An umbrella review of the prevalence of depression during the COVID-19 pandemic: Call to action for post-COVID-19 at the global level DOI Creative Commons
Mohammad Mohseni, Saber Azami–Aghdash, Salman Bashzar

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 23, 2024

Pandemics can lead to mental health problems such as depression. This meta-analysis of meta-analyses aimed estimate the precise prevalence depression during COVID-19 pandemic. Web Science, PubMed, Scopus, and Embase were searched for published using relevant keywords, depression, prevalence, COVID-19, up March 18, 2024 according PRISMA guidelines. Relevant journals well search engine Google Scholar manually discover more articles. The AMSTAR tool was used quality assessment. A random-effects model analysis. All analyses conducted STATA 17 software. Of 535 records, 82 included. results showed that overall 30% [95% CI: 29–32] with a high heterogeneity (I2: 90.98%). highest population group found in medical students (40% [30–49]), specific groups [3–78]), patients (36% [27–45]). meta-regression based on different times between start last date articles (week) each past week Covid-19 increases by almost 0.00021% -0.00025, 0.00068], P-value: 0.36, but "time" is not significant predictor an increase pandemic, particularly among students. Policy makers should pay attention these those who are at greater risk. Primary interventions policies necessary support individuals

Language: Английский

An umbrella review of the prevalence of depression during the COVID-19 pandemic: Call to action for post-COVID-19 at the global level DOI Creative Commons
Mohammad Mohseni, Saber Azami–Aghdash, Salman Bashzar

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 23, 2024

Pandemics can lead to mental health problems such as depression. This meta-analysis of meta-analyses aimed estimate the precise prevalence depression during COVID-19 pandemic. Web Science, PubMed, Scopus, and Embase were searched for published using relevant keywords, depression, prevalence, COVID-19, up March 18, 2024 according PRISMA guidelines. Relevant journals well search engine Google Scholar manually discover more articles. The AMSTAR tool was used quality assessment. A random-effects model analysis. All analyses conducted STATA 17 software. Of 535 records, 82 included. results showed that overall 30% [95% CI: 29–32] with a high heterogeneity (I2: 90.98%). highest population group found in medical students (40% [30–49]), specific groups [3–78]), patients (36% [27–45]). meta-regression based on different times between start last date articles (week) each past week Covid-19 increases by almost 0.00021% -0.00025, 0.00068], P-value: 0.36, but "time" is not significant predictor an increase pandemic, particularly among students. Policy makers should pay attention these those who are at greater risk. Primary interventions policies necessary support individuals

Language: Английский

Citations

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