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Further evidence for the validity of the beck anxiety inventory with psychiatric outpatients
Journal ofAnxiery Disorders. Vol. 7, Pp. 195-205, Printed in the USA. All rights resaved.
0887-6185193 $6.00 + .I0 Copyright Q 1993 Pergamon Press Ltd.
1993
Further Evidence for the Validity of the Beck Anxiety Inventory with Psychiatric Outpatients ROBERT A. STEER, ED.D.,AND WILLIAM F. RANIERI, D.O. Department of Psychiatry, University of Medicine and Dentistry of New Jersey
AARON T. BECK, M.D. Department of Psychiatry, University of Pennsylvania Medical School
DAVID A. CLARK, PH.D. University of New Brunswick
Abstract -
To provide further information about the psychometric characteristics of the Beck Anxiety Inventory (BAI), the BAI was administered to 470 outpatients with mixed psychiatric disorders along with the revised Beck Depression Inventory (BDI) and the SCL-90-R. The BAI’s internal consistency was high (alpha = .92), and it was significantly more correlated with the SCL-90-R Anxiety subscale (r = .81) than it was with SCL-90-R Depression subscale (r = .62). However, it was also significantly correlated with the BDI (r = .61). The mean BAI scores of the 141 (30.0%) outpatients with mood disorders and the 86 (18.3%) outpatients with anxiety disorders were comparable, but higher than the mean BAI score of the 243 (51.7%) outpatients with other disorders. A principal components analysis found the previously reported subjective, neurophysiological, panic, and autonomic dimensions. The results are discussed as providing further evidence for the use of the BAI with psychiatric outpatients.
The current revision process for the DSM-IV has rekindled interest in the repeated controversy over the differentiation of anxiety and depression (Katon & Roy-Byrne, 1991). Numerous researchers have noted the high degree of convergence between anxiety and depression with respect to mood, symptoms, and syndromes (Clark & Watson, 1991; Maser & Cloninger, 1990; Stavrakaki & Vargo, 1986; Watson & Kendall, 1989). A number of reasons for the strong relationship between anxiety and depression have been postulated,
Correspondence and reprint requests should be sent to Robert A. Steer, UMDNJ, School of Osteopathic Medicine, Department of Psychiatry, 301 Haddon Ave., Camden, NJ 08103-1505. 195
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and these include (a) considerable overlap in the symptoms and signs used to define anxiety and depression (Clark, 1989); (b) high comorbidity rates for major depression, panic, and generalized anxiety disorders (Barlow et al., 1986; Breier et al., 1985); (c) a probable common underlying biological and genetic diathesis (Kendler et al., 1987; Watson & Kendall, 1989); and (d) a common underlying, negative affect dimension (Clark & Watson, 1991; Watson & Tellegen, 1985). No doubt the strongest evidence supporting the unitary view of anxiety and depression as representing a single continuum concerns the high correlation between the self-report and clinical rating scales used to assess anxiety and depression. Anxiety and depression measures often correlate as highly between constructs as within constructs (Dobson, 1985; Gotlib & Cane, 1989). In their extensive review of anxiety and depression instruments, Clark and Watson (1991) concluded that the average convergent validity (correlation between measures of the same construct) was in the low .7Os, whereas the discriminant validity (correlation between measures of different constructs) ranged from .62 to .70. One of the reasons for the low degree of discriminant validity has been attributed by Gotlib and Cane (1989) to the extent of item overlap found within self-report instruments of anxiety and depression. For example in their review, Gotlib and Cane (1989) found that on average, 17% of these instruments’ items assessed symptoms common to both anxiety and depression. The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988; Beck & Steer, 1990) is a 21-item self-report instrument for measuring the severity of anxiety, especially developed to minimize its relationship with depression. Emphasis was placed on including items in the BAI that measured unique symptom features of anxiety not shared with depression. Because the BAI focused on unique features of anxiety, 14 of its items represent somatic symptoms, whereas the remaining seven symptoms reflect specific cognitions associated with the subjective aspects of anxiety and panic. In using the BAI, subjects rate the severity of each symptom on a four-point scale ranging from (0) “Not at all” to (3) “Severely - I could barely stand it.” A total score is calculated by summing across severity ratings for all 21 items. Because the BAI is a new instrument, few researchers have investigated its psychometric properties. The inventory possesses high internal consistency (alphas of .92 and .94) and one-week test-retest reliabilities of .75 and .73 according to Beck, Epstein et al. (1988) and Fydrich et al. (1992), respectively. Moreover, Beck and Steer (1990) conducted a centroid cluster analysis on 393 outpatients with anxiety disorders and found that the 21 BAI items reflected four symptom clusters representing neurophysiological, subjective, panic, and autonomic features of anxiety. The BAI displays high concurrent validity with other self-report and clinical rating scales of anxiety. For example, Beck, Epstein et al. (1988) found that it correlates .51 with the revised Hamilton Rating Scale for Anxiety (Riskind, Beck, Brown, & Steer, 1987), and Fydrich et al. (1992) reported that it correlates .58 and .47, respectively, with the Trait and State scales of the State-Trait Anxiety Inventory, Form-Y (Spielberger, 1983). Furthermore, ini-
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tial studies on the discriminant validity of the BAI were encouraging, with Beck, Epstein et al. (1988) reporting a .48 correlation between the BAI and revised Beck Depression Inventory (BDI; Beck & Steer, 1987) for 160 diagnostically mixed outpatients. The purpose of the present study is to provide further information about the psychometric properties of the BAI. First, we wished to ascertain what the convergent and discriminant validities of the BAI were with respect to other standardized self-report measures of anxiety and depression. Second, we wanted to determine if the symptom dimensions for the BAI that Beck and Steer (1990) found for outpatients evaluated at the Philadelphia Center for Cognitive Therapy would be comparable to those for psychiatric outpatients drawn from a different treatment facility. METHOD Patients The sample consisted of 470 consecutive outpatients evaluated by the faculty practice plan of the Department of Psychiatry, University of Medicine and Dentistry, School of Osteopathic Medicine, located in Cherry Hill, NJ. All the patients were diagnosed by experienced psychiatrists according to DSM-III-R (American Psychiatric Association, 1987) criteria. Although the psychiatrists were asked to use the Structured Clinical Interview for DSM-III-R (SCID; Spitzer et al., 1990) in making their diagnoses, none of them was monitored with respect to its use. These psychiatrists were actively involved in teaching medical students and residents how to derive DSM-III-R diagnoses from semi-structured interviews based upon the SCID criteria, but no interjudge agreement study was conducted with respect to diagnosis. The sample was composed of 284 (60.4%) women and 186 (39.6%) men. There were 460 (97.9%) whites, 8 (1.7%) blacks, and 2 (0.4%) Asians. The mean age was 40.31 (SD = 14.67) years old. The patients were considered to represent three broad diagnostic groups for analysis purposes; there were 141 (30.0%) patients diagnosed with mood disorders, 86 (18.3%) with anxiety disorders, and 243 (51.7%) with other types of disorders. Major depression diagnoses (N = 92, 19.6%) reflected the majority of the mood disorders; panic disorder (N = 32, 6.8%) was the modal diagnosis in the anxiety disorders; and adjustment diagnoses (N = 153, 32.6%) represented the majority of the other disorders. Less than 5% of the sample was diagnosed with a comorbid disorder. Instruments Beck Depression Inventory. The revised BDI (Beck & Steer, 1987) is a 21item self-report instrument used to assess the severity of depression. Each of the 21 symptoms is represented by four statements reflecting increasing levels of depression. Each item is rated on a four-point scale ranging from 0 to 3, and a BDI total score is calculated by summing the 21 ratings. A number of studies have described and supported the psychometric properties of the BDI with
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respect to diverse samples of psychiatric populations (Beck, Steer, & Garbin, 1988). The coefficient alpha for the BDI in the present sample is .90. SCL-90-R The SCL-90-R (Derogatis, 1983) was selected as a self-report instrument for measuring a broad spectrum of psychopathology. It is a go-item symptom inventory for which patients are asked to rate the degree of distress they experience with respect to each symptom, using a five-point rating scale ranging from 0 (“Not at all”) to 4 (“Extremely”). The SCL-90-R was scored for its nine syndromes representing (1) Somatization, (2) Obsessive-Compulsiveness, (3) Interpersonal Sensitivity, (4) Depression, (5) Anxiety, (6) Hostility, (7) Phobic Anxiety, (8) Paranoid Ideation, and (9) Psychoticism, along with three global indices of distress called the Global Severity Index, Positive Symptom Distress Index, and Positive Symptom Total. The coefficients alpha of the aforementioned scales for the 366 (77.9%) outpatients who completed the SCL-90-R here are .90, .88, .88, .86, .9 1, .89, 83, .83, .80, .82, and .97, respectively. The SCL-90-R was specifically included to evaluate the BAI’s concurrent validity with respect to the SCL-90-R Anxiety subscale and its discriminant validity with respect to the SCL-90-R Depression subscale. Procedure After signing voluntary consent forms, the patients were administered printed versions of the BDI, BAI, and SCL-90-R as part of a standardized intake evaluation battery completed by everyone seeking outpatient treatment. Because the SCL-90-R was added later to the intake battery, only 366 (77.9%) outpatients completed this instrument. RESULTS The mean BAI total score for the 470 outpatients was 18.70 (SD = 12.67). This mean value indicates that the sample was moderately anxious according to the diagnostic ranges presented by Beck and Steer (1990). The difference of 4.8 points between the mean BAI total scores of the 284 women (M = 20.60, SD = 12.70) and 186 men (M = 15.80, SD = 12.08) was significant, f(468) = 4.08, p < .OOl, but age (yrs) was not significantly correlated (r = .02) with the BAI total scores. Internal Consistency The coefficient alpha for the BAI was .92, and the corrected item-total correlations of the 21 items ranged from .41 for item 1 (Numbness) to .68 for item 9 (Terrified). All the corrected item-total correlations were significant beyond the .OOl level, one-tailed test, even after a Bonferroni adjustment (alpha/21) was used to control for the experimentwise error rate.
FURTHER
Component
EVIDENCE
199
Structure
To determine whether gender and age should be controlled for in evaluating the interrelationships among the BAI responses, canonical correlations were first calculated between these two demographic variables and the set of 21 BAI items. The canonical correlation of the set of BAI items with gender (0 = Male, 1 = Female) was .32, which was significant beyond the .OOl level, two-tailed test, Wilks’ lambda = .90, F(21, 448) = 2.44. With respect to age (yrs), the canonical correlation of .30 was also significant, Wilks’ lambda = .91, F (21, 448) = 2.13. Because gender and age explained 10.2% and 9.1%, respectively, of the variation in the BAI responses, these variables were controlled for in the subsequent principal-components analysis, even though we did not consider such percentages to be clinically meaningful. A partial intercorrelation matrix among the 21 BAI items was calculated in which the items’ relationships with sex and age were partiallcd out, and this matrix was used in the principal components analysis. Table 1 presents the varimax-rotated principal components loadings for the BAI items after controlling for gender and age. Kaiser’s Measure of Sampling Adequacy (Dziuban & Shirkey, 1974) was .93, a value that Kaiser (1970) considers to be “marvelous.” The partial correlation matrix for the 21 BAI items had four eigenvalues > 1.00, and varimax rotation was thus restricted to four components. The consecutive eigenvalues were 8.27, 1.66, 1.29, and 1.09, and the four rotated components explained 58.7% of the total variation (Table 1). The structure of the principal components presented in Table 1 for the present sample of 470 outpatients with mixed psychiatric disorders corresponds almost exactly to the item compositions of the four clusters described by Beck and Steer (1990) with 393 outpatients diagnosed with anxiety disorders. Therefore, their naming conventions were used. The salient variable similarity indices (s-index) (Cattell et al., 1969) between Beck and Steer’s (1991) clusters and the same-named components here were all significant beyond the .05 level. As Table 1 shows, the BAI symptoms with salient loadings (2 .45) on the first component are unable to relax, fear of the worst happening, terrified, nervous, fear of losing control, and scared, and this component represents subjective aspects of anxiety. The second component presented in Table 1 was composed of numbness, wobbliness, dizzy, unsteady, hands trembling, shaky, and faint. These symptoms reflected neurophysiological aspects of anxiety. The third component’s symptoms were feeling hot, face flushed, and sweating, and this component suggested autonomic aspects of anxiety. With respect to the fourth component, the symptoms were feelings of choking, difficulty breathing, and fear of dying. This component had symptoms typical of those experienced by patients during panic attacks and was called the panic component. The only two items that did not load saliently (2 .45) on any of the principal components were for heart pounding and indigestion. The highest loadings for these two items were on the second, neurophysiological component (Table 1). These two symptoms were the only two items that differed with respect to belonging to the same symptom dimensions that Beck and Steer (1990) found. Heart pounding loaded on their panic dimension, and indigestion loaded on their autonomic dimension.
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R.A.STEERET AL. TABLE 1 VARIMAX-ROTATEDPFUNCIPALCOMPONENTS LOALXNGSOFTHEBECKANXIEIY INVENTORYFOROUIFATENTSCONTROLLINGFORGENDERAND AGE
Components Item
I
II
III
IV
h2
.16 .l4 .lO .23
.24 .19 .I0 -.08 .26 .32 .31 .17 .29 .05 .61 .02 .08 .12 .a .hz .30 .17 .43 .14 .05 5.2 17.1
.33 66 .57 60 .67 .52 .49 .65 .67 .66 .55 64 .65 .62 .56 .61 66 .30 .56 64 .72 58.7 loo.0
Numbness
.07
.&I
Feeling hot Wobbliness Unable to relax Fear of the worst Dizzy Heart pounding Unsteady Terrified Nervous Feelings of choking Hand trembling Shaky
.18 .21 .fz .z .lO .29 .28 .7_1 .l2
.12 .a .31 .ll .u .40 .ll .28 .27 .24 .7J .B .26 .27 .oo .20 .35 .@ .21 .17 7.9 30.0
Fear losing control Difficulty breathing Fear of dying Scared Indigestion Faint Face flushed Sweating % Total % Common
.12
.34 .32 .l!J .15 .40 .Q .27 .03 .16 .20 39.4 31.6
.ll .36 .38 .17 .08 .23 .13 .lO .ll .20 .31 .03 .12 .26 .36 .74 .8fI 6.2 21.3
N&e.N = 470Salient loadings > .45areundalmed.
To estimate the stability of the four components, the 470 outpatients were randomly divided in half, and a separate principal components analysis was performed for each sample of 235 outpatients, controlling for sex and age and using a varimax rotation. The factor matching procedure described by Kaiser et al. (1971) was then used to compare not only the match between the two sets of principal components structures, but also the matches among the specific components found in each sample. The mean cosine between the two samples’ overall principal-components structures was .97, and the cosines between the components in both samples corresponding to the subjective, neurophysiological, autonomic, and panic dimensions were .98, .98, .98, and .96, respectively. For interpretive purposes, the cosines may be considered to correspond to correlation coefficients in which a value of 0 indicates no similarity and a value of 1.00 indicates total similarity. Therefore, the stability of the principal components structure based upon the total sample of 470 outpatients was considered by us to be extremely high.
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FURTHER EVIDENCE
Concurrent and Discriminant
Validities
The correlation between the BAI and BDI was .61 (p < .OOl), and this coefficient was significantly higher than the coefficient of .48 reported by Beck, Epstein et al. (1988), z = 2.02, p c .05. Table 2 gives the correlations of the BAI with the SCL-90-R subscales along with those of the BDI for comparative purposes. The BAI and BDI were both significantly correlated with all of the SCL-90-R subscales, even after using a separate Bonferroni adjustment of alpha/l2 for each of the Beck instruments. However, the BAI was more positively correlated with the SCL-90-R Anxiety subscale than the BDI was, Hotelling t(363) = 7.26, p c .OOl. In contrast, the BDI was more positively correlated with the SCL-90-R Depression scale than the BAI was, Hotelling t(363) = 7.82, p < .OOl. Such a pattern of correlations supports not only the concurrent validities of the BAI and BDI, but also their discriminant validities. Each Beck instrument was more positively related to its same-named SCL-90R subscale than each was to the opposite-named SCL-90-R subscale. Table 2 shows the correlations of the BAI and BDI with the SCL-90-R Global Severity Index for 366 of the outpatients for whom SCL-90-R data were available; this index is the best single estimate of overall symptom distress (Derogatis, 1983). The magnitudes of both correlations were high (2 .75) and indicated that the Beck instruments were also measuring overall symptom distress. However, the BDI was more positively correlated with the Global Severity Index than the BAI was, Hotelling t(363) = 2.15, p < .05; the BDI may thus be more affected by overall symptom distress than the BAI is. Because the correlation (r = .61) between the BAI and the BDI was significantly higher than that (r = .48) reported by Beck, Epstein et al. (1988). we
TABLE 2 CoRRELAnoNs OF THE BECK ANXIEIY AND DEPRESION INVENTURIESWITH THE SCL-90-R Instrument
BAI
BDI
Somatization
.75
Obsessive-compulsive Interpersonal sensitivity Depression Anxiety Hostility Phobic anxiety Paranoid ideation Psychoticism Global severity index Positive symptom total Positive symptom distress index
.63 .51 .62 .81 .47 .57 .45 .52 .75 .70 64
.58 .71 66 .82 .62 .58 .47 .57 66 .80 .72 .70
N&Z.N= 366BAI
= Beck Anxiety Inventory, BDI = revised Beck Depression Invenlory. All of the correlations are significant beyond the ,001 level. onetailed test. after using a Bonfmerroni adjustment of a&h/12.
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decided to ascertain whether the difference might be related to the different diagnostic compositions of the two outpatient samples. Approximately 32% of Beck, Epstein et al.‘s (1988) sample was composed of outpatients diagnosed with mood disorders, whereas 58% were diagnosed with anxiety disorders. In contrast, 30.0% of the present outpatients were diagnosed with mood disorders; 18.3% were diagnosed with anxiety disorders; and 51.7% were diagnosed with other types of disorders, especially adjustment disorders. Consequently, we drew a subsample of our 470 outpatients to match the broad diagnostic proportions reflected by Beck, Epstein et al.‘s (1988) 160 outpatients. There were only 86 outpatients diagnosed with anxiety disorders in our sample. Therefore, we included all of them in the subsample and then randomly selected 47 of the 141 patients with mood disorders and 15 out of the 243 with other types of disorders to compose the rest of the subsample. In the resulting 148 outpatient subsample, the diagnostic composition was comparable to Beck, Epstein et al’s (1988) sample with respect to mood (32%), anxiety (58%), and other (10%) disorders. The correlation between the BAI and BDI in the subsample decreased to .50 (p < .OOl), and was now comparable to the correlation of .48 previously described by Beck, Epstein et al. (1988) z = .23, n.s. A one-way analysis of variance was used to determine whether the BAI total scores differentiated the outpatients diagnosed with mood, anxiety, and other types of disorders, F(2.467) = 5.80, p < .Ol. Because the ANOVA indicated that the mean levels of self-reported anxiety had significantly differed among the diagnostic groups, a post hoc Scheffe’ test was conducted. The mean BAI total score for the 141 outpatients diagnosed with mood disorders was 20.78 (SD = 12.55); the mean BAI total score for the 86 outpatients diagnosed with anxiety disorders was 20.66 (SD = 12.65); and the BAI total score for the 243 outpatients diagnosed with other types of disorders was 16.79 (SD = 12.49). The Scheffe’ test indicated that the mean BAI total scores of the outpatients diagnosed with anxiety and mood disorders were comparable, and each of these two groups’ mean BAI total scores was significantly higher than the mean BAI total score of the outpatients diagnosed with other types of disorders, p < .Ol. Because the BAI was specifically developed to minimize its relationships with depressive symptoms, and the above results indicated that the mean BAI total scores of the anxiety and mood groups were comparable, we wished to ascertain whether patients diagnosed with specific types of anxiety disorders might be differentiated from patients with mood disorders. Only the outpatients diagnosed with panic disorders represented a sufficient number (N > 30) of cases to permit such a comparison. The mean BAI total score (M = 26.41, SD = 13.30) of the 32 outpatients with panic disorders was significantly higher than that reported above for the 141 outpatients diagnosed with mood disorders, r(171) = 2.26, p < .05. Because < 5% of the sample had been diagnosed with comorbid disorders, we were unable to test whether the mean BAI total scores of the outpatients differed with respect to the presence of either a comorbid mood or a comorbid anxiety disorder.
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EVIDENCE
DISCUSSION The overall pattern of results provides additional support for the reliability and validity of the BAI as an instrument for measuring the severity of anxiety in psychiatric outpatients. The internal consistency of the BAI here (alpha = .92) with a mixed diagnostic sample of 470 outpatients is identical to that found by Beck, Epstein et al. (1988) with their clinical sample. The compositions of the BAI symptom dimensions in the present outpatients are comparable to those reported by Beck and Steer (1990) for outpatients diagnosed with anxiety disorders. Therefore, the BAI’s symptoms represent neurophysiological, subjective, panic, and autonomic dimensions of selfreported anxiety that are generalizable not only to outpatients diagnosed with mixed DSM-III-R disorders, but also outpatients diagnosed only with DSMIII-R anxiety disorders. The findings with respect to the BAI’s ability to discriminate psychiatric disorders are mixed. The outpatients diagnosed with either anxiety or mood disorders had higher mean BAI total scores than the mean BAI total score of the outpatients diagnosed without anxiety and mood disorders, but the mean BAI total scores of the outpatients diagnosed with either anxiety or mood disorders were comparable. The BAI was unable to differentiate the outpatients classified into broad groups representing either anxiety or mood disorders. The inability of the BAI to distinguish between anxiety and mood disorders in general might be attributable to a lack of diagnostic completeness.* Although the psychiatrists had been asked to follow SCID criteria and screen for comorbid disorders, the low rate of comorbidity (< 5%) suggests that they may have only focused on the primary disorder. Consequently, the prevalence of comorbid mood and anxiety disorders might have actually been higher than that found. Patients diagnosed with comorbid mood and anxiety disorders would be expected to have higher BAI total scores than those diagnosed only with mood disorders. However, the mean BAI total score of the outpatients diagnosed with panic disorders was significantly higher than the mean BAI total score of the outpatients diagnosed with mood disorders. Additional research is needed to determine whether the BAI is clinically useful for differentiating anxious and depressed outpatients in general, but the present study does indicate that the BAI discriminates outpatients diagnosed with panic disorders from those diagnosed with mood disorders. With respect to the controversy over the differentiation of anxiety and depression, the present study adds more fuel to the debate because the association between self-report measures of anxiety and depression was found to be sensitive to the diagnostic composition of the outpatients being studied. The magnitude of the relationship between the BAI and BDI was higher (r = .61) when the diagnostic composition of the present sample reflected primarily nonmood and nonanxiety disorders (52%). but decreased (r = SO) in a subsample that represented primarily anxiety disorders (58%). The increase in the proportion of clinically anxious outpatients may have, in turn, increased the *The authors are indebted to an anonymous reviewer for offering the following possible explanation for the lack of differentiation
of patients diagnosed
with mood and anxiety disorders.
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number and severity of physiological hyperarousal symptoms in the subsample; such symptoms have been postulated by Clark and Watson (1991) in their tripartite model of common and unique symptoms of anxiety and depression to be the distinguishing symptoms of anxiety. The BAI would be sensitive to the presence of such unique symptoms, because 14 of its 21 items reflect somatic symptoms related to physiological hyperarousal. Future research will have to ascertain what balance in the diagnostic composition of a sample affects the magnitude of the relationship between self-reported anxiety and depression, and whether physiological hyperarousal symptoms, instead of cognitions and feelings, are the crucial symptoms for distinguishing anxiety from depression. Gender was significantly related to the BAI total scores. The mean difference of approximately five points found here between the sexes is only one point higher than the four-point difference that Beck and Steer (1990) found in patients diagnosed with anxiety disorders. Women describe slightly higher overall levels of anxiety with the BAI than men do, and it may be advisable to weigh the gender of a respondent in interpreting the overall severity of a patient’s BAI total score. However, both Beck and Steer’s (1990) and our outpatients did not represent diagnostic samples that were balanced with respect to gender, and the present data are thus more representative of women’s, than men’s, responses. It is not recommended that separate cut-off scores be employed for men and women. The present sample of outpatients was predominantly white and drawn from a suburban, middle- to upper-middle class community near a large east-coast city. Obviously, future research with the BAI needs to assess its psychometric characteristics with respect to minorities, patients drawn from other geographical locations, and different age groups, such as adolescents. The usefulness of the BAI for measuring the severity of anxiety in inpatients should also be addressed. Finally, the specific relationships between the BAI and measures of depression, such as the BDI, need to be more thoroughly investigated in diverse clinical settings.
REFERENCES American Psychiatric
Association (1987). Diagnosfic and statisfical manual of mental disorders (3rd edition, Revised). Washington, DC: Author. Barlow, D. H., DiNardo, P A., Vermilyea, B. B., Vennilyea, .I. A., & Blanchard, E. B. (1986). Comorbidity and depression among the anxiety disorder: Issues in diagnosis and classification. Journal of Nervous and Mental Disease, 174,63-72. Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56, 893-897. Beck, A. T., & Steer, R. A. (1987). Manual for the revised Beck Depression Inventory. San Antonio, TX: Psychological Corporation. Beck, A. T., & Steer, R. A. (1990). Manual for the Beck Anxiety Inventory. San Antonio, TX: Psychological Corporation. Beck, A. T., Steer, R. A., & Garbin, M. G. (1988). Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8, 77-100.
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Breier, A., Charney, D. S., & Heninger, G. R. (1985). The diagnostic validity of anxiety disorders and their relationship to depressive illness. American Journal of Psychiatry, 142,787-797. Cattell, R. B., Balcar, K. R., Horn, J. L., & Nesselroade, J. D. (1969). Factor matching procedures: An improvement of the s-index; with tables. Educational and Psychological Measurement, 29,781-792.
Clark, L. A,, & Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal ofAbnormal Psychology, 100.316-336. Derogatis, L. R. (1983). SCL-90-R administration, scoring, and procedures manual-II. Towson, MD: Clinical Psychometric Research. Dobson, K. S. (1985). The relationship between anxiety and depression. Clinical Psychology Review, $307-324.
Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for factor analyses. Psychological Bulletin, 81,358-361. Fydrich, T., Dowdall, D., & Chambless, D. L. (1992). Reliability and validity of the Beck Anxiety Inventory. Journal of Anxiety Disorders, 6.55-61. Gotlib, I. H., & Cane, D. B. (1989). Self-report assessment of depression and anxiety. In P. C. Kendall & D. Watson @is.), Anxiery and depression: Distinctive and overlapping features (pp. 131-169). New York: Academic Press. Kaiser, H. E (1970). A second generation little jiffy. Psychometrika, 35,401-415. Kaiser, H. F., Hunka, S., & Bianchini, J. C. (1971). Relating factors between studies based upon different iodividuats. Multivariate Behavioral Research, 6,409422. Katon, W., & Roy-Byrne, P P (1991). Mixed anxiety and depression. Journal of Abnormal Psychology, 100.337-345. Kendler, K., Heath, A. C., Martin, N. G., & Eaves, L. J. (1987). Symptoms of anxiety and symptoms of depression. Archives of Geneml Psychiutry, 44.451-457. Maser, J. D., & Cloninger, C. R. (Eds.) (1990). Comorbidity of mood and anxiety disorders. Washington, DC: American Psychiatric Press. Spielberger, C. D. (1983). Manual for the State-Trait Anxiety Inventory (Form Y). Palo Alto, CA: Consulting Psychologists Press. Spitzer, R. L., Williams, J. B. W., Gibbon. M., & First, M. B. (1990). User’s guidefor the Structured Clinical Interview for DSM-III-R. Washington, DC: American Psychiatric Press. Stavrakaki, C., & Vargo, B. (1986). The relationship of anxiety and depression: A review of the literature. British Journal of Psychiutty, 149.7-16. Watson, D., & Kendall, P C. (1989). Common and differentiating features of anxiety and depression: Current findings and future directions. In P. C. Kendall & D. Watson @ids.), Anxiety and depression: Distinctive and overlapping features (pp. 83-129). New York: Academic Press. Watson, D., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219-235.
0887-6185193 $6.00 + .I0 Copyright Q 1993 Pergamon Press Ltd.
1993
Further Evidence for the Validity of the Beck Anxiety Inventory with Psychiatric Outpatients ROBERT A. STEER, ED.D.,AND WILLIAM F. RANIERI, D.O. Department of Psychiatry, University of Medicine and Dentistry of New Jersey
AARON T. BECK, M.D. Department of Psychiatry, University of Pennsylvania Medical School
DAVID A. CLARK, PH.D. University of New Brunswick
Abstract -
To provide further information about the psychometric characteristics of the Beck Anxiety Inventory (BAI), the BAI was administered to 470 outpatients with mixed psychiatric disorders along with the revised Beck Depression Inventory (BDI) and the SCL-90-R. The BAI’s internal consistency was high (alpha = .92), and it was significantly more correlated with the SCL-90-R Anxiety subscale (r = .81) than it was with SCL-90-R Depression subscale (r = .62). However, it was also significantly correlated with the BDI (r = .61). The mean BAI scores of the 141 (30.0%) outpatients with mood disorders and the 86 (18.3%) outpatients with anxiety disorders were comparable, but higher than the mean BAI score of the 243 (51.7%) outpatients with other disorders. A principal components analysis found the previously reported subjective, neurophysiological, panic, and autonomic dimensions. The results are discussed as providing further evidence for the use of the BAI with psychiatric outpatients.
The current revision process for the DSM-IV has rekindled interest in the repeated controversy over the differentiation of anxiety and depression (Katon & Roy-Byrne, 1991). Numerous researchers have noted the high degree of convergence between anxiety and depression with respect to mood, symptoms, and syndromes (Clark & Watson, 1991; Maser & Cloninger, 1990; Stavrakaki & Vargo, 1986; Watson & Kendall, 1989). A number of reasons for the strong relationship between anxiety and depression have been postulated,
Correspondence and reprint requests should be sent to Robert A. Steer, UMDNJ, School of Osteopathic Medicine, Department of Psychiatry, 301 Haddon Ave., Camden, NJ 08103-1505. 195
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and these include (a) considerable overlap in the symptoms and signs used to define anxiety and depression (Clark, 1989); (b) high comorbidity rates for major depression, panic, and generalized anxiety disorders (Barlow et al., 1986; Breier et al., 1985); (c) a probable common underlying biological and genetic diathesis (Kendler et al., 1987; Watson & Kendall, 1989); and (d) a common underlying, negative affect dimension (Clark & Watson, 1991; Watson & Tellegen, 1985). No doubt the strongest evidence supporting the unitary view of anxiety and depression as representing a single continuum concerns the high correlation between the self-report and clinical rating scales used to assess anxiety and depression. Anxiety and depression measures often correlate as highly between constructs as within constructs (Dobson, 1985; Gotlib & Cane, 1989). In their extensive review of anxiety and depression instruments, Clark and Watson (1991) concluded that the average convergent validity (correlation between measures of the same construct) was in the low .7Os, whereas the discriminant validity (correlation between measures of different constructs) ranged from .62 to .70. One of the reasons for the low degree of discriminant validity has been attributed by Gotlib and Cane (1989) to the extent of item overlap found within self-report instruments of anxiety and depression. For example in their review, Gotlib and Cane (1989) found that on average, 17% of these instruments’ items assessed symptoms common to both anxiety and depression. The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988; Beck & Steer, 1990) is a 21-item self-report instrument for measuring the severity of anxiety, especially developed to minimize its relationship with depression. Emphasis was placed on including items in the BAI that measured unique symptom features of anxiety not shared with depression. Because the BAI focused on unique features of anxiety, 14 of its items represent somatic symptoms, whereas the remaining seven symptoms reflect specific cognitions associated with the subjective aspects of anxiety and panic. In using the BAI, subjects rate the severity of each symptom on a four-point scale ranging from (0) “Not at all” to (3) “Severely - I could barely stand it.” A total score is calculated by summing across severity ratings for all 21 items. Because the BAI is a new instrument, few researchers have investigated its psychometric properties. The inventory possesses high internal consistency (alphas of .92 and .94) and one-week test-retest reliabilities of .75 and .73 according to Beck, Epstein et al. (1988) and Fydrich et al. (1992), respectively. Moreover, Beck and Steer (1990) conducted a centroid cluster analysis on 393 outpatients with anxiety disorders and found that the 21 BAI items reflected four symptom clusters representing neurophysiological, subjective, panic, and autonomic features of anxiety. The BAI displays high concurrent validity with other self-report and clinical rating scales of anxiety. For example, Beck, Epstein et al. (1988) found that it correlates .51 with the revised Hamilton Rating Scale for Anxiety (Riskind, Beck, Brown, & Steer, 1987), and Fydrich et al. (1992) reported that it correlates .58 and .47, respectively, with the Trait and State scales of the State-Trait Anxiety Inventory, Form-Y (Spielberger, 1983). Furthermore, ini-
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197
tial studies on the discriminant validity of the BAI were encouraging, with Beck, Epstein et al. (1988) reporting a .48 correlation between the BAI and revised Beck Depression Inventory (BDI; Beck & Steer, 1987) for 160 diagnostically mixed outpatients. The purpose of the present study is to provide further information about the psychometric properties of the BAI. First, we wished to ascertain what the convergent and discriminant validities of the BAI were with respect to other standardized self-report measures of anxiety and depression. Second, we wanted to determine if the symptom dimensions for the BAI that Beck and Steer (1990) found for outpatients evaluated at the Philadelphia Center for Cognitive Therapy would be comparable to those for psychiatric outpatients drawn from a different treatment facility. METHOD Patients The sample consisted of 470 consecutive outpatients evaluated by the faculty practice plan of the Department of Psychiatry, University of Medicine and Dentistry, School of Osteopathic Medicine, located in Cherry Hill, NJ. All the patients were diagnosed by experienced psychiatrists according to DSM-III-R (American Psychiatric Association, 1987) criteria. Although the psychiatrists were asked to use the Structured Clinical Interview for DSM-III-R (SCID; Spitzer et al., 1990) in making their diagnoses, none of them was monitored with respect to its use. These psychiatrists were actively involved in teaching medical students and residents how to derive DSM-III-R diagnoses from semi-structured interviews based upon the SCID criteria, but no interjudge agreement study was conducted with respect to diagnosis. The sample was composed of 284 (60.4%) women and 186 (39.6%) men. There were 460 (97.9%) whites, 8 (1.7%) blacks, and 2 (0.4%) Asians. The mean age was 40.31 (SD = 14.67) years old. The patients were considered to represent three broad diagnostic groups for analysis purposes; there were 141 (30.0%) patients diagnosed with mood disorders, 86 (18.3%) with anxiety disorders, and 243 (51.7%) with other types of disorders. Major depression diagnoses (N = 92, 19.6%) reflected the majority of the mood disorders; panic disorder (N = 32, 6.8%) was the modal diagnosis in the anxiety disorders; and adjustment diagnoses (N = 153, 32.6%) represented the majority of the other disorders. Less than 5% of the sample was diagnosed with a comorbid disorder. Instruments Beck Depression Inventory. The revised BDI (Beck & Steer, 1987) is a 21item self-report instrument used to assess the severity of depression. Each of the 21 symptoms is represented by four statements reflecting increasing levels of depression. Each item is rated on a four-point scale ranging from 0 to 3, and a BDI total score is calculated by summing the 21 ratings. A number of studies have described and supported the psychometric properties of the BDI with
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respect to diverse samples of psychiatric populations (Beck, Steer, & Garbin, 1988). The coefficient alpha for the BDI in the present sample is .90. SCL-90-R The SCL-90-R (Derogatis, 1983) was selected as a self-report instrument for measuring a broad spectrum of psychopathology. It is a go-item symptom inventory for which patients are asked to rate the degree of distress they experience with respect to each symptom, using a five-point rating scale ranging from 0 (“Not at all”) to 4 (“Extremely”). The SCL-90-R was scored for its nine syndromes representing (1) Somatization, (2) Obsessive-Compulsiveness, (3) Interpersonal Sensitivity, (4) Depression, (5) Anxiety, (6) Hostility, (7) Phobic Anxiety, (8) Paranoid Ideation, and (9) Psychoticism, along with three global indices of distress called the Global Severity Index, Positive Symptom Distress Index, and Positive Symptom Total. The coefficients alpha of the aforementioned scales for the 366 (77.9%) outpatients who completed the SCL-90-R here are .90, .88, .88, .86, .9 1, .89, 83, .83, .80, .82, and .97, respectively. The SCL-90-R was specifically included to evaluate the BAI’s concurrent validity with respect to the SCL-90-R Anxiety subscale and its discriminant validity with respect to the SCL-90-R Depression subscale. Procedure After signing voluntary consent forms, the patients were administered printed versions of the BDI, BAI, and SCL-90-R as part of a standardized intake evaluation battery completed by everyone seeking outpatient treatment. Because the SCL-90-R was added later to the intake battery, only 366 (77.9%) outpatients completed this instrument. RESULTS The mean BAI total score for the 470 outpatients was 18.70 (SD = 12.67). This mean value indicates that the sample was moderately anxious according to the diagnostic ranges presented by Beck and Steer (1990). The difference of 4.8 points between the mean BAI total scores of the 284 women (M = 20.60, SD = 12.70) and 186 men (M = 15.80, SD = 12.08) was significant, f(468) = 4.08, p < .OOl, but age (yrs) was not significantly correlated (r = .02) with the BAI total scores. Internal Consistency The coefficient alpha for the BAI was .92, and the corrected item-total correlations of the 21 items ranged from .41 for item 1 (Numbness) to .68 for item 9 (Terrified). All the corrected item-total correlations were significant beyond the .OOl level, one-tailed test, even after a Bonferroni adjustment (alpha/21) was used to control for the experimentwise error rate.
FURTHER
Component
EVIDENCE
199
Structure
To determine whether gender and age should be controlled for in evaluating the interrelationships among the BAI responses, canonical correlations were first calculated between these two demographic variables and the set of 21 BAI items. The canonical correlation of the set of BAI items with gender (0 = Male, 1 = Female) was .32, which was significant beyond the .OOl level, two-tailed test, Wilks’ lambda = .90, F(21, 448) = 2.44. With respect to age (yrs), the canonical correlation of .30 was also significant, Wilks’ lambda = .91, F (21, 448) = 2.13. Because gender and age explained 10.2% and 9.1%, respectively, of the variation in the BAI responses, these variables were controlled for in the subsequent principal-components analysis, even though we did not consider such percentages to be clinically meaningful. A partial intercorrelation matrix among the 21 BAI items was calculated in which the items’ relationships with sex and age were partiallcd out, and this matrix was used in the principal components analysis. Table 1 presents the varimax-rotated principal components loadings for the BAI items after controlling for gender and age. Kaiser’s Measure of Sampling Adequacy (Dziuban & Shirkey, 1974) was .93, a value that Kaiser (1970) considers to be “marvelous.” The partial correlation matrix for the 21 BAI items had four eigenvalues > 1.00, and varimax rotation was thus restricted to four components. The consecutive eigenvalues were 8.27, 1.66, 1.29, and 1.09, and the four rotated components explained 58.7% of the total variation (Table 1). The structure of the principal components presented in Table 1 for the present sample of 470 outpatients with mixed psychiatric disorders corresponds almost exactly to the item compositions of the four clusters described by Beck and Steer (1990) with 393 outpatients diagnosed with anxiety disorders. Therefore, their naming conventions were used. The salient variable similarity indices (s-index) (Cattell et al., 1969) between Beck and Steer’s (1991) clusters and the same-named components here were all significant beyond the .05 level. As Table 1 shows, the BAI symptoms with salient loadings (2 .45) on the first component are unable to relax, fear of the worst happening, terrified, nervous, fear of losing control, and scared, and this component represents subjective aspects of anxiety. The second component presented in Table 1 was composed of numbness, wobbliness, dizzy, unsteady, hands trembling, shaky, and faint. These symptoms reflected neurophysiological aspects of anxiety. The third component’s symptoms were feeling hot, face flushed, and sweating, and this component suggested autonomic aspects of anxiety. With respect to the fourth component, the symptoms were feelings of choking, difficulty breathing, and fear of dying. This component had symptoms typical of those experienced by patients during panic attacks and was called the panic component. The only two items that did not load saliently (2 .45) on any of the principal components were for heart pounding and indigestion. The highest loadings for these two items were on the second, neurophysiological component (Table 1). These two symptoms were the only two items that differed with respect to belonging to the same symptom dimensions that Beck and Steer (1990) found. Heart pounding loaded on their panic dimension, and indigestion loaded on their autonomic dimension.
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R.A.STEERET AL. TABLE 1 VARIMAX-ROTATEDPFUNCIPALCOMPONENTS LOALXNGSOFTHEBECKANXIEIY INVENTORYFOROUIFATENTSCONTROLLINGFORGENDERAND AGE
Components Item
I
II
III
IV
h2
.16 .l4 .lO .23
.24 .19 .I0 -.08 .26 .32 .31 .17 .29 .05 .61 .02 .08 .12 .a .hz .30 .17 .43 .14 .05 5.2 17.1
.33 66 .57 60 .67 .52 .49 .65 .67 .66 .55 64 .65 .62 .56 .61 66 .30 .56 64 .72 58.7 loo.0
Numbness
.07
.&I
Feeling hot Wobbliness Unable to relax Fear of the worst Dizzy Heart pounding Unsteady Terrified Nervous Feelings of choking Hand trembling Shaky
.18 .21 .fz .z .lO .29 .28 .7_1 .l2
.12 .a .31 .ll .u .40 .ll .28 .27 .24 .7J .B .26 .27 .oo .20 .35 .@ .21 .17 7.9 30.0
Fear losing control Difficulty breathing Fear of dying Scared Indigestion Faint Face flushed Sweating % Total % Common
.12
.34 .32 .l!J .15 .40 .Q .27 .03 .16 .20 39.4 31.6
.ll .36 .38 .17 .08 .23 .13 .lO .ll .20 .31 .03 .12 .26 .36 .74 .8fI 6.2 21.3
N&e.N = 470Salient loadings > .45areundalmed.
To estimate the stability of the four components, the 470 outpatients were randomly divided in half, and a separate principal components analysis was performed for each sample of 235 outpatients, controlling for sex and age and using a varimax rotation. The factor matching procedure described by Kaiser et al. (1971) was then used to compare not only the match between the two sets of principal components structures, but also the matches among the specific components found in each sample. The mean cosine between the two samples’ overall principal-components structures was .97, and the cosines between the components in both samples corresponding to the subjective, neurophysiological, autonomic, and panic dimensions were .98, .98, .98, and .96, respectively. For interpretive purposes, the cosines may be considered to correspond to correlation coefficients in which a value of 0 indicates no similarity and a value of 1.00 indicates total similarity. Therefore, the stability of the principal components structure based upon the total sample of 470 outpatients was considered by us to be extremely high.
201
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Concurrent and Discriminant
Validities
The correlation between the BAI and BDI was .61 (p < .OOl), and this coefficient was significantly higher than the coefficient of .48 reported by Beck, Epstein et al. (1988), z = 2.02, p c .05. Table 2 gives the correlations of the BAI with the SCL-90-R subscales along with those of the BDI for comparative purposes. The BAI and BDI were both significantly correlated with all of the SCL-90-R subscales, even after using a separate Bonferroni adjustment of alpha/l2 for each of the Beck instruments. However, the BAI was more positively correlated with the SCL-90-R Anxiety subscale than the BDI was, Hotelling t(363) = 7.26, p c .OOl. In contrast, the BDI was more positively correlated with the SCL-90-R Depression scale than the BAI was, Hotelling t(363) = 7.82, p < .OOl. Such a pattern of correlations supports not only the concurrent validities of the BAI and BDI, but also their discriminant validities. Each Beck instrument was more positively related to its same-named SCL-90R subscale than each was to the opposite-named SCL-90-R subscale. Table 2 shows the correlations of the BAI and BDI with the SCL-90-R Global Severity Index for 366 of the outpatients for whom SCL-90-R data were available; this index is the best single estimate of overall symptom distress (Derogatis, 1983). The magnitudes of both correlations were high (2 .75) and indicated that the Beck instruments were also measuring overall symptom distress. However, the BDI was more positively correlated with the Global Severity Index than the BAI was, Hotelling t(363) = 2.15, p < .05; the BDI may thus be more affected by overall symptom distress than the BAI is. Because the correlation (r = .61) between the BAI and the BDI was significantly higher than that (r = .48) reported by Beck, Epstein et al. (1988). we
TABLE 2 CoRRELAnoNs OF THE BECK ANXIEIY AND DEPRESION INVENTURIESWITH THE SCL-90-R Instrument
BAI
BDI
Somatization
.75
Obsessive-compulsive Interpersonal sensitivity Depression Anxiety Hostility Phobic anxiety Paranoid ideation Psychoticism Global severity index Positive symptom total Positive symptom distress index
.63 .51 .62 .81 .47 .57 .45 .52 .75 .70 64
.58 .71 66 .82 .62 .58 .47 .57 66 .80 .72 .70
N&Z.N= 366BAI
= Beck Anxiety Inventory, BDI = revised Beck Depression Invenlory. All of the correlations are significant beyond the ,001 level. onetailed test. after using a Bonfmerroni adjustment of a&h/12.
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decided to ascertain whether the difference might be related to the different diagnostic compositions of the two outpatient samples. Approximately 32% of Beck, Epstein et al.‘s (1988) sample was composed of outpatients diagnosed with mood disorders, whereas 58% were diagnosed with anxiety disorders. In contrast, 30.0% of the present outpatients were diagnosed with mood disorders; 18.3% were diagnosed with anxiety disorders; and 51.7% were diagnosed with other types of disorders, especially adjustment disorders. Consequently, we drew a subsample of our 470 outpatients to match the broad diagnostic proportions reflected by Beck, Epstein et al.‘s (1988) 160 outpatients. There were only 86 outpatients diagnosed with anxiety disorders in our sample. Therefore, we included all of them in the subsample and then randomly selected 47 of the 141 patients with mood disorders and 15 out of the 243 with other types of disorders to compose the rest of the subsample. In the resulting 148 outpatient subsample, the diagnostic composition was comparable to Beck, Epstein et al’s (1988) sample with respect to mood (32%), anxiety (58%), and other (10%) disorders. The correlation between the BAI and BDI in the subsample decreased to .50 (p < .OOl), and was now comparable to the correlation of .48 previously described by Beck, Epstein et al. (1988) z = .23, n.s. A one-way analysis of variance was used to determine whether the BAI total scores differentiated the outpatients diagnosed with mood, anxiety, and other types of disorders, F(2.467) = 5.80, p < .Ol. Because the ANOVA indicated that the mean levels of self-reported anxiety had significantly differed among the diagnostic groups, a post hoc Scheffe’ test was conducted. The mean BAI total score for the 141 outpatients diagnosed with mood disorders was 20.78 (SD = 12.55); the mean BAI total score for the 86 outpatients diagnosed with anxiety disorders was 20.66 (SD = 12.65); and the BAI total score for the 243 outpatients diagnosed with other types of disorders was 16.79 (SD = 12.49). The Scheffe’ test indicated that the mean BAI total scores of the outpatients diagnosed with anxiety and mood disorders were comparable, and each of these two groups’ mean BAI total scores was significantly higher than the mean BAI total score of the outpatients diagnosed with other types of disorders, p < .Ol. Because the BAI was specifically developed to minimize its relationships with depressive symptoms, and the above results indicated that the mean BAI total scores of the anxiety and mood groups were comparable, we wished to ascertain whether patients diagnosed with specific types of anxiety disorders might be differentiated from patients with mood disorders. Only the outpatients diagnosed with panic disorders represented a sufficient number (N > 30) of cases to permit such a comparison. The mean BAI total score (M = 26.41, SD = 13.30) of the 32 outpatients with panic disorders was significantly higher than that reported above for the 141 outpatients diagnosed with mood disorders, r(171) = 2.26, p < .05. Because < 5% of the sample had been diagnosed with comorbid disorders, we were unable to test whether the mean BAI total scores of the outpatients differed with respect to the presence of either a comorbid mood or a comorbid anxiety disorder.
FURTHER
203
EVIDENCE
DISCUSSION The overall pattern of results provides additional support for the reliability and validity of the BAI as an instrument for measuring the severity of anxiety in psychiatric outpatients. The internal consistency of the BAI here (alpha = .92) with a mixed diagnostic sample of 470 outpatients is identical to that found by Beck, Epstein et al. (1988) with their clinical sample. The compositions of the BAI symptom dimensions in the present outpatients are comparable to those reported by Beck and Steer (1990) for outpatients diagnosed with anxiety disorders. Therefore, the BAI’s symptoms represent neurophysiological, subjective, panic, and autonomic dimensions of selfreported anxiety that are generalizable not only to outpatients diagnosed with mixed DSM-III-R disorders, but also outpatients diagnosed only with DSMIII-R anxiety disorders. The findings with respect to the BAI’s ability to discriminate psychiatric disorders are mixed. The outpatients diagnosed with either anxiety or mood disorders had higher mean BAI total scores than the mean BAI total score of the outpatients diagnosed without anxiety and mood disorders, but the mean BAI total scores of the outpatients diagnosed with either anxiety or mood disorders were comparable. The BAI was unable to differentiate the outpatients classified into broad groups representing either anxiety or mood disorders. The inability of the BAI to distinguish between anxiety and mood disorders in general might be attributable to a lack of diagnostic completeness.* Although the psychiatrists had been asked to follow SCID criteria and screen for comorbid disorders, the low rate of comorbidity (< 5%) suggests that they may have only focused on the primary disorder. Consequently, the prevalence of comorbid mood and anxiety disorders might have actually been higher than that found. Patients diagnosed with comorbid mood and anxiety disorders would be expected to have higher BAI total scores than those diagnosed only with mood disorders. However, the mean BAI total score of the outpatients diagnosed with panic disorders was significantly higher than the mean BAI total score of the outpatients diagnosed with mood disorders. Additional research is needed to determine whether the BAI is clinically useful for differentiating anxious and depressed outpatients in general, but the present study does indicate that the BAI discriminates outpatients diagnosed with panic disorders from those diagnosed with mood disorders. With respect to the controversy over the differentiation of anxiety and depression, the present study adds more fuel to the debate because the association between self-report measures of anxiety and depression was found to be sensitive to the diagnostic composition of the outpatients being studied. The magnitude of the relationship between the BAI and BDI was higher (r = .61) when the diagnostic composition of the present sample reflected primarily nonmood and nonanxiety disorders (52%). but decreased (r = SO) in a subsample that represented primarily anxiety disorders (58%). The increase in the proportion of clinically anxious outpatients may have, in turn, increased the *The authors are indebted to an anonymous reviewer for offering the following possible explanation for the lack of differentiation
of patients diagnosed
with mood and anxiety disorders.
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number and severity of physiological hyperarousal symptoms in the subsample; such symptoms have been postulated by Clark and Watson (1991) in their tripartite model of common and unique symptoms of anxiety and depression to be the distinguishing symptoms of anxiety. The BAI would be sensitive to the presence of such unique symptoms, because 14 of its 21 items reflect somatic symptoms related to physiological hyperarousal. Future research will have to ascertain what balance in the diagnostic composition of a sample affects the magnitude of the relationship between self-reported anxiety and depression, and whether physiological hyperarousal symptoms, instead of cognitions and feelings, are the crucial symptoms for distinguishing anxiety from depression. Gender was significantly related to the BAI total scores. The mean difference of approximately five points found here between the sexes is only one point higher than the four-point difference that Beck and Steer (1990) found in patients diagnosed with anxiety disorders. Women describe slightly higher overall levels of anxiety with the BAI than men do, and it may be advisable to weigh the gender of a respondent in interpreting the overall severity of a patient’s BAI total score. However, both Beck and Steer’s (1990) and our outpatients did not represent diagnostic samples that were balanced with respect to gender, and the present data are thus more representative of women’s, than men’s, responses. It is not recommended that separate cut-off scores be employed for men and women. The present sample of outpatients was predominantly white and drawn from a suburban, middle- to upper-middle class community near a large east-coast city. Obviously, future research with the BAI needs to assess its psychometric characteristics with respect to minorities, patients drawn from other geographical locations, and different age groups, such as adolescents. The usefulness of the BAI for measuring the severity of anxiety in inpatients should also be addressed. Finally, the specific relationships between the BAI and measures of depression, such as the BDI, need to be more thoroughly investigated in diverse clinical settings.
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Association (1987). Diagnosfic and statisfical manual of mental disorders (3rd edition, Revised). Washington, DC: Author. Barlow, D. H., DiNardo, P A., Vermilyea, B. B., Vennilyea, .I. A., & Blanchard, E. B. (1986). Comorbidity and depression among the anxiety disorder: Issues in diagnosis and classification. Journal of Nervous and Mental Disease, 174,63-72. Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56, 893-897. Beck, A. T., & Steer, R. A. (1987). Manual for the revised Beck Depression Inventory. San Antonio, TX: Psychological Corporation. Beck, A. T., & Steer, R. A. (1990). Manual for the Beck Anxiety Inventory. San Antonio, TX: Psychological Corporation. Beck, A. T., Steer, R. A., & Garbin, M. G. (1988). Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8, 77-100.
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Breier, A., Charney, D. S., & Heninger, G. R. (1985). The diagnostic validity of anxiety disorders and their relationship to depressive illness. American Journal of Psychiatry, 142,787-797. Cattell, R. B., Balcar, K. R., Horn, J. L., & Nesselroade, J. D. (1969). Factor matching procedures: An improvement of the s-index; with tables. Educational and Psychological Measurement, 29,781-792.
Clark, L. A,, & Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal ofAbnormal Psychology, 100.316-336. Derogatis, L. R. (1983). SCL-90-R administration, scoring, and procedures manual-II. Towson, MD: Clinical Psychometric Research. Dobson, K. S. (1985). The relationship between anxiety and depression. Clinical Psychology Review, $307-324.
Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for factor analyses. Psychological Bulletin, 81,358-361. Fydrich, T., Dowdall, D., & Chambless, D. L. (1992). Reliability and validity of the Beck Anxiety Inventory. Journal of Anxiety Disorders, 6.55-61. Gotlib, I. H., & Cane, D. B. (1989). Self-report assessment of depression and anxiety. In P. C. Kendall & D. Watson @is.), Anxiery and depression: Distinctive and overlapping features (pp. 131-169). New York: Academic Press. Kaiser, H. E (1970). A second generation little jiffy. Psychometrika, 35,401-415. Kaiser, H. F., Hunka, S., & Bianchini, J. C. (1971). Relating factors between studies based upon different iodividuats. Multivariate Behavioral Research, 6,409422. Katon, W., & Roy-Byrne, P P (1991). Mixed anxiety and depression. Journal of Abnormal Psychology, 100.337-345. Kendler, K., Heath, A. C., Martin, N. G., & Eaves, L. J. (1987). Symptoms of anxiety and symptoms of depression. Archives of Geneml Psychiutry, 44.451-457. Maser, J. D., & Cloninger, C. R. (Eds.) (1990). Comorbidity of mood and anxiety disorders. Washington, DC: American Psychiatric Press. Spielberger, C. D. (1983). Manual for the State-Trait Anxiety Inventory (Form Y). Palo Alto, CA: Consulting Psychologists Press. Spitzer, R. L., Williams, J. B. W., Gibbon. M., & First, M. B. (1990). User’s guidefor the Structured Clinical Interview for DSM-III-R. Washington, DC: American Psychiatric Press. Stavrakaki, C., & Vargo, B. (1986). The relationship of anxiety and depression: A review of the literature. British Journal of Psychiutty, 149.7-16. Watson, D., & Kendall, P C. (1989). Common and differentiating features of anxiety and depression: Current findings and future directions. In P. C. Kendall & D. Watson @ids.), Anxiety and depression: Distinctive and overlapping features (pp. 83-129). New York: Academic Press. Watson, D., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219-235.