•  
  •  
 

Abstract

Background. Computer Vision Syndrome (CVS) is one of the emerging diseases in the 21st century because of advanced technology with the global prevalence around 60 million from various population characteristics and could cause an economic burden equivalent to 192 trillion rupiah. To determine the relationship of individual, environmental, and computer factors as well as the dominant risk factor with the occurrence of CVS in the Central Jakarta Metropolitan Police Officers in 2020. Methods. This study uses a cross-sectional study approach with sample of 92 police officers who are serving at the headquarters. Data were collected through questionnaire and direct environmental measurements using lux meter and RH Index along June 2020. Descriptive statistics (chi square) and binary logistic regression were carried out to compute frequencies, proportion, relevant associations and dominant risk factors. Results. There was no significant relationship on all variables from individual, environment, and computer factors with the occurrence of CVS. Nevertheless, there are four variables that are risk factors for CVS such as refractive errors (OR=1.65), smoking behavior (OR=1.89), humidity (OR=2.50), and computer monitor type (OR=1.11). Multivariate analysis showed that humidity had a significant relationship with CVS (p=0,04) and is the dominant risk factor (OR=2.50). Conclusions. There are four risk factors that can cause CVS occurrence in the police officers at the Central Jakarta Metropolitan Police Headquarters.

References

  1. Kominfo. Survey Penggunaan TIK Serta Implikasinya Terhadap Sosial Budaya Masyarakat. Badan Penelit dan Pengemb Sumber Daya Mns 2017;1–30.
  2. BPS. Statisik Telekomunikasi Indonesia tahun 2018. 2018
  3. Ali KM, Sathiyasekaran BWC. Computer professionals and carpal tunnel syndrome (cts). Int J Occup Saf Ergon 2006;12(3):319–25.
  4. Shu Q, Tu Q, Wang K. The impact of computer self-efficacy and technology dependence on computer-related technostress: A social cognitive theory perspective. Int J Hum Comput Interact 2011;27(10):923–39.
  5. Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults - A prospective cohort study. BMC Public Health 2011;11.
  6. Dessie A, Adane F, Nega A, Wami SD, Chercos DH. Computer vision syndrome and associated factors among computer users in Debre Tabor town, Northwest Ethiopia. J Environ Public Health 2018;2018.
  7. Loh KY, Reddy SC. Understanding and preventing computer vision syndrome. Malaysian Fam Physician 2008;3(3):128–30.
  8. Sen A, Richardson S. A study of computer-related upper limb discomfort and computer vision syndrome. J Hum Ergol (Tokyo) 2007;36 (2):45–50.
  9. Rahmayanti NM. Universitas indonesia hubungan karakteristik individu, lingkungan kerja, dan karakteristik komputer dengan kejadian. 2015;Available from: http://lib.ui.ac.id/file?file=digital/2016-2/20411999-S59862-NurulMaretia R.pdf
  10. Vilela MAP, Pellanda LC, Fassa AG, Castagno VD. Prevalence of asthenopia in children: A systematic review with meta-analysis. J Pediatr (Rio J) [Internet] 2015;91(4):320–5. Available from: http://dx.doi.org/10.1016/j.jped.2014.10.008
  11. Ranasinghe P, Wathurapatha WS, Perera YS, Lamabadusuriya DA, Kulatunga S, Jayawardana N, et al. Computer vision syndrome among computer office workers in a developing country: An evaluation of prevalence and risk factors. BMC Res Notes 2016;9(1):1–9.
  12. Ha A, Kim YK, Park YJ, Jeoung JW, Park KH. Intraocular pressure change during reading or writing on smartphone. PLoS One 2018;13(10):1 –12.
  13. Afifah A. Analisis Faktor Risiko Keluhan Subjektif Computer Vision Syndrome pada Pegawai Bank Negara Indonesia Cabang Universitas Indonesia, Direktorat Kemahasiswaan, dan Pengembangan & Pelayanan Sistem Informasi Universitas Indonesia. 2014;1–17.
  14. Prasad MA. Study of Prevalence of Health Problems Among Computer Professionals in Selected Information Technology (IT) Company In Nagpur District of Central India. Innov J Med Heal Sci 2014;4(3):96–8.
  15. Wittenborn JS, Zhang X, Feagan CW, Crouse WL, Shrestha S, Kemper AR, et al. The economic burden of vision loss and eye disorders among the united states population younger than 40 years. Ophthalmology [Internet] 2013;120 (9):1728–35. Available from: http://dx.doi.org/10.1016/j.ophtha.2013.01.068
  16. Daum KM, Clore KA, Simms SS, Vesely JW, Wilczek DD, Spittle BM, et al. Productivity associated with visual status of computer users. Optometry 2004;75(1):33–47.
  17. Rosenfield M. Computer vision syndrome: A review of ocular causes and potential treatments. Ophthalmic Physiol Opt 2011;31(5):502–15.
  18. Akinbinu TR, Mashalla YJ. Medical Practice and Review Impact of computer technology on health : Computer Vision Syndrome ( CVS ). Acad Journals 2014;5(November):20–30.
  19. Gowrisankaran S, Sheedy JE. Computer vision syndrome: A review. Work 2015;52(2):303–14.
  20. C RS, Jailkhani S. Prevalence and Associated Risk Factor of Computer Vision Syndrome among the Computer Science Students of an Engineering College of Bengaluru-A Cross-Sectional Study. Galore Int J Heal Sci Res [Internet] 2019;4(3):10–5. Available from: www.gijhsr.com
  21. Hyon JY, Yang HK, Han SB. Association between Dry Eye Disease and Psychological Stress among Paramedical Workers in Korea. Sci Rep [Internet] 2019;9(1):1–6. Available from: http://dx.doi.org/10.1038/s41598-019-40539-0
  22. Sa EC, Ferreira Junior M, Rocha LE. Risk factors for computer visual syndrome (CVS) among operators of two call centers in São Paulo, Brazil. Work 2012;41(SUPPL.1):3568–74.
  23. Anggrainy P, Ashar T, Lubis RR. Difference in Computer Vision Syndrome between Laptop and Desktop Computer Users. Indones J Med 2018;3 (2):65–70.
  24. POLRI. Tentang POLRI [Internet]. 2020;Available from: https://www.polri.go.id/tentang-visimisi
  25. AOA. The Effects of Computer Use on Eye Health and Vision. Am Optom Assoc [Internet] 1997;(314):1–9. Available from: http://www.aoa.org/Documents/optometrists/effects-of-computer-use.pdf
  26. Gangamma M, Poonam, Rajagopala M. A clinical study on “Computer vision syndrome” and its management with Triphala eye drops and Saptamrita Lauha. AYU (An Int Q J Res Ayurveda) 2010;31(2):236.
  27. Hastono SP. Analisa Data Bidang Kesehatan. 2006;1–212.
  28. Chader GJ, Taylor A. Preface: The aging eye: Normal changes, age-related diseases, and sight -saving approaches. Investig Ophthalmol Vis Sci 2013;54(14):2–5.
  29. Esenwah EC. The Aging Eye and Vision : A Review. Int J Heal Sci Res 2014;(June 2014).
  30. Martini FH, Nath JL, Bartholomew EF. Fundamentals of Anatomy & Physiology. 9th ed. San Fransisco: Pearson Education; 2012.
  31. Anshel J. Visual Ergonomics Handbook [Internet]. Boca Raton: CRC Press; 2005. Available from: 9780367392611
  32. Chawla A, Lim TC, Shikhare SN, Munk PL, Peh WCG. Computer Vision Syndrome: Darkness Under the Shadow of Light. Can Assoc Radiol J 2019;70:5–9.
  33. Mork R, Falkenberg HK, Fostervold KI, Thorud HMS. Visual and psychological stress during computer work in healthy, young females— physiological responses. Int Arch Occup Environ Health [Internet] 2018;91(7):811–30. Available from: http://dx.doi.org/10.1007/s00420-018-1324- 5
  34. Ostrovsky A, Ribak J, Pereg A, Gaton D. Effects of job-related stress and burnout on asthenopia among high-tech workers. Ergonomics 2012;55 (8):854–62.
  35. Shih YN, Huang RH, Lu SF. The influence of computer screen polarity and color on the accuracy of workers’ reading of graphics. Work 2013;45(3):335–42.

Bahasa Abstract

Pendahuluan. Computer Vision Syndrome (CVS) merupakan penyakit yang muncul sejak perkembangan teknologi diabad ke-21 dengan tingkat prevalensi kejadian secara global sebesar 60 juta dan kerugian Rp192 trilliun setiap tahunnya. Mengetahui hubungan faktor individu, lingkungan dan komputer serta faktor risiko dominan dengan kejadian CVS pada staf POLRES Metro Jakarta Pusat tahun 2020. Metode. Penelitian ini menggunakan pendekatan studi potong lintang dengan jumlah sampel 92 staf kepolisian yang bertugas di markas besar POLRES Metro Jakarta Pusat dan waktu penelitian pada bulan Juni 2020. Pengumpulan data dilakukan dengan instrumen kuesioner dan pengukuran lingkungan langsung menggunakan lux meter dan RH index. Analisis deskriptif dengan melihat frekuensi serta proporsi, uji kai kuadrat memunculkan nilai odd ratio dan uji regresi logistik ganda. Hasil. Hasil penelitian menunjukan tidak ada hubungan yang signifikan pada semua variabel dari faktor individu, lingkungan dan komputer dengan kejadian CVS. Walaupun begitu, terdapat empat variabel yang menjadi faktor risiko dengan kejadian CVS diantaranya kelainan refraksi (OR=1,65), perilaku merokok (OR=1,89), kelembaban (OR=2,50) dan jenis monitor (OR=1,11). Analisis multivariat menunjukan kelembaban ruang kerja memiliki hubungan yang signifikan dengan kejadian CVS (p=0,04) dan merupakan faktor risiko dominan (OR=2,50). Kesimpulan. Terdapat empat faktor risiko yang dapat menyebabkan kejadian CVS pada staf POLRES Metro Jakarta Pusat.

Download

Share

COinS