Prevalence and determinants of digital eye strain among school children during the COVID-19 pandemic

Authors

  • Catherine Simon Department of Community Medicine, Azeezia Institute of Medical Sciences and Research, Kollam, Kerala, India
  • Shalet Paul Department of Ophthalmology, Azeezia Institute of Medical Sciences and Research, Kollam, Kerala, India

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20214863

Keywords:

Digital eye strain, Prevalence, School children, Digital devices, COVID

Abstract

Background: Digital eye strain (DES) is an emerging public health problem due to continuous exposure to electronic gadgets and digital devices for educational, occupational or entertainment purposes, especially during this COVID-19 pandemic. Children are more vulnerable to DES, as they continue to attend online classes but are unaware of early symptoms of DES and do not complain till their vision deteriorates. The objective of this study was to assess the prevalence and risk factors of DES among school children during this pandemic.

Methods: A questionnaire-based cross-sectional study was conducted among 176 school children aged 12-16 years, studying in 8th, 9th and 10th standards of a randomly selected school in Kollam district of Kerala, using the validated computer vision syndrome questionnaire (CVSQ), sent online via Google form to parents/guardians for recording their children’s pattern of digital device usage and DES symptoms.

Results: The prevalence of DES among school children was 29.5%. Their commonest symptom was headache (n=125, 69.9%). The smartphone was the most commonly used digital device (n=159, 93.5%). The independent risk factors of DES were the preferred use of smart phone (adjusted odds ratio (AOR)=2.846; 95% CI=1.371-5.906; p=0.005) and viewing distance of digital device <18 inches (AOR=2.762; 95% CI=1.331-5.731; p=0.006).

Conclusions: This study has highlighted some of the risk factors associated with DES. A concerted effort is needed to raise awareness about DES by experts in the health and education sectors, along with parents and teachers, so that digital device use among children can be optimised.

References

Association AO. Computer vision syndrome. Available at: https://www.aoa.org/healthy-eyes/eye-and-vision-conditions/computer-vision-syndrome? sso=y. Accessed on 30 August 2021.

Carbonell X, Chamarro A, Oberst U, Rodrigo B, Prades M. Problematic use of the internet and smartphones in university students: 2006-2017. Int J Environ Res Public Health. 2018;15(3):475.

Madhan MRR. Computer vision syndrome. Nurs J India. 2009;100(10):236-7.

Raja AM, Janti SS, Chendilnathan C, Adnan M. Ocular problems of computer vision syndrome: Review. J Mahatma Gandhi Inst Med Sci. 2015;20(2):134-6.

Bhattacharya S, Saleem SM, Singh A. Digital eye strain in the era of COVID-19 pandemic: an emerging public health threat. Indian J Ophthalmol. 2020;68(8):1709-10.

Ichhpujani P, Singh RB, Foulsham W, Thakur S, Lamba AS. Visual implications of digital device usage in school children. BMC Note. 2016;19:76.

Mohan A, Sen P, Shah C, Jain E, Jain S. 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 J Ophthalmol. 2021;69(1):140-4.

Mdel MS, Cabrero-García J, Crespo A, Verdú J, Ronda E. A reliable and valid questionnaire developed to measure computer vision syndrome at the workplace, J Clinic Epidemiol. 2015;68(6):662-73.

Sheppard AL, Wolffsohn JS. Digital eye strain: Prevalence, measurement and amelioration. BMJ Open Ophthalmol. 2018;3(1):000146.

Loh K, Reddy S. Understanding and preventing computer vision syndrome. Malaysian Fam Phys. 2008;3(3):128-30.

Hazarika A, Singh K. Computer vision syndrome. SMU Med J. 2014;1(2):132-8.

Vilela MA, Pellanda LC, Fassa AG, Castagno VD. Prevalence of asthenopia in children: A systematic review with meta-analysis. J Pediatr Brazil. 2015;91(4):320-5.

Portello JK, Rosenfield M, Bababekova Y, Estrada JM, Leon A. Computer related visual symptoms in office workers. Ophthalmic Physiol Opt. 2012;32(5):375-82.

Amarnath MV, Ribot FMD. Digital eye strain among children in South India: prevalence and risk factors during the COVID-19 pandemic- case study. Asian J Res Rep Ophthalmol. 2021;4(2):24-34.

Ranasinghe P, Wathurapatha WS, Perera YSD, Lamabadusuriya A, 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.

Lemma, MG, Beyene KG, Tiruneh MA. Computer vision syndrome and associated factors among secretaries working in ministry offices in Addis Ababa, Ethiopia. Clinic Optomet. 2020;12:213-22.

Lakshmi V. Progress of medical undergraduates to an era of computer vision syndrome and insomnia as an aftermath of increased digitalization during covid-19 pandemic. EJMCM. 2020;7(11):8225-33.

Agarwal S, Goel D, Sharma A. Evaluation of the factors which contribute to the ocular complaints in computer users. J Clinic Diagnost Res. 2013;7(2):331-5.

Mufti M, Sayeed SI, Jaan I, Nazir S. Does digital screen exp cause dry eye? Indian J Clinic Ana Physiol. 2019;6(1):68-72.

Babu JV, Abraham S, Biju MJ, Jose J. Impact of digitilisation in Covid lockdown period in Muvattupuzha, Kerala. An epidemiological study. J Drug Delivery Therapeut. 2021;11(1):7-14.

Joju A, Anthrayose CV, Puthiyedathu R, Babu N. Eyestrain & RF in UG med. Study in covid. Ind J Clin Exptal Ophthal. 2021;7(2):308-13.

Wang J, Li Y, Musch DC, Wei N, Qi X, Ding G, et al. Progression of myopia in school-aged children after COVID-19 home confinement. JAMA Ophthalmol. 2021;139(3):293-300.

Ahuja S, Stephen M, Ranjith N, Parthiban. Assessing the factors and prevalence of digital eye strain among digital screen users using a validated questionnaire-an observational study. Int J Med Public Health. 2021;11(1):19-23.

Lavin W, Taptagaporn S, Khruakhorn S, Kanchanaranya N. Prevalence and associated risk factors of digital eye strain among children in secondary schools in Pathumthani Province, Thailand. J Med Assoc Thai. 2018;101:957-63.

Sanodiya I, Kujur A, Sirohi S, Khatri AK. A cross sectional overview of digital eye strain: a growing health concern in this digital age in central India (Madhya Pradesh). Int J Community Med Public Health. 2019;6(5):4828-33.

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;5:161-8.

Reshma KAS, Iram S. Prevalence of dry eye in computer users. IP Int J Ocul Oncol Oculoplast. 2020;6(2):95-8.

Kaaya H, Investigation of the effect of online education on eye health in COVID-19 pandemic, Turkey. International J Assess Tool Edu. 2020;7(3):488-96.

Ganne P, Najeeb S, Chaitanya G, Sharma A, Krishna. J. Digital eye strain epidemic amid COVID-19 pandemic-a cross-sectional. Surv Ophthal Epidemiol. 2021;28(4):285-92.

Moon JH, Lee MY, Moon NJ. Association between video display terminal use and dry eye disease in school children. J Pediatr Ophthalmol Strabismus. 2014;51:87-92.

Gammoh Y. Digital eye strain and its risk factors among a university student population in Jordan: a cross-sectional study. Cureus. 2012;13(2):13575.

Kim J, Hwang Y, Kang S, Kim M, Kim TS, Kim J, et al. Association between exposure to smartphones and ocular health in adolescents. Ophthal Epidemiol. 2016;23:269-76.

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Published

2021-12-27

How to Cite

Simon, C., & Paul, S. (2021). Prevalence and determinants of digital eye strain among school children during the COVID-19 pandemic. International Journal Of Community Medicine And Public Health, 9(1), 7–15. https://doi.org/10.18203/2394-6040.ijcmph20214863

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Original Research Articles