Computational Strategies to Tailor Existing Interventions for First Major Depressive Episodes to Inform and Test Personalized Interventions

The goal of this study is to develop a model examining clinical, genetic, and demographic factor relations to depression course/outcomes and treatment response, using Kaiser Permanente Northern California data and the Kaiser Permanente Research Bank to develop and apply predictive computational algorithms to inform and test interventions; prepare the model for clinical implementation using a human factors framework and stakeholder input; and translate probability thresholds into treatment recommendations.

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