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A cross sectional study to assess the prevalence and associated factors of computer vision syndrome among engineering students of Hyderabad, Telangana
Article | IMSEAR | ID: sea-201076
Background: Computer vision syndrome is a complex of eye and vision problems related to near work which are experienced due to prolonged computer use. Computers demand near work, for longer duration which increases discomfort of eye and prolonged exposure to the discomfort leads to a cascade of symptoms that can be referred as computer vision syndrome. The aims and objectives of the study were to determine the prevalence of computer vision syndrome among engineering students of Hyderabad, Telangana and to determine the factors related to computer vision syndrome among study population.Methods: A cross sectional study was carried out from March to June 2017 among students of an engineering college in Hyderabad, Telangana. A convenient sample of 300 students was taken and a predesigned, pre tested questionnaire was used to obtain information.Results: Majority of study population were males (56.3%). Around 75.1% of study population were using all the electronic gadgets like computers, laptops and smartphones. The prevalence of computer vision syndrome was found to be 60.3%. Around 46.7% of study population viewed the screen from a distance of 22-40 centimeters.Conclusions: As students pursuing engineering stream are the future IT and Computer software engineers, preventive strategies adopted by them will significantly decrease the burden of computer vision syndrome and improve productivity. In this study a significant proportion of the engineering students were found to be having vision problems, which emphasizes the need to adopt preventive measures to avoid computer vision syndrome
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Texto completo: 1 Índice: IMSEAR Tipo de estudio: Observational_studies / Prevalence_studies / Risk_factors_studies Año: 2019 Tipo del documento: Article
Texto completo: 1 Índice: IMSEAR Tipo de estudio: Observational_studies / Prevalence_studies / Risk_factors_studies Año: 2019 Tipo del documento: Article