Nonclinical panicker personality: Profile and discriminative ability

Pergamon

Journal of Anxiety Disorders. Vol. 8, No. 1, pp.3S47. 1994 Copyright0 1994 Ehwier Science Ltd Printed in the USA. AJJ rights reserved 0887-6185B4 $6.00 + .I0

Nonclinical Panicker Personality: Profile and Discriminative Ability HARVEY

RICHMAN,

M.A., ANDROSEMERYNELSON-GRAY,PH.D.

Department of Psychology, University of North Carolina at Greensboro

Abstract -Differences in personality between nonclinical panickers and nonpanickers hi a college population were examined in two studies. In Study 1, 590 undergraduate students completed the Panic Attack Questionnaire (PAQ), the Structured Clinical Interview for the DSM-III-R Personality Disorders-II Self Report (SCID-II), and the Millon Clinical Multiaxial Inventory (MCMI). Nonclinical panickers evidenced more personality disorder symptomatology than nonpanickers on both the MCMI and SCID-II inventories. In Study 2, 288 undergraduates completed the SCID-II inventory, the Eysenck Personality Inventory (EPI), the MMPI anxiety subscale (MMPI-A), the State Trait Anxiety Inventory (STAI), the Barratt Impulsiveness Scale (BIS), the Eysenck Impulsiveness Scale version 7 (1.7), and the Beck Depression Inventory (BDI). Personality profiles of nonclinical panickers are discussed, as well as the ability of these personality measures to discriminate between nonclinical panickers and nonpanickers.

With introductions of DSM-III (American Psychiatric Association, 1980) and DSM-III-R (American Psychiatric Association, 1987), interest in the relationship between Axis I disorders and the personality disorders (PD) coded on Axis II has increased (e.g., the relationship between panic disorder and personality disorders). Friedman, Shear, and Frances (1987), utilizing the Structured Clinical Interview for the DSM-III-R Personality Disorders-II (Spitzer & Williams, 1984), noted a “relatively high prevalence” of personality disorders among a sample of 27 panic disorder patients. These authors also noted that symptomatology from Cluster C (anxious-fearful) was prominent, and that avoidant personality disorder symptomatology was associated with increased self-reported agoraphobic avoidance. Personality disorder symptomatology has been shown to influence treatment outcome among agoraphobics (Chambless, Renneberg, Goldstein, & Gracely, 1992; Mavissakalian & Hamann, 1987). However, Mavissakahan and The authors wish to thank Richard Farmer and the staff of the University of North Carolina at Greensboro StatisticaI Consulting Center for their assistence in this research. Address correspondence and requests for reprints to Harvey Richman, M.A., Department of Psychology, 296 Eberhart Building, University of North Carolina at Greensboro, Greensboro, NC 27412-5001. 33

34

H.RICHMANANDR.NELSON-GRAY

Hamann (1987) found that some personality disorder symptomatology decreased with treatment of agoraphobia. Mavissakalian and Hamann’s (1987) findings led them to hypothesize that avoidant and histrionic personality disorder symptomatology (and their related traits) might be enduring and/or primary, whereas dependent traits might be secondary to agoraphobia. Several theories have been posited regarding the relationship between Axis I disorders and the personality disorders (Akiskal, Hirschfeld, & Yerevanian, 1983). These theories include the characterologic predisposition hypothesis (individuals develop maladaptive behavior patterns that play a role in the development of the clinical disorder), the modification hypothesis (nonetiological view suggesting that personality factors influence the expression of the clinical disorder), the attenuation hypothesis (personality disorders and clinical disorders derive from the same causes and represent milder or more severe expressions of the same condition, respectively), the complication hypothesis (personality disorder develops secondary to an episode of a clinical disorder and may vary in intensity and duration), and the orthogonal hypothesis (personality disorders and clinical disorders are independent entities whose coexistence in an individual is the result of chance occurrence). It is difficult to answer questions relating to the role of personality disorders by studying individuals already suffering from panic disorder and agoraphobia. Prospective studies would help clarify these relationships. A prospective study by Nystrom and Lindegard (1975) found that baseline personality of individuals who subsequently developed anxiety and depressive disorders at six-year follow-up differed from the rest of the sample. Nystrom and Lindegard (1975) reported a modest relationship between hysteroid personality (a pattern including overdependency) and emergence of anxiety state at the six-year follow-up (Stewart, Knize, & Pihl, 1992). This provides some support for the predisposition hypothesis. Beginning with a study by Norton, Harrison, Hauch, and Rhodes (1985) a literature has rapidly grown around the study of nonclinical panickers (individuals, often college students, who experience panic attacks but do not meet criteria for a DSM-III-R diagnosis of panic disorder). This literature has been reviewed by Malan, Norton, and Cox (1990) and by Norton, Cox, and Malan (1992). The study of personality among nonclinical panickers may provide insights into the role of personality in the development and maintenance of panic disorder and agoraphobia. The present research examined personality differences between nonclinical panickers and nonpanickers in a college population. For brevity and clarity, nonclinical panickers will subsequently be referred to as “panickers.” Individuals with a DSM-III-R diagnosis of panic disorder will be referred to as clinical panickers when discussed. Study 1 contrasted the profiles of panickers and nonpanickers on two personality inventories that follow the categorical organization of the DSM-III-R personality disorders: the Structured Clinical Interview for the DSM-III-R Personality Disorders-II Self Report (SCID-II; Spitzer, Williams, Gibbon, & First, 1990) and the Millon Clinical Multiaxial Inventory (MCMI; Millon, 1983). Study 2 compared the DSM-III-R categorically organized SCID-II with the twodimensional personality conceptualizations of Eysenck (1967) and of Gray (1970, 1972, 1973) on ability to discriminate panickers from nonpanickers.

NONUINICAL. PANICKER PERSONALXIT

35

STUDY 1 Subjects A total of 590 undergraduate students attending the University of North Carolina at Greensboro completed questionnaires. Questionnaire packets were distributed to 508 randomly selected students during mass testing. Of the 508 randomly sampled students, 26.18% (n = 133) were classified as panickers. Classification as a panicker required having experienced at least one panic attack that included four of the 13 DSM-III-R panic symptoms listed on the Panic Attack Questionnaire (Norton, Dorward, & Cox, 1986). Occurrence of a spontaneous or “out of the blue” attack was not a requirement. The remaining 375 students were classified as nonpanickers. Eighty-four additional students filled out the PAQ after responding to a poster asking for subjects who had experienced at least one “episode involving intense anxiety or panic during the past year.” Eighty-two of these students (all but two) met criteria for classification as a panicker on the PAQ as described above. Thus, a total of 215 panickers participated in Study 1. Mean age of participants was 19 years. Participants were predominantly female (86%). Questionnaires

and Procedure

Subjects completed the Structured Clinical Interview for the DSM-III-R Personality Disorders-II Self Report (SCID-II; Spitzer et al., 1990), and the Millon Clinical Multiaxial Inventory (MCMI; Millon, 1983). The SCID-II assesses for personality disorder symptomatology in terms of DSM-III-R diagnostic criteria. Because the number of DSM-III-R criteria comprising the various personality disorders varies, SCID-II scores were computed as the percentage of possible criteria met on a given scale (e.g., for borderline, 6 of 8 criteria met = 6/8 = 75%). The MCMI contains 11 scales corresponding to the DSM-III-R personality disorders. MCMI raw scores (number of items endorsed on each scale) were utilized. SCID-II data were incomplete for three panickers and seven nonpanickers. Thus, SCID-II analyses were carried out utilizing data from 212 panickers and 368 nonpanickers. MCMI data were incomplete for 18 panickers and 25 nonpanickers. Thus, MCMI analyses were carried out utilizing data from 197 panickers and 350 nonpanickers. Results SCZD-ZZ. SCID-II means, standard deviations, and between-group t-statistics for the SCID-II scales are presented in Table 1, in terms of percentage of DSM-III-R criteria met. As can be seen, means for panickers significantly exceeded means for nonpanickers on all of the SCID scales, including the “proposed” category of selfdefeating PD. This clearly suggests greater personality dysfunction among panickers. Differences, in percentage of DSM-III-R criteria met, ranged from 3.24 for schizoid, t(578) = 1.99, p = .05, to 18.72 for borderline, t(578) = 8.32,

H. RICHMAN AND R. NELSON-GRAY

36

TABLE 1 SCID-II PERSONALrrYSCALESANDCLUSIER,PRlNCIPALCOMPONENlS(STUDY l)h&ANS, STANDARDDEVIATIONS,ANDPERCENTMEF~NG DSM-III-R CRITERIONFORPERSONAL~IY DISORDER

Scale Schizoid Schizolypal Paranoid Histrionic Narcissistic Borderline Avoidant Dependent Obs. Comp. Passive Agg. (Self Defeat) Cluster A Cluster B Cluster C B-borderline

Panicker (n = 212) 21.54 (21.0) so.39 (24.2) 59.97 (25.9) 53.23 (23.1) 44.66 (22.1) 14.71 (18.6) 50.00 (28.2) 37.53 (26.9) 29.04 (24.2) 44.86 (21.3) 39.20 (21.3) 48.82 (22.6) .4312 (1.30) 6009 (1.44) .5883 (1.73) .4331 (1.21)

Nonpanicker (n = 368) 4% 17% 67% 54% 41% NAa 43% 32% 23% 40% 31% 39%

18.30 (17.5) 37.50 (22.9) 48.45 (27.4) 43.32 (24.6) 35.45 (20.1) 8.87 (14.7) 31.28 (24.8) 26.13 (22.3) 19.63 (18.3) 33.70 (18.2) 31.04 (20.0) 35.77 (23.0) -.2484 (1.19) -.3462 (1.41) -.3389 (1.38) -.2495 (1.26)

f 3% 5% 50% 38% 23% NAa 18% 14% 7% 20% 16% 21%

1.99 6.40 4.98 4.78 5.12 4.17 8.32 5.49 5.28 6.69 4.62 6.62 6.42 7.71 7.07 6.36

P

< < < < < < < < < < < < < < <

.0500 .oool aJO1 .OOOl a001 .OOOl .OOOl a001 a001 .oool a001 .OoOl .ODOl .OOOl .OOOl a001

aPercent of subjects meeting criterion cannot be determined for Antisocial Personality Disorder on the basis of the SCID-II Self Report Questionnaire alone.

p c .OOOl. This suggests that groups differed to a greater extent on some scales than on others. Profile analysis (test for lack of parallelism of profiles) confirms that magnitude of panicker-nonpanicker differences was not constant across SCID-II scales, Hotelling-Lawley Trace, F( 10, 569) = 5.79, p = .OOOl. In other words, magnitude of group differences was significantly different on at least one pair of adjacent scales within the profile. The group difference on the borderline scale was notable. Percentage of panickers and nonpanickers who met the number of DSM-IIIR criteria required for a personality disorder diagnosis was calculated for each personality disorder category (e.g., 4 of 7 criteria met for avoidant). Personality disorder diagnoses should not be made on the basis of the SCID-II questionnaire alone, because doing so results in many false positives. However, this approach does provide additional group comparisons on the DSM-III-R personality disorder categories. Not surprisingly, group differences in percentage of individuals who “met criterion” on each SCID-II scale was generally greatest on the same scales on which group means differed most (see Table 1). In order to determine the extent to which panickers and nonpanickers differed on symptomatology from each of the three DSM-III-R clusters, a standardized principal component was extracted from the SCID-II scales comprising each cluster: Cluster A (schizoid, schizotypal, and paranoid), Cluster B (histrionic, narcissistic, antisocial, and borderline), and Cluster C (avoidant,

NONCLINICAL PAN1CKF.RPERSONALITY

37

dependent, obsessive compulsive, and passive aggressive). Each of the three principal component analyses involved only the scales belonging to the cluster for which a principal component was being derived. Principal components were extracted via SAS Proc Princomp (SAS Institute, 1985). As can be seen from Table 1, means for panickers exceeded means for nonpanickers on each of the three standardized cluster principal components. Profile analysis suggested that panicker-nonpanicker differences were not constant across clusters, Hotelling Lawley Trace, F(2, 577) = 3.52, p = .0301. Principal component means (Table 1) suggest that panickers and nonpanickers differed to a slightly greater extent on symptomatology from Clusters B and C than on symptomatology from Cluster A. Means indicate that the groups differed to a greater extent on Cluster B than on Cluster C. However, if the borderline scale is removed from the Cluster B principal component (leaving the histrionic, narcissistic, and antisocial scales), the Cluster C group difference becomes the greatest. MCMI.

MCMI raw score means, standard deviations, and f-statistics for panicker-nonpanicker differences on the MCMI personality scales are presented in Table 2. As was the case with the SCID-II, profile analysis indicated that magnitude of panicker-nonpanicker differences was not constant across individual MCMI scales, Hotelling-Lawley Trace, F(10, 536) = 5.75, p = .OOOl. Panicker means exceeded nonpanicker means on nine of the eleven MCMI personality scales, with seven of these differences being significant at the .05 level or better. Differences on these seven scales ranged from .97 for dependent, t(578) = 1.98, p = 0481 to 5.24 for borderline, t(578) = 7.53, p < .OOOl. As was done with the SCID-II scales, a standardized principal component was extracted from the MCMI scales comprising each cluster: Cluster A (schizoid, schizotypal, and paranoid), Cluster B (histrionic, narcissistic, antisocial, and borderline), and Cluster C (avoidant, dependent, obsessive-compulsive, and passive-aggressive). Means and standard deviations for the three MCMI cluster principal components for panickers and nonpanickers are presented in Table 2. Profile analysis suggested that panicker-nonpanicker differences were not constant across clusters, Hotelling-Lawley Trace, F(2, 544) = 11.45, p = BOOI. Statistically significant group differences were observed on the Cluster A and Cluster C principal components. The group difference on the Cluster B principal component was not statistically significant despite a notable group difference on the borderline scale. Principal component means suggested a modest “Cluster C effect.” In other words, panickers and nonpanickers appeared to differ to a somewhat greater extent on symptomatology from Cluster C than on symptomatology from Clusters A or B. STUDY

2

Subjects The Panic Attack Questionnaire (PAQ; Norton et al., 1986) was distributed to 296 randomly selected undergraduate students attending the University of North Carolina at Greensboro during mass testing. Criteria for classification as

38

H. RKHMANANDR. NELSON-GRAY TABLE 2 MCMI PERSONALWY SCALES ANLI ChJsTEa,PfUNCJF’AL COMF’ONF.NIX (STUDY1): MEANSANDSTANDAIUI DEV~A~ONS

PersonalityScale Schizoid scllizotypal Paranoid Histrionic Narcissistic Antisocial Borderline Avoidant Dependent Obs. camp.

Pass. agg. Cluster A Cluster B Cluster C

Panicker (II= 197) 10.80 9.42 11.37 15.65 19.98 13.95 11.60 10.39 13.56 22.95 10.73 .3791 -.1080 .5005

(5.1) (7.8) (5.7) (5.8) (8.1) (5.0) (9.6) (7.7) (5.7) (7.3) (6.3) (1.53) (1.45) (1.59)

Nonpaaicker (n = 350) 9.32 6.56 9.76 15.50 20.54 13.75 6.36 6.93 12.59 24.20 7.44 -.2134 .0608 -.2817

(4.5) (5.8) (5.4) (5.9) (8.1) (5.6) (6.6) (5.6) (5.4) (8.6) (5.1) (1.26) (1.39) (1.20)

t

P

3.51 4.89 3.30 .29 .77 .43 7.53 6.04 1.98 1.72 6.66 4.88 1.34 6.47

DO05 < 0001 < .OOlO .7727 .4395 6698 < a001 < a001 0481 .0863 < a001 < a001 .1802 < .oool

a panicker was as in Study 1. Ninety-nine (33.44%) students from the random sample were classified as panickers. The remaining 197 students were classified as nonpanickers. Of the students who completed the PAQ during mass testing, 86 panickers and 94 nonpanickers agreed to complete packets containing additional questionnaires. An additional 108 student panickers who did not participate in mass testing were recruited as in Study 1. This brought the total number of panickers participating in Study 2 to 194. As in Study 1, participants were predominantly female (78%), with a mean age of 19 years. Questionnaires

and Procedures

Study 2 participants completed the Structured Clinical Interview for the DSM-III-R Personality Disorders-II Self Report (SCID-II; Spitzer, Williams, Gibbon, & First, 1990), the Eysenck Personality Inventory, Form A (EPI; Eysenck Jz Eysenck, 1968), the State-Trait Anxiety Inventory, Form Y2 (STAI; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983), the Minnesota Multiphasic Personality Inventory-II anxiety subscale (MMPI-A; Graham, 1990), the “impulsiveness narrow” subscale of the Impulsiveness Questionnaire, Seventh Edition (1.7; Eysenck, Pearson, Easting, & Allsopp, 1985b), the Barratt Impulsiveness Scale, Version 10 (BIS-10; Barratt, unpublished manuscript), and the Beck Depression Inventory (BDI; Beck, 1978). As in Study 1, scores on the SCID-II scales were expressed in terms of percentage of criteria met on each scale. The remaining measures utilized the two-dimensional personality conceptualizations of Eysenck (1967) and Gray (1970, 1972, 1973). The Eysenck Personality Inventory contains 57 items. The neuroticism and introversion-extroversion scales of the EPI each contain 24 truefalse items. No questionnaire has been specifically developed to assess

NONUINICAL

PANICKER PERSONALJTY

39

individuals on Gray’s dimensions of anxiety and impulsivity. In an attempt to obtain a broad sampling of items relating to each of these dimensions, two inde pendent questionnaires were utilized to assess individuals on each dimension. An anxiety index was derived by extracting a standardized principal component from scores on the STAI and the MMPI anxiety scale. The form of the STAI used in this study contains 20 items rated on a four-point Likert scale to assess trait anxiety. The MMPI anxiety subscale is comprised of 39 true-false items. In like manner, an impulsiveness index was derived by extracting a standardized principal component from scores on the Eysenck I.7 and BIS-10 scales. The Eysenck I.7 impulsiveness scale contains 19 yes-no questions. The BIS-10 contains 34 statements rated on a four-point Likert scale. Though unpublished, the BIS-10 has been used in a number of studies and has been found to be a valid index of impulsiveness (Barratt, 1985, 1987; Barratt, Pritchard, Faulk, & Brandt, 1987). SAS Proc Princomp was utilized for deriving principal compcF nents. The derived anxiety index likely contains a considerable amount of redundant information, as the STAI and the MMPI anxiety scale were found to correlate .83 in this sample. This appears to be less the case with the impulsiveness index, as the BIS-10 and Eysenck I.7 were found to correlate only +.66. The DSM-III-R categories, the Eysenck dimensions, the Gray dimensions, and depression (assessed via the BDI) were compared on ability to discriminate panickers from nonpanickers utilizing discriminant analyses. Results Profiles for panickers and nonpanickers on all of the variables assessed in Study 2 are plotted in Fig. 1. Variables have been standardized (mean = 0, standard deviation = 1) to aid in comparison. Means, standard deviations, and between-group t-statistics for the SCID-II inventory are presented in Table 3. As in Study 1, these are in terms of percentage of DSM-III-R criteria met. As in Study 1, SCID-II means for panickers exceeded means for nonpanickers on all 11 of the DSM-III-R categories and on the “proposed category” of self-defeating personality disorder. Tests were significant at the .05 level or better for 10 of the 11 DSM-III-R categories and for the self-defeating scale. Profile analysis (test for lack of parallelism of profiles) indicated that magnitude of panicker-nonpanicker differences was not constant across SCID-II scales, Hotelling-Lawley Trace, F(10, 277) = 2.51, p = .0066. Differences, in percentage of DSM-III-R criteria met, ranged from 5.47 for histrionic, t(286) = 1.69, p = .0930, to 16.93 for borderline, t(286) = 5.19, p c .OOOl. As was the case in Study 1, generally greater personality dysfunction among panickers is suggested. Additionally, the scale evidencing the greatest betweengroup difference was borderline. As in Study 1, percentage of panickers and nonpanickers who met DSMIII-R criterion for a personality disorder diagnosis within each category was also calculated. As Table 3 suggests, group differences in percentage of individuals who met criterion for each personality disorder category were again generally consistent with group differences in mean percentage of criteria met on each scale.

H. RICHMAN AND R. NELSON-GRAY

40

FIG. 1. STANDARDUEDMEANSFORPANICKERSANDNONPANICKEFESONSTUDY

2 MEASURF.S(MEAN= 0,

Sm. DEV.= 1).

TABLE 3 SCIIhII PERSONALrrYSCALESANDCLUSTER,PRINCIPALCOMPONENTS(SIIIDY 2): b'&ANS, STANDARD DEVIATIONS, ANDPERCENT MEE~NGDSM-III-R CR~IXRION FORPFXSONAL~~Y DISORIXR

Personality Scale Schizoid ScIlizotypal Paranoid Histrionic Narcissistic AntisociaI Borderline Avoidant Dependent Obs. Comp. Passive Agg. (Self Defeat) Cluster A Cluster B Cluster C

Panicker (n = 194) 31.62 (19.9) 42.96 (21.1) 59.13 (26.8) 50.86 (26.5) 53.09 (19.7) 11.89 (13.75) 54.96 (25.1) 46.61 (26.4) 36.48 (20.4) 53.21 (17.1) 40.38 (20.8) 49.10 (20.1) .2723 (1.15) .2508 (1.44) .3030 (1.34)

Nonpanicker (n = 94) 9% 3% 66% 42% 54% NAa 49% 47% 24% 54% 32% 38%

26.42 (17.7) 29.61 (21.7) 43.77 (30.7) 45.39 (24.4) 45.74 (19.5) 7.80 (10.69) 38.03 (26.0) 31.76 (27.7) 24.70 (18.5) 47.16 (17.9) 32.15 (21.7) 36.97 (20.5) -.5619 (1.28) -.5175 (1.37) -.6253 (1.48)

4% 1% 43% 32% 45% NAa 26% 24% 9% 44% 26% 17%

I 2.19 4.98 4.35 1.69 2.98 2.53 5.19 4.41 4.74 2.77 3.11 4.47 5.56 4.32 5.31

P .0293 < .OOOl < .OOOl .0930 ,032 .0118 < .ODOl < .oool < .OOOl ,059 .0021 < .cOOl < .OOOl < .OOOl < .OcOl

aPercent of subjects meeting criterion cannot be determined for Antisocial Personality Disorder on the basis of the SCID-II Self Report Questionnaire alone.

41

NONCLINICAL PANICKERPERSONALITY

To determine the extent to which panickers and nonpanickers differed on symptomatology from each of the three DSM-III-R clusters, standardized principal components were again extracted from the SCID-II scales comprising each cluster. As can be seen from Table 3, means for panickers exceeded means for nonpanickers on each of the three standardized cluster principal components. The test for lack of parallelism of cluster profiles failed to reach statistical significance, Hotelling-Lawley Trace, F(2, 285) = SO98, p = .6011, suggesting that the extent to which panickers and nonpanickers differed on personality disorder symptomatology was not significantly different across clusters. Though the test for a group by cluster effect did not reach statistical significance, the panicker-nonpanicker cluster difference was greatest on Cluster C (Table 3). Standardized means, standard deviations, and t-statistics for Eysenck’s dimensions of neuroticism and extroversion, Gray’s dimensions of anxiety and impulsivity. and the Beck’s Depression Inventory are presented for panickers and nonpanickers in Table 4. With regard to the Eysenck dimensions, panickers significantly exceeded nonpanickers on neuroticism. The panicker-nonpanicker difference on extroversion approached statistical significance (p = .0!9). Mean for panickers significantly exceeded the mean for nonpanickers on Gray’s dimension of anxiety, but not on impulsivity. It is not surprising that large group differences were observed on both neuroticism and on the anxiety index. Measures of these two dimensions correlate very highly (they were found to correlate +.80 in this sample, N = 288). Panickers were also significantly more symptomatic than nonpanickers on the Beck Depression Inventory. This is also not surprising, as depression has generally been observed to correlate highly (on the order of +.60 to +.70) with measures of anxiety. BDI depression correlated +.72 with the anxiety index used in Study 2 (N = 288). Four discriminant analyses were performed comparing (a) the categorically organized DSM-III-R personality disorders (SCID-II scales), (b) Eysenck’s two-dimensional personality framework, (c) Gray’s two-dimensional personality framework, and (d) BDI depression on ability to discriminate panickers from nonpanickers. The proportion of panickers correctly classified as panickers and the proportion of nonpanickers correctly classified as nonpanickers are depicted in Fig. 2. As can be seen in Fig. 2, overall these four models did not differ significantly in predictive ability. The Eysenck model correctly TABLE 4 STANDARDIZED DIMENSIONAL MFASURES (STUDY2): MEANSAND STANDARD DEVIATIONS

Scale Neuroticism Extroversion Anxiety Irnpulsivity BDI Dawssion

Panicker (n = 194) .2923 -.0699 .3434 .0582 .2191

(0.91) (1.01) (1.32) (1.27) (1.02)

Nonpanicker (n = 94) -6033 .1443 -.7086 -.I201 -.4522

(0.90) (0.97) (1.14) (1.34) (0.78)

t 7.84 1.71 6.65 1.10 5.62

P < .OOOl .0882 < a001 .2715 < .OOOl

H. RICHMAN AND R. NELSON-GRAY

42

C I

80

a ;

70

i

80

: 30 e

y 20 I Y 10 DSM-III-R

m

EYSENCK

GRAY

BDI

Nonpanlckers

FIG. 2. DLSCRIMINANT ANALYSISCLASSIFICATION RAIES.

fied 69% of all subjects on panicker status. Predictive ability was due almost entirely to neuroticism, F(1, 286) = 61.49, p < .OCOl, with extroversion contributing little to the model, F( 1, 286) = 2.92, p = .0882. The Gray model correctly classified 67% of all subjects on panicker status. As was the case with the Eysenck model, virtually all of the model’s predictive ability was due to a single dimension, in this case anxiety, F(1, 286) = 44.16, p < .OOOl, with impulsivity not contributing to the model, F( 1, 286) = 1.21, p = .2715. The DSM-III-R personality disorder categories (SCID-II scales) correctly classified 68% of subjects on panicker status. All SCID-II scales were significant at the .05 level or better with the exception of histrionic (p = .09). The 11 SCIDII scales were ordered as follows with regard to decreasing magnitude of F statistics and R squared: borderline, schizotypal, dependent, avoidant, paranoid, passive-aggressive, narcissistic, obsessive-compulsive, antisocial, schizoid, and histrionic. To determine what, if anything, might link those SCID-II scales that contributed most to the discriminative ability of this model, Pearson correlations were performed on the Study 2 data (n = 288).

NONCLINICAL. PANICKER PERSONALITY

43

Magnitude of SCID-II scale correlations with the Study 2 anxiety index were ordered as follows: avoidant (+.67), self-defeating (+.65), borderline (+.64), dependent (+.61). paranoid (+.53), schizotypal (+.49), narcissistic (+.45), passive-aggressive (+.44). obsessive-compulsive (+.37), antisocial (+.30), schizoid (+.18). and histrionic (+.12). Ordering of SCID-II scale correlations with neuroticism were similar, with borderline PD being most strongly related to neuroticism (r = +.68). Although not a perfect one-to-one correspondence, there does appear to be a considerable relationship between discriminative ability, magnitude of group differences, and the extent to which the SCID-II scale correlates with anxiety and neuroticism. BDI depression correctly classified 66% of subjects on panicker status, F( 1. 286) = 31.57, p c .OOOl. Although the models did not differ markedly in overall discriminative ability, the Eysenck model (i.e., neuroticism) was modestly superior in terms of correctly classifying panickers as such, correctly classifying 71% of panickers (see Fig. 2). It is of interest that BDI depression appeared quite predictive of status as a nonpanicker (87% correctly classified), but not of status as a panicker (only 44% correctly classified). General Discussion The prevalence rates of nonclinical panic of 26.18% in Study 1 and 33.44% in Study 2 are generally consistent with the average of 34.5% for 16 questionnaire studies reported by Norton et al. (1992). As in the present research, these 16 studies did not require the occurrence of a “spontaneous” attack. Some of these studies, as well as the present research, required that panickers experience at least one attack that involved four or more symptoms. Other studies did not maintain this criterion. Comparisons made by Norton et al. (1992) suggest that prevalence rates will be influenced by (a) whether the study involves clinical interviews or questionnaires, (b) whether or not the “spontaneity” criterion is maintained, and (c) whether or not the four-symptom criterion is maintained. Reports of “spontaneous panic,” which may be indicative of greater severity (Cox, Endler, & Swinson, 1991), were rare in both Studies 1 and 2. Panickers were more symptomatic than nonpanickers on seven of the MCMI scales, although magnitude of group differences on the individual scales varied considerably. As was expected, panicker-nonpanicker differences were evident on the avoidant and passive-aggressive scales, both members of the anxious-fearful cluster (Cluster C). Notable panicker-nonpanicker differences were also observed on the borderline scale, and to a lesser extent, on the schizotypal scale. Given that dependent personality disorder has been associated with panic disorder (Mauri, 1992). agoraphobia, (Chambless et al., 1992), and anxiety “neurosis” in general (Tyrer, Casey, & Gall, 1983), a greater panicker-nonpanicker difference on this scale might have been expected. One interpretation of the observed small but statistically significant group difference is that dependent symptomatology might be a “complication” of panic disorder and agoraphobia, and as such would not be fully developed in nonclinical panickers. This interpretation is supported by reports of personality change in response to treatment of agoraphobia. Mavissakalian and Hamann

44

H. RICHMAN AND R. NELSON-GRAY

(1987) found that dependent personality traits, among others, decreased after treatment for agoraphobia whereas other traits (e.g., avoidant) remained comparatively stable. This would appear to support a “complication hypothesis” (Akiskal et al., 1983) for dependent personality disorder in agoraphobics. Panicker means exceeded nonpanicker means on the SCID-II scales in Study 1 more consistently than they did on the MCMI scales, presenting a picture of generally greater personality dysfunction among panickers. Panicker means exceeded nonpanicker means on all SCID-II scales in both studies; however, panicker elevations on one scale in Study 2 (histrionic) did not reach the .OS level of significance. Scales on which consistent SCID-II group differences were apparent across studies were borderline, avoidant, dependent, schizotypal. paranoid, and the proposed category of self-defeating personality disorder. Group differences in terms of percentage of individuals who met DSM-III-R criteria for a personality disorder diagnosis within each category were consistent with group differences in percentage of criteria met. In comparing MCMI and SCID-II data, it becomes apparent that group differences in personality disorder symptomatology will, to some extent, reflect the instrument being used. However, if two instruments converge on the same results, we may be somewhat more confident that a group difference does indeed exist on the construct that the two instruments purportedly measure. MCMI and SCID-II individual scale analyses appear to converge on panickernonpanicker differences in borderline, avoidant, schizotypal, passive-aggressive, and to a somewhat lesser extent, dependent and paranoid symptomatology. In both studies, the scale on which panickers and nonpanickers differed to the greatest extent was borderline. Borderline personality disorder has, in fact, been associated with panic disorder/agoraphobia. Chambless et al. (1992) identified 48% of a sample of 48 agoraphobics as having borderline PD using the MCMI. However, these researchers found the prevalence of borderline PD among agoraphobics to be considerably lower using the MCMI-II. Mauri et al. (1992), utilizing clinical interviews, found borderline to be the most frequently diagnosed personality disorder among 40 panic disordered individuals. Mauri et al. note that Akiskal (1981) also reported an association between borderline personality disorder and panic disorder. The notable group differences on borderline personality disorder observed in these samples suggest a need for further investigation into the relationship between panic and borderline personality disorder. Borderline symptomatology may be a correlate, precursor, consequence, or all of the above in relation to panic attacks. It might be that some individuals are developing both disorders simultaneously. Additionally, it may be that panickers and borderlines experience different symptoms within the borderline personality disorder category. One undertaking that might clarify this relationship would be to determine the extent to which those specific SCID-II borderline items commonly endorsed by panickers differed from, or were similar to, those specific items endorsed by borderlines. For example, we might expect panickers to endorse items related to identity confusion and fear of abandonment, as opposed to items relating to impulsivity and suicidality. Another interesting finding is the large panicker-nonpanicker difference on the schizotypal scale of the SCID-II. Here again, panickers might be endorsing particular items on this scale (e.g., social anxiety and unusual perceptual expe-

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45

riences). Symptomatology from clusters other than C (anxious-fearful) is not unusual in samples of clinical panickers/agoraphobics. This becomes apparent in studies where subthreshold levels of personality disorder symptomatology are reported (e.g., Mavissakalian & Hamann, 1986. 1987). Additionally, some nonspecificity in personality dysfunction would be expected in a group of college-age nonclinical panickers, as personality may not yet have fully solidified at-this young age. It seems intuitive that individuals with anxiety disorders, and anxious individuals in general, should surpass nonanxious controls to a greater extent on personality disorder symptomatology from the anxious-fearful cluster (Cluster C) than on symptomatology from the other two clusters. There have been observations of a “Cluster C” effect among panickers (Friedman et al., 1987) and agoraphobics (Renneberg, Chambless, & Gracely, 1992). The betweengroups cluster differences observed in the present research are modest. However, if we assume a connection between nonclinical and clinical panickers, these findings would appear to support the suggestion of Friedman et al. (1987) that the Cluster C personality disorders (anxious-fearful) are “on a spectrum with panic disorder.” In Study 2, the DSM-III-R categorical personality framework was compared with the dimensional frameworks of H. J. Eysenck (1967) and Jeffrey Gray (1970, 1972, 1973) on ability to discriminate panickers from nonpanickers. Because of its close relationship with anxiety, the discriminative ability of depression, as assessed by the BDI, was also considered. The four models were quite similar in overall predictive ability. All correctly classified a little better than two-thirds of Study 2 subjects on panicker-nonpanicker status, with the Eysenck model being modestly superior in correctly classifying panickers. It should be noted that both the Eysenck and Gray models are essentially onevariable models, as little predictive ability was due to extroversion or impulsivity, respectively. Thus, knowledge of symptomatology on the 11 DSM-III-R categories provided no more discriminative ability than knowledge of one’s position on a single dimension (neuroticism or anxiety). The SCID-II scales, and the other measures utilized in the discriminant analyses, likely contain much redundant information, as no additional variable substantially improved a model containing either neuroticism or anxiety. Interestingly, the BDI was not very successful in correctly classifying panickers (47% correct), but was quite successful in correctly classifying nonpanickers (87% correct). A possible interpretation is that most subjects low on depression were not nonclinical panickers, but not all nonclinical panickers were highly depressed. This would appear to add support to the suggestion of Norton et al. (1992) that nonclinical panickers do not simply represent a group of individuals who are high on general psychopathology. In summary, the present research found that panickers exceeded nonpanickers on MCMI-assessed personality disorder symptomatology on the Cluster C scales (especially avoidant and passive-aggressive), the Cluster A scales, and the borderline scale. On the SCID-II scales, panickers were generally more symptomatic than nonpanickers across both studies, with notable group differences on the borderline, avoidant, schizotypal, self-defeating, and paranoid scales. These scales appeared to have in common a strong relationship with anxiety and neuroticism. Borderline symptomatology was prominent among

46

H. RICHMAN

AND R. NELSON-GRAY

panickers, and more research into this relationship is suggested. Panickers tended to surpass nonpanickers more on symptomatology from Cluster C (anxious-fearful) than on symptomatology from the other two clusters. Though modest in size, this “Cluster c” effect was consistent, if one allows for the strong group difference on the borderline scale. The observed pattern of panicker-nonpanicker differences in personality disorder symptomatology, both on the individual scales of the SCID and MCMI inventories and on the DSM-III-R cluster principal components, suggests similarities between nonclinical panickers and clinical panickers and agoraphobics. This would seem to support the conceptualization of nonclinical panickers as being intermediate on an anxiety continuum between nonpanickers and individuals with panic disorder/agoraphobia. Nonclinical panickers would appear to be an important group for the study of personality variables that may predispose individuals to panic attacks and agoraphobic avoidance. Given the general acceptance of a biological “vulnerability or predisposition” in panic disorder/agoraphobia, it is somewhat surprising that applicability of the theorizing of Eysenck and Gray to these problems has not been well researched. Eysenck’s dimension of neuroticism and Gray’s dimension of anxiety did well in discriminating panickers from nonpanickers when compared with the more complex DSM-III-R personality disorder categories. Neuroticism or anxiety might provide a good starting point in building a model with good predictive ability in determining which nonclinical panickers may eventually develop panic disorder and agoraphobia.

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Eysenck, H. J. (1967). The bid&car basis of person&y. Springfield, IL: Charles C. Thomas. Eysenck, S. B. G., Pearson, P. R., Easting, G., & Allsopp, J. E (1985b). Age norms for impulsiveness, venturesomeness, and empathy in adults. Personality and Individual Dinrences, 6, 613-619.

Friedman, K., Shear, M. K., & Frances, A. (1987). DSM-III personality disorders in panic patients. Journal of Person&y Disorders, 1.132-135. Graham, J. R (1990). MMPI-2Assessing Personality and PsychopathoIogy.New York: oxford Press. Gray, J. A. (1970). The psychophysiological basis of introversion-extroversion. Behavior Research and Therapy, 8, U9-266. Gray, J. A. (1972). lbe psychophysiological nature of introversion-extraversion: A modification of Eysenck’s theory. In V. D. Neblitsyn & J. A Gray (Eds.), Biological bases of individual behavior. London: Academic Press.

Gray, J. A. (1973). Casual theories of personality and how to test them. In J. R. Royce (Ed.), Multivariate analysis of psychological theory. New York: Academic Press. Malan, J. R., Norton, G. R., & Cox, B. J. (1990). Non-clinical panickers: A review of the literature. Canadian Psychology, 31.33 1. Mauri, M., Samo, N., Rossi, V. M., Armani, A., Zambotto, Cassano, G. B., & Akiskal, H. S. (1992). Personality disorders associated with generalized anxiety, panic, and recurrent depressive disorders. Journal of Anxiety Disorders, 6(2), 162-167. Mavissakalian, M., & Hamann, M. S. (1986). DSM-III personality disorder in agoraphobia. Comprehensive Psychiatry, 21,471-479. Mavissakalian, M., & Hamann, M. S. (1987). DSM-III personality disorder in agoraphobia. II. Changes with treatment. Comprehensive Psychiatry, 28.356-361. Millon, T. (1983). Millon Clinical Multiaxial Inventory Manual (3rd edition). Minneapolis: National Computer Systems. Norton, G. R., Dorward, J., & Cox, B. J. (1986). Factors Associated with Panic Attacks in nonclinical subjects. Behavior Therapy, 17,239-252. Norton, G. R., Harrison, B., Hauch, J., & Rhodes, L.(1985). Characteristics of people with infrequent panic attacks. Journal ofAbnormal Psychology, 94,216-221. Norton, G. R., Cox, B. J., & Malan, J. (1992). Nonclinical panickers: A critical review. Clinical PsychoIogy Review, 12,121-139. Nystrom, S., & Lindegrud, B. (1975). Predisposition for mental syndromes: A study comparing predisposition for depression, neurasthenia and anxiety state. Acta Psychiatrica Scandanavia, S&69-76.

Renneberg, B., Chambless, D. L., & Graccly, E. J. (1992). Prevalence of SCID-diagnosed personality disorders in agoraphobic outpatients. Journal of Anxiety Disorders, 6, 11l-l 18. SAS Institute (1985) SAS user’s guide: Statistics (Version 5). Caty, NC: SAS Institute. Spielberger, C. D., Lushene, R. R., Vagg, P R., & Jacobs, G. A. (1983). Manual for the StateTrai?AnxietyInventory (Form Y). Palo Alto, CA: Consulting Psychologists Press. Spitzer, R. L., Williams, J. B. W. (1984). Structured clinical interview for DSM-III personality disorders (KID II). State Psychiatric Institute, New York, NY. Spitzer, R. L., Williams, J. B. W., Gibbon, M.. & First, M. (1990). Strucrured clinical interview for DSM-III-R-personality disorders (SCID-II, vex 1.0). Washington, DC.: American Psychiatric Press. Stewart, S. H., Knize, K., & PihI, R. 0. (1992). Anxiety sensitivity and dependence iu clinical and nonclinical panickers and controls. Journal of Anxiety Disorders, 6, 119-I 3 1. Tyrer, P, Casey, P., & Gall, J. (1983). Relationship between neurosis and personality disorder. British Journal of Psychiatry, 142,404-408.