通过可解释机器学习解析大学生自杀动机的多因素驱动

Suicide among university students remains a major public health concern, yet existing prediction approaches often lack both theoretical depth and practical interpretability. This study aimed to integrate structural equation modeling (SEM) and interpretable machine learning to examine suicidal tendency among Chinese university students within the framework of the Integrated Motivational-Volitional (IMV) model. A total of 3,785 students completed psychological and behavioral measures relevant to suicidal risk. SEM was used to examine theoretically specified associations, and machine learning mod