JMIR Formative Research (Feb 2022)

Assessing COVID-19 Health Information on Google Using the Quality Evaluation Scoring Tool (QUEST): Cross-sectional and Readability Analysis

  • Vismaya S Bachu,
  • Heba Mahjoub,
  • Albert E Holler,
  • Tudor Crihalmeanu,
  • Dheevena M Bachu,
  • Varun Ayyaswami,
  • Pearman D Parker,
  • Arpan V Prabhu

DOI
https://doi.org/10.2196/32443
Journal volume & issue
Vol. 6, no. 2
p. e32443

Abstract

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BackgroundThe COVID-19 pandemic spurred an increase in online information regarding disease spread and symptomatology. ObjectiveOur purpose is to systematically assess the quality and readability of articles resulting from frequently Google-searched COVID-19 terms in the United States. MethodsWe used Google Trends to determine the 25 most commonly searched health-related phrases between February 29 and April 30, 2020. The first 30 search results for each term were collected, and articles were analyzed using the Quality Evaluation Scoring Tool (QUEST). Three raters scored each article in authorship, attribution, conflict of interest, currency, complementarity, and tone. A readability analysis was conducted. ResultsExactly 709 articles were screened, and 195 fulfilled inclusion criteria. The mean article score was 18.4 (SD 2.6) of 28, with 7% (14/189) scoring in the top quartile. National news outlets published the largest share (70/189, 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<.05). The average reading level was 11.7 (SD 1.9, range 5.4-16.9). Only 3 (1.6%) articles were written at the recommended sixth grade level. ConclusionsCOVID-19–related articles are vastly varied in their attributes and levels of bias, and would benefit from revisions for increased readability.