Distinguishing the Associations Between Evening Screen Time and Sleep Quality Among Different Age Groups: A Population-Based Cross-Sectional Study

Sleep quality and screen time among university professors: impact of emergency remote teaching amidst COVID-19 crisis

PURPOSE

Sleep plays a crucial role in maintaining physical and mental health. The COVID-19 pandemic has brought about unprecedented global changes, and disruptions in sleep quality have emerged as a challenge. The pandemic prompted a dramatic shift in the working landscape for university professors, necessitating emergency remote teaching (ERT). This transition substantially increased professors' screen time for academic and research endeavors. This study explores the relationship between screen time and sleep quality among university professors during the pandemic and examines associated factors, including psychological well-being.

METHODS

An electronic survey, covering demographics, education, screen time, sleep quality, and mental health, was administered to professors who worked during the spring semester of 2020. Standardized measures were used to assess sleep quality and mental health. Correlations, Mann-Whitney tests, and multivariate regression explored associations between screen time, sleep quality, and other variables.

RESULTS

One hundred sixty participants exhibited poor sleep quality, subthreshold insomnia, and mild depression. Increased screen time correlated with poorer sleep quality, elevated stress levels, and heightened depression severity. Evening screen users reported more insomnia than daytime users. Depression emerged as a significant predictor of poor sleep quality and insomnia, along with evening screen use.

CONCLUSION

This study among university professors underscores the impact of screen time on sleep quality during the COVID-19 pandemic. Participants faced poor sleep, largely influenced by heightened screen time due to ERT. Considering these findings, this study emphasizes the importance of curbing daytime screen exposure and abstaining from screens in the evening, especially for university professors reliant on technology for their professional responsibilities.

Interactive effects of sleep and physical activity on depression among rural university students in China

Background

Decreased sleep quality and physical activity among university students have become important concerns, while depressive symptoms are on the rise, especially in rural areas. Previous studies have confirmed the association between sleep quality and physical activity and depressive symptoms, but the effect of their interaction on depressive symptoms has been less studied. For this reason, the present study analyzed the interaction between sleep quality and physical activity on depressive symptoms to provide reference and assistance for mental health promotion and intervention for university students in rural areas of China.

Methods

In this study, we investigated sleep quality, physical activity, and depressive symptoms in 11,423 university students in rural areas of China. The association of sleep quality and physical activity with depressive symptoms was analyzed by using univariate analysis and logistic regression analysis. And further analyzed the association between the interaction effect of sleep quality and physical activity and depressive symptoms.

Results

The proportion of university students with depressive symptoms in rural China was 33.3%, with a higher proportion of girls students (36.7%) having depressive symptoms than boys students (28.8%). Logistic regression analysis of the interaction between sleep quality and physical activity and depressive symptoms in university students showed that university students with poor sleep quality and MVPA>60 min/d (OR = 4.40,95% CI: 3.75-5.05) had the highest risk of depressive symptoms (p < 0.001). University students with moderate sleep quality and MVPA of 30-60 min/d (OR = 1.18, 95% CI: 0.75-1.61) had the lowest risk of depressive symptoms (p < 0.001). Moreover, there was no gender difference in this result.

Conclusion

The prevalence of depressive symptoms was higher among university students in rural areas of China. There was an interaction between sleep quality and MVPA on depressive symptoms, maintaining a good quality of sleep and an appropriate length of MVPA has a contributory effect on mental health, and the same trend was found for both boys and girls students. It is recommended that university students in rural areas of China should first maintain proper sleep quality while maintaining 30-60 min of MVPA per day, which may reduce the risk of depressive symptoms.

Association between Sleep Quality and Depression Symptoms in Chinese College Students during the COVID-19 Lockdown Period

Background: The outbreak of COVID-19 has seriously threatened the health of people around the world. To prevent the spread of the epidemic, Chinese universities have implemented closed management of campuses. The implementation of restrictive measures has gradually caused changes in the quality of sleep and the psychological state of college students. In addition, college students are faced with the dual pressure of employment and study, and the psychological pressure is huge. Therefore, it is necessary to investigate sleep and depressive symptoms among college students. Methods: Using the method of stratified cluster sampling, 6695 college students were selected from three universities in Jiangxi, Anhui, and Xinjiang provinces from April to May 2022. The Chinese version of the Pittsburgh sleep quality index (PSQI) and the self-rating depression scale (SDS) were used for the survey. Hierarchical logistic regression analysis was used to analyze the relationship between the PSQI and the SDS. Results: Overall, during the outbreak of COVID-19, 69.0% of males and 73.5% of females had poor sleep quality among Chinese college students and the detection rate of depressive symptoms was 43.6% for males and 47.8% for females, respectively. Taking students with good sleep quality as references, after controlling for covariates, hierarchical logistic regression shows that Chinese college students with poor sleep quality have a higher OR value (OR = 12.0, 95%CI: 10.2~14.1, p < 0.001), especially in males (OR = 43.8, 95%CI:30.2~63.6, p < 0.001). For both males and females, the OR value of college students with the following characteristics was higher: rural college students (males, OR = 50.32, 95%CI: 32.50−77.93; females, OR = 8.03, 95%CI: 6.45−9.99), overweight college students (males, OR = 62.17, 95%CI: 19.47−198.53; females, OR = 16.67, 95%CI: 6.48−42.88), and college students drinking sugar-sweetened beverages (males, OR = 59.00, 95%CI: 36.96−94.18; females, OR = 8.16, 95%CI: 6.63−10.05) (p < 0.001). Conclusions: Poor sleep quality is associated with depressive symptoms among Chinese college students, especially college males. Our research suggests that it is necessary to consider the improvement of sleep quality and depressive symptoms among college students during the COVID-19 epidemic.

Screen time and depression risk: A meta-analysis of cohort studies

BACKGROUND

The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk.

METHODS

The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I ² statistic. Potential publication bias was evaluated using a funnel plot and Begg's and Egger's tests.

RESULTS

The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05-1.14), with significant heterogeneity (I ² = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found.

CONCLUSION

This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant's age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression.