@Article{info:doi/10.2196/25118,
author="Lin, Yu-Hsuan
and Chen, Chung-Yen
and Wu, Shiow-Ing",
title="Efficiency and Quality of Data Collection Among Public Mental Health Surveys Conducted During the COVID-19 Pandemic: Systematic Review",
journal="J Med Internet Res",
year="2021",
month="Feb",
day="10",
volume="23",
number="2",
pages="e25118",
keywords="COVID-19; mental health; Newcastle-Ottawa Scale; review; data collection; survey; surveillance; literature; research",
abstract="Background: The World Health Organization has recognized the importance of assessing population-level mental health during the COVID-19 pandemic. During a global crisis such as the COVID-19 pandemic, a timely surveillance method is urgently needed to track the impact on public mental health. Objective: This brief systematic review focused on the efficiency and quality of data collection of studies conducted during the COVID-19 pandemic. Methods: We searched the PubMed database using the following search strings: ((COVID-19) OR (SARS-CoV-2)) AND ((Mental health) OR (psychological) OR (psychiatry)). We screened the titles, abstracts, and texts of the published papers to exclude irrelevant studies. We used the Newcastle-Ottawa Scale to evaluate the quality of each research paper. Results: Our search yielded 37 relevant mental health surveys of the general public that were conducted during the COVID-19 pandemic, as of July 10, 2020. All these public mental health surveys were cross-sectional in design, and the journals efficiently made these articles available online in an average of 18.7 (range 1-64) days from the date they were received. The average duration of recruitment periods was 9.2 (range 2-35) days, and the average sample size was 5137 (range 100-56,679). However, 73{\%} (27/37) of the selected studies had Newcastle-Ottawa Scale scores of <3 points, which suggests that these studies are of very low quality for inclusion in a meta-analysis. Conclusions: The studies examined in this systematic review used an efficient data collection method, but there was a high risk of bias, in general, among the existing public mental health surveys. Therefore, following recommendations to avoid selection bias, or employing novel methodologies considering both a longitudinal design and high temporal resolution, would help provide a strong basis for the formation of national mental health policies. ",
issn="1438-8871",
doi="10.2196/25118",
url="http://www.jmir.org/2021/2/e25118/",
url="https://doi.org/10.2196/25118",
url="http://www.ncbi.nlm.nih.gov/pubmed/33481754"
}