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Self-Reported Computer Vision Syndrome among Thai University Students in Virtual Classrooms during the COVID-19 Pandemic: Prevalence and Associated Factors.

Kampanat WangsanPhit UpaphongPheerasak AssavanopakunBianca BrijnathWachiranun SirikulAmornphat KitroNaphasorn SirimaharajSawita KuanprasertManeekarn SaenpoSuchada SaetiaoThitichaya Khamphichai
Published in: International journal of environmental research and public health (2022)
During the COVID-19 pandemic, computer vision syndrome (CVS) related to online classrooms were unavoidable. This cross-sectional study aimed to explore the prevalence, characteristics and associated factors of CVS. A total of 527 students who were currently studying in a virtual classroom (70.40% female, mean (standard deviation; SD) age of 20.04 (2.17) years) were included. The prevalence of CVS assessed by an online CVS-Questionnaire was 81.0% (427/527). Comparing with those in the period before the online study, an increase in screen time (interquartile range) in students with and without CVS was 3 (0-3) and 2 (1-5) h, respectively. Overall, 516 students (97.9%) experienced at least one symptom. The most frequent symptom in CVS subjects was eye pain (96.5%). The most intense symptoms were the feeling of worsening eyesight (15.9%). The factors associated with CVS were female ( p < 0.001), age ( p = 0.010), atopic diseases ( p = 0.020), prior ocular symptoms ( p < 0.001), astigmatism ( p = 0.033), distance from display <20 cm ( p = 0.023), presence of glare or reflection on screen ( p < 0.001), low screen brightness ( p = 0.045), sleep duration ( p = 0.030), inadequate break time between classes ( p < 0.001) and increased screen time usage during online study ( p < 0.001). Recommendations to prevent CVS based on the adjustable factors might reduce the burden of online study.
Keyphrases
  • high throughput
  • social media
  • risk factors
  • health information
  • healthcare
  • deep learning
  • depressive symptoms
  • case report
  • machine learning
  • physical activity
  • sleep quality
  • psychometric properties
  • patient reported