App-Enhanced CBT for Adolescents at High Risk for Severe Mood Disorders

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PROJECT SUMMARY This K23 career development award will position the candidate to become an independent clinical researcher with expertise in the application of mobile health (mHealth) technologies to improve psychosocial clinical trials for youth at high risk for severe mood disorders (SMD; i.e., bipolar I/II disorder and recurrent or unremitting major depression). BACKGROUND. Psychosocial treatments (most notably cognitive-behavioral therapy (CBT)) for adolescents at high risk for SMD show some efficacy in reducing symptoms and rates of mood episode relapse; however, the size of the effects range from small to moderate. A contributing factor to the variable effect sizes is the low rates of adherence to CBT’s prescribed treatment tasks (e.g., cognitive reappraisal). CBT’s mechanisms of therapeutic change hinge upon practice and implementation of the treatment tasks between sessions. However, adolescents commonly report low motivation, forgetfulness, and a lack of resources as barriers to completing the CBT treatment tasks. This challenges clinical researchers to devise better methods of engaging patients in these treatment tasks. SPECIFIC AIMS. This proposal aims to better engage participants in treatment and bridge treatment sessions by (1) adapting and testing the acceptability of an existing mobile application (app) that will reinforce session content, facilitate practice of treatment skills, and allow participants to log and monitor thoughts and symptoms; and (2) conducting a randomized-controlled trial (RCT) to test the efficacy of an app-enhanced CBT for adolescents (ages 13-17) at high risk for SMD in improving participant adherence. TRAINING. The candidate will achieve short-term goals through a resource-rich institutional environment and a cohesive training plan in (1) the planning, delivery, and evaluation of mHealth technologies, (2) the conduct of clinical trials, and (3) statistical methodologies to examine high dimensional mHealth data through the use of functional data analysis. MENTORSHIP. The candidate will be supported by an expert interdisciplinary team: David Miklowitz, PhD (primary mentor), Bonnie Zima, MD, MPH (co-mentor), Catherine Sugar, PhD (co-mentor), Armen Arevian MD, PhD (collaborator), Eric Granholm, PhD (consultant), and Jill Ehrenreich-May, PhD (consultant). IMPACT. In line with NIMH funding priorities, the proposed research will answer critical questions about (1) the acceptability and initial efficacy of a mobile app in improving participant adherence and acceptability for adolescents at high risk for SMD and (2) begin to uncover the initial mechanisms by which a mobile app can influence participant adherence. While initial studies will focus on adolescents at high risk for SMD, it is anticipated that the candidate’s training and research will have broad applications to a range of age populations and psychiatric conditions. Through this K23 award, the candidate will gain the training and preliminary data necessary to apply for a larger NIMH clinical trial to determine what components of a mobile app affect participant adherence and test participant adherence as a mediator of psychiatric and psychosocial treatment outcomes.