Ou Jingyi, Wang Kunyu, Zuo Mingzhang, Chen Di, Luo Heng
Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China.
Behav Sci (Basel). 2025 May 2;15(5):618. doi: 10.3390/bs15050618.
The mental health of college students, particularly first-year students, deserves significant attention. As they transition from high school to college, they experience substantial changes not only in their learning behaviors but also in their daily behaviors, which may pose mental health challenges. However, existing studies exploring the factors influencing college students' mental health still have limitations in the selection of predictor variables and behavior assessment. Building on this, our study adopted a cross-sectional design involving 110 first-year college students in China (M = 17.94 years; 47 males, 63 females) and analyzed the impact of daily behaviors on mental health. We collected daily behavioral data through a designed mini program, and assessed mental health using the GHQ-28. LASSO regression was applied to identify key behavioral predictors, and semi-structured interviews were conducted to further explore the impact of these factors. The results show that sleep quality, planned and implemented physical exercise, average self-evaluation scores, average daily number of planned tasks, and the completion rate of planned tasks have a positive impact on mental health. These findings contribute to enhancing the theoretical understanding of how daily behaviors shape college students' mental health and offer practical guidance for universities to carry out mental health education.
大学生，尤其是大一新生的心理健康值得高度关注。当他们从高中过渡到大学时，不仅在学习行为上，而且在日常行为上都会经历巨大的变化，这可能会带来心理健康挑战。然而，现有的探索影响大学生心理健康因素的研究在预测变量的选择和行为评估方面仍然存在局限性。在此基础上，我们的研究采用横断面设计，涉及110名中国大一学生（平均年龄17.94岁；男性47名，女性63名），分析日常行为对心理健康的影响。我们通过设计的小程序收集日常行为数据，并使用一般健康问卷-28（GHQ-28）评估心理健康。应用LASSO回归来识别关键行为预测因素，并进行半结构化访谈以进一步探讨这些因素的影响。结果表明，睡眠质量、计划并实施的体育锻炼、平均自我评价得分、平均每日计划任务数量以及计划任务完成率对心理健康有积极影响。这些发现有助于增强对日常行为如何塑造大学生心理健康的理论理解，并为大学开展心理健康教育提供实践指导。
