109, 112, 115, 121, 124, 141, 145, 152, 153, 154, 156, 157, 196, 197, 212, 215, 218 Western culture, 12, 104 white women, 191 winter, 152 wisdom, 43 withdrawal, 23, 25, 40, 229 wives, 2 women, viii, x, xi, 2, 7, 10, 13, 14, 17, 19, 20, 31, 33, 37, 39, 40, 41, 42, 44, 46, 56, 64, 66, 67, 69, 70, 71, 73, 74, 75, 76, 77, 78, 79, 80, 81, 90, 92, 93, 156, 159, 183, 184, 189, 190, 191, 192, 193, 195, 196, 197, 198, 199, 200, 201, 203, 204, 207, 209, 210, 211, 213, 214, 215

252 words, 156 work, 127, 128, 141, 155 work environment, 209 workers, 2, 6, 213 workload, 196 workplace, 32, 213 work-related stress, 199, 211, 216 world wide web, 92 worry, 29, 52, 56, 147, 162, 172

Index writing, ix, x, 13, 18, 26, 34, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 156, 157, 158, 159

Y young adults, ix, 10, 36, 41, 91, 102, 105, 106, 126, 184, 192, 193, 194 young men, 20, 38, 184, 191, 193 young women, x, 69, 183, 184, 189 yuan, 115