Skip to main content

Advertisement

SpringerLink
Log in

Application of the Tripartite Model to a Complicated Sample of Residential Youth with Externalizing Problems

  • Original Article
  • Published:
Child Psychiatry & Human Development Aims and scope Submit manuscript

Abstract

The tripartite model of anxiety and depression has received strong support among child and adolescent populations. Clinical samples of children and adolescents in these studies, however, have usually been referred for treatment of anxiety and depression. This study investigated the fit of the tripartite model with a complicated sample of residential youths with externalizing problems. Structural Equation Modeling was used to test the tripartite model relationships between negative affect, positive affect, and mood symptoms. Multiple fit indices were used to provide a reliable and conservative evaluation of the model. As predicted, the tripartite model provided a good fit for symptoms of emotional disorders in this complicated sample of children and adolescents. Implications of these findings are discussed in terms of the utility of the tripartite model in understanding anxiety and depression in more diverse populations and recommendations for residential assessment.

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
Fig. 2

Similar content being viewed by others

Notes

  1. We chose to divide our sample into these two age groups in order to have comparable sample sizes in each group.

References

  1. Clark LA, Watson D (1991) Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Child Psychol 100:316–336

    Article  Google Scholar 

  2. Brown TA, Chorpita BF, Barlow DH (1998) 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 107:179–192

    Article  PubMed  Google Scholar 

  3. Chorpita BF (2002) The tripartite model and dimensions of anxiety and depression: an examination of structure in a large school sample. J Abnorm Child Psychol 30:177–190

    Article  PubMed  Google Scholar 

  4. Chorpita BF, Daleiden EL (2002) Tripartite dimensions of emotion in a child clinical sample: measurement strategies and implications for clinical utility. J Consult Clin Psychol 70:1150–1160

    Article  PubMed  Google Scholar 

  5. Joiner TE Jr, Catanzaro SJ, Laurent J (1996) Tripartite structure of positive and negative affect, depression, and anxiety in child and adolescent psychiatric inpatients. J Abnorm Psychol 105:401–409

    Article  PubMed  Google Scholar 

  6. Joiner TE Jr, Lonigan CJ (2000) Tripartite model of depression and anxiety in youth psychiatric inpatients: relations with diagnostic status and future symptoms. J Clin Child Psychol 29:372–382

    Article  PubMed  Google Scholar 

  7. Watson D, Clark LA, Weber K, Assenheimer JS, Strauss ME, McCormick RA (1995) Testing a tripartite model: II. Exploring the symptom structure of anxiety and depression in student, adult, and patient samples. J Abnorm Psychol 104:15–25

    Article  PubMed  Google Scholar 

  8. Watson D, Gamez W, Simms LJ (2005) Basic dimensions of temperament and their relation to anxiety and depression: a symptom-based perspective. J Res Pers 39:46–66

    Article  Google Scholar 

  9. American Psychiatric Association (2000) Diagnostic and statistical manual of mental disorders, text revised, 4th edn. APA, Washington, DC

    Google Scholar 

  10. American Psychiatric Association (2010) D 05 mixed anxiety/depression. Available at: from http://www.dsm5.org/ProposedRevisions/Pages/proposedrevision.aspx?rid=40. Accessibility verified 6 Oct 2012

  11. Dyck MJ, Jolly JB, Kramer T (1994) An evaluation of positive affectivity, negative affectivity, and hyperarousal as markers for assessing between syndrome relationships. Pers Individ Differ 17:637–646

    Article  Google Scholar 

  12. Philipp LM, Washington C, Raouf M, Norton PJ (2008) Cross-cultural examination of the tripartite model in adults. Cogn Behav Ther 37:221–232

    Article  PubMed  Google Scholar 

  13. Gorusch R (1983) Factor analysis. Erlbaum, Hillsdale, NJ

    Google Scholar 

  14. Loehlin JS (1987) Latent variable models. Erlbaum, Hillsdale, NJ

    Google Scholar 

  15. Chorpita BF, Albano M, Barlow DH (1998) The structure of negative emotions in a clinical sample of children and adolescents. J Abnorm Psychol 107:74–85

    Article  PubMed  Google Scholar 

  16. Lambert SF, McCreary BT, Joiner TE, Schmidt NB, Ialongo NS (2004) Structure of anxiety and depression in urban youth: an examination of the tripartite model. J Consult Clin Psychol 72:904–908

    Article  PubMed  Google Scholar 

  17. Buckby JA, Cotton SM, Cosgrave EM, Killackey EJ, Yung AR (2008) A factor analytic investigation of the tripartite model of affect in a clinical sample of young Australians. BMC Psychiatry 8:1–12

    Article  Google Scholar 

  18. Chorpita BF, Daleiden EL, Moffitt C, Yim L, Umemoto LA (2000) Assessment of tripartite factors of emotion in children and adolescents I: structural validity and normative data of an affect and arousal scale. J Psychopathol Behav Assess 22:141–160

    Article  Google Scholar 

  19. Daleiden E, Chorpita BF, Lu W (2000) Assessment of tripartite factors of emotion in children and adolescents II: concurrent validity of the affect and arousal scales for children. J Psychopathol Behav Assess 22:161–182

    Article  Google Scholar 

  20. Joiner TE, Steer RA, Beck AT, Schmidt NB, Rudd DM, Catanzaro SJ (1999) Physiological hyperarousal: construct validity of a central aspect of the tripartite model of depression and anxiety. J Abnorm Psychol 108:290–298

    Article  PubMed  Google Scholar 

  21. Fanti KA, Henrich CC (2010) Trajectories of pure and co-occurring internalizing and externalizing problems from age 2 to age 12: findings from the national institute of child health and human development study of early child care. Dev Psychol 46:1159–1175

    Article  PubMed  Google Scholar 

  22. Laurent J, Catanzaro SJ, Joiner TE Jr, Rudo KD, Potter KI, Lambert S et al (1999) A measure of positive and negative affect for children: scale development and preliminary validation. Psychol Assess 11:326–338

    Article  Google Scholar 

  23. Chorpita BF, Yim L, Moffitt C, Umemoto LA, Francis SE (2000) Assessment of symptoms of DSM-IV anxiety and depression in children: a revised child anxiety and depression scale. Behav Res Ther 38:835–855

    Article  PubMed  Google Scholar 

  24. Connor DF, Doerfler LA, Toscano PF, Volungis AM, Steingard RJ (2004) Characteristics of children and adolescents admitted to a residential treatment center. J Child Fam Stud 13:497–510

    Article  Google Scholar 

  25. Hughes AA, Kendall PC (2009) Psychometric properties of the positive and negative affect scale for children (PANAS-C) in children with anxiety disorders. Child Psychiatry Hum Dev 40:343–352

    Article  PubMed  Google Scholar 

  26. Kovacs M (1981) Rating scales to assess depression in school-aged children. Acta Paedopsychiatria 46:305–315

    Google Scholar 

  27. Spielberger CD (1973) Preliminary manual for the state-trait anxiety inventory for children (“How I feel Questionnaire”). Consulting Psychologists Press, Palo Alto, CA

    Google Scholar 

  28. Chorpita BF, Moffitt CE, Gray J (2005) Psychometric properties of the revised child anxiety and depression scale in a clinical sample. Behav Res Ther 43:309–322

    Article  PubMed  Google Scholar 

  29. Ullman JB (2007) Structural equation modeling. In: Tabachnick BG, Fidell LA (eds) Using multivariate statistics. Pearson, Boston, pp 676–780

    Google Scholar 

  30. Chorpita BF, Plummer CM, Moffitt CE (2000) Relations of tripartite dimensions of emotion to childhood anxiety and mood disorders. J Abnorm Child Psychol 28:299–310

    Article  PubMed  Google Scholar 

  31. Muthen LK, Muthen BO (2007) Mplus user’s guide, 5th edn. Muthen & Muthen, Los Angeles, CA

    Google Scholar 

  32. Yuan K, Bentler PM (2000) Three likelihood-based methods for mean and covariance structure analysis with non-normal missing data. Sociol Methodol 30:167–202

    Google Scholar 

  33. Jaccard JC, Wan CK (1996) LISREL approaches to interaction effects in multiple regression. Sage, Thousand Oaks, CA

    Google Scholar 

  34. Schumacker RE (1992) Goodness of fit criteria in structural equation modeling. In: Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA. Abstract retrieved from http://www.eric.ed.gov/ERICWebPortal/contentdelivery/servlet/ERICServlet?accno=ED344926

  35. Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6:1–55

    Article  Google Scholar 

  36. Browne MW, Cudeck R (1993) Alternative ways of assessing model fit. In: Bollen KA, Long JS (eds) Testing structural models. Sage, Newbury Park, CA, pp 136–162

    Google Scholar 

  37. Bentler PM (1995) EQS: structural equations program manual. Multivariate Software Inc, Encino, CA

    Google Scholar 

  38. Bentler PM, Bonett DG (1980) Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull 88:588–606

    Article  Google Scholar 

  39. Bentler PM (1990) Comparative fit indexes in structural models. Psychol Bull 107:238–246

    Article  PubMed  Google Scholar 

  40. Tucker LR, Lewis C (1973) A reliability coefficient for maximum likelihood factor analysis. Psychometrika 38:1–10

    Article  Google Scholar 

  41. Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16:223–297

    Google Scholar 

  42. Satorra A, Bentler P (1994) Corrections to test statistics and standard errors in covariance structure analysis. In: von Eye A, Clogg CC (eds) Latent variable analysis: applications for developmental research. Sage, Thousand Oaks, CA, pp 399–419

    Google Scholar 

  43. Cannon MF, Weems C (2006) Do anxiety and depression cluster into distinct groups? A test of tripartite model predictions in a community sample of youth. Depress Anxiety 23:453–460

    Article  PubMed  Google Scholar 

  44. Lonigan CJ, Phillips B, Hooe E (2003) Relations of positive and negative affectivity to anxiety and depression in children: evidence from a latent variable longitudinal study. J Consult Clin Psychol 71:465–481

    Article  PubMed  Google Scholar 

  45. Barlow DF (2000) Unraveling the mysteries of anxiety and its disorders from the perspective of emotion theory. Am Psychol 55:1247–1263

    Article  PubMed  Google Scholar 

  46. Brown TA, Antony MM, Barlow DH (1995) Diagnostic comorbidity in panic disorder: effect on treatment outcome and course of comorbid diagnoses following treatment. J Consult Clin Psychol 63:408–418

    Article  PubMed  Google Scholar 

  47. Ebesutani C, Smith A, Bernstein A, Chorpita BF, Higa-McMillan C, Nakamura B (2011) A bifactor model of negative affectivity: fear and distress components among younger and older youth. Psychol Assess 23:679–691

    Article  PubMed  Google Scholar 

  48. Gaylord-Harden NK, Elmore CA, Campbell CL, Wethington A (2011) An examination of the tripartite model of depressive and anxiety symptoms in African American youth: stressors and coping strategies as common and specific correlates. J Clin Child Adolesc Psychol 40:360–374

    Article  PubMed  Google Scholar 

  49. Ialongo NS, Kellam SG, Poduska J (1999) Manual for the Baltimore how i feel, Tech Rep No. 2. John Hopkins University, Baltimore, MD

  50. Campbell DT, Fiske DW (1959) Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull 56:81–105

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychology, University of Mississippi, Oxford, MS, 38677, USA

    Eu Gene Chin & John Young

  2. Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-749, South Korea

    Chad Ebesutani

Authors
  1. Eu Gene Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chad Ebesutani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John Young
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eu Gene Chin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chin, E.G., Ebesutani, C. & Young, J. Application of the Tripartite Model to a Complicated Sample of Residential Youth with Externalizing Problems. Child Psychiatry Hum Dev 44, 469–478 (2013). https://doi.org/10.1007/s10578-012-0341-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10578-012-0341-y

Keywords

Search

Navigation