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Background: Computer vision syndrome (CVS), also known as digital eye strain, is a growing visual health concern resulting from prolonged exposure to digital screens, including computers, laptops, tablets, and mobile phones. The condition manifests as a cluster of ocular and visual symptoms that impair productivity, comfort, and overall visual performance. With increasing digital dependency across all age groups, preventive and corrective strategies have become essential to mitigate the burden of CVS in routine screen users. Objective: To evaluate and compare the effectiveness of Eyeblink software and the 20-20-20 rule in reducing symptoms of computer vision syndrome among young computer users. Methods: A quasi-experimental study was conducted at The University of Faisalabad, with participants recruited from the University of Engineering and Technology Lahore. A total of 50 individuals aged 15–30 years with mild to moderate CVS (scores 6–18) were enrolled. Following informed consent, participants were divided into two equal groups. Group 1 received verbal instructions on the 20-20-20 rule, whereas Group 2 installed Eyeblink software and received training for its use. The validated CVS questionnaire was administered at baseline and at two follow-up visits, each spaced 15 days apart. Data were analyzed using IBM SPSS version 25 to compare changes within and between groups. Results: At baseline, 37 participants (74%) exhibited mild CVS and 13 (26%) had moderate CVS. At the first follow-up, no participants remained in the moderate category, with 31 (62%) showing mild and 19 (38%) showing no CVS. At the second follow-up, 19 participants (38%) had mild CVS, whereas 31 (62%) demonstrated complete improvement. Significant between-group differences were found at both follow-ups (p = 0.043 and p = 0.000), with Eyeblink software showing superior effectiveness compared with the 20-20-20 rule. Conclusion: Both interventions decreased CVS symptoms; however, Eyeblink software demonstrated a more substantial and consistent reduction, highlighting its usefulness as a digital tool for managing computer vision syndrome.
Published in: Insights-Journal of Health and Rehabilitation
Volume 3, Issue 10, pp. 193-200
DOI: 10.71000/tev3sx39