Department of Public Health, College of Medical and Health Sciences, Samara University, Semera, Ethiopia.
Department of Computer Science, College of Engineering and Technology, Samara University, Semera, Ethiopia.
Sci Rep. 2023 Jan 31;13(1):1801. doi: 10.1038/s41598-023-28750-6.
Although computer vision syndromes are becoming a major public health concern, less emphasis is given to them, particularly in developing countries. There are primary studies on different continents; however, there are inconsistent findings in prevalence among the primary studies. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of computer vision syndrome. 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Online electronic databases, including PubMed/Medline, CINAHL, and Google Scholar, were used to retrieve published and unpublished studies. The study was conducted from December 1 to April 9/2022. Study selection, quality assessment, and data extraction were performed independently by two authors. Quality assessment of the studies was performed using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument tool. Heterogeneity was assessed using the statistical test I. STATA 14 software was used for statistical analysis. A total of 7,35 studies were retrieved, and 45 studies were included in the final meta-analysis. The pooled prevalence of computer vision syndrome was 66% (95% CI: 59, 74). Subgroup analysis based on country was highest in Pakistan (97%, 95% CI: 96, 98) and lowest in Japan (12%, 95% CI: 9, 15). Subgroup analysis based on country showed that studies in Saudi Arabia (I = 99.41%, p value < 0.001), Ethiopia (I = 72.6%, p value < 0.001), and India (I = 98.04%, p value < 0.001) had significant heterogeneity. In the sensitivity analysis, no single study unduly influenced the overall effect estimate. Nearly two in three participants had computer vision syndrome. Thus, preventive practice strategic activities for computer vision syndrome are important interventions.
尽管计算机视觉综合征正成为一个主要的公共卫生问题，但人们对其关注较少，尤其是在发展中国家。不同大洲都有针对该综合征的初步研究，但这些研究的患病率结果并不一致。因此，本系统评价和荟萃分析旨在评估计算机视觉综合征的综合患病率。本研究按照系统评价和荟萃分析的 Preferred Reporting Items 指南进行综述。使用在线电子数据库（包括 PubMed/Medline、CINAHL 和 Google Scholar）检索已发表和未发表的研究。研究于 2022 年 12 月 1 日至 4 月 9 日进行。两名作者独立进行了研究选择、质量评估和数据提取。使用 Joanna Briggs 研究所 Meta 分析统计评估和审查工具对研究进行质量评估。使用统计检验 I 评估异质性。使用 STATA 14 软件进行统计分析。共检索到 735 项研究，其中 45 项研究纳入最终荟萃分析。计算机视觉综合征的综合患病率为 66%（95%CI：59，74）。基于国家的亚组分析中，巴基斯坦的患病率最高（97%，95%CI：96，98），日本的患病率最低（12%，95%CI：9，15）。基于国家的亚组分析显示，沙特阿拉伯（I=99.41%，p 值<0.001）、埃塞俄比亚（I=72.6%，p 值<0.001）和印度（I=98.04%，p 值<0.001）的研究存在显著异质性。敏感性分析中，没有单个研究对总体效应估计产生不当影响。近三分之二的参与者患有计算机视觉综合征。因此，针对计算机视觉综合征的预防实践战略活动是重要的干预措施。
