Mood disorders are associated with significant financial and health costs for the United States, partially due to cognitive problems in these patients that can worsen disease course and impair treatment response. This study proposes to use smartphone-based technology to monitor cognitive problems in patients with mood disorders by linking brain network changes with predicted worsening of mood symptoms. The proposed study will provide evidence for using smartphone-based passive sensing as a cost-effective way to predict illness course and treatment response.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Neuroimaging
Timeframe: Change from week 2 to week 4.
BiAffect Metric
Timeframe: Measured at the end of week 4 after using the BiAffect app for 4 weeks
Clinical symptoms
Timeframe: Measured at baseline.
Cognition
Timeframe: Change from week 2 to week 4