Prevalence of Digital Eye Strain and Its Associated Factors Among Bankers
DOI:
https://doi.org/10.55735/a9nm9615Keywords:
Bankers, Computer vision syndrome, Digital eye strain, Occupational health concern, Screen timeAbstract
Background: Digital eye strain is a rising occupational health concern, especially among professionals with prolonged screen exposure. Bankers are particularly at risk due to constant use of computers and digital devices, leading to symptoms like eye fatigue, blurred vision, dryness, and headaches. Objective: To evaluate the prevalence of digital eye strain and its associated factors among bankers. Methodology: A cross-sectional study was conducted from March to August 2025 after obtaining ethical approval from the Department of Allied Health Sciences, University of Sialkot. About 278 bankers from various public and private banks in Sialkot, aged between 20 and 40 years, who used a computer for a minimum of three hours per day were included. Individuals were excluded if they had visual problems or injuries, systemic conditions, including collagen vascular or endocrine diseases, or a history of recent ophthalmic surgery within the past six months, ocular toxoplasmosis, lack of clear ocular media. Written informed consent was obtained from each participant before data collection. The CVS-Smart and CVS-Q questionnaires were administered under the researcher’s supervision to ensure completeness and clarity. Frequencies and percentages were calculated for demographic, symptoms, risk factors, and the computer vision syndrome group. Cross-tabulations were performed to find the association of the computer vision group with risk factors using the chi-square test. Results: Among 278 bankers (60.1% male; mean age 30.7±5.3 years), headache (10.1%), double vision (8.3%), and blurred vision (7.9%) were the most common digital eye strain symptoms. Nearly all (95.7%) used screens for over three hours daily, while 41% took regular breaks. Most (67.3%) used both desktop and mobile devices, but only 9.4% wore glasses. Ergonomic practices were followed by 45.3%, and 88.8% adjusted screen brightness. Awareness was low (25.9%), with a mean computer vision syndrome score of 4.83±2.27; 25.2% were computer vision syndrome-positive, and 33.8% had a high probability. Conclusion: This study found a high prevalence of digital eye strain among bankers in Sialkot, significantly associated with prolonged screen time, poor ergonomic practices, and limited awareness. To reduce its occurrence, preventive strategies such as promoting regular screen breaks, ergonomic setups, and conducting awareness programs are strongly recommended.
Downloads
References
1. Pucker AD, Kerr AM, Sanderson J, et al. Digital Eye Strain: updated perspectives. Clinical Optometry 2024; 16: 233–46.
https://doi.org/10.2147/OPTO.S412382
2. Abdulmannan DM, Naser AY, Ibrahim OK, et al. Visual health and prevalence of dry eye syndrome among university students in Iraq and Jordan. BMC Ophthalmology 2022; 22(1): 265.
https://doi.org/10.1186/s12886-022-02485-w
3. Auffret É, Gomart G, Bourcier T, et al. Digital eye strain. Symptoms, prevalence, pathophysiology, and management. Journal Francais D’Ophtalmologie 2021; 44(10): 1605–10.
https://doi.org/10.1016/j.jfo.2020.10.002
4. Khan S, Khan S, Midya MZ, et al. Comparison of prevalence data about digital eye strain (DES), pre-lockdown versus post-lockdown period in India: a systematic review study. International Journal of Research and Review 2021; 8(5): 59–68.
https://doi.org/10.52403/ijrr.20210509
5. Mohan A, Sen P, Shah C, et al. Prevalence and risk factor assessment of digital eye strain among children using online e-learning during the COVID-19 pandemic: Digital eye strain among kids (DESK study-1). Indian Journal of Ophthalmology 2021; 69(1): 140–44.
https://doi.org/10.4103/ijo.IJO_2535_20
6. Iqbal M, El-Massry A, Elagouz M, et al. Computer vision syndrome survey among the medical students in Sohag University Hospital, Egypt. Ophthalmology Research: An International Journal 2018; 8(1): 1–8.
https://doi.org/10.9734/OR/2018/38436
7. Ccami-Bernal F, Soriano-Moreno DR, Romero-Robles MA, et al. Prevalence of computer vision syndrome: A systematic review and meta-analysis. Journal of Optometry 2024; 17(1): 100482.
https://doi.org/10.1016/j.optom.2023.100482
8. Peter RG, Giloyan A, Harutyunyan T, et al. Computer Vision Syndrome (CVS): the assessment of prevalence and associated risk factors among the students of the American University of Armenia. Journal of Public Health 2023; 33(8): 1703–12.
https://doi.org/10.1007/s10389-023-02138-2
9. Kaur K, Gurnani B, Nayak S, et al. Digital eye strain: a comprehensive review. Ophthalmology and Therapy 2022; 11(5): 1655–80.
https://doi.org/10.1007/s40123-022-00540-9
10. Shah M, Saboor A. Computer Vision Syndrome: Prevalence and its associated risk factors among computer-using bank workers in Pakistan. Turkish Journal of Ophthalmology 2022; 52(5): 295–301.
https://doi.org/10.4274/tjo.galenos.2021.08838
11. Gunawardana SD, Jayawaradana D. Digital eye strain: prevalence and associated socio-demographic factors among banking assistants in Colombo District, Sri Lanka. Journal of the College of Community Physicians of Sri Lanka 2025; 30(4): 240–47.
https://doi.org/10.4038/jccpsl.v30i4.8742
12. Uba-Obiano CU, Onyiaorah AA, Nwosu SN, et al. Self-reported computer vision syndrome among bank workers in Onitsha, Nigeria. Journal of West African College of Surgeons 2022; 12(3): 71–8.
https://doi.org/10.4103/jwas.jwas_120_22
13. Bin Maneea MW, Alamawi HO, Almuqbil A, et al. Digital Eye Straining: exploring its prevalence, associated factors, and effects on the quality of life. Cureus 2024; 16(5): e59442.
https://doi.org/10.7759/cureus.59442
14. Zayed HAM, Saied SM, Younis EA, et al. Digital eye strain: prevalence and associated factors among information technology professionals, Egypt. Environmental Science and Pollution Research 2021; 28(20): 25187–95.
https://doi.org/10.1007/s11356-021-12454-3
15. Parrey MUR, Alshammari AO, Bedaiwi AA, et al. Digital eye strain: knowledge, attitude, and practice among university students. Archives of Pharmacy Practice 2023; 14(3): 33–37.
https://doi.org/10.51847/jwUgTazd60
16. Gammoh Y. Digital Eye Strain and its risk factors among a university student population in Jordan: a cross-sectional study. Cureus 2021; 13(2): e13575.
https://doi.org/10.7759/cureus.13575
17. Almahmoud OH, Mahmmod KM, Mohtaseb SA, et al. Assessment of digital eye strain and its associated factors among school children in Palestine. BMC Ophthalmology 2025; 25(1): 81.
https://doi.org/10.1186/s12886-025-03919-x
18. Ekemiri K, McKnight D, Ekemiri C, et al. Computer vision syndrome and associated factors among urban and rural bankers in Trinidad and Tobago. PeerJ 2024; 12: e18584.
https://doi.org/10.7717/peerj.18584
19. Portello JK, Rosenfield M, Bababekova Y, et al. Computer-related visual symptoms in office workers. Ophthalmic & Physiological Optics: The Journal of the British College of Ophthalmic Opticians (Optometrists) 2012; 32(5): 375–82.
https://doi.org/10.1111/j.1475-1313.2012.00925.x
20. Seguí Mdel M, Cabrero-García J, Crespo A, et al. A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace. Journal of Clinical Epidemiology 2015; 68(6): 662–73.
https://doi.org/10.1016/j.jclinepi.2015.01.015
21. Dimitrijević V, Todorovic I, Viduka B, et al. Prevalence of computer vision syndrome in computer users: A systematic review and meta-analysis. Vojnosanitetski Pregled 2023; 80(10): 860–70.
https://doi.org/10.2298/VSP220301024D
22. Sheppard AL, Wolffsohn JS. Digital eye strain: prevalence, measurement, and amelioration. BMJ Open Ophthalmology 2018; 3(1): e000146.
https://doi.org/10.1136/bmjophth-2018-000146
23. Boadi-Kusi SB, Abu SL, Acheampong GO, et al. Association between poor ergophthalmologic practices and computer vision syndrome among university administrative staff in Ghana. Journal of Environmental and Public Health 2020; 7516357.
https://doi.org/10.1155/2020/7516357
24. Reddy SC, Low CK, Lim YP, et al. Computer vision syndrome: a study of knowledge and practices in university students. Nepalese Journal of Ophthalmology: A B-iannual Peer-Reviewed Academic Journal of the Nepal Ophthalmic Society 2013; 5(2): 161–68.
https://doi.org/10.3126/nepjoph.v5i2.8707
25. Moore PA, Wolffsohn JS, Sheppard AL. Digital eye strain and its impact on working adults in the UK and Ireland. Contact Lens & Anterior Eye: The Journal of the British Contact Lens Association 2024; 47(6): 102176.
https://doi.org/10.1016/j.clae.2024.102176
26. Tesfaye AH, Alemayehu M, Abere G, et al. Prevalence and associated factors of computer vision syndrome among academic staff in the University of Gondar, Northwest Ethiopia: an institution-based cross-sectional study. Environmental Health Insights 2022; 16: 11786302221111865.
https://doi.org/10.1177/11786302221111865
27. Sharma A, Satija J, Antil P, et al. Determinants of digital eye strain among university students in a district of India: a cross-sectional study. Journal of Public Health 2024; 13: 1–6.
https://doi.org/10.1007/s10389-023-01924-2
28. Rosenfield M. Computer vision syndrome (a.k.a. digital eye strain). Optometry in practice 2016; 17: 1–10.
29. Bhattacharya S, Saleem SM, Singh A. Digital eye strain in the era of the COVID-19 pandemic: An emerging public health threat. Indian Journal of Ophthalmology 2020; 68(8): 1709–10.
https://doi.org/10.4103/ijo.IJO_1782_20
30. Leung TW, Li RW, Kee CS. Blue-light filtering spectacle lenses: Optical and Clinical Performances. PloS One 2017; 12(1): e0169114.
Downloads
Published
License
Copyright (c) 2026 Hafsa Nawaz, Yashfa Irshad, Momna Riaz, Warda Ashraf, Maryam Afzal, Raveena Rajput

This work is licensed under a Creative Commons Attribution 4.0 International License.