Accepted for/Published in: JMIR Formative Research
Date Submitted: Jul 28, 2021
Date Accepted: Jan 6, 2022
Date Submitted to PubMed: Jan 7, 2022
Warning: This is an author submission that is not peer-reviewed or edited.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 QUEST Quality and Readability Analysis of COVID-19 Health Information on Google: A Cross-Sectional Analysis
ABSTRACT
Background:
The coronavirus disease-19 (COVID-19) pandemic spurred an increase of online information regarding disease spread and symptomatology.
Objective:
Our purpose was to systematically assessed the quality and readability of articles resulting from frequently Google-searched COVID-19 terms in the United States.
Methods:
We utilized Google Trends to determine the 25 most commonly searched health-related phrases between 2/29/20 and 4/30/20. The first 30 search results for each term were collected, and articles were analyzed using Quality Evaluation Scoring Tool (QUEST). Three raters scored each article in authorship, attribution, conflict of interest, currency, complementarity, and tone.
Results:
A readability analysis was conducted. Exactly 709 articles were screened, and 195 fulfilled inclusion criteria. The mean article score was 18.9 ± 2.9 out of 28 with 7% scoring in the top quartile. National news outlets published the largest share (36%) of articles. Peer-reviewed journals attained the highest average QUEST score compared to national/regional news outlets, national/state government sites, and global health organizations (all p < 0.05). The average reading level was 11.7 ± 1.9 (range 5.4 to 16.9). Only 3 (1.6%) articles were written at the recommended 6th grade levels.
Conclusions:
COVID-19 related articles are vastly varied in their attributes and levels of bias and would benefit from revisions for increased readability. Clinical Trial: n/a
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.