This study investigates the feasibility of using smartphone sensor data to monitor sleep in college students. Data from 67 students using the mindLAMP app over 28 days was analyzed. Sensor-based sleep duration estimates correlated strongly with self-reported sleep duration (r=0.83). A predictive model using sensor data and surveys accurately predicted Pittsburgh Sleep Quality Index (PSQI) scores within 1 point. The findings suggest smartphone-based sleep monitoring offers a practical and scalable alternative to traditional methods.
Publisher
npj Mental Health Research
Published On
Mar 17, 2023
Authors
Carsten Langholm, Andrew Jin Soo Byun, Janet Mullington, John Torous
Tags
smartphone sensors
sleep monitoring
college students
data analysis
predictive modeling
self-reported sleep
digital psychiatry
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