Smartphone App Predicts Adolescent Mental Health Risk

Researchers at Imperial College London conducted a 14-day study (n=103) using the Mindcraft smartphone app to collect daily self-reports and continuous passive sensor data from school-going adolescents. A contrastive pretraining deep learning model integrating active and passive streams predicted SDQ-high risk, insomnia, suicidal ideation, and eating disorder with balanced accuracies 0.71, 0.67, 0.77, and 0.70; external validation (n=45) achieved 0.63–0.72. Findings indicate feasibility for scalable, school-based early detection.