Research on the Intervention Effect of University Precision Mental Health Education Enabled by Artificial Intelligence on College Students' Psychological Anxiety
Fei ChenAbstract
Objective
Modern college students endure persistent academic and interpersonal psychological pressure, causing unstable mental states and hidden mental health disorders. Traditional campus psychological intervention is extensive yet poorly targeted. This study explores AI’s value in precise mental health education to solve intervention dilemmas, define ethical norms and comprehensively improve students’ mental health.
Subjects and Methods
Adopting literature analysis, case comparison and theoretical deduction, this research selects undergraduates with differentiated psychological pressure and mental health levels as samples. It summarizes AI’s strengths in mental health monitoring, psychological risk screening and personalized counseling, and sorts out ethical risks that damage students’ spiritual states.
Results
AI precisely identifies hidden psychological pressure and tracks abnormal mental fluctuations, improving the efficiency of mental health intervention. Without complete ethical constraints, improper technical use triggers anxiety and privacy fears, causing secondary harm to students’ mental health and obstructing targeted psychological education implementation.
Conclusions
AI-powered modes offer new support for university precise mental health education. Defining ethical boundaries and optimizing practice paths effectively relieve students’ accumulated psychological pressure, regulate negative mental states and ward off psychological risks. This research constructs a humanized framework for sound development of campus mental health services.
Corresponding Author
Fei Chen, Sichuan University, School of Marxism, Chengdu, 610000, Sichuan, China