Background: Although different psychological treatments of depression seem equally effective, studies in this area have not taken sufficient account of the heterogeneity among patients. Modern techniques for longitudinal data analysis can be helpful in examining differential effects of psychological interventions on specific subpopulations of patients. Methods: Outpatients in mental health care, diagnosed with DSM-IV major depressive disorder, were randomly assigned to cognitive behavior therapy (N = 199) or treatment as usual (N = 226). Every 3 months for a total of 1.5 years, depressive symptomatology was measured using the SCL-90. Growth mixture modeling techniques were used to identify different trajectory classes of patients. The impact of type of treatment (treatment as usual vs. cognitive behavior therapy) was examined for each identified trajectory. Results: On average, patients in both test conditions improved significantly from baseline to posttest, and no significant difference was found between the conditions. However, four different trajectory classes could be distinguished within the sample. Most patients were classified into the two classes with the lowest depression scores at baseline (31% and 33% of the total sample). For these two classes, no significant differences in the course of depressive symptoms were found between the two conditions. In the two classes with the more severe depression scores (10% and 26% of the sample), however, cognitive behavior therapy was significantly more effective than treatment as usual. Conclusions: Although different treatments may seem to be equally effective, this does not have to be true for all classes of patients. Longitudinal research on the treatment of mental disorders should take heterogeneity among patients into account.

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Journal of Affective Disorders
Pediatric Psychiatry

Cuijpers, P, van Lier, P.A.C, van Straten, A, & Donker, M.C.H. (2005). Examining differential effects of psychological treatment of depressive disorder: An application of trajectory analyses. Journal of Affective Disorders, 89(1-3), 137–146. doi:10.1016/j.jad.2005.09.001