•  
  •  
 

Abstract

Due to the Covid-19 pandemic, many activities that were previously carried out offline have turned into online, including the education sector. This condition increased the use duration of electronic devices with digital screens/VDT, especially among students. It is one of the risk factors for Computer Vision Syndrome. Apart from duration, several risk factors are also associated with Computer Vision Syndrome. The aims of this study are to see an overview of Computer Vision Syndrome incidence and analyze the relationship between Computer Vision Syndrome incidence and its risk factors in regular (S1) and postgraduate (S2) students, FKM UI during the Covid-19 pandemic. This research was conducted in March-June 2022 using the CVS-Q questionnaire and several short questions related to risk factors distributed online. The study design used in this study was cross-sectional and involved 250 respondents from regular undergraduate and postgraduate students of FKM UI. The results of this study indicate that there are 6 variables that have a significant relationship, namely age (P 0.000), duration of use of digital screens/VDT (P=0.006), rest pattern (P=0.007), eye refraction abnormalities (P=0.014), use of antiglare (P=0.011), and Screen brightness (P=0.030). Therefore, further controls and interventions are needed so that these problems can be overcome.

References

ANSHEL, J. (2005) Visual Ergonomics Handbook. CRC Press. Available at: https://doi.org/https://doi.org/10.1201/9781420032055.

ANSHEL, J. (2006) Optometric Management - CVS: Constructing a New Approach to Visual Ergonomics. Available at: https://www.optometricmanagement.com/issues/2006/september-2006/cvs-constructing-a-new-approach-to-visual-ergonom (Accessed: March 28, 2022).

Arif, K.M. and Alam, M.J. (2015) “Computer Vision Syndrome,” Faridpur Medical College Journal, 10(1), pp. 33–35. Available at: https://doi.org/10.3329/FMCJ.V10I1.27923.

Assefa, N.L. et al. (2017) “Prevalence and associated factors of computer vision syndrome among bank workers in Gondar City, northwest Ethiopia, 2015,” Clinical optometry, 9, pp. 67–76. Available at: https://doi.org/10.2147/OPTO.S126366.

Blehm, C. et al. (2005) “Computer vision syndrome: a review,” Survey of ophthalmology, 50(3), pp. 253–262. Available at: https://doi.org/10.1016/J.SURVOPHTHAL.2005.02.008.

Cantó-Sancho, N. et al. (2020) “Computer vision syndrome prevalence according to individual and video display terminal exposure characteristics in Spanish university students,” International Journal of Clinical Practice, 75(3), pp. 1–8. Available at: https://doi.org/10.1111/ijcp.13681.

Computer vision syndrome | AOA (2022). Available at: https://www.aoa.org/healthy-eyes/eye-and-vision-conditions/computer-vision-syndrome?sso=y (Accessed: March 13, 2022).

Gowrisankaran, S. and Sheedy, J.E. (2015) “Computer vision syndrome: A review,” Work (Reading, Mass.), 52(2), pp. 303–314. Available at: https://doi.org/10.3233/WOR-152162.

Li, R. et al. (2021) “Prevalence of Self-Reported Symptoms of Computer Vision Syndrome and Associated Risk Factors among School Students in China during the COVID-19 Pandemic,” Ophthalmic Epidemiology, 00(00), pp. 1–11. Available at: https://doi.org/10.1080/09286586.2021.1963786.

Loh, K.Y. and Reddy, S.C. (2008) “Understanding and Preventing Computer Vision Syndrome,” Malaysian Family Physician : the Official Journal of the Academy of Family Physicians of Malaysia, 3(3), p. 128. Available at: https://pmc/articles/PMC4170366/ (Accessed: March 16, 2022).

Mowatt, L. et al. (2018) “Computer vision syndrome and ergonomic practices among undergraduate university students,” International Journal of Clinical Practice, 72(1). Available at: https://doi.org/10.1111/ijcp.13035.

Muchtar, H. and Sahara, N. (2016) “Hubungan Lama Penggunaan Laptop Dengan Timbulnya Keluhan Computer Vision Syndrome (Cvs) Pada Mahasiswa/I Fakultas Kedokteran Umum Universitas Malahayati,” Jurnal Medika Malahayati, 3(4), pp. 197–203.

Nadia, A.S., Paramita, A. and Rahman, A.O. (2021) “Hubungan Durasi Penggunaan Komputer Portabel Dengan Kejadian Computer Vision Syndrome Pada Mahasiswa Fakultas Kedokteran Dan Ilmu Kesehatan Universitas Jambi Tahun 2020,” Medical Dedication (medic) : Jurnal Pengabdian kepada Masyarakat FKIK UNJA, 4(1), pp. 179–184. Available at: https://doi.org/10.22437/MEDICALDEDICATION.V4I1.13480.

R, A.T. and J, M.Y. (2014) “Impact of computer technology on health: Computer Vision Syndrome (CVS),” Medical Practice and Reviews, 5(3), pp. 20–30. Available at: https://doi.org/10.5897/MPR.2014.0121.

Rahman, Z.A. and Sanip, S. (2011) “Computer User: Demographic and Computer Related Factors that Predispose User to Get Computer Vision Syndrome,” International Journal of Business, 1(2). Available at: www.ijbhtnet.com (Accessed: June 28, 2022).

Seguí, M.D.M. et al. (2015) “A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace,” Journal of clinical epidemiology, 68(6), pp. 662–673. Available at: https://doi.org/10.1016/J.JCLINEPI.2015.01.015.

Selvaraj, S., Ganesan, D.K. and Jain, T. (2021) “A study on single versus multiple symptoms of computer vision syndrome (CVS) among engineering students in Kancheepuram District, Tamil Nadu,” International Journal of Current Research and Review, 13(6), pp. 51–55. Available at: https://doi.org/10.31782/IJCRR.2021.13605.

Sen, A. and Richardson, S. (2006) “A study on computer related Upper Limb discomfort and computer vision syndrome in Malaysia,” Proceedings - Ergo Future 2006, International Symposium on Past, Present and Future Ergonomics, Occupational Safety and Health, pp. 327–331.

Shantakumari et al. (2014) “Computer use and vision-related problems among university students in ajman, United arab emirate,” Annals of medical and health sciences research, 4(2), p. 258. Available at: https://doi.org/10.4103/2141-9248.129058.

Wang, L., Wei, X. and Deng, Y. (2021) “Computer Vision Syndrome During SARS-CoV-2 Outbreak in University Students: A Comparison Between Online Courses and Classroom Lectures,” Frontiers in Public Health, 9(July), pp. 1–7. Available at: https://doi.org/10.3389/fpubh.2021.696036.

Yulita, R. (2016) Hubungan perilaku penggunaan komputer dengan kejadian sindrom penglihatan akibat komputer computer vision syndrome (CVS) pada mahasiswa FIKUI angkatan 2012-2015. Universitas Indonesia. Available at: http://digilib.ui.ac.id/detail?id=20429286 (Accessed: June 28, 2022)

Bahasa Abstract

Akibat adanya pandemi Covid-19, banyak kegiatan yang semula dilakukan secara offline, berubah menjadi daring, termasuk dalam sektor pendidikan. Hal ini mengakibatkan durasi penggunaan alat elektronik dengan layar digital/VDT meningkat, khususnya di kalangan mahasiswa. Durasi penggunaan layar digital/VDT ini merupakan salah satu faktor risiko dari Computer Vision Syndrome (CVS). Selain durasi, terdapat beberapa faktor risiko lain yang juga berhubungan dengan CVS. Tujuan dilakukannya penelitian ini adalah untuk melihat gambaran kejadian CVS dan faktor risikonya, serta menganalisis hubungan antara kejadian CVS dan faktor risikonya pada mahasiswa (S1 Reguler dan pascasarjana S2) FKM UI di masa pandemi Covid-19 tahun 2022. Penelitian ini dilakukan pada bulan Maret-Juni 2022 dengan menggunakan kuesioner CVS-Q dan beberapa pertanyaan singkat terkait faktor risiko yang disebar secara online. Desain studi yang digunakan pada penelitian ini adalah cross-sectional dan melibatkan 250 responden yang berasal dari mahasiswa S1 reguler dan pascasarjana S2 FKM UI. Hasil dari penelitian ini menunjukkan terdapat 6 variabel yang mempunyai hubungan yang signifikan, yaitu usia (P= 0,000), durasi penggunaan layar digital/VDT(P= 0,006), pola istirahat (P= 0,007), kelainan refraksi mata(P= 0,014), penggunaan antiglare (P= 0,011), dan screen brightness (P= 0,030). Oleh karena itu, dibutuhkan pengendalian dan intervensi lebih lanjut agar masalah tersebut dapat diatasi.

Kata Kunci: CVS, Computer Vision Syndrome, Mahasiswa, Laptop, Smartphones

Download

Share

COinS