大学生课业压力–睡眠–体重关联模型构建与护理干预措施

Construction of the Correlation Model of Academic Stress, Sleep and Body Weight among College Students and Relevant Nursing Interventions

摘要: 目的：构建大学生课业压力–睡眠–体重的AI关联模型探讨护理措施干预效果。方法：选取756名本科生，筛选40名中高风险学生随机均分为干预组与对照组。对照组接受常规健康宣教；干预组依托AI模型进行风险分层，实施分层、个体化、多学科联动干预：低风险以健康行为巩固为主(健康知识推送、AI睡眠打卡、线上心理疏导)；中风险增加个性化运动与膳食指导；高风险启动校医、心理教师、辅导员联合干预(一对一情绪疏导、正念训练、精准营养管理)，动态监测并调整方案。干预8周后比较核心指标。结果：干预后，干预组PSQI评分降至5.7 ± 1.9 (降幅32.9%)、PSS评分降至19.7 ± 5.0 (降幅24.2%)、BMI降至23.3 ± 2.5 (降幅3.3%)、体脂率降至24.6 ± 3.8% (降幅7.2%)，改善效果均显著优于对照组(P < 0.05或P < 0.01)。结论：基于AI关联模型的风险分层为制定大学生课业压力–睡眠–体重的护理干预措施提供了可操作的决策框架。

Abstract: Objective: To construct an artificial intelligence correlation model of academic stress, sleep quality and body mass among college students, and explore the corresponding nursing intervention strategies. Methods: A total of 756 undergraduate students from local universities were enrolled and surveyed by questionnaire from February to June 2025. Forty students with moderate to high health risks were selected and divided into the intervention group and the control group, with 20 cases in each group. The control group received routine health education. The intervention group underwent risk stratification via the AI correlation model and received hierarchical, individualized and multidisciplinary nursing interventions. Low-risk students received customized health tips, AI sleep tracking and online psychological guidance. Moderate-risk students were provided with tailored exercise and diet plans to rectify unhealthy lifestyles. High-risk students got combined support from school doctors, counselors and tutors, including one-on-one emotional counseling, daily mindfulness training and targeted nutrition management, with real-time monitoring and plan adjustment. Core indicators of the two groups were compared after 8 weeks of intervention. Results: After intervention, the Pittsburgh Sleep Quality Index (PSQI) score of the intervention group decreased to 5.7 ± 1.9, with a reduction rate of 32.9%; the Perceived Stress Scale (PSS) score decreased to 19.7 ± 5.0, with a reduction rate of 24.2%; the Body Mass Index (BMI) decreased to 23.3 ± 2.5, with a reduction rate of 3.3%; the body fat percentage decreased to 24.6 ± 3.8%, with a reduction rate of 7.2%. The improvement of all indicators in the intervention group was significantly better than that in the control group (P < 0.05 or P < 0.01). Conclusion: The risk stratification based on the AI correlation model provides a decision-making framework for developing targeted nursing interventions for academic stress, sleep quality and body weight among college students.