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Study of computer vision syndrome among medical undergraduates of Kumaon region, Uttarakhand
Asian Journal of Medical Sciences ; 13(12):169-173, 2022.
Article in English | Academic Search Complete | ID: covidwho-2198403
ABSTRACT

Background:

Activity on digital screen has increased so much during the COVID era that there is surge in persons complaining of symptoms of computer vision syndrome (CVS). Aims and

Objectives:

The aim of the study was to determine the prevalence of CVS among the medical students and its associated factors during COVID period and to compare it with pre-COVID period. Materials and

Methods:

A cross-sectional study was conducted among 337 undergraduate medical students at Government Medical College, Haldwani, Uttarakhand using pretested structured questionnaire which was filled through Google form for which link was circulated in class WhatsApp group. Data were analyzed using SPSS version 16. Frequency, percentage, binary logistic regression, and McNemar test was applied. P<0.05 was considered significant.

Results:

The prevalence of CVS was significantly higher during COVID period, 54.9% (95% CI=49.7–60.1) that was significantly higher than non-COVID period. Eye strain (16.6%) was the most common CVS symptom during both pre-COVID and COVID period. The prevalence of CVS was significantly associated with use of preventive measures. During COVID period, average hours spent in digital screen was significantly higher as compared to non-COVID period.

Conclusion:

This study showed that there was increase in CVS among the study participants during COVID era as there was increase in spending hours on digital screen and not or reduction in adopting preventive measures. It is important to increase awareness regarding the symptoms and precautions related to CVS. [ FROM AUTHOR]
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Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Language: English Journal: Asian Journal of Medical Sciences Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Academic Search Complete Language: English Journal: Asian Journal of Medical Sciences Year: 2022 Document Type: Article