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      Latent classes of health risk behaviors in medical students and depressive symptoms

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          Abstract

          Objective To identify the latent classes of various health risk behaviors among medical students and further analyze the correlation between different classes and depression.

          Methods Using the method of convenient sampling, 2 014 medical students were selected from Anhui Medical University in October 2018. Self-designed online questionnaire were used to collect demographic data, health risk behavior (including smoking, drinking, suicide, sleep disorders, mobile phone dependence and lack of exercise) and depressive symptoms. Latent Class Analysis was used to cluster individuals. Logistic regression was provided to further analyze the association between health risk behaviors and depressive symptoms for the groups.

          Results The health hazard behaviors of medical students could be divided into three separate classes: substance dependence group (8.4%), mobile phone dependence group (22.4%) and low-risk group (69.2%). The distribution of health risk behaviors of medical students with different gender, major, grade, only child, father’s educational level, monthly living expenses, academic achievement and number of friends were statistically significant (χ 2 = 99.37, 19.07, 12.05, 6.64, 14.28, 19.35, 20.61, 26.39, P<0.05). The results of Logistic regression analysis showed that after adjusting for gender, major, grade, only child, father’s educational level, monthly living expenses, academic achievement and number of friends, the mobile phone dependence group was positively correlated with depressive symptoms (β = 1.75, P<0.01).

          Conclusion Different ratent classes of health risk behaviors have different correlation with depressive symptoms in groups. lt is suggested that school health workers should make individualized intervention plan for different types of health hazard behavior of medical students in the future educational activities, carry out stratified intervention, alleviate the symptoms of depression and promote the mental health of medical students.

          Abstract

          【摘要】 目的 识别医学生多种健康危害行为的潜在类别,并进一步分析不同潜类别与抑郁症状的关联。 方法 采用方便抽样的原则,于 2018 年 10 月在安徽医科大学整群抽取 2 014 名医学生开展横断面调査。使用自编手机问卷,调査内容 包括一般人口学资料、健康危害行为评价以及抑郁症状。采用潜在类别分析方法分析吸烟、饮酒、自杀、睡眠障碍、手机依 赖、缺乏运动等 6 种健康危害行为潜在类别,采用 Logistic 回归方法进一步分析不同类别与抑郁症状的关联。 结果 医学生健康危害行为分为物质依赖组 (8.4%)、手机依赖组 (22.4%) 和低危风险组 (69.2%) 3 个潜在类别。不同性别、专业、年 级、是否为独生子女、父亲文化程度、每月生活费、学习成绩及朋友个数之间医学生健康危害行为分布差异均有统计学意义 (χ 2 值分别为 99.37, 19.07, 12.05, 6.64, 14.28, 19.35, 20.61, 26.39, P 值均<0.05)。Logistic 回归分析结果显示,调整性别、专 业、年级、独生子女及父亲文化程度、每月生活费、学习成绩以及朋友个数后,手机依赖组与抑郁症状呈正相关 (β=1.75, P<0.01)。 结论 医学生健康危害行为呈现类别分布,各潜类别健康危害行为与抑郁症状关联不同。提示学校卫生工作者在 今后的教育活动中应针对医学生不同类别的健康危害行为制定个体化干预方案,进行分层干预,缓解抑郁症状,促进学生 心理健康。

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          Author and article information

          Journal
          CJSH
          Chinese Journal of School Health
          Chinese Journal of School Health (China )
          1000-9817
          01 April 2021
          01 April 2021
          : 42
          : 4
          : 583-586
          Affiliations
          [1] 1School of Nursing, Anhui Medical University, Hefei (230601), China
          Author notes
          *Corresponding author: WU Xiaoyan, E-mail: xywu85@ 123456126.com
          Article
          j.cnki.1000-9817.2021.04.024
          10.16835/j.cnki.1000-9817.2021.04.024
          2ff79015-738f-40ea-9889-87394b33926f
          © 2021 Chinese Journal of School Health

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

          Product
          Self URI (journal-page): http://www.cjsh.org.cn
          Categories
          Journal Article

          Ophthalmology & Optometry,Pediatrics,Nutrition & Dietetics,Clinical Psychology & Psychiatry,Public health
          Mental health,Depression,Regression analysis,Students,Dangerous behavior

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