安徽省医学院校大学生抑郁与网络成瘾及失眠的关联

季文平; 张鸿雁; 田英汉; 杨铖; 汪松; 时玉东; 胡亮亮; 吴碧容; 夏磊

doi:10.16835/j.cnki.1000-9817.2023.08.012

安徽省医学院校大学生抑郁与网络成瘾及失眠的关联

doi: 10.16835/j.cnki.1000-9817.2023.08.012

1.
安徽医科大学附属巢湖医院科研科(研究生培养科), 合肥 238000
2.
安徽医科大学附属巢湖医院党委宣传科
3.
安徽医科大学附属巢湖医院精神科
4.
安徽医科大学附属巢湖医院教育科
5.
安徽医科大学公共卫生学院

基金项目:

安徽省高校人文社会科学研究项目 SK2020A0149

详细信息

作者简介:
季文平(1986-), 男, 安徽无为人, 硕士, 卫生管理师, 主要从事医学教育与科研管理方面工作

通讯作者:
夏磊, E-mail: xialei@ahmu.edu.cn

利益冲突声明 所有作者声明无利益冲突。
中图分类号: B844.2 C913.5 G478
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- 被引次数: 0
出版历程
- 收稿日期: 2023-05-12
- 修回日期: 2023-06-06
- 网络出版日期: 2023-08-26
- 刊出日期: 2023-08-25

Association of depressive symptoms, Internet addiction and insomnia among medical students in Anhui Province

1.
Department of Postgraduate Training, Chaohu Hospital of Anhui Medical University, Hefei (238000), China

摘要

摘要: 目的了解医学院校大学生失眠、网络成瘾与抑郁症状现况, 探讨网络成瘾对失眠的影响及抑郁在二者关系中的中介作用, 以期为医学院校大学生制定针对性干预对策和措施提供依据。方法 2021年6月, 采取分层整群抽样方法, 选取安徽省3所医学院校的全日制1 438名在校大学生为调查对象。采用中文版失眠严重程度指数(ISI)量表、网络成瘾测试(IAT)量表、9项患者健康问卷(PHQ-9)对大学生失眠、网络成瘾与抑郁进行评估。采用多因素Logistic回归分析探讨医学院校大学生失眠的影响因素, 分别分析失眠与网络成瘾及抑郁症状的关系。结果大学生网络成瘾检出率为49.5%, 抑郁症状检出率为39.5%, 失眠检出率为18.6%。学习压力大、周围人确诊为新冠病毒感染, 与较高失眠的风险有关(P值均 < 0.05)。随着网络成瘾程度越高(轻度, OR=2.59;中度/重度, OR=4.21)、抑郁症状的程度越严重(轻度, OR=6.35;中度/重度, OR=19.32), 大学生失眠风险越高(P值均 < 0.05)。中介效应分析显示, 网络成瘾对失眠具有直接预测作用(β=0.02, P < 0.05), 还可通过抑郁间接影响失眠(中介效应值为0.07, 95%CI=0.06~0.08)。结论安徽省医学院校大学生失眠、网络成瘾及抑郁检出率均较高, 网络成瘾和抑郁症状是失眠的相关因素。应加强关注, 必要时予以适宜的干预, 以提高大学生身心健康水平。
- 抑郁 /
- 睡眠障碍 /
- 因特网 /
- 行为, 成瘾 /
- 精神卫生 /
- 回归分析 /
- 学生
Abstract: Objective To investigate the status of insomnia, Internet addiction, and depressive symptoms among medical students and to analyze the effect of Internet addiction on insomnia and the mediating role of depressive symptoms, in order to provide a basis for the development of targeted interventions and measurements for medical students. Methods A stratified whole-group sampling method was used to select full-time college students from three medical universities in Anhui Province. The Chinese version of Insomnia Severity Index (ISI), Internet Addiction Test (IAT) scale and 9-item Patient Health Questionnaire (PHQ-9) were used to evaluate the symptoms of insomnia, Internet addiction and depressive in students. A multivariate Logistic regression analysis was used to explore the factors influencing insomnia among medical students and to analyze the relationship between insomnia with Internet addiction and depressive symptoms, respectively. Results The overall rate of Internet addiction was 49.5%, depressive symptoms was 39.5%, insomnia was 18.6%. High academic stress, and the presence of surrounding people diagnosed with COVID-19 were associated with a higher risk of insomnia (P < 0.05). The higher the level of Internet addiction (mild, OR=2.60; moderate/severe, OR=4.21) and depression. (mild, OR=6.35; moderate/severe, OR=19.32), the higher the risk of insomnia. Mediated effect analysis showed that Internet addiction had a direct predictive effect (β=0.02, P < 0.05) on insomnia and also indirectly affected insomnia through depression (indirect effect=0.07, 95%CI=0.06-0.08). Conclusion The detected rates of insomnia, Internet addiction and depressive symptoms are high among medical students in Anhui Province, and Internet addiction and depressive symptoms are risk factors for insomnia, which should be given more attention and appropriate interventions when necessary to improve their physical and mental health.
- Depression /
- Sleep disorders /
- Internet /
- Behavior, addictive /
- Mental health /
- Regression analysis /
- Students
注释:

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表 1 安徽省医学院校不同组别大学生失眠检出率比较

Table 1. Comparison of the prevalence of insomnia between groups of college students in medical universities in Anhui Province

组别	选项	人数	失眠人数	χ²值	P值
年龄/岁	≤18	418	73(17.5)	0.47	0.49
	＞18	1 020	194(19.0)
性别	男	600	108(18.0)	0.22	0.64
	女	838	159(19.0)
所在地区	合肥	599	106(17.7)	6.33	0.04
	蚌埠	388	88(22.7)
	芜湖	451	73(16.2)
专业	医学类	874	165(18.9)	3.18	0.20
	药学类	260	39(15.0)
	其他非医药类	304	63(20.7)
学历	本科	1 200	227(18.9)	0.59	0.44
	研究生	238	40(16.8)
每周体育锻炼频次	＜3	991	202(20.4)	6.95	0.01
	≥3	447	65(14.5)
独生子女	是	1 006	187(18.6)	0.00	0.98
	否	432	80(18.5)
父母婚姻状况	正常	1 285	236(18.4)	0.33	0.57
	不正常	153	31(20.3)
学习压力	小	88	11(12.5)	47.20	＜0.01
	一般	975	142(14.6)
	大	375	114(30.4)
周围人确诊为新冠病毒感染	无	1 358	240(17.7)	12.92	＜0.01
	有	80	27(33.8)
接受疫情相关信息的频率	较少	346	63(18.2)	1.22	0.54
	一般	476	82(17.2)
	较多	616	122(19.8)
网络成瘾	无	726	75(10.3)	79.99^a	＜0.01
	轻度	554	137(24.7)
	中度	140	45(32.1)
	重度	18	10(55.6)
抑郁症状	无	870	51(5.9)	293.75	＜0.01
	轻度	414	126(30.4)
	中度	105	60(57.1)
	重度	49	30(61.2)
注：()内数字为检出率/%；父母婚姻状况不正常包括分居或离异，单方或双方去世；a为采用Fisher确切概率法。

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表 2 安徽省医学院校大学生失眠相关因素的二分类Logistic回归分析(n=1 438)

Table 2. Binary Logistic regression analysis of factors associated with insomnia among college students in medical universities in Anhui Province(n=1 438)

自变量	选项	模型1		模型2
自变量	选项	OR值(95%CI)	P值	OR值(95%CI)	P值
所在地区	蚌埠	1.28(0.92~1.78)	0.15	1.23(0.86~1.75)	0.27
	芜湖	0.94(0.67~1.32)	0.72	1.03(0.72~1.50)	0.86
每周体育锻炼频次	≥3	0.79(0.58~1.09)	0.16	0.94(0.66~1.32)	0.72
学习压力	一般	1.39(0.70~2.75)	0.34	1.37(0.65~2.90)	0.41
	大	3.14(1.56~6.28)	0.01	2.01(0.94~4.30)	0.07
周围人确诊为新冠病毒感染	有	1.97(1.18~3.28)	＜0.01	1.75(1.00~3.06)	＜0.05
网络成瘾	轻度	2.59(1.90~3.55)	＜0.01	-	-
	中度/重度	4.21(2.76~6.40)	＜0.01	-	-
抑郁症状	轻度	-	-	6.35(4.44~9.08)	＜0.01
	中度/重度	-	-	19.32(12.40~30.10)	＜0.01
注：自变量所在地区、每周体育锻炼频次、学习压力、周围人确诊为新冠病毒感染、网络成瘾、抑郁分别以合肥、＜3次、小、无、无、无为参照。

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