Jiang Minmin, Zhao Ying, Wang Jing, Hua Long, Chen Yan, Yao Yingshui, Jin Yuelong
Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, Wuhu, China.
Anhui College of Traditional Chinese Medicine, Wuhu, China.
Psychiatry Investig. 2022 Jan;19(1):9-15. doi: 10.30773/pi.2021.0147. Epub 2022 Jan 7.
This cross-sectional study explores the serial multiple mediation of the correlation between internet addiction and depression by social support and sleep quality of college students during the COVID-19 epidemic.
We enrolled 2,688 students from a certain university in Wuhu, China. Questionnaire measures of internet addiction, social support, sleep quality, depression and background characteristics were obtained.
The prevalence of depression, among 2,688 college students (median age [IQR]=20.49 [20.0, 21.0] years) was 30.6%. 32.4% of the students had the tendency of internet addiction, among which the proportion of mild, moderate and severe were 29.8%, 2.5% and 0.1%, respectively. In our normal internet users and internet addiction group, the incidence of depression was 22.6% and 47.2%, respectively. The findings indicated that internet addiction was directly related to college students' depression and indirectly predicted students' depression via the mediator of social support and sleep quality. The mediation effect of social support and sleep quality on the pathway from internet addiction to depression was 41.97% (direct effect: standardized estimate=0.177; total indirect effect: standardized estimate=0.128). The proposed model fit the data well.
Social support and sleep quality may continuously mediate the link between internet addiction and depression. Therefore, the stronger the degree of internet addiction, the lower the individual's sense of social support and the worse the quality of sleep, which will ultimately the higher the degree of depression. We recommend strengthening monitoring of internet use during the COVID-19 epidemic, increasing social support and improving sleep quality, so as to reduce the risk of depression for college students.
本横断面研究探讨在新冠疫情期间，社会支持和睡眠质量对大学生网络成瘾与抑郁之间相关性的系列多重中介作用。
我们招募了来自中国芜湖某大学的2688名学生。通过问卷调查获取了网络成瘾、社会支持、睡眠质量、抑郁及背景特征等相关数据。
在2688名大学生（中位年龄[四分位间距]=20.49[20.0,21.0]岁）中，抑郁患病率为30.6%。32.4%的学生有网络成瘾倾向，其中轻度、中度和重度的比例分别为29.8%、2.5%和0.1%。在我们的正常上网用户组和网络成瘾组中，抑郁发生率分别为22.6%和47.2%。研究结果表明，网络成瘾与大学生抑郁直接相关，并通过社会支持和睡眠质量的中介作用间接预测学生的抑郁。社会支持和睡眠质量在网络成瘾到抑郁的路径上的中介效应为41.97%（直接效应：标准化估计值=0.177；总间接效应：标准化估计值=0.128）。所提出的模型与数据拟合良好。
社会支持和睡眠质量可能持续中介网络成瘾与抑郁之间的联系。因此，网络成瘾程度越强，个体的社会支持感越低，睡眠质量越差，最终抑郁程度越高。我们建议在新冠疫情期间加强对网络使用的监测，增加社会支持并改善睡眠质量，以降低大学生抑郁的风险。
