Behavioral Activation as a Mechanism of Change in Residential Treatment for Mood Problems: A Growth Curve Model Analysis. Issue 6 (November 2019)

• Record Type: Journal Article
• Authors: Santos, María M.; Ullman, Jodie; Leonard, Rachel C.; Puspitasari, Ajeng J.; Cook, Jessica; Riemann, Bradley C.
• Is Part Of: Behavior therapy. Volume 50:Issue 6(2019)
• Page Start: 1087
• Page End: 1097
• Publication Date: 2019-11
• Subjects: mechanism of action -- behavioral activation -- activation -- depression; Behavior therapy -- Periodicals; 616.8914205
• DOI: 10.1016/j.beth.2019.05.004
• Languages: English
• ISSNs: 0005-7894

Abstract

Abstract: Research on the efficacy, effectiveness, and dissemination potential of behavioral activation (BA)-focused interventions for depression and comorbid disorders has expanded rapidly. However, research that examines how BA interventions work has seen less growth. A primary purported mechanism of BA is activation, which reflects a person's meaningful (re)engagement in life. BA theory posits that depression will decrease as activation increases, and that changes in the mechanism variable will lead to changes in outcome. The current study aims to investigate activation as a potential mechanism of change in the context of a BA-focused residential treatment intervention for mood problems using repeated measures of self-reported activation and depression from a large comorbid sample ( N = 578). Growth curve modeling was used to examine between-person differences in within-person change over time. Findings suggest that self-reported activation increases and depression decreases over time. Moreover, results show both linear and quadratic growth and that the rate of change in activation predicts the rate of change of depression. BA-focused residential treatment may facilitate activation, which exerts an effect on depression among residents with diagnostically complex presentations. Highlights: Behavioral activation increases over the course of residential treatment. Depression symptoms decrease over time. The rate of change in activation predicts rate of change in depression.