Cognitive dysfunction in the context of mood disorders has been associated with poorer treatment response and is a key risk factor for recurrence after remission. Thus, accurate, objective assessment of cognitive function in patients with mood disorders is of paramount clinical utility. The proposed study will use a novel smartphone technology (?BiAffect?) that uses typing dynamics and motor kinematics to unobtrusively, securely, and passively monitor cognitive function in a transdiagnostic sample of participants with mood disorders (unipolar depression, bipolar disorder type I/II, dysthymia). The core technology of BiAffect is a custom-built smartphone virtual keyboard that replaces the native default keyboard, allowing the collection of real-time data of real and potential clinical relevance while individuals interact with their device as usual within their natural environment. BiAffect will be used in the sample to predict 1) altered brain network properties associated with cognitive dysfunction in mood disorders and 2) prospective changes in clinical mood symptoms in a transdiagnostic sample of participants with mood disorders.
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.