Machine Lerning-Based Analysis of Psychological Issues and Game Intervention for College Students

This thesis explores the growing mental health problems of today's students, with a special focus on depression among college students. By analyzing relevant data and literature, the possibility of using games as an innovative psychological calming tool to alleviate students' psychological stress is proposed. The paper first introduces the background and severity of students' mental health problems, as well as the limitations of traditional psychological assessment and medication. Then, it elaborates on the game-based psychological assessment technology and the application of decision tree and random forest modeling in analyzing college students' psychological data. Subsequently, the thesis designs and realizes a driving game based on classical music and natural scenery, and verifies the effectiveness of the game in relieving stress through experiments. Finally, the importance and potential of the game for students' mental health are summarized, and future research directions are envisioned. The thesis provides new ideas and methods to improve students' mental health and provide better psychological support and assistance to students.