Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study (Preprint)
Abstract:BACKGROUND
Digital behavioral interventions can reduce binge drinking events (BDEs: consuming 4+/5+ drinks per occasion for women/men) in young adults, however, they may not be optimized for timing or content. Delivering support in the hours prior to a predicted drinking event could improve the impact of that support.
OBJECTIVE
In this paper, our goal is to explore the feasibility of predicting… Show more
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