Mental health at risk: Predicting psychological distress in Australian youth through machine learning models

This study's innovative ML approach uncovers critical social and emotional risk factors for psychological distress in Australian youth. The findings highlight ML's significant role in enhancing early prediction, guiding targeted public health actions, and supporting clinical decisions to improve mental health outcomes for young people. Additionally, they reveal strong real-world potential for integration into school, community, and digital health initiatives, facilitating early detection and personalised mental health assistance.