Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps.
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PURPOSE OF REVIEW As rates of suicide continue to rise there is urgent need for innovative approaches to better understand predict and care for those at high risk of suicide Numerous mobile and sensor technology solutions have already been proposed are in development or are already available today This review seeks to assess their clinical evidence and help the reader understand the current state of the field RECENT FINDINGS Advances in smartphone sensing machine learning methods and mobile apps directed towards reducing suicide offer promising evidence however most of these innovative approaches are still nascent Further replication and validation of preliminary results is needed Whereas numerous promising mobile and sensor technology based solutions for real time understanding predicting and caring for those at highest risk of suicide are being studied today their clinical utility remains largely unproven However given both the rapid pace and vast scale of current research efforts we expect clinicians will soon see useful and impactful digital tools for this space within the next 2 to 5 years