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Assessment of Computer Vision Syndrome and Personal Risk Factors among Employees of Commercial Bank of Ethiopia in Addis Ababa, Ethiopia.

Haile DerbewAnsha Nega AhmedWorku TeferaTekie ZafuKenfe TsehayeKebede HaileBelsity Temesgen
Published in: Journal of environmental and public health (2021)
The prevalence of computer vision syndrome in the last 12 months among the total study subjects, 359 (98% response rate), was 262 (74.6%) (95% confidence interval [CI] = 70.1, 79.5). Risk factors that could not be intervened with were sex (AOR: 1.8; 95% CI (1-3)) and age group (AOR: 3.11; 95% CI (1.2-8)). Causal factors that could be intervened with were use of electronic materials outside work (AOR: 3.11; 95% CI (1.15-8.36). Protective factor that could be intervened with was habit of taking a break (AOR: 0.44; 95% CI (0.3-0.8)). Conclusion and Recommendation. Three-fours of the employees were at risk. Sex, age, habit of taking a break, and use of electronic materials outside work environment were significantly associated with the presence of CVS. Remedial actions need to be considered at individual level.
Keyphrases
  • risk factors
  • deep learning
  • case report
  • machine learning
  • clinical evaluation