A Structured Interview for the Assessment of the Five-Factor Model of Personality: Facet-Level Relations to the Axis II Personality Disorders

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1 A Structured Interview for the Assessment of the Five-Factor Model of Personality: Facet-Level Relations to the Axis II Personality Disorders Timothy J. Trull University of Missouri Columbia Thomas A. Widiger University of Kentucky Rachel Burr University of Missouri Columbia ABSTRACT The Structured Interview for the Five-Factor Model (SIFFM; Trull & Widiger, 1997) is an 120-item semistructured interview that assesses both adaptive and maladaptive features of the personality traits included in the five-factor model of personality, or Big Five. In this article, we evaluate the ability of SIFFM scores to predict personality disorder symptomatology in a sample of 232 adults (46 outpatients and 186 nonclinical college students). Personality disorder symptoms were assessed using the Personality Diagnostic Questionnaire-Revised (PDQ-R; Hyler & Rider, 1987). Results indicated that many of the predicted associations between lower-order personality traits and personality disorders were supported. Further, many of these associations held even after controlling for comorbid personality disorder symptoms. These Correspondence concerning this article should be addressed to Timothy J. Trull, Department of Psychology, 210 McAlester Hall, University of Missouri Columbia, Columbia, MO Electronic mail may be sent via Internet to: TrullT@missouri.edu Journal of Personality 69:2, April Copyright 2001 by Blackwell Publishers, 350 Main Street, Malden, MA 02148, USA, and 108 Cowley Road, Oxford, OX4 1JF, UK.

2 176 Trull et al. findings may help inform conceptualizations of the personality disorders, as well as etiological theories and treatment. Unlike its predecessors, the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) acknowledges alternative models for conceptualizing personality disorders and personality pathology. One such alternative dimensional model is the five-factor model (FFM) of personality (Digman, 1990; Goldberg, 1993; John, 1990; Wiggins & Pincus, 1992). Although there is some variation in the labels given to the five higherorder factors or domains of the FFM, they are often referred to as Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Further, each one of these higher-order traits is comprised of first-order personality trait facets. For example, Extraversion facets include Warmth, Gregariousness, Assertiveness, Activity, Excitement Seeking, and Positive Emotions, while Conscientiousness facets include Competence, Order, Dutifulness, Achievement Striving, Self-Discipline, and Deliberation. The relationship between FFM personality constructs and Axis II personality disorders has been examined by a number of researchers (e.g., Ball, Tennen, Poling, Kranzler, & Rounsaville, 1997; Costa & McCrae, 1990; Soldz, Budman, Demby, & Merry, 1993; Trull, 1992; Wiggins & Pincus, 1989). The results of these studies indicate that the FFM is relevant to the personality disorders and support the inclusion of FFM measures in assessment batteries aimed at evaluating personality traits and personality pathology in patients (Widiger & Costa, 1994). However, these studies are limited in several ways. First, to date, only paper-and-pencil questionnaires or checklists that measure FFM traits have been used. Although these measures offer a number of advantages, there are limitations as well. For example, self-report measures may be susceptible to mood-state effects, and it is not possible to clarify answers or to follow up answers with additional probes (Widiger & Trull, 1997; Zimmerman, 1994). These issues may be especially problematic when assessing Neuroticism traits in clinical samples and when other Axis I disorders (e.g., substance use disorders) are present that may confound personality trait personality disorder relations. Second, most of the previous studies did not examine the relations between lower-order (first-order) FFM traits and Axis II disorders (but see Dyce and O Connor, 1998). Such an examination is important because relations between

3 Structured Interview for the Five-Factor Model 177 higher-order personality traits (e.g., the Big Five dimensions) and individual personality disorders are not likely to be distinctive (Harkness, 1992). For example, most of the personality disorders (and many Axis I disorders) are characterized by higher scores on Neuroticism, and lower scores on Extraversion, Agreeableness, and Conscientiousness (Trull, 1992; Trull & Sher, 1994). Differentiating among these personality disorders will require more specific assessments. There are a number of potential advantages offered by an interviewbased assessment of personality and personality pathology. The interview method enables the clinician or researcher to tease apart and elicit additional information directly relevant to several major issues concerning personality traits and personality disorders. For example, compared to paper-and-pencil questionnaires or checklists, interviews are better equipped to assess whether a behavior or purported personality feature is primarily situational or, rather, indicative of an underlying trait or disposition. This assessment is accomplished by determining both the persistence (across time) and pervasiveness of the feature across situations and interpersonal relationships. Further, interviews allow for a more comprehensive assessment of the adaptive and maladaptive features of a personality trait. For example, following endorsement of a feature or behavior, the respondent can be asked whether or not there are any associated problems or distress. These additional aspects of personality assessment are crucial because, by definition, personality traits are long-standing and pervasive, and, if there is significant distress or maladaptivity associated with these traits, may be indicative of personality disorder (APA, 1994). Recently, Trull and Widiger (1997) developed the Structured Interview for the Five-Factor Model of Personality (SIFFM) to assess the FFM higher-order dimensions as well as lower-order trait facets for each dimension. Axelrod, Widiger, Trull, and Corbitt (1997), in a preliminary study using a draft of the SIFFM, demonstrated the potential of differentiating among the Antisocial, Borderline, Narcissistic, Paranoid, and Passive-Aggressive personality disorders with respect to facets of antagonism. In another study, Trull et al. (1998) demonstrated that SIFFM domain scores showed acceptable levels of internal consistency (range =.72 to.89), that dimensions underlying the SIFFM approximated the FFM, that SIFFM scores were fairly stable over two weeks (range =.81 to.93 for domain scores), that SIFFM scores demonstrated convergent and discriminant validity with other FFM measures (i.e., the

4 178 Trull et al. NEO-PI-R; Costa & McCrae, 1992; range of convergent correlations for domain scores =.65 to.84), and that peer ratings on FFM dimensions converged with corresponding scores from the SIFFM (range of convergent correlations for domain scores =.32 to.67). Although the previous study by Trull et al. (1998) demonstrated the potential utility of the SIFFM s higher-order trait dimensions in personality and personality disorder assessment, the authors did not report the relationship between specific, lower-order trait facets and personality disorder symptomatology. As indicated by Livesley, Jang, and Vernon (1998), a consideration of lower-order traits is necessary in order to provide a comprehensive account of personality and personality disorder. In this follow-up report, we tested the propositions of Trull and Widiger (1997) regarding hypothesized relations between personality disorder constructs and FFM lower-order (i.e., facet) traits. Table 1 presents these hypothesized relations between personality disorder constructs and FFM lower-order personality trait facets. 1 We assessed these predicted relationships in the current study in two ways. First, we computed bivariate correlations between personality disorder symptom counts and scores from the SIFFM. Second, we conducted a series of hierarchical regression analyses that evaluated which of the hypothesized SIFFM scores accounted for a significant amount of the variance in personality disorder symptom counts after controlling for comorbidity (i.e., other personality disorder symptom counts). In this way, we were able to assess which of the predicted SIFFM personality traits were significantly related to respective individual personality disorder scores after taking into account the influence of general, nonspecific personality disorder pathology. Thus, we were able to determine which of the hypothesized traits were associated with each individual personality disorder s variance that was unique beyond general personality disorder pathology. 1. The theoretical predictions of Widiger et al. (1994) and Trull and Widiger (1997) regarding FFM trait and personality disorder relations are similar, but not identical. The major reason for revision was that Widiger et al. (1994) focused on the DSM-III-R descriptions whereas Trull and Widiger considered both DSM-III-R and DSM-IV descriptions of these disorders.

5 Structured Interview for the Five-Factor Model 179 Table 1 Hypothesized Relations Between Personality Disorders and Five- Factor Model Lower-Order Traits (Trull & Widiger, 1997) Schizoid (SZD) Neuroticism facets Hostility (L), Self-Consciousness (L); Extraversion facets Warmth (L), Gregariousness (L), Activity (L), Positive Emotions (L); Openness facets Openness to Feelings (L). Schizotypal (SZT) Neuroticism facets Anxiety (H), Self-Consciousness (H), Vulnerability (H); Extraversion facets Gregariousness (L); Openness facets Openness to Fantasy (H), Openness to Aesthetics (H), Openness to Feelings (L), Openness to Actions (H), Openness to Ideas (H), Openness to Values (H); Agreeableness facets Trust (L). Paranoid (PAR) Neuroticism facets Anxiety (H), Hostility (H); Extraversion facets Positive Emotions (L); Openness facets Openness to Ideas (L), Openness to Values (L); Agreeableness facets Trust (L), Compliance (L), Tender Mindedness (L). Avoidant (AVD) Neuroticism facets Anxiety (H), Depression (H), Self-Consciousness (H), Vulnerability (H); Extraversion facets Gregariousness (L), Assertiveness (L), Activity (L), Excitement-Seeking (L); Openness facets Openness to Actions (L); Agreeableness facets Modesty (H); Conscientiousness facets Competence (L). Dependent (DEP) Neuroticism facets Anxiety (H), Hostility (L), Depression (H), Vulnerability (H); Extraversion facets Warmth (H), Gregariousness (H), Assertiveness (L), Activity (L); Agreeableness facets Trust (H), Straightforwardness (H), Altruism (H), Compliance (H), Modesty (H), Tender-Mindedness (H); Conscientiousness facets Competence (L), Deliberation (L). Obsessive-Compulsive (OBC) Neuroticism facets Hostility (H); Extraversion facets Warmth (L), Assertiveness (H), Activity (H), Excitement-Seeking (L), Positive Emotions (L); Openness facets Openness to Fantasy (L), Openness to Aesthetics (L), Openness to Feelings (L), Openness to Actions (L), Openness to Ideas (L), Openness to Values (L); Agreeableness facets Altruism (L), Compliance (L); Conscientiousness facets Competence (H), Order (H), Dutifulness (H), Achievement-Striving (H), Self-Discipline (H), Deliberation (H).

6 180 Trull et al. Table 1 Continued Histrionic (HIS) Neuroticism facets Hostility (H), Self-Consciousness (H), Vulnerability (H); Extraversion facets Warmth (H), Gregariousness (H), Activity (H), Excitement-Seeking (H), Positive Emotions (H); Openness facets Openness to Fantasy (H), Openness to Feelings (H), Openness to Actions (H), Openness to Ideas (L); Agreeableness facets Trust (H), Straightforwardness (L), Altruism (L), Tender-Mindedness (H); Conscientiousness facets Self-Discipline (L), Deliberation (L). Narcissistic (NAR) Neuroticism facets Hostility (H), Depression (L), Self-Consciousness (H), Vulnerability (H/L); Extraversion facets Assertiveness (H), Positive Emotions (H/L); Openness facets Openness to Fantasy (H); Agreeableness facets Altruism (L), Modesty (L), Tender-Mindedness (L); Conscientiousness facets Competence (H), Achievement-Striving (H). Borderline (BRD) Neuroticism facets Anxiety (H), Hostility (H), Depression (H), Impulsiveness (H), Vulnerability (H); Extraversion facets Warmth (H), Gregariousness (H), Assertiveness (H); Openness facets Openness to Fantasy (H), Openness to Feelings (H); Agreeableness facets Trust (L), Straightforwardness (L), Compliance (L); Conscientiousness facets Achievement-Striving (L), Deliberation (L). Antisocial (ANT) Neuroticism facets Anxiety (L), Hostility (H), Depression (L), Self- Consciousness (L), Impulsiveness (H), Vulnerability (L); Extraversion facets Excitement-Seeking (H); Agreeableness facets Trust (L), Straightforwardness (L), Altruism (L), Compliance (L), Modesty (L), Tender-Mindedness (L); Conscientiousness facets Order (L), Dutifulness (L), Achievement-Striving (L), Self-Discipline (L), Deliberation (L). Note: L = Low score, H = High score.

7 Structured Interview for the Five-Factor Model 181 METHOD There were a total of 233 participants, including 187 undergraduate students from the University of Missouri Columbia as well as 46 outpatients who were receiving treatment at a community mental health clinic in Columbia, Missouri. 2 All participants completed the Personality Diagnostic Questionnaire-Revised (PDQ-R; Hyler & Rieder, 1987). The PDQ-R is a 152-item inventory that assesses the DSM-III-R (American Psychiatric Association, 1987) criteria for the Axis II personality disorders. PDQ-R scores for each of the DSM-III-R personality disorders were computed, representing the number of criteria met for each disorder. In this report, we present data for only the 10 personality disorders that appear in DSM-IV. In addition to the PDQ-R, the SIFFM (Trull & Widiger, 1997) was administered to all participants. The SIFFM is a 120-item semistructured interview that taps the five major dimensions of the FFM (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) as well as 30 first-order trait facets that comprise these dimensions. Thirty-two of the 120 SIFFM items are reverse-scored. Answers to each SIFFM item (i.e., set of interview questions) are scored 0 (absent), 1 (present and does not result in significant dysfunction), or 2 (present and may result in significant dysfunction). For example, one of the SIFFM items that assesses the Neuroticism facet of Hostility consists of the following questions: In general, do you get angry easily? IF YES: Has this caused you to have problems in your relationships with other people (e.g., arguing or snapping at others)? Give me some examples. Endorsing the first but not the second question would earn a score of 1, but endorsing both questions and giving examples would earn a score of 2. More details regarding the development of the SIFFM and sample SIFFM items are presented in Trull and Widiger (1997) and Trull et al. (1998). Participants Undergraduate participants were solicited from the University of Missouri Columbia s Introduction to Psychology subject pool, and all received research credit for their participation. The mean age of the undergraduate sample was 2. In this article, we focus on analyses and results based on the entire, combined sample of undergraduates and clinical participants. The advantage of this approach is that broader ranges of personality disorder symptoms and levels of personality traits are included in this combined sample, increasing the variability on each measure. However, such a sample may limit the generalizations and interpretations that can be made. Further, because our clinical sample was rather small and included only outpatients, generalizations to other clinical samples may be limited. Studies using the SIFFM in large and diverse clinical as well as community samples are needed.

8 182 Trull et al (SD = 2.05); 52.41% were women. All of the clinic participants were currently receiving treatment for a psychological condition. These individuals were at various stages in their treatment at the time of assessment, and the median number of treatment sessions at the time of assessment was 17.5 (range = 1 to 95 sessions). Clinic participants were paid $15.00 for their participation, and all participants gave their written informed consent. The mean age of the clinic sample was (SD = 8.27; range = 20 to 61 years of age), 78.26% of the sample were women, 54.35% had at least a college degree, 45.65% had never been married, 30.43% had at least one child, and the average annual income was $12,350 (SD = $11,586; range = $1,200 to $55,000). Approximately 39% of the clinic participants (n = 18) were taking medication for their psychological conditions at the time of the assessment; most were taking an antidepressant medication. As for history of previous treatment, the average number of previous courses of outpatient treatment in this sample was 1.91 (SD = 1.65; range = 0 to 9). Approximately 20% of the sample had a history of at least one inpatient hospitalization for a psychological condition (range = 1 to 5 hospitalizations). According to the clinic charts, 13% of the sample had a history of at least one suicide attempt, 8.7% had a history of self-mutilation, 19.6% had a history of substance abuse, 6.5% had a history of at least one arrest, 2.2% had a history of violent or assaultive behavior, 6.5% had a history of hallucinations, and 4.3% had a history of delusions. DSM-IV diagnostic information, provided by the treating clinician, was also gathered from the clinic charts. The majority of the clinic sample (86.96%; n = 40) had at least one Axis I diagnosis. Twenty-two participants received only one Axis I diagnosis, twelve participants received two Axis I diagnoses, and six participants received three Axis I diagnoses. The most frequently occurring Axis I diagnoses were Dysthymic Disorder (n = 21; 45.65%), Major Depressive Disorder (n = 10; 21.74%), and Adjustment Disorder (n = 5; 10.87%). On Axis II, 16 patients (34.78%) received at least one personality disorder diagnosis and 3 patients received two diagnoses on Axis II. The most prevalent Axis II diagnoses in this sample were Personality Disorder Not Otherwise Specified (n = 5; 10.87%) and Borderline Personality Disorder (n = 5; 10.87%). Interrater Reliability Three men and five women served as interviewers for this study. All had backgrounds in psychology or clinical psychology. All SIFFM interviews were audiotaped, and a random sample of the tapes (n = 86; 36.9%) were reviewed and rescored by an independent reliability checker. The average intraclass correlation coefficient for the five SIFFM domains was.96 (range =.94 to.97)

9 Structured Interview for the Five-Factor Model 183 and.92 for the 30 SIFFM facets (range =.71 to.98). Intraclass correlation coefficients were comparable for clinic and undergraduate participants. RESULTS Bivariate Correlations All participants except one (n = 232) completed the PDQ-R (Hyler & Rieder, 1987). Zero-order correlations between the SIFFM and the PDQ-R are presented in Table 2. Focusing first on the correlations between SIFFM domain scores and PDQ-R scores, we see that the majority of personality disorder constructs were positively correlated with SIFFM Neuroticism scores, negatively correlated with SIFFM Extraversion scores, and negatively correlated with SIFFM Conscientiousness scores. These results are consistent with those from previous studies that have examined the relations between personality disorder constructs and scores from self-report FFM measures (e.g., Costa & McCrae, 1990; Soldz et al., 1993; Trull, 1992; Wiggins & Pincus, 1989). In addition to this general pattern of relations between higher-order FFM traits and personality disorders, several other findings were noteworthy. SIFFM Openness domain scores were most highly correlated with Schizotypal and Borderline scores reflecting perhaps the association between these disorders and the experience of cognitive and perceptual aberrations. Although many personality disorders were negatively related to SIFFM Agreeableness scores, Dependent scores were positively correlated with Agreeableness. Although this is an expected finding, previous studies have not reported such a result. This is perhaps due to limitations in alternative FFM measures that do not appear to assess maladaptive variants of high Agreeableness. There were unexpected SIFFM domain and personality disorder score findings as well. For example, Histrionic scores were not positively correlated with Extraversion scores, Openness scores were not negatively correlated with Schizoid, Paranoid, or Obsessive Compulsive scores, and Obsessive Compulsive scores were not positively correlated with Conscientiousness scores. Table 2 also presents bivariate correlations between SIFFM facet scores and personality disorder scores. Consulting the predicted associations between facets and personality disorders that are presented in Table 1, it can be seen that the majority of predictions were supported for Schizoid (four of seven), Schizotypal (eight of 11), Paranoid (six of eight), Avoidant (11 of 11), Dependent (10 of 16), Borderline (11 of 15),

10 184 Trull et al. Table 2 Correlations Between SIFFM Scores and PDQ-R Personality Disorder Symptom Counts (n = 232) PDQ-R Symptom Count SZD SZT PAR AVD DEP OBC HIS NAR BRD ANT SIFFM Neuroticism N: Anxiety N: Hostility N: Depression N: Self- Consciousness N: Impulsiveness N: Vulnerability Extraversion E: Warmth E: Gregariousness E: Assertiveness E: Activity E: Excitement Seeking E: Positive Emotions Openness O: Fantasy O: Aesthetics O: Feelings O: Actions O: Ideas O: Values Agreeableness A: Trust A: Straightforwardness A: Altruism A: Compliance A: Modesty A: Tendermindedness

11 Structured Interview for the Five-Factor Model 185 Table 2 Continued PDQ-R Symptom Count SZD SZT PAR AVD DEP OBC HIS NAR BRD ANT SIFFM Conscientiousness C: Competence C: Order C: Dutifulness C: Achievement Striving C: Self-Discipline C: Deliberation Note: SZD = Schizoid, SZT = Schizotypal, PAR = Paranoid, AVD = Avoidant, DEP = Dependent, OBC = Obsessive Compulsive, HIS = Histrionic, NAR = Narcissistic, BRD = Borderline, and ANT = Antisocial. Decimal signs have been omitted. All correlations.13 are significant at the p <.05 two-tailed level; all correlations.17 are significant at the p <.01, two-tailed level; and all correlations.23 are significant at the p <.001, two-tailed level. and Antisocial (10 of 18) personality disorders. In contrast, less support was obtained for predictions involving Obsessive Compulsive (4 of 20), Histrionic (8 of 18), and Narcissistic (6 of 12) personality disorders. Further, primarily for these latter three personality disorders, there were several correlations obtained that were significant in the opposite direction than was predicted Although we present correlational results for the full, combined sample, we did compute bivariate correlations separately by sample to ensure that significant predicted results replicated across clinical and nonclinical participants. Across all of the significant correlations that supported the facet-level predictions (78 total), there were 10 instances in which the result for the combined sample was not replicated across clinical and nonclinical samples (i.e., the correlation approached 0 in one sample, or the correlations for the 2 samples were in the opposite direction). Specifically, the following correlations were not replicated across samples: Schizotypal and Openness to Values, Avoidant and Openness to Actions, Dependent and Activity, Dependent and Altruism, Dependent and Compliance, Dependent and Modesty, Histrionic and Self-Consciousness, Narcissistic and Altruism, Borderline and Openness to Feelings, and Antisocial and Trust.

12 186 Trull et al. Hierarchical Regressions Although bivariate correlations are instructive, they cannot identify which of the predicted personality traits are most strongly related to unique variance in each personality disorder because symptoms from various personality disorders co-occur, and the traits themselves are intercorrelated. Therefore, we also conducted a series of regression analyses. For each personality disorder symptom count, two regressions were conducted. In the first regression, those SIFFM facets hypothesized to be most relevant to the personality disorder in question (see Table 1) were entered as a block of predictors to determine whether a significant amount of the variance in the personality disorder symptom counts could be accounted for. In the second set of regressions, total symptom counts from nontargeted personality disorders were entered first, followed by the block of SIFFM facets hypothesized to relate to the personality disorder in question. For both sets of regressions, if the block of SIFFM facet predictors was significant, beta weights for SIFFM facets were examined to determine which were most highly (and significantly) related to personality disorder symptom counts (taking into account the intercorrelations among predictors). Table 3 indicates that the block of SIFFM facets predicted to relate to the respective personality disorder symptom counts accounted for a significant amount of the variance for each disorder. The amount of variance accounted for (i.e., adjusted R 2 ) ranged from.16 (Obsessive Compulsive) to.57 (Avoidant), averaging.34. The regressions assessing whether hypothesized SIFFM facets accounted for variance in respective personality disorder symptom counts beyond the variance accounted for by comorbid personality disorder symptoms indicated that for all disorders except Obsessive Compulsive, hypothesized SIFFM facets demonstrated significant relationships to their respective personality disorders. An examination of the significant beta weights after the second step of these regressions indicated those hypothesized SIFFM facets that demonstrated a significant association to the respective symptom counts after controlling for comorbid personality disorder features: Schizoid low Warmth, low Gregariousness, and low Positive Emotions; Schizotypal Self-Consciousness, Aesthetics, low Feelings, and Ideas; Paranoid low Trust; Avoidant Self-Consciousness, low Gregariousness, low Assertiveness, and low Excitement Seeking; Dependent Depression, Vulnerability, Warmth, Gregariousness, and Trust; Obsessive Compulsive no facets;

13 Table 3 Regression Results Criterion Symptom R 2 Significant SIFFM Count Step/Predictors df (adjusted) F Predictors Schizoid (SZD) 1. SIFFM-SZD facets 7, *** Warmth ( ), Gregariousness ( ) Positive Emotions ( ) Schizoid (SZD) 1. Non-SZD symptoms 1, *** 2. SIFFM-SZD facets 7, *** Warmth ( ), Gregariousness ( ), Positive Emotions ( ) Schizotypal (SZT) 1. SIFFM-SZT facets 11, *** Anxiety (+), Self-Consciousness (+++), Fantasy (+), Feelings ( ), Ideas (++), Trust ( ) Schizotypal (SZT) 1. Non-SZT symptoms 1, *** 2. SIFFM-SZT facets 11, *** Self-Consciousness (++), Aesthetics (+), Feelings ( ), Ideas (++) Paranoid (PAR) 1. SIFFM-PAR facets 8, *** Hostility (+++), Trust ( ) Paranoid (PAR) 1. Non-PAR symptoms 1, *** 2. SIFFM-PAR facets 8, *** Trust ( ) Avoidant (AVD) 1. SIFFM-AVD facets 11, *** Self-Consciousness (+++), Activity ( )

14 Table 3 Continued Criterion Symptom R 2 Significant SIFFM Count Step/Predictors df (adjusted) F Predictors Avoidant (AVD) 1. Non-AVD symptoms 1, *** 2. SIFFM-AVD facets 11, *** Self-Consciousness (+++), Gregariousness ( ), Assertiveness ( ), Excitement Seeking ( ), Competence (+) Dependent (DEP) 1. SIFFM-DEP facets 16, *** Hostility (+), Depression (+++), Vulnerability (++), Warmth (+), Gregariousness (++), Assertiveness ( ), Trust (+), Modesty ( ) Dependent (DEP) 1. Non-DEP symptoms 1, *** 2. SIFFM-DEP facets 16, *** Depression (++), Vulnerability (++), Warmth (++), Gregariousness (+), Achievement Striving ( ), Trust (+++), Modesty ( ) Obsessive Compulsive (OBC) 1. SIFFM-OBC facets 20, *** Hostility (+), Fantasy (+) Obsessive Compulsive (OBC) 1. Non-OBC symptoms 1, *** 2. SIFFM-OBC facets 20,

15 Table 3 Continued Criterion Symptom R 2 Significant SIFFM Count Step/Predictors df (adjusted) F Predictors Histrionic (HIS) 1. SIFFM-HIS facets 18, *** Gregariousness (+++), Excitement Seeking ( ), Fantasy (+), Feelings (+++), Altruism ( ) Histrionic (HIS) 1. Non-HIS symptoms 1, *** 2. SIFFM-HIS facets 18, *** Warmth (+), Gregariousness (+++), Excitement Seeking ( ), Feelings (+++), Altruism ( ), Tendermindedness (+) Narcissistic (NAR) 1. SIFFM-NAR facets 12, *** Hostility (++), Fantasy (+++), Modesty ( ), Achievement Striving (+) Narcissistic (NAR) 1. Non-NAR symptoms 1, *** 2. SIFFM-NAR facets 12, *** Fantasy (++), Modesty ( ), Achievement Striving (+++) Borderline (BRD) 1. SIFFM-BRD facets 15, *** Anxiety (++), Hostility (+++), Impulsiveness (++) Borderline (BRD) 1. Non-BRD symptoms 1, *** 2. SIFFM-BRD facets 15, *** Anxiety (++), Hostility (++), Deliberation ( )

16 Table 3 Continued Criterion Symptom R 2 Significant SIFFM Count Step/Predictors df (adjusted) F Predictors Antisocial (ANT) 1. SIFFM-ANT facets 18, *** Hostility (+), Impulsiveness (++), Excitement Seeking (+++), Tendermindedness ( ), Achievement Striving ( ) Antisocial (ANT) 1. Non-ANT symptoms 1, *** 2. SIFFM-ANT facets 18, *** Impulsiveness (+), Vulnerability ( ), Excitement Seeking (+++), Tendermindedness ( ), Achievement Striving ( ), Self Discipline (+) Note: df = degrees of freedom; R 2 = change in R 2 ; F = F change; *p <.05, **p <.01, ***p <.001; Significant SIFFM predictors = those SIFFM facet scores predicted to be associated with the respective Axis II symptom count (see Table 1) that were uniquely and significantly related to that symptom count at that step; +++ = facet positively related at p <.001; ++ = facet positively related at p <.01; + = facet positively related at p <.05; = facet negatively related at p <.001; =facetnegatively relatedatp <.01; = facet negatively related at p <.05.

17 Structured Interview for the Five-Factor Model 191 Histrionic Warmth, Gregariousness, Feelings, low Altruism, and Tendermindedness; Narcissistic Fantasy, low Modesty, and Achievement Striving; Borderline Anxiety, Hostility and low Deliberation; and Antisocial Impulsiveness, low Vulnerability, Excitement Seeking, low Tendermindedness, and low Achievement Striving. DISCUSSION Personality disorders are said to involve inflexible and maladaptive personality traits that cause impairment or distress (APA, 1994). Because the SIFFM purports to measure a wide range of personality traits, including both adaptive and maladaptive levels of these traits, it was predicted that SIFFM scores would be related to personality disorder scores. A number of investigators have assessed the relations between FFM measure scores and personality disorder symptoms (e.g., Ball et al., 1997; Costa & McCrae, 1990; Soldz et al., 1993; Trull, 1992; Wiggins & Pincus, 1989). Very few of these investigators, however, reported relationships between facet scores and personality disorder symptomatology. Based on a review of DSM-III-Rand DSM-IV personality disorder criteria, Trull & Widiger (1997) made a number of predictions regarding the relationships between SIFFM domain and facet scores and the range of Axis II disorders. In the present study, we found that SIFFM domain and facet scores were significantly related to personality disorder symptom counts in a manner that was consistent with the relations predicted by Trull and Widiger (1997). Further, despite a number of major methodological differences between studies (e.g., instrumentation, assessment method, analytic strategy), the current study confirmed most of the regression findings obtained by Dyce and O Connor (1998). The major difference was that our study identified additional facets that made contributions toward explaining the unique personality disorder symptomatology variance. Although space limitations preclude a systematic evaluation of all the predictions that were made by Trull and Widiger (1997), we will provide several examples. Regarding SIFFM domain scores, we found that SIFFM Neuroticism was positively related to most of the personality disorders, especially Avoidant and Borderline personality disorder. Thus, while this broad personality domain characterizes personality disorder in general, Neuroticism does not appear to aid in the discrimination between specific forms of personality disorder.

18 192 Trull et al. Most disorders were negatively related to SIFFM Extraversion (especially Avoidant and Schizoid); SIFFM Openness was positively related toafewofthepersonalitydisorders(especiallyschizotypal,borderline, and Histrionic); SIFFM Agreeableness was negatively related to Paranoid, Narcissistic, and Antisocial scores whereas Agreeableness was positively related to Dependent personality disorder; and SIFFM Conscientiousness scores were negatively related to most of the Axis II disorders (especially Borderline). Therefore, among the Big Five domains, Openness and Agreeableness demonstrated the greatest ability to differentiate between the individual personality disorders. However, relying solely on global SIFFM domain correlations results in a potential loss of information because differential patterns of facet correlations within a given domain appear to be the rule, not the exception. For example, as predicted, both the Dependent and the Avoidant personality disorders correlated highly with Neuroticism. More importantly, the multiple regression analyses indicated that, consistent with expectations (Trull & Widiger, 1997; Widiger et al., 1994), Dependent personality disorder symptomatology was associated primarily with the Neuroticism facets of Depression and Vulnerability, whereas Avoidant symptomatology was associated primarily with the facet of Self-Consciousness. Similarly, whereas both the Avoidant and Schizoid personality disorders correlated highly with introversion, each could again be differentiated with respect to particular facets of introversion. Schizoid personality disorder symptomatology was associated primarily with low Positive Emotions (along with low Gregariousness & low Warmth). Avoidant symptomatology, on the other hand, was associated primarily with low Assertiveness and low Excitement-Seeking (along with low Gregariousness), consistent with the expected differentiations of these personality disorders at the facet level (Trull and Widiger, 1997; Widiger et al., 1994). Facet traits help distinguish and characterize other personality disorders as well. For example, Antisocial personality disorder symptomatology was weakly related to the broad domain of Neuroticism, but was significantly associated with the particular Neuroticism facets of Hostility and Impulsiveness. Similarly, Histrionic personality disorder symptomatology was uncorrelated with the broad domain of Extraversion but, as predicted, was significantly correlated with the particular Extraversion facet of Gregariousness. Finally, Borderline personality disorder was not significantly correlated (i.e., negatively) with the

19 Structured Interview for the Five-Factor Model 193 domain of Agreeableness, but did correlate negatively with the Agreeableness facet of Straightforwardness. A failure to consider the association of personality disorders with the FFM at the level of the facets within these domains could have resulted in failure to recognize these relations. Thus, the present results support theoretical predictions regarding personality trait personality disorder relations, and demonstrate the potential utility of differentiating personality disorders on the basis of the more fine-grained facet scores. These results help to explain not only why some personality disorders co-occur (e.g., because they involve Neuroticism) but also suggest how clinical differentiation among the disorders might be accomplished by considering lower-order traits. However, it should be noted that, for certain personality disorders, scores on the broad domains do a reasonable job of characterizing the associated personality features. For example, as mentioned above, Neuroticism relates positively to most if not all personality disorders (the exception: Antisocial). High Openness appears to characterize Schizotypal well, and low Extraversion seems to capture the clinical features of Schizoid. Based on these results, it appears that an examination of lower-order FFM may be more important for some but not all personality disorders. An important feature of the present study was the use of regression analyses to identify those SIFFM facet scores that were most highly related to respective personality disorder symptom counts after taking into account the intercorrelation among predictors. Further, we were able to control for comorbidity of Axis II symptoms in order to identify SIFFM facets that remained significantly related to each Axis II disorder. Because both personality facet scores and personality disorder symptom counts are intercorrelated, respectively, bivariate correlations between SIFFM scores and Axis II symptom counts alone cannot identify facet scores that are significantly related to the unique aspects of Axis II disorders over and above general personality pathology. Thus, our regression analyses were better able to address predictions regarding specific relations between lower-order traits and personality disorders that have been offered by theorists (Trull & Widiger, 1997; Widiger et al., 1994). For example, a simple count of the significant correlations of Dependent personality disorder symptomatology with respective facet scales of the SIFFM indicated that 10 of the 16 predicted relationships were confirmed. However, more important, perhaps, is that the multiple regression results indicated that the facets of Depression, Vulnerability,

20 194 Trull et al. Warmth, Gregariousness, low Assertiveness, and Trust provided unique contributions toward understanding Dependent symptomatology (the significant contributions of Depression, Vulnerability, Warmth, Gregariousness, and Trust remained even after removing variance due to non-dependent personality disorder symptomatology). These results suggest that the personality disorders may indeed represent constellations of extreme, maladaptive variants of normally occurring personality traits. Dependent personality disorder, for example, may include elements of neurotic depression and vulnerability along with an excessive need for warmth and interpersonal involvement, maladaptively low assertiveness, and excessive trust or gullibility (Widiger et al., 1994). It should be noted, however, that controlling for comorbidity, while affecting the regression results for several of the personality disorders, did not result in markedly different sets of significant SIFFM facet predictors for certain disorders. For example, the regression results for Schizoid, Paranoid, Dependent, or Narcissistic personality disorder did not change much after taking into account general personality disorder pathology. This suggests a robust relationship between these facets and their respective personality disorders, regardless of comorbid personality disorder symptoms. Although many findings supported our theoretical predictions, one notable exception was the failure to confirm the predictions concerning Obsessive-Compulsive symptomatology. Dyce and O Connor (1998) identified four facets of Conscientiousness significantly related to variance in Obsessive-Compulsive symptomatology. In contrast, the regression analyses from the current study, contrary to expectations, identified none. This inconsistency in findings for the Obsessive-Compulsive personality disorder has been reported in other studies and may reflect differences in the PDQ-R (Hyler & Rieder, 1987) and the MCMI-III (Millon, Millon, & Davis, 1994) assessment of this disorder (Widiger & Costa, 1994). In addition to the findings for Obsessive-Compulsive personality disorder, there were also some inconsistencies regarding the direction of associations across the correlational and regression analyses. For example, we predicted that Modesty (an Agreeableness facet) would be positively correlated with Dependent symptomatology. Although this was confirmed in the bivariate analyses, our regression analyses indicated a negative relationship once the intercorrelation among predictors was

21 Structured Interview for the Five-Factor Model 195 taken into account. Such a pattern of results suggests a suppressor effect that may not replicate in future studies. 4 The findings from our study should aid theoreticians and researchers regarding their formulations of the descriptive features of the Axis II disorders because our results suggest which lower-order personality traits best characterize each Axis II disorder. Although DSM-IV acknowledges that personality disorders are comprised of inflexible and maladaptive personality traits, the manual does not specify which traits are implicated for each disorder. By examining the relationships between a wide range of major personality traits and personality disorder symptoms, our study, and those like it, represents an important step in defining, refining, and distinguishing the personality disorders. Further, our analyses controlling for comorbid personality disorder symptoms help identify those traits that appear to be most associated with unique variance in each Axis II disorder. For example, our findings suggest that Borderline personality disorder is characterized primarily by high levels of Anxiety, Hostility, and Impulsiveness and low levels of Deliberation. After controlling for comorbid Axis II symptoms, these relations remained, except in the case of Impulsiveness. Thus, our results point to the importance of negative affect, affective instability, and some degree of impulsivity (i.e., at least a relative lack of thoughtful deliberation). These findings are consistent with etiological theories of borderline personality disorder more generally, as well as with theories regarding the tendency of those with BPD to abuse various substances (Trull, Sher, Minks-Brown, Durbin, & Burr, 2000). Our study also provides further support for an interview-based assessment of personality traits and personality pathology. Most measures of personality traits are paper-and-pencil questionnaires or brief self-rating checklists. There are currently no other semistructured interviews for the assessment of a dimensional model of personality and personality disorder (Widiger & Trull, 1997). Although there are economic advantages (both in terms of time and cost) to questionnaires, most clinicians prefer interview forms of assessment. Further, because additional probes and 4. Another noteworthy result that did not replicate across correlational and regression analyses concerned the relation between Warmth and Dependent personality disorder. The bivariate correlation was negative (contrary to predictions), but both regression results revealed a significant positive relation between Warmth scores and Dependent scores (consistent with predictions).

22 196 Trull et al. clarifications are possible with interviews, we believe that interviews may be well-suited to assessing maladaptive behaviors that are associated with a personality trait. Self-report measures of personality, for example, may be able to assess the level of a trait that is present but unable to determine if there is dysfunction associated with the trait. Dysfunction and maladaptivity are integral to personality disorders, by definition (APA, 1994). Therefore, interviews like the SIFFM may be especially useful in the assessment of personality pathology. However, the use of a structured interview like the SIFFM in clinical work will remain limited (due to time and administration constraints) until it can be demonstrated that the reliability and validity of SIFFM scores significantly exceed the reliability and validity of scores from other available instruments. On the other hand, information garnered from other modes of assessment may complement that obtained from the SIFFM. Therefore, the optimal approach to assessment might include multiple methods of assessment (e.g., self- report and interview methods). Finally, we do want to mention several features of our study that serve to limit the generalizations that can be drawn. First, it is conceivable that some of our findings are sample-specific, and attempts to replicate these findings should be undertaken (e.g., our findings for Modesty and Dependent personality disorder symptomatology). Although our total sample did include clinical subjects, the majority of our sample was nonclinical. Many of our participants were fairly young, and it is possible that their relatively limited life experience as an adult was not sufficient to allow for the development of additional Axis II symptoms. Further, we did not sample any clinical inpatients. Second, personality disorder symptoms were assessed using a self-report inventory. It will be important to gather similar data using an Axis II semistructured interview. In addition, although there were few major changes in Axis II criteria from DSM-III-R to DSM-IV, our Axis II measure was based on DSM-III-R criteria sets. Finally, because we included only those facets hypothesized to relate to respective personality disorders in our regression analyses, our approach may have failed to uncover other, non-hypothesized relationships.

23 Structured Interview for the Five-Factor Model 197 REFERENCES American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author Axelrod, S. R., Widiger, T. A., Trull, T. J., & Corbitt, E. M. (1997). Relations of five-factor model antagonism facets with personality disorder symptomatology. Journal of Personality Assessment, 69, Ball, S. A., Tennen, H., Poling, J. C., Kranzler, H. R., & Rounsaville, B. J. (1997). Personality, temperament, and character dimensions in substance abusers. Journal of Abnormal Psychology, 106, Costa, P. T., Jr., & McCrae, R. R. (1990). Personality disorders and the five-factor model of personality. Journal of Personality Disorders, 4, Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI): Professional manual. Odessa, FL: Psychological Assessment Resources. Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual Review of Psychology, 41, Dyce, J. A., & O Connor, B. P. (1998). Personality disorders and the five-factor model: A test of facet-level predictions. Journal of Personality Disorders, 12, Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48, Harkness, A. R. (1992). Fundamental topics in the personality disorders: Candidate trait dimensions from lower regions of the hierarchy. Psychological Assessment, 4, Hyler, S. E., & Rieder, R. O. (1987). Personality Diagnostic Questionnaire Revised (PDQ-R). New York: Author. John, O. P. (1990). The Big Five factor taxonomy: Dimensions of personality in the natural language and in questionnaires. In L. A. Pervin (Ed.), Handbook of personality (pp ). New York: Guilford Press. Livesley, W. J., Jang, K. L., & Vernon, P. A. (1998). Phenotypic and genetic structure of traits delineating personality disorder. Archives of General Psychiatry, 55, Millon, T., Millon, C., & Davis, R. (1994). Millon Clinical Multiaxial Inventory-III. Minneapolis, MN: National Computer Systems. Soldz, S., Budman, S., Demby, A., & Merry, J. (1993). Representation of personality disorders in circumplex and five-factor space: Explorations with a clinical sample. Psychological Assessment, 5, Trull, T. J. (1992). DSM-III-R personality disorders and the five-factor model of personality: An empirical comparison. Journal of Abnormal Psychology, 101, Trull, T. J., & Sher, K. J. (1994). Relationship between the five-factor model of personality and Axis I disorders in a nonclinical sample. Journal of Abnormal Psychology, 103, Trull, T. J., Sher, K. J., Minks-Brown, C., Durbin, J., & Burr, R. (2000). Borderline personality disorder and substance use disorders: A review and integration. Clinical Psychology Review, 20,

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