Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 19, 2020
Date Accepted: Jan 16, 2021
Date Submitted to PubMed: Jan 22, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A systematic review for the efficiency and quality of data collection in the public mental health surveys during the COVID-19 pandemic
ABSTRACT
Background:
The World Health Organization has recognized the importance of considering population-level mental health during the COVID-19 pandemic. In a global crisis like the COVID-19 pandemic, a timely surveillance method is urgently needed to track the impact on public mental health.
Objective:
This brief review focuses on the efficiency and quality of data collection in the existing literature
Methods:
The following search strings were used: ((COVID-19) OR (SARS-CoV-2)) AND ((Mental health) OR (psychological) OR (psychiatry)). We screened the titles, abstracts, and texts to exclude irrelevant articles. We used the Newcastle-Ottawa Scale to evaluate the quality of each research.
Results:
There were 37 relevant mental health surveys of the general public during the COVID-19 pandemic found by searching the database PubMed on July 10, 2020. All the public mental health surveys examined were cross-sectional in design, and the journals efficiently made these available online in an average of 18.7 (range: 1–64) days from the date the article was received. The average duration of recruitment periods was 9.2 (range: 2–35) days, and the average sample size was 5137 (range: 100–56679). However, 73.0% (27/37) of the studies on the general public had scores on the Newcastle-Ottawa Scale of < 3 points, which suggests these studies are of too poor quality for inclusion in a meta-analysis.
Conclusions:
This review found that the data collection was efficient but generally had a high risk of bias among existing public mental health surveys. Following a recommendation to avoid selection bias, or to apply novel methodologies considering both longitudinal design and high temporal resolution, would help provide a strong basis for the formation of national mental health policies.
Citation
