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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

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

In several studies, including Suffoletto et al [35], we found that proactively prompting goal commitment to limit drinking before drinking onset is a critical component of JIT interventions. As such, a prediction-based intervention approach avoids delivering messages or support during a drinking event when cognitive and motivational impairment due to acute alcohol use might limit message utility.

Sang Won Bae, Brian Suffoletto, Tongze Zhang, Tammy Chung, Melik Ozolcer, Mohammad Rahul Islam, Anind K Dey

JMIR Form Res 2023;7:e39862

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