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

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          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.

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          Most cited references97

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          Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement

          Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.
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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              The PRISMA 2020 statement: An updated guideline for reporting systematic reviews

              The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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                Author and article information

                Journal
                SAGE Open Med
                SAGE Open Med
                SMO
                spsmo
                SAGE Open Medicine
                SAGE Publications (Sage UK: London, England )
                2050-3121
                9 December 2022
                2022
                : 10
                : 20503121221142402
                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
                Author notes
                [*]Etsay Woldu Anbesu, Department of Public Health, College of Medical and Health Sciences, Samara University, 132, Semera, Afar region, Ethiopia. Email: etsaywold@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-4532-6720
                Article
                10.1177_20503121221142402
                10.1177/20503121221142402
                9743027
                36518554
                aa905f99-3324-4b0f-8cc1-34ae1afe909f
                © The Author(s) 2022

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 9 September 2022
                : 14 November 2022
                Categories
                Systematic Review
                Custom metadata
                January-December 2022
                ts1

                pooled prevalence,determinants,computer vision syndrome,systematic review,meta-analysis

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