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Predicting Post-discharge Suicidal Behavior in Bipolar Disorders Using Passive Sensing and Pattern Recognition

Young Investigator Grant
Amount Awarded: $89,995
Focus Area: Psychosocial Studies

Abigail Ortiz, M.D., M.Sc., FRPC

Abigail Ortiz, M.D., M.Sc., FRPC
University of Toronto (Canada)

Mentor: Benoit Mulsant, M.D., M.Sc., FRPC, University of Toronto (Canada)

Inside the Research

Up to 60% of bipolar disorder patients attempt suicide at least once in their lifetime. As a result, several interventions for suicide prevention have been developed. This study aims to analyze high-dimensional, multi-modal objective (sleep, activity), subjective (mood, anxiety, energy, sleep), and physiological data (heart rate variability) using wearable sensors and mathematical modeling to extract and interpret individual patterns suggestive of future suicidal behavior. Developing the capacity to detect and predict relapses and suicidal behaviors may improve prevention.