Effect of Digital Device on Computer Vision Syndrome: Meta-Analysis
DOI:
https://doi.org/10.26911/jepublichealth.2023.08.02.03Abstract
Background: Computers are an integral part of today's modern human life, where long-term use can cause complaints of visual disturbances. Eye complaints related to computer use are called computer vision syndrome. This study aims to determine the magnitude of the influence of the use of digital screens or devices on the occurrence of computer vision syndrome with meta-analysis.
Subjects and Method: The meta-analysis was carried out using the PRISMA flowchart and the PICO Population: students model. Intervention: the duration of using the digital screen is long. Comparison: the duration of using the digital screen is short. Outcome: the incidence of computer vision syndrome. The databases used are PubMed, ScienceDirect, Web of Science, Cochrane library, Google Scholar and CINAHL with keywords (Computers OR Handheld OR Mobile Devices OR “Digital Device” OR Digital Screen) AND (Asthenopia OR “Computer Vision Syndrome” OR Eye Strain OR Digital Eye Strain) AND (“Students” OR School Children OR Secondary Children OR Postgraduate Students). The inclusion criteria in this study were full text articles with a cross-sectional design for 2018 to 2022 in English. The article was then critically reviewed using the Prisma flow chart diagram and analyzed with RevMan 5.3.
Results: Meta-analysis was conducted on 9 articles with a cross-sectional study design originating from Ghana, Saudi Arabia, Ethiopia, Spain, Thailand, Lebanon and China involving 28,888 students. The results of the meta-analysis show that the long duration of digital device use increases the risk of experiencing CVS by 2.31 times compared to the short duration of digital device use (aOR= 2.31; 95% CI= 1.60 to 3.32; p<0.001).
Conclusion: The duration of using digital devices has a higher risk of experiencing Computer Vision Syndrome.
Keywords: Student, Digital Device, Computer Vision Syndrome, Meta-Analysis
Correspondence: Asri Wahyu Azzahro. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java, Indonesia. Email: asriwahyuazzahro@gmail.com. Mobile: +6281328543318.
References
Akowuah PK, Nti AN, Ankamah LS, Frimpong AA, Fummey J, Boadi P, Osei Poku K, et al. (2021). Digital device Use, Computer Vision Syndrome, and Sleep Quality among an African Undergraduate Population. Adv Public Health. doi: 10.1155/2021/6611348.
Aldukhayel A, Baqar SM, Almeathem FK, Alsultan FS, AlHarbi GA. (2022). Digital Eye Strain Caused by Online Education Among Children in Qassim Region, Saudi Arabia: A Cross-Sectional Study. Cureus. 14(4). doi: 10.7759/cureus.23813.
Aldy F, Rina RS. (2021). Hubungan Perilaku Dan Durasi Penggunaan Komputer Dengan Keluhan Computer Vision Syndrome (CVS) pada Mahasiswa STIKes Flora (Correlation between Behavior and Duration of Computer Use with Complaints of Computer Vision Syndrome (CVS) in STIKes Flora Students). Ejournal STIKes Flora. 14(2): 120–129.
AOA (2020). Computer vision syndrome. American Ophtometric Association. 9(28): 1.
Bali J, Neeraj N, Bali RT. (2014). Computer Vision Syndrome: A Review. Clin Ophthalmol. 2: 61-68.
Belay S, Alemayehu AM, Hussen MS. (2019). Prevalence of Computer Vision Syndrome and Associated Factors among Postgraduate Students at University of Gondar, Northwest Ethiopia. Indian J Clin Exp Ophthalmol. 11(4): 1–5. doi: 10.35248/21559570.20.11.849.
Cantó SN, Sánchez BM, Ivorra SB, Seguí CM. (2021). Computer vision syndrome prevalence according to individual and video display terminal exposure characteristics in Spanish university students. Int J Clin Pract. 75(3): 1–8. doi: 10.1111/ijcp.13681.
Ciputra F, Dwipayani NM. (2022). Computer Vision Syndrome: Sebuah Tinjauan Pustaka (Computer Vision Syndrome: A Literature Review). 5(1): 49–59.
Lavin W, Taptagaporn S, Khruakhorn S, Kanchanaranya N (2018). Prevalence and Associated Risk Factors of Digital Eye Strain among Children in Secondary Schools in Pathumthani Province, Thailand. J Med Assoc Thai. 101: 957-63.
Li L, Jing C, Moxin L, Xue C, Qiao J, Run L, Zhihao Z, et al. (2021). Contribution of Total Screen/Online-Course Time to Asthenopia in Children During COVID-19 Pandemic via Influencing Psychological Stress. Public Health Front. 9(12): 1–11. doi: 10.3389/fpubh.2021.736617.
Li R, Ying B, Qian Y, Chen D, Li X, Zhu H, Liu H (2022). Prevalence of Self-Re-ported Symptoms of Computer Vision Syndrome and Associated Risk Factors among School Students in China during the COVID-19 Pandemic. Ophthalmic Epidemiol. 29(4): 363–373. doi:10.1080/09286586.2021.1963786
Lumolos MP, Polii H, Marunduh SR. (2016). Pengaruh lama paparan dan masa kerja terhadap visus pada pekerja rental komputer di Kecamatan Sario dan Malalayang Kota Manado. e-Biomedik. 4(2): 1–5. doi: 10.35790/ebm.4.2.2016.14613.
Nadhiva RF, Mulyono M. (2020). The Relation between Symptoms of Computer Vision Syndrome and Visual Display Terminal Utilization. IJOSH. 9(3): 328–337. doi: 10.20473/ijosh.v9i3.2020.328-337.
Pratiwi AD, Safitri A, Lisnawaty J. (2020). Faktor yang Berhubungan dengan Kejadian Computer Vision Syndrome (CVS) pada Pegawai PT. Media Kita Sejahtera Kendari. J Fak Kesehat Masy. 7(1): 41–47.
Rahman Z, Sanip S. (2011). Computer Vision Syndrome: The Association with Ergonomic Factors. J. Epidemiol. 65: 2-493. doi: 10.1136/jech.2011.142-976m.20.
