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Computer vision syndrome and its determinants: A systematic review and meta-analysis
Asamene Kelelom Lema1, Etsay Woldu Anbesu2
1Department of Computer Science, College of Engineering and Technology, Samara University, Samara, Ethiopia.
SAGE Open Medicine
|December 15, 2022
Summary
Computer vision syndrome affects two-thirds of users, with female gender and poor ergonomics increasing risk. Good knowledge of computer vision syndrome (CVS) can reduce its prevalence.
Area of Science:
- Ophthalmology
- Public Health
- Ergonomics
Background:
- Computer vision syndrome (CVS) is a growing public health concern with varied reported prevalence.
- Existing research presents inconsistent findings regarding CVS prevalence and contributing factors.
Purpose of the Study:
- To systematically review and meta-analyze the pooled prevalence of computer vision syndrome.
- To identify key determinants associated with computer vision syndrome.
Main Methods:
- Systematic review and meta-analysis adhering to PRISMA guidelines.
- Searched PubMed/Medline, CINAHL, and Google Scholar from December 2021 to April 2022.
- Assessed study quality using JBI-MAStARI and analyzed data with RevMan and STATA 14.
Main Results:
- Included 49 studies from 725 retrieved, revealing a pooled prevalence of 66% for computer vision syndrome.
- Significant risk factors included being female, improper posture, non-work device use, lack of breaks, prolonged VDT use, short screen distance, and poor ergonomics.
- Conversely, good knowledge of CVS was associated with decreased odds of developing the condition.
Conclusions:
- Approximately two-thirds of individuals experience computer vision syndrome.
- Identified risk factors highlight the importance of ergonomic practices and user behavior.
- Enhanced awareness and knowledge of CVS are crucial for mitigating its impact.
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