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Using Smartphone GPS Data to Detect the Risk of Adolescent Suicidal Thoughts and Behaviors.
Randy P Auerbach1,2, Paul A Bloom1,2, David Pagliaccio1,2
1Department of Psychiatry, Columbia University, New York, New York.
Adolescent suicide risk can be predicted using smartphone GPS data. Increased time spent at home (homestay) in a week was linked to a higher likelihood of suicidal events in the following week.
Area of Science:
- Digital Phenotyping
- Adolescent Psychiatry
- Suicide Prevention
Background:
- Adolescent suicide rates are rising, with a critical need for tools to predict suicidal behaviors.
- Current clinical tools for assessing suicide risk in adolescents are limited.
Purpose of the Study:
- To determine if smartphone-based geolocation metrics can predict next-week suicidal events and ideation in high-risk adolescents.
- To explore the utility of passive sensor data for early detection of suicide risk.
Main Methods:
- A case series study involving 186 high-risk adolescents (13-18 years) with affective and/or substance use disorders.
- Utilized the Effortless Assessment Research System (EARS) app for passive geolocation (GPS) and weekly experience sampling.
- Employed repeated measures mixed-effects logistic models to analyze associations between geolocation features and suicidal events/ideation.
Main Results:
- Greater weekly homestay (time spent at home) was associated with a 2-fold increased odds of subsequent suicidal events (OR, 1.99).
- Geolocation metrics like entropy and distance traveled were not significantly associated with suicidal events.
- The homestay model demonstrated modest predictive accuracy (AUC, 0.64).
Conclusions:
- Smartphone-derived geolocation, specifically homestay duration, shows potential for identifying adolescents at increased risk for suicidal events.
- This novel approach offers a starting point for developing digital tools for suicide prevention.
- Future research can leverage smartphone sensor data for timely risk identification and intervention.
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