Facultad de Medicina Humana, Universidad de San Martín de Porres, Chiclayo, 15011, Peru.
Centro de Investigación en Atención Primaria en Salud, Universidad Peruana Cayetano Heredia, Lima, 15102, Peru.
BMC Public Health. 2024 Feb 29;24(1):640. doi: 10.1186/s12889-024-17636-5.
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.
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 I, and the R version 4.2.3 program was used for statistical analysis.
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.
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.
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.
计算机视觉综合征已成为一个重大的公共卫生问题,尤其是在发展中国家。因此,本研究旨在确定 COVID-19 大流行期间计算机视觉综合征的患病率。
对截止到 2023 年 2 月 22 日的 PubMed、Scopus、Web of Science 和 Embase 数据库进行了系统的文献回顾和荟萃分析,使用的检索词为“Computer Vision Syndrome”和“COVID-19”。三位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评估研究质量。使用统计检验 I 评估异质性,并使用 R 版本 4.2.3 程序进行统计分析。
共检索到 192 项研究,其中 18 项研究被纳入最终的荟萃分析。总样本包括来自 12 个国家的 10337 名参与者。计算机视觉综合征的总患病率为 74%(95%CI:66,81)。基于国家的亚组分析显示,巴基斯坦的计算机视觉综合征患病率较高(99%,95%CI:97,100),土耳其的患病率较低(48%,95%CI:44,52)。此外,基于研究对象的亚组分析显示,非学生中计算机视觉综合征的患病率为 82%(95%CI:74,89),学生中为 70%(95%CI:60,80)。
根据本研究,74%的参与者在 COVID-19 大流行期间出现了计算机视觉综合征。鉴于这一发现,有必要实施预防和治疗措施,以降低患计算机视觉综合征的风险,提高受影响人群的生活质量。
本系统评价和荟萃分析的方案已在国际系统评价注册中心,即国际前瞻性系统评价注册库(PROSPERO)进行了注册,注册号为 CRD42022345965。