Dataset Information

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

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.

SUBMITTER: Lema AK

PROVIDER: S-EPMC9743027 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Lema Asamene Kelelom AK Anbesu Etsay Woldu EW

SAGE open medicine 20221209

<h4>Objective</h4>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.<h4>Methods</h4>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 Go ...[more]

PMID: 36518554

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Project description:BackgroundSchizophrenia is a severe psychiatric disorder that causes significant social and functional impairment. Currently, the diagnosis of schizophrenia is based on information gleaned from the patient's self-report, what the clinician observes directly, and what the clinician gathers from collateral informants, but these elements are prone to subjectivity. Utilizing computer vision to measure facial expressions is a promising approach to adding more objectivity in the evaluation and diagnosis of schizophrenia.MethodWe conducted a systematic review using PubMed and Google Scholar. Relevant publications published before (including) December 2021 were identified and evaluated for inclusion. The objective was to conduct a systematic review of computer vision for facial behavior analysis in schizophrenia studies, the clinical findings, and the corresponding data processing and machine learning methods.ResultsSeventeen studies published between 2007 to 2021 were included, with an increasing trend in the number of publications over time. Only 14 articles used interviews to collect data, of which different combinations of passive to evoked, unstructured to structured interviews were used. Various types of hardware were adopted and different types of visual data were collected. Commercial, open-access, and in-house developed models were used to recognize facial behaviors, where frame-level and subject-level features were extracted. Statistical tests and evaluation metrics varied across studies. The number of subjects ranged from 2-120, with an average of 38. Overall, facial behaviors appear to have a role in estimating diagnosis of schizophrenia and psychotic symptoms. When studies were evaluated with a quality assessment checklist, most had a low reporting quality.ConclusionDespite the rapid development of computer vision techniques, there are relatively few studies that have applied this technology to schizophrenia research. There was considerable variation in the clinical paradigm and analytic techniques used. Further research is needed to identify and develop standardized practices, which will help to promote further advances in the field.

Project description:AimTo conduct the first systematic review and meta-analysis assessing whether attention-deficit/hyperactivity disorder (ADHD) is associated with disorders of the eye, and/or altered measures of visual function.MethodBased on a pre-registered protocol (PROSPERO: CRD42021256352), we searched PubMed, Web of Knowledge/Science, Ovid Medline, Embase and APA PsycINFO up to 16th November 2021, with no language/type of document restrictions. We included observational studies reporting at least one measure of vision in people of any age meeting DSM/ICD criteria for ADHD and in people without ADHD; or the prevalence of ADHD in people with and without vision disorders. Study quality was assessed with the Appraisal tool for Cross-Sectional Studies (AXIS). Random effects meta-analyses were used for data synthesis.ResultsWe included 42 studies in the narrative synthesis and 35 studies in the meta-analyses (3,250,905 participants). We found meta-analytic evidence of increased risk of astigmatism (OR = 1.79 [CI: 1.50, 2.14]), hyperopia and hypermetropia (OR = 1.79 [CI: 1.66, 1.94]), strabismus (OR = 1.93 [CI: 1.75, 2.12]), unspecified vision problems (OR = 1.94 [CI: 1.38, 2.73]) and reduced near point of convergence (OR = 5.02 [CI: 1.78, 14.11]); increased lag (Hedge's g = 0.63 [CI: 0.30, 0.96]) and variability (Hedge's g = 0.40 [CI: 0.17, 0.64]) of the accommodative response; and increased self-reported vision problems (Hedge's g = 0.63 [CI: 0.44, 0.82]) in people with ADHD compared to those without ADHD (with no significant heterogeneity). We also found meta-analytic evidence of no differences between people with and without ADHD on retinal nerve fiber layer thickness (Hedge's g = -0.19 [CI: -0.41, 0.02]) and refractive error (Hedge's g = 0.08 [CI: -0.26, 0.42]) (with no significant heterogeneity).DiscussionADHD is associated with some self-reported and objectively ascertained functional vision problems, but not with structural alterations of the eye. Further studies should clarify the causal relationship, if any, between ADHD and problems of vision.Trial registrationPROSPERO registration: CRD42021256352.

Dataset Information

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

Objective

Methods

Result

Conclusion

Publications

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

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