Latent Profiles of Cognitive and Interpersonal Risk Factors for Adolescent Depression and Implications for Personalized Treatment
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A personalized approach to treatment with patients being matched to the best-fit treatment has been proposed as one possible solution to the currently modest treatment response rates for adolescent depression. Personalized treatment involves identifying and characterizing subgroups likely to respond differently to different treatments. We investigated the feasibility of this approach, by focusing on two key risk factors that are the purported treatment targets of cognitive behavioral therapy (CBT) and interpersonal psychotherapy for depressed adolescents (IPT-A): negative unrealistic cognitions and interpersonal relationship difficulties, respectively. We sought to learn whether subgroups high and low on the two risk factors, respectively, might be identified in a large sample of depressed, treatment-seeking adolescents. Latent class analysis (LCA) was conducted on measures of the two risk factors among 431 adolescents (age 12–17) in the Treatment for Adolescents with Depression Study. LCA identified three classes: (1) adolescents with high levels of problems in both family relationships and cognitions (21.6% of sample), (2) adolescents with moderate levels of problems in both domains (52.4%), and (3) adolescents with low levels of problems in both domains (26.0%). These subgroups did not predict treatment outcome with CBT or CBT + fluoxetine (COMB). The results challenge a current assumption about how treatments could be personalized, and they support a multi-causal model of depression rather than a risk-factor-specific model. Strategies other than risk factor-based personalizing for case assignment to CBT vs. IPT-A are discussed.
KeywordsAdolescents Depression Treatment Cognitions Family
Compliance with Ethical Standards
Conflict of Interest
There are no conflicts of interest to report.
The coordinating center at Duke University Medical Center and the Institutional Review Board at each site approved and monitored the study. The Data and Safety Monitoring Board of the National Institute of Mental Health performed quarterly review.
Adolescents and at least one parent/caregiver provided written informed consent and assent.
- American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association.Google Scholar
- Brent, D. A., Holder, D., Kolko, D., Birmaher, B., Baugher, M., Roth, C., ... Johnson, B. A. (1997). A clinical psychotherapy trial for adolescent depression comparing cognitive, family, and supportive therapy. Archives of General Psychiatry, 54, 877–885.Google Scholar
- Curry, J., Rohde, P., Simons, A., Silva, S., Vitiello, B., Kratochvil, C., et al. (2006). Predictors and moderators of acute outcome in the treatment for adolescents with depression study (TADS). Journal of the American Academy of Child and Adolescent Psychiatry, 45, 1427–1439. https://doi.org/10.1097/01.chi.0000240838.78984.e2.CrossRefGoogle Scholar
- Feeny, N. C., Silva, S. G., Reinecke, M. A., McNulty, S., Findling, R. L., Rohde, P., ... March, J. S. (2009). An exploratory analysis of the impact of family functioning on treatment for depression in adolescents. Journal of Clinical Child and Adolescent Psychology, 38, 814–825.Google Scholar
- Feng, Z. D., & McCulloch, C. E. (1996). Using bootstrap likelihood ratios in finite mixture models. Journal of the Royal Statistical Society, 58(Series B, 609–617.Google Scholar
- Jacobs, R. H., Silva, S. G., Reinecke, M. A., Curry, J. F., Ginsburg, G. S., & Kratochvil, C. J. (2009). Dysfunctional attitudes scale perfectionism: A predictor and partial mediator of acute treatment outcome among clinically depressed adolescents. Journal of Clinical Child and Adolescent Psychology, 38, 803–813.CrossRefGoogle Scholar
- Kaufman, J., Birmaher, B., Brent, D., & Rao, U. (1997). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 980–988. https://doi.org/10.1097/00004583-199707000-00021.CrossRefGoogle Scholar
- Kingery, J. N., Kepley, H. O., Ginsburg, G. S., Walkup, J. T., Silva, S. G., Hoyle, R. H., ... March, J. S. (2009). Factor structure and psychometric properties of the Children’s negative cognitive error questionnaire with a clinically depressed adolescent sample. Journal of Clinical Child and Adolescent Psychology, 38, 768–780.Google Scholar
- Leitenberg, H., Yost, L. W., & Carroll-Wilson, M. (1986). Negative cognitive errors in children: Questionnaire development, normative data, and comparisons between children with and without self-reported symptoms of depression, low self-esteem, and evaluation anxiety. Journal of Consulting and Clinical Psychology, 54(4), 528–536.CrossRefGoogle Scholar
- Lewinsohn, P. M., Hops, H., Roberts, R. E., Seeley, J. R., & Andrews, J. A. (1993). Adolescent psychopathology: I. prevalence and incidence of depression and other DSM-III-R disorders in high school students. Journal of Abnormal Psychology, 102, 133–144. https://doi.org/10.1037/0021-843X.102.1.133.CrossRefGoogle Scholar
- Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., & Schabenberger, O. (2006). SAS for mixed models (2nd ed.). Cary: SAS Institute.Google Scholar
- Marton, P., & Kutcher, S. (1993). The prevalence of cognitive distortion in depressed adolescents. Journal of Psychiatry and Neuroscience, 20, 33–38.Google Scholar
- Mufson, L., Dorta, K. P., Moreau, D., & Weissman, M. M. (2004). Interpersonal psychotherapy for depressed adolescents (2nd ed.). New York: Guilford Press.Google Scholar
- Muthen, L. K., & Muthen, B. O. (2010). Mplus User's Guide (6th ed.). Los Angeles.Google Scholar
- Poznanski, E. O., & Mokros, H. B. (1996). The Children's depression rating scale - revised (CDRS-R). Los Angeles: Western Psychological Services.Google Scholar
- Robin, A. L., & Foster, S. L. (1989). Negotiating parent-adolescent conflict: A behavioral-family systems approach. New York: Guilford.Google Scholar
- Robin, A. L., & Weiss, J. G. (1980). Criterion-related validity of behavioral and self-report measures of problem-solving communication skills in distressed and non-distressed parent-adolescent dyads. Behavioral Assessment, 2, 339–352.Google Scholar
- SAS Institute Inc. (2008). SAS/STAT® 9.2 User’s Guide. Cary, NC: SAS Institute Inc.Google Scholar
- TADS Team. (2004). Fluoxetine, cognitive–behavioral therapy, and their combination for adolescents with depression: Treatment for adolescents with depression study (TADS) randomized controlled trial. Journal of the American Medical Association, 292, 807–820. https://doi.org/10.1001/jama.292.7.807.CrossRefGoogle Scholar
- Weersing, V. R., & Gonzalez, A. (2009). Effectiveness of interventions for adolescent depression: Reason for hope or cause for concern? Handbook of depression in adolescents, 589–616.Google Scholar
- Weissman, A., & Beck, A. T. (1978). Development and validation of the Dysfunctional Attitudes Scale. Paper presented at the Association for the Advancement of behavior therapy, Chicago, IL.Google Scholar
- Weisz, J. R., McCarty, C. A., & Valeri, S. M. (2006). Effects of psychotherapy for depression in children and adolescents: A meta-analysis. Psychological Bulletin, 132, 132–149.Google Scholar
- Weisz, J. R., Kuppens, S., Ng, M. Y., Eckshtain, D., Ugueto, A. M., Vaughn-Coaxum, R., ... Fordwood, S. R. (2017). What five decades of research tells us about the effects of youth psychological therapy: A multilevel meta-analysis and implications for science and practice. American Psychologist, 72, 79–117.Google Scholar