Digital eye strain among university students: a cross-sectional study from Hyderabad, India

Umesh D. Bhammarkar

doi:10.18203/2320-6012.ijrms20251773

Authors

Umesh D. Bhammarkar Department of Vitreoretinal Surgery, Lions Club of Hyderabad Sadhuram Eye Hospital (Post Graduate Institute of Ophthalmology), Hyderabad, Telangana, India

DOI:

https://doi.org/10.18203/2320-6012.ijrms20251773

Keywords:

Digital eye strain, Computer vision syndrome, University students, Ocular symptoms, Screen time

Abstract

Background: Digital eye strain (DES) or computer vision syndrome (CVS) represents a growing public health concern as digital device usage increases globally, particularly among university students. This study aimed to assess the prevalence and characteristics of digital eye strain among university students in Hyderabad, India.

Methods: A descriptive cross-sectional study was conducted among 112 university students in Hyderabad, India, from November to December 2024. Data was collected using a self-administered questionnaire. Non-probability convenience sampling was employed, and statistical analysis included calculation of percentages and means using statistical package for the social sciences (SPSS).

Results: All participants (100%) owned smartphones, while 60.7% owned laptops. The mean age was 22.3±2.5 years, with 65.2% female participants. The most common symptoms reported were headache (75.0%), burning or itching sensation in eyes (50.0%), and watering from eyes (49.1%). Significant increases in screen time were observed over the preceding three years.

Conclusions: Digital eye strain symptoms are highly prevalent among university students, with headaches being the predominant complaint. Preventive measures and awareness programs are essential to mitigate the effects of prolonged digital device usage on ocular health.

Metrics

Metrics Loading ...

References

Eldo BM, Mathews NE, Johnson B, Roy AS. Impact of increased screen-time on ocular health ofmedical undergraduate students during COVID-19: a cross-sectional study. Int J Community Med Public Health. 2024;11:4393-8. DOI: https://doi.org/10.18203/2394-6040.ijcmph20243304

Al Rashidi SH, Alhumaidan H. Computer vision syndrome prevalence, knowledge and associated factors among Saudi Arabia University Students: is it a serious problem? Int J Health Sci (Qassim). 2017;11:17-9.

AOA. Computer vision syndrome. Available at: https://www.aoa.org/healthy-eyes/eye-and-vision conditions/computer-vision-syndrome?sso=y. Accessed on 12 March 2025.

Iqbal M, El-Massry A, Elagouz M, Elzembely H: Computer vision syndrome survey among the medical students in Sohag University Hospital, Egypt. Ophthalmol Res An Int J. 2018;8:1-8. DOI: https://doi.org/10.9734/OR/2018/38436

Maneea MWB, Alamawi HO, Almuqbil A, Abukhlaled JK, Alsuwailem G, Alabdulminaim Jr J, et al. Digital Eye Straining: Exploring Its Prevalence, Associated Factors, and Effects on the Quality of Life. Cureus. 2024;16(5).

Parrey MUR, Alshammari AO, Bedaiwi AA, Salama B. Digital Eye Strain: Knowledge, Attitude and Practice Among University Students. Arch Pharm Pract. 2023;14(3):33-7. DOI: https://doi.org/10.51847/jwUgTazd60

Ichhpujani P, Singh RB, Foulsham W, Thakur S, Lamba AS. Visual implications of digital device usage in school children: a cross-sectional study. BMC Ophthalmol. 2019;19(1):76. DOI: https://doi.org/10.1186/s12886-019-1082-5

Assefa NL, Zenebe D, Weldemichael, Haile Alemu HW, Anbesse DH. Prevalence and associated factorsof computer vision syndrome among bank workers in Gondar City, northwest Ethiopia, 2015. Clin Optometr. 2017;9:67-76. DOI: https://doi.org/10.2147/OPTO.S126366

Loh K, Redd S. Understanding and preventing computer vision syndrome. Malaysian Fam physician Off J Acad Fam Physicians Malaysia. 2008;3:128-30.

Alkousheh H, Alkousheh Y, Qawaqzeh R, Al Juneidi L, Al-Zerikat L, Hussain A, et al. The hidden cost of digital learning: a cross-sectional study assessing the prevalence of computer vision syndrome (CVS) among medical students in Jordan. BMJ Open. 2025;15(1):e093939. DOI: https://doi.org/10.1136/bmjopen-2024-093939

Sen. A, Richardson S. A study of computer-related upper limb discomfort and computer visionsyndrome. J Hum Ergol Tokyo. 2007;36(2):45-50.

Scott K, Morris A, Marais B. Medical student use of digital learning resources. Clin Teach. 2018;15:29-33. DOI: https://doi.org/10.1111/tct.12630

Anbesu EW, Lema AK. Prevalence of computer vision syndrome: a systematic review and meta-analysis. Sci Rep. 2023;13:1801. DOI: https://doi.org/10.1038/s41598-023-28750-6

AlQarni AM, AlAbdulKader AM, Alghamdi AN, Altayeb J, Jabaan R, Assaf L, et al. Prevalence of Digital Eye Strain Among University Students and Its Association with Virtual Learning During the COVID-19 Pandemic. Clin Ophthalmol. 2023;17:1755-68. DOI: https://doi.org/10.2147/OPTH.S406032

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. DOI: https://doi.org/10.7759/cureus.13575

Kaur K, Kannusamy V, Gurnani B, Mouttapa F, Balakrishnan L. Knowledge, attitude, and practice patterns related to digital eye strain among parents of children attending online classes in the COVID-19 era: A cross-sectional study. J Pediatr Ophthalmol Strabismus. 2022;59(4):224-35. DOI: https://doi.org/10.3928/01913913-20211019-01