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