Impact of screen time on digital eye strain and visual acuity among medical students in Peshawar, Pakistan

Main Article Content

Iqbal Haider
Muhammad Osama
Nazli Gul
Asad Rehman Khattak

Abstract

OBJECTIVES:   To determine the impact of screen time with digital eye strain (DES), visual acuity, and near point of accommodation (NPA).


METHODS: This cross-sectional study was conducted at Khyber Medical College Peshawar, Pakistan. This study included 244 students of 3rd year to 5th year MBBS, who consented to participate. A Snellen chart and Royal Air Force (RAF) rule were used to assess the visual acuity, and NPA. Chi-Square, Pearson Correlation, and multiple regression analyses were conducted using SPSS software.


RESULTS: Out of 244 participants, 181 (74.1%) reported at least one symptom of digital eye strain. Headache (n=87; 35.6%) and eye pain (n=64; 26.22%) were the most common reported symptoms. Refractive error was reported in 98 (40.16%) students, including myopia (n=86; 35.25%), hyperopia (n=12; 4.92%), and astigmatism (n=12; 4.92%). Mobile (n=244; 100%) and Laptop (n=212; 86.90%) were the main electronic gadgets used by participants. Headache, eye pain, tearing of the eyes, eye redness, and itching of the eyes were significantly associated with screen time (p<0.05). Headache, blurred vision, itching of eyes, and eye pain were significantly associated with refractive error (p<0.05). Multiple regression analysis explains a 32.9% variance in the digital eye strains.


CONCLUSION: This study reveals a concerning 74.1% prevalence of DES among medical students in Peshawar, Pakistan, emphasizing the impact of prolonged screen time on ocular health. Our study reveals a significant link between screen time and DES, with headache & eye pain being the prevalent symptoms. Associations between symptoms, screen time, and refractive errors emphasize the relevance of these factors.

Article Details

How to Cite
Haider, I., M. Osama, N. Gul, and A. R. Khattak. “Impact of Screen Time on Digital Eye Strain and Visual Acuity Among Medical Students in Peshawar, Pakistan”. KHYBER MEDICAL UNIVERSITY JOURNAL, vol. 15, no. 4, Dec. 2023, pp. 229-34, doi:10.35845/kmuj.2023.23402.
Section
Original Articles

References

Rosenfield M, Howarth PA, Sheedy JE, Crossland MD. Vision and IT display a whole new visual world. Ophthalmic Physiol Opt 2012;32(5):363-6. https://doi.org/10.1111/j.1475 1313.2012.00936.x

American Optometric Association. Computer vision syndrome [Internet]. Accessed on: July 04, 2023. Available from URL: https://www.aoa.org/healthy-eyes/eye-and-vision-conditions/computer-vision-syndrome

Council V. Eyes overexposed: The digital device dilemma. Alexandria, VA: The Vision Council. 2016. Accessed on: July 04, 2023. Available from URL: https://www.kodaklens.us/wp-content/uploads/2017/03/TheVisionCouncil_2016EyeStrain_Report_WEB.pdf

Cantó-Sancho N, Sánchez-Brau M, Ivorra-Soler B, Seguí-Crespo M. Computer vision syndrome prevalence according to individual and video display terminal exposure characteristics in Spanish university students. Int J Clin Pract 2021;75(3):e13681. https://doi.org/10.1111/ijcp.13681. Erratum in: Int J Clin Pract 2021;75(12):e15017. https://doi.org/10.1111/ijcp.15017

Reddy SC, Low CK, Lim YP, Low LL, Mardina F, Nursaleha MP. Computer vision syndrome: a study of knowledge and practices in university students. Nepal J Ophthalmol 2013;5(2):161-8. https://doi.org/10.3126/nepjoph.v5i2.8707

Nisar N, Salman R, Farooq S. Screen Time and its Relation with Ophthalmic Problems among Medical Students. Pak J Med Health Sci 2022;16(12):295-9. https://doi.org/10.53350/pjmhs20221612295

Hadi KN, Rehman MH, Toru HK, Orakzai AA, Khalid S, Iftikhar B. Assessment of Computer Vision Syndrome in University Students in Peshawar: A Descriptive Cross-Sectional Study. Stetho 2021; 2(6):6-14.

Tehreem F, Tahira Z. Prevalence of Computer Vision Syndrome and Its Associated Risk Factors among Under Graduate Medical Students of Urban Karachi. Pak J Ophthalmol 2016;32(3):106. https://doi.org/10.36351/pjo.v32i3.106

Goyal A, Mandawat N, Joshi A. RAF RULE: A Double Edge Weapon. Global J Res Anal 2020;9 (8):21-2. https://doi.org/10.36106/gjra

Hashemi H, Pakbin M, Ali B, Yekta A, Ostadimoghaddam H, Asharlous A, et al. Near Points of Convergence and Accommodation in a Population of University Students in Iran. J Ophthalmic Vis Res 2019;14(3):306-14. https://doi.org/10.18502/jovr.v14i3.4787

Anbesu EW, Lema AK. Prevalence of computer vision syndrome: a systematic review and meta-analysis. Sci Rep 2023;13(1):1801. https://doi.org/10.1038/s41598-023-28750-6

Dimitrijević V, Todorović I, Viduka B, Lavrnić I, Viduka D. Prevalence of computer vision syndrome in computer users: A systematic review and meta-analysis. Vojnosanit Pregl 2023;80(10):860-70. https://doi.org/10.2298/VSP220301024D

Adane F, Alamneh YM, Desta M. Computer vision syndrome and predictors among computer users in Ethiopia: a systematic review and meta-analysis. Trop Med Health 2022;50(1):26. https://doi.org/10.1186/s41182-022-00418-3

Altalhi A, Khayyat W, Khojah O, Alsalmi M, Almarzouki H. Computer Vision Syndrome Among Health Sciences Students in Saudi Arabia: Prevalence and Risk Factors. Cureus 2020;12(2):e7060. https://doi.org/10.7759/cureus.7060

Zenbaba D, Sahiledengle B, Bonsa M, Tekalegn Y, Azanaw J, Kumar Chattu V. Prevalence of Computer Vision Syndrome and Associated Factors among Instructors in Ethiopian Universities: A Web-Based Cross-Sectional Study. Scientific World J 2021;2021:3384332. https://doi.org/10.1155/2021/3384332

Garg S, Mallik D, Kumar A, Chunder R, Bhagoliwal A. Awareness and prevalence of computer vision syndrome among medical students: A cross-sectional study. Asian J Med Sci 2021:12(9):44-8. https://doi.org/10.3126/ajms.v12i9.37247

Akowuah PK, Nti AN, Ankamah-Lomotey S, Frimpong AA, Fummey J, Boadi P, et al. Digital device use, computer vision syndrome, and sleep quality among an African undergraduate population. Adv Public Health 2021;2021:1-7. https://doi.org/10.1155/2021/6611348

Nwankwo B, Mumueh K, Olorukooba A, Usman N. Computer vision syndrome: prevalence and associated risk factors among undergraduates in a tertiary institution in northwestern Nigeria. Kanem J Med Sci 2021;15(1):1-8. https://doi.org/10.36020/kjms.2021.1501.003

Arshad S, Qureshi MF, Ali M, Piryani K, Shafqat K, Mateen M, et al. Computer vision syndrome: prevalence and predictors among students. Ann Psychophysiol 2019;6(1):15-22. https://doi.org/10.29052/2412-3188.v6.i1.2019.15-22

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;9:150. https://doi.org/10.1186/s13104-016-1962-1

Al Tawil L, Aldokhayel S, Zeitouni L, Qadoumi T, Hussein S, Ahamed SS. Prevalence of self-reported computer vision syndrome symptoms and its associated factors among university students. Eur J Ophthalmol 2020;30(1):189-95. https://doi.org/10.1177/1120672118815110

Kang JW, Chun YS, Moon NJ. A comparison of accommodation and ocular discomfort change according to display size of smart devices. BMC Ophthalmol 2021;44(1):1-9. https://doi.org/10.1186/s12886-020-01789-z

Chen Y, Chen YA, Gui Z, Bao W, Zhang J, Tan K, et al. Association of sedentary behaviors with visual acuity among primary school students: a cohort study. Chinese J School Health 2021;42(8):1144-7. https://doi.org/10.16835/j.cnki.1000-9817.2021.08.006

Abudawood GA, Ashi HM, Almarzouki NK. Computer vision syndrome among undergraduate medical students in King Abdulaziz University, Jeddah, Saudi Arabia. J Ophthalmol 2020;2020:1-7. https://doi.org/10.1155/2020/2789376

Moon JH, Kim KW, Moon NJ. Smartphone use is a risk factor for pediatric dry eye disease according to region and age: a case-control study. BMC Ophthalmol 2016;16(1):188. https://doi.org/10.1186/s12886-016-0364-4

Coles-Brennan C, Sulley A, Young G. Management of digital eye strain. Clin Exp Optom 2019;102(1):18-29. https://doi.org/10.1111/cxo.12798