Published online Jun 19, 2023. doi: 10.5498/wjp.v13.i6.361
Peer-review started: February 27, 2023
First decision: March 24, 2023
Revised: April 7, 2023
Accepted: April 24, 2023
Article in press: April 24, 2023
Published online: June 19, 2023
Processing time: 111 Days and 20.4 Hours
Existing research has demonstrated that depression is positively related to smartphone addiction, but the role of sleep has not been discussed thoroughly, especially among engineering undergraduates affected by the coronavirus disease 2019 pandemic.
To evaluate sleep as a mediator of the association between smartphone addiction and depression among engineering undergraduates.
Using a multistage stratified random sampling method, a cross-sectional survey was conducted among 692 engineering undergraduates from a top engineering university in China, and data were collected by self-reported electronic questionnaires. The data included demographic characteristics, such as age, gender, the Smartphone Addiction Scale-Short Version (SAS-SV), the 9-item Patient Health Questionnaire, and the Pittsburgh Sleep Quality Index. Pearson correlation and multiple linear regression analyses were used to examine the association between smartphone addiction and depression, while structural equation models were established to evaluate the possible mediating role of sleep.
Based on the cutoffs of the SAS-SV, the rate of smartphone addiction was 63.58 percent, with 56.21 percent for women and 65.68 percent for men, among 692 engineering students. The prevalence of depression among students was 14.16 percent, with 17.65 percent for women, and 13.18 percent for men. Smartphone addiction was positively correlated with depression, and sleep played a significant mediating effect between the two, accounting for 42.22 percent of the total effect. In addition, sleep latency, sleep disturbances, and daytime dysfunction significantly mediated the relationship between depression and smartphone addiction. The mediating effect of sleep latency was 0.014 [P < 0.01; 95% confidence interval (CI): 0.006-0.027], the mediating effect of sleep disturbances was 0.022 (P < 0.01; 95%CI: 0.011-0.040), and the mediating effect of daytime dysfunction was 0.040 (P < 0.01; 95%CI: 0.024-0.059). The influence of sleep latency, sleep disturbances, and daytime dysfunction accounted for 18.42%, 28.95%, and 52.63% of the total mediating effect, respectively.
The results of the study suggest that reducing excessive smartphone use and improving sleep quality can help alleviate depression.
Core Tip: This study described the prevalence of depression and smartphone addiction among engineering students during the coronavirus disease 2019 pandemic and analyzed the relationship between depression, smartphone addiction, and sleep. The results showed that there was an alarmingly high rate of smartphone addiction among engineering students, and they suffered from mild depression on average. Smartphone addiction and poor sleep were significant factors affecting depression, and sleep mediated the relationship between smartphone addiction and depression, including sleep latency, sleep disturbances, and daytime dysfunction.