International Open Access Journal Platform

基于AI的高校心理健康分级干预闭环机制研究 ——以山东省学生文化特质为导向

Research on a Closed-loop Mechanism for AI—Based Tiered Intervention in University Student Mental Health —Oriented Towards the Cultural Characteristics of Students in Shandong Province

Psychology of China / 2026,8(2): 170-177 / 2026-03-03 75 63

View Download PDF

• Authors: 强景 王胜川 闫迎春
• Information:

  济宁医学院，济宁

• Keywords:
  Artificial intelligence; University students; Mental health; Tiered intervention; Closed-loop mechanism; Cultural characteristics; Shandong province
  人工智能; 高校学生; 心理健康; 分级干预; 闭环机制; 文化特质; 山东省
• Abstract: Addressing the issues of disconnected intervention links, insufficient cultural adaptability, and the lack of a long-term feedback mechanism in mental health interventions for university students in Shandong Province under the context of AI empowerment, this study constructs an AI-driven closed-loop mechanism for tiered mental health intervention, guided by the cultural characteristics of university students in Shandong Province. Based on an analysis of the psychological traits of university students in Shandong Province under the influence of Confucian culture, and centering on a multi-modal data fusion and cultural adaptation model, this study establishes a four-ring linked closedloop framework: AI-based intelligent identification, culturally adapted intervention, multi-dimensional effectiveness evaluation, and dynamic model optimization. Taking the pilot applications in multiple universities in Shandong Province as the research subject and employing action research and case analysis methods to verify the mechanism’s effectiveness, the results show that this mechanism effectively addresses the issue of low intervention acceptability caused by the introverted emotional expression of students in Shandong. It achieves an organic connection among all links of mental health intervention and significantly improves intervention accuracy and resource allocation efficiency. Finally, a multi-dimensional guarantee system is proposed, covering data ethics, organizational collaboration, and technological iteration, providing a feasible path for the intelligent and localized development of mental health interventions in universities in Shandong Province and across China. 针对人工智能赋能背景下山东省高校学生心理健康干预存在的干预环节脱节、文化适配性不足、缺乏长效反馈机制等问题，本研究构建以山东省高校学生文化特质为导向的AI赋能心理健康分级干预闭环机制。研究在解构儒家文化影响下山东省高校学生心理特质的基础上，以多模态数据融合与文化适配模型为核心，搭建AI智能识别—文化适配干预—多维度效果评估—模型动态优化的四环联动闭环架构。以山东省多所高校试点应用为研究对象，采用行动研究与案例分析方法验证闭环机制的运行效果，结果表明该机制有效解决了山东高校学生情绪表达内敛导致的干预接受度低问题，实现了心理健康干预各环节的有机衔接，显著提升了干预精准度与资源配置效率。最后研究提出数据伦理、组织协同、技术迭代的多维保障体系，为山东省乃至全国高校心理健康干预的智能化、本土化发展提供可行路径。
• DOI: https://doi.org/10.35534/pc.0802027 (registering DOI)
• Cite: 强景, 王胜川, 闫迎春. (2026). 基于AI的高校心理健康分级干预闭环机制研究——以山东省学生文化特质为导向. 中国心理学前沿, 8 (2), 170-177.