depression and anxiety: integrating the tripartite and cognitive content-specificity assessment...

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Journal of Psychopathology and Behavioral Assessment (JOBA) pp936-joba-470624 August 29, 2003 22:53 Style file version June 25th, 2002

Journal of Psychopathology and Behavioral Assessment, Vol. 25, No. 4, December 2003 (C© 2003)

Depression and Anxiety: Integrating the Tripartiteand Cognitive Content-Specificity Assessment Models

Richard Beck,1,2 Bradley Benedict,1 and Angie Winkler1

Accepted April 23, 2003

The cognitive content-specificity hypothesis proposes that depression and anxiety can be discriminatedon the basis of unique cognitive profiles. Alternatively, the Tripartite model suggests that, althoughdepression and anxiety share a general distress factor, anhedonia is a characteristic of depression withanxious arousal a characteristic of anxiety. Past research devoted to integrating these two modelshas been limited in a number of ways. To remedy these limitations, this study attempted to assessthe complete Tripartite model and used a multidimensional cognitive assessment tool to handle theheterogeneity of anxious cognitive content. Results on data collected from 411 clients seeking servicesat a university counseling center suggested that a one-to-one mapping between Tripartite dimensionsand cognitive content was possible. Further, variables from each model simultaneously explainedunique variance in depression and anxiety ratings.

KEY WORDS: depression; anxiety; cognitive content-specificity; tripartite model; assessment.

Since the 80s, clinicians and researchers alike havedevoted intensive attention toward the diagnostic and as-sessment issues surrounding depressive and anxious dis-orders. As most are aware, mood and anxiety disor-ders are often comorbid (Judd & Burrows, 1992; Roth,Gurney, Garside, & Kerr, 1972) and depression and anx-iety assessment scales are often significantly intercorre-lated (Dobson, 1985; Gotlib, 1984; Mendels, Weinstein, &Cochrane, 1972; Tanaka-Matsumi & Kameoka, 1986;Zuckerman, Persky, Eckman, & Hopkins, 1967). Over theyears this situation has lead researchers to develop variousassessment schemes to provide clinicians with quantita-tively assessed diagnostic features that can effectively aidin the differential diagnosis of depression and anxiety.

The cognitive content-specificity (CCS) strategy fol-lows basic tenets of Aaron Beck’s cognitive theory ofemotional disorders (Beck, 1976). Hypothesizing a di-rect link between cognition and affect, the CCS strategysuggests that depressive and anxious populations display

1Department of Psychology, Abilene Christian University, Abilene,Texas.

2To whom correspondence should be addressed at Department of Psy-chology, Abilene Christian University, ACU Box 28011, Abilene, Texas79699; e-mail: [email protected].

distinctive cognitive profiles. For over a decade, researchhas generally supported the utility of this model (Beck,Brown, Eidelson, Steer, & Riskind, 1987; Bruch, Mattia,Heinberg, & Holt, 1993; Clark, Beck, & Brown, 1989;Clark, Beck, & Stewart, 1990; Clark, Steer, Beck, &Snow, 1996; Epkins, 1996; Garber, Weiss, & Shanley,1993; Jolly, 1993; Jolly, Dyck, Kramer, & Wherry, 1994;McDermut & Haaga, 1994; Thorpe, Barnes, Hunter, &Hines, 1983; Westra & Kuiper, 1996; Wickless & Kirsch,1988; Woody, Taylor, McLean, & Koch, 1998).

The Tripartite model (Clark & Watson, 1991), analternative strategy for distinguishing depression fromanxiety, has tended to focus on the emotional and physio-logical symptoms of depression and anxiety. The Tripar-tite model suggests that a global distress factor—labeledas either “negative affectivity” or “general distress”—iscommon to both anxiety and depression. Depression isdistinguished from anxiety in that it involves the dimen-sion labeled “anhedonia” or “low positive affect,” whichis characterized by depressed physiology and behaviorwith a concurrent loss of interest in and/or experiencesof pleasure. Anxiety, by contrast, involves the final fac-tor of anxious arousal, characterized by physiological hy-perarousal, which distinguishes it from depressed states.Similar to the CCS strategy, the Tripartite model has been

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252 Beck, Benedict, and Winkler

extensively researched and has demonstrated promise inthe discrimination of depression from anxiety (Watson,Clark, et al., 1995; Watson, Weber, et al., 1995).

What is intriguing about the CCS and Tripartite mod-els is that, viewed as a whole, they are complimentary indescribing the full phenomenological range of depressiveand anxious experiences: Cognition, emotion, and expe-rienced physiological states. This suggests that, if the twomodels could be integrated, a comprehensive picture of de-pression and anxiety should emerge. This thought is notnew, and attempts have been made at integration. However,these efforts have been limited in two important ways.

First, many attempts (e.g., Beck et al., 2001; Jollyet al., 1994; Shapiro, Roberts, & Beck, 1999) aimed at in-tegrating the CCS and Tripartite models have failed to as-sess the full Tripartite model. Second, many studies (e.g.,Beck et al., 2001; Clark, Cook, & Snow, 1998; Jolly et al.,1994; Shapiro et al., 1999) have failed to deal with thelack of specificity displayed by anxious cognitive contentmeasures (Beck & Perkins, 2001). This lack of specificityis likely due to the heterogeneous content of anxious cog-nition (e.g., worry vs. panic-related cognition). This studyattempted to improve upon past efforts at integration byassessing the full Tripartite structure and by using a mul-tidimensional cognitive content measure.

To summarize, this study was an attempt to integratethe CCS and Tripartite assessment models for anxiety anddepression by forging empirical links between cognitivecontent and the Tripartite dimensions. Following previ-ous research, three specific relationships were predicted:Worry would be the cognitive correlate of negative affec-tivity, depressive cognition would be the correlate of an-hedonia, and panic-related cognition would be the cogni-tive correlate of anxious arousal. To test these predictions,clients seeking counseling services at a university coun-seling center completed an assessment battery assessingdepression, anxiety, cognitive content, and the Tripartitedimensions. Improving upon past efforts at integration,a multidimensional assessment of cognitive content wasused. In addition, the Mood and Anxiety Symptom Ques-tionnaire was employed rather than the Positive and Nega-tive Affect Schedule to provide comprehensive assessmentof the entire Tripartite model.

METHOD

Participants and Procedure

Participants were 411 clients seeking counseling ser-vices at Abilene Christian University’s Counseling Center.Approximately 69% of the sample was female with a mean

age of 21.15 (SD= 4.44). As a part of the intake process,participants completed measures of depression, anxiety,cognitive content, and the Tripartite dimensions.

Assessment Instruments

Beck Depression Inventory-II

The Beck Depression Inventory-II (BDI-II; Beck,Steer, & Brown, 1996) is a 21-item self-report inven-tory assessing depressive symptomatology. The BDI-IIhas demonstrated robust reliability and validity coeffi-cients across a variety of populations. In this sample theBDI-II yielded an alpha coefficient of .92.

Beck Anxiety Inventory

The Beck Anxiety Inventory (BAI; Beck & Steer,1993) is a 21-item self-report inventory assessing somaticsymptoms related to anxiety as well as anxious affect. TheBAI has also demonstrated robust reliability and validitycoefficients (Beck & Steer, 1993). In this sample the BAIyielded an alpha of .93.

Mood and Anxiety Symptom Questionnaire

The Mood and Anxiety Symptom Questionnaire(MASQ; Watson & Clark, 1991) is a 90-item self-reportscale developed to assess the Tripartite dimensions ofAnhedonia, Anxious Arousal, and General Distress (Thereare actually three General Distress scales: Depressive,Anxious, and Mixed. In this study only the nonspecificGeneral Distress-Mixed subscale was used). In numerouslarge samples, the MASQ has performed well in identify-ing and discriminating the shared versus unique featuresof depression and anxiety (see Watson, 2000, for a litera-ture review of the MASQ’s psychometric performance). Inthis sample, all the MASQ subscales generated reliabilitycoefficients greater than .80.

University of British Columbia Cognitions Inventory

The University of British Columbia Cognitions In-ventory (UBC-CI; Woody et al., 1998) is a 77-item self-report scale assessing depressive and anxious cognition.For this the Depression, Worry, and Panic subscales ofthe UBC-CI were used. In this sample, the Depression,Worry, and Panic subscales generated alpha coefficientsof .96, .78, and .89 respectively.

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Integrating the Tripartite and CCS Models 253

Table I. Zero-Order Correlations Between Beck Inventories, Mood andAnxiety Symptom Questionnaire (MASQ), and University of British

Columbia—Cognitions Inventory (UBC-CI)

1. 2. 3. 4. 5. 6. 7.

1. BDI-II2. BAI .623. MASQ-General Distress .84 .714. MASQ-Anhedonia .76 .50 .715. MASQ-Anxious Arousal .58 .88 .68 .456. UBC-CI-Worry .48 .44 .42 .28 .427. UBC-CI-Depression .80 .53 .66 .64 .49 .508. UBC-CI-Panic .53 .74 .55 .41 .70 .50 .58

Note. All correlations significant atp < .001.

RESULTS

Correlational Analyses

Table I presents the zero-order correlations betweenthe measures. As might be expected given the nature ofthe variables and the size of the sample, all the measureswere significantly correlated. Much of the intercorrelationbetween these measures can be conceptualized as sharedvariance with General Distress (i.e., negative affectivity).Consequently, partial correlations between all measurescontrolling for shared variance with MASQ-General Dis-tress scores are reported in Table II. Contrasting the zero-order and partial correlations begins to clarify the rela-tionships between the variables. Specifically, once sharedvariance with General Distress was removed, the BDI-IIremained significantly correlated with MASQ-Anhedoniascores but was unrelated to MASQ-Anxious Arousal rat-ings. In contrast, the BAI partial correlation with MASQ-Anxious Arousal was significant, but its relationship withMASQ-Anhedonia was observed to be nonsignificant.

Table II. Partial Correlations Between Beck Inventories, Mood andAnxiety Symptom Questionnaire (MASQ), and University of BritishColumbia—Cognitions Inventory (UBC-CI) Controlling for MASQ-

General Distress Scores

1. 2. 3. 4. 5. 6.

1. BDI-II2. BAI .033. MASQ-Anhedonia .39∗ .044. MASQ-Anxious Arousal .03 .76∗ .085. UBC-CI-Worry .22∗ .27∗ .04 .25∗6. UBC-CI-Depression .59∗ .07 .32∗ .04 .32∗7. UBC-CI-Panic .16 .59∗ .04 .51∗ .38∗ .32∗

∗ p < .001.

Overall, this pattern of results is consistent with the Tripar-tite model. Seeking to observe links between the cognitivevariables and the Tripartite dimensions, it was observedthat, once General Distress was controlled for, UBC-CIPanic scores remained correlated with MASQ-AnxiousArousal scores but were unrelated to MASQ-Anhedoniaratings. UBC-CI Depression scores displayed the oppo-site trend, remaining correlated with MASQ-Anhedoniabut unrelated to MASQ-Anxious Arousal. UBC-CI Worrypartial correlations indicated that worry ratings remainedcorrelated with MASQ-Anxious Arousal rating but wereunrelated to MASQ-Anhedonia scores. Looking over thepartial correlations between the cognitive content and Tri-partite measures, the relationships appear to support spe-cific and unique links between the CCS and Tripartitemodels. As proposed, it appears that depressive cogni-tion shares a unique relationship with anhedonic stateswhereas panic-related cognition appears to be related tophysiological hyperarousal.

A set of hierarchical regression analyses also sup-ported these conclusions. In an equation predicting BDI-IIscores, MASQ-General Distress and UBC-CI Worryscores were entered on step one, MASQ-Anxious Arousaland UBC-CI Panic scores on step two, and, on the finalstep, MASQ-Anhedonia and UBC-CI Depression ratings.On step one, both General Distress (β = .78, p < .001)and Worry ratings (β = .13, p < .001) were significantpredictors accounting for 72% (p < .001) of BDI-II vari-ance. Anxious Arousal and Panic cognition scores did notmake a significant contribution on step two. However, onthe final step both Anhedonia (β = .19, p < .001) andDepressive cognition (β = .37, p < .001) did account foradditional variance in BDI-II scores (1R2 = .10, p <.001). In a second equation predicting BAI scores, againDistress and Worry scores were entered first, with Anhe-donia and Depressive cognition scores entered on step two,and Anxious Arousal and Panic cognition ratings enteredon the final step. Again, both Worry (β = .19, p < .001)and General Distress (β = .63, p < .001) were signifi-cant predictors at step one, accounting for 55% of BAIvariance (p < .001). Neither Anhedonia nor Depressivecognition scores contributed to the prediction at step two.In contrast, both Anxious Arousal (β = .56, p < .001)and Panic cognition (β = .24, p < .001) were significantpredictors on the final step (1R2 = .27, p < .001). Over-all, these analyses suggested that the cognitive and Tripar-tite predictors were not redundant. That is, each explainedunique variance in BDI-II and BAI scores when the as-sociated variables were in the regression equation (e.g.,Panic cognition accounted for unique variance in BAIratings even when Anxious Arousal scores were in theequation).

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Group Comparisons

Given that participants were generally college stu-dents seeking psychological assistance at a universitycounseling center, the sample was mainly comprisedof mild to moderately distressed persons (BDI-II:M =17.97,SD= 11.82; BAI: M = 11.42,SD= 11.33), mostof whom would not meet DSM criteria for mood or anx-iety disorders. In the absence of diagnostic information,cutoffs were employed on both the BDI-II and BAI toidentify severely depressed and anxious individuals. Toensure that participants’ symptoms would meet diagnos-tic criteria, individuals were identified who were in the“severe” range according to the BDI-II and BAI manuals(i.e., BDI-II scores>28 and BAI scores>25). From theseindividuals a subset was identified that exhibited mild tono symptoms (according to the Beck Inventory manuals)on the second scale (BDI-II scores<20 and BAI scores<16). Using these cutoffs, 26 individuals were identifiedas Depressed (BDI-II> 28, BAI< 16) and 6 individualsas Anxious (BAI> 25, BDI-II < 20).

Table III presents the group contrasts for the Anxiousand Depressed groups for the General Distress, AnxiousArousal, and Anhedonia subscales of the MASQ as well asthe Panic, Worry, and Depression subscales of the UBC-Cognitions Inventory. As can be seen in Table III, theAnxious and Depressed groups did not differ on either theGeneral Distress or Worry measures. As expected, thissuggests that negative affectivity and worry are sharedfeatures of both depression and anxiety. By contrast, theDepressed group displayed significantly higher scores onAnhedonia and Depressive cognition, each hypothesizedto be unique features of depression. Finally, the Anxiousgroup displayed significantly higher Anxious Arousal andPanic-related cognition scores. Again, these features werepredicted to be unique features of anxiety.

Table III. Mean Differences for Depressed (BDI-II Scores>28 and BAI Scores<16) and Anxious(BAI > 25, BDI-II < 20) Groups on MASQ and UBC-Cognitions Inventory Subscales

Depressed group Anxious group(N = 26) (N = 6)

Tripartite and CCS measure Mean SD Mean SD t(30)

MASQ-General Distress 46.77 5.93 44.00 5.93 1.03MASQ-Anhedonia 85.72 14.26 70.33 14.12 2.38∗MASQ-Anxious Arousal 23.35 4.79 39.66 8.48 6.46∗∗∗UBC-CI-Worry 15.60 6.29 17.17 5.91 0.55UBC-CI-Depression 54.16 15.85 31.17 3.54 3.49∗∗UBC-CI-Panic 15.38 5.74 24.33 10.09 2.96∗∗

∗ p < .05 (two-tailed).∗∗ p < .01 (two-tailed).∗∗∗ p < .001 (two-tailed).

DISCUSSION

The findings of this study provide a framework tointegrate the CCS and Tripartite models of depression andanxiety. Most of the links between these models havebeen noted by others in the literature. What is uniqueabout the current study was the comprehensive assess-ment of the both the CCS and Tripartite models. Follow-ing the data, it appears that a fairly clear one-to-one map-ping can be made between the cognitive and affective/physiological domains. Specifically, worry (i.e., cognitiverumination) appears to be common to both depression andanxiety and is accompanied by emotional distress and tur-moil (i.e., negative affectivity). Depression can be dis-tinguished from anxiety in that it is characterized by an-hedonic states accompanied by self-critical and hopelessautomatic thoughts. And, finally, anxiety, in contrast to theanhedonic states of depression, is characterized by phys-iological hyperarousal which appears to be accompaniedby panic-related automatic thoughts (e.g., “I’m going tohave a heart attack”). In retrospect, these links are obvi-ous, but, because of psychometric issues in this literaturediscussed earlier, it has taken some time to verify each linkempirically within a single sample.

Should these relationships continue to be replicatedin other samples, and this is important given the sizeof the diagnostic groups used in this study, cliniciansmight be armed with a more comprehensive diagnostictool when making differential diagnoses. That is, althoughsome might contend that one model is effective enough,the present data suggest that each model accounts forunique variance in depression and anxiety scores. Thissuggests that clinicians should simultaneously evaluatephysiology, emotion, and cognition when making differ-ential diagnoses. Should symptoms in one domain proveopaque, the clinician could sample a correlated domain for

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Integrating the Tripartite and CCS Models 255

clarification. That is, cognitive content might illuminatephysiology and vice versa. Knowing the specific cogni-tive and physiological correlates in this situation would beimportant. For example, worry, historically thought to beassociated with anxiety disorders, is not helpful in discrim-inating mood from anxiety disorders. In short, cliniciansshould be able to incrementally improve diagnostic valid-ity by employing multiple correlated diagnostic indices.Future research using such a protocol might be tested todetermine if diagnostic improvement is actually observedin the clinic.

One of the theoretical problems that has plagued theCCS and Tripartite model research, and plagues this studyas a consequence, has been the failure to deal effectivelywith the heterogeneity of the anxiety disorders. Depres-sion is a fairly homogeneous syndrome, which mostlyvaries in severity. The anxiety disorders, by contrast, area diverse lot. Clearly not all anxiety disorders are char-acterized by physiological hyperarousal and panic-relatedthoughts. However, Panic Disorder is uniquely character-ized by these symptoms. In short, the Tripartite and CCSmodels appear to have developed two methods for dis-criminating Major Depression from Panic Disorder. Thisis no mean feat in that depression and Panic Disorder arefrequently comorbid (Breier, Charney, & Heninger, 1984;Leckman, Merikangas, Pauls, Prusoff, & Weissman, 1983;Vollrath & Angst, 1989). However, it remains an openempirical issue as to whether the other anxiety disorderscan be effectively discriminated from depression. Thismay prove difficult in some cases. For example, worry,the defining feature of Generalized Anxiety Disorder, hasbeen found to be a shared feature of depression and anxi-ety. Perhaps, it might be suggested, Generalized AnxietyDisorder (and some other anxiety disorders) is indicatedby elevated Anxious Arousal scores without concurrentelevations of panic-related cognition. However, it remainsto be seen that the physiological hyperarousal displayedin other anxiety disorders (like GAD) is severe enough todistinguish it from depressive states.

Finally, given the concurrent assessment of cogni-tion, mood, and physiological state it is impossible to es-tablish, in this data set, the primacy of cognition or emo-tion. This issue has a long theoretical and empirical history.The present data support the proposition that one-to-onemappings between cognition and emotion do exist. How-ever, in this study the temporal ordering of cognition andemotion could not be specified. Do panic-related thoughtsproduce physiological hyperarousal? Alternatively, doesanhedonia produce hopelessness? Although the causal in-teraction between cognition and emotion is probably bidi-rectional and mutually reinforcing, most theoretical workhas suggested that the causal flow is from cognition to

emotion. That is, most cognitive theorists suggest that itis information-processing (i.e., cognitive attributions) thatproduces emotional and physiological experiences in re-sponse to life events. Even more precisely, cognitive the-ory suggest thatspecific cognitionsgeneratespecific emo-tional responses. Thus, cognitive theory implies a clearmapping between cognition and emotion. Although thereare exceptions to this model, the current data strongly sup-port these basic tenets of the cognitive theory of emotionaldisorders.

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