Advances in Personality Assessment: Volume 10 9780805818048

Citation preview

ADVANCES IN PERSONALITY ASSESSMENT Volume 10

Edited by

James N. Butcher U niversity o f M innesota

Charles D. Spielberger U niversity o f South Florida

VD Psychology Press A

Taylor & Francis Group NEW YORK AND LONDON

First Published 1995 by Lawrence Erlbaum Associates, Inc. Published 2014 by Psychology Press 711 Third Avenue, New York, NY 10017 and by Psychology Press 27 Church Road, Hove, East Sussex, BN3 2FA Psychology Press is an imprint o f the Taylor & Francis Group, an informa business Copyright © 1995 by Lawrence Erlbaum Associates, Inc. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without perm ission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. L ibrary of Congress Cataloging-in-Publication Data

ISBN 13: 978-0-805-81804-8 (hbk)

Publisher’s Note The publisher has gone to great lengths to ensure the quality o f this reprint but points out that some imperfections in the original may be apparent.

Contents

Preface 1.

2.

An Idiographic and Nomothetic Study of Personality Description Ruth Schiller, Auke Tellegen, and Jean Evens Development of an MMPI-2 Scale to Assess the Presentation of Self in a Superlative Manner: The S Scale James N. Butcher and Kyunghee Han

v

109

25

3.

Measuring Alexithymia: Reliability, Validity, and Prevalence Wolfgang Linden, Frances Wen, and Delroy L. Paulhus

4.

Relations Between Mood and Personality: Findings From the Israeli Mood Studies Moshe Almagor and Yossef S. Ben-Porath

97

A Comparison of the Benefits of Two Therapeutic Community Treatment Regimens for Inner-City Substance Abusers Samuel Karson and Robert B. Gesumaria

109

5.

6.

MMPI-2 Measures of Substance Abuse Nathan C. Weed, James N. Butcher, and Yossef S. Ben-Porath

51

121

iii

iv

CONTENTS

7.

Measuring the Prosocial Personality Louis A. Penner, Barbara A. Fritzsche, J. Philip Craiger, and Tamara S. Freifeid

8.

Rorschach Susceptibility to Malingered Depressive Disorders in Adult Females Sherry L. Caine B ill N. Kinder, and B. Christopher Frueh

,

Author Index Subject Index

175 183

147

165

Preface

We began this Advances series in the early 1980s to facilitate the rapid dissemina­ tion of important new developments in theory and research on all aspects of personality assessment. We were impressed at that time with the extensive re­ search on test development and validation that was going on, and were concerned with the limited publication resources devoted to personality assessment. With this Advances series, we hoped to provide a publication opportunity and resource for reports of personality assessment research and / or clinical practice that might not conveniently fit in journal format because of length, focus, or content. We believe that the first nine volumes of Advances in Personality Assessment have accomplished our goal exceptionally well by highlighting new empirical and theoretical developments, providing descriptions of new scale development, and in publishing timely reviews of important research. Volume 10 continues in the same tradition as the previous volumes, with chapters devoted to scale con­ struction, theoretical interpretation, and empirical analysis. The first chapter, by Ruth Schiller, Auke Tellegen, and Jean Evens, describes both idiographic and nomothetic studies of personality. In chapter 2, James Butcher and Kyunghee Han provide a detailed description of a new MMPI-2 scale they developed for assessing “Superlative Self-presentation,” a potentially invalidating test response condition. In chapter 3, Wolfgang Linden, Frances Wen, and Delroy Paulhus review empirical approaches to measuring alexithymia. Chapter 4, by Moshe Almagor and Yossef Ben-Porath, provides a summary of recent empirical research on affectivity in Israel. An empirical evaluation of a pioneering substance abuse treatment program is reported by Samuel Karson and Robert Gesumaria in chap­ ter 5. Chapter 6, by Nathan Weed, James Butcher, and Yossef Ben-Porath,

v

Vi

PREFACE

reports the findings of an empirical comparison of several MMPI-2 scales for assessing alcohol and drug abuse problems. An approach to measuring prosocial behavior is reported in chapter 7 by Louis Penner, Barbara Fritzsche, J. Philip Craiger, and Tamara Freifeld. In the final chapter, Sherry Caine, Bill Kinder, and Christopher Frueh report the findings of a study that evaluates the detection of malingering on the Rorschach. In this, the concluding volume of our series, we sign off knowing that an important void has been filled at a time when publication opportunities in the field of personality assessment were quite limited. Since we began this series, a great deal has happened. The Journal o f Personality Assessment, the official publication of the Society for Personality Assessment (published by Lawrence Erlbaum Associates, Inc.), has substantially expanded its page allotment. Several new journals devoted to psychological assessment have also been established and others have been “reorganized” to encompass personality assessment topics. The American Psychological Association initiated publication of Psychological A s­ sessment, and expanded coverage of the personality area in the Journal o f Per­ sonality and Social Psychology. Two additional APA journals relevant to assess­ ment, Health Psychology, and Neuropsychology, were also initiated. In addition, Psychological Assessment Resources, Inc. (PAR) has established a new journal dealing with psychological assessment, and Plenum Press has expanded the scope of Behavioral Assessment to include articles dealing with personality as­ sessment and psychopathology. We close our series with a feeling of both accomplishment and a slight sense of regret now that our efforts for more than a decade are at an end. In concluding our work on this series, we feel assured that the torch has been passed on to others. Finally, we would like to express our great appreciation and deepest respect to Larry Erlbaum for his unwavering support and encouragement of this series over the years. James N. Butcher Charles D. Spielberger

1

An Idiographic and Nomothetic Study of Personality Description

Ruth S ch iller A u ke T elleg en Jean Evens

U niversity o f Minnesota

For the past several decades, trait psychologists have used lexical personality descriptors to investigate the structure of personality. A great deal of this research has converged on a dimensional model of personality known as the Big Five (Digman, 1990; Goldberg, 1990, 1993; John, 1990). Although the five-factor model is not without its critics, consensus regarding the Big Five has evolved to where some researchers advance the model as fundamentally correct and propose moving the inquiry forward to its implications and applications (e.g., McCrae & John, 1992). The widespread acceptance of five basic personality dimensions is the result of a long process of rational and empirical distillation. Initially, Cattell (1957) per­ formed a reduction of Allport and Odbert’s (1936) well-known descriptor list that resulted in 12 oblique dimensions. Others have not been able to replicate Cattell’s factors. His methodology required visual rather than objective rotations, introduc­ ing an element of subjectivity, and his results reflected errors in computation (Digman & Takemoto-Chock, 1981). John (1990) observed that it is difficult to avoid the conclusion that Cattell’s variables and factors seem to represent the traits that Cattell considered most important. Subsequent studies by Tupes and Christal (1961), Norman (1963), and Borgatta (1964) all yielded five major factors. However, because these studies drew on Cattell’s reduced set of 35 descriptors, it was not clear whether the five factors were an accurate representation of lexical personality description. Subsequently, Norman (1967) provided an updated de­ scriptor list, from which Goldberg (e .g ., 1992) selected new sets of descriptors. In other contemporary studies (e.g., Digman & Inouye, 1986; McCrae & Costa 1985, 1987), the descriptor sets were likewise selected independently of Cattell’s list. These later studies have also replicated the five-factor structure.

1

2

SCHILLER, TELLEGEN, EVENS

Despite these developments, the issue of the representativeness of the Big Five has recently been raised again. Do these dimensions indeed capture naturallanguage personality characterization? Tellegen (1993) questioned the elimina­ tion of so-called “evaluative” and “state” terms from the descriptor sets used in previous studies. He maintained that the elimination of such terms may have resulted in an incomplete variable set (i.e., a set with fewer or different person­ ality dimensions than actually represent natural-language personality descrip­ tion). Tellegen and Waller (in press) conducted a study using what they consid­ ered a truly representative set of lexical personality descriptors, including evaluative and emotional terms (the latter to be used as emotional trait descrip­ tors) from the American Heritage Dictionary. They recovered seven major fac­ tors, including two large evaluative or valence dimensions: Positive Evaluation and Negative Evaluation. Positive Evaluation appears to be a socially oriented dimension ranging from excellent (dazzling, important) to nothing special. Neg­ ative evaluation appears to be a character-oriented dimension ranging from awful (evil, destructive, deceitful, immoral) to decent. Even with a new set of descrip­ tors, four of the other five dimensions clearly resemble the Big Five. For the fifth factor, Tellegen and Waller offered Conventionality (vs. Unconventionality) as a reversed alternative to Digman’s (1990) and Goldberg’s (1990) interpretation of the factor as Intellect, and to McCrae and Costa’s (1987) interpretation of it as Openness to Experience. In another study, descriptors were generated by the subjects rather than being selected from a dictionary. Chaplin and John (unpublished data, cited in John, 1990) asked 300 college students to describe desirable and undesirable charac­ teristics of their own personalities. The 60 most frequent terms generated by these students were further analyzed in a separate sample of subjects, and five factors closely resembling the Big Five were recovered. Chaplin and John’s use of the descriptors generated by the individuals was an important advance in the study of natural-language personality description. They assembled their subjects’ descriptors into a single questionnaire, and then had a new group of subjects complete the questionnaire to derive the usual matrix of R-correlations charac­ teristic of a nomothetic design. The dimensions underlying the natural-language descriptions of self and others, such as those assembled in Chaplin and John’s study, may “represent shared personal constructs of personality . . . personperceptual schemata that are attuned to those available cues . . . of the social landscape that are relevant to the perceiver’s most important everyday social needs” (Tellegen, 1993, p. 126). If these interindividual studies are tapping into a person’s perception of personality, and if the Big Five or Big Seven dimensions recovered are a representation of how people actually think about personality, then these same dimensions should be recoverable from the personality descrip­ tions generated by a single person. To test this hypothesis, it would be necessary to examine the way in which each individual uses his or her terms to describe other people (i.e ., to employ an

1.

AN IDIOGRAPHIC AND NOM O THETIC STUDY

3

idiographic design). An idiographic study would have each subject generate his or her own descriptors, as well as use these descriptors to describe a large number of known others. Separate analyses of P-correlations could then be employed for each dataset. Only an idiographic design can actually provide access to an individual’s dimensional personality constructs. Zevon and Tellegen (1982) pointed out that idiographic studies are an important complement to nomothetic designs, and that the use of multiple P-data studies can lead to nomothetic inferences. The present investigation is based on the assumption that the generation and use of descriptors by single subjects is important, and even essential, for identifying the actual dimensional structure of people’s everyday personality descriptions. Embedded in these idiographic structures are the under­ pinnings of the nomothetic folk concepts of personality (Tellegen, 1993). The aim of this study is to explore how people, using their own words, describe other people. Will it be possible to integrate a series of idiographic studies and make nomothetic sense of them? Will five major dimensions similar to the Big Five consistently emerge in and across individual studies? Will evalua­ tive dimensions also emerge? To address these questions, 12 subjects were asked to generate their own personality descriptors and to use these descriptors in rating 100 acquaintances. Separate P-analyses were conducted on each of the 12 datasets, and 23 judges were recruited to rate the content of the factors from all 12 sets. The rating task was designed to reveal whether naive judges could identify, with any degree of regularity, representatives of the Big Five or Big Seven among the idiographic factors. If they did, then, at last, one could con­ clude that the Big Five capture important dimensional features of how individu­ als actually characterize personality differences.

METHOD AND RESULTS The 12 Idiographic Studies Subjects. Twelve subjects participated in this phase, including eight female University of Minnesota undergraduate psychology students recruited from a personality class and four friends (two female) of the first author. The participat­ ing psychology students received extra credit toward their course grade (all subjects also received a book at the conclusion of the study, but were not told about this ahead of time). Procedure. The participants were given a brief overview of the study and the tasks involved. Then each subject individually completed the study tasks at home in three steps. First, each subject made a list of 100 real-life acquaintances, identifying them by first name and initial only of last name. Acquaintances were individuals whom the subject knew well enough personally to have some opinions about

4

SCHILLER, TELLEGEN, EVENS

(thus excluding public and mass media figures). The investigator handed each subject several sheets of paper containing 100 numbered blocks, one block per acquaintance, and asked her or him to generate as many descriptive terms or short phrases as were needed to describe each acquaintance. Subjects were told that they could, but need not, repeat previously used terms to describe subse­ quent persons on their list. If a descriptive term was very unclear or complex, the investigator recommended that the subject’s think of simpler terms to describe the concept. Each subject generated 150-300 descriptors for her or his 100 acquaintances. After every subject returned the completed list of acquaintances and descriptors to the investigator, she transferred each distinct descriptor gener­ ated by each subject to a 3 x 5 card. This resulted in several stacks of cards, one per subject, with each stack containing only those descriptors generated by a given subject. Second, each subject was given her or his stack of descriptor cards and was instructed to sort the cards into groups of highly similar descriptors that could be considered interchangeable. The investigator explained that the groupings were necessary to make the task in the last step manageable. Once the groups were formed, she asked the subjects to select one to three descriptors from each group that most accurately summarized the meaning of that group. She then entered the list of these summary descriptors and the subject’s list of 100 acquaintances in the rows and columns of a large matrix, respectively. Care was taken to place somewhat dissimilar descriptors adjacent to each other, and to intermix positive and negative descriptors. Third, the investigator instructed the subjects to use the matrix of summary descriptors and acquaintances to rate each acquaintance on each descriptor using the following 4-point rating scale: (1) very inaccurate or very uncharacteristic, (2) slightly inaccurate or slightly uncharacteristic, (3) slightly accurate or slight­ ly characteristic, and (4) very accurate or very characteristic. Each subject was given 2 weeks to complete this lengthy task, and each was encouraged to rate only a small number of acquaintances in any one session. Factor Analyses. Exploratory factor analyses were carried out on the 12 idiographic datasets. Principal components were extracted from each matrix of P-correlations among descriptors, followed by normalized varimax rotations. Initially, four rotated solutions were obtained for each dataset: a solution based on the Kaiser criterion (rotation of all components with eigenvalues greater than or equal to one); a five-factor solution; a seven-factor solution (the former two were selected on the basis of previous research); and an (n + 5)-factor solution, where n equals the number of factors chosen according to the Kaiser criterion (this rotation ensured the extraction of all factors of any substance). On the basis of inspections of the four solutions for each dataset, the authors adopted the Kaiser solution as the most satisfactory across all 12 datasets. The five- and seven-factor solutions tended to eliminate some substantial factors and

1.

AN IDIOGRAPHIC AND NO M OTHETIC STUDY

TABLE 1.1 Rotated Varimax Kaiser Solution for l-Study 3

Descriptors

FI

Calm/Passive Gentle, Sensitive Patient Shy Humble Vain/Judgmental Phony Spoiled/Selfish Overbearing Cruel/Insensitive Uptight/Emotional Hypochondriac/Paranoid Confused/Troubled Sad Complainer/Moody Happy/Fun-Loving Loveable/Friendly Charming Outgoing/Gregarious A Tease Weil-Read/Smart Complex/Deep On Top of Things Sure of Self/Together Witty/Sharp Violent Macho Sneaky/”Ladies Man” Rebel/Troublemaker Irresponsible/Untrustworthy Orderly Unorganized/Sloppy Perfectionist Responsible/Dependable OutlandishAA/eird Bizarre Attention Seeker/Obnoxious Silly Conservative Red Necked/Bigoted Hard Working/Diligent

.77 .75 .75 .70 .66

-.39

F2

F3

F4

F5

F6

F7

F8

F9

-.38 .72 .67 .67 .66 .60 .84 .76 .75 .69

.39 .37

.68

.83 .82 .74 .35 .36

.68

.58

.38 -.54 .56

.82 .78 .64 .58 .48 .78 .72 .66 .65 .60 .93 -.81 .77 .35

.40

-.45

.55

.44 . 37

.43 .59 .65 .38 .37 .67 .44 .41

meaningful doublets that appeared in the other solutions. The (n + 5)-factor solution was clearly an overextraction: The additional factors generated were singlets or fragments of more meaningful, larger factors appearing in other solutions. Summed over all 12 participants, the 12 selected solutions yielded 112 intraindividual factors (hereafter referred to as I-factors). Three of these 12 solutions are presented in Tables 1.1, 1.2, and 1.3. The five highest factor loadings greater than or equal to .35 are shown for each factor in each study.

6

SCHILLER, TELLEGEN, EVENS TABLE 1.2 Rotated Varimax Kaiser Solution for l-Study 7

Descriptors

Dogmatic/Controlling Superior Attitude Rude Hosti 1e/Argu me ntative Flexible/Compliant Verbal Charismatic/Assertive Outgoing/Interesting Introverted Passive/Nonmotivated 1mmatu re/l nconsiste nt Responsible/Dependable Mature Professional Organized/Competent Loser Psychotic/Unpredictable Incompetent Hypochondriac Trustworthy Spiritual/Ethical Peaceful Dedicated/Consistent Positive Hospitable/Caring Self-Destructive Confused/Fearful Insecure Grieving Lonely/Vulnerable Wishful Creative Musical

FI

F2

-.78 -.77 -.69 -.68 .67

F3

F4

F5

F6

F8

.36 -.35 .77 .69 .68 -.61 -.60

.35 -.82 .74 .66 .62 .58

.39

-.37 .54

.36

.54

.35 .45

.57 .37

F7

.39 .52

.77 .76 .58 .52 -.43

.43 .59 .48 .45 .38 .38 .66 .47 .43

.36 .69 .55 .56 .49 .44

The Content-Rating Study To systematically assess the similarity of the I-factors to the nomothetic Big Five/Big Seven personality dimensions, the authors undertook a content-rating study. Briefly, we assembled a collection of rating stimuli in the form of descrip­ tive summaries of the I-factors and a collection of standard comparison stimuli representing the Big Five/Big Seven dimensions. Using these stimuli, raters assessed the similarities of each of the I-factors to each of the Big Five/Big Seven comparison sets.

Assem bling the 1-Factor Slips All major idiographic factors were included in the rating task, with a major factor being defined as one having at least three markers. A marker was defined as a descriptor with a factor loading of .35 or more. Under this criterion, 92

1.

AN IDIOGRAPHIC A ND NOM OTHETIC STUDY

7

TABLE 1.3 Rotated Varimax Kaiser Solution for l-Study 11

Descriptors

Unsympathetic Caring/Warm Real/Nice Not Real Friend/Ungenuine Manipulative Sociable/Talkative Reserved/Quiet Young at Heart/Energetic Fun Loving/Spontaneous High on Life/Smiley Intelligent/Worldly Powerful Businesslike Bright Achiever/Ambitious Uptight/Tense Bitchy Pushy Patient Relaxed Moralistic Dirty minded Rebelious Innocent/Naive Conservative Lazy Hard working Immature/Spoiled Sensual/Dramatic Ritzy/Elegant Puts on a Front Insecure Self-Centered/Know it All Opinionated Does His/Her Own Thing Boring/Normal Different

F1

F2

F3

F4

F5

F6

F7

F8

F9

-.86 .81 .81 -.78 -.76 .82 -.79 .72 .72 .65

.43 .71 .67 .65 .62 .58

.36 -.71 -.87 -.58 .55 .50

-.41 -.51 .58 .38

.77 -.59 -.55 .51 .43

.42 -.39 -.46

-.39 -.82 .77 -.57

-.53

.69 .55

.41 -.43 -.35

-.44 .63 .37 -.51

.72 .48 .37 .35 .55 -.49 .39

factors of the 112 yielded by the 12 idiographic studies (hereafter called I-stud­ ies) qualified as major I-factors. For the rating task, each major I-factor was represented by a separate slip of paper, an “I-factor slip,” on which the factor markers had been typed. Each I-factor slip displayed the markers with positive loadings and negative loadings under separate headings entitled “One Pole” and “Other Pole,” respectively. The I-factor slips displayed the markers in the order of the sizes of their absolute factor loadings. At most, 10 markers were included per pole. Each I-factor slip was assigned a random number to identify the I-factor in question.

8

SCHILLER, TELLEGEN, EVENS

Assem bling the Big Five!Big Seven Comparison Sets The authors assembled nine sets of selected adjectives representing each of the Big Five/Big Seven dimensions. Each dimension was represented by one set of adjectives, with the exception of Big Five Factor V. Because of the controver­ sies surrounding it (e.g., John, 1990), Big Five Factor V was represented by three different sets of adjectives, each one representing the differing interpreta­ tions previously reported as Intellect, Openness to Experience, and Conven­ tionality (Va, Vb, and Vc, respectively). We assembled our descriptor sets on the basis of inspections of several avail­ able lists of Big Five/Big Seven descriptors, including those provided by Dig­ man and Inouye (1986), Digman and Takemoto-Chock (1981), Goldberg (1992), McCrae and Costa (1985, 1987), Tellegen and Waller (Tellegen, 1993), and Tupes and Christal (1961). The nine Big Five/Big Seven comparison sets are shown in Table 1.4. For the rating task, sheets of paper were prepared showing the nine Big Five/Big Seven comparison sets, each followed by a blank space for entering the identification numbers of appropriate I-factors. As shown in Table 1.4, and consistent with the format of the I-factor slips, descriptors with positive and negative loadings were displayed under separate headings. The labels clarifying each comparison (set in parentheses in Table 1.4) were, of course, not shown to the raters.

Raters Twenty-four University of Minnesota students (19 women) recruited from an upper division personality class participated in the rating task in return for extra credit. One female subject’s ratings were subsequently discarded because she failed to comply with the instructions, leaving us with 23 usable sets of ratings.

The Rating Task Each participant rated the similarities between each of the I-factors and each of the Big Five/Big Seven personality dimensions. In structuring the task, the experimenter stressed that both the I-factor slips and the Big Five/Big Seven sets of descriptors represented dimensions spanning two contrasting poles. The ex­ perimenter pointed out that the I-factor slips needed to be aligned appropriately (which might require reversal of the poles) to maximize and meaningfully rate the similarity of the dimension shown on the slip to a given comparison dimen­ sion. She also indicated that the ratings should be based on overall dimensional meaning, rather than on single words. All raters were given the 92 I-factor slips, arranged randomly, along with the nine nomothetic Big Five/Big Seven comparison sets. The raters were asked to

1.

AN IDIOGRAPHIC AND NOM OTHETIC STUDY

TABLE 1.4 Big Five/Big Seven Comparison Sets Other Pole

One Pole

One Pole

Other Pole

(1: Extraversion)

Timid Quiet Unauthoritative Not speaking/Silent Seclusive Distant/Aloof Retiring/Reserved

Bold Talkative Dominant Gregarious Sociable Affectionate Energetic

(II: Agreeableness)

Warm Agreeable Gentle Hearted Self-Effacing Forgiving Soft-Hearted Sympathetic

(IV: Neuroticism)

(III: Conscientiousness) Carefull Well-Organized Reliable Conscientious Deliberate Neat Governed by Sound Thinking

Careless Unorderly Undependable Negligent Lazy Disorganized

(Va: Intellect) Knowledgeable Abstract Thinker Analytical Reflective Academically Oriented

Uninquisitive Unreflective Unphilosophical Not Academically Oriented

(Vc: Conventionality) Unconventional Unusual Different Liberal Radical

Conforming Conventional Conservative Adhering to Tradition Orthodox

Cold Touchy Stubborn Self-Willed Jealous Ruthless Vengeful

Calm At Ease Relaxed

Worrying Nervous Easily Troubled Easily Offended High Strung Envious/Jealous

(Vb: Openness to Experience) Curious Imaginative Creative Broad Interests Original Open to Experiences

(VI: Positive Evaluation) Outstanding First rate Excellent Exceptional Special Lofty Refined

(VII: Negative Evaluation) Decent Fair Good Ethical Upstanding

Unimaginative Not Curious Narrow Interests Prefers Routine

Depraved Evil Immoral Deceitful Detestable Lousy Cruel Destructive Mentally Imbalanced

Note. Category titles shown in parentheses were not shown to the judges.

Ordinary Run-of-the-Mill Nothing Special Everyday

10

SCHILLER, TELLEGEN, EVENS

proceed as follows. They were to compare the content of a given I-factor slip with each comparison set before proceeding with the next slip. They were to enter the identification number of the I-factor slip under a particular comparison set if the idiographic factor in question bore “some resemblance” to the compari­ son set. They were to add a star (*) behind the identification number if the similarity between the I-factor slip and the comparison set was rated as substan­ tial. In subsequent analyses, the unstarred and starred entries were assigned similarity scores of 1 and 2, respectively. If the I-factor slip in question had not been entered in the space provided under a specific comparison set, it was assigned a similarity rating of 0. Thus, each individual rater’s comparisons of a given I-factor with the nine comparison sets produced nine similarity ratings potentially ranging from 0 to 2 for that factor. The raters were also asked to assign to a 10th category any idiographic factors that did not show similarity to any of the nine comparisons sets. Although such assignments would not add information to that provided by a series of zero ratings, this residual category served to remind the raters that a given idiographic factor did not have to resemble any of the Big Five/Big Seven dimensions.

Analysis o f the Content Ratings The 23 ratings for each I-factor on each of the nine Big Five/Big Seven comparison sets were averaged, and these average ratings were compiled in a table labeled the Composite Matrix. To estimate the reliability of these aggre­ gated ratings, the intercorrelations among the 23 ratings for each comparison set were computed, averaged, and adjusted by the Spearm an-Brown formula. The resulting reliabilities ranged from .93 to .97, with the exception of a reliability of .85 for Positive Evaluation. We used the Composite Matrix of average ratings to evaluate the distinctive­ ness of each of the Big Five/Big Seven dimensions for each subject’s set of I-factors. In each dataset, the highest rating assigned to a given factor on a particular Big Five/Big Seven dimension, X, was compared with the secondhighest rating for the same factor on another dimension, Y. If the difference between the highest and second-highest rating exceeded .50 (our arbitrary, but reasonable, threshold value), then the I-factor in question was considered to have a strongly distinctive rating on dimension X. For example, of all the I-factors generated from the dataset of Subject 3, the seventh one received the highest composite rating for Conscientiousness— namely, 1.78. The next-highest com­ posite rating for the same I-factor on a second comparison set (Intellect) was .04. Because the difference between these two ratings exceeded .50, we concluded that the seventh I-factor in this subject’s dataset received a strongly distinctive rating for the Conscientiousness dimension (the distinctiveness value was 1.72). Strongly distinctive exemplars of the Big Five/Big Seven dimensions are shown in Table 1.5. Absent from Table 1.5 is a factor resembling Positive Evaluation which did not emerge as weakly or strongly distinctive in any of the 12 I-studies.

1.

AN IDIOGRAPHIC AND NO M OTHETIC STUDY

11

TABLE 1.5 Examples of l-Factors Rated as Strongly Distinctive on Big Five/Big Seven Comparison Sets

Extraversion

(12:6* DR - 1.18b)

Verbal/Sociable Optimistic/Jovial Totally Reckless Not Shy/Passive

Agreeableness

Conscientiousness

Neuroticism

(9:2 DR = 1.26 )

(3:7 DR = 1.72)

(1:3 DR = 1.70)

Nice/Pleasant Comfortable/Easygoing Positive Humble Caretaker Not Sarcastic/Obnoxious Not Arrogant/SelfCentered

Orderly Perfectionistic Fastidious Responsible Not Unorganized Not Sloppy

Insecure Self-Conscious Scared Sad Paranoid Not Relaxed Not Content

Intellect

Openness To Experience

Conventionality

Negative Evaluation

(3:5 DR = .57)

(7:9 DR = 1.13)

(11:9 DR = .92)

(12:1 DR = .78)

Well-Read/Smart Wishful Creative Complex/Deep Witty/Sharp Musical Sure of Self/Together Not Immature/Naive Not Submissive Not easily influenced

Dishonest Boring/Normal Doesn’t Do Own Thing Filthy Minded Not Different Materialistic Asshole Not Religious Not Strong Not Brave

ax:x = I-study:factor number. ^D R = distinctiveness value.

Table 1.6 is a summary of the judged associations between each of the 92 I-factors recovered from the 12 I-studies and the nine Big Five/Big Seven com­ parison sets. When examining Table 1.6, one has to bear in mind that, in any given I-study, the same dimension may appear more than once. When a particu­ lar I-study shows two I-factors that are rated as strongly distinctive on the same dimension, the factor with the highest rating is marked with an asterisk (*), and the one with the lower rating is marked with an ampersand (&). For example, in I-Study 1, two I-factors, F3 and F5, received strongly distinctive ratings on Neuroticism. O f these two, F3 received the higher rating, and is therefore marked with an asterisk; F5 is marked with an ampersand. All values appearing for the strongly distinctive factors in Table 1.6 represent the original composite ratings assigned to each factor, rather than the distinctiveness values, so that entries are consistent throughout the table. To complement our distinctiveness analysis, we placed all ratings over .50 into three additional categories that also appear in Table 1.6. These categories are characterized in terms of the person­ ality dimensions (comparison sets) that the rated I-factors represent.

Agree .87&

Agree .91*

7

-NegEv .52

4

Extrv 1.22*

Agree 1.39*

PosEv .52

4

Openn .57

4

Consc .61

Agree 1.13

-(NegEv .61)

Agree .70

Extrv 1.39

Agree .96

Neurt 1.78*^

F3

Consc .87*

Consc 1.30*

Extrv I.04&

Consc 1.43*

Neurt .78

Extrv 1.52& Agree .74

Openn .61

4

Intel0 1.04

F2

Agree 1.43*

-(NegEv .57)'

Agree 1.26*

-Agree .74

4

NegEv 1.00

SAgree .78

4-

NegEv13 91

F1a

6

5

4

3

2

1

l-Study

XX

Neurt .87*

Extrv 1.39*

Extrv .52

Extrv .83

XXh

Agree 52

F4

-Agree .52

NegEv 1.00

Consc .61

Intel 1.26

PosEv .74

Intel 1.00*

Neurt 1.22*

Neurt 1.046&e

F5

Neurt 1.09*

Intel .65

Openn .78

Consc 1.13*

NegEv .78

NegEv 1.00*

Agree 1.13*

Convt 1.13*

F6

TABLE 1.6 Summary of Judged Associations Between l-Factors and Comparison Sets

Neurt .65

XX

Convt 1.26*

Consc .96&

Consc 1.78*

Extrv 1.65*

Consc 1.26*

F7

'

Openn1.43*

Extrv .91*

Convt .87&

f

F8

Convt 1.22*

F9

Neurt 1.43*

Extrv 1.17*

Agree 1.22&

Extrv 1.09&

Agree 1.26*

NegEv 1.22*

9

10

11

12 Neurt 1.78*

Intel .65

PosEv .65

Openn .65

* -Neurt .57

Extrv .65

Extrv 1.22*

Openn .65

Intel .91 * PosEv .78

-Agree .91

I

Neurt 1.04

-Agree .65

NegEv .74

Extrv 1.26*

Intel 1.04*

Consc .96*

NegEv .91*

Agree 1.09*

Convt .65

4

Consc .70

Exttv 1.00&

Extrv 1.48*

Consc 1.13*

Extrv 1.22*

Openn .70

PosEv .96

X) Indicates a submerged dimension.

^XX Indicates a factor that received no ratings over .50.

4

Intel 1.04

Consc 1.30*

A bbreviations: Extrv = Extraversion, Agree = Agreeableness, Consc = Conscientiousness, Neurt = Neuroticism, Intel = Intellect, Openn = Openness to Experience, Convt = Conventionality, PosEv = Positive Evaluation, and NegEv = Negative Evaluation. ^ In d ic a te s the highest strongly distinctive rating on a specific dimension in an I-Study. e& Indicates the second-highest strongly distinctive rating on a specific dim ension in an I-Study. ^Several of the I-studies generated less than nine substantial factors. 8- Indicates an inverse relation between two associated (e.g., linked) dimensions.

k'Vindicates linked dimensions.

Substantial factors are presented in order o f their magnitude in the original I-studies.

Agree .52

Agree 1.52*

-(NegEv .65)

Agree 1.30*

Neurt .61

8

Agree .57

XX

Convt .57

NegEv 1.13*

XX

XX

XX

4

-Convt .78

Openn 1.00

Convt .92*

14

SCHILLER, TELLEGEN, EVENS

7. Submerged Dimensions. A Big Five/Big Seven dimension is submerged when an I-factor received a composite rating greater than .50 on this dimension (comparison set), but the factor was rated strongly distinctive on another Big Five/Big Seven dimension. For example (see Table 1.6), the first I-factor of Subject 3 received a composite rating of 1.26 on Agreeableness and a rating of .57 for Negative Evaluation. Because the difference between these two ratings is greater than .50, the I-factor is considered a strongly distinctive representation of Agreeableness. The submerged dimension represented by this factor is Negative Evaluation. Submerged dimensions appear in parentheses under their respective distinctive dimensions in this table. 2. Linked Dimensions. Two Big Five/Big Seven dimensions are linked for a given I-factor when judges assigned ratings greater than .50 to an I-factor on two (sometimes three) dimensions, and the difference between the ratings was less than .50. They are linked because the similarity of the ratings suggests that the subject does not clearly distinguish between the dimensions in question. For example, individual I-factors were often given similar ratings greater than .50 on Agreeableness and Negative Evaluation. This seems to reflect a close association between the two dimensions in the thinking of the subjects (other possibilities are considered later). Linked dimensions are shown with a connecting arrow in Table 1.6. Notice that I-Study 5 (F2), I-Study 9 (F6), and I-Study 12 (F4) each appears to have one I-factor with three linked dimensions. 3. Weakly Distinctive Dimensions. A Big Five/Big Seven dimension is con­ sidered weakly distinctive when the highest rating an I-factor received on the dimension was greater than .50, but the difference between the highest rating and the next-highest rating (on another dimension) did not exceed .50. Weakly dis­ tinctive dimensions are identified in Table 1.6 by single values (e .g ., the value of .52 for Agreeableness in I-Study 1, Factor 4). The letters-XX were placed in Table 1.6 whenever an I-factor received no average ratings greater than .50 for any dimension. The personality dimensions represented by these I-factors were considered to be idiosyncratic.

Results o f the Content Rating's Analysis Table 1.6 reveals that Big Five/Big Seven Factors I (Surgency or Extraver­ sion), II (Agreeableness), and III (Conscientiousness) emerge with strongly dis­ tinctive ratings in 9 of the 12 I-studies, and Big Five/Big Seven Factor IV (Emotional Stability vs. Neuroticism) in 6. The Factor V interpretations of Intellect, Openness to Experience, and Conventionality are assigned strongly distinctive I-factor ratings in 2, 1, and 4 of the I-studies, respectively. Positive Evaluation does not appear to be associated with any strongly distinctive I-factor, but Negative Evaluation makes a strongly distinctive showing in four studies.

1.

AN IDIOGRAPHIC AND NO M O THETIC STUDY

15

The linked and submerged dimensions are also informative. Agreeableness and Negative Evaluation appear strongly associated in 8 of the 12 I-studies. In I-Studies 1, 2, 5, 7, and 10, they are linked; in I-Studies 3, 4, and 8, Agreeable­ ness is strongly distinctive, but Negative Evaluation is in evidence as a sub­ merged dimension. Consistent associations also appear between the dimensions representing the various interpretations of Factor V, and it is noteworthy that Positive Evaluation is often linked to these interpretations— especially to the Intellect interpretation. Neuroticism appears as strongly distinctive in only 6 of the 12 I-studies. However, I-factors associated with this dimension receive weakly distinc­ tive ratings in I-Studies 3 and 8, and the dimension is linked in I-Studies 9 and 11 . As the preceding inspection of Table 1.6 indicates, the Big Five/Big Seven dimensions appear in many of the individual datasets. If we simplify our summa­ ry by using a rating that exceeds .50 for a particular dimension as a criterion, we find that every subject’s dataset contains at least one I-factor representing Agree­ ableness, that 11 idiographic datasets contain factors with a rating above .50 on Extraversion, and that both Conscientiousness and Neuroticism appear in 10 I-studies. This suggests that the vast majority of our subjects individually rated their acquaintances in terms similar to the first four of the Big Five dimensions. According to the judges, the other dimensions are apparently not as salient. Some subjects contributed a larger number of Big Five/Big Seven-like factors than did others (e.g., Subject 4 contributed I-factors with distinctive ratings on only two different Big Five/Big Seven dimensions, whereas Subjects 3 ,7 ,8 , and 11 each contributed five). Different subjects also linked certain Big Five/Big Seven dimensions in different ways. For example, in Study 11, one factor re­ ceived high ratings on both Neuroticism and Agreeableness, suggesting a con­ ceptual link between the two dimensions for this subject (major descriptors of the I-factor in question included Relaxed, Satisfied, Contented, Friendly, Loveable, and Mature vs. Uptight, Tense, Bitchy, Insecure, and Inconsiderate). However, for Subject 9, Neuroticism appeared linked with Extraversion, indicating that this subject associated anxious behavior with introverted, rather than with dis­ agreeable, behavior (the I-factor descriptors include Confident, Poised, Strong, Tough, and Positive vs. Dependent, Weak, Scared, Angry, Anxious, Cornplainer, and Defensive). Seven substantial, but apparently idiosyncratic, factors appear in the data as well (there may also be a number of smaller unique factors that were not an­ alyzed). Although these factors were not rated as resembling any of the Big Five/Big Seven personality dimensions, each appears to hold substantial mean­ ing for the subject who generated it. These seven factors are shown in Table 1.7. As a final step in our analysis of idiosyncrasy, we took a closer look at those datasets in which judges failed to discern a representation of one of the first four dimensions.

l-Study 6: Factor 7

Mothering Controlling Blaming

l-Study 2: Factor 4

Childish/Independent Undisciplined Unintelligent Immature/Silly Deceitful Fakey Selfish/Hedonistic Not Needy/Depressed Not Insecure/ Self-Conscious Not Critical/Rude Trustworthy Discriminating Social Not Unpredictable Not Incompetent Not Hypochondriac Not Rude

l-Study 7: Factor 4

Frugal Nosy Argumentative Direct

l-Study 8: Factor 7

TABLE 1.7 Idiosyncratic Factors

A Romantic Flirtatious Not Independent

l-Study 10: Factor 8

Sensual/Dramatic Ritzy/Elegant Not Conservative

l-Study 11: Factor 7

1.

AN IDIOGRAPHIC AND NO M OTHETIC STUDY

17

7. Absence o f Extraversion in I-Study 7. Examination of the subjects’ lists of descriptors revealed few pertaining to Extraversion of Introversion. O f the 58 self-generated descriptor categories, only 2 could be considered descriptive of Extraversion (Shy/M eek and Cheerful/Friendly). This is highly unusual because previous research indicates that descriptors representing Extraversion are among the most prolific when subjects are asked to generate their own personalitydescriptive adjectives. Shy/M eek had its highest loading on a factor that the judges gave a strongly distinctive rating for the Neuroticism category. Cheer­ ful/Friendly received its highest loading on Factor 4 of I-Study 1, which also showed salient loadings for Easy Going, Considerate, Compassionate, Devoted, and Caring versus Sick and Senile. It is easy to see why judges gave this factor somewhat elevated ratings for Agreeableness (.52) and Negative Evaluation (.44), rather than salient ratings for Extraversion. It is possible that, for this subject, Agreeableness and Extraversion were conceptually linked or fused. 2. Absence o f Conscientiousness in I-Studies 2 and 10. Factor 4 of I-Study 2 is not included among the factors listed in Table 1.6, and is shown as an idio­ syncratic factor in Table 1.7. In other words, this factor received no mean rating over .50 for any of the comparison sets. Its markers are Childish, Indecisive, Undisciplined, Unintelligent, Immature, Silly, Fakey, Selfish, Needy, De­ pressed, Insecure, and Self-Conscious. Some are clearly negative markers of Conscientiousness, but others could be interpreted as descriptors of Neuroticism or Negative Evaluation. In addition, positive Conscientiousness markers are lacking altogether. However, by far the highest loadings on Factor 4 are Child­ ish/Indecisive, Undisciplined, Unintelligent, and Immature/Silly. In Big Five terms, this I-factor is perhaps best interpreted as (low) Conscientiousness with a substantial infusion of neurotic maladjustment. I-Factor 1 of Study 10 presents a similar phenomenon. This factor received a strongly distinctive rating of 1.09 for Extraversion, with a secondary rating of .48 for Conscientiousness. The descriptors include Ambitious, Persistent, Smart, Responsible, and Clever/Quick Wit versus Not Ambitious Unmotivated/ Unambitious, Irresponsible, and Complains A Lot. Unmotivated/Unambitious, Not Ambitious, Responsible, Persistent, and Irresponsible all had loadings rang­ ing from .64 to .95, whereas the loading for Clever/Quick Wit was only .38. Thus, this factor would seem to fit the Conscientiousness category best, although it also has an Extraverted component. Actually, this factor is a good exemplar of Agentic Positive Emotionality. Agentic and Communal Positive Emotionality are the two branches of Positive Emotionality in Tellegen’s reinterpretation of Extra­ version (Tellegen & Waller, in press). Viewed in this way, the I-factor would represent a type of Extraversion after all. 3. Absence o f Neuroticism in I-Studies 4 and 5. Although Factor 4 in I-Study 4 includes several clear Neuroticism descriptors, its highest rating is

18

SCHILLER, TELLEGEN, EVENS

a weak .52 for Extraversion. Its makers include Independent/Self-Confident, Together/W holesome, Dominant, and Optimistic/Cheerful versus Insecure/ Dependent, Self-Destructive, Negative/Bitchy, Conforming/Follower, and Neu­ rotic/Uptight/Anxious. The positive pole of the factor is similar to Tellegen and Waller’s Agentic Positive Emotionality, whereas some descriptors from the nega­ tive pole are reminiscent of Neuroticism. Overall, this factor seems to represent a rather undifferentiated adjustment versus maladjustment dimension. In I-Study 5, Factors 3 and 4 were given a strongly distinctive rating of Ex­ traversion. Descriptors for I-Factor 3 include Assertive/Fearless and Ambitious/ Competitive versus Unsure and Dependent /Submissive/Timid. Although Fear­ ful and Dependent may be construed as weak Neuroticism components in this factor, it seems at least reasonable to describe the factor as a Dominant/ Ambitious expression of Agentic Positive Emotionality.

DISCUSSION The purpose of this study was to determine whether P-data generated by a series of subjects would support claims based on R-correlational data regarding major lexical personality dimensions, particularly the Big Five and Tellegen and Wal­ ler’s two evaluative dimensions. The results clearly corroborate the first four of the Big Five dimensions. According to the pooled ratings of 23 independent judges, Extraversion, Agreeableness, Conscientiousness, and Neuroticism emerged recognizably in nearly all of the 12 I-studies (see Table 1.6). Some of the exceptions are in the form of I-factors that appear to be composites of certain Big Five dimensions. Each of three proposed versions of Factor V received some support from our data. Tellegen and Waller’s Conventionality emerged as strongly distinctive in 4 of the 12 I-studies, Digm an’s Intellect in 2, and Costa and M cCrae’s Openness to Experience in 1. Table 1.6 shows several judged linkages involving these ver­ sions of Factor V, particularly between Openness and Intellect, and between Intellect and Positive Evaluation. Gliskey, Tataryn, Tobias, Kihlstrom, and McConkey (1991) empirically ex­ amined the relations between Tellegen’s Multidimensional Personality Question­ naire (MPQ) Absorption scale, subscales of Costa and M cCrae’s Openness to Experience scale of the NEO Inventory, and hypnotizability. They found that a subset of the Openness scale (measuring aspects of attention and consciousness such as aesthetic sensitivity, unusual perceptions and associations, fantasy and dreams, unconventional view of reality, and awareness of inner feelings) was related to measures of Absorption and Hypnotizability, and that another subset of the Openness scale (pertaining to intellectual curiosity and political liberalism) was relatively independent of the other variables. Gliskey et al. concluded that “present measures of openness to experience

1.

AN IDIOGRAPHIC AND NO M OTHETIC STUDY

19

may have inadvertently conflated two dimensions of personality that should be kept separate” (p. 271). The Absorption subset, which describes a propensity to be imaginatively involved in and have an openness to a wide range of emo­ tionally involving experiential states, may not have been encoded as a lexical dimension underlying everyday personality perceptions. The more lexical second subset of the Openness scale seems to depict curiosity and wide-ranging inter­ ests. These latter characteristics recall the linkage mentioned earlier between Big Five Openness and Intellect in our analysis, and are perhaps most aptly sub­ sumed under the concept of Inquiring Intellect (Fiske’s label; cited in Digman & Inouye, 1986). However, Inquiring Intellect and (low) Conventionality can be thought of as conceptually similar. Tellegen and Waller’s Conventionality in­ cludes markers such as Conservative and Adhering to Tradition versus Promoting Reform/Progressive and Revolutionary (similar to Costa and M cCrae’s Liberal Values). In summary, this study does not conclusively clarify the interpretation of Factor V, but it does lend support to an interpretation more similar to Tellegen and Waller’s Conventionality than to McCrae and Costa’s more inclusive Open­ ness. Positive Evaluation received no strongly distinctive ratings in our study. Its descriptors were intended to capture a superlative person, and judges attempting to assign I-factor slips may have found Category VI too exclusive to provide good matches. The subjects did not actually generate descriptors such as Out­ standing, Exceptional, and Refined, perhaps because they had been asked to describe their real-life acquaintances, rather than the larger than life people we often read about in newspapers or see on TV. They are an important part of our lives, but usually not in our immediate social environment. It would be informa­ tive to study the descriptors and the I-factor structures generated by subjects asked to describe a broader range of salient individuals. It is also interesting that judges rated some factors in our dataset as a combina­ tion of Positive Evaluation and Intellect. Our conjecture is that more liberally defined acquaintance sets would not only yield a robust Positive Evaluation dimension, but one that would absorb the Intellect version of Factor V. Another interesting feature of our data was the judges’ consistent pairing of Agreeableness and Negative Evaluation. Although Negative Evaluation was rated as a strongly distinctive I-factor structure in only 4 of the 12 I-studies, it emerged in combination with Agreeableness in virtually every remaining study. I-Study 6, which yielded two factors with a strongly distinctive Agreeableness rating, is the one exception. These results may reflect the difficulty of concep­ tually separating the negative pole of Agreeableness (Cold, Touchy, Stubborn, Self-Willed, Jealous, Ruthless, Vengeful) from Negative Evaluation (Depraved, Evil, Immoral, Deceitful, Detestable, Lousy). This difficulty may reflect a true lack of distinctiveness between the negative categories of Big Five Agreeable­ ness and Big Seven Negative Evaluation. In Tellegen and Waller’s Big Seven study, Negative Evaluation and Agreeableness did emerge as clearly distinctive

20

SCHILLER, TELLEGEN, EVENS

factors. In these analyses of a set of truly representative lexical descriptors, Agreeableness is more specifically a Compliant-versus-Stubbom dimension lacking the more patently evaluative markers included in Big Five Agreeable­ ness. Had we defined our Agreeableness category in terms of its Big Seven, rather than its Big Five, features, several additional I-factors might have been rated as strongly distinctive Negative Evaluation exemplars. In addition, as in the case of Positive Evaluation, subjects do not usually have acquaintances who are genuinely depraved or evil, although some fairly colorful adjectives did appear in the data and judges did recognize more instances of Negative Evaluation than Positive Evaluation. Perhaps one encounters enemies in the workplace more often than one encounters truly great persons. We would expect both evaluative dimensions to emerge as prominent dimensions when subjects are given free rein to describe their heroes, villains, and hero-villains.

CONCLUSIONS Our idiographic datasets substantially corroborate the results of previous nomothetic lexical studies, indicating the existence of several major dimensions of personality. Our analyses largely support the first four of the Big Five, and also show that individuals perceive aspects of the fifth dimension as well as evaluative aspects of personality. In addition, our study has revealed individual restructurings of these major dimensions. For example, some individuals seem to fuse Extraversion and Agreeableness, perceiving extraverted people as agreeable and vice versa (I-Study 4). Others seem to combine several potentially distinctive dimensions into one em otional-social adjustment construct (I-Study 9). Our subjects also generated what appeared to be truly idiosyncratic factors, some of which are listed in Table 1.7. Still other factors were too small, and consequently too doubtful with respect to meaning and replicability, to warrant inclusion in our analysis. Although our use of nomothetic categories to elicit judges’ ratings yielded informative results, future analyses could explore less highly structured ap­ proaches. For example, one could ask judges to sort the idiographic factor slips into nonoverlapping piles of similar items reflecting their own salient distinc­ tions. A co-occurrence matrix could then be derived, which could be cluster or factor analyzed to yield a set of content-based “megafactors.” These factors could then be examined and labeled in a manner similar to the way other factors are interpreted and labeled. Similarities of these factors to previous renditions of the Big Five or Big Seven could be identified (see Tel­ legen, 1981; Tellegen & Waller, in press, for examples of this methodology). This approach would have the advantage of being fully exploratory (i.e., the judges would not be asked to categorize factor slips according to preconceived distinctions).

1.

AN IDIOGRAPHIC AND NOM OTHETIC STUDY

21

Regardless of whether one adopts this kind of analysis, or relies on the more structured one reported here, studies of multiple idiographic datasets are, as argued earlier, necessary for arriving at nomothetic generalizations that support or disconfirm previous claims regarding major lexical personality dimensions. A dozen or so idiographic datasets also appear sufficient to evaluate nomothetic claims regarding everyday life constructs of personality. Allport’s (1937, 1961) perspective on idiography notwithstanding, there is no inherent opposition between idiographic methodology and nomothetic substance, although there is a maximum of heuristic tension between the two. Idiographic studies have great corroborative nomothetic power precisely because idiosyncra­ tic features are given the greatest possible opportunity to overshadow nomothetic regularities. Therefore, the repeated emergence of the same salient feature in separate, independent I-studies is maximally compelling evidence of a shared structure— of nomothetic order. We interpreted the nomothetic features that emerged from our particular id­ iographic datasets, which consisted of natural-language personality descriptions, as defining a set of dimensional folk concepts. However, what applied here to folk concepts of personality has applied elsewhere to scientific personality con­ cepts. The most compelling nomothetic personological insights of the past (in­ cluding some of Freud’s, Kelly’s, M aslow’s, and Rogers’ seminal ideas) were not only discovered, but also initially corroborated, by case studies conducted in an idiographic spirit. Idiographic studies seemed to provide not only the “context of discovery,” but also a crucial “context of justification.” Today’s more objective and systematic idiographic methodology encourages us to explicitly claim that systematic idiography is both the growing edge and final testing ground of nomothetic personality psychology.

SUM M ARY Research on personality dimensions employing lexical descriptors has tended to yield five major factors— the “Big Five.” Descriptor sets used in these studies were taken from the dictionary on the basis of various rational and empirical selection criteria. The Big Five emerged as nomothetic dimensions from interin­ dividual (R-) factor analyses of data collected on these descriptor sets. By con­ trast, the present exploratory study is idiographic in design. Twelve subjects generated their own set of descriptors to rate a large number of acquaintances. Exploratory intraindividual (P-) factor analyses revealed meaningful factors in each of the 12 individual datasets. Twenty-three judges rated the similarities between each of the intraindividual factors and each of several descriptor sets representing the Big Five, as well as a recent alternative to the Big Five— the Big Seven. Our results strongly support that four of the Big Five and Big Seven factors capture important aspects of how individuals represent personality differ­

22

SCHILLER, TELLEGEN, EVENS

ences. Although the findings are more mixed, the results support similar conclu­ sions regarding aspects of the fifth factor and regarding the two evaluative (or valence) dimensions of the Big Seven. We discuss possible limitations imposed by sampling acquaintances, which point to the use of alternative sampling ap­ proaches in future studies. Taken as a whole, this study demonstrates the use of idiographic studies for evaluating nomothetic claims.

REFERENCES Allport, G. W., & Odbert, H. S. (1936). Trait names: A psycho-lexical study. Psychological Mono­ graphs, 47, (No. 211). Allport, G. W. (1937). Personality: A psychological interpretation. New York: Holt. Allport, G. W. (1961). Pattern and growth o f personality. New York: Holt. Borgatta, E. F. (1964). The structure of personality characteristics. Behavioral Science, 9, 8-17. Cattell, R. B. (1957). Personality and motivation structure and measurement. Yonkers-on-Hudson, NY: World Book. Digman, J. M. (1990). Personality structure: Emergence of the Five-Factor Model. Annual Review o f Psychology, 41, 417-440. Digman, J. M., & Inouye, J. (1986). Further specification of the five robust factors of personality. Journal of Personality and Social Psychology, 50, 116-123. Digman, J. M., & Takemoto-Chock, N. K. (1981). Factors in the natural language of personality: Re-analysis, comparison, and interpretation of six major studies. Multivariate Behavioral Re­ search, 16, 149-170. Gliskey, M. L., Tataryn, D. J., Tobias, B. A., Kihlstrom, J. F ., & McConkey, K. M. (1991). Ab­ sorption, Openness to Experience, and hypnotizability. Journal o f Personality and Social Psy­ chology, 60, 263-272. Goldberg, L. R. (1990). An alternative “description of personality”: The Big-Five factor structure. Journal o f Personality and Social Psychology, 59, 1216-1229. Goldberg, L. R. (1992). The development of markers for the Big Five Factor structure. Psychologi­ cal Assessment, 4, 26-42. Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48, 26-34. John, O. P. (1990). The Big-Five factor taxonomy: Dimensions of personality in the natural lan­ guage and in questionnaires. In L. Pervin (Ed.), Handbook of personality theory and research (pp. 66-100). New York: Guilford. McCrae, R. R., & Costa, P. T. (1985). Updating Norman’s “Adequate taxonomy”: Intelligence and personality dimensions in natural language and in questionnaires. Journal o f Personality and Social Psychology, 49, 710-721. McCrae, R. R., & Costa, P. J. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52, 81-90. McCrae, R. R ., & John, O. P. (1992). An introduction to the five-factor model and its applications. Journal o f Personality, 60, 175-215. Norman, W. T. (1963). Toward an adequate taxonomy of personality attributes: Replicated factor structure in peer nomination personality ratings. Journal o f Abnormal and Social Psychology, 66, 574-583. Norman, W. T. (1967). 2,800 personality trait descriptors: Normative operating characteristics fo r a university population. Ann Arbor: University of Michigan Press.

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Tellegen, A. (1981). Practicing the two disciplines for relaxation and enlightenment: Comment on Qualls and Sheehan. Journal of Experimental Psychology: General, 110, 217-226. Tellegen, A. (1993). Folk concepts and psychological concepts of personality and personality disor­ der. Psychological Inquiry, 4, 122-130. Tellegen, A., & Waller, N. G. (in press). Exploring personality through test construction: Develop­ ment of the Multidimensional Personality Questionnaire. In S. R. Briggs & J. M. Cheek (Eds.), Personality measures: Development and evaluation (Vol. 1). Greenwich, CT: JAI. Tupes, E. C., & Christal, R. E. (1961). Recurrent personality factors based on trait ratings. Techni­ cal Report (No. 61-67, pp I-V II, 1-40). Lackland Air Force Base, TX: U.S. Air Force. Zevon, M. A., & Tellegen, A. (1982). The structure of mood change: An idiographic/nomothetic analysis. Journal of Personality and Social Psychology, 43, 111-122.

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2

Development of an M M P I-2 Scale to Assess the Presentation of Self in a Superlative Manner: The 5 Scale

J a m e s N. B utcher

University o f Minnesota K yu n g h ee Han

University o f M ississippi

Self-report personality assessment can be influenced by the perceived need of some individuals to present themselves in a favorable light. Some test takers deny minor problems or faults that most people recognize and are willing to endorse on personality scales. This overly virtuous response set produces a different pattern of MMPI scores than the typical performance of nonclinical, or “norm al,” subjects who endorse the items in a straightforward, honest manner. Psychologists conducting personnel screening of family custody evaluations— settings that have a high percentage of virtue claimants— are often faced with M M P I-2 profiles that are viewed as extremely defensive and with low informa­ tion presented through the clinical scale scores. Several strategies have been previously developed to assess overly virtuous self-presentations on the MMPI. The earliest approach— the Lie (L) scale, which is made up of 15 blatant claims of extreme virtue— was developed by Hathaway and McKinley (1940) to assess the tendency of people to lie about their adjust­ ment, following a method originally studied by Hartshorne and May (1928). The MMPI L scale was originally constructed using a rational item-selection proce­ dure to detect some individual’s tendency to portray themselves as extremely virtuous and honest. Since its development, a great deal of research has been published on the use of the L scale in assessing response distortion on the MMPI and as an indicator of the “good impression” profile. Burish and Houston (1976) reported that the L scale correlated with denial; Matarazzo (1955) found that the L scale was associated with lower levels of manifest anxiety; and Coyle and Heap (1965), studying forensic patients, concluded that some hospitalized patients were “pathologically convinced of their own perfection” (p. 729). Problems with the scale have been noted, however. One problem with this rationally derived

25

26

BUTCHER A ND HAN

scale is that the item content is made up of extremely obvious and somewhat unrealistic claims of virtue, which more sophisticated individuals might “see through” and avoid. Meehl and Hathaway (1946) reported that this scale was found to be easily distorted. Vincent, Linsz, and Greene (1966) considered the L scale, with its transparent content, most useful in detecting response distortion in unsophisticated clients. However, Butcher (1994) reported that the L scale was also elevated among college-educated airline pilot applicants. A second approach to detecting overly positive response distortion— the K scale— was developed by Meehl and Hathaway (1946). The scale involved two purposes. First, the authors wanted to identify psychiatric hospital inpatients who produce normal-range MMPI profiles, but who show evidence of actually having psychological problems. Persons responding high on the K scale are viewed as defensive or in denial of their psychopathology. Scores on the K scale are be­ lieved to reflect denial of problems and the tendency to present an overly positive social image (Dahlstrom, Welsh, & Dahlstrom, 1972). Second, Meehl and Hath­ away recommended the use of the K scale as a correction for test defensiveness in an effort to improve the discrimination of defensive clinical patients. Varying amounts of the K score were actually added to several scale scores to improve the discrimination. However, as a correction factor for defensive self-presentation, the K scale has not been well supported by research (Cronbach, 1990). Early studies by Hunt, Carp, Cass, Winder, and Kantor, (1947) and Silver and Sines (1962) found that non-ATcorrected scores worked as well as K-corrected scores in inpatient assessment. Several recent studies have reported that, as a correction factor for test defensiveness, the K scale does not perform in a uniformly suc­ cessful manner (Colby, 1989; Hunt, 1948; Wrobel & Lachar, 1982). Recently, the possibility that the K correction actually lowers external test validity has been reported (Weed, Ben-Porath, & Butcher, 1990; Weed & Han, 1992). One problem with the K scale is that it was not developed for use with noninpatient psychiatric samples (e.g., nonclinical groups such as family custo­ dy cases or applicants for employment who have a clear motivation to assert extremely good adjustment in order to present a favorable picture of themselves usually have extreme K scores). There is no research to guide practitioners to apply K in this context, or even to ensure that any K correction should be made. The K scale was not developed with samples of nonhospitalized subjects who have a known motive to deceive through asserting that they are better adjusted than “normals” usually report. Rather, it was simply assumed (because of their low scores in a psychiatric setting) that the original K samples underreported symptoms. Several other weaknesses have been noted while using the K scale in noninpa­ tient samples. The K scale has been shown to be influenced by education level; the higher the level of education, the higher the K score (Butcher, 1990). There­ fore, it is difficult to determine, on the basis of K alone, whether one is dealing

2.

ASSESSING SUPERLATIVE SELF-PRESENTATION

27

with a defensive client or someone who simply has a higher level of education. Moreover, some individuals who have motivation to present themselves in a very positive light (e.g., airline pilots) produce consistently high K scores. Butcher (1994) reported that over 87% of pilot applicants have defensive (high-AT) pro­ files. Because most of the individuals in the group have K scores in the “defen­ sive range,” the scale may be considered to have limited utility because almost all subjects exceed the threshold for identifying defensiveness. The K scale is composed of 30 items that deal with: denial of anger or loss of control, denial of worry, assertion of self-confidence, and beliefs in human goodness. Another approach to assessing test defensiveness with the original MMPI involved directly assessing malingering of positive characteristics with a scale derived from an experimental study of test takers known to be faking their responses. The Positive Malingering scale (Mp), developed by Cofer, Chance, and Judson (1949), was developed to detect individuals who attempt to present a favorable picture of themselves. They developed the scale by asking subjects to complete the MMPI three times: honestly, faking psychological disturbance, and giving the best possible impression of themselves. Cofer et al. found 34 items that detected the tendency for people to use a socially desirable response ap­ proach. They considered these items to represent common flaws that most nor­ mal individuals might acknowledge, but those trying to make the best possible impression would endorse differently. The Mp scale was not maintained in M M PI-2 because it did not contribute uniquely to the assessment of faking good, and because it contained seven items that were deleted during the MMPI revision to reduce objectionable item content (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989).

CURRENT USE OF L AND K IN DETECTING VIRTUOUS SELF-DESCRIPTION Recent research has been designed to refine the discrimination of individuals who “fake good” on personality scales. Faking good has been shown to involve different strategies (e.g., self-deceptive enhancement and impression manage­ ment; Lanyon, in press; Paulhus, 1986). Lanyon (1993) studied two strategies for faking good: excessive virtue and endorsement of superior adjustment. He re­ ported that these different response approaches could be differentiated in selfreport. The relative effectiveness of the L and K scales to detect underreporting of symptoms, along with discussion of their limitations, is described in Baer, Wet­ ter, and Berry (1992). Baer et al. concluded that the L and K scales showed a modest ability to discriminate individuals who deny problems and see themselves

28

BUTCHER AND HAN

in a favorable light. Baer et al. conducted a meta-analysis of 25 studies designed to detect underreporting of psychological problems. They found that L, K, Mp, and Sd (Social Desirability) were effective at detecting underreporting. However, they called for more research on the problem because most of the existing studies involved using normals to simulate good adjustment. They pointed out that, “The extent to which these subjects’ responses resemble those of individuals who are actually under reporting symptoms of psychopathology in a realistic situation, such as a job application, is unknown” (p. 521).

RATIONALE FOR THE PRESENT STUDY The present study was designed to explore a different approach to assessing some individuals’ tendency to proclaim the possession of extreme virtue and absence of psychopathology on the M M PI-2 item pool. Well-educated individuals, such as airline pilots, who are applying for a highly desirable job tend to approach the MMPI items with a cognitive set to convince the assessment psychologist that they have a sound mind, high responsibility, strong moral values, and great capacity to work effectively with others. In their efforts to perform well on personality evaluation, airline pilot applicants tend to deny psychological symp­ toms, disclaim moral flaws, and assert that they are responsible people who get along extremely well with others, and have the ability to compromise in interper­ sonal situations for the good of safety. In addition, they report being responsible and optimistic about the future, and they assert that they have a degree of good adjustment that most normals do not. In summary, they present themselves in a superlative manner, claiming to be more superior in terms of their mental health and morality than people in general. They claim to be devoid of any problems, and only report extremely positive views of themselves in terms of psychological adjustment. The goal of this study was to develop an empirical scale that differentiated high virtue-claiming individuals (airline flight crew applicants) from a general nonclinical sample— the M M PI-2 normative sample, composed of a large group of individuals randomly drawn from across the United States to serve as norms for the M M PI-2. It was hypothesized that an empirical item set that differenti­ ated a group of people with a clear, strong motivation to show themselves as extremely well adjusted from people in general would reflect the tendency to portray oneself in a superlative manner. The goal was to develop a scale of superlative claim assertions that could summarize the attempt to proclaim overly positive self-presentation and would not be as susceptible to conscious distortion (as scale L), moreover, the potential scale would allow for a clearer evaluation of test defensiveness than the K scale (developed on inpatients) is able to do for normals.

METHOD AND PROCEDURES Subjects The subjects used in this scale development study were 274 men applying for the position of airline pilot for a major air carrier. All of the applicants were college educated (held a 4-year degree) and had acquired the necessary flight experience to qualify for the position. All of the subjects in the initial item selection for the scale were men because most airline pilot applicants are men. Information on ethnic group membership was not available for this pilot group; however, ap­ proximately 94% of airline pilot applicants are White (Butcher, 1986). Although there were minority group applicants in the present sample, they were not identi­ fied as such in the database, making it impossible to examine possible ethnic differences. In a previous study, Butcher (1986) found no MMPI-based person­ ality or symptomatic differences between Whites and minority group members who were applying for airline pilot positions.

Testing Procedures Pilot applicants were tested individually or in small groups as part of their medical-psychological screening at preemployment. Applicants were initially briefed as to the purposes and procedures involved in the testing program. The M M PI-2s were administered by a trained test administrator who also obtained signed release of information forms. Applicants were given an M M PI-2 booklet and answer sheet on a clipboard at the beginning of the testing program; they completed their responses to the inventory over the course of the day-long testing program. Their M M PI-2 items were usually answered while they were waiting for other m edical-psychological tests, such as vision checks, treadmill stress tests, laboratory tests, and general physical exams. The M M PI-2 was adminis­ tered to the applicants as part of a test battery that included: the Wechsler Adult Intelligence Scale-Revised (W AIS-R), Bender-Gestalt Test (BGT), Wechsler Memory Scale-Revised (W M S-R), Coping Inventory for Special Situations (CISS), and a clinical interview. The only test included in the present study is the M M PI-2.

M M P I-2 Normative Study The reference sample of normal subjects employed in this study was the 1,138 men and 1,462 women who had been administered the M M PI-2 in a sample that was drawn randomly from seven regions of the United States for the MMPI restandardization project. This sample is reported in more detail in the M M PI-2 manual (Butcher et al., 1989). The subjects for the MMPI restandardization study were administered the revised MMPI in small groups. A combined sample

29

30

BUTCHER AND HAN

of men (N = 1,138) and women (N = 1,139) from the M M PI-2 normative sample, referred to as the “unisex normative sam ple,” was used in this study to develop nongender-specific norms for the S scale (see Tellegen, Butcher, & Hoeglund, 1992). Couples Study As part of the MMPI restandardization study, 822 of the randomly drawn sub­ jects were asked to bring this spouse to the testing session so he or she could participate in the study. Each of the couples was administered the MMPI Bio­ graphical Information form, Significant Life Events form, and the Dyadic Ad­ justm ent scale (Spanier & Filsinger, 1983). In addition, each husband and wife were asked to complete a set of personality ratings on their spouse on a modified version of the Katz Adjustment scales (Katz, 1968). The 110 personality and interpersonal items have been widely used in the validation of scales on the M M PI-2 (Butcher et al., 1989; Butcher, Graham, Williams, & Ben-Porath, 1990). The 110 personality variables were factor analyzed during the MMPI restandardization project to provide stable ratings of general maladjustment from the spousal ratings (Butcher et al., 1989).

RESULTS AND DISCUSSION The results of this study are presented in four parts. First, the initial scale development procedures employed in the development of the Superlative SelfPresentation scale (S ) are described, and the items are provided. Second, the factorial composition of the scale is described to provide an understanding of the item composition of the S scale. The five subscales developed for the S scale are described. Third, the T-score distributions of the S scale for both men and women separately and for a combined (unisex) sample are given. Fourth, exter­ nal validity data on the S scale are presented. Item-Selection Procedures The items for the S scale were selected in three stages. The M M PI-2 item responses of the 274 pilot applicants (a set of airline pilot applicants on whom item-response data were available) were contrasted with item-response data from 1,138 men in the M M PI-2 normative sample (see Butcher, 1994, for a fuller discussion of airline pilot M M PI-2 performance). Initially, in this analysis, 52 items were identified as significantly discriminating the two groups at the .001 level of significance, with a 25% or greater difference between the groups on response frequency for each item. Further analyses were conducted to determine if all items contributed to the homogeneity of the scale. Alpha coefficients were

2.

ASSESSING SUPERLATIVE SELF-PRESENTATION

31

computed to assess the internal consistency of the preliminary scale, and to determine the relative contribution of each item to the total score. Two items were dropped at this stage because they did not sufficiently contribute to the in­ ternal consistency of the scale (they actually lowered the scale reliability). The final 50-item S scale is listed in Table 2.1 in order of the items’ appearance in the MMPI-2 booklet, their scored direction, and their contribution to the alpha level. The final version of the S scale showed a high degree of internal consistency— alpha coefficients of .86 for men and .85 for women in the normative sample. Internal Relationships and Factor Structure of the S Scale The correlations between the S scale and other M M PI-2 scales are shown in Table 2.2. As expected, the S scale is highly positively correlated with other M M PI-2 scales that assess denial or the assertion of positive personality charac­ teristics: K in both men (.81) and women (.82); Es for men (.49) and women (.58); Re for men (.60) and women (.55); R for men (.46) and women (.40); L for men (.46) and women (.34); and O -H for men (.47) and women (.43). The S scale is negatively correlated with scales measuring symptom expression: Sc for men ( - .67) and women ( —.67); Pt for men ( —.72) and women ( - .73); CYN for men ( —.78) and women ( —.76); ANG for men ( —.71) and women ( —.73); ANX for men ( —.67) and women ( —.71); and A for men ( —.74) and women ( —.77). The pattern of correlations suggests that high scorers on S will generally be associated with low scores on scales appraising psychological symptoms, and with high scores on those scales that focus on more positive characteristics. Relationship Between S and K Given that the S and K scales were devised by different strategies to assess different manifestations of test defensiveness, it is important to evaluate their relationship. We pointed out earlier that these two scales are highly correlated (in men, r — .81; in women, r = .82). However, it should be recognized that the two scales have only nine items in common (only one of the S items overlaps with L). We conducted a further analysis of the S-scale items that are not included on the K scale to evaluate the operation of the ^-specific items. This set of 41 items, referred to as the S - K scale in Table 2.2, appears to operate as a “virtueclaiming” or problem-denial scale, although it contains no K items (see Table 2.2). This finding suggests that the K scale is not accounting for a great deal of the overly positive self-appraisal test-item content that can be found in the M M PI-2. The S - K items have high internal consistency and appear to be measuring a more consistent set of attributes than the K scale. The internal consistencies for S - K were .82 for men (N = 1,083) and .80 for women (N = 1,366), whereas the

TABLE 2.1 Internal Consistencies (Alpha) and Item-Scale Correlations (rj.s) For S Scale

Women (n = 1,353)

Men (n * 1,077)

Item

O'-s

Alpha it Item Deleted (Alpha = .86)

15(F) 50(F) 58(F) 76(F) 81 (F) 87 (F) 89 (F) 104 (F) 110 (F) 120 (F) 121 (T) 123 (F) 148 (T) 154 (F) 184 (T) 194 (T) 196 (F) 205 (F) 213 (F) 225 (F) 264 (F) 279 (F) 284 (F) 290 (F) 302 (F) 337 (F) 341 (F) 346 (F) 352 (F) 373 (F) 374 (F) 403 (F) 420 (F) 423 (F) 428 (F) 430 (F) 433 (F) 442 (F) 445 (F) 449 (F) 461 (F) 486 (F) 487 (F) 523 (F) 534 (T) 538 (F) 542 (F) 545 (F) 547 (F) 560 (T)

.18 .33 .39 .36 .42 .32 .28 .35 .43 .22 .21 .36 .16 .14 .20 .17 .45 .38 .33 .37 .17 .19 .33 .35 .43 .20 .29 .31 .36 .32 .46 .45 .31 .36 .33 .42 .36 .36 .38 .30 .34 .31 .09 .24 .16 .34 .42 .26 .24 .15

.86 .86 .86 .86 .85 .86 .86 .86 .85 .86 .86 .86 .86 .86 .86 .86 .85 .86 .86 .86 .86 .86 .86 .86 .85 .86 .86 .86 .86 .86 .85 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .86 .85 .86 .86 .86

32

n-s

Alpha if Item Deleted (Alpha = .85)

.18 .36 .35 .33 .41 .36 .19 .29 .42 .22 .17 .24 .18 .13 .21 .16 .43 .33 .32 .40 .15 .19 .39 .33 .37 .19 .32 .31 .34 .31 .43 .45 .29 .30 .32 .41 .28 .37 .34 .25 .33 .33 .11 .17 .26 .32 .38 .25 .22 .20

.85 .85 .84 .85 .84 .84 .85 .85 .84 .85 .85 .85 .85 .85 .85 .85 .84 .85 .85 .84 .85 .85 .84 .85 .84 .85 .85 .85 .85 .85 .84 .84 .85 .85 .85 .84 .85 .84 .84 .85 .85 .85 .85 .85 .85 .85 .84 .85 .85 .85

2.

ASSESSING SUPERLATIVE SELF-PRESENTATION

33

TABLE 2.2 Correlations Between S, S-K, and /^Scales with MMPi-2 Basic, Content, and Supplementary Scales for Normative Adult Sample

Women (n = 1,462)

Men (n - 1,138)

Scale

S

S-K

K

S

S-K

K

L F K Hs D Hy Pd Mf Pa Pt Sc Ma Si ANX FRS OBS DEP HEA BIZ ANG CYN A SP TPA LSE SOD FAM WRK TRT MDS APS AAS A R ES MAC DO RE MT OH

.46 -.43 .81 -.41 -.18 .29 -.41 -.12 -.06 -.72 -.67 -.46 -.39 -.67 -.34 -.69 -.59 -.39 -.49 -.71 -.78 -.69 -.76 -.52 -.28 -.64 -.69 -.62 -.49 -.41 -.40 -.74 .46 .49 -.34 .38 .60 -.74 .47

.46 -.44 .74 -.41 -.19 .25 -.44 -.13 -.10 -.71 -.67 -.46 -.38 -.65 -.34 -.68 -.59 -.40 -.47 -.71 -.73 -.66 -.75 -.51 -.29 -.64 -.69 -.62 -.50 -.42 -.43 -.73 .44 .49 -.34 .37 .59 -.73 .47

.37 -.36 1.00 -.33 -.10 .44 -.21 -.02 -.01 -.68 -.60 -.35 -.43 -.61 -.29 -.63 -.56 -.29 -.44 -.66 -.71 -.60 -.68 -.52 -.31 -.55 -.63 -.57 -.42 -.31 -.27 -.71 .46 .46 -.29 .43 .54 -.67 .48

.34 -.45 .82 -.48 -.33 .14 -.45 -.05 -.15 -.73 -.67 -.50 -.41 -.71 -.40 -.72 -.64 -.47 -.49 -.73 -.76 -.66 -.70 -.57 -.27 -.62 -.72 -.64 -.52 -.37 -.41 -.77 .40 .58 -.24 .45 .55 -.74 .43

.36 -.46 .76 -.46 -.33 .11 -.47 -.07 -.18 -.72 -.68 -.50 -.40 -.69 -.38 -.71 -.64 -.45 -.48 -.74 -.71 -.63 -.71 -.55 -.27 -.63 -.72 -.64 -.53 -.38 -.44 -.76 .39 .56 -.23 .43 .55 -.73 .44

.28 -.40 1.00 -.45 -.29 .24 -.28 -.03 -.15 -.71 -.62 -.36 -.51 -.67 -.41 -.69 -.63 -.43 -.46 -.69 -.70 -.57 -.65 -.60 -.38 -.57 -.69 -.63 -.49 -.26 -.26 -.77 .34 .57 -.15 .51 .49 -.69 .41

Note. S -K scale consists of 41 S items that do not overlap with K scale.

internal consistencies for K were .74 for men (N = 1,103) and .72 for women (N = 1,412). Comparison of S with Mp To determine the relationship between S and Mp, we conducted several analyses. First, we computed correlations between the S scale and the original Mp scale (33 items), using the data from Form AX from the MMPI restandardization study

34

BUTCHER AND HAN

(Butcher et al., 1989), to evaluate the present (shortened) Mp scale in the M M PI-2 and the original scale before items were deleted. The correlation for both men and women was .38. Next, we examined the relationship between the S scale and the surviving Mp items in M M PI-2 (26 items), and found that the correlations were actually greater for men (.47) and women (.45) than in the original scale. Thus, the deletion of the objectionable and nonworking items from Mp during the MMPI revision program actually served to increase its relationship to the construct underlying the S scale. Only six items overlap the revised Mp and S scales. When these were removed and correlations were com­ puted on nonoverlapping items, we found a correlation of .40 for men and .39 for women. Given the correlations obtained between S and Mp, the scales do not appear to be measuring exactly the same qualities. Internal Components of the S Scale To examine the major components of the S scale to determine the important content dimensions that make up the scale, a component analysis of the 50 items on S was conducted. An interitem matrix of tetrachoric correlations was com­ puted separately for men and women from the normative sample. The correla­ tions were then factor analyzed separately for each group. Using a scree test (Cattell, 1966) to determine the appropriate number of factors to extract, a fivefactor solution was chosen for both groups. This varimax-rotated, five-factor solution accounted for 67% of the variance for the men and 66.5% for the women. The five factors contained on the scale for men are shown in Table 2.3, and are described as follows: 1. Beliefs in Human Goodness— Most people will use somewhat unfair means to get ahead in life (F); Most people are honest chiefly because they are afraid of being caught (F). 2. Serenity— My hardest battles are with myself (F); I frequently find myself worrying about something (F). 3. Contentment with Life— If I could live my life over again I would not change much (T); I am satisfied with the amount of money I make (T). 4. Patience and Denial of Irritability and Anger— I get made easily and then get over it soon (F); I easily become inpatient with people (F). 5. Denial of Moral Flaws— I have enjoyed using marijuana (F); I have used alcohol excessively (F). Table 2.4 shows factor loadings for the five-factor solution in women. The factors in Table 2.4 have been reordered using the structures observed in men for comparison. The congruence coefficients computed between men and women factor loadings on Factors 1 and 5 are .97 and .91, respectively, showing

TABLE 2.3 Factor Loadings for Normative Men {N = 1,138) on the Five Factors Extracted from the 5 Scale

Factors Item 15 50 58 76 81 87 89 104 110 120 121 123 148 154 184 194 196 205 213 225 264 279 284 290 302 337 341 346 352 373 374 403 420 423 428 430 433 442 445 449 461 486 487 523 534 538 542 545 547 560 Variance %

F1

F2

F3

F4

F5

.01 .67 .85 .78 .89 .16 .15 .87 .89 .63 -.32 .50 -.21 -.19 -.03 -.17 .23 .28 .21 .61 -.24 -.05 .79 .15 .27 .00 .00 .63 .82 .37 .91 .68 .11 .52 .32 .30 .42 .22 .73 .14 .22 .18 -.19 .21 -.43 .78 .27 .27 .18 -.34

.14 -.11 .05 .15 .13 .73 .50 .05 .17 -.32 -.24 .13 -.63 .56 -.47 -.44 .54 .36 .06 .10 .15 .71 .24 .37 .31 .72 .61 -.11 .17 .37 .17 .04 .47 .08 .33 .25 .55 .50 .05 .08 .31 .06 -.05 .25 -.37 .09 .23 .48 .52 .01

.54 .38 .09 .25 .10 .38 .45 .05 .04 .22 -.20 .25 -.30 .15 -.29 -.34 .50 .53 .27 .44 .20 -.11 -.07 .57 .24 .18 .23 .19 .08 .07 .12 .43 .01 .10 .63 .45 -.11 .45 .41 .56 .41 .13 .25 -.06 -.57 .14 .58 .26 -.01 -.57

.18 .30 .31 .18 .01 .03 -.03 .14 .04 .30 -.23 .09 -.11 .16 -.23 -.25 .35 .23 .72 .26 .10 .09 -.04 .18 .66 -.04 .29 .40 .20 .18 .05 .41 .65 .58 .04 .65 .26 .36 .27 .49 .45 .57 -.18 .59 .10 .08 .38 .10 .36 -.01

.26 -.05 -.04 -.17 .24 .09 .29 -.05 .25 -.11 -.69 .65 -.16 -.05 -.57 -.44 .32 .34 .21 .12 .70 .09 .29 .43 .38 .14 .28 -.10 .04 .49 .16 -.05 .03 .31 .25 .10 .40 .02 -.14 .14 .14 .48 .77 -.15 -.21 .28 .44 .03 -.06 -.45

22.7

12.7

11.0

10.4

10.2

Note. Highest loading for each item is italicized.

35

TABLE 2.4 Factor Loadings for Normative Women (A/= 1,462) on the Five Factors Extracted from the 5 Scale

Factors Item 15 50 58 76 81 87 89 104 110 120 121 123 148 154 184 194 196 205 213 225 264 279 284 290 302 337 341 346 352 373 374 403 420 423 428 430 433 442 445 449 461 486 487 523 534 538 542 545 547 560 Variance %

F1

F2

F3

F4

F5

.10 .72 .84 .80 .87 .21 -.20 .84 .85 .46 -.23 .26 -.21 -.05 -.03 -.04 .17 .27 .24 .69 -.11 -.05 .74 .17 .27 .21 .10 .68 .76 .26 .92 .75 .19 .40 .24 .26 .28 .20 .80 .37 .32 .26 -.21 .11 -.40 .77 .27 .11 .26 -.23

.69 .26 .15 .20 .12 .68 .77 -.06 .18 .27 -.35 .12 -.62 .30 -.67 -.55 .84 .66 .60 .47 .30 .32 .11 .77 .62 .50 .61 .18 .21 .42 .15 .42 .36 .31 .65 .78 .11 .70 .23 .52 .40 .62 .33 .03 -.70 .09 .69 .61 .23 -.66

-.06 .30 .20 .04 -.14 -.06 -.04 -.17 -.13 .53 .01 -.03 .33 -.06 -.06 .02 -.08 -.01 .22 .20 .14 -.51 -.23 -.14 .09 -.60 -.09 .19 -.01 -.09 -.12 .28 -.10 .41 .11 .14 -.27 .06 .28 .08 .17 .15 .06 -.09 .12 -.16 .11 -.11 .17 -.01

-.21 .12 .11 .19 .00 .18 .03 .07 .01 .14 .00 .03 -.32 .33 -.17 -.33 .29 .20 .13 .11 -.12 .34 .15 .01 .32 .15 .39 .32 .29 .22 .04 .24 .70 .32 .05 .27 .44 .36 .01 .08 .48 .01 -.26 .72 -.05 -.04 .19 .21 .45 .13

-.11 .02 -.01 -.14 .29 .31 .10 .09 .27 -.01 -.70 .82 -.05 -.25 -.44 -.33 .15 .19 .24 .13 .76 .12 .42 .24 .23 -.18 .24 -.19 .04 .59 .17 -.04 -.04 .38 .33 .05 .59 .14 -.03 -.21 .21 .24 .79 -.06 -.25 .31 .31 -.04 -.01 -.42

4.2

7.0

21.6

23.3

Note. Highest loading for each item is italicized.

36

10.4

2.

ASSESSING SUPERLATIVE SELF-PRESENTATION

37

good convergence between sexes. For Factor 4, there is a moderate convergence between both sample, with a congruence coefficient of .77. Factors 2 and 3 of men merge into Factor 2 of women. The most notable difference between factor structures of men and those of women appeared to be Factor 3 for women, which is described as Self-Confidence/Social Poise. Some differences in factor struc­ tures were expected between men and women because the S scale was derived from the male samples. Further research is needed to explore cross-sex applica­ tion. The factor structure of the S scale for men was employed to develop the S scale subscales listed in Appendix A. Items with the highest factor loadings on each factor served as the initial composition of the five subscales. One item, “I daydream very little,” was dropped from 5*5 because it was too oriented toward airline pilot applicants’ “need to be alert,” and not central to the construct reflected by the other items in the S5 subscale— Denial of Moral Flaws. The F-score distributions for the S scale subscales are given in Appendix A. Intercorrelation of the S Subscales To evaluate the possible relationships among the S scale subscales, correlations between the subscales were computed using the M M PI-2 samples of normative men and women. The results of these analyses are given in Table 2.5. Although the subscales are intercorrelated, the scales do not contain common items, con­ tain relatively few items, and were derived through a factor analysis involving an orthogonal rotation. This finding suggests that the S subscales are measuring, or are a part of, a single underlying dimension of superlative self-reporting. F-Score Distributions Linear F-scores were calculated for the S scale on samples of both men (N = 1,138) and women (N = 1,462) from the M M PI-2 normative sample data. The S scale scores for the normative sample of men (N = 1,138) and women (N = 1,462) were employed in the development of F-scores. As with other M M PI-2

TABLE 2.5 Correlations Between S Subscales for Normative Men {n= 1,138) and Women {n= 1,462)

5 Subsca/es

S1

S1 S2 S3 S4 S5

.35 .37 .46 .23

S2

S3

S4

S5

.34

.36 .45

.44 .46 .41

.19 .22 .26 .21

.42 .43 .29

.38 .32

.25

38

BUTCHER A ND HAN TABLE 2.6 T-Score Conversions for S Scale for Men, Women, and the Combined (Unisex) Sample

Men (n = 1,138)

Raw Score

0-8 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 47 48 49 50

Women (n = 1,462)

Unisex Sample (n = 2,277)

T-Score

Raw Score

T-Score

Raw Score

T-Score

30 32 33 34 35 36 37 38 40 41 42 43 44 45 47 48 49 50 51 52 53 55 56 57 58 59 60 61 63 64 65 66 67 68 70 71 72 73 74 75 76 78 79

0-9 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 47 48 49 50

30 31 33 34 35 36 37 39 40 41 42 43 45 46 47 48 49 51 52 53 54 55 57 58 59 60 61 63 64 65 66 68 69 70 71 72 74 75 76 77 78 80

0-8 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 47 48 49 50

30 31 32 33 35 36 37 38 39 40 42 43 44 45 46 47 49 50 51 52 53 54 56 57 58 59 60 62 63 64 65 66 67 69 70 71 72 73 74 76 77 78 79

validity scales (Butcher et al., 1989), a linear F-score transformation was used in the generation of F-scores. The mean score for each sex was converted to a F-score of 50, and the standard deviation for each scale was transformed to a score of 10 for men and women separately. The F-score distributions for men and women are given in Table 2.6. A set of unisex F-scores was also computed on a subset of the M M PI-2 normative group (also given in Table 2.6; see Tellegen,

2.

39

ASSESSING SUPERLATIVE SELF-PRESENTATION Percent Frequency

10

8 e 4

2 FIG. 2.1. Linear T-score distri­ bution of S-norm ative men (N = 1,138).

O '—

20

30

40

00

60

70

6C

90

100

T- Score skewness - .114

Butcher, & Hoeglund, 1993). The skewness o f the linear T-score distributions for men (skewness = .114) and women (skewness = .036) are given in Figs. 2.1 and 2.2, respectively.

Validation Study In this section, we explore the external relationships between the S scale and rated personality characteristics based on the ratings o f couples from the M M P I2 revision project. The validity information on the S scale was obtained through the M M P I-2 normative couples study as part o f the revision o f the M M PI.

M M P I-2 Standard Scale Differences fo r Low- and High-Scoring S Responders The scores for men (see Table 2.7) and women (see Table 2.8) from the sample o f normal couples who obtain low scores on S (below a T-score o f < 4 0 ) are contrasted with those individuals who score high on S (> 6 5 T). An inspection o f

Percent Frequency 10

8

8 4

2

FIG. 2.2. Linear T-score distri­ bution o f S-norm ative wom en (N = 1,462).

0 20

30

40

00

60

T S c o re skewness - .036

70

00

90

100

40

BUTCHER AND HAN TABLE 2.7 Means, Standard Deviations, and Significance Tests for the MMPI-2 Scales for Male Normative Couple Sample

M

Scale

SD

M

Pb

ii

60.4 43.9 63.4 42.8 47.7 54.6 43.6 48.7 50.6 38.7 39.9 42.9 42.7

§

6.4 10.5 5.6 9.8 10.6 9.4 10.2 10.1 11.7 9.0 8.5 10.1 9.4

43.6 57.4 37.8 56.3 51.7 45.1 56.3 51.2 52.2 61.1 60.9 57.1 57.1

fa

S >65

S < 40 (n = 133)

L F K Hs D Hy Pd Mf Pa Pt Sc Ma Si

SD

12.6 7.5 5.7 8.0 8.1 8.7 6.5 9.0 7.5 4.5 5.0 5.8 8.0

12.8 10.0 32.1 10.4 2.9 7.3 9.9 1.8 1.1 20.6 20.0 11.4 11.4

.000 .000 .000 .000 .004 .000 .000 .072 .269 .000 .000 .000 .000

a Reported lvalues are absolute values o f t. f-tests are all two-tailed with 210 degrees o f freedom, bp < .004 and less is considered significant using the Bonferroni correction for multiple comparisons.

TABLE 2.8 Means, Standard Deviations, and Significance Tests for the MMPI-2 Scales for Female Normative Couple Sample

SD

M

Scale

46.0 57.6 37.3 56.9 56.3 47.3 56.1 49.9 53.1 62.2 60.7 56.2 59.1

a Reported t vaiues

7.9 12.0 6.0 10.8 11.6 11.8 11.1 10.1 11.9 10.2 10.0 10.1 10.0 absolute values o f t

fa

Pb

S >65 (n = 69)

S < 40 (n * 132)

L F K Hs D Hy Pd Mf Pa Pt Sc Ma Si

SD

M

54.8 43.0 65.0 41.9 45.0 52.3 43.8 52.2 50.0 38.5 38.6 41.3 42.8

9.4 3.9 5.3 6.8 4.8 7.3 5.2 9.2 7.2 4.4 4.6 6.1 5.9

7.0 9.8 32.4 10.6 7.7 3.4 8.8 1.5 2.0 18.4 17.4 11.2 12.4

.000 .000 .000 .000 .000 .001 .000 .126 .045 .000 .000 .000 .000

t - tests are all two-tailed with 1 9 9 degrees o f freedom.

b p < .004 and less is considered significant using the Bonferroni correction for multiple comparisons.

2.

ASSESSING SUPERLATIVE SELF-PRESENTATION

41

Tables 2.7 and 2.8 shows that normal men and women who score low on the 5 scale tend to have higher elevation on Hs, Pd, Pt, Sc, and Ma for men and Hs, D, Pd, Pt, Sc, and Ma for women than normals who score high on the S scale. As expected, high-5 responding is associated with low levels of symptom endorse­ ment shown by the prominent elevations on the clinical scales. External Validity of the S Scale In the next analyses, we examine the relationships between the S scale and individuals’ personalities as viewed and rated by their spouses. In the first exter­ nal validity analysis, we examine how high- and low-5 men and women are generally rated by their spouses using the Global Rating Scale. Then we examine specific behavioral correlates for 5 in men and women as described in specific ratings by their spouses. Global Rating by Spouse. The rating instruments were factor analyzed, and the results were reported in the M M PI-2 manual (Butcher et al., 1989). Six behavioral clusters were obtained in the analysis: Dysphoria, Hostility, Sociability, Impulsivity, Conformity, and Antisocial behavior. The spousal rat­ ings of low-5 and high-5 men and women are given in Table 2.9. Low-5 men are viewed by their spouses as showing more Dysphoria, Hostility, and Impulsivity than are high-5 men. The former are also viewed by their spouses as more sociable than high-5 men. Similar results were found for women in the couples sample. Specific Correlates o f S. The significant behavioral items for the 5 scale are shown in Table 2.10 for men and in Table 2.11 for women. The significant positive correlates for 5 indicate that high-5 scorers are rated by their spouses as being self-confident, pleasant, relaxed, cheerful, and cooperative (women), and as attending religious services (men). In addition, there were several significant correlates that were negative, denoting a lower level of these rated behaviors. For example, high-5 men were rated by their spouses as not arguing, not having temper problems, not easily upset or annoyed, not having physical complaints, not worrying, and so on (see Table 2.10 for a complete listing of significant correlates). For women, the 5 scale was negatively related to spousal ratings of being nervous, restless, fearful, sad, bored, moody, argumentative, suspicious, irritable, temperamental, and so on (see Table 2.11 for a complete listing of significant correlates). The presentation of self as well adjusted, responsible, and highly virtuous appears to have clear external foundation, at least as far as spousal confirmation goes in this study. High scores on 5 are associated with subjects being judged by their significant others as showing a high degree of emotional control and as experiencing low levels of anxiousness, temper problems, impulsive behavior, and other negative qualities.

ro

■P*

45.6 25.5 50.1 28.9 24.2 8.3

S 65 (n = 78)

38.2 19.4 55.7 26.0 26.0 7.5

M

5.4 6.2 4.9 3.6 2.6 3.2

ta

.000 .000 .000 .000 .011 .002

Pb

SD

8.4 4.8 6.8 4.5 3.1 0.7

SD

S >65 (n = 68)

40.7 20.3 56.8 25.4 26.5 7.3

M

Female

bp 1.0) yielded three factors: Difficulty in Expressing Feelings, Importance of Feelings, and Daydreaming/Introspection, which was said to ex­ plain 58% of the common variance. Shipko and Noviello (1984) reported a factor

3.

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61

analysis on 46 undergraduates using principal factors and varimax rotation. They extracted four factors: Three were similar to Blanchard et al. (1981), and the fourth was related to extraversion. No alpha was reported. The SS PS -R was administered by Parker, Taylor, Bagby, and Thomas (1991) to 112 male and 286 female university students. Internal consistency determined via the K uder-Richardson formula was .50. A factor analysis revealed congru­ ence with the theoretical domains of the alexithymia construct, but lacked homo­ geneity. Test-Retest. The SSPS was given twice to 46 undergraduates (Shipko & Noviello, 1984). The test-retest correlation over a 2-week interval was .76 {p < .001).

Validity Relationship With Behavioral and physiological Measures. Martin and Pihl (1986) compared 15 subjects with high alexithymia; from Martin, Pihl, and D obkin’s (1984) study came 15 subjects with low alexithymia. Frontalis electro­ myogram (EMG), digital blood volume pulse amplitude, heart rate, and stress ratings were measured during periods of stress and relative relaxation. Subjects high in alexithymic characteristics had more variable stress ratings and reported significantly greater levels of overall cognitive anxiety (p < .01). During stress and recovery periods, alexithymics also showed elevated levels of sympathetic activity and a dissociation between subjective and physiological stress responses. Papciak et al. (1985) screened 271 college students with the SSPS. Fifteen alexithymics and 15 nonalexithymics were selected, and frontalis EMG, heart rate, and blood pressure were monitored during adaptation, baseline, stress quiz, and recovery periods. Mood ratings were provided at adaptation, before and after the stress, and during recovery. Tension mood scores increased significantly before the stressor in alexithymics, and increased following the stressor in non­ alexithymics. The alexithymics had higher heart rate before and during the experiment and recovery. Although these results demonstrate that elevation in physiological arousal is associated with SSPS-measured alexithymia, they also suggest a decoupling phenomenon. No group differences were observed in EMG or blood pressure. In a study examining physiological correlates in 46 undergraduate males (Martin, Pihl, Young, Ervin, & Tourjman, 1986), alexithymia was found to be correlated with tryptophan metabolism. In addition, muscle tension and blood volume pulse amplitude distinguished between high and low alexithymics, re­ flecting an elevated level of sympathetic activity in high alexithymics. Rabavilas (1987) divided 105 patients with generalized anxiety into a high-alexithymia group (n = 19) and a low-alexithymia group (n = 19). The high alexithymics showed significantly higher levels of arousal on electrodermal measures, and

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significantly slower recovery time during novel stimulation. Subjective anxiety ratings failed to differentiate the two groups. Semistructured interviews regarding stressful life events were conducted with 20 essential hypertension outpatients and 20 cardiovascular patients without hy­ pertension (Osti, Trombini, & Magnani, 1980). Subjects were matched on demo­ graphic variables. Essential hypertension patients showed more alexithymia than controls, and had been exposed to more undesirable life events before the onset of their disorder. This pattern suggests that alexithymia may be a response to psychological stress. Relationship With Self-Report M easures. Note again that low scores on the SSPS indicate higher alexithymia. A number of researchers investigated the concurrent validity of the SSPS with other alexithymia measures and noted generally limited overlap. Krystal et al. (1986) studied 45 male veterans and found no significant correlation between SSPS and any other measure of alex­ ithymia (BIQ; MMPI Alexithymia scale; and Alexithymia Provoked Response Questionnaire, a 17-item BIQ prototype). In Paulson’s (1985) study of 53 hyper­ tensives, the SSPS was given along with the BIQ and the MMPI Alexithymia scale (M M PI-A ) within the context of the full MMPI and separately. No rela­ tionship was found between the SSPS and either administration of the M M PI-A . The t tests of independent means revealed no significant differences in the SSPS scores between the BIQ-determined alexithymia and nonalexithymia groups. The correlation between the SSPS and the BIQ revealed no relationship between the two scales (r = .02). Kleiger and Jones (1980) found a nonsignificant correlation between the BIQ and the SSPS (r = .21) in 50 respiratory patients. The SSPS failed to discriminate between alexithymics and nonalexithymics as classified by the BIQ (nonsignificant t test). The authors noted a narrow range of scores in the SSPS (range = 12-35, M = 23.4, SD = 5.41). Eighty-three mobile home owners, undergraduate students, hospital personnel, and church members com­ pleted the SSPS and the Alexithymia scale (Faryna et al., 1986). The correlation of scores from the two scales was .40. Many studies on the construct validity of the SSPS have been conducted as well. Blanchard et al. (1981) administered the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Rathus Assertiveness Scale, Bri­ quet’s Syndrome Questionnaire (BSQ), and the Psychosomatic Symptom Check­ list to 230 undergraduates. SSPS scores did not correlate with depression, asser­ tiveness, or state anxiety, but were correlated with psychosomatic symptoms (.r = - .29), the BSQ (r = - . 16), and the trait anxiety measure (r = - .21). The authors concluded that the SSPS was related to psychosomatic concerns, but was orthogonal to other psychological features. In a study with 50 gastrointestinal patients, the SSPS was negatively correlated with extraversion (p < .02), as measured by the Maudsley Personality Inventory (Fava, Baldaro, & Osti, 1980), but unrelated to neuroticism.

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Martin et al. (1986) examined SSPS correlations with the BDI, the Neuroticism scales of the Eysenck Personality Inventory, the Hysteria and Social Intro­ version and Extraversion scales of the MMPI, and trait anxiety (Endler & Okada, 1974). Social introversion showed a negative and Neuroticism a positive partial correlation with SSPS scores as did Hysteria, indicating an inverse relationship between alexithymic and neurotic characteristics. Higher alexithymia also pre­ dicted less expression of hostility in response to stress. Shipko and Noviello (1984) administered the SSPS and the MMPI to 43 undergraduates. The SSPS correlated with the Social Introversion scale (r = .32, p < .01), the Depression scale (r = .32, p < .01), and the Schizophrenia scale (r = .29, p < .02). The general trend of correlations was that alexithymia correlated with the psycho­ pathology scales except Hysteria. Bagby et al. (1988) gave 209 undergraduates the SSPS, the M M PI-A , the Toronto Alexithymia Scale (TAS), the M arlowe-Crowne social desirability scale (M -C SD S), the SUNYA revision of the Psychosomatic Symptom Checklist, and the Somatization subscale of the SC L-90R . The TAS significantly correlated with the SSPS (r = - . 19, but the M M PI-A did not (r = .05). The SSPS showed low, nonsignificant correlations with the Psychosomatic Symptom Checklist (r = —.09), Somatization (r = —.03), and Social Desirability (r = .07). In addition, the SSPS was factor analyzed, using principal factor analysis to extract three factors: (a) Difficulty Describing Feelings, (b) Daydreaming, and (c) Importance of Feelings. The three-factor rotation was not confirmed by the eigenvalues, suggesting an unstable factor structure. When the SSPS factor matrix of this study was compared to the one obtained in a previous study (see Bagby et al., 1986b), the first two factors showed good to fair congruence (.91 and .87, respectively), but the third factor showed less congruence (.76), suggesting a somewhat unstable factor structure. Using two samples of undergraduates (n = 213 and n = 217), the SSPS was not related to other self-report measures (Martin et al., 1984). In addition, separate factor analyses were carried out on each sample and showed that the factor structure of the SSPS was stable, replicable, and consistent with alex­ ithymia characteristics. Both analyses revealed similar factors: (a) Ability to Describe Feelings, (b) Daydreaming, and (c) Apathy. Correlations between the two factor structures revealed that correlations on all factors were significant at the level of p < .001. The researchers also developed a new scoring system based on nine items identified in the factor analysis. McDonald and Prkachin (1990) compared 10 alexithymic university students (SSPS scores on the full 20-item test less than 50) and a control group of 10 nonalexithymics. All subjects were videotaped during tasks designed to elicit spontaneous and posed facial expressions of emotion. They also rated the emo­ tional impact of the tasks and prototypic displays of emotion. Alexithymics did not differ in their judgment of the impact of provocative slides or in their ability to accurately label posed expressions. Alexithymics and nonalexithymics did

64

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equally well in posing emotions, with the exception of anger and happiness, which alexithymics found difficult to pose. Alexithymics did show a deficit in spontaneous displays of negative affect. Normative and Prevalence Data In a group of 129 male and 109 female undergraduates, approximately 8.2% of males and 1.8% of females scored in the alexithymia range (Blanchard et al., 1981). Males had X = 57.0 (SD = 4.48), and females had X = 59.9 (SD = 4.18). The SSPS was given to two sets of undergraduate students (Martin et al., 1984). The first set consisted of 213 students, 2.4% of which was alexithymic. The second set was composed of 217 students, with 1.4% being alexithymic. The combined total had a prevalence of 1.9% alexithymic. Papciak et al. (1985) found 1.1% of female and 3.2% of male scores in the alexithymia range in a sample of 271 undergraduates (89 females, 182 males), which is consistent with Blanchard et al. (1981). In another study with 430 undergraduates, SSPS scores ranged from 46 to 72 (M = 59.8, SD = 4.27), with a median of 60 (Martin et a l., 1984). Using a revised scoring system (range 9-36), the mean becomes 28.4 (SD = 2.7). Prevalence data are also available for a variety of clinical samples. Shipko (1982) found X = 59.4 (SD = 3.86) in 27 normals, X = 58.7 (SD = 3.83) in 15 psychosomatic patients, and X = 51.0 (SD = 4.86) in 12 somatizers. Twenty psychoneurotics and 20 inflammatory bowel disease patients could not be differ­ entiated using the SSPS or the BIQ (Taylor et al., 1981). Kleiger and Jones (1980) gave the SSPS to 50 chronic respiratory ill patients. The SSPS did not discriminate effectively between alexithymic and nonalexithymic subjects as classified by the BIQ. Twenty-seven normal controls, 15 psychosomatics, and 12 somatizers were given the SSPS (Shipko, 1982). In the control group, the mean score was 59.4 (SD = 3.86), and two (7.4%) were alexithymic. The psycho­ somatic group had a mean of 58.7 (SD = 3.83), and none was alexithymic. A t test failed to discriminate between these two groups. The somatization group had X = 51.0 (SD = 4.86), and was significantly different from controls and psycho­ somatics. Six (50%) of the somatizers were alexithymic, whereas two others were borderline alexithymic. Fava et al. (1980) gave the SSPS to a consecutive series of 150 medical patients. Twenty outpatients with essential hypertension (X = 49.50, SD — 5.43) exhibited more alexithymia traits than 20 patients with cardiovascular disease other than hypertension (X = 44.40, SD = 6.82). Sixty inpatients with dermatological disorder, divided into three diagnostic subgroups, revealed no signif­ icant difference among the groups. Fifty patients with gastrointestinal disorders showed no significant differences between three diagnostic subgroups. Osti et al. (1980) reported means of 49.5 for hypertensives and 44.4 for cardiac patients without hypertension.

3.

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65

Rabavilas (1987) reported a mean of 56.8 on a sample of 105 neurotic pa­ tients. In another study, 101 male alcoholics were given the SSPS, and the group mean was 47.2 (SD — 5.1), with 78 of the patients in the alexithymic range (Rybakowski, Ziolkowski, Zasadzka, & Brzezinski, 1988). Of the group, 42 had concomitant psychosomatic illnesses divided into five diagnostic subgroups. Patients with hypertension in = 18) were significantly more alexithymic than those without (X = 44.9). In a group of 48 nonalcoholic male subjects divided into three subgroups (n = 16) based on family history of alcoholism, significant differences were found between groups (Finn, Martin, & Pihl, 1987). The high-risk group (extensive multigenerational family histories of alcoholism in male paternal relatives) were significantly more alexithymic (X = 25.6) than the moderate-risk (alcoholic father); X = 28.9) and the low-risk (no identifiable alcoholics in the two previous family generations; X = 27.8) groups. Shipko, Alvarez, and Noviello (1983) found that of 22 combat Vietnam veterans with PTSD, 9 (41%) scored as alexithymic on the SSPS. This preva­ lence is five times the expected frequency of alexithymia in normative data. Relationship to Pathological Mechanisms. Rodenhauser, Khamis, and Faryna (1986) explored the relationship between alexithymia and handedness to assess the possibility of left-hemisphere impairment as an etiological contribu­ tion. One hundred undergraduates and faculty were twice given the SSPS, which also included an item on handedness. A higher incidence of alexithymia was found in individuals who were not right-handed (p = .041). Cole and Bakan (1985) studied the relationship between conjugate lateral eye movements as an index of right-hemisphere activation and alexithymia in 102 undergraduates. There was a significant positive correlation between eye move­ ments and alexithymia scores for all subjects (r = .20, p < .05), suggesting a modest relationship between right-hemisphere activation and alexithymia. Conclusions The data regarding the reliability of the SSPS are mixed: They show poor internal consistency, but acceptable test-retest reliability over a short interval. The SS PS -R (Sifneos, 1986) fared no better in this regard. Four studies support elevated sympathetic activity as a biological correlate of alexithymia as measured by the SSPS. The first three studies were of similar and strong experimental designs, thus adding a replication element. The first two and the fourth study also suggested a decoupling of subjective and physiological stress responses. There was evidence for a relationship between the SSPS and self-report measures of psychological constructs related to alexithymia, and numerous factor analyses suggest high content validity of the SSPS. Although the BIQ appears to be a fairly reliable and valid measure of alexithymia, and is thus the most important

66

LINDEN, W EN, PAULHUS

alexithymia instrument for concurrent validation, it does not relate to the SSPS, even though the latter was derived from BIQ items (Apfel & Sifneos, 1979; Papciak et al., 1985). The existence of at least moderate construct validity is suggested via behav­ ioral and psychological correlates. The ability of the SSPS to discriminate be­ tween clinical groups remains equivocal. Two groups of researchers failed to discriminate between groups, whereas four other groups of researchers found significant differences between psychosomatic and control groups. The SSPS discriminated hypertensive from nonhypertensive patients, but did not differenti­ ate among diagnostic subgroups of dermatological and gastrointestinal patients. The prevalence of alexithymia among undergraduates was consistently low, whereas prevalence in somatizers and alcoholics was high. The data from the prevalence studies are generally supportive of the validity of the SSPS. We conclude that the problems with validity (e.g., lack of concurrent validity) are the result of the noted underlying reliability problems (i.e., heterogeneous test items and low internal consistency).

THE MMPI ALEXITHYMIA SCALE The MMPI alexithymia scale (M M PI-A ) is a 22-item self-report subscale of the MMPI (see Kleiger & Kinsman, 1980, for a list of MMPI items comprising this subscale). Selected items were associated with different average BIQ scores (taped interviews independently rated by three judges) from the responses of 100 hospitalized patients with respiratory illness (Kleiger & Kinsman, 1980). Kleiger and Kinsman warned that the scale does not appear to have face validity because individual items appear to measure diverse behavioral and inter­ est patterns, but that a pattern of global denial is reflected in the response pattern of alexithymic individuals. They see this denial as a manifestation of an alex­ ithymia characteristic called pseudonormality. Impoverished fantasy is reflected in one item, denial of affect in two items, and preoccupation with somatic cues in two items. A score of 14 or greater indicates alexithymia. Equivalent BIQ scores can be calculated using this regression equation: BIQ score = .3405(M M PI-A score) + 1.3675. Reliability Internal Consistency. For 209 undergraduates, the internal reliability coeffi­ cient was .24 for males (n = 72) and .53 for females (n = 129), indicating poor internal consistency (Bagby et al., 1988). Mean interitem correlations were very low: for males, r = .01; for females, r = .05. This indicates disparate sets of items. Finally, a factor analysis yielded an unstable three-factor structure (Bagby, Parker, & Taylor, 1991a). In a sample of 187 female undergraduate students, the

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67

M M P I-A internal consistency score (Cronbach’s alpha) was .39 (Norton, 1989). Reanalysis of M M PI-A scale data from 618 psychiatric patients indicated Kuder-Richardson reliability coefficients .58 for inpatients and .61 for outpa­ tients (Bagby, Parker, & Taylor, 1991). Interitem correlations were virtually nonexistent (r = .06 for inpatients; r — .06 for outpatients). Factor analysis revealed poor relations of factors to the theoretical domains of the alexithymia construct. Test-Retest. For 60 respiratory ill patients over a time lapse of 0.8 -5 3 .1 months (X = 8.0, SD = 10.6), the M M PI-A showed stability over time (r = .84; Kleiger & Kinsman, 1980). Validity Relationship With Behavioral Measures. Kleiger and Dirks (1980) adminis­ tered the M M PI-A to 202 asthma patients. The criterion was a score of 12. Alexithymics were rehospitalized for twice as many days as nonalexithymics. The number of days rehospitalized was not accounted for by the objective severi­ ty of the illness. In another sample of 579 asthmatics, alexithymia was signifi­ cantly related to rehospitalization (i.e., within 6 months of discharge from hospi­ tal, 37.4% of alexithymic patients were rehospitalized, compared with 28.4% of nonalexithymics; Dirks, Robinson, & Dirks, 1981). For the rehospitalized pa­ tient group, alexithymics average 1.4 times the number of days rehospitalized compared with nonalexithymics. Across the entire sample, alexithymics aver­ aged significantly more days rehospitalized than nonalexithymic patients. In a study of 66 hypertensive outpatients, physiological measures of blood pressure, optic fundi, electrocardiogram, chest X-ray, renal studies, and patient history were gathered (Gage & Egan, 1984). Alexithymia was correlated with the severi­ ty of hypertension, but not with the severity of atherosclerosis. Relationship With Self-Report Measures. A small number of studies with student populations and a substantial number of clinical studies provided valu­ able information in this category. In 123 students (Cooper & Holmstrom, 1984), alexithymia correlated negatively with the Cornell Medial Index (r = —.25), which did not support the expectation of a positive relationship between alex­ ithymia and somatic complaints. Alexithymia was strongly associated with the repression pole (which we interpret as lack of symptoms) of the R epressionSensitization (R -S ) scale of the MMPI (r = —.58), even when the four items shared by the two subscales were deleted. However, when the presumed denial effect was controlled for, alexithymia correlated positively with somatic com­ plaints (r = .16). An analysis of sex effects indicated that this association only held true for women (r = .24); in males, r = —.06. Bagby et al. (1988) assessed a sample of 209 undergraduates; M M PI-A scores did not correlate with the TAS

68

LINDEN, W EN, PAULHUS

(r = — .06) or the SSPS (r = .05). The M M PI-A correlated in the opposite of the expected direction with the Social Desirability Inventory (r = .33) and the symptom checklist (r = —.28). Problems with concurrent validity were noted by a number of researchers. In 45 male Vietnam veterans, the M M PI-A did not correlate with the BIQ (r = .05), SSPS (r = - .3 9 ) , or APRQ (r = .01; Krystal et al., 1986). Multiple comparisons revealed no significant differences between any of the diagnostic subgroups. Demers-Desrosiers, Cohen, Catchlove, and Ramsay (1983) did not find a significant correlation between the BIQ and the M M PI-A (r = —.21) using a group of 30 pain patients. Twelve of these patients also completed the Archetypal Test With Nine Elements, and no correlation with the M M PI-A (r = —.06) was noted. There was no correlation between the M M PI-A and the BIQ in 53 hypertensives, regardless of whether the M M PI-A was given within the context of the entire MMPI or was given separately (Paulson, 1985). The M M PI-A in either administration failed to discriminate between BIQdetermined alexithymic and nonalexithymic groups. Using a sample of 56 mi­ graine headache patients, Federman and Mohns (1984) did not find a significant correlation between the BIQ and the M M PI-A (r = —.22). Of the nine alex­ ithymic subjects determined by the BIQ, only one was alexithymic according to the M M PI-A . The BIQ-determined alexithymics had a lower M M PI-A alex­ ithymia score than the BIQ-determined nonalexithymics, indicating the nondiscriminative nature of the M M PI-A . Postone (1986) gave the BIQ and M M PIA to 18 chronic pain patients, 19 psychotherapy control patients, and 9 normal control spouses. The two scales were significantly related (r = .34). Brown, Fukuhara, and Feiguine (1981) found that in 136 alexithymic and 134 nonalexithymic asthmatics, the alexithymic subgroup reported fewer affective and somatic components of respiratory distress. On a number of psychological measures, Mendelson (1982) found differences between 60 pain patients with or without alexithymia. Alexithymics had significantly lower Neuroticism and higher Lie scores on the Eysenck Personality Inventory (EPI) and a longer duration of pain symptoms. On the Illness Behavior Questionnaire, alexithymics had significantly lower hypochondriasis, affective disturbance, and irritability. They did not differ on extraversion, depression, state or trait anxiety, hostility, and direction of hostility. Feiguine and Johnson (1984) found that in 96 chronic bronchitis/emphysema patients, alexithymic subjects did not differ in their report of affective, somatic, or collateral components of respiratory distress. Papciak, Feuerstein, Belar, and Pistone (1987) also found psychological mea­ sures validating the M M PI-A on a sample of 207 outpatients referred to a behavioral medicine service. On the MMPI, alexithymics scored higher on the Lie scale and the K-Correction scale, whereas nonalexithymics scored higher on the Psychopathic Deviate scale and the Hypomania scale. The McGill Pain Questionnaire (MPQ) and a pain severity scale did not correlate significantly with alexithymia.

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Ninety-six chronic bronchitis/emphysema patients were given the MMPI and the Respiratory Illness Questionnaire (Feiguine & Jones, 1987). Several scales discriminated between the M M PI-A-determined alexithymic and nonalexithymic groups: two validity scales, L and F; three clinical scales, Psychopathic Deviance, Mania, and Social introversion; and one research scale, Welsh’s Re­ pression. Alexithymics also gave more negative evaluations of hospital staff. Data from 178 psychiatric patients who had completed the MMPI and a set of other standardized measures were used to test the construct validity of the M M PI-A (Bagby et al., 1991b). On three of four scales assessing somatic complaints, alexithymics actually achieved higher scores than non alexithymics, thus reflecting results in the opposite direction from what would have been predicted for a measure with high construct validity. Norton’s (1989) data also indicated that the M M PI-A scores were not correlated with somatic complaints, whereas M M PI-A alexithymia was associated with inhibition and introversion (r = .37 and r = .19, respectively). M M PI-A scores did correlate with scores derived from other alexithymia measures (i.e., SSPS and SAT9). Finally, Doody and Taylor (1983) attempted to seek construct validation by relating affective responses to Thematic Apperception Test (TAT) and Rorschach cards to the M M PI-A scores. Twenty neurotic and 20 psychosomatic patients (ulcerative colitis and Crohn’s disease) served as subjects. None of the Ror­ schach responses correlated with the M M PI-A scores. Affect word count on the TAT did not correlate, but high-alexithymic subjects used fewer words overall in their TAT responses than did low alexithymics (r = —.33). Normative and Prevalence Data In a sample of 209 undergraduates, males (n = 12) had a X = 8.3 (SD = 2.3) and females (n = 129) had a X = 9.4 (SD = 3.0; Bagby et al., 1988), thus suggesting a significant sex difference. Scores ranged from 3 to 21 with a X = 12.0 (SD = 4.0) for 100 respiratory illness patients (Kleiger & Kinsman, 1980). In 476 asthmatics, alexithymia was more prevalent in middle adulthood (40-59 years, 43%) and late adulthood (6 0 76 years, 60%) than in adolescents (14-19 years, 22%) and early adulthood (2 0 39 years, 19%; Feiguine, Hulihan, & Kinsman, 1982). Of 96 chronic bron­ chitis/emphysema patients, 42 subjects (44%) were alexithymic and 54 subjects (56%) were nonalexithymic (Feiguine & Johnson, 1984). Similarly, among 579 asthmatics, 33.7% were alexithymic, 47.8% were borderline alexithymic, and 18.5% were nonalexithymic (Dirks et al., 1981). Federman and Mohns (1984) found that of 50 migraine patients who com­ pleted the M M PI-A , 21 (42%) were alexithymic. The M M PI-A failed to dis­ criminate between BIQ-determined alexithymic and nonalexithymic groups. Papciak et al. (1987) found that of 207 outpatients of a behavioral medicine service, 74 were alexithymic (35.8%) and 133 were nonalexithymic (64.3%). In a sample

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of 60 chronic pain patients, 28 were alexithymic (47%) and 32 were nonalexithymic (53%; Mendelson, 1982). In another chronic pain group (Postone, 1986), 38% of pain patients, 57% of a spouse control group, and 5% of a psychotherapy control group were alexithymic. The scores of the psychotherapy group significantly differed from the pain group and the spouse control group. The age-adjusted group means are as follows: pain group (n = 18), 12.33; normal spouse control group (n = 9), 10.24; and psychotherapy control group (n = 19), 9.47. Of 66 hypertensives, 31 were alexithymic (47%), with a group mean of 15.6, and 35 were nonalexithymic (53%), with a group mean of 10.3 (Gage & Egan, 1984). Greenberg and O ’Neill (1988) found a significantly lower percentage of alexithymic individuals in a large sample of psychiatric inpatients than in sam­ ples of patients with a variety of physical disorders (e.g., migraine headaches, asthma, bronchitis/emphysema, and hypertension). In a sample of 45 veterans, the M M PI-A failed to discriminate among diag­ nostic subgroups of in- and outpatients with and without PTSD (Krystal et al., 1986). Greenberg and Dattore (1983) also failed to find that the M M PI-A discriminated among diagnostic subgroups. The prevalence of alexithymia among 181 male veterans, when broken down into subgroups, was as follows: (a) physical illness, 39%; (b) psychosomatic illness, 48%; (c) psychiatric disor­ der, 32%; and (d) well group, 51%. Conclusions The reliability and validity of the M M PI-A scale have been called into question before (Lesser, 1981). In light of the research conducted since that time, the reliability and validity of the scale are still unsatisfactory. Internal consistency was low, although test-retest stability was high. The three-factor structure was found to be unstable and explained little of the variance. The data regarding the validity of the M M PI-A in relation to self-report measures are generally nonsupportive. There is some evidence that relates the M M P I-A to personality inventories such as the EPI and the entire MMPI, but the expected positive relationship between alexithymia and somatic complaints was rarely found. The scale finds support in the rehospitalization, hypertension, and somatic and affect report data. The M M PI-A was repeatedly confounded with response sets. Furthermore, of six studies comparing the M M PI-A to other alexithymia measures, only one found a significant relation between the M M PI-A and another measure (the BIQ). The scale has remarkably little concurrent validity with other alexithymia scales. The M M PI-A fairly consistently suggested a prevalence of alexithymia for psychosomatic groups in the 40% range. However, some of the prevalence findings in nonpsychosomatic groups were puzzling. The prevalence of alex­ ithymia in a normal spouse control group was unexpectedly high, whereas the

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prevalence in a psychotherapy group was quite low. The M M PI-A consistently failed to discriminate among groups of male veterans, whereas the prevalence of alexithymia in a group of healthy veterans was unexpectedly high. Overall, the evidence suggests that this measure of alexithymia has substantial reliability and validity problems.

THE ARCHETYPAL TEST WITH NINE ELEMENTS The Archetypal Test With Nine Elements (AT9) was designed to measure one central component of alexithymia— the inhibition of symbolic functioning (Durand, 1970). It presents the patient with nine mythical items or symbols (e .g ., character, devouring monster, sword, refuge, something cyclic that turns or progresses, fall, fire, animal, and water) that he or she must use to create a drawing and answer a questionnaire. The object is to resolve anxiety elicited by certain items (monster, fall) using other items (sword, refuge, something cyclical) and a resolving agent (character and accessory items). Scoring can be done using projective techniques, which require extensive training and psychoanalytic background (PAT9) or a newer, objective, quantifiable scoring system (SAT9). The latter is scored on a continuum with a high score meaning normalcy, cutpoint 65. For details about the scoring, see Cohen, Demers-Desrosiers, and Catchlove (1983). Cohen et al. developed the SAT9, the objective scoring system, as follows: Forty-two psychosomatic patients were given the AT9, which was scored both objectively and projectively. Twelve were labeled psychofunctional because they appeared normal on the PAT9. Positive scores were assigned on the SAT9 when­ ever any of the nine symbols was included in the drawing or the story, and whenever such an included items was ascribed a meaning of a symbol. Any interaction of items also received a positive score. The final weights assigned to the item values were those that produced the best correlation between the SAT9 and the PAT9. The PAT9 was scored by only one rater, but the SAT9 score was the average of two raters. As a result, the overall correlation between the PAT9 and the SAT9 was r = .91. Reliability Internal Consistency. For 61 pain patients and 30 somatic patients, a cluster analysis was performed from results of the SAT9 (Cohen, Auld, Demers, & Catchlove, 1985). For the 11 clusters generated, KR-20 reliability coefficients ranged from .80 to .96. For the entire scale the KR-20 was .91, indicating high internal consistency. Interrater Reliability. Thirty pain patients and 12 psychofunctional (i.e., 1ow-PAT9) psychosomatic patients were rated on the SAT9 (Cohen et al., 1983). Based on the total scale for the total sample, the interrater reliability coefficient

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was .91. For the pain patient group, the coefficient was .93, but for the psycho­ functional group, the coefficient was not significant because all SAT9 scores were very high. In a sample of 187 female students, Norton (1989) found very low interrater reliability (r = .36). Although the author reports to have strictly followed the scoring instructions provided by Cohen et al. (1983), the reliability score is much lower than that of the Cohen et al. investigator group. At the very least, these discrepancies suggest that scoring consistency for the SAT9 is diffi­ cult to achieve. Validity Catchlove, Cohen, Braha, and Demers-Desrosiers (1985) found low SAT9 scores in 30 chronic pain patients; given the inverse scoring method, this finding is consistent with alexithymia. The observed nonsignificant correlations with the Hysteria, Hypochondriasis, and Depression scales of the MMPI were said to be consistent with alexithymia, and provided evidence of the discriminant validity of the test. The SAT9 also was not related to scores on the McGill Pain Question­ naire (MPQ). According to these researchers, choosing MPQ descriptors may not involve affective perception per se, but may simply indicate the degree to which patients can recognize affect when provided with the terms. Demers-Desrosiers et al. (1983) found no correlation of the SAT9 with the M M PI/A (r = —.06), but a significant correlation with the BIQ (r = —.47). No significant correlation was found between SAT9 scores and the Clarke Vocabu­ lary Scale measure of IQ in 61 pain patients and 30 medical patients (Cohen et al., 1985). SAT9 scores also did not correlate with either SSPS (r = - .0 3 ) or M M P I-A scores (r = .02; Norton, 1989). Normative and Prevalence Data For 12 psychofunctional subjects (i.e., normal based on PAT9 scores), X was 71.50 (SD = 7.32); for 30 chronic pain patients, X = 39.85 (SD = 20.94; Cohen et al., 1983). Demers-Desrosiers et al. (1983) and Catchlove et al. (1985) ap­ peared to use the same pain patient sample. In the same group of 30 chronic pain patients, Catchlove et al. found no significant differences between males and females, nor between four pain-location groups (Catchlove et al., 1985). But the SAT9 significantly discriminated between 61 pain patients and 30 minor surgery ill patients. The average SAT9 score for the surgery group was nearly twice the average SAT9 score for the pain patients (Cohen et al., 1985). Conclusions The research on the SAT9 to date is limited to studies by a small group of researchers and concentrates on pain patients and healthy populations. It may be a promising instrument for the measurement of inhibited symbolic functioning

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(albeit this is only one component of alexithymia). The internal consistency was high, but the interrater reliability was high only when the measure was used by Cohen’s group. The SAT9 correlated significantly with the BIQ, but not with the MMPI or MPQ. The nonsignificant correlation with the M M PI-A is probably a function of the questionable reliability and validity of the latter measure. The nonsignificant correlation with the IQ scale suggests that the SAT9 is not simply a measure of low intelligence. The prevalence studies indicate that the SAT9 discriminates between pain patients and other groups. The drawbacks to this scale are that: it measures only one feature of alexithymia, rater consistency is difficult to obtain, and the literature on the development and use of the SAT9 has been limited to two groups of researchers mostly drawing on one common subject pool. Nevertheless, the SAT9 appears to be a potentially useful adjunct to other alexithymia measures.

THE TORONTO ALEXITHYMIA SCALE The Toronto Alexithymia Scale (TAS) is a self-report instrument composed of 26 five-point Likert scales (Taylor, Ryan, & Bagby, 1985). The items cover four aspects of the alexithymia: (a) ability to identify and distinguish between feelings and bodily sensations, (b) ability to describe feelings, (c) daydreaming, and (d) externally oriented thinking. Possible scores range from 26 to 130. Taylor, Bag­ by, Ryan, et al (1988) recommended TAS cutoff scores of 7 4 > for alexithymia, and 6 2 < for definitely nonalexithymic. The scale was developed using a construct-oriented theoretical approach: Taylor et al. (1985) reviewed the literature and selected five content areas thought to reflect the substantive domain of the alexithymia construct. Based on these content areas, 41 self-descriptive statements were written— approximately half positively keyed and half negatively keyed. These original items were ad­ ministered to 542 undergraduates. From the 41 items, 26 were included on the final version of the scale. They were selected for high item-total scale correla­ tions and/or high item-factor scale correlations, and low correlations with a measure of social desirability. Factor analysis of the scale produced a four-factor solution consistent with the alexithymia construct.

Reliability Internal Consistency. When data from the 542 undergraduates used in the development of the scale were split into two groups, the alpha coefficients of both samples were .77, and similar four-factor solutions were produced (Taylor et al., 1985). For 209 undergraduates, Bagby et al. (1988) found alphas of .76 and .75 for males and females, respectively. The mean interitem correlation of the TAS (.10) was at the expected level for a multifactor scale. Cronbach’s alpha

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for 333 students was .77 (Loiselle & Dawson, 1988), and for 125 male substance abusers it was .68 (Haviland, Shaw, MacMurray, & Cummings, 1988b). Test-Retest. Taylor et al. (1985) gave the TAS to 37 subjects and read­ ministered the TAS 1 week later, yielding a correlation of 0.82. Another 211 were given the TAS 5 weeks later, with a correlation of 0.75. Linden, Wen, Paulhus, Lenz, and Siegel (1991) found a test-retest correlation of .68 over 7 months in a sample of 54 healthy students. Validity Relationship With Self-Report Measures and Clinician Ratings. Bagby, Tay­ lor, and Ryan (1986a) administered a test battery to 81 students; the battery was composed of the TAS, the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory-Form Y (STA I-Y), the Need for Cognition Scale-Short Form, the Psychological Mindedness Scale, the Shipley-Hartford Scale (as an index of IQ), and the Basic Personality Inventory (BPI). Significant positive correlations were found between TAS and the BPI personality features of per­ secutory ideation, anxiety, thought disorder, impulse expression, social introver­ sion, and self-depreciation. The TAS was independent of denial, interpersonal problems, alienation, and deviation. There was no significant correlation be­ tween the TAS and nonverbal IQ, but a significant negative correlation with verbal IQ (r = —.27) and full-scale IQ (r = —. 19). There were high correlations between the TAS and depression (r = .60) and trait anxiety (r = .39). As expected, there was a strong correlation between the TAS and hypochondriasis, and negative correlations with psychological mindedness (r = —.33) and need for cognition (r — —.42). According to the authors, these relationships are mostly consistent with the alexithymia construct, and thus support the construct validity of the TAS. Subsequently, a group of 209 undergraduates was given the TAS, the SSPS, the M M PI-A , the Social Desirability Inventory, and the Psycho­ somatic Symptom Checklist (PSC; Bagby, Taylor, & Parker, 1988). The TAS correlated significantly with the SSPS (r = - .1 9 ) , but not with the M M PI-A (r = .05). The TAS also correlated significantly with the PSC (r = .32) and the symptom checklist (r = .31). The TAS showed a low magnitude correlation with social desirability (r — —.18). On three measures of psychometric adequacy for factor analysis, the TAS was superior to the SSPS, suggesting the TAS was more internally consistent. Factor analysis of the TAS revealed four factors. The reliability of the factor matrices was tested through comparison with the matrix presented in an earlier study (Taylor et a l., 1985). This comparison revealed good factor congruence across all four factors, with congruence values of .9 5 -.9 7 . The authors concluded that the TAS has a more reliable and stable factor structure than the SSPS (see section on the SSPS).

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Newton and Contrada (1990) focused on the overlap of response style and alexithymia. They selected 95 healthy young women from a sample of 597 students. Using the Taylor Manifest Anxiety Scale and the M ariow e-Crow ne Social Desirability Scale, three groups were formed: (a) repressor (high social desirability and low anxiety), (b) low anxious (low social desirability and low anxiety), and (c) high anxious (low social desirability and high anxiety). All subjects completed the TAS and participated in a lab stress test, where they were instructed to prepare for and recite a 3-minute speech about their most un­ desirable personality characteristic. State affect and cardiovascular activity were monitored throughout the task. These researchers noted that alexithymia and repression were unrelated, and that alexithymics were most frequently found among the high-anxious subjects. Interestingly, alexithymic women displayed desynchrony in negative affect-heart rate linkage, such that high negative affect was associated with small heart rate changes. In a similar vein, Linden, Fensome, and Con ( 1992) administered a question­ naire package containing the TAS, anger expression, self- and other deception questionnaires, and overt behavioral expression of affect to a group of 83 healthy university students. High alexithymia scores were associated with anger-in ten­ dencies (r = . 32 , p < . 01 ), with reduced overt behavioral expressions of positive affect (r = —. 35 , p < . 001 ) and reduced tendencies at impression management (r = — . 31 , / ? < . 01 ). A peer rating of behavioral affect expression also correlated negatively with the TAS (r = —. 33 , p < . 01 ), thus duplicating the self-reported affect expression finding. These findings suggest that high TAS scorers are likely to keep their anger in, do not try to leave a particularly positive impression on others (hence, are not defensive), and are rather unexpressive when it comes to positive affect. J. M ayer (personal communication, 1992) reported TAS correlations of .38 and .30 with the BDI and the Carver-Scheier Optimism scale, respectively. He also noted that the first two subfactors (Emotional Identification, Emotional Description) account for the correlations with various measures of negative af­ fect. Construct validation was also attempted in two samples of 117 and 74 students, respectively, who completed the Imaginal Processes Inventory, and measures of ego strength, anger expression, and physical symptoms (Bagby, Taylor, & Parker, 1988). In Sample 1, TAS scores correlated negatively with positive constructive daydreaming (r = —.38, p < .001), positively with the guilt and fear of failure daydreaming (r = .44, p < .001), and positively with poor attentional control (r = .46, p < .001). In Sample 2, high TAS scores were related to low ego strength (r = —.45 >P < .001), anger in (r = .36, p < .001), inhibited anger-out behavior (r = —.22, p < .01), and elevated symptom report­ ing (r = .21, p < .01). The relationship of self-disclosure and private selfconsciousness to TAS scores was investigated in 333 university students (Loiselle & Dawson, 1988). Subjects with high TAS scores reported difficulty with disclosure (r = .29, p < .001), and thought that disclosure was not impor­

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tant (r = —.14, p = .012). In 190 university students, high TAS scores were associated with introversion (r = .37, p < .001), neuroticism (r = .29, p < .001), psychoticism (r = .11, p < .05), and somatic symptom reporting (r = .21, p < .01). TAS did not correlate with a Lie scale (Parker, Bagby, & Taylor, 1989). An attempt to understand the depression-alexithymia overlap was undertaken by factor analyzing the responses of 406 undergraduate students to the TAS and the BDI (Parker, Bagby, & Taylor, 1991). This analysis yielded a four-factor solution, where Factor 1 clearly represented the BDI items, whereas TAS items loaded on Factors 2 ,3 , and 4. The authors then replicated this pattern of findings in 164 psychiatric outpatients. The results support the view that alexithymia is distinct from depression. Although the TAS has been mostly validated on student populations, there are nevertheless a number of clinical studies as well. Untangling the overlap between depression and TAS scores in a clinical sample was undertaken by Haviland, Shaw, Cummings, and MacMurray (1988a), who tested 55 male alcoholics at intake and after 3 weeks of inpatient treatment. BDI scores dropped significantly with treatment (from M = 18.6 to M = 9.7), whereas TAS scores remained unchanged (M = 71.1 and M = 69.5). This differential change over time sug­ gests at least some conceptual independence of alexithymia from depression. TAS scores were correlated at r = .39, p < .001 with depression (BDI) in 125 male substance abusers (Haviland et al., 1988b). Factor analysis revealed three factors that were consistent with the original analyses by the Taylor and Bagby group (note that Factors 1 and 2 were pooled by Haviland et al. because of their high intercorrelations). Item analysis revealed that the BDI correlated only with items from Factor 1, labeled the feeling factor. Sriram et al. (1987) gave the TAS, the BIQ, and the TAT to 30 patients with psychogenic pain disorder and 30 normal, matched controls. The pain patients scored significantly higher on the TAS and the BIQ, but not on the TAT. The TAS significantly correlated with the BIQ (r = .62) and the total word count measure of the TAT (r = —.40). Sixty chronic pain patients were given the TAS, Analog Alexithymia Scale (AAS), and Alexithymia Provoked Response Ques­ tionnaire (APRQ; Pierce, Faryna, Davidson, Markart, & Krystal, 1989). The 43item TAS (TA S-43) did not correlate with the APRQ (r = .21), nor did the 26item TAS (TAS-26; r = .08). The AAS was significantly correlated with the TA S-26 (r = .55) and the TA S-43 (r = .60). The TA S-26 was significantly related to the TA S-43 (r = .94). For subjects clinically rated as alexithymic versus nonalexithymic, the TAS failed to distinguish between groups. Taylor et al. (1988) gave the TAS to 46 patients referred to a behavioral medicine clinic. Clinical alexithymia ratings derived from observed interviews served as the alexithymia criterion. TAS scores were significantly higher for the group of patients identified by raters as alexithymic than for the group identified as nonalexithymic. Mood, obsessive personality style, and TAS scores were assessed in 97 psychiatric outpatients and 81 inpatients (Wise, Mann, & Hill, 1990). TAS

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scores correlated with depressive mood (r = .33 and r = .29); when mood was statistically controlled, obsessive personality remained as a significant correlate of TAS scores. A sample of 44 male substance abusers was classified as alexithym icnonalexithymic using a 74-point cutoff (Taylor, Parker, & Bagby, 1990). The resulting two groups differed significantly on a variety of psychological measures. Alexithymics were more depressed, more hypochondriacal, more socially intro­ verted, more anxious, and more sensitizing, and scored lower on Ego Strength but higher on the Schizophrenia and Psychasthenia subscales of the MMPI. Bagby, Taylor, Parker, and Loiselle (1990) undertook a series of factor an­ alyses to test the stability of the TAS factor structure. Three samples (n = 161 healthy adults, n — 214 psychiatric outpatients, and n = 332 college students) served as subjects. Factor structures confirmed the four-factor solution advocated previously (Taylor et al., 1985), and were remarkably similar across the three samples. The authors did not address the intercorrelations of the resulting four factors. Previous observations that alexithymia is a multidimensional, rather than a single-factor, phenomenon prompted Haviland, Hendryx, Cummings, Shaw, and MacMurray (1991) to relate affective disorder to each single subfactor of TAS-defined alexithymia, as well as the aggregate score. The samples used for analyses were the same as described previously (Haviland et al., 1988a, 1988b). Using LISREL software, the researchers learned that the TAS embraces three independent, unrelated dimensions: Feelings, Daydreaming, and External Think­ ing. Only the Feelings factor (tapping the ability to identify feelings and distin­ guish them from bodily sensations) correlated with depression. Goodness of fit was used as the primary criterion for judging the appropriate­ ness of one-, two-, three-, or four-factor solutions to TAS item analysis (Hendryx, Haviland, Gibbons, & Clark, 1992). Data were obtained from 130 male alcoholics. As in previous factor analyses, a three-factor solution emerged as a winner, and the factors were Emotional Awareness Deficit; Lack of Imagina­ tive Ability; and External, Operative Cognitive Style. Because the Emotional Awareness Deficit factor is conceptually the closest to the definition of alex­ ithymia, and is represented by a disproportionately large number of items, Hendryx et al. argued that the TAS mostly taps the Emotional Awareness Defi­ cit, and that the other two factors have relatively little impact on the aggregate score of the TAS. Relationship With Behavioral and Physiological Indices Mayer, DiPaolo, and Salorey (1990) correlated TAS alexithymia with a number of experimental variables derived from ratings of emotional qualities of visual stimuli, including faces, colors, and abstract designs. Subjects were 139 college students. TAS scores did not predict agreement with the overall consensus about the emotional qualities of these stimuli. Surprisingly, high TAS subjects reported more and more varied emotions in response to the presented stimuli than did lowTAS subjects. The TAS also correlated .34 with the Eysenck Neuroticism scale.

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Linden et al. (1992) subjected 80 healthy young adults to lab stress and ambulatory blood pressure testing. The objective was to test whether high TAS scorers were differentially responsive at the cardiovascular level. All subjects completed subjective stress ratings during the lab tasks and daily stress ratings paralleling the ambulatory blood pressure measurement. Lab tasks consisted of isometric handgrip, mental arithmetic, and discussion of a recent emotionally distressing social interaction. Cardiovascular activity for low, medium, and high TAS terciles were compared with one another. No group differences were found on ambulatory blood pressure or heart rate, and high alexithymics also showed blood pressure responses to all lab tasks that were comparable in magnitude to those of other groups. Only heart rate responses were slightly smaller in high alexithymics. The authors concluded that alexithymics were not consistently under- or overaroused on cardiovascular activity indices. Normative and Prevalence Data In a sample of 209 undergraduates, Bagby et al. (1988) found a group mean of X = 61.8 (SD = 13.2) for 72 males and X = 60.5 (SD = 1 1 .5 ) for 129 females. Of 125 male alcoholics, 50.4% were classified as alexithymic using the standard 74-point cutoff (Haviland, Shaw, MacMurray, & Cummings 1988b). Conclusions Although the TAS is one of the most recent measures on alexithymia, reliability and validity results are, on the whole, impressive. The development of the scale was guided by a high level of psychometric sophistication, with an unusual amount of attention given to all aspects of reliability, as well as construct, concurrent, and content validity. The TAS literature is still relatively weak in showing discriminant validity for distinguishing between various psychiatric and psychosomatic, clinical, and healthy groups. The most extensively tested nonhealthy group is male substance abusers, of whom about 50% are alexithymics (using the > 7 4 cutoff). The reliability evidence is consistently favorable, although alpha coefficients should ideally exceed .8 and the TAS tends to fall slightly below this criterion. The TAS correlated with the BIQ, SSPS, and the AAS, thus providing concur­ rent validity evidence. The TAS also was related to various other psychological measures (tapping imagination abilities, insight, ego strength, etc.) in a manner consistent with the alexithymia concept, thus supporting the construct validity of the TAS. Inconsistent with the original alexithymia conception was the consis­ tent finding of elevated neuroticism, anxiety, and depression with high TAS scores. Hence, the TAS either is a measure of negative affect or at least has unsatisfactory discriminant validity from negative affect. Treatment was found to reduce depression, but not alexithymia (Haviland et al., 1988a). In addition,

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factor analysis of a TAS/BDI item matrix identified BDI depression as loading clearly on a single, distinct factor. Hence, the most plausible explanation is the one of unsatisfactory discriminant validity from negative affect measures. Inci­ dentally, the consistent overlap of TAS and negative affect measures strongly rebukes the accusation that the TAS is confounded by desirable responding or is merely a measure of repression. Although speculative at this time, we posit that the TAS inadvertently taps negative affect because depressed and anxious individuals tend to score high on measures that somehow tap negative affect. Indeed, some researchers (Watson & Clark, 1984) have convincingly argued that neuroticism, anxiety, depression, psychasthenia, hypochondriasis, and so on all tap one and the same underlying phenomenon— negative affect. Because the TAS Factor 1 refers to negative feelings and emotional confusion, and because Factor 1 has the most items, depressed subjects are likely to score high on the TAS. A constructive solution for achieving discriminant validity is that of giving the TAS with a depression measure (Haviland et al., 1991). The overlap between TAS scores and negative affect measures is unfortunate because alexithymia measures presumably discriminate healthy from psycho­ somatic individuals, but psychosomatic patients may react with depression to the diagnosis of illness (especially if the condition is chronic and painful). What is really needed is prospective work that investigates the predictive validity of TASdefined alexithymia for psychosomatic disease. If executed, the same type of study would also permit an analysis of whether one or more subfactors or the aggregate score is actually the most clinically useful index. The TAS items have been reported to load on four subfactors (the Toronto group) or three factors (Haviland’s group). In the psychometric domain, a scale is considered particularly useful when it loads on a single factor— namely, the trait or feature it purports to tap. The multifactorial structure of the TAS makes us believe that the scale’s creators think of alexithymia as a pattern of behavior with several somewhat distinct subfeatures. The already completed validation work concentrates on the use of aggregate scores, and we do not know whether the four identified subfactors could harbor differential validity in distinguishing among clinical groups. This certainly represents one area of worthwhile further validation research on the TAS. Interestingly enough, the creators of the TAS have since revised the scale in an attempt to deal with the issue of subfactors (for details, see the following section).

THE REVISED TORONTO ALEXITHYMIA SCALE The creators of the TAS recently revised the original instrument (Taylor, Bagby, & Parker, 1992). The objectives for the revision were to: (a) attempt to consolidate the first two factors that were highly intercorrelated, thus likely measuring the same

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underlying phenomenon; (b) remove the Daydreaming factor, which was not theoretically coherent with the alexithymia construct; thus this factor actually correlated negatively with the first factor; and (c) rewrite the scale so that roughly even numbers of items were available for the measurement of underlying factors. The revised TAS (TAS-R) was created by adding 17 pilot items to the original set of 26. Some of these pilot items tapped the ability to describe feelings to others, and most of the items reflected imaginal and externally oriented think­ ing. This 43-item revised scale was administered to 389 male and 576 female university students. The format was left unchanged (i.e., 5-point Likert scales were used). Using this data pool, 23 items were selected for the T A S-R , given that these items had reasonably high factor loadings, high internal reliabilities, and low correlations with social desirability indices. The T A S-R no longer contains items on daydreaming or imaginal activity, whereas there are more items assessing externally oriented thinking. Reliability Internal Consistency. Cronbach’s alpha for the 23-item T A S-R was .82, and the mean interitem correlation was .16. Factor analysis confirmed the in­ tended two-factor solution, and this factor pattern was replicated in two addition­ al samples of another 401 college students and 218 psychiatric patients. Intercor­ relations between the factors ranged from .21 to .28, thus confirming little overlap. Alpha coefficients for the two additional samples also replicated the earlier finding of high internal consistency (.80 and .82). The observed internal consistency of the T A S -R is slightly higher than the TAS; this is likely because the Daydreaming factor, which correlated negatively with the other three TAS factors, has been removed from the TA S-R . Validity Relationship With Self-Report Measures. Convergent and discriminant va­ lidity was established by showing that the T A S-R scores correlated positively with poor attentional control (r = .50), negatively with need for cognition (r = —.52), and negatively with psychological mindedness (r = —.40). The T A S-R also correlated with the Anger Expression Scale (r = —.25), three scales of somatic complaints (r = .43, r = .36, and r = .28), and hypochondriasis (r = .37). The T A S-R scores were negatively related to ego strength (r = —.43), but not correlated with attributional style or perfectionism (Taylor et al., 1992). Normative and Prevalence Data Outpatients in a behavioral medicine clinic were blindly rated by three clinicians for alexithymic features. Those patients— who by two-thirds agreement classified for

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alexithymia— obtained significantly different scores from nonalexithymics (X = 66.4, SD = 13.4); X = 56.7, SD = 12.2). Means for university students were 55.3 (SD = 10 . 9 ) and 55.0 (SD = 12 . 0 ) for men (ft = 159 and women (ft = 242 ); for healthy adults, means were 59.8 ( 11 . 0 ) and 59.1 ( 10 .4 ) for men and women, respectively; and for psychiatric outpatients, means were 63 . 8 ( 13 . 1) and 63 . 0 ( 14 . 6 ) for men and women , respectively. Neither sample had a significant sex difference (Taylor et al., in press). Conclusion All the information provided previously was derived from a single article (Taylor et al., in press). It is impressive that researchers can accumulate so much infor­ mation on reliability and validity in a single publication on a new, or in this case revised, scale. The T A S-R appears very reliable, and the convergent and dis­ criminant validity studies are supportive of the revised scale. Test-retest stability data were not available. However, given the stability of the original TAS scores, it seems likely that test-retest reliability for the revised scale may also be high. No evidence was provided on potential overlap between T A S-R and depression. Despite the considerable efforts that have gone into the revision of the TAS, the problematic overlap of TAS-defined alexithymia with negative affect (and de­ pression in particular) is not dealt with any more clearly in the revision than in the original scale. Also, more clinical validation is needed to substantiate wheth­ er one or more factors differentially relate to clinical diagnoses of psychosomatic dysfunctions. Other than reflecting a simplified factor structure, the T A S -R does not appear clearly superior to its predecessor.

THE ALEXITHYMIA PROVOKED RESPONSE QUESTIONNAIRE The Alexithymia Provoked Response Questionnaire (APRQ) was proposed by Krystal et al. (1986). Subjects participate in a BIQ-prototype, structured inter­ view designed to provoke them into producing affective material via imagination of a variety of potentially stressful settings. Interviewers can follow up on ambig­ uous responses with more questions. Responses are scored dichotomously (i.e., 0 for alexithymic, 1 for nonalexithymic). An alexithymia score is given if they describe action but not affect, provide detailed descriptions of situations but no affective responses, describe physical sensations rather than affect, and when a word indicating affect is not used in a meaningful way. Reliability Internal Consistency. The reliability coefficients were .84 for total score assessment and .59 for global assessment (Krystal et al., 1986).

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Interrater Reliability. The overall level of interrater agreement was 82.6% , with specific agreement for the presence of alexithymia at 71.4% and absence of alexithymia at 87.5% (Krystal et a l., 1986). For the 17 items analyzed separately, interrater agreement was excellent for 4 items, good for 6 items, fair for 5 items, and poor for 2 items. For 60 chronic pain patients, interrater reliability was good (r = .85; Pierce et al., 1989).

Validity The APRQ was given to 45 male veterans divided into four diagnostic subgroups (inpatient vs. outpatient with PTSD, inpatient with affective disorder, inpatient with somatic disorder). The M M PI-A , SSPS, and BIQ were also given. The affective disorder group was less alexithymic than the somatic disorder group and the inpatient PTSD group. Correlations among scales were calculated, as well as interrater reliabilities. Relationship With Self-Report Measures. The BIQ and APRQ are highly correlated (r = .72), suggesting the APRQ has concurrent validity (Krystal et a l., 1986). The APRQ did not correlate with the M M PI-A (r = .01) or with the SSPS (r = —.23). Pierce et al. (1989) gave 60 chronic pain patients the APRQ, TAS, and AAS. The APRQ correlated significantly with the AAS (r = .30) and nonsignificantly with the TA S-26 (r = .08).

Normative and Prevalence Data A number of clinical groups were tested by Krystal et al. (1986): (a) inpatient PTSD (n = 10), X = 5.9, SD = 3.6; (b) inpatient affective disorder (n = 14), X = 11.0, SD = 4.8; (c) outpatient PTSD (n = 11), X = 8.7, SD = 5.5; and (d) inpatient somatic disorder (n — 11), X = 7.3, SD = 4.2.

Conclusions Although only two studies have been presented, the data suggest internal con­ sistency and good interrater reliability. Test-retest reliability data were not avail­ able. The APRQ only correlated with the BIQ and AAS measures of alex­ ithymia. The BIQ has been judged a reliable and valid alexithymia measure, therefore the concurrent validity of the APRQ is supported. At this early stage in its development, the APRQ appears to hold promise, although it is not clear that it makes an original contribution above and beyond the BIQ, on which it is based and with which it highly intercorrelates. Instead, the APRQ may be considered a standardized subtype of the BIQ procedure.

THE ANALOG ALEXITHYMIA SCALE The Analog Alexithymia Scale (AAS) was developed by Faryna et al (1986). It is a 22-item paired-statement questionnaire, and is based on 19 of the 20 SSPS questions. One question was omitted (No. 19), two were added, and one was revised. The paired statements are placed at each end of a 10-cm line, and are staggered so the midpoint is not obvious. The score for each statement is the distance in millimeters from the subject’s mark to the end of the line nearest the more alexithymic statement. Hence, low scores indicate alexithymia. An AAS score of 1,098 is equivalent to an SSPS score of 50.

Reliability The scale was administered to 256 students, hospital workers, church members, mobile home residents, and faculty members (Faryna et al., 1986). Internal consistency was low (Cronbach’s alpha .43). Test-retest reliability (100 stu­ dents and faculty completed the AAS 6 weeks later) was .76 (Faryna et al. 1986). Factor analysis yielded four factors: (a) Emotional Life, (b) Fantasy Life, (c) Attention to Detail, and (d) People’s Reactions to What Happens to Them.

Validity Faryna et al. found that the correlation between the AAS and SSPS (n = 83) was .40. An SSPS score of 50 or less identified 6.8% of the sample as alexithymic. Only two of the nine subjects identified by the SSPS were classified as alex­ ithymic by the AAS. The sensitivity of the AAS is .22, and the specificity is .91 using the SSPS as the reference standard. In a sample of 60 chronic pain patients given the AAS, TAS, and APRQ, the AAS significantly correlated with the APRQ (r = .30), the T A S-26 (r = .55), and the TA S-43 (r = .60; Pierce et al., 1989).

Conclusions From these two studies, the evidence supporting the AAS is uneven. The internal consistency is unacceptable, but the test-retest reliability is good. The question of validity is problematic in one study, but the second study supports the validity of the AAS in relation to two other recently developed alexithymia measures. It remains unclear why the AAS intercorrelates only r = .40 with the SSPS, with which it shares all but three items.

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THE NEW MMPI ALEXITHYMIA SCALE (BASED ON THE SSPS) Another MMPI Alexithymia scale was based on the SSPS and not the BIQ (Shipko & Noviello, 1984). It is a 20-item self-report subscale of the MMPI. For each MMPI item, the average SSPS alexithymia scores were computed for those subjects who had responded “true” and those who responded “false.” The differ­ ence between SSPS scores for the two groups was taken as a measure of the degree to which that MMPI item is related to alexithymia. Those items that produced the most significant differences were selected for this scale. A score of 16.5 or above indicates alexithymia. This scale correlates with the MMPI Social Introversion and Psychopathology scales. The correlation between the two MMPI Alexithymia scales is r — —.32, suggesting limited overlap. The differ­ ences between scales could also be a function of the different populations used to derive the scale. The SSPS/MMPI norms were obtained from 46 healthy under­ graduates, whereas the BIQ/MMPI scale was given to 100 hospitalized respira­ tory patients. No data have been generated regarding the reliability of this new MMPI scale, therefore the validity is questionable as well.

PROJECTIVE TESTS— THE RORSCHACH TEST AND THE THEMATIC APPERCEPTION TEST Alexithymia has also been assessed using other already available methods, for which extensive psychometric background research has been executed (i.e., the protective techniques of the Rorschach test and the Thematic Apperception Test and [TAT]). The question is to what degree these personality measurement tech­ niques also tap the alexithymia concept. Reliability and Validity For a detailed review of the controversies around reliability and validity of the Rorschach and TAT overall, the reader is referred to reviews like Weiner (1986). Even the advocates of projective measurement concur that acceptable levels of reliability require considerable amounts of training and experience for the test interpreters. Validity Specific to the Alexithymia Concept Relationship in methods to assess mixed personality liability using the

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Prevalence Studies. Acklin and Bernat (1987) used these 33 lower back pain patients, 210 depressive inpatients, 200 disorder patients, and 600 normal controls. Interrater re­ Exner system was 94%. These researchers have proposed

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Rorschach indices of alexithymia, which include Impoverished Fantasy, Affec­ tive Response, and Adaptively Integrated Affect; Cognitive Constriction and Perceptual Stereotypy; and Depression. Back pain patients scored in the pre­ dicted direction on all indices and could be clearly distinguished from the other groups. Subsequently, Acklin and Alexander (1988) conducted a Rorschach study on four psychosomatic groups and one nonpatient group: (a) lower back pain (n = 33), (b) gastrointestinal (n = 31), (c) dermatology (n = 29), (d) migraine headache (n = 35), and (e) nonpatient controls (n = 600). Psychosoma­ tic patients were found to be highly distinguishable from nonpatients on the Rorschach alexithymia variables. Psychosomatic patients exhibited significant decrements in fantasy life, adaptive emotional responsiveness, and stereotypic perception and cognition, and limited resources available for coping and adaptive efforts in relation to nonpatients. Pain patients were found to be significantly more alexithymic than the gastrointestinal and the headache patients on the majority of alexithymia indicators, but were indistinguishable from the dermatol­ ogy patients. Significant personality differences between low back pain patients and other psychosomatic groups, as well as the nonpatient group, were found by clustering selected Rorschach variables. On both Rorschach and TAT, it was demonstrated that violent offenders (n = 68 homicide or assault convicts) have an inability to fantasize and express imag­ ined thoughts or emotions verbally (Keltikangas-Jarvinen, 1982). However, some studies failed to support the use of projective tests for alexithymia classifi­ cation or provided only weak support. Keltikangas-Jarvinen (1985) did not find that either test (TAT or Rorschach) differentiated between 107 psychosomatic patients and 86 somatic controls. The BIQ, however, did distinguish between groups. In another study, Taylor and Doody (1985) assessed the same subject sample, but scored the TAT for a number of different affective words, thus generating an affect vocabulary score. Psychosomatic subjects had less verbal production and a more limited vocabulary for expressing feelings. Taylor et al. (1981) gave both the Rorschach and the TAT to 20 psychoneurotic and 20 inflammatory bowel disease patients. Both tests discriminated the neurotics from the bowel disease patients, the former having produced longer stories on the TAT and used more affect words. Vollhardt, Ackerman, and Shindeldecker (1986) compared 30 mixed arthritis, 18 nonSERA (negative for serum rheumatoid factor), and 16 SERA patients on short forms of the TAT, for which an alexithymia rating procedure was developed using five lexical variables that characterize alexithymia. The patients were scored on the five variables, and a total alexithymia score was computed. Alex­ ithymia score ranged from 0 to 5 for each card and 0 to 35 for all seven TAT cards. Interrater reliability was at 86.5%. Only one variable was found to dis­ criminate between diagnostic groups. On imaginative thinking, the SERA group scored significantly higher. The total alexithymia score did not distinguish be­ tween groups.

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Thirty patients with psychogenic pain disorder and 30 normal matched con­ trols completed the BIQ, TAS, and TAT (Sriram et al., 1987). The TAT failed to significantly discriminate between groups, whereas both the TAS and BIQ did. The total word count on the TAT significantly correlated with the BIQ (r = —.40) and TAS (r = —.37), but the other two TAT measures (affect word count and affect variability) did not. Abramson, McClelland, and Kellner (1990) classi­ fied 30 diabetics and 49 same-age, healthy controls as alexithymic (or not) using the responses to six TAT stories. Coder reliability was 87%. Diabetics were clearly more alexithymic than controls, and use of fewer emotion words was associated with poorer metabolic control in the diabetics. The TAT was able to discriminate 20 Type A and 20 Type B subjects in terms of their projective reduplication, functional relationship to the body, lack of libidinal investment of personal activities and interpersonal relationships, and poverty of fantasy (Defourny, Hubin, & Luminet, 1977). Taylor and Doody (1982) were able to dis­ criminate between 20 neurotics and 20 psychosomatic patients (ulcerative colitis and Crohn’s disease) using a nine-card subset of TAT. The psychoneurotic group was significantly different from both psychosomatic subgroups. The psycho­ somatic subjects showed decreased verbal expression manifested in decreased total and affect word count. Conclusions Given the lack of evidence, no fair evaluation can be made of the face, content, construct, and discriminative validity of these tests. The Rorschach approach has no failures to date. Only three studies have called validity into question— one of these used a new TAT alexithymia scoring system to distinguish subgroups within one clinical group: arthritics (Vollhardt et al., 1986). The TAT-based alexithymia classification has been found to correlate with the TAS and the BIQ, but only on total word count (Sriram et al., 1987). No evidence is avail­ able on the test-retest reliability of measuring alexithymia with the Rorschach or TAT.

SPEECH ANALYSIS The last category of methods to be discussed here is speech analysis. Given that a distinctive verbal expression is the essence of alexithymia, this technique has a priori face and content validity. The predominant approach is to score speech samples on the G ottshalk-G leser Scales (GGSs)— an approach that was system­ atized by Ahrens (1985). The GGSs were used to analyze speech in 42 psychosomatic, 22 neurotic, and 31 patients with medical problems, who were also given a checklist of bipolar adjectives (Ahrens, 1985). From these, two measures were scored: cognitive

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attribution processes and unconscious responses to different affective stimuli. Neurotics showed more anxiety and hostility than the other two groups. No other group differences were found on either index. In a study of 40 psychoneurotics and 40 matched psychosomatics, speech was analyzed using an interview situa­ tion (Lolas, von Rad, & Scheibler, 1981). These groups were discriminated on the basis of anxiety and hostility scores. A concordance with clinical classifica­ tion was reached in 80% of the patients. Psychosomatic patients exhibited lower affect scores. In a second study with 92 psychoneurotic and 56 psychosomatic patients, these results could not be replicated based on verbal samples produced in response to a request to narrate a dramatic life episode. The concordance rate for the raters was 62.8%. Twenty neurotic and 20 psychosomatic subjects could not be differentiated by their expression on the Anxiety, Hostility Outward, and Hope scales of the GGS (Taylor & Doody, 1985). However, the psychosomatic patients had a more lim­ ited emotional vocabulary than their neurotic counterparts, as measured by affect vocabulary scores. The GGSs correlated oppositely to the expected direction with several scales measuring alexithymia (BIQ, SSPS, M M PI-A ) and other measures (K scale of MMPI, TAT total word count, and responses on the Rorschach). Affect vocabulary scores did not correlate with the alexithymia measures, but did correlate in the expected direction with the K scale of the MMPI, TAT total word count, and Rorschach responses. Von Rad, Drucke, Knauss, and Lolas (1979) obtained verbal samples from 40 psychoneurotic and 40 matched psychosomatic patients. Five of six Anxiety subscales on the GGS and three of four Hostility scales significantly distinguished between groups. Overbeck (1977) was able to identify an alexithymic subgroup of 90 chronic ulcer patients using items on the Giessen Test, which is composed of five factors consistent with the alexithymia concept. Tenhouten, Hoppe, Bogen, and Walter (1985a, 1985b, 1985c, 1985d, 1986, 1987) presented a series of studies examining eight cerebral commissurotomized patients and eight matched normal controls. Speech was analyzed on lexical, sentential, and global content levels, and with the GGS. Significant differences between groups were found. An overall alexithymia index was generated and it too distinguished between groups. Using factor analysis, these researchers pro­ posed a psychosomatic personality construct, with which alexithymia charac­ teristics are closely related. A discriminant function analysis was performed that indicates the construct validity of speech analysis. The four factors identified are consistent with the construct of alexithymia. These factors were: Capacity for Symbolization, Percentage of Affect-Laden Terms, Percentage of Auxiliary Verbs, and Fantasizing About Symbols. Callosotomy (a type of brain surgery) patients were significantly less verbally expressive of the symbolic and emotion­ al content of a film about death than were the control subjects. This was con­ firmed by reduced levels of electroencephalogram (EEG) alpha-band interhemispheric coherence.

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Conclusions Research findings regarding the discriminative validity of speech analysis tech­ niques are equivocal. Three of the six studies produce evidence against the discriminative validity of the GGSs and a computer-run content analysis. No test-retest reliability research has been found. Although it is difficult to dispute the face and content validity of these techniques, speech analysis appears to be of unknown reliability and limited validity. Furthermore, the high cost associated with speech analysis is prohibitive.

EVALUATION OF ALEXITHYMIA MEASURES Our review of the assessment of alexithymia has revealed a wealth of studies published since the Lesser (1981) review. Considerably more information on the reliability and validity of the early alexithymia instruments is now available, and several new measures have been developed. Without exception, all measures described here appear to possess content validity; the quantity and quality of other psychometric data vary widely. Unfortunately, the scale development strategy has varied dramatically across research teams. On some measures, we found strong basic psychometric work but limited clinical validation (e.g., the TAS), whereas others jumped boldly into large-scale clinical evaluations using measures with questionable reliability (e .g ., the SSPS). With some measures, it was not clear why the sample of choice was sometimes pain patients as opposed to alcoholics or arthritis patients, for example. The broadest sampling of clinical groups has been performed with the BIQ. Extensive data also support he reliability and validity of the BIQ. A fair amount of research on the SSPS and the M M PI-A is available, but it provides, at best, modest support for the validity and reliability of these scales: Although of questionable validity itself, the SSPS nevertheless appears to be more useful than the M M PI-A . The SAT9 has generally acceptable reliability and validity data, but it assesses only one alexithymia characteristic— symbolic functioning. The APRQ, AAS, and new MMPI Alexithymia scale do not have enough empirical research to support claims of their validity or reliability. Of those three, the APRQ shows the most promise for further research, especially because of its linkage to the BIQ. The TAS is a promising self-report measure with high reliability and especially strong content, concurrent, and construct validity. Our criticisms include a relative paucity of prevalence studies in psychosomatic pop­ ulations, the conceptual overlap of the TAS with negative affect measures, and the fact that three independent factors need to be assessed for a diagnosis of alexithymia. The latter point is important because no evidence is available at this time that either the aggregate TAS score or any of the subfactors have predictive validity for the development of psychosomatic disease.

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The Rorschach and the TAT have questionable reliability. Nevertheless, some findings suggest content, construct, and discriminative validity. Their routine use, however, is hampered by the need for costly training in scoring, as well as theoretical background in psychodynamic theory. Speech analytic techniques are also very complex and costly, and are questionable in their construct and discrim­ inative validity. Hence, the BIQ, which requires a standardized interview situation, and the TAS, which is a self-report scale, are currently recommended here as the best measures of alexithymia. The two measures correlate reasonably well (r = .62). Indeed, the degree of association is impressive given the method difference; the TAS is a self-report measure, whereas the BIQ involves an interview. The TAS was remarkably free of response-style confounds, both of the impression-management type and the self-deception type. The BIQ, however, was confounded with denial tendencies, suggesting that in the direct interaction with an interviewer, alexithymic patients try to give a biased, desirable impres­ sion of themselves— also called pseudonormality. However, when testing is done under anonymous conditions (as was the case during the TAS development), there is inherently less need for impression management (Paulhus, 1984). This would also explain why alexithymics classified via self-report measures were more likely to report anxiety and depression. The limited test-retest reliability of the BIQ may also be a reflection of changing situational characteristics during the interview situation; this validity threat does not apply equally to a self-report instrument. Based on our review of the literature, we propose a moratorium on new measures. Further studies should concentrate on semistructured interviews and extensive rater training for the BIQ, and should deal with the noted limitations of the TAS (or the TA S-R). If possible, the two measures should be used concur­ rently because they may be tapping different aspects of alexithymia. If a choice is necessary, the self-report format of the TAS gives it an advantage over the BIQ. The self-report is easier to collect than clinician ratings, which are costly, require a great deal of training in application and scoring, and have the additional problem of interrater reliability requirements. REFERENCES Abramson, L., McClelland, D. C., & Kellner, S., Jr. (1990). Alexithymic characteristics and metabolic control in diabetics and controls (Abstract). Psychosomatic Medicine, 52, 245. Acklin, M. W ., & Alexander, G. (1988). Alexithymia and somatization: A Rorschach study of four psychosomatic groups. The Journal of Nervous and Mental Disease, 176, 343-350. Acklin, M. W., & Bemat, E. (1987). Depression, alexithymia and pain prone disorder: A Rorschach study. Journal o f Personality Assessment, 57, 462-479. Ahrens, S. (1985). Alexithymia and affective verbal behaviour of three groups of patients. Social Science in Medicine, 20, 691-694. Apfel, R. J., & Sifneos, P. E. (1979). Alexithymia: Concept and measurement. Psychotherapy and Psychosomatics, 32, 180-190.

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Nemiah, J. C. (1977). Alexithymia: Theoretical considerations. Psychotherapy and Psychosoma­ tics, 28, 199-206. Nemiah, J. C. (1978). Alexithymia and psychosomatic illness. Journal of Clinical and Experimen­ tal Psychiatry, 39, 25-37. Newton, T. L., & Contrada, R. J. (1990, April). The relationship between alexithymia and repres­ sive coping. Paper presented at the meeting of the Society for Behavioral Medicine, Chicago, IL. Norton, N. C. (1989). Three scales of Alexithymia: Do they measure the same thing? Journal of Personality Assessment, 53, 621-637. Osti, R.M .A., Trombini, G., & Magnani, B. (1980). Stress and distress in essential hypertension. Psychotherapy and Psychosomatics, 33, 193-197. Overbeck, G. (1977). How to operationalize alexithymic phenomena: Some findings from speech analysis and the Giessen Test (GT). Psychotherapy and Psychosomatics, 28, 106-117. Papciak, A. S., Feuerstein, M., Belar, C. D., & Pistone, L. (1987). Alexithymia and pain in an outpatient behavioral medicine clinic. International Journal of Psychiatry in Medicine, 16, 347357. Papciak, A. S., Feuerstein, M., & Spiegel, J. A. (1985). Stress reactivity in alexithymia: Decou­ pling of physiological and cognitive processes. The Journal o f Human Stress, 11, 135-142. Parker, J.D.A., Bagby, R. M., & Taylor, G. J. (1989). Toronto Alexithymia Scale, EPQ and self-report measures of somatic complaints. Personality and Individual Differences, 10, 599604. Parker, J.D.A., Bagby, R. M., & Taylor, G. J. (1991). Alexithymia and depression: Distinct or overlapping constructs? Comprehensive Psychiatry, 32, 387-394. Parker, J.D.A., Taylor, G. J., Bagby, R. M., & Thomas, S. (1991). Problems with measuring alexithymia. Psychosomatics, 32, 196-202. Paulhus, D. L. (1984). Two-component models of socially desirable responding. Journal of Person­ ality and Social Psychology, 46, 498-609. Paulhus, D. L., Fridhandler, B., & Hayes, S. (in press). Psychological defense. R. Hogan, J. Johnson, & S. R. Briggs (Eds.), Handbook of personality. San Diego: Academic Press. Paulson, J. E. (1985). State of the art of alexithymia measurement. Psychotherapy and Psychosoma­ tics, 44, 57-64. Pierce, M. J., Faryna, A., Davidson, A., Markart, R., & Krystal, J. H. (1989). A comparison of interview and self-report alexithymia measures (Abstract). Psychosomatic Medicine, 51, 254255. Pierloot, R., & Vinck, J. (1977). A pragmatic approach to the concept of alexithymia. Psycho­ therapy and Psychosomatics, 28, 156-166. Postone, N. (1986). Alexithymia in chronic pain patients. General Hospital Psychiatry, 8, 163— 167. Rabavilas, A. D. (1987). Electrodermal activity in low and high alexithymia neurotic patients. Psychotherapy and Psychosomatics, 47, 101-104. Rodenhauser, P., Khamis, H. J., & Faryna, A. (1986). Alexithymia and handedness: A pilot study. Psychotherapy and Psychosomatics, 45, 169-173. Rybakowski, J ., Ziolkowski, M., Zasadzka, T., & Brzezinski, R. (1988). High prevalence of alexithymia in male patients with alcohol dependence. Drug and Alcohol Dependence, 21, 133— 136. Shipko, S. (1982). Alexithymic and somatization. Psychotherapy and Psychosomatics, 37, 193— 201.

Shipko, S., Alvarez, W. A., & Noviello, N. (1983). Towards a teleological model of alexithymia: Alexithymia and post-traumatic stress disorder. Psychotherapy and Psychosomatics, 39, 122— 126. Shipko, S., & Noviello, N. (1984). Psychometric properties of self-report scales of alexithymia. Psychotherapy and Psychosomatics, 41, 85-90.

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Sifneos, P. E. (1972). Short-term psychotherapy and emotional crisis. Cambridge, MA: Harvard University Press. Sifneos, P. E. (1973). The prevalence of “alexithymic” characteristics in psychosomatic patients. Psychotherapy and Psychosomatics, 22, 255-262. Sifneos, P. E. (1986). The Schalling-Sifneos personality scale revised. Psychotherapy and Psycho­ somatics, 45, 161-165. Smith, G. R., Jr. (1983). Alexithymia in medical patients referred to a consultation/liaison service. The American Journal o f Psychiatry, 140(1), 99-101. Sriram, T. G., Chaturvedi, S. K., Gopinath, P. S., & Shanmugam, V. (1987). Controlled study of alexithymic characteristics in patients with psychogenic pain disorder. Psychotherapy and Psy­ chosomatics, 47, 11-17. Sriram, T. G., Pratap, L., & Shanmugham, V. (1988). Towards enhancing the utility of Beth Israel Hospital Psychosomatic Questionnaire. Psychotherapy and Psychosomatics, 49, 205-211. Tantam, D., Kalucy, R., & Brown, D. G. (1982). Sleep, scratching and dreams in eczema: A new approach to alexithymia. Psychotherapy and Psychosomatics, 37, 26-35. Taylor, G. J. (1984). Alexithymia: Concept, measurement, and implications for treatment. The American Journal o f Psychiatry, 141, 725-732. Taylor, G. J., Bagby, R. M., & Parker, J.D.A. (1991). The alexithymia construct. A potential paradigm for psychosomatic medicine. Psychosomatics, 32, 153-164. Taylor, G. J., Bagby, R. M., & Parker, J.D.A. (1994). The Revised Toronto Alexithymia Scale: Some reliability, validity, and normative data. Psychotherapy and Psychosomatics, 57, 34-41. Taylor, G. J., Bagby, R. M., Ryan, D. P., Parker, J. D., Doody, K. F., & Keefe, P. (1988, September-October). Criterion validity of the Toronto Alexithymia Scale. Psychosomatic Medi­ cine, 50, 500-509. Taylor, G., & Doody, K. (1982). Psychopathology and verbal expression in psychosomatic and psychoneurotic patients. Psychotherapy and Psychosomatics, 38, 121-127. Taylor, G. J., & Doody, K. (1985). Verbal measures of alexithymia: What do they measure. Psycho­ therapy and Psychosomatics, 43, 32-37. Taylor, G., Doody, K., & Newman, A. (1981). Alexithymic characteristics in patients with inflam­ matory bowel disease. Canadian Journal o f Psychiatry, 26, 470-474. Taylor, G. J., Parker, J.D.A., & Bagby, R. M. (1990). A preliminary investigation of alexithymia in men with psychoactive substance dependence. American Journal o f Psychiatry, 147, 1228-1230. Taylor, G. J., Ryan, D., & Bagby, R. M. (1985). Toward the development of a new self-report alexithymia scale. Psychotherapy and Psychosomatics, 44, 191-199. TenHouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1985a). Alexithymia and the split brain: Lexical-level content analysis. Psychotherapy and Psychosomatics, 43, 202-208. TenHouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1985b). Alexithymia and the split brain: Sentential-level content analysis. Psychotherapy and Psychosomatics, 44, 1-5. Tenhouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1985c). Alexithymia and the split brain: Global-level content analysis of fantasy and symbolization. Psychotherapy and Psycho­ somatics, 44, 89-94. TenHouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1985d). Alexithymia and the split brain: Gottschalk-Gleser content analysis, an overview. Psychotherapy and Psychosomatics, 44, 113-121. TenHouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1986). Alexithymia: An experi­ mental study of cerebral commissurotomy patients and normal control subjects. American Jour­ nal o f Psychiatry, 143, 312-316. TenHouten, W. D., Hoppe, K. D., Bogen, J. E., & Walter, D. O. (1987). Alexithymia and the split brain: EEG alpha-band interhemispheric coherence analysis. Psychotherapy and Psychosomatics, 47, 1-10. Vollhardt, B. R., Ackerman, S. H., & Shindeldecker, R. D. (1986). Verbal expression of affect in

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4

Relations Between Mood and Personality: Findings From the Israeli Mood Studies

Moshe Alm agor University o f Haifa

Yossef S. Ben-Porath Kent State University

During the past 10 years, Almagor and his colleagues (Almagor, 1993; Almagor & Ben-Porath, 1989, 1990; Almagor & Ehrlich, 1990) have conducted a series of studies on the structure and correlates of mood. The purpose of this chapter is to integrate findings from these investigations, which we term The Israeli Mood Studies, within the broader context of mood research, and to present additional, unpublished data from these studies. We begin with research into the fundamental structure of mood as measured by adjective checklists. We then turn to the identification of personality corre­ lates of mood level and fluctuation, and review studies of intrapersonal mood variation and its correlates. We end this chapter with an attempt to identify several conclusions and directions for future research suggested by the Israeli Mood Studies.

THE STRUCTURE OF MOOD Several studies of the structure and nature of self-reported mood have demon­ strated the existence of two broad, bipolar dimensions: Positive and Negative Affect (Diener & Emmons, 1984; Gotlib & Meyer, 1986; Tellegen, 1985; Wat­ son, 1988a, 1988b; Watson & Tellegen, 1985; Zevon & Tellegen, 1982). Positive Affect represents the extent to which an individual avows a zest for life. A person experiencing high Positive Affect is characterized as being attentive, interested, alert, and enthusiastic, whereas a person experiencing low Positive Affect is described as being sleepy and tired. Negative Affect reflects the extent to which a

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person conveys feelings of distress and unpleasant arousal. Persons high in Negative Affect describe themselves as fearful, hostile, angry, and guilty, where­ as those with low Negative Affect tend to report being calm and content. The two mood dimensions conform closely to the natural configuration of common mood descriptors (Zevon & Tellegen, 1982), and are suggested to be related to primary and higher order personality factors (Tellegen, 1985). They have also been repli­ cated across cultures (Watson, Clark, & Tellegen, 1984). Clark and Watson (1988) studied relations between mood and daily social activity and found that pleasurable social events (e.g., parties) are strongly associated with Positive Affect. Negative Affect has been found to be asso­ ciated with self-reported health complaints (e.g., Costa & McCrae, 1987, 1989; Vassend, 1989; Watson, 1988b) and perceived stress (Watson, 1988b; Watson & Clark, 1984), whereas Positive Affect has not. These two factors also help distinguish between measures of Anxiety and Depression (Tellegen, 1985). Alternative models of mood have been proposed by Russell (1978, 1979, 1980), whose model also includes two dimensions: Degree of Arousal and Pleasantness-unpleasantness. Larsen and Diener (1985) proposed a similar mod­ el, in which two affective dimensions are included: Intensity, which refers to intensity of the experienced emotion, and Hedonic level, consisting of Positive and Negative Affect terms that form a bipolar Pleasantness factor. Watson and Tellegen (1985) demonstrated that these factors are included in the 45-degree rotation of their model, and essentially these factors are a mixture of Negative and Positive Affect as described by Tellegen (1985). Our own research has helped shed some light on the issue of the structure of mood. Following Watson et al., (1984), who were able to replicate the twodimensional mood model in Japan using the Japanese language, we sought to determine whether this model can also be replicated in Israel using the Hebrew language. Cross-cultural replication can lend support to the construct validity of a psychological model if it is hypothesized, as Tellegen (1985) has, that the underlying constructs of the model reflect universal, biologically founded sys­ tems. Almagor and Ben-Porath (1989) translated the Mood Adjective Checklist developed by Zevon and Tellegen (1982) into Hebrew, and thus were able, in a series of factor analyses, to replicate the basic two-dimensional model of Positive and Negative Affect. Moreover, they reported findings that concurred with those of Watson and Tellegen (1985), indicating that a 45-degree rotation of Positive and Negative Affect was able to account for several alternative models discussed earlier in this chapter. Almagor and Ben-Porath’s (1989) successful replication of the two-dimensional mood model also allowed Almagor and his colleagues to use the translated mood checklist in a series of studies described next in this chapter.

THE TW O-DIMENSIONAL MODEL OF MOOD AND PERSONALITY The Negative and Positive Affect dimensions described originally by Zevon and Tellegen (1982) form a two-dimensional sphere that divides into four quadrants. These quadrants fit with the four traditional temperamental types: (a) Choleric, characterized by emotional lability and quick temper; (b) Phlegmatic, described as being sluggish, tired, and sleepy; (c) Sanguine, identified, among other attri­ butes, by the adjective sociable; and (d) Melancholic, characterized by the adjectives depressed, gloomy, and suspicious. Hepburn and Eysenck (1989) cited Wundt (1903), who argued that the Choleric and Melancholic types tend to have strong affect, whereas the Sanguine and Phlegmatic types tend to be less emo­ tionally intense. Hepburn and Eysenck located these four affective types on two axes: Extraversion-Introversion and Stable-Unstable. The Choleric and San­ guine affective types are suggested to correspond to Extraversion, the former being less stable than the latter. The Melancholic and Phlegmatic types are proposed to correspond to the personality type of Introversion, again, the former being less stable than the latter. As just reviewed, Watson and Tellegen (1985) and Almagor and Ben-Porath (1989) demonstrated how various mood models can be accommodated by a 45degree rotation of Positive and Negative Affect (PA and NA). Thus, the model proposed by Hepburn and Eysenck (1989) can likely be accommodated by the bidimensional mood model. Using this model, a number of investigators have studied the relation between mood and personality. Meyer and Schack (1989) and Williams (1990) found that NA is closely related to the Neuroticism dimension of the Eysenck Personality Inventory (EPI), whereas PA is closely related to Extroversion. Almagor and Ehrlich (1990) showed that PA is positively related to Well-Being, Social Closeness, Social Potency, and Absorption scales of the Multidimensional Personality Question­ naire (MPQ; Tellegen, 1982), whereas NA is positively correlated with Stress Reaction, Alienation, and Aggression scales. Additionally, PA was positively correlated with Tellegen’s (1982) higher order Positive Emotionality factor, whereas NA was correlated with the higher order Negative Emotionality factor. These findings provide further empirical support for Tellegen’s (1985) proposal that the two mood dimensions are related to underlying personality traits. However, some investigators have proposed that the pattern of relations be­ tween mood and personality is not as clear as was suggested by the studies just cited. Diener, Larsen, and Emmons (1984) conducted a study investigating rela­ tions between the EPI and Jackson’s Personality Research Form and PA and NA. They concluded that the relations between mood and personality are not consis­ tent. However, in a later study using mood scores averaged over a longer period of time, Emmons and Diener (1986) found a significant correlation between PA

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and Extraversion and between NA and Neuroticism, as predicted by Tellegen (1985). Hepburn and Eysenck (1989) studied relations between PA and NA, the Eysenck Personality Questionnaire (EPQ; Eysenck & Eysenck, 1975), Tellegen’s Multidimensional Personality Questionnaire (MPQ; Tellegen, 1982), the M ariow e-Crow ne Social Desirability Scale (M -C-SO S; Crowne & Marlowe, 1964), and the Impulsiveness Venturesomeness Empathy Questionnaire (IVE; Eysenck & Eysenck, 1978). They used Zevon and Tellegen’s (1982) PA and NA markers as mood indicators and measured average mood and mood variability. These authors found that mean overall mood and mean PA were positively correlated with Extraversion. Neuroticism was correlated with NA, but not with mood level. Unfortunately, this important study used a small number of subjects and a multiplicity of measures, suggesting the need for replication of the find­ ings. Using data collected over the course of the Israeli Mood Studies, we seek here to provide further information on the relations between mood and personality. In addition to looking at mean level of mood across a given time period, we also examine intrasubject mood variability. We describe the methodology used to collect these data in some detail because it is essentially identical to that used in all of the Israeli Mood Studies. The subjects for these analyses were 50 women and 67 men. Of the women, 20 were undergraduate students and 30 were technicians at a high-tech industrial plant in Israel. Their ages ranged from 18 to 47 years (M = 26.2, SD = 6.03). The men were undergraduate students, and their ages ranged from 18 to 55 (M = 25.5, SD = 7.2). The men and women did not differ significantly in age. The measures used for this study were the following. The M ood Checklist is a self-report instrument constructed by Tellegen (1980) that has been used in a number of studies (e.g., Almagor & Ben-Porath, 1989, 1990; Watson & Tell­ egen, 1985; Zevon & Tellegen, 1982). The measure was translated to Hebrew by Almagor and Ben-Porath (1989), as described earlier. The PA and NA factors were scored in the present study according to weights derived for Israeli subjects in Almagor and Ben-Porath’s cross-cultural replication study. The Multidimen­ sional Personality Questionnaire (MPQ; Tellegen, 1982) is a 300-item self-report personality inventory that was developed through an iterative factor-analytic procedure, resulting in the construction of 11 primary (lower order) scales: WellBeing, Social Potency, Achievement, Social Closeness, Stress Reaction, Aliena­ tion, Aggression, Control, Harm Avoidance, Traditionalism, and Absorption. Three higher order factors emerged from factor analyses of the primary MPQ scales: Positive Emotionality, Negative Emotionality, and Constraint. The WellBeing, Social Potency, and Achievement scales are primarily associated with Positive Emotionality; the Stress Reaction, Alienation, and Aggression scales are associated with Negative Emotionality; and Control, Harm Avoidance, and Tra­ ditionalism are associated with Constraint. Tellegen (1982) presented data docu­

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menting the scales’ convergent and discriminant validity, test-retest reliability, and internal consistency. Ben-Porath, Almagor, Tellegen, and Hoffman-Chemi (in press) translated and validated the MPQ for Israeli subjects. Over a period of 45 consecutive days, subjects filled out the mood checklist daily— 2 days in the morning and the following 2 days in the afternoon. Subjects were given 3-day supplies of the checklist, which were returned to a prearranged location. At this point, a new 3-day supply was issued. In addition (and by agreement), research assistants called the subjects daily to remind them to fill out the checklist. Prior to starting their participation, subjects read and signed a consent form that described the study as a study of mood changes over time and personality. The first step in data analysis included analyzing the entire dataset using principal component factor analysis, with squared multiple correlation as communality estimates followed by a varimax rotation. Two major factors were extracted, PA and NA, accounting for over 70% of the total variance. The mean factor scores across the 45-day period for PA and NA served as an index for mood level. Pearson product-m om ent correlation coefficients were computed between the MPQ scales and PA and NA mean scores. The correlations were tested for statistical significance using the Bonferroni correction. The results indicated that PA scores were positively correlated with Well-Being (r = .39, p < .007), Social Closeness (r = .25, p < .004), and Traditionalism (r = .41, p < .007). NA scores were positively correlated with Stress Reaction (r = .28, p < .004), Aggression (r = .40, p < .007), and Negative Emotionality (r = .42, p < .007). The pattern of correlations found in this study indicates that PA is related to traits associated with Tellegen’s Positive Emotionality and Eysenck’s Extraver­ sion, whereas NA is related to traits associated with Tellegen’s Negative Emo­ tionality and Eysenck’s Neuroticism. Replication of these patterns in a different culture lends further support to Tellegen’s (1985) proposal that PA and NA represent affective states that are manifestations of the underlying organismic personality traits of Positive and Negative Emotionality.

MOOD FLUCTUATION STUDIES The research just described confirms that individuals’ overall mood levels are related to underlying personality traits. Another important aspect of mood is the way in which it tends to fluctuate. Two types of mood fluctuation have been studied: (a) Intraperson mood variability, which refers to the amount of fluctua­ tion a person experiences over time and may reflect a personal disposition; and (b) time-delineated mood variation, which relates to patterns of change that occur in mood over a specific time period.

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Intraperson Mood Variability Campbell, Chew, and Scratchley (1991) found that self-esteem was negatively correlated with mood variability. Cowdry, Gardner, O ’Leary, Leibenluft, and Rubinow (1991) found that patients diagnosed as having major depression varied less than those diagnosed with borderline personality disorder or those with premenstrual syndrome (PMS) on mood measures. With respect to mood variability, Eysenck and Eysenck (1985) predicted that Neuroticism is related to mood changes from neutral to negative, whereas Extra­ version is related to changes from neutral to positive. This prediction was based on the assumption that persons with high PA are more likely to shift from neutral to positive emotional states, whereas those with high NA are less likely to do the same. These tendencies characterized Extraversion and Neuroticism, respec­ tively. Operationally,. this means that variability of PA will be correlated with Extraversion, whereas variability of NA will correlate with Neuroticism. These predictions were supported by Hepburn and Eysenck (1989), who found that Extraversion was positively associated with variability of PA, NA, and overall mood variability. Neuroticism was associated with the variability of NA and overall mood variability, but not with variability of PA. Williams (1990) used various affect measures and found that both Extraver­ sion and Neuroticism correlated with the variability of both PA and NA. W il­ liams concluded that neurotic introverts showed more variation around a more negative mood level than did stable extraverts. Using the same dataset described earlier, we sought to examine the relation­ ship between variability in PA and NA across a 45-day period and the personality traits measured by the MPQ (Tellegen, 1982). Thus, for each of our 117 subjects, we computed a variability score on PA and NA, which consisted of their variance on each of these scales, respectively, over the course of the study. We found that variability in NA correlated positively with the higher order Negative Emo­ tionality factor of the MPQ (r = .26, p < .004) and negatively with Constraint (r = - . 2 7 , p < .007). Variability in PA did not correlate with any of the personality measures. The pattern emerging from studies on mood variability is that variability of NA is associated consistently with Negative Emotionality or Neuroticism. That is, individuals who at the trait level are higher than others on Negative Emo­ tionality tend to experience greater fluctuations in NA, as well as an overall higher level of NA. There are some indications that greater variability in NA is also associated with lower levels of Control or Constraint. The personality corre­ lates of variability in PA are less consistent and require further investigation. Time-Delineated Mood Variation The second aspect of mood fluctuation relates to mood changes over a con­ stricted period of time. Several studies have been conducted in this area. Wess-

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man and Ricks (1966) and Stone, Hedges, Neale, and Satin (1985) studied mood variability across the days of the week and failed to find evidence of a consistent pattern. However, Almagor and Ehrlich (1990) found that men tend to vary in a consistent and predictable manner over the days of the week. They studied 68 men over a 28-day period. Using a spectral analysis method (Chatfield, 1975), Almagor and Ehrlich were able to detect a significant 7-day cycle for both PA and NA, with a 3-day lag between two mood dimensions. PA tended to peak toward the end of the week, whereas NA peaked during the beginning of the week. These trends are consistent with the colloquial notion of “Blue Monday.” A similar pattern was reported earlier by Rossi and Rossi (1977). Time-delineated mood variation in women was a topic of investigation in one of the Israeli Mood Studies. Using a methodology similar to the one used by Almagor and Ehrlich (1990), Almagor and Ben-Porath (1990) investigated mood fluctuations during the menstrual cycle and the effect of oral contraceptives on these fluctuations. They found that oral contraceptive users experience a higher level of PA during the cycle than do nonusers; no differences were found with respect to NA. No cyclic variations were detected for PA and NA during the menstrual period. Some investigators (Lahmeyer, Miller, & DeLeon-Jones, 1981; Parlee, 1973; Slade, 1984) have questioned the existence of menstrually related emotional effects. However, others (e.g., McFarlane, Martin, & W illiams, 1988) have found an increase in PA during follicular and ovulatory phases of the menstrual cycle. Almagor and Ben-Porath (1990) did not find between-phase differences during the cycle for both users and nonusers of oral contraceptives. With respect to premenstrual affective effects, some retrospective studies (e.g., Endicott & Halbreich, 1982) have found an increase in NA during this phase of the cycle. However, prospective studies (e.g., Almagor & Ben-Porath, 1990; McFarlane et al., 1988) have not detected such changes. A final area of time-delineated mood variation involves studies of diurnal variation in PA and NA. Benoit, Foret, Merle, and Reinberg (1981) found that changes in mood and vigilance were associated with sleep-w ake rhythms. Thayer (1978) found that variation on the Activation factor was similar to that of body temperature. The peak in Activation occurred during the late morning hours, with a secondary peak during late afternoon hours. The Activation factor is marked by adjectives such as lively, active, fu ll o f pep, energetic, peppy, vigorous, and activated, and is thus similar to PA. Monk, Fookson, Moline, and Poliak (1985) studied circadian mood rhythms during temporal isolation, and found significant time effects for alertness, sleepiness, happiness, and well­ being. Taub and Berger (1972) studied the phenomenon in males using the M cN air-Lorr Adjective Check-List (McNair & Lorr, 1964). They collected data at 8:30 a.m ., 12:30 p.m ., and 5:30 p.m ., and found that concentration, activity, and friendliness increased from morning to noon, whereas fatigue and depression decreased toward the afternoon. Taub and Berger (1974) found that disturbance

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of sleep caused deficits in mood and performance. Elsas, Mellerup, Rafaelsen, and Theilgaard (cited in Pollitt, 1982) found that healthy individuals feel more cheerful either in the afternoon or evening, or alternatively in the mornings. A final phase of the Israeli Mood Studies focused on the issue of diurnal mood variation. Almagor (1993) conducted two studies of mood variation over the waking hours. The first used 186 subjects, and a between-subject design was employed. This study indicated a significant reduction in PA during the early afternoon hours, followed by an increase in NA. The second experiment used a within-subject design and 51 subjects, and revealed a similar pattern. One of the more interesting findings was a consistent pattern in both studies indicating a decrease in PA and an increase in NA during the afternoon hours. This finding was interpreted as reflecting the “siesta effect,” which is common in many warmer climates around the world. These findings are consistent with Lavie’s (1986) “gate theory of sleep.” According to this theory, there are two periods during the day in which a person can most easily fall asleep should he or she choose to do so, while this is almost impossible at other times. The gates for sleep occur in the afternoon and late at night; in contrast, it is difficult to fall asleep in the morning (e.g., 10 a.m .) or the evening (e.g., 7 p.m.). Lavie (1986) suggested that the gate phenomenon is related to biological factors because it behaves much like an endogenous rhythm. A final set of analyses conducted by Almagor (1993) sought to investigate individual differences in the siesta effect. A common colloquial differentiation is made between “morning people” and “night people.” Home and Ostenberg (1976) constructed a Momingness Eveningness Questionnaire (MEQ) that can be used to classify subjects into morning, neutral, and evening types. Almagor (1993) administered this questionnaire to subjects in his diurnal mood variation study, and identified 15 morning types, 17 neutral types, and 16 evening types. He then conducted a two-factor analysis of variance (ANOVA), with Time of Day and Subject Type as factors. Almagor found that for PA, both factors had a significant effect [F (l,2 ) = 8.52, p < .0002 for type, and F (l,1 7 ) = 9.21, p < .0001 for hour]. A post hoc Tukey analysis indicated that the morning and evening groups differed significantly from each other and the morning group differed from the neutral group, but the night group did not differ significantly from the neutral group. The differences between the morning and night group clustered between 7 a.m. to 9 a.m. and 10 p.m. to midnight. There were no significant effects for type or hour for NA and no interaction. Overall, Alm agor’s study indicated that both PA and NA demonstrated diur­ nal variation patterns. However, individual differences were found only for PA. This suggests that diurnal variation in NA may be tied directly to circadian patterns that are independent of other systems, whereas diurnal variation in PA is more complex, involving individual differences in behavioral activation patterns. Further research in this area might focus on identifying neurochemical correlates of these patterns.

SUM M ARY OF THE ISRAELI MOOD STUDIES The Israeli Mood Studies have yielded a number of findings that help to elucidate the phenomenon of mood. First, Almagor and Ben-Porath (1989) were able to replicate Zevon and Tellegen’s (1982) mood model across language and cul­ ture. Coupled with the Watson et al. (1984) findings in Japan, these results provide support for Tellegen’s (1985) suggestion that PA and NA are mood manifestations of underlying organismic traits that should be found universally. Additionally, successful replication of the model allowed Almagor and his colleagues to use the translated mood checklist in a number of subsequent studies. A second study focused further on Tellegen’s suggestion that PA and NA represent mood manifestations of underlying trait dimensions that he termed Positive and Negative Emotionality. Unpublished data from the Israeli Mood Studies reported in this chapter provide clear support for this theory. Individual differences in mean level of PA and NA across a 45-day period were correlated in the predicted direction with scores on Tellegen’s scales of Positive and Negative Emotionality. The Israeli Mood Studies also focused on the phenomenon of mood fluctua­ tion. Intrapersonal mood variability (i.e., the tendency to experience greater variability in mood over a certain period of time) was discussed first. Un­ published data reported in this chapter indicate that variability in NA is associ­ ated consistently with Negative Emotionality or Neuroticism. That is, individu­ als who at the trait level are higher than others on Negative Emotionality tend to experience greater fluctuations in NA, as well as an overall higher level of NA. The personality correlates of variability in PA are less consistent and require further investigation. A final set of studies focused on time-delineated mood variability. Almagor and Ehrlich (1990) found a “day of the week effect,” whereby PA reached its peak at the beginning of the weekend and NA peaked during the first part of the week. Almagor and Ben-Porath did not find menstrual cycle-related mood fluc­ tuation in women, regardless of whether they used oral contraceptives, although they did find that, overall, oral contraceptive users were higher in PA than nonusers when averaged across the menstrual cycle. No differences were found for NA. Finally, Almagor (1993) found that both PA and NA tend to fluctuate in predictable patterns across different hours of the day. However, individual differ­ ences in these patterns were found only for PA. Overall, the Israeli Mood Studies have provided considerable support for Tellegen’s (1985) mood theory. These studies point to the existence of two robust mood dimensions that can be replicated across cultures and languages. PA and NA show individual patterns of level and fluctuation that suggest that they may be tied, at least in part, to biologically based systems. Further study is needed in this area to delineate the nature of these biological systems, and the ways in

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which they interact with psychosocial variables to yield normal and abnormal mood phenomena.

REFERENCES Almagor, M. (1993). Individual differences in diurnal mood variation. Manuscript submitted for publication. Almagor, M., & Ben-Porath, Y. S. (1989). The two-factor model of self reported mood: A cross cultural replication. Journal of Personality Assessment, 53, 10-21. Almagor, M., & Ben-Porath, Y. S. (1990). Mood fluctuations during the menstrual cycle: The effect of use of oral contraceptives. Journal o f Psychosomatic Research, 35, 721-728. Almagor, M., & Ehrlich, S. (1990). Personality correlates and cyclicity in Positive and Negative Affect. Psychological Reports, 66, 1159-1169. Benoit, O ., Foret, J., Merle, B., & Reinberg, A. (1981). Circadian rhythms of short and long sleepers: Effects of sleep deprivation. Chronobiologia, 8, 341-350. Ben-Porath, Y. S., Almagor, M ., Tellegen, A., & Chemi-Hoffman, A. (in press). A cross-cultural study of the Multidimensional Personality Questionnaire. Journal o f Cross-Cultural Psychology. Campbell, J. D., Chew, B., & Scratchley, L. S. (1991). Cognitive and emotional reactions to daily events: The effects of self esteem and self complexity. Journal o f Personality, 59, 474-505. Chatfield, C. (1975). The analysis o f time series: Theory and practice. London: Chapman and Hall. Clark, L. A ., & Watson, D. (1988). Mood and the mundane: Relations between daily life events and self reported mood. Journal o f Personality and Social Psychology, 54, 296-308. Costa, P. T., & McCrae, R. R. (1987). Hypochondriasis, neuroticism, and aging: When are somatic complaints unfounded? American Psychologist, 40, 19-28. Costa, P. T., & McCrae, R. R. (1989). Neuroticism, somatic complaints, and disease: Is the bark worse than the bite? Journal o f Personality, 55, 299-316. Cowdry, R. W., Gardner, D. L., O ’Leary, K. M., Leibenluft, E., & Rubinow, D. R. (1991). Mood variability: A study of four groups. American Journal of Psychiatry, 148, 1505-1511. Crowne, D. P., & Marlowe, D. (1964). The approval motive: Studies in emotional dependence. New York: Wiley. Diener, E ., & Emmons, R. A. (1984). The independence of positive and negative affect. Journal of Personality and Social Psychology, 47, 1105-1117. Diener, E., Larsen, R. J., & Emmons, R. A. (1984). Person X situation interactions: Choice of situations and congruence models. Journal o f Personality and Social Psychology, 47, 1105-1117. Emmons, R. A., & Diener, E. (1986). Influence of impulsivity and sociability on subjective well­ being. Journal of Personality and Social Psychology, 50, 89-97. Endicoot, J ., & Halbreich, U. (1982). Psychobiology of premenstrual change. Psychopharmacology Bulletin, 18, 109-112. Eysenck, H. J ., & Eysenck, S.B.J. (1975). Manual fo r the Eysenck Personality Questionnaire. San Diego: Educational and Industrial Testing Service. Eysenck, H. J., & Eysenck, S.B.J. (1978). Manual fo r the Impulsiveness Venturesomeness Empathy Questionnaire. San Diego: Educational and Industrial Testing Service. Eysenck, H. J., & Eysenck, M. W. (1985). Personality and individual differences. New York: Plenum. Gotlib, I. H ., & Meyer, J. P. (1986). Factor analysis of the Multiple Affect Check List: A separation of positive and negative affect. Journal of Personality and Social Psychology, 50, 1161-1165. Hepburn, L., & Eysenck, M. W. (1989). Personality, average mood and mood variability. Person­ ality and Individual Differences, 10, 975-983.

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Home, J. A., & Ostenberg, O. (1976). A self-assessment questionnaire to determine momingnesseveningness in human circadian rhythms. International Journal o f Chronobiology, 4, 97-110. Lahmeyer, W. H., Miller, M., & DeLeon-Jones, F. (1981). Anxiety and mood fluctuation during the normal menstrual period. Psychosomatic Medicine, 44, 183-194. Larsen, R. J., & Diener, E. (1985). A multitrait-multimethod examination of affect structure: He­ donic level and emotional intensity. Personality and Individual Differences, 6, 631-636. Lavie, P. (1986). Ultrashort sleep-waking schedules: III. Gates and the forbidden zones for sleep. EEG and Clinical Neurophysiology, 63, 414-425. McFarlane, J., Martin, C. L., & Williams, T. L. (1988). Mood fluctuations: Women versus men and menstrual versus cycles. Psychology o f Women Quarterly, 12, 201-223. McNair, D. M., & Lorr, M. (1964). An analysis of mood in neurotics. Journal o f Abnormal and Social Psychology, 69, 620-625. Meyer, G. J., & Schack, J. R. (1989). Structural convergence of mood and personality: Evidence for old and new directions. Journal o f Personality and Social Psychology, 57, 691-706. Monk, T. H., Fookson, J. E., Moline, M. L., & Poliak, C. P. (1985). Diumal variation in mood and performance in a time-isolated environment. Chronobiology International, 2, 185-193. Parlee, M. B. (1973). The premenstrual syndrome. Psychological Bulletin, 80, 454-465. Pollitt, J. (1982). Moodiness: A heavenly problem? Observations on the pathology of moodiness. Journal o f the Royal Society o f Medicine, 75, 7-16. Rossi, A. S., & Rossi, P. E. (1977). Body time and social time: Mood patterns by menstrual cycle and day of the week. Social Science Research, 6, 273-308. Russell, J. A. (1978). Evidence of convergent validity on the dimensions of affect. Journal of Personality and Social Psychology, 36, 1152-1168. Russell, J. A. (1979). Affective space is bipolar. Journal o f Personality and Social Psychology, 37, 1161-1178. Russell, J. A. (1980). A circumplex model of affect. Journal o f Personality and Social Psychology, 39, 1161-1178. Slade, P. (1984). Premenstrual emotional changes in normal women: Fact or fiction? Journal of Psychosomatic Research, 24, 1-7. Stone, A. A., Hedges, S. M., Neale, J. M., & Satin, M. S. (1985). Prospective and cross-sectional mood reports offer no evidence of a “Blue Monday” phenomenon. Journal o f Personality and Social Psychology, 49, 129-134. Taub, J. M., & Berger, R. J. (1972). Diumal variation in mood as assessed by self-report and content analysis. Journal of Psychiatry Research, 10, 83-88. Taub, J. M ., & Berger, R. J. (1974). Acute shifts in the sleep-wakefulness cycle: Effects on performance and mood. Psychosomatic Medicine, 36, 164-173. Tellegen, A. (1982). Belief manual for the Multidimensional Personality Questionnaire. Un­ published manuscript, University of Minnesota, Minneapolis, MN. Tellegen, A. (1985). Structures of mood and personality and their relevance to assessing anxiety, with an emphasis on self report. In A. H. Tuma & J. D. Maser (Eds.), Anxiety and the anxiety disorders (pp. 681-706). Hillsdale, NJ: Lawrence Erlbaum Associates. Thayer, R. E. (1978). Toward a psychological theory of multidimensional activation (Arousal). Motivation & Emotion, 2, 1-34. Vassend, O. (1989). Dimensions of negative affectivity, self reported somatic symptoms, and health related behaviors. Social Science Medicine, 28, 29-36. Watson, D. (1988a). The vicissitudes of mood measurement: Effects of varying descriptors, time frames, and response formats on measures of positive and negative affect. Journal o f Personality and Social Psychology, 55, 128-141. Watson, D. (1988b). Intraindividual and interindividual analyses of positive and negative affect: Their relation to health complaints, perceived stress, and daily activities. Journal of Personality and Social Psychology, 54, 1020-1030.

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Watson, D., & Clark, L. A. (1984). Negative affectivity: The disposition to experience negative emotional states. Psychological Bulletin, 96, 465-490. Watson, D., Clark, L. A., & Tellegen, A. (1984). Cross-cultural convergence in the structure of mood: A Japanese replication and a comparison with U.S. findings. Journal o f Personality and Social Psychology, 47, 127-144. Watson, D ., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219-235. Wessman, A. E., & Ricks, D. F. (1966). Mood and personality. New York: Holt, Reinhart, & Winston. Williams, D. G. (1989). Personality effects in current mood: Pervasive or reactive? Personality and Individual Differences, 10, 941-948. Zevon, M. A., & Tellegen, A. (1982). The structure of mood change: An idiographic/nomothetic analysis. Journal of Personality and Social Psychology, 43, 111-122.

5

A Comparison of the Benefits of Two Therapeutic Community Treatment Regimens for Inner-City Substance Abusers

Samuel Karson Robert V. Gesumaria Second Genesis, !nc.f Bethesda, M aryland

Although residential treatment in therapeutic communities for chronic substance abusers has been described as cost-effective for clients who graduate or remain in the program for at least 3 -6 months (Gerstein & Harwood, 1990; Hubbard, Marsden, Rachal, Harwood, Cavanaugh, & Ginzburg, 1989; Simpson, 1981), many questions remain about how treatment outcomes can be improved. Toward this end, studies have aimed at predicting early dropouts (Craig, 1985; DeLeon, 1989), reducing relapse rates (Donovan & Marlatt, 1988), and matching treat­ ment programs more closely to client circumstances, motivation, readiness, and suitability for treatment (DeLeon & Jainchill, 1986) to increase time in treat­ ment, which is currently regarded as the best predictor of outcome at follow-up (DeLeon, 1989). This study was another step toward maximizing treatment and cost-effectiveness by comparing a well-established, standard therapeutic community at Har­ vard Street with a newly developed, enhanced therapeutic community known as Second Genesis EAST.1 The former had a standard 10- to 12-month residential component with a 2-month aftercare program, whereas the latter had an experi­ mental 6-month residential phase plus a 6-month continuing care outpatient component.2 The two facilities qualified as therapeutic communities because both empha­ sized the teaching of responsibility and competence within a highly structured, 24-hour-a-day program provided in a drug-free, family milieu that included peer 1 George DeLeon, PhD, and David J. Mactas served as expert consultants in the planning stages of the Second Genesis grant. 2 A description of the two therapeutic communities is available from the authors.

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encounter groups, family therapy, and group counseling, as well as other treat­ ment, educational, and vocational services (DeLeon, 1989). In the early stages of the respective programs, negative reinforcement was used to eliminate undesir­ able behavior; later, positive reinforcement and privileges were used more exten­ sively in both facilities. Nevertheless, there were readily discernible differences between the programs, namely, length of stay and aftercare, and a clinical staffto-client ratio of about 1:7 in the control Harvard Street facility, compared with a 1:4 ratio at the experimental EAST facility. Further, the 64-bed control program, including 14 beds for women, was located in an urban residence in downtown Washington, DC, whereas the 60-bed experimental program, with 20 beds for women, was situated on the St. Elizabeths Hospital campus in southeast D C .3’4 Previously, a standard therapeutic community regimen usually required a 2-year stay for graduation. However, in the past decade, the residential require­ ment has often been shortened to 18 months or, in many instances, to 1 year. When this study began, concern was expressed about compressing the residential treatment phase to 6 months, given the nature of the clientele and their history of chronic substance abuse. Admittedly, the great majority of Second Genesis cli­ ents had a D S M -III-R Axis I diagnosis of either opiate or cocaine dependence, as well as an Axis II diagnosis of antisocial personality disorder (> 50% for males), or less often borderline, passive aggressive, or narcissistic (American Psychiatric Association, 1987). In fact, only 20% of our male sample was not diagnosed as personality disordered according to the Structured Clinical Inter­ view for D SM -III-R (Spitzer, Williams, Gibbon, & First, 1990). In compliance with the ethical guidelines of the American Psychological Association (APA), all clients were briefed on the research status of the two treatment facilities and the random-assignment procedure in their initial interviews. Clients agreed to partic­ ipate only after they were fully informed of their alternatives by admissions counselors. Clients were also briefed on what they would be required to undergo, namely, extensive psychological testing plus interviews and random monthly urine specimens. Moreover, all client tasks used in this study required formal approval by the Second Genesis institutional review board. Furthermore, a certif­ icate of confidentiality was obtained from the National Institute on Drug Abuse (NIDA) to protect the identity of all research participants, over 70% of whom were court referred and the remainder of whom were volunteer self-referrals. 3 Second Genesis has been operating residential, drug-free-therapeutic community facilities for over two decades under the same executive leadership in the greater Washington, DC metropolitan area. 4 A special tribute is owed to the late James B. (Jimmy) Hendricks, regional director of facilities for many years, for having shared his expertise with the authors. Also acknowledged are the contribu­ tions of Barry W. Brown, PhD, the original National Institute of Drug Abuse (NIDA) project officer, and Herman I. Diesenhaus, PhD, the current Center for Substance Abuse Treatment (CSAT) project officer. Appreciation is due to Garry L. Palsgrove, MBA, and Richard Needle, PhD, current NIDA project officers.

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The design also included a 3-month posttreatment follow-up by telephone and/or interview to determine current employment status, posttreatment criminal justice involvement, and current drug and alcohol usage. The present study must be regarded as interim because it was limited to an analysis of the intreatment benefits of the first 6 months of treatment (Howard, Kopta, Krause, & Orlinsky, 1986). As the major hypothesis in this research, the Null hypothesis was tested— namely, there would be no differences found in benefits to male clients when a comparison of the two facilities with different treatment regimens was made after the first 6 months of treatment based on Minnesota Multiphasic Personality Inventory-2 (M M PI-2) test scores, includ­ ing certain supplementary scales.5 Furthermore, did a treatment dosage of 6 months in a therapeutic community result in positive changes in certain MMPI-2 scales described as typical of a large sample of chronic drug abusers at admission on the MMPI (DeLeon, 1989)— specifically, in confusion, psychopathy, aliena­ tion, self-esteem, depression, and anxiety?

SAMPLE The sample consisted of all male clients (N = 116) admitted to either Second Genesis EAST or Harvard Street from February 1992 to January 1993. With one exception, all were African American. Their ages ranged from 20 to 55 (M = 32). They averaged 10 years of schooling, and 40% had a high school diploma (GED) or higher. At admission, 76% were involved with the criminal justice system. Over half had been convicted of drug distribution charges, whereas the rest were convicted of possession of cocaine, narcotics, and other controlled dangerous substances; theft; robbery; assault; breaking and entering; and burgla­ ry. Prior to admission, they averaged six felony arrests, three convictions, and 19 months of incarceration as adults. Eight percent were married, 76% had never married, and the remaining 16% were divorced or separated. Nearly 70% listed cocaine or crack as their primary drug of abuse, and 25% selected heroin and other opiates. Almost 40% reported that at least one parent abused alcohol or drugs, which is often associated with a history of physical and sexual abuse, as well as a broad range of psychological distress in inner-city samples. Given their ages and past histories, it was not surprising that the majority had had previous drug treatment services either as outpatients or as residents for no more than 30 days. However, there were no significant differences between the clients in the two facilities in this respect or on any of the other demographic variables de­ scribed previously. To select measures that could be used appropriately for this sample, the 5 The Second Genesis treatment evaluation battery included the Sixteen Personality Factor Ques­ tionnaire and the Bender-Gestalt Test. These data are currently being analyzed.

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Peabody Reading Comprehension Test, a subtest of the Peabody Individual Achievement Test-Revised (Markwardt, 1989) and the Shipley Institute for Liv­ ing Scale (Zachary, 1991) were administered to incoming clients early during admission and prior to the treatment evaluation battery, namely, the M M PI-2, the 16PF Forms A and B, and the Bender-G estalt Test (BGT; Reichenberg & Raphael, 1992). This battery was given twice: the first time within 5 days of admission, and then repeated within 10 days of their 6-month admission. All testing was accomplished by two m aster’s-level psychometricians, respectively housed in each residential facility. All of the testing was done in small groups except for the BGT, which was administered individually.6 Because Second Genesis had been using both the MMPI and 16PF for over a decade, it was deemed advisable to continue their usage; they were built into the treatment programs to help formulate treatment plans, as an aid in diagnosis and alerting staff to potential suicide attempts, and for studies aimed at predicting retention. Given the low socioeconomic level of the sample and the percentage with poor reading ability, it was apparent that a sizable number of cases from our African-American sample would be eliminated if traditional cutoff scores for identifying invalid tests on Caucasian samples were adhered to strictly. For­ tunately, this problem was dealt with extensively in the new manual for the M M PI-2 (Butcher, Dahlstrom, Graham, Tellegen & Kaemmer, 1989) and in the M M PI-2 literature (Butcher, 1990; Graham, 1990; Greene, 1991). Through a comparison of each questionable M M PI-2 profile with the rest of the peer sample, 19 (16%) cases of the 116 were eliminated. The original sample had a mean score on the Peabody Individual Achievement Test-Revised (PIAT-R) Reading Comprehension Test of 8.68 (SD = 3.53), a mean Shipley Vocabulary raw score of 21.76 (SD — 6.68), and a mean Abstraction raw score of 18.41 (SD = 8.70). This information served to underscore the clients’ need for multiple services, including remedial reading as well as other basic educational and voca­ tional services that were built into the teaching services offered in both programs. On the M M P I-2, the mean consistency raw scores were: Infrequency Scale (F) = 10.29 (SD = 6.67), FB = 8.27 (SD = 5.79), Variable Response Inconistency Scale (VRIN) = 7.62 (SD = 3.67), and True Response Inconsistency Scale (TRIN) = 10.05 (SD = 2.47). After the elimination, the mean consistency raw scores of the sample used in this study were: F = 8.99 (SD = 5.17), Back F (FB) = 7.30 (SD - 4.71), VRIN = 7.18 (SD = 3.42), and TRIN = 9.98 (SD = 2.19). This final sample included only those cases with a raw score on F of less than 25, and a raw score on LIE (L) of less than 9 in both administrations of the M M PI-2, namely, at admission and after 6 months of treatment. In Greene’s (1991) book, a table is given on cutting scores for assessing 6 The Second Genesis battery also included the Porteus Mazes, W eigl-Goldstein-Scheerer Color Form Blocks, Shipley Institute for Living Scale, and the Community-Oriented Programs Environ­ ment Scale.

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113

M M PI-2 validity in psychiatric settings. These data guided the selection of the sample in this research, with specific regard to consistency of item endorsement. Although all clients were randomly assigned from a central intake unit to our two research facilities, as a check on the random-assignment procedure, a one­ way analysis of variance (ANOVA) was performed using the admission M M PI-2 raw scores in both facilities. No significant differences emerged on the 13 basic scales or the 21 supplementary scales. These results suggest that the two client samples were in fact successfully randomly assigned and were drawn from the same pool of drug abusers in the DC area. These findings further indicate that these clients were comparable at admission with regard to severity of psycho­ pathology as measured by the M M PI-2. It was noteworthy that the 6-month retention rates were 69 out of 100 (69%) for the control Harvard Street facility, and 96 out of 126 (76%) for the experimental EAST facility, not significantly different by chi-square (1.46).

RESULTS AND DISCUSSION On two specified occasions, M M PI-2 test data for both treatment groups were collected in each facility, yielding one admission score and one 6-month treat­ ment dosage score for each client. The main hypothesis of the study was tested by the multivariate interaction effects of treatment regimen by time, and the secondary hypothesis was tested by the main effects of time (pre- and posttreat­ ment with both groups combined) when two separate 2 x 2 multivariate analyses of variance (MANOVAs; experimental, standard regimen x pre- and posttreat­ ment) were performed on the basic M M PI-2 clinical scales and the supplemen­ tary scales. The multivariate interaction effects of treatment regimen by time were not significant: F(13, 83) = 1 . 1 2 and F (21, 75) = .74 for either of the two sets of scales, respectively. However, the main effects of time were highly significant: F(13, 83) = 5.03, p < .001 and F(21, 75) = 6.56, p < .001. The results justified doing univariate repeated-measures ANOVAs on the individual scales to examine the main effects of time, but not for the interaction effects of regimen by time. Subsequently, one-way univariate repeated-measures ANOVAs were done separately for each basic clinical and supplementary scale. The magnitude of the changes that occurred consequent to treatment was determined by calculating effect sizes for each M M PI-2 scale. Specifically, in Tables 5 .1 -5 .6 , which demonstrate the main effect of change over time, effect sizes are calculated by dividing the difference between the admission and 6-month scores for each scale by the pooled standard deviation of the scores of both groups at admission. The results indicate that when both samples were combined and the M M PI-2 changes after 6 months of treatment were analyzed, 9 of the 13 scales changed significantly. The largest changes occurred on scales Pt and Pd, as indicated by

114

KARSON A N D G ESUM AR IA TABLE 5.1 Comparison of MMPI-2 Test-Retest at Both Facilities Combined

1st Raw Score

Scale

3.64 8.99 11.78 7.52 21.59 19.49 24.37 25.33 12.54 19.75 22.25 23.25 28.56

L F K Hs D Hy Pd Mf Pa Pt Sc Ma Si

Mean T-Score

SD

2nd Raw Score

Mean T-Score

52 64 43 54 59 47 64 48 61 62 63 62 54

2.09 5.17 4.30 4.10 5.36 5.08 3.85 4.50 4.14 8.12 9.20 4.24 7.87

4.02 7.95 13.49 6.57 19.23 18.57 22.42 25.25 11.58 15.51 18.02 22.71 26.75

52 61 47 54 52 45 62 48 57 57 60 62 51

SD

2.06 5.35 4.52 4.32 4.54 4.73 3.82 4.28 3.68 7.43 9.43 4.43 8.15

( N =

97)

F(1, 95)

3.48 6.52* 22.25*** 5.69* 26.64*** 2.85 17.37*** .04 6.29* 47.59*** 30.17*** 1.41 7.64**

Effect Size

.18 .20 .40 .23 .44 .18 .51 .02 .23 .52 .46 .13 .23

* p < .05; * * p < .01; * * * p < .001.

their medium effect sizes given in Table 5.1. The next largest changes occurred on Sc, D, and K, as indicated by their respective effect sizes, followed by smaller effect size changes on Hs, Pa, Si, and F. In terms of clinically, as opposed to statistically, significant T-scale changes, as suggested by Greene (1988), only D and Pt showed 5-point scale reductions, while K and Pa just missed. Nonethe-

TABLE 5.2 Comparison of MMPI-2 Supplementary Scales at Both Facilities Combined ( N= 97)

Scale

ANX FRS OBS DEP HEA BiZ ANG CYN ASP TPA LSE SOD FAM WRK TRT ES MAC-R RE APS AAS MA1

1st Raw Score

9.28 6.80 7.55 11.00 8.48 6.59 8.31 15.88 14.65 9.38 7.26 8.41 8.99 11.82 8.14 31.42 29.30 14.01 25.12 6.23 3.55

Mean T-Score

SD

2nd Raw Score

Mean T-Score

57 60 59 63 58 67 56 62 69 50 57 50 60 59 59 36 67 34 54 65 66

4.46 3.12 3.48 4.63 4.57 3.97 3.28 3.60 3.28 3.53 4.56 4.17 3.66 5.55 4.15 5.19 3.76 3.82 3.66 2.02 1.28

7.52 6.68 6.82 8.25 7.91 4.58 7.80 14.23 13.62 9.43 5.73 7.87 8.36 9.56 7.01 34.31 28.84 14.40 24.11 5.44 3.25

55 60 56 58 58 60 56 56 65 50 55 50 57 56 56 42 67 34 52 60 58

* p < .05; * * p < .01; * ** p < .0 0 1 .

SD

4.07 3.68 3.81 4.61 4.72 3.42 3.13 4.60 3.64 3.92 3.98 4.37 3.88 5.31 4.52 5.44 4.07 3.84 3.73 1.68 1.41

F(1, 95)

23.09*** .18 5.85* 36.40*** 1.93 35.14*** 3.70 17.67*** 10.19** .02 18.21*** 2.38 3.53 27.29*** 7.17** 42.78*** 1.55 1.50 8.46** 13.34*** 3.85

Effect Size

.39 .04 .21 .59 .12 .51 .16 .46 .31 .01 .34 .13 .17 .41 .27 .56 .12 .10 .28 .39 .23

5.

115

THERAPEUTIC C O M M U N IT Y TREATMENT REGIMENS

TABLE 5.3 Comparison of MMPI-2 Test-Retest at Control Program(N = 43 )

Scale L F K Hs D Hy Pd Mf Pa Pt Sc Ma Si

1st Raw Score

3.70 8.98 11.72 6.79 21.05 18.44 24.02 24.88 12.93 19.77 23.26 23.33 29.35

Mean T-Score

52 64 43 51 57 43 64 48 61 62 65 62 54

SD

2.19 5.36 4.56 3.55 5.06 4.37 4.27 4.25 4.35 8.90 10.55 4.98 8.44

2nd Raw Score

Mean T-Score

3.84 8.19 13.26 5.98 19.58 17.84 23.65 24.74 11.91 16.00 19.14 23.21 27.02

52 61 45 51 54 43 64 48 57 55 60 65 51

SD

1.95 5.50 4.30 4.25 4.07 4.93 3.67 4.40 4.06 8.32 10.57 4.28 8.18

F(1, 41)

.18 1.96 8.11** 2.24 5.44* .53 .29 .06 3.35 16.80*** 9.94** .03 5.30*

Effect Size

.07 .15 .36 .20 .27 .12 .10 .03 .25 .46 .45 .03 .30

* p < .05; * * p < .01; ***p