EngageTriBoost predicts user engagement in a digital mental health intervention with 84% accuracy and uses SHAP to highlight emotional dysregulation and stigma as key influences.
Online suicide risk screening and intervention with college students: a pilot randomized controlled trial
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EngageTriBoost: Predictive Modeling of User Engagement in Digital Mental Health Intervention Using Explainable Machine Learning
EngageTriBoost predicts user engagement in a digital mental health intervention with 84% accuracy and uses SHAP to highlight emotional dysregulation and stigma as key influences.