Skip to main content
SpringerLink
Log in

A Multi-wave Web-based Evaluation of Cognitive Content Specificity for Depression, Anxiety, and Anger

  • Original Article
  • Published:
Cognitive Therapy and Research Aims and scope Submit manuscript

Abstract

This study tested the cognitive content specificity hypothesis of Beck’s cognitive theory using a web based report of mood and cognitions for that day completed once a week for 5 weeks. The use of a multi-wave design and structural equation modeling allowed for the separation of occasion-specific variability from over-time stability, thereby increasing sensitivity to the relatively brief changes in negative affect typical of student populations. To further increase specificity, an expanded set of cognitive themes was tested for depression, anxiety, and anger. Consistent with models indicating that these mood states share a general negative mood, all cognitions had a significant non-specific relationship to all three mood states. For tests of occasion-specific cognitive content specificity, thoughts of Transgression were incrementally specific to angry mood whereas Defectiveness, Hopelessness, and Abandonment were each specific to depressed mood. Failure was more strongly related to depression and anxiety than anger. Contrary to hypotheses, both Dependence and Vulnerability to Harm were non-specific only.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. It is important to note that a high coefficient α, indicating acceptable internal consistency, does not insure that the scale is unidimensional (Nunnally and Bernstein 1994). The unidimensionality of a scale is best tested with confirmatory factor analysis to provide explicit tests of a two (or more) factor model versus a one factor model (Anderson and Gerbing 1988).

  2. Inclusion criteria were a Center for Epidemiological Studies-Depression (CES-D; Radloff 1977) Scale score of 16 or above and/or a State-Trait Anger Expression Inventory-II (STAXI; Spielberger et al. 1995): Trait Anger Scale score of 23 or above. Scores of 16 on the CES-D and 23 on the STAXI have been identified as cut-off scores for significant levels of depressive and angry symptoms (Beekman et al. 1997; Spielberger 1999). Unfortunately, limitations in available space and time during the mass screening precluded administering a third screening measure (e.g., of anxiety).

  3. In the tutorial, the participant was briefly instructed in how to combine information about the intensity, frequency, and duration of the distress during that day to make a severity rating for the distress items (depression, anxiety, anger). The participant then rated the frequency of certain thoughts identified in each of three vignettes and compared each rating to the ratings of a criterion group consisting of four clinical doctoral students and a clinical psychologist with training in behavioral assessment and cognitive theory and therapy for depression and anxiety. Feedback was given on these ratings so as to roughly calibrate each participant’s ratings with the criterion group.

  4. Correlation coefficients between depression, anxiety, and anger within each model are depicted in Fig. 1 for the Defectiveness model. Given that these relationships were approximately equivalent across the final models for all cognitions, they are not reported in Table 2.

  5. Although the factor and disturbance relationships are reported as correlations in Table 2, the actual SEM tests for differences in the magnitude of the relationship are conducted on the covariances.

References

  • Anderson, J. C. (2001). Empirical direction in design and analysis. Mahway, NJ: Erlbaum.

    Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 3, 411–423.

    Article  Google Scholar 

  • Beck, A. T. (1976). Cognitive therapy and the emotional disorders. New York: International Universities Press.

    Google Scholar 

  • Beck, A. T. (1996). Beyond belief: A theory of modes, personality, and psychopathology. In P. M. Salkovksis (Ed.), Frontiers of cognitive therapy (pp. 1–25). New York, NY: Guilford Press.

    Google Scholar 

  • Beck, A. T., Brown, G., Steer, R. A., Eidelson, J. I., & Riskind, J. H. (1987). Differentiating anxiety and depression: A test of the cognitive content-specificity hypothesis. Journal of Abnormal Psychology, 96, 179–183.

    Article  PubMed  CAS  Google Scholar 

  • Beck, R., & Perkins, T. S. (2001). Cognitive content-specificity for anxiety and depression: A meta-analysis. Cognitive Therapy and Research, 25, 651–663.

    Article  Google Scholar 

  • Beck, A. T., Steer, R. A., & Brown, G. K. (1993). Manual for the Beck anxiety inventory. San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  • Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck depression inventory (2nd ed.). San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  • Beck, A. T., Weissman, A., & Lester, D. (1974). The measurement of pessimism: The hopelessness scale. Journal of Consulting & Clinical Psychology, 42, 861–865.

    Article  CAS  Google Scholar 

  • Beekman, A. T. F., Deeg, D. J. H., Van Limbeek, J., et al. (1997). Criterion validity of the Center for Epidemiological Studies Depression scale (CES-D): Results from a community-based sample of older subjects in the Netherlands. Psychological Medicine, 27, 231–235.

    Article  PubMed  CAS  Google Scholar 

  • Bentler, P. M. (1995). EQS structural equation program manual. Encino, CA: Multivariate Software.

    Google Scholar 

  • Bolger, N., DeLongis, A., Kessler, R. C., & Schilling, E. A. (1989). Effects of daily stress on negative mood. Journal of Personality and Social Psychology, 57, 808–818.

    Article  PubMed  CAS  Google Scholar 

  • Bolger, N., & Schilling, E. A. (1991). Personality and the problems of everyday life: The role of neuroticism in exposure and reactivity to daily stressors. Journal of Personality, 59, 355–386.

    Article  PubMed  CAS  Google Scholar 

  • Brown, G. P., Hammen, C. L., Craske, M. G., & Wickens, T. D. (1995). Dimensions of dysfunctional attitudes as vulnerabilities to depressive symptoms. Journal of Abnormal Psychology, 104, 431–435.

    Article  PubMed  CAS  Google Scholar 

  • Bruch, M. A., Mattia, J. I., Heimberg, R. G., & Holt, C. S. (1993). Cognitive specificity in social anxiety and depression: Supporting evidence and qualifications due to affective confounding. Cognitive Therapy and Research, 17, 1–21.

    Article  Google Scholar 

  • Burns, D. D., & Eidelson, R. J. (1998). Why are depression and anxiety correlated? A test of the tripartite model. Journal of Consulting and Clinical Psychology, 66, 461–473.

    Article  PubMed  CAS  Google Scholar 

  • Cho, Y., & Telch, M. J. (2005). Testing the cognitive content-specificity hypothesis of social anxiety and depression: An application of structural equation modeling. Cognitive Therapy and Research, 29, 399–416.

    Article  Google Scholar 

  • Clark, D. A., & Beck, A. T. (1999). Scientific foundations of cognitive theory and therapy of depression. New York, NY: John Wiley & Sons.

    Google Scholar 

  • Clark, D. A., Beck, A. T., & Brown, G. (1989). Cognitive mediation in general psychiatric outpatients: A test of the content-specificity hypothesis. Journal of Personality and Social Psychology, 56, 958–964.

    Article  PubMed  CAS  Google Scholar 

  • Clark, D. A., Steer, R. A., Beck, A. T., & Snow, D. (1996). Is the relationship between anxious and depressive cognitions and symptoms linear or curvilinear? Cognitive Therapy & Research, 20, 135–154.

    Article  Google Scholar 

  • Clark, L. A., & Watson, D. (1991). Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. Journal of Abnormal Psychology, 100, 316–336.

    Article  PubMed  CAS  Google Scholar 

  • Cole, D. A., Peeke, L. G., & Martin, J. M. (1998). A longitudinal look at the relation between depression and anxiety in children and adolescents. Journal of Consulting & Clinical Psychology, 66, 451–460.

    Article  CAS  Google Scholar 

  • Deffenbacher, J. L., Demm, P., Brandon, A. (1986). High general anger: Correlates and treatment. Behavior Research & Therapy, 24, 481–489.

    Article  CAS  Google Scholar 

  • DiGiuseppe, R., & Froh, J. J. (2002). What cognitions predict state anger? Journal of Rational-Emotive & Cognitive Behavior Therapy, 20, 133–150.

    Article  Google Scholar 

  • Dwyer, J. H. (1983). Statistical models for the social and behavioral sciences. Oxford: New York.

    Google Scholar 

  • Eckhardt, C. I., Barbour, K. A., & Davison, G. C. (1998). Articulated thoughts of martially violent and nonviolent men during anger arousal. Journal of Consulting and Clinical Psychology, 66, 259–269.

    Article  PubMed  CAS  Google Scholar 

  • Eckhardt, C. I., & Dye, M. L. (2000). The cognitive characteristics of martially violent men: Theory and evidence. Cognitive Therapy and Research, 24, 139–158.

    Article  Google Scholar 

  • Epkins, C. C. (1996). Cognitive specificity and affective confounding in social anxiety and dysphoria in children. Journal of Psychopathology and Behavioral Assessment, 18, 83–101.

    Article  Google Scholar 

  • Fichman, L., Koestner, R., Zuroff, D. C., & Gordon, L. (1999). Depressive styles and the regulation of negative affect: A daily experience study. Cognitive Therapy & Research, 23, 483–495.

    Article  Google Scholar 

  • Haynes, S. N., & O’Brien, W. H. (2000). Principles and practice of behavioral assessment. New York, NY: Kluwer Academic/Plenum Publishers.

    Google Scholar 

  • Hill, C. V., Oei, T. P. S., & Hill, M. A. (1989). An empirical investigation of the specificity and sensitivity of the automatic thoughts questionnaire and dysfunctional attitudes scale. Journal of Psychopathology and Behavioral Assessment, 11, 291–311.

    Article  Google Scholar 

  • Hollon, S. D., & Kendall, P. C. (1980). Cognitive self-statements in depression: Development of an automatic thoughts questionnaire. Cognitive Therapy & Research, 4, 383–395.

    Article  Google Scholar 

  • Jolly, J. B., & Dykman, R. A. (1994). Using self report data to differential anxious and depressive symptoms in adolescents: Cognitive content specificity hypothesis and global distress? Cognitive Therapy & Research, 18, 25–37.

    Article  Google Scholar 

  • Jolly, J. B., & Kramer, T. A. (1994). The hierarchical arrangement of internalizing cognitions. Cognitive Therapy and Research, 18, 1–14.

    Article  Google Scholar 

  • Kendall, P. C., & Hollon, S. D. (1989). Anxious self-talk: Development of the anxious self-statements questionnaire (ASSQ). Cognitive Therapy & Research, 13, 81–93.

    Article  Google Scholar 

  • Lee, C. W., Taylor, G., & Dunn, J. (1999). Factor structure of the schema questionnaire in a large clinical sample. Cognitive Therapy and Research, 23, 441–451.

    Article  Google Scholar 

  • Marco, C. A., Neale, J. M., Schiffman, J. E., Schwartz, S., & Stone, A. A. (1999). Coping with daily events and short-term mood changes: An unexpected failure to observe effects of coping. Journal of Consulting and Clinical Psychology, 67, 755–764.

    Article  PubMed  CAS  Google Scholar 

  • McDermut, W., & Haaga, D. A. F. (1994). Cognitive balance and specificity in anxiety and depression. Cognitive Therapy & Research, 18, 333–352.

    Article  Google Scholar 

  • Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.

    Article  Google Scholar 

  • Riskind, J. H. (1997). Looming vulnerability to threat: A cognitive paradigm for anxiety. Behaviour Research & Therapy, 35, 685–702.

    Article  CAS  Google Scholar 

  • Safren, S. A., Heimberg, R. G., Lerner, J., Henin, A., Warman, M., & Kendall, P. C. (2000). Differentiating anxious and depressive self-statements: Combined factor structure of the anxious self-statements questionnaire and the automatic thoughts questionnaire-revised. Cognitive Therapy & Research, 24, 237–344.

    Article  Google Scholar 

  • Schmidt, N. B., Joiner, T. E., Young, J. E., & Telch, M. J. (1995). The schema questionnaire: Investigation of psychometric properties and the hierarchical structure of a measure of maladaptive schemas. Cognitive Therapy and Research, 19, 295–321.

    Article  Google Scholar 

  • Scott, W. D., Ingram, R.E, & Shadel, W. G. (2003). Hostile and sad moods in dysphoria: Evidence for cognitive specificity in attributions. Journal of Social & Clinical Psychology, 22, 233–252.

    Article  Google Scholar 

  • Spielberger, C. D. (1979). Preliminary manual for the state-trait personality inventory (STPI). University of South Florida: Tampa, FL.

    Google Scholar 

  • Spielberger, C. D. (1999). Manual for the state-trait anger expression inventory-second edition. Odessa, FL: Psychological Assessment Resources.

    Google Scholar 

  • Spielberger, C. D., Reheiser, E. C., & Sydeman, S. J. (1995). Measuring the experience, expression, and control of anger. In H. Kassinove (Ed.), Anger disorders: Definition, diagnosis, and treatment (pp. 49–67). Philadelphia, PA: Taylor & Francis.

    Google Scholar 

  • Spielberger, C. D., Ritterband, L. M., & Reheiser, E. C. (2003). The nature and measurement of depression. International Journal of Clinical & Health Psychology, 3, 209–234.

    Google Scholar 

  • Stader, S. R., & Hokanson, J. E. (1998). Psychosocial antecedents of depressive symptoms: An evaluation using daily experiences methodology. Journal of Abnormal Psychology, 107, 17–26.

    Article  PubMed  CAS  Google Scholar 

  • Stopa, L., Thorne, P., Waters, A., & Preston, J. (2001). Are the short and long forms of the young schema questionnaire comparable and how well does each version predict psychopathology scores. Journal of Cognitive Psychotherapy, 15, 253–272.

    Google Scholar 

  • Warner, M. B., Morey, L. C., Finch, J. F., Gunderson, J. G., Skodol, A. E., Sanislow, C. A., et al. (2004). The longitudinal relationships of personality traits and disorders. Journal of Abnormal Psychology, 113, 217–227.

    Article  PubMed  Google Scholar 

  • Welburn, K., Coristine, M., Dagg, P., Pontefract, A., & Jordan, S. (2002). The schema questionnaire-short form: Factor analysis and relationship between schemas and symptoms. Cognitive Therapy & Research, 26, 519–530.

    Article  Google Scholar 

  • Westra, H. A., & Kuiper, N. A. (1996). Communality and specificity of dysfunctional cognitions, and the prediction of four different forms of psychological maladjustment. Personality and Individual Differences, 20, 575–588.

    Article  Google Scholar 

  • Young, J. E., & Brown, G. (1990). Young schema questionnaire. New York: Cognitive Therapy Center of New York.

Download references

Author information

Authors and Affiliations

  1. Department of Psychology, Texas Tech University, MS 2051, Lubbock, TX, 79409-2051, USA

    Phillip N. Smith & Gregory H. Mumma

Authors
  1. Phillip N. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregory H. Mumma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gregory H. Mumma.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Smith, P.N., Mumma, G.H. A Multi-wave Web-based Evaluation of Cognitive Content Specificity for Depression, Anxiety, and Anger. Cogn Ther Res 32, 50–65 (2008). https://doi.org/10.1007/s10608-007-9171-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10608-007-9171-9

Keywords

Search

Navigation