ArticleCureus2024
The Prevalence and Severity of Computer Vision Syndrome Among Primary Care Health Workers in the Ministry of National Guard Health Affairs, Central Region, Saudi Arabia.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Article
- Exploratory machine learning models for computer vision syndrome in occupational health.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Computer vision syndrome (CVS) is a common condition affecting individuals who spend prolonged periods using electronic devices. It is characterized by symptoms such as eye strain, dryness, headaches, and neck pain. This study aims to assess the prevalence of CVS symptoms among healthcare professionals, their awareness of the condition, and the effectiveness of various preventative practices. Methodology A cross-sectional survey was conducted among 233 healthcare professionals, including physicians, nurses, pharmacists, lab technicians, and non-medical staff. Participants were asked about their demographic characteristics, awareness of CVS, device usage patterns, and preventative practices. The prevalence of CVS symptoms and their association with demographic factors and preventative measures were analyzed using chi-square tests. Results The average age of participants was 37 years, with 94 male (40.3%) and 139 female (59.7%). A significant majority, 192 (82.2%), of the participants had not heard of CVS, and 174 (74.8%) were unsure if it was a permanent condition. The most commonly used devices were mobile phones (199, 85.5%), followed by computers/laptops/iPads (117, 50.2%). Common CVS symptoms included neck or shoulder pain (171, 73.4%), headaches (162, 69.5%), and eye dryness (149, 64.0%). Significant associations were found between wearing glasses or contact lenses and a higher prevalence of symptoms (p = 0.042). Taking breaks while using devices was significantly associated with fewer symptoms (p = 0.050). Although adjusting device brightness and using anti-glare filters approached significance, they were not statistically significant. Conclusion The study highlights a considerable lack of awareness about CVS among healthcare professionals and a high prevalence of symptoms. Preventative practices, particularly taking breaks, are crucial in reducing CVS symptoms. Educational initiatives to raise awareness and promote healthier visual habits are needed to mitigate the impact of CVS. Addressing these issues can enhance the well-being and productivity of healthcare professionals in digital environments.
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Registered trials
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.