Low-burden Adaptive Mobile Interventions for Mood and Suicide Risk

项目总结/文摘

Project Summary/Abstract Depression is the #1 cause of disease-related disability worldwide and prevalence rates for depression and suicide have increased significantly in the United States over the past 25 years. Young adults, including college students, have especially high rates of depression, yet a majority of individuals with clinically significant symptoms do not seek formal treatment. Previous work by the Candidate (Dr. Adam Horwitz) suggests that college students at elevated risk for suicide may decline formal treatment due to barriers such as lack of time, low perceived need for treatment, or limited access to services. Mobile health technologies offer promising new opportunities to overcome these barriers and improve outcomes. Further, the use of mobile technologies in combination with wearable sensors allow for the gathering of real-time subjective and objective data, and an ability to respond to mood changes directly with an intervention at the time it is needed. This K23 Mentored Career Development Award application proposes a program of focused research and training to facilitate the Candidate’s transition to an independent career in patient-oriented research with a specialization in low-burden adaptive mobile preventative interventions for mood and suicide risk. The specific research aims are to: 1) using a participatory action approach, identify the target population preferences, barriers to engagement, and relevant domains for ecological momentary assessments and personalized feedback messages; and 2) conduct a pilot feasibility micro-randomized trial of a mobile health personalized feedback intervention with college students (N = 60) at risk for depressive episodes. The Candidate will pursue these research aims by obtaining specific training to gain expertise in: 1) participatory action research methods for intervention development; 2) mHealth, micro-randomized trials, and adaptive mobile intervention development and evaluation; and 3) advanced statistical analysis for mobile, sensor, and ecological momentary assessment data. These training objectives will be met through close mentorship from experts in these content areas, specialized trainings and didactics, and applied research experiences. Findings from the outlined investigations will provide invaluable pilot data regarding acceptability, feasibility, perceived helpfulness, and hypothesized mechanisms of change, as well as potential features and thresholds that can be used as intervention triggers in an adaptive design. Together, these findings will directly inform an NIH R01 application at the conclusion of the study period seeking to evaluate a just-in-time adaptive intervention designed to optimize the delivery of personalized feedback messages, and provide additional coping tips, tools, and/or resources when indicated. In summary, the training and research opportunities outlined in this proposal will provide the necessary skills for a promising Candidate to launch a career in developing accessible and impactful adaptive mobile interventions to reduce depression and suicide among young people.