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
- Author:
Minmin JIANG
1
;
Ying ZHAO
;
Jing WANG
;
Long HUA
;
Yan CHEN
;
Yingshui YAO
;
Yuelong JIN
Author Information
- Publication Type:Original Article
- From:Psychiatry Investigation 2022;19(1):9-15
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective: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.
Methods: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.
Results: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.
Conclusion: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.
