Modeling Mood Course to Detect Markers of Effective Adaptive Interventions

Bipolar disorder is successfully treated by combining medication with psychosocial therapy, but care can prove inadequate in practice. With gaps in coverage and medication, along with imprecise guidelines on when, where, and how to intervene, promising psychosocial therapies require adaptive strategies to better address the specific needs of individuals in a timely manner. Accomplishing this, however, requires evidence-based practices for adapting a psychosocial therapy. The long-term goal of this study is to address this knowledge gap, by establishing a mobile health platform for translating a psychosocial therapy in bipolar disorder into an effective adaptive intervention.

An important first step is to determine how best to engage individuals with bipolar disorder in long-term monitoring of their daily patterns of mood, stress, sleep, circadian rhythm, and medical adherence. To answer this question, individuals with bipolar disorder will interact with a smart-phone application and activity tracker over six weeks. Individuals will record their symptoms twice-daily with the smart-phone application while activity, sleep, and heart rate are recorded with their activity tracker. In addition, individuals will be interviewed on a weekly basis.

This study focuses on testing three engagement strategies

  • using activity trackers rather than self-reports
  • reviewing recorded symptoms with another person on a weekly basis
  • and synthesizing a person’s data into charts and graphs.   

This study has received approval from: IRBMED HUM00126732