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Category: Project

Description: Major depression affects 10% of the U.S. adult population annually, contributing to significant comorbidity, impairment, and disability totaling $200 billion (Brody et al., 2018; Hasin et al., 2018). Treatment response to depressive symptoms is a non-linear process characterized by combinations of gradual changes and abrupt shifts (Aderka et al., 2012), although less is known about differential treatment response among people engaging in digital mental health interventions. The proposed study will utilize a model-based clustering approach called repeated-measures latent profile analysis (RMLPA; Lanza & Collins, 2006) to examine changes in depressive symptoms among people enrolled in a 12-week intervention called Meru Health. This study will also evaluate associations between treatment response patterns and program engagement.