Mr. Voelz is a PhD candidate in the Department of Psychology at Florida State University in Tallahassee.

Dr. Joiner is the Bright-Burton Professor of Psychology and director of the University Psychology Clinic in the Department of Psychology at Florida State University.

For information on measures which assess negative and positive affectivity (ie, Positive and Negative Affect Schedule), and physiological hyperarousal (ie, Beck Anxiety Inventory), contact Thomas Joiner (joiner@psy.fsu.edu).

Acknowledgments: The authors report no financial, academic, or other support of this work.


 

Abstract

With sound theory and demonstrated validity, the Tripartite Model of Anxiety and Depression has been shown to enhance conceptualization of anxious and depressive symptomatology, leading to more reliable assessment and diagnosis of depressive disorders among adolescents and adults in clinical, community, and college samples. It is suggested that the attendant measurement techniques of negative and positive affectivity (ie, Positive and Negative Affect Schedule) and physiological hyperarousal (ie, Beck Anxiety Inventory) be incorporated into standard assessment protocol as quick, convenient, and reliable methods of screening patients for anxiety, depression, and comorbid anxiety and depression.  Improved identification and conceptualization of presenting depressive and anxious symptomatology will lead to more accurate patient diagnoses which, in turn, will lead to implementation of the most appropriate and effective treatment for a given disorder.

 

Introduction

Mood disorders are the most common mental disorders treated by psychiatrists, comprising 28% of overall psychiatric visits.1 This standing is unlikely to change, as the incidence of depression in the general population appears to be steadily increasing.2  Prevalence rates for major depressive disorder have been estimated at 20% to 25% for women and 9% to 12% for men, with women experiencing major depression twice as often as men.3 Notably, these prevalence rates and gender differences appear to persist across the adult life span. As the risk for depression continues to grow, researchers have also found the age of onset to be steadily decreasing,4 thus directing attention toward an increasingly vulnerable and potentially undertreated population—adolescents. As is true with adults, the occurrence of depressive disorders among adolescents is common (lifetime incidence is 20% or greater), costly (for both patients and healthcare providers), persistent (the average episode length is 8 months), recurrent (single episodes are very rare, if they exist at all), and relapsing (75% to 80% of patients will relapse prior to complete symptom remission). It is thus crucial that mental health providers be competent in their ability to clearly identify presenting depressive symptomology, make reliable clinical diagnoses, and implement the most appropriate and effective treatment for any given depressive disorder among both adults and adolescents.

 

The Tripartite Model

Logically, effective treatment of depression depends largely upon the accurate identification and conceptualization of presenting symptomology, which then leads to a treatment-directing clinical diagnosis. It is thus assumed that more accurate conceptualizations of symptoms will ultimately lead to more effective treatment. The Tripartite Model of Anxiety and Depression5 may serve such a purpose. Developed by Clark and Watson, the model proposes that anxiety and depressive disorders have shared and specific components. More explicitly, it suggests that pure anxiety and depression overlap considerably through a general, nonspecific factor called negative affectivity (NA), which reflects the level of averse feelings within an individual. For example, low NA corresponds to a state of calmness and serenity, whereas high NA includes mood states such as anger, contempt, disgust, fear, and nervousness.6 However, there are areas of differentiation between anxiety and depression. The remaining two factors of this model are positive affectivity (PA), which, when low, is relatively specific to depression and represents the level of pleasant feelings within an individual—eg, interest, enthusiasm, delight, and excitement,—and physiological hyperarousal (PH)—eg, heart pounding, shortness of breath, trembling or shaking hands, dizziness, dry mouth, and lightheadedness—which is relatively specific to anxiety.

To sum up, the Tripartite Model of Anxiety and Depression proposes the following:

(1) Anxiety is characterized by high NA and high PH;
(2) Depression is characterized by high NA and low PA (feelings of anhedonia); and
(3) Comorbid anxiety and depression is characterized by high NA, low PA, and high PH.

In support of this model, a large body of research has validated these three factors in child, adolescent, and adult samples.7-11

How has the conceptualization of these three factors been integrated with, and useful to, existing research on depression? Importantly, the conceptualization of depressive symptomology based on the tripartite model has shed light on the long-asserted existence of gender differences among depressed adolescents. A consistent finding over the past few decades is that approximately twice as many adolescent girls are depressed as adolescent boys,12 a finding that parallels the gender differences found in depressed adults.13

What might account for the gender difference observed in clinical depression? While some have suggested that the gender difference results from greater recurrence of depression among girls,14 others have suggested that girls simply experience twice the number of new depressive cases when compared to boys.12 However, Joiner, and colleagues15 applied the conceptualization of the tripartite model (ie, measuring levels of NA, PA, and PH) to a sample of depressed adolescent inpatients, and produced intriguing preliminary results that may elucidate prior questions and inconsistencies regarding the debate over gender differences. They found that previously asserted gender differences do not exist among adolescents with pure depression (high NA, low PA). Rather, they found that girls with depressive symptoms were far more likely to have comorbid anxious symptoms (+high PH) than boys with depressive symptoms. Thus, prior research examining potential gender differences may not have differentiated between pure forms and comorbid forms of depressive and anxious psychopathology. The findings of Joiner and colleagues support the emerging view that generalized negative affect and PH (the two tripartite components that represent pure anxiety when elevated) are important in understanding gender differences in depression (for similar findings among adult samples, see Joiner and Blalock,16 Ochoa and colleagues,17 and Romanoski and colleagues18).

Not only have the components of the tripartite model (ie, NA, PA, and PH) been shown to be associated with self-report measures of anxiety and depression, they have also been shown to be closely related to physiological measures in recent research examining differential brain activity in anxious and depressed individuals. For example, in 1995, Heller and colleagues19 found that individuals with high levels of anxiety exhibited increased right parietotemporal activity compared to individuals with low levels of anxiety. In contrast, individuals with high levels of depression exhibited reduced right parietotemporal activity compared to individuals with low levels of depression (for similar findings, see Keller and colleagues20). Recently, Voelz and colleagues21 extended these findings by providing evidence for a longitudinal relationship between patterns of right posterior brain activity and the components of the tripartite model. Accordingly, they found that the level of right posterior brain activity successfully predicted future levels of PH (anxiety) and PA (depression) such that increased right posterior activity was associated with increased anxiety (including the specific component of PH) while decreased right posterior activity was associated with decreased PA.

Recent studies have also demonstrated that PA appears to be related to the left frontal region of the brain.  More specifically, while increased left frontal activity is associated with increased PA (hence, less depressive symptomology22,23), decreased left frontal activity is associated with decreased PA (hence, increased depressive symptomology24,25). Davidson and colleagues26 recently replicated the reported association between PA and left frontal brain activity and further reported that decreased activity in the left frontal region (and thus low PA) appears to also be related to decreased immunological functioning in humans. This finding is consistent with prior investigations that have found levels of PA and NA to be associated with quality of self-reported health. More specifically, high levels of NA and low levels of PA, appear to be independently related to poorer health conditions.27-30 In summation, research has invaluably strengthened the external validity of the tripartite model while concurrently expanding our knowledge of depressive phenomena through its own application, by uncovering intriguing relationships between NA, PA, PH, regional brain activation, and personal health.

 

Improved Assessment and Treatment of Depression

With sound theory and demonstrated validity, the tripartite model has been shown to enhance our conceptualization of anxious and depressive symptomology, leading to more reliable assessment and diagnosis of depressive disorder among adolescents and adults in clinical, community, and college samples. To further explain, let us revisit the findings of past research that has found that twice as many females experience depression as males. Most of these studies involved clinical populations that were diagnosed using standard screening and assessment procedures within hospitals and other public mental health facilities.

With this in mind, recall the recent findings of Joiner and colleagues,11 which, using the tripartite factors of NA, PA, and PH to assess adolescent patients, found that there were no gender differences among pure depressives. In fact, the 2:1 gender difference held only when patients with comorbid anxiety and depression were included in the sample (not just pure depressives), in which case there were many more females. The alarming aspect of this observation is that thousands of individuals (twice as many females as males) had passed through “standard” assessment procedures within community hospitals and mental health facilities without being identified as comorbid for depression and anxiety. Why is this so alarming? Research has shown that outcome effects and long-term prognosis are affected by the presence of more than one disorder.31,32 Likewise, comorbidity often serves as a moderator of treatments for which evidence continues to emerge.33

Whether pharmacologic or psychosocial in nature, mental health treatment varies as a function of pure depression, pure anxiety, and comorbid depressive-anxiety conditions. Failing to identify the comorbid status of depressed patients makes it unlikely that they will receive the most appropriate and effective treatment for their true condition. Administering less than optimal treatment because of this unfortunate oversight can lead to increased persistence of depressive episodes, increased recurrence, increased rates of relapse, and higher overall costs of health care. Clearly, the oversight of comorbid diagnostic status, particularly those concerning comorbid depression and anxiety, may result in negative consequences that are self-defeating to healthcare providers and consumers. With this in mind, it is enlightening that utilization of the tripartite model within our assessment protocol can help in identifying pure and comorbid forms of depression and anxiety.

How is the tripartite model easily incorporated into a clinical setting, and how are its three factors measured? Instrumentation and norms for the assessment of PA and NA are in place, and are available from current research literature. The quickest, simplest, and most widely researched assessment measure is the Positive and Negative Affect Schedule (PANAS), by Watson, Clark, and Tellegen.34 While other measures exist which appraise PA and NA, the PANAS is perhaps the only such scale that has demonstrated discriminant validity with comorbid anxiety and mood disorders among adolescents and adults. The scale was originally developed in connection with basic research on the nature and structure of human emotion.

The PANAS includes two 10-item scales, one for PA (items include interested, active, excited, attentive) and one for NA (items include nervous, irritable, distressed, jittery). Each item is rated on a scale of 1–5 (1=very slightly or not at all; 5=extremely); patients rate items based on how self-descriptive they are. Scores are derived by tallying item ratings separately for the NA and PA items. Thus, scores for PA and NA can each range from 10–50. The completion of the scale, as well as its scoring and interpretation, are quite brief—the entire process takes approximately 5 minutes. The scale is self-explanatory, and thus can easily be administered by anyone in the medical office (eg, clerical staff, nursing staff). Measurement techniques for the third component of the tripartite model—PH—are less well developed. The best available strategy is to use a current scale, such as the Beck Anxiety Inventory (BAI)3—a 21-item self-report inventory that assesses general symptoms of anxiety. For the purpose of measuring the tripartite component of PH specifically, particular emphasis would be placed on the somatic or physiological items of the BAI.35

 

Conclusion

The Tripartite Model of Anxiety and Depression5 has allowed mental health professionals to more accurately conceptualize the development and presentation of depressive symptomology and its relationship to anxiety among adolescents and adults. As illustrated above, utilization of the tripartite conceptualization (ie, examining factors of NA, PA, and PH) within current depression research has led to new insight regarding the nature of current depressive phenomenology (eg, gender differences, regional patterns of brain activation, and personal health). It is further suggested that the attendant measurement techniques of NA (ie, PANAS), PA (ie, PANAS), and PH (ie, BAI) be incorporated into standard assessment protocol as quick, convenient, and more reliable methods of screening patients for pure anxiety, pure depression, and comorbid anxiety and depression.  Improved identification and conceptualization of presenting depressive and anxious symptomology may lead to more accurate patient diagnoses which, in turn, will lead to implementation of the most appropriate and effective treatment for a given disorder.   PP

 

References

1.    Maxmen JS, Ward NG. Essential Psychopathology and Its Treatment. 2nd ed. New York, NY: WW Norton & Company; 1995:206-243.
2.    Lewinsohn PM, Rohde P, Seeley JR, Fischer SA. Age-cohort changes in the lifetime occurrence of depression and other mental disorders. J Abnorm Psychol. 1993;102:110-120.
3.    Antonuccio DO, Danton WG, DeNelsky GY, Greenberg RP, Gordon JS. Raising questions about antidepressants. Psychother Psychosom. 1999;68:3-14.
4.    Weissman MM, Bruce ML, Leaf PJ, Florio LP, Holzer C. Affective disorders. In: Robins LN, Regier DS, eds. Psychiatric Disorders of America:  The Epidemiologic Catchment Area of Study. New York, NY: Free Press; 1991:53-80.
5.    Clark LA, Watson D. Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Psychol. 1991;100:316-336.
6.    Watson D, Clark LA, Carey G. Positive and negative affectivity and their relation to anxiety and depressive disorders. J Abnorm Psychol. 1988;97:346-353.
7.    Brown TA, Chorpita BF, Barlow DH. Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. J Abnorm Psychol. 1998;107:179-192.
8.    Chorpita BF, Albano AM, Barlow, DH. The structure of negative emotions in a clinical sample of children and adolescents. J Abnorm Psychol. 1998;107:74-85.
9.    Joiner Jr TE. A confirmatory factor-analytic investigation of the tripartite model of depression and anxiety in college students. Cognit Ther Res. 1996;20:521-539.
10. Joiner Jr TE, Catanzaro SJ, Laurent J. The tripartite structure of positive and negative affect, depression, and anxiety in child and adolescent psychiatric inpatients. J Abnorm Psychol. 1996;105:401-409.
11.    Joiner Jr TE, Steer RA, Beck AT, Schmidt NB, Rudd MD, Cantanzaro SJ. Physiological hyperarousal: construct validity of a central aspect of the tripartite model of depression and anxiety. J Abnorm Psychol. 1999;108:290-298.
12.   Hankin BL, Abramson LY, Moffitt TE, Silva PA, McGee R, Angell KE. Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. J Abnorm Psychol. 1998;107:128-140.
13.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994:317-391.
14.    Amenson CS, Lewinsohn PM. An investigation into the observed sex differences in prevalence of unipolar depression. J Abnorm Psychol. 1981;90:1-13.
15.    Joiner Jr TE, Blalock JA, Wagner KD. Preliminary examination of gender differences in depressive symptoms among adolescent psychiatric inpatients: The role of anxious symptoms and generalized negative affect. J Clin Child Psychol. 1999;28:211-219.
16.    Joiner TE Jr, Blalock JA. Gender differences in depression: the role of anxiety and generalized negative affect. Sex Roles. 1995;33:91-108.
17.    Ochoa L, Beck AT, Steer RA. Gender differences in comorbid anxiety and mood disorders. Am J Psychiatry. 1992;149:1409-1410.
18.    Romanoski AJ, Folstein MF, Nestadt G, et al. The epidemiology of psychiatrist-ascertained depression and DSM-III depressive disorders. Results from the Eastern Baltimore Mental Health Survey Clinical Reappraisal. Psychol Med. 1992;22:629-655.
19.    Heller W, Etienne MA, Miller GA. Patterns of perceptual asymmetry in depression and anxiety: implications for neuropsychological models of emotion and psychopathology. J Abnorm Psychol. 1995;104:327-333.
20.    Keller J, Nitschke JB, Bhargava T, et al. Neuropsychological differentiation of depression and anxiety. J Abnorm Psychol. 2000;109:3-10.
21.    Voelz ZR, Gencoz F, Gencoz T, Pettit JW, Perez M, Joiner TE Jr. Patterns of hemispheric perceptual asymmetries: left-hemispatial biases predict changes in anxiety and positive affect among undergraduate women. Emotion. 2000;1:339-347.
22.    Jacobs GD, Snyder D. Frontal brain asymmetry predicts affective style in men. Behav Neurosci. 1996;110:3-6.
23.    Tomarken AJ, Davidson RJ. Frontal brain activation in repressors and nonrepressors. J Abnorm Psychol. 1994;103:339-349.
24.    Allen JJ, Iacono WG, Depue RA, Arbisi P. Regional electroencephalographic asymmetries in bipolar seasonal affective disorder before and after exposure to bright light. Biol Psychiatry. 1993;33:642-656.
25.    Henriques JB, Davidson RJ. Regional brain electrical asymmetries discriminate between previously depressed and healthy control subjects. J Abnorm Psychol. 1990;99:22-33.
26.    Davidson RJ, Coe CC, Dolski I, Donzella B. Individual differences in prefrontal activation asymmetry predict natural killer cell activity at rest and in response to challenge. Brain Behav Immun. 1999;13:93-108.
27.    Costa Jr PT, McCrae RR. Hypochondriasis, neuroticism, and aging: when are somatic complaints unfounded? Am Psychol. 1985;40:19-28.
28.    Costa Jr PT, McCrae RR. Neuroticism, somatic complaints, and disease: is the bark worse than the bite? J Pers. 1987;55:299-316.
29.    Dua JK. Comparative predictive value of attributional style, negative affect, and positive affect in predicting self-reported physical health and psychological health. J Psychosom Res. 1994;38:669-680.
30.    Watson D, Pennebaker JW. Health complaints, stress, and distress: exploring the central role of negative affectivity. Psychol Rev. 1989;96:234-254.
31.    Harrington R, Fudge H, Rutter M, Pickles A, Hill J. Adult outcomes of childhood and adolescent depression. II: links with antisocial disorders. J Am Acad Child Psychiatry. 1991;30:434-439.
32.    Kazdin AE, Crowley M. Moderators of treatment outcome in cognitively based treatment of antisocial children. Cognit Ther Res. 1997;21:185-207.
33.    Kazdin AE, Weisz JR. Identifying and developing empirically supported child and adolescent treatments. J Consult Clin Psychol. 1998;66:19-36.
34.    Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS Scales. J Pers Soc Psychol. 1988;54:1063-1070.
35.    Beck AT, Epstein N, Brown G, Steer R. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56:893-897.