Prevalence of computer vision syndrome: A systematic review and meta-analysis

Fabricio Ccami-Bernal, David R. Soriano-Moreno, Milton A. Romero-Robles, Fernanda Barriga-Chambi, Kimberly G. Tuco, Sharong D. Castro-Diaz, Janeth N. Nuñez-Lupaca, Josmel Pacheco-Mendoza, Tomas Galvez-Olortegui, Vicente A. Benites-Zapata*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

Purpose: This review aimed to estimate the prevalence of computer vision syndrome (CVS) in the general population and subgroups. Methods: A search was conducted in the following the databases: PubMed, SCOPUS, EMBASE, and Web of Science until February 13, 2023. We included studies that assessed the prevalence of CVS in any population. The Joanna Briggs Institute's critical appraisal tool was used to evaluate the methodological quality. A meta-analysis of the prevalence of CVS was done using a random-effects model, assessing the sources of heterogeneity using subgroup and meta-regression analyses. Results: A total of 103 cross-sectional studies with 66 577 participants were included. The prevalence of CVS was 69.0% (95% CI: 62.3 to 75.3; I2: 99.7%), ranging from 12.1 to 97.3% across studies. Point prevalence was higher in women than in men (71.4 vs. 61.8%), university students (76.1%), Africa (71.2%), Asia (69.9%), contact lens wearers (73.1% vs. 63.8%) in studies conducted before the COVID-19 pandemic (72.8%), and in those that did not use the CVS-Q questionnaire (75.4%). In meta-regression, using the CVS-Q scale was associated with a lower prevalence of CVS. Conclusion: Seven out of ten people suffer from CVS. Preventive strategies and interventions are needed to decrease the prevalence of this condition which can affect productivity and quality of life. Future studies should standardize a definition of CVS.

Original languageEnglish
Article number100482
JournalJournal of Optometry
Volume17
Issue number1
DOIs
StatePublished - 1 Jan 2024

Keywords

  • Computer vision syndrome
  • Electronic devices
  • Occupational health
  • Vision disorders
  • Visual ergonomic
  • Workspace ergonomics

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