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学生心理健康监测预警的人工智能实践研究

Research on the Practice of Artificial Intelligence in Monitoring and Early Warning of Students’ Mental Health

Psychology of China / 2025,7(12): 1617-1622 / 2025-12-26 9 5

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• Authors: 余璇¹ 邓旭² 罗姝³ 平苹⁴ 杨楠⁵ 郝博成⁶
• Information:

  1．西南石油大学经济管理学院，成都；
  2．重庆城市管理职业学院继续教育学院，重庆；
  3．重庆师范大学学生心理健康教育与咨询中心，重庆；
  4．云南省昭通市昭阳区第二中学，昭通；
  5．四川石室联合成飞学校，成都；
  6．重庆城市管理职业学院大数据与信息产业学院，重庆

• Keywords:
  Student mental health; Monitoring and early warning; Artificial intelligence; Multi-modal assessment; Home-school co-education
  学生心理健康; 监测预警; 人工智能; 多模态评估; 家校共育
• Abstract: With the increasing prominence of mental health issues on campus, the traditional psychological scale assessment model, which has drawbacks such as negative implications, low accuracy, and insufficient home-school collaboration, is no longer adequate for the needs of regular monitoring and early warning. This study takes the DEEPAssess system artificial intelligence solution for campus mental health as a practical example to deeply explore the application paths of AI technology in the monitoring and early warning of student mental health. It analyzes the practical effects of multi-modal dynamic AI expert assessment paradigms, AI mental interviews, and intelligent home visits, and verifies their value in improving screening accuracy, promoting home-school co-education, and building a localized mental health system through specific school cases. The research finds that AI technology can effectively break through the limitations of traditional monitoring models, achieving precise identification, graded intervention, and full-cycle protection of student mental health, while providing a feasible direction for the intelligent and localized development of campus mental health services. 随着校园心理健康问题日益凸显，传统心理量表测评模式因存在负面暗示、准确率低、家校联动不足等缺陷，已难以满足常态化监测预警需求。本研究以DEEP-Assess系统校园心理健康人工智能解决方案为实践样本，深入探讨人工智能技术在学生心理健康监测预警中的应用路径，分析多模态动态AI专家评估范式、AI心智访谈、智能家访等技术与模式的实践效果，并结合具体学校案例验证其在提升筛查准确率、推动家校共育、构建本土化心理健康体系等方面的价值。研究发现，人工智能技术能有效突破传统监测模式的局限，实现学生心理健康的精准识别、分级干预与全周期守护，同时为校园心理健康服务的智能化、本土化发展提供了可行方向。
• DOI: https://doi.org/10.35534/pc.0712262 (registering DOI)
• Cite: 余璇, 邓旭, 罗姝, 平苹, 杨楠, 郝博成. (2025). 学生心理健康监测预警的人工智能实践研究. 中国心理学前沿, 7 (12), 1617-1622.