The Effectiveness of the 20-20-20 Algorithm in Reducing the Risk of Computer Vision Syndrome (CVS) Among Millitary Medical Cadets at the Republic of Indonesia Defense University
Keywords:
Computer Vision Syndrome (CVS), 20-20-20 algorithm, Military Medical Student, Eye HealthAbstract
Background: The digital era has changed many aspects of life, especially in education and the professional field, with increased reliance on computers and Visual Display Terminals (VDT) for work, communication, and learning. In academic environments, particularly among medical students, computers are essential for accessing information and completing assignments. However, excessive screen use can cause health risks, especially eye strain and visual discomfort. Medical students often engage in long study sessions and rely on digital resources, but constant exposure without adequate breaks can result in fatigue, decreased concentration, and vision problems. One common condition associated with prolonged screen time is Computer Vision Syndrome (CVS). To reduce the risk of CVS, the 20-20-20 algorithm is highly recommended, which involves taking a 20-second break every 20 minutes to look at an object 20 feet away. This study aims to evaluate the effectiveness of the 20-20-20 algorithm among medical students at the Republic of Indonesia Defense University and to determine whether its implementation significantly reduces the risk of CVS, as well as increasing awareness about digital eye strain and providing recommendations for students, educators, and institutional policymakers.
Methods: The method used in this research is a true experimental design with a one group pretest-posttest approach. A total of 77 cadets from the Military Medicine Study Program participated in this research. They underwent CVS symptom measurements before the intervention, followed by the application of the 20-20-20 algorithm for two weeks, and then repeated symptom measurements after the intervention. The collected data was analyzed using the McNemar test to determine the effectiveness of the algorithm in reducing CVS symptoms.
Results: There was a significant change in CVS symptoms after implementing the 20-20-20 algorithm. Of the 77 respondents, 34 respondents did not experience CVS symptoms at the pretest and still did not experience symptoms at the posttest. A total of 25 respondents who previously experienced CVS symptoms managed to overcome this condition after intervention. Statistical analysis showed a p-value of 0.000, which indicated a significant difference between CVS symptoms before and after intervention.
Conclusion: The 20-20-20 algorithm was shown to be effective in reducing the risk of Computer Vision Syndrome (CVS) among military medical students. With a p-value < 0.05, these results indicate that this algorithm can be an effective solution for computer users who have the potential to experience CVS.
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Copyright (c) 2025 Muhammad Daffa Akbar Prasetyo, Nirawan Putranto, Satria Pratama, Elies Fitriani (Author)
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