Combining daily self-reports with smartphone sensor data predicted adolescent mental health risk categories with balanced accuracies of 0.67 to 0.77 in a 103-participant feasibility study.
The mental health of young people: the view from primary care
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Digital Phenotyping for Adolescent Mental Health: A Feasibility Study Employing Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data
Combining daily self-reports with smartphone sensor data predicted adolescent mental health risk categories with balanced accuracies of 0.67 to 0.77 in a 103-participant feasibility study.