Prevalence of depression, anxiety, and insomnia symptoms among patients with COVID-19: A meta-analysis of quality effects model

COVID-19 患者抑郁、焦虑和失眠症状的患病率:质量效应模型荟萃分析

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Abstract

BACKGROUND: Evidence from previous virus epidemics has shown that infected patients are at risk for developing psychiatric and mental health disorders, such as depression, anxiety, and insomnia. Hence, to collect high-quality data on the impact of COVID-19 pandemic on the prevalence of depression, anxiety, and insomnia symptoms among patients infected with SARS-CoV-2 should be the immediate priority. METHODS: A comprehensive search of Medline, Embase, Web of Science, and PsycINFO databases was conducted from January 1, 2020 to December 26, 2020 for eligible studies reporting on the prevalence of depression, anxiety, and insomnia symptoms in patients with COVID-19. Studies meeting the following criteria were included in the analysis: (1) included patients with COVD-19; (2) recorded the prevalence of depression, anxiety, or insomnia symptom; (3) sample size ≥30; (4) with validated screening tools; and (5) passed through the international peer-review process. Data extraction and quality assessment was independently performed by two reviewers. The quality effects meta-analysis was conducted further to calculate the pooled prevalence. RESULTS: Twenty-two studies were included for analysis with a total of 4318 patients. The pooled prevalence of depression, anxiety and insomnia symptoms was 38% (95% CI = 25-51), 38% (95% CI = 24-52), and 48% (95% CI = 11-85), respectively. Neither subgroup analysis nor sensitivity analysis can explain the source of high heterogeneity. In addition, the prevalence estimates of depression, anxiety and insomnia symptoms varied based on different screening tools. CONCLUSIONS: The present systematic review and meta-analysis suggest that depression, anxiety, and insomnia symptoms are prevalent in a considerable proportion of patients with COVID-19. Thus, early detection and properly intervention for mental illness in this population are of great significance. Additionally, the quality of included studies to date has been variable, and ongoing surveillance is essential.

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