Effectiveness of the 20-20-20 Algorithm in Reducing the Risk of Computer Vision Syndrome (CVS) Among Military Medical Cadets at the Republic of Indonesia Defense University
DOI:
https://doi.org/10.47353/ajmpm.v2i2.27Keywords:
.Keywords: Computer Vision Syndrome; 20-20-20 algorithm; military medical student; eye healthAbstract
Background: The digital era has changed many aspects of life, especially in education and professional fields, with increased reliance on computers and visual display terminals 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 eye strain and visual discomfort. 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 recommended: taking a 20-second break every 20 minutes to look at an object 20 feet away. This study aimed to evaluate the effectiveness of the 20-20-20 algorithm among medical students at the Republic of Indonesia Defense University.
Methods: This study used a one-group pretest-posttest design. A total of 77 cadets from the
Military Medicine Study Program participated. Respondents underwent CVS symptom measurement before the
intervention, applied the 20-20-20 algorithm for two weeks, and repeated symptom measurement after the intervention. Data were analyzed using the McNemar test.
Results: There was a significant change in CVS symptoms after implementation of the 20-20-20 algorithm. Of 77 respondents, 34 respondents did not experience CVS symptoms at pretest and remained asymptomatic at posttest. A total of 25 respondents who previously experienced CVS symptoms no longer experienced CVS after intervention. Statistical analysis showed a p-value of 0.000, indicating a significant difference before and after intervention.
Conclusion: The 20-20-20 algorithm was effective in reducing the risk of CVS among military medical students. With p < 0.05, this algorithm can be considered an effective, simple, and practical solution for computer users at risk of CVS
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Copyright (c) 2025 Muhammad Daffa Akbar Prasetyo, Nirawan Putranto, Satria Pratama, Elies Fitriani
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