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Published in: BMC Public Health 1/2024

Open Access 01-12-2024 | COVID-19 | Research

Prevalence of computer vision syndrome during the COVID-19 pandemic: a systematic review and meta-analysis

Authors: Darwin A. León-Figueroa, Joshuan J. Barboza, Abdelmonem Siddiq, Ranjit Sah, Mario J. Valladares-Garrido, Suraj Adhikari, Edwin Aguirre-Milachay, Sanjit Sah, Alfonso J. Rodriguez-Morales

Published in: BMC Public Health | Issue 1/2024

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Abstract

Background

Computer vision syndrome has become a significant public health problem, especially in developing countries. Therefore, this study aims to identify the prevalence of computer vision syndrome during the COVID-19 pandemic.

Methods

A systematic review and meta-analysis of the literature was conducted using the databases PubMed, Scopus, Web of Science, and Embase up to February 22, 2023, using the search terms "Computer Vision Syndrome" and "COVID-19". Three authors independently performed study selection, quality assessment, and data extraction, and the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument was used to evaluate study quality. Heterogeneity was assessed using the statistical test I2, and the R version 4.2.3 program was used for statistical analysis.

Results

A total of 192 studies were retrieved, of which 18 were included in the final meta-analysis. The total sample included 10,337 participants from 12 countries. The combined prevalence of computer vision syndrome was 74% (95% CI: 66, 81). Subgroup analysis based on country revealed a higher prevalence of computer vision syndrome in Pakistan (99%, 95% CI: 97, 100) and a lower prevalence in Turkey (48%, 95% CI: 44, 52). In addition, subgroup analysis based on study subjects showed a prevalence of 82% (95% CI: 74, 89) for computer vision syndrome in non-students and 70% (95% CI: 60, 80) among students.

Conclusion

According to the study, 74% of the participants experienced computer vision syndrome during the COVID-19 pandemic. Given this finding, it is essential to implement preventive and therapeutic measures to reduce the risk of developing computer vision syndrome and improve the quality of life of those affected.

Trial registration

The protocol for this systematic review and meta-analysis was registered in the international registry of systematic reviews, the International Prospective Register of Systematic Reviews (PROSPERO), with registration number CRD42022345965.
Literature
13.
23.
26.
go back to reference Estrada Araoz EG, Paricahua Peralta JN, Zuloaga Araoz MC, Gallegos Ramos NA, Valverde YP, Herrera RQ, et al. Prevalence of computer vision syndrome in Peruvian university students during the COVID-19 health emergency. Arch Venez Farmacol Ter. 2022;264:70. Estrada Araoz EG, Paricahua Peralta JN, Zuloaga Araoz MC, Gallegos Ramos NA, Valverde YP, Herrera RQ, et al. Prevalence of computer vision syndrome in Peruvian university students during the COVID-19 health emergency. Arch Venez Farmacol Ter. 2022;264:70.
32.
43.
go back to reference Khan S, Khan S, Midya MZ, Khan IJ, Raghib M. Comparison of prevalence data about digital eye strain (DES), pre-lockdown versus post-lockdown period in India: a systematic review study. Children. 2021;17:18. Khan S, Khan S, Midya MZ, Khan IJ, Raghib M. Comparison of prevalence data about digital eye strain (DES), pre-lockdown versus post-lockdown period in India: a systematic review study. Children. 2021;17:18.
52.
go back to reference Hassan A, Mmk B. Prevalence of computer vision syndrome (CVS) amongst the Students of Khyber Medical University, Peshawar. En: Islamabad Congress of Ophthalmology. 2017. p. 59. Hassan A, Mmk B. Prevalence of computer vision syndrome (CVS) amongst the Students of Khyber Medical University, Peshawar. En: Islamabad Congress of Ophthalmology. 2017. p. 59.
53.
go back to reference Rao S, et al. Addressing computer vision syndrome among different sections of society working digitally amidst prevailing COVID-19 pandemic: a cross-sectional study. Al Ameen J Med Sci. 2021;14(4):305–13. Rao S, et al. Addressing computer vision syndrome among different sections of society working digitally amidst prevailing COVID-19 pandemic: a cross-sectional study. Al Ameen J Med Sci. 2021;14(4):305–13.
Metadata
Title
Prevalence of computer vision syndrome during the COVID-19 pandemic: a systematic review and meta-analysis
Authors
Darwin A. León-Figueroa
Joshuan J. Barboza
Abdelmonem Siddiq
Ranjit Sah
Mario J. Valladares-Garrido
Suraj Adhikari
Edwin Aguirre-Milachay
Sanjit Sah
Alfonso J. Rodriguez-Morales
Publication date
01-12-2024
Publisher
BioMed Central
Keyword
COVID-19
Published in
BMC Public Health / Issue 1/2024
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-024-17636-5

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