Evidence map›Paper›PMID 42433873›Full record

ArticleAnnals of medicine and surgery (2012)2026

Addressing workplace practices: combating the rising prevalence of computer vision syndrome.

Syed Shahmeer Ahmed, Shakeeba Zubair, Nadia Mehmood, Muhammad Tauseef Haider Malik, Abedin Samadi

Abstract readLetter
In one paragraph

Article in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Syed Shahmeer AhmedDepartment of Medicine, Karachi Medical & Dental College, Karachi, Pakistan.
Shakeeba ZubairDepartment of Medicine, PNS Shifa Hospital, Karachi, Pakistan.
Nadia MehmoodDepartment of Medicine, Aga Khan University Hospital, Karachi, Pakistan.
Muhammad Tauseef Haider MalikDepartment of Medicine, Dow University of Health Sciences, Karachi, Pakistan.
Abedin SamadiDepartment of Medicine, Kabul University of Medical Sciences Abu Ali Sina, Kabul, Afghanistan.ORCID https://orcid.org/0009-0007-8614-3924

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computer vision syndrome (CVS) is an increasingly prevalent occupational health concern associated with prolonged use of digital devices, affecting millions worldwide. Characterized by symptoms such as eyestrain, dryness, blurred vision, redness, and headaches, CVS significantly affects productivity and quality of life. This review highlights the growing burden, risk factors, pathophysiology, and preventive strategies related to CVS. Key contributing factors include extended screen time, poor ergonomics, reduced blink rate, improper screen positioning, and lack of regular breaks. Dry eye disease plays a central role in its pathogenesis due to increased corneal exposure and decreased tear film stability. Preventive strategies, particularly the 20-20-20 rule, have shown effectiveness in reducing symptoms and improving ocular surface health. Ergonomic modifications, such as positioning screens below eye level and maintaining proper posture, further help in minimizing discomfort. Despite its high prevalence, awareness regarding CVS remains inadequate among both employees and employers, leading to underutilization of preventive measures. Implementation of workplace policies, regular awareness sessions, and adherence to evidence-based ergonomic practices are essential to mitigate the rising burden of CVS. Addressing these factors is crucial to promote ocular health and ensure a safer, more productive working environment in the digital age.

Indexed as

20-20-20 rulecomputer vision syndromedigital eye straindry eye diseaseergonomics

Identifiers

PMID42433873
PMCPMC13354463

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.