Sleep quality as a mediator of the relationship between screen time and negative emotions among Chinese college freshmen.

College freshmen are special populations facing great challenges in adapting to the brand new environment, and their lifestyle and emotional states are worthy of attention. Especially during the COVID-19 pandemic, their screen time and prevalence of negative emotions were significantly increased, but few studies have focused on such situation of college freshmen and illustrated relevant mechanisms. Thus, based on a sample of Chinese college freshmen during the COVID-19 pandemic, the current study aimed to investigate the association between their screen time and negative emotions (depression, anxiety and stress), and further explore the mediating effects of sleep quality. Data from 2,014 college freshmen was analyzed. The screen time was self-reported by participants using predesigned questionnaires. The Pittsburgh Sleep Quality Index (PSQI) and Chinese Version of Depression Anxiety and Stress Scale-21 (DASS-21) were used to assess sleep quality and emotional states, respectively. The mediation analysis was conducted to examine the meditation effect. Results indicated that participants with negative emotions tended to have longer daily screen time and worse sleep quality, sleep quality partially mediated the association between screen time and negative emotions.The critical role of sleep quality and related intervention measures should be recognized and implemented.

Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.

BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COVID-19 pandemic. This study aimed to explore the prevalence of depressive symptoms and evaluate the importance of influencing factors through Back Propagation Neural Network (BPNN). METHODS: Data were sourced from the psychology and behavior investigation of Chinese residents (PBICR). A total of 21,916 individuals in China were included in the current study. Multiple logistic regression was applied to preliminarily identify potential risk factors for depressive symptoms. BPNN was used to explore the order of contributing factors of depressive symptoms. RESULTS: The prevalence of depressive symptoms among the general population during the COVID-19 pandemic was 57.57 %. The top five important variables were determined based on the BPNN rank of importance: subjective sleep quality (100.00 %), loneliness (77.30 %), subjective well-being (67.90 %), stress (65.00 %), problematic internet use (51.20 %). CONCLUSIONS: The prevalence of depressive symptoms in the general population was high during the COVID-19 pandemic. The BPNN model established has significant preventive and clinical meaning to identify depressive symptoms lay theoretical foundation for individualized and targeted psychological intervention in the future.

Risk factors for depression in the elderly: An umbrella review of published meta-analyses and systematic reviews.

BACKGROUND: Depression has been identified as one of the leading causes of the disease burden worldwide. Identification of the potential factors that increased or decreased the risk of depression could be important to provide prevention strategies. We aimed to conduct an umbrella review of risk factors for depression in the elderly and assessed the credibility of evidence of the association between each factor and depression. METHODS: We searched PubMed and Web of Science from 1990 to April 11, 2021 for articles investigating associations between potential factors and depression. For each association, we recalculated the summary effect size and 95% confidence intervals using random effects models. The 95% prediction interval and between-heterogeneity were also reported. For publication bias, small-study effect and excess of significance bias were assessed. RESULTS: Twenty-five publications met the inclusion criteria, including twenty-two meta-analyses and three qualitative systematic reviews. Approximately 1,199,927 participants and 82 unique factors were reported. Two factors were rated as convincing evidence and four factors showed highly suggestive evidence. These risk factors were aspirin use, individuals aged 80 years and above, sleep disturbances and persistent sleep disturbances, hearing problem, poor vision, and cardiac disease. LIMITATIONS: Most studies that we included were of low quality. CONCLUSIONS: We found several risk factors for depression with different levels of evidence, in which aspirin use and individuals aged 80 years and above presented the strongest evidence. Further research is warranted to support other findings from this umbrella review using a large, well-designed cohort study.