Preliminary Research on Risk Early Warning Models for College Students Based on Big Data

本研究旨在通过问卷调查的方式，系统分析大学生健康风险的影响因素，构建健康与风险状况评估体系。研究采用自行设计的“大学生健康与风险状况调查问卷”，包含学业压力感知、心理健康状况、人际适应与交往、生活行为习惯、健康风险认知与求助意识以及对风险预警技术态度六个维度，共31个题项。通过对云南某高校800名大学生的有效样本进行调查，运用探索性因子分析、验证性因子分析和结构方程模型等统计方法进行数据分析。研究发现：(1) 心理健康状况在大学生健康体系中扮演核心角色，直接影响人际适应、生活习惯和健康风险认知；(2) 学业压力对心理健康的影响呈现复杂的正向关系，适度的学业压力可能激发学习动力和成就感；(3) 生活行为习惯主要受心理健康状况的显著影响，而非外部压力的直接作用；(4) 健康风险认知与求助意识同时受到心理健康状况和生活行为习惯的双重影响；(5) 健康风险认知与求助意识对风险预警技术态度有显著正向影响。基于研究结果，本研究提出三个核心对策建议：一是建立专业化心理健康服务体系，将心理健康教育置于学生健康管理的核心位置；二是实施综合性教育管理策略，针对学业压力实施差异化管理，推进健康生活方式教育；三是构建智能化健康风险预警平台，基于大数据和人工智能技术开发智能预警算法，实现对风险学生的早期识别和个性化干预。本研究揭示了大学生健康风险的内在结构和相互作用机制，为理解大学生健康状况的形成提供了系统性的科学依据，对于提升高校学生管理水平和促进大学生身心健康发展具有重要的理论价值和实践意义。This study aims to systematically analyze the influencing factors of health risks among college students and construct an assessment system for health and risk status through a questionnaire survey. The research adopts a self-designed “College Students’ Health and Risk Status Questionnaire”, which covers six dimensions: academic stress perception, mental health status, interpersonal adaptation and communication, lifestyle habits, health risk cognition and help-seeking awareness, and attitudes toward risk warning technologies, comprising a total of 31 items. By surveying 800 valid samples from a university in Yunnan, exploratory factor analysis, confirmatory factor analysis, and structural equation modeling were used for data analysis. The results revealed: (1) Mental health status plays a central role in the college student health system, directly affecting interpersonal adaptation, lifestyle habits, and health risk cognition; (2) The impact of academic stress on mental health presents a complex positive relationship, where moderate academic stress may stimulate motivation and a sense of achievement; (3) Lifestyle habits are mainly influenced by mental health status, rather than by direct external pressure; (4) Health risk cognition and help-seeking awareness are simultaneously influenced by both mental health status and lifestyle habits; (5) Health risk cognition and help-seeking awareness have a significant positive impact on attitudes toward risk warning technologies. Based on the research findings, three core countermeasures are proposed: first, to establish a professional mental health service system and place mental health education at the core of student health management; second, to implement comprehensive educational management strategies, manage academic stress differentially, and promote health lifestyle education; third, to build an intelligent health risk warning platform and develop smart warning algorithms based on big data and artificial intelligence technologies to achieve early identification and personalized intervention for at-risk students. This study reveals the internal structure and interaction mechanism of health risks among college students, providing a systematic scientific basis for understanding the formation of college students’ health status. It holds important theoretical and practical significance for improving student management in colleges and promoting the physical and mental health development of college students.