Factors associated with Computer Vision Syndrome in students and teachers of a private university in Peru during the SARS-CoV-2 pandemic

Authors

DOI:

https://doi.org/10.56294/saludcyt2024939

Keywords:

Asthenopia, Medical Students, Educational Personnel, Education, Distance, Ocular Health

Abstract

Introduction: computer Vision Syndrome is also considered the ocular epidemic of the 21st century. It is essential to determine the number of individuals suffering from CVS and the associated factors.
Objective: to identify the factors associated with Computer Vision Syndrome in medical students and faculty at Peruvian Private University during the SARS-CoV-2 pandemic in 2021.
Methods: this was an observational, cross-sectional, retrospective, and analytical study. The participants included students and faculty members from the School of Human Medicine. The Computer Vision Syndrome Questionnaire (CVS-Q) from Google Forms was used. For bivariate analysis, the chi-squared test was used with a 95 % confidence level. Frequency and proportion calculations were used for qualitative variables, and measures of central tendency and dispersion were calculated for quantitative variables.
Results: 56,0 % of faculty and students suffered from computer vision syndrome (CVS). In the bivariate analysis, it was found that the use of eyeglasses (p < 0,004), a computer/cell phone screen distance of <45cm (p < 0,031), and a family history of visual diseases (p < 0,010) were associated with CVS.
Conclusions: there is a high prevalence of computer vision syndrome, with faculty members being the most affected. Factors associated with CVS were the use of eyeglasses, a computer/cell phone screen distance of <45cm, and a family history of visual diseases

References

1. Chawla A, Lim TC, Shikhare SN, Munk PL, Peh WCG. Computer Vision Syndrome: Darkness under the Shadow of Light. Can Assoc Radiol J. 1 de febrero de 2019;70(1):5-9.

2. Maru Alemayehu A. Pathophysiologic Mechanisms of Computer Vision Syndrome and its Prevention: Review. World Journal of Ophthalmology & Vision Research. 12 de noviembre de 2019;2.

3. Bellini MI, Pengel L, Potena L, Segantini L, ESOT COVID-19 Working Group. COVID-19 and education: restructuring after the pandemic. Transpl Int. febrero de 2021;34(2):220-3.

4. Vásquez D. Ventajas, desventajas y ocho recomendaciones para la educación médica virtual en tiempos del COVID-19: Revisión de Tema. CES Medicina. 12 de junio de 2020;34:14-27.

5. Bonett DC, Aguilar AS, de Estadística S, Calderón RR. 1.1 Evolución del acceso a las Tecnologías de Información y Comunicación en los hogares. :55.

6. Quispe-Torres D. Prevalencia y factores asociados al síndrome visual informático en estudiantes de Medicina Humana del Perú durante la educación virtual por la pandemia del COVID-19 [Internet]. Universidad Ricardo Palma; 2021 [citado 23 de julio de 2021]. Disponible en: http://repositorio.urp.edu.pe/handle/URP/3608

7. Fernandez-Villacorta D, Soriano-Moreno AN, Galvez-Olortegui T, Agui-Santivañez N, Soriano-Moreno DR, Benites-Zapata VA. Computer visual syndrome in graduate students of a private university in Lima, Perú. Arch Soc Esp Oftalmol (Engl Ed). 12 de febrero de 2021;S0365-6691(21)00005-8.

8. Honorio A, Franklin Y, Galván E, Paola D, Vilchez H, Malpartida M, et al. Cambios en la ergonomía en tiempos de COVID-19 en estudiantes de una universidad Peruana.

9. Sohrabi C, Alsafi Z, O’Neill N, Khan M, Kerwan A, Al-Jabir A, et al. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int J Surg. abril de 2020;76:71-6.

10. Johns Hopkins Coronavirus Resource Center. [Internet]. Johns Hopkins Coronavirus Resource Center. [citado 23 de julio de 2021]. Disponible en: https://coronavirus.jhu.edu/

11. Lovón Cueva MAL, Cisneros Terrones SAC. Repercusiones de las clases virtuales en los estudiantes universitarios en el contexto de la cuarentena por COVID-19: El caso de la PUCP. Propósitos y Representaciones. 5 de septiembre de 2020;8(SPE3):588.

12. Dostálová N, Vrubel M, Kachlík P. Computer vision syndrome - symptoms and prevention. Cas Lek Cesk. 2021;160(2-3):88-92.

13. 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). diciembre de 2017;11(5):17-9.

14. Zevallos-Cobeña VS. Apuntes sobre los factores de riesgo asociados al síndrome visual informático en estudiantes de la Facultad de Ciencias de la Salud de la Universidad Técnica de Manabí. Dominio de las Ciencias. 10 de mayo de 2021;7(3):239-59.

15. Boadi-Kusi SB, Abu SL, Acheampong GO, Adueming POW, Abu EK. Association between Poor Ergophthalmologic Practices and Computer Vision Syndrome among University Administrative Staff in Ghana. J Environ Public Health. 2020;2020:7516357.

16. Fernández EF. Prevalencia del Sidrome Visual Informatico en trabajadores del Hospital Universitario Virgen de la Arrixaca. [España]: Universidad Miguel Hernandez; 2018.

17. 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. marzo de 2021;75(3):e13681.

18. Esparza Córdova DFE. Riesgo de Síndrome Visual del Computador en relación a la utilización de dispositivos informáticos en estudiantes de la Carrera de Medicina de la Universidad Nacional de Loja. [Ecuador]; 2017.

19. 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. diciembre de 2013;5(2):161-8.

20. Moreno Benítez M, Salazar Román YN. Factores de riesgo que causan fatiga visual en estudiantes del programa de optometría de AREANDINA Fundación Universitaria del Área Andina Pereira durante el año 2017. 2017 [citado 23 de julio de 2021]; Disponible en: https://digitk.areandina.edu.co/handle/areandina/992

21. Xu Y, Deng G, Wang W, Xiong S, Xu X. Correlation between handheld digital device use and asthenopia in Chinese college students: a Shanghai study. Acta Ophthalmologica. 2019;97(3):e442-7.

22. Freyle Hernández MT, Pineda Gonzalez JA, Torres Cabrera LB. Prevalencia, población y factores asociados del Síndrome Visual Informático 2010-2020: Revisión de Alcance [Internet] [masterThesis]. reponame:Repositorio Institucional EdocUR. Universidad del Rosario; 2020 [citado 23 de julio de 2021]. Disponible en: https://repository.urosario.edu.co/handle/10336/30745

23. Castillo Caballero DA. Factores asociados a síndrome visual informático en estudiantes de medicina de la Universidad Privada Antenor Orrego. Universidad Privada Antenor Orrego [Internet]. 2022 [citado 24 de junio de 2022]; Disponible en: https://repositorio.upao.edu.pe/handle/20.500.12759/8799

24. Medina Espinoza I, Preciado Lara M. “Uso de la computadora, y su impacto en la agudeza visual de los educandos de la ciudad de Tarma - Perú”. [Huanuco]: Universidad de Huanuco; 2020.

25. Sivaraman V, Janarthanam JB. Computer vision syndrome in the time of COVID-19: Is blue-blocking lens a panacea for digital eye strain? Indian J Ophthalmol. marzo de 2021;69:779.

26. Ruiz J. COVID-19: chronicle of a pandemic foretold. Microbes, Infection and Chemotherapy. 25 de enero de 2022;2:e1343-e1343.

Downloads

Published

2024-05-22

How to Cite

1.
Zapana-Tito M, Gómez-Gonzales W, Gómez-Livias MF, Gamarra Bustillos C, Chihuantito-Abal L. Factors associated with Computer Vision Syndrome in students and teachers of a private university in Peru during the SARS-CoV-2 pandemic. Salud, Ciencia y Tecnología [Internet]. 2024 May 22 [cited 2024 Dec. 10];4:939. Available from: https://sct.ageditor.ar/index.php/sct/article/view/771