Computer vision syndrome and its determinants: A systematic review and meta-analysis

Asamene Kelelom Lema; Etsay Woldu Anbesu

doi:10.1177/20503121221142402

Computer vision syndrome and its determinants: A systematic review and meta-analysis

SAGE Open Med. 2022 Dec 9:10:20503121221142402. doi: 10.1177/20503121221142402. eCollection 2022.

Authors

Asamene Kelelom Lema¹, Etsay Woldu Anbesu²

Affiliations

¹ Department of Computer Science, College of Engineering and Technology, Samara University, Samara, Ethiopia.
² Department of Public Health, College of Medical and Health Sciences, Samara University, Samara, Ethiopia.

Abstract

Objective: Computer vision syndromes are becoming a major public health concern. Inconsistent findings existed on computer vision syndrome. This systematic review and meta-analysis aimed to estimate the pooled prevalence of computer vision syndrome and identify its determinants.

Methods: In this study, the review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Online electronic databases, including PubMed/Medline, CINAHL, and Google Scholar, were used to retrieve studies from 1 December to 9 April 2022. Quality assessment of the studies was performed using the JBI-MAStARI. RevMan and STATA 14 software were used for statistical analysis.

Result: A total of 725 studies were retrieved, and 49 studies were included. The pooled prevalence of computer vision syndrome was 66% (95%, Confidence interval: 59, 74). Being female (Odd Ratio = 1.74, 95% Confidence interval [1.2, 2.53]), improper body posturing while using electronic devices (Odd Ratio = 2.65, 95% Confidence interval [1.7, 4.12]), use of electronic devices out of work (Odd Ratio = 1.66, 95% CI [1.15, 2.39]), no habit of taking breaks (Odd Ratio = 2.24, 95% Confidence interval [1.13, 4.44]), long duration of visual display terminal use (Odd Ratio = 2.02, 95% Confidence interval [1.08, 3.77]), short distance screen (Odd Ratio = 4.24, 95% Confidence interval [2.33, 7.71]), and general ergonomic practice (Odd Ratio = 3.87, 95% Confidence interval [2.18, 6.86]) were associated with increased odds of computer vision syndrome. However, good knowledge (Odd Ratio = 4.04, 95% Confidence interval [2.75, 5.94]) of computer vision syndrome was associated with decreased odds of computer vision syndrome.

Conclusion: Nearly two in three participants had computer vision syndrome. Being female, improper body posturing, use of electronics devices out of work, no habit of taking a break, long-hour duration of visual display terminal use, short-distance screen, and general ergonomic practice were associated with increased odds of computer vision syndrome.

Keywords: Pooled prevalence; computer vision syndrome; determinants; meta-analysis; systematic review.

Publication types

Review