Predicting multiple mental health outcomes in adolescents using explainable machine learning models

Introduction

Adolescent mental health problems, including depression, anxiety, and stress, are an increasing public health concern, yet the factors associated with different mental health outcomes may vary across domains. This study investigated shared and outcome-specific predictive features of depression, anxiety, perceived stress, and psychological well-being using explainable machine learning models.