Evidence map›Paper›PMID 39716132›Full record

SynthesisBMC public health2024

An umbrella review of the prevalence of depression during the COVID-19 pandemic: Call to action for post-COVID-19 at the global level.

Mohammad Mohseni, Saber Azami-Aghdash, Salman Bashzar, Haleh Mousavi Isfahani, Elaheh Parnian, Mostafa Amini-Rarani

Abstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mohammad MohseniHealth Management and Economics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Saber Azami-AghdashTabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Salman BashzarSocial Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Haleh Mousavi IsfahaniDepartments of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Elaheh ParnianDepartment of Health Economics, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Mostafa Amini-RaraniSocial Determinants of Health Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. m.amini@mng.mui.ac.ir.

Funding

Isfahan University of Medical Sciences IR.MUI.NUREMA.REC.1403.025
6 · The paper itself

Abstract

backgroundPandemics can lead to mental health problems such as depression. This meta-analysis of meta-analyses aimed to estimate the precise prevalence of depression during the COVID-19 pandemic.

methodsWeb of Science, PubMed, Scopus, and Embase were searched for published meta-analyses using relevant keywords, such as depression, prevalence, COVID-19, and meta-analysis up to March 18, 2024 according to the PRISMA guidelines. Relevant journals as well as the search engine Google Scholar were manually searched to discover more articles. The AMSTAR tool was used for quality assessment. A random-effects model was used for the analysis. All analyses were conducted using the STATA 17 software.

resultsOf 535 records, 82 meta-analyses were included. The results showed that the overall prevalence of depression was 30% [95% CI: 29-32] with a high heterogeneity (I

conclusionsThe results showed that the prevalence of depression was high during the COVID-19 pandemic, particularly among medical students. Policy makers should pay more attention to these groups and those who are at greater risk. Primary mental health interventions and policies are necessary to support the mental health of these individuals during the pandemic.

Indexed as

COVID-19DepressionGlobal HealthHumansMeta-Analysis as TopicPandemicsPrevalenceCOVID-19DepressionMeta-analysisPandemicPrevalence

Identifiers

PMID39716132
PMCPMC11664853

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.