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Objective: To examine prevalence and correlates of insomnia symptoms in older Chinese adults (OCAs) during the COVID-19 outbreak.Background: During the COVID-19 pandemic, insomnia is a major health concern of elderly individuals, but its subtypes have not been investigated.Methods: Altogether, 590 OCAs (50+ years) were recruited via snowball sampling during the COVID-19 outbreak. Standardized self-report questions were used to assess the presence of difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), and early morning awakening (EMA). Classification tree analysis (CTA) was used to identify correlates of insomnia.Results: The one-month prevalence (95% confidence interval) of any subtype of insomnia symptoms was 23.4% (20.0-26.8%), with DIS, DMS, and EMA being 15.4% (12.5-18.3%), 17.1% (14.1-20.2%), and 11.2% (8.64-13.7%), respectively. Worry about being infected with COVID-19 emerged as the most salient correlate of insomnia (P < .001); compared to participants who were not worried about being infected, those who were worried and very worried were 3.2-fold (24.3% vs 7.5%) and 5.5-fold (24.3% vs 7.5%) more likely to have insomnia, respectively. Among participants in the "very worried" branch, those residing in Wuhan were 1.8-fold more likely to have insomnia than those residing in other places (50.0% vs 27.5%, P = .011). Among participants in the "worried" branch, unemployed persons were 2.0-fold more likely to have insomnia than employed persons (37.0% vs 18.1%, P < .001).Conclusions: Insomnia symptoms were prevalent among OCAs during the COVID-19 outbreak. Selective intervention programs targeting elderly individuals who are worried about being infected, living in the epicenter of COVID-19, and unemployed might be effective. [ABSTRACT FROM AUTHOR]

Background: During the COVID-19 pandemic, interventions for public mental health were mostly delivered through online modalities. Although many studies have explored the effectiveness of online psychosocial interventions through randomized controlled trials, there is a lack of quantitative synthesis of the effectiveness of online psychosocial interventions and an examination of their overall application.Objective: To understand the commonly used psychosocial interventions during the COVID-19 pandemic and the effectiveness of the interventions.Methods: Risk bias was assessed in the included studies according to the Cochrane Collaboration criteria, and data from post-test and follow-up were combined for standardized mean differences using Stata 16.0 software, and sources of heterogeneity were explored by subgroup analysis, and risk bias was assessed in the included studies using Review Manager 5.4 software. The study was written in strict accordance with PRISMA specifications, and registration was completed on the PROSPERO platform (CRD42022302917).Results: The online psychosocial intervention had an ameliorating effect on anxiety (SMD = -0.78), depression (SMD = -0.80), and insomnia (SMD = -0.19) in the public during the COVID-19 pandemic, was ineffective for the intervention on stress, and the effectiveness of the intervention on depression continued at follow-up. Subgroup analyses showed that the type of intervention, intervention form, Duration of intervention, and setting of the control group influenced the trial results to some extent, with cognitive behavioral therapy being the most effective intervention for anxiety and depressive symptoms, self-help interventions being more effective than interventions with therapist interventions, and 1-4 week interventions being more effective than 5-8 week interventions. Due to the limited number of studies included in the analysis and variability in quality, more randomized controlled trials are needed to test the findings.Conclusion: Online psychosocial interventions can be effective in improving symptoms of anxiety, depression, stress, and insomnia in the public during the COVID-19 pandemic. However, additional randomized controlled trial studies are needed to determine which types of interventions are more appropriate for which populations and how they can be implemented to achieve better intervention outcomes. [ABSTRACT FROM AUTHOR]