COMPUTER VISUAL SYNDROME IN MEDICAL STUDENTS IN VIRTUAL EDUCATION OF A PERUVIAN UNIVERSITY DURING 2021

ORIGINAL ARTICLE

REVISTA DE LA FACULTAD DE MEDICINA HUMANA 2021 - Universidad Ricardo Palma
10.25176/RFMH.v23i1.5525

COMPUTER VISUAL SYNDROME IN MEDICAL STUDENTS IN VIRTUAL EDUCATION OF A PERUVIAN UNIVERSITY DURING 2021

SÍNDROME VISUAL INFORMÁTICO EN ESTUDIANTES DE MEDICINA EN EDUCACIÓN VIRTUAL DE UNA UNIVERSIDAD PERUANA DURANTE EL 2021

Rosario Mercedes Meneses Castañeda ORCID 1, Sergio Luis Ramos Rodriguez ORCID 1, Chiara del Carmen Molfino Jaramillo ORCID 1, Ely Luisa Sánchez Miraval ORCID 1, David Francisco Stein Montoros ORCID 1, Lourdes Guissel Chávez Rodríguez ORCID 1

1Facultad de Medicina Humana, Universidad Ricardo Palma. Lima, Perú.

ABSTRACT:

Introduction: During virtual classes in the context of COVID-19, students were exposed to digital screens for many hours, so they could present computer vision syndrome. Objective: To determine the frecuency of computer vision syndrome in sixth-year students of the Faculty of Human Medicine of the Ricardo Palma University in the context of virtual education due to COVID-19 during the period October - November 2021. Methods: Cross-sectional descriptive study in 147 sixth-year medical students who received virtual education at a Peruvian university during 2021. A non-probability sampling was used for convenience and the SVI was evaluated with the SVI-Q questionnaire, in addition characteristics were evaluated. demographics, visual preventive measures and eye diseases. The results were analyzed with SPSS v.21 for Windows. The study was approved by the Ethics Committee. On the other hand, in an exploratory way, the factors associated with SVI were evaluated, for age the Mann-Whitney U test was used, and for the rest of the variables the Fisher exact test was used. A value of p<0.05 was considered significant. Results: Most of the students were young adults (54%) and female (60%). The frequency of computer visual syndrome was 93%, it occurred in 94% of women and 90% of men. Most of the students reported having myopia (44%) and astigmatism (22%). Regarding visual symptoms, the students mainly presented tearing (7.9%), itching (7.6%), and headache (7.6%). Conclusions: In the present study, a high frequency of computer visual syndrome was found in medical students who took virtual classes.

Keywords: Vision Disorders, Education, Distance, Students, Medical. (Source: MeSH NLM).

RESUMEN:

Introducción: Durante las clases virtuales en el contexto del COVID-19 los estudiantes estuvieron expuestos muchas horas a pantallas digitales, por lo que podrían presentar síndrome visual informático. Objetivo: Determinar la frecuencia del síndrome visual informático en estudiantes de sexto año de la facultad de medicina humana de la Universidad Ricardo Palma en el contexto de la educación virtual por COVID-19 durante el periodo octubre - noviembre 2021. Métodos: Estudio descriptivo transversal en 147 estudiantes de medicina de sexto año que recibieron educación virtual en una universidad del Perú durante el 2021. Se utilizó un muestreo no probabilístico por conveniencia y el SVI se evaluó con el cuestionario SVI-Q, además se evaluaron características demográficas, medidas preventivas visuales y enfermedades oculares. Los resultados se analizaron con SPSS v.21 para Windows. El estudio fue aprobado por el Comité de Ética. Resultados: : La mayoría de los estudiantes fueron adultos jóvenes (54%) y del sexo femenino (60%). La frecuencia de síndrome visual informático fue de 93%, se presentó en el 94% de mujeres y el 90% de hombres. La mayoría de las estudiantes refirió tener miopía (44%) y astigmatismo (22%). En lo referente a los síntomas visuales, los estudiantes presentaron principalmente lagrimeo (7,9%), picor (7,6%), dolor de cabeza (7,6%). Conclusiones: En el presente estudio se encontró una elevada frecuencia de síndrome visual informático en estudiantes de medicina que llevaron clases virtuales.

Palabras Clave: Trastornos de visión, Educación a Distancia, Estudiantes de Medicina. (Fuente: DeCS BIREME).

INTRODUCCION:

Currently, technology is a part of our daily life and has become indispensable; Electronic devices such as cell phones, tablets, computers, and televisions have been brought into our homes with increasing frequency for recreational and/or vocational purposes. In the last century, the modern world has become addicted to the screens of such devices, thus generating a great demand for daily use; these make life easier for many people worldwide; however, their inappropriate use can cause damage to health (1).

The year 2020 brought a pandemic due to SARS-COV2, which altered the lifestyle of many people. The primary measure was confinement and social distancing, depriving physical and social interaction. On the other hand, this promoted relationships through electronic devices; thus, people relied on devices to obtain information or for entertainment (2).

The American Optometric Association (AAO) defines the term computer vision syndrome (CVS) as a group of eye and vision problems related to excessive and prolonged use of electronic equipment (1).

For example, a person who dedicates a large part of their day to being in front of a computer as an employee or student performs 12,000 to 35,000 head and eye movements daily, and their pupils react 5,000 to 17,000 times. Consequently, symptoms such as dry eye, blurred vision, eye pain, neck and shoulder pain, and headache occur (1,3).

The prevalence of people around the world suffering from CVS ranges from 64% to 90%, and approximately 60 million people have been affected. In addition, 75% of people who spend more than 6 hours a day in front of a computer have a higher incidence of visual problems (4). A report by the AAO indicates that each year, 10 million people go to a health center for eye examinations for visual problems related to the increased use of computers (1).

University students make up one of the groups most exposed to CVS after the group of office workers. One report indicates that approximately 81% of college students are affected by CVS; the widespread use of electronic devices for various academic activities explains this. Another study reveals that 89.9% of university students who use the computer for more than 2 hours a day suffer from CVS. This syndrome negatively impacts students' daily work, thus affecting productivity, efficiency, time management, general health, and well-being (4,5).

Therefore, the present investigation aims to determine the prevalence of computer vision syndrome in 6th-year medical students in a Peruvian university in the context of virtual education due to COVID-19.

METHODS:

Design and study area

A cross-sectional descriptive observational study was carried out at a university in the Peruvian capital.

Population and sample

The population consisted of sixth-year medical students from the Faculty of Human Medicine of Ricardo Palma University, who received virtual education from October to November 2021. To find the sample size, the EPIDAT software was used. 4.2, considering a population size of 238, a prevalence of computer vision syndrome of 0.50, a confidence level of 95%, and an error of 5%. A total sample of 147 students was obtained, and a non-probabilistic sampling was carried out for convenience.

Variables and instruments

The dependent variable was computer vision syndrome (CVS), defined as the set of ocular, visual, and extra-ocular symptoms caused by exposure to the screen of electronic devices (1). For its evaluation, the Computer vision Syndrome Questionnaire (CVS-Q) was used in its original Spanish version, which consists of 7 questions. The instrument was validated in Peru and applied to administrative personnel, where a Cronbach's alpha of 0.87 was found. This is considered an acceptable level (6). Therefore, those medical students who presented a score greater than or equal to 6 in the total score were considered positive for CVS.

The independent variables sex, use of glasses, taking breaks during computer use, use of preventive visual measures, time of continuous use of cell phones per day, time of continuous use of laptop per day, and ocular disease were included. For data collection, a questionnaire was used that included sociodemographic characteristics and other factors that could influence the prevalence of CVS.

Procedure

The questionnaires and informed consent were sent virtually to the students in the 6th year of medicine through a Google Docs file for their respective completion.

Statistic analysis

Data was entered and analyzed using the statistical program SPSS v.21 for Windows. Likewise, the results were presented in single and double-entry tables in numerical and percentage form.

Ethical aspects

The Research Ethics Committee of Ricardo Palma University approved the study. Therefore, participation in the study was carried out before informed consent was accepted. Furthermore, the information used for the research purposes was stored in a coded form, avoiding any information that would allow the identification of the participants. In this sense, the physical and psychological integrity of those involved in the study was guaranteed.

RESULTS

Regarding the sociodemographic characteristics, we found that most students were young adults (54%) and females (60%). Most wore glasses (78%), both frame (75%) and contact (3%). The highest percentage of students spent more than 6 hours uninterrupted computer use (43%). Likewise, most spent less than two hours of uninterrupted cell phone use (27%). Regarding visual rest, most students rested at least every hour (29%), followed by rest at least every 2 hours (23%). Regarding the use of preventive measures, most of them did not take any preventive measure (44%), followed by those who kept their eyes closed for a while (27%), and finally, those who gazed at distant places (18%) (Table 1).

Table 1. Sociodemographic characteristics and characteristics of eye care.

Variable

N (%)

Age group

 

 

19 -24 (Young adult)

79 (54%)

≥ 25 (Adult)

68 (46%)

Sex

 

 

Female

88 (60%)

Male

59 (40%)

Use of lenses

 

 

Yes, with a frame

110 (75%)

Yes, contact lenses

4 (3%)

I don't wear glasses

33 (22%)

Uninterrupted use of the computer

 

 

Less than 2 hours

9 (6%)

2 - 4 hours

41 (28%)

4 - 6 hours

34 (23%)

More than 6 hours

63 (43%)

Uninterrupted cell phone use

 

 

Less than 2 hours

40 (27%)

2 - 4 hours

48 (33%)

4 - 6 hours

31 (21%)

More than 6 hours

28 (19%)

Taking visual breaks

 

 

Yes, at least every 20 minutes

23 (16%)

Yes, at least every hour

42 (29%)

Yes, at least every 2 hours

34 (23%)

Yes, after more than 2 hours

30 (20%)

I don't take eye breaks

17 (12%)

Use of preventive measures for vision care

 

 

Use of artificial tears

15 (10%)

Stare at distant places

26 (18%)

Keep your eyes closed for a while

39 (27%)

I do not take ny preventive measures

64 (44%)

I rest and perform a face wash

1 (1%)

Sleep

1 (1%)

Laptop screen distance

1 (1%)

Total

147 (100%)



Regarding any diagnosed visual disease, the majority reported having myopia (44%), followed by those with astigmatism (22%) and hyperopia (4%). Likewise, 27% did not present disease (Table 2).

Table 2. Diagnosed visual disease.

Diagnosed visual disease

N (%)

Astigmatism

32 (22%)

Myopia

65 (44%)

Farsightedness

6 (4%)

Cataracts

0 (0%)

Eye surgery

0 (0%)

No disease

39 (27%)

Eyestrain

1 (1%)

Pterygium

1 (1%)

Myopia and astigmatism

3 (2%)

Total

147 (100%)



The students mainly presented tearing (7.9%), itching (7.6%), headache (7.6%), heavy eyelids (7.2%), and blurred vision (6.7%). Regarding the frequency of tearing, the students reported that they presented this symptom occasionally (51%), often or always (24%), and finally, never (25%). Regarding itching, the majority present this symptom occasionally (61%), never (28%), and often in a lower percentage (11%). Finally, regarding the headaches, the students presented them occasionally (50%), never 828%), and to a lesser extent often or always (22%) (Table 3).

Table 3. Frequency of ocular symptoms presented by the students.

Symptoms

Total

Often or always

Occasionally

Never

N (%)

N (%)

N (%)

N (%)

Tearing

110 (7,9%)

35 (24%)

75 (51%)

37 (25%)

Itching

106 (7,6%)

16 (11%)

90 (61%)

41 (28%)

Headache

106 (7,6%)

33 (22%)

73 (50%)

41 (28%)

Heavy eyelids

100 (7,2%)

24 (16%)

76 (52%)

47 (32%)

Blurry vision

93 (6,7%)

16 (11%)

77 (52%)

54 (37%)

Increased sensitivity

92 (6,6%)

22 (15%)

70 (48%)

55 (37%)

Excessive blinking

90 (6,5%)

20 (15%)

70 (48%)

57 (39%)

Burning

89 (6,4%)

19 (13%)

70 (48%)

58 (39%)

Foreign body sensation

87 (6,3%)

15 (10%)

72 (49%)

60 (41%)

Dryness

85 (6,1%)

25 (17%)

60 (41%)

62 (42%)

Eye redness

80 (5,8%)

17 (12%)

63 (43%)

67 (46%)

Eye pain

76 (5,5%)

13 (9%)

63 (43%)

71 (48%)

Difficulty focusing

76 (5,5%)

15 (10%)

61 (41%)

71 (48%)

Sensation of seeing worse

74 (5,3%)

9 (6%)

65 (44%)

73 (50%)

Double vision

65 (4,7%)

12 (8%)

53 (36%)

82 (56%)

Colored halos

60 (4,3%)

17 (12%)

43 (29%)

87 (59%)



Regarding the intensity of the symptoms, tearing was mainly moderate (59%), mild (25%), and to a lesser extent, intense (16%). The itching was mainly moderate (54%), mild (28%), and less intense (18%). Headaches were mainly moderate (44%), mild (28%), and severe (28%). Regarding the frequency of CVS, it was found that 93% (136) of the students presented CVS. Regarding the relationship between the student's sex and CVS, this syndrome was more frequent in women, presenting CVS in 94% of them and 90% of men.

Table 4 studied the comorbidities associated with CVS, of which only preventive measures were associated (p=0.025).



Table 4.Associated factors with computer vision syndrome in the study population

No CVS CVS Total P-value
Age 24.0 (22.0-25.0) 24.0 (23.0-26.0) 24.0 (23.0-26.0) 0.120
Sex
Female 7 (8.0%) 81 (92.0%) 88 (100.0%) 0.280
Male 8 (13.6%) 51 (86.4%) 59 (100.0%)
Use of lenses
I don't wear glasses 5 (15.2%) 28 (84.8%) 33 (100.0%) 0.570
Yes, with frame 10 (9.1%) 100 (90.9%) 110 (100.0%)
Yes, contact lenses 0 (0.0%) 4 (100.0%) 4 (100.0%)
Uninterrupted use of the computer
Less than 2 hours 1 (11.1%) 8 (88.9%) 9 (100.0%) 0.530
2 - 4 hours 3 (7.3%) 38 (92.7%) 41 (100.0%)
4 - 6 hours 2 (5.9%) 32 (94.1%) 34 (100.0%)
More than 6 hours 9 (14.3%) 54 (85.7%) 63 (100.0%)
Uninterrupted use of the cell phone
Less than 2 hours 4 (10.0%) 36 (90.0%) 40 (100.0%) 0.470
2 - 4 hours 6 (12.5%) 42 (87.5%) 48 (100.0%)
4 - 6 hours 1 (3.2%) 30 (96.8%) 31 (100.0%)
More than 6 hours> 4 (14.3%) 24 (85.7%) 28 (100.0%)
Taking visual breaks
Yes, at least every 20 minutes 4 (17.4%) 19 (82.6%) 23 (100.0%) 0.160
Yes, at least every hour 1 (2.4%) 41 (97.6%) 42 (100.0%)
Yes, at least every 2 hours 3 (8.8%) 31 (91.2%) 34 (100.0%)
Yes, after more than 2 hours 4 (13.3%) 26 (86.7%) 30 (100.0%)
I don't take visual breaks 3 (16.7%) 15 (83.3%) 18 (100.0%)
Use of preventive measures for vision care
No 11 (17.2%) 53 (82.8%) 64 (100.0%) 0.025
Yes 4 (4.8%) 79 (95.2%) 83 (100.0%)
Diagnosis of ocular disease
No 7 (17.9%) 32 (82.1%) 39 (100.0%) 0.072
Yes 8 (7.4%) 100 (92.6%) 108 (100.0%)
Total N=15 N=132 N=147


DISCUSSION:

The present study found that the frequency of Computer Vision Syndrome was high, similar to that found in various studies in the population of medical students (7-10). However, other studies found a mean prevalence oscillating between 50%-60% (8,11). Likewise, at the national level, there is only one study on postgraduate students belonging to various faculties, resulting in a prevalence of 61%. The prevalence in students at the medical school level was 32.8% (12). In national studies on employees, a high prevalence was found related to workers with digital tasks (13,14). It should be noted that, due to the increasing use of information computer technologies (ICTs) in academic and work tasks, computer vision syndrome could be considered a public health problem, taking into account the reference of its prevalence at the national level and worldwide and still the ignorance of the approach and impact of this problem.

Likewise, it was found that women have a higher frequency of CVS than men. This coincides with studies reported on medical students, in which it was observed that females had a higher risk of developing CVS than males (7,8). This may be due to hormonal factors, in which women may be more predisposed to developing dry eye (15), as well as other external factors. On the other hand, at the national level, no significant difference has been found in the prevalence in both sexes (12). Therefore, more studies would be needed to determine if, in reality, there is a significant variation in the prevalence of CVS in terms of gender and perhaps also considering the type of occupation.

Among the most frequent symptoms of computer vision syndrome in the students who were part of our population, tearing was observed with the highest percentage of responses (7.9%). This is similar to the finding in the study by Ghufran et al., where excessive tearing was the predominant ocular symptom (20.6%) (7). In the present work, tied for second place we found itchy eyes and headaches (7.6% of responses for both), the latter symptom being the most frequent in other studies such as that of Altalhi A et al. (9) and Iqbal et al. (10) (68% and 50.2% respectively), differing from our results. Itchy eyes were found to be the third most prevalent symptom (63%) in the study by Altalhi A et al. (9); however, it is not described among the most frequent symptoms in others. In our study, heavy eyelids ( 7.2%) ranked third, a symptom not evidenced in previous works. However, in the study by Vikanaswari, GI & Handayani, A. (12) they mention tense or tired eyes as the most frequent (72.8%). In addition, unlike our study, other works agree that neck pain is the most characteristic symptom of computer vision syndrome (7,12). In this sense, a degree of variability is observed in relation to the report of symptoms most representative of this syndrome in the people suffering from it.

Another finding is the higher prevalence of CVS in those medical students who use a computer/laptop for more than 6 hours compared to those with only a few hours of exposure. This coincides with other studies carried out amongst medical students in which a significant correlation is found, the longer the hours of consumption (greater than 4 to 6 hours approximately) of digital devices, the greater the risk of presenting symptoms of CVS, and the one that occurs with the most frequent is myopia (16-18). On the other hand, two previous studies were presented, the first being carried out in Jamaica and the second in Saudi Arabia, both with a sample similar to this present work. Both did not find a significant relationship between the presence of CVS symptoms and the time the participants spent in front of the computer/laptop (4,19). This discrepancy may be due to factors specific to the sample or the methodology. However, a significant association between exposure time and suffering from CVS symptoms is explained by the fact that the longer the time spent on a laptop screen, the frequency of blinking decreases, and the production of the tear film decreases, which leads to its vaporization and causes symptoms associated with CVS.

Regarding the use of preventive measures against CVS, at least 41% of the students did not take any preventive measures, which is reflected in the study by Mendoza et al., where 59% of the population studied did not take preventive measures during the use of electronic devices, considering it a significant risk factor for developing CVS (20).

On the other hand, within the preventive measures against CVS, the techniques most used by students were: keeping their eyes closed for a specific time and trying to fix their gaze on distant sites, with 28% and 18%, respectively. These results are consistent with various national and international studies where students opt to use these measures to help relax muscles and provide a change in eye focus, preventing eye fatigue (5,13,21). Although, in the present study, around 10% stated the use of artificial tears as a preventive measure, studies such as the one by Wang et al. (2) consider the use of these agents as a symptomatic treatment to reduce the effects of dry eyes in CVS, but not as preventive measures per se.

Regarding the use of preventive measures, this factor was found to be associated with SVI (p=0.025), where 44% of the students did not take any preventive measure. Similarly, in the study by Mendoza et al., 59% of the study population did not take preventive measures while using electronic devices either.

Among the study's limitations is its methodology; the cross-sectional information collection does not allow for determining causal inferences. Likewise, the collection of information virtually could generate a selection bias, where only those 6th-year students with internet access were able to participate in the study. Likewise, as it is a virtual questionnaire, the resolution of possible doubts of the participant concerning the questions of the questionnaire is limited, which could generate an information bias.

CONCLUSION:

In conclusion, a high frequency of CVS was found amongst 6th-year students of the Faculty of Human Medicine, which showed a higher percentage of women being affected. Therefore, it is recommended to educate medical students on the use of preventive measures to avoid CVS, such as taking breaks of approximately 5 minutes every hour and placing the computer/laptop screen at a distance between 50 and 60 cm, among others, during virtual classes.


Authorship contributions: Computer visual syndrome in medical students in virtual education of a peruvian university during 2021.
Financing: Self-financed.
Declaration of conflicts of interest: The authors declare that they have no conflict of interest.
Received: 03/11/2022.
Approved: 04/12/2022.


Corresponding Author: Rosario Mercedes Meneses Castañeda.
Address: Av. Benavides 330 Dpto 102 - Miraflores.
Phone: 999369700 - 444-6077
E-mail: drcharimeneses@hotmail.com


Article published by the Journal of the faculty of Human Medicine of the Ricardo Palma University. It is an open access article, distributed under the terms of the Creatvie Commons license: Creative Commons Attribution 4.0 International, CC BY 4.0(https://creativecommons.org/licenses/by/1.0/), that allows non-commercial use, distribution and reproduction in any medium, provided that the original work is duly cited. For commercial use, please contact revista.medicina@urp.edu.pe.


BIBLIOGRAPHIC REFERENCES

    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. Available at: https://pubmed.ncbi.nlm.nih.gov/30474390/
    2. Wang L, Wei X, Deng Y. Computer Vision Syndrome During SARS-CoV-2 Outbreak in University Students: A Comparison Between Online Courses and Classroom Lectures. Front Public Health [Internet]. 2021;9:696036. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296301/
    3. Frómeta Leyé I, Beltrán Castellano Y, Grandales Laffita AE, Alonso Ramírez M. Síndrome visual informático. Rev Inf Científica [Internet]. 2012;74(2). Available at: https://www.redalyc.org/articulo.oa?id=551757272038
    4. Mowatt L, Gordon C, Santosh ABR, Jones T. Computer vision syndrome and ergonomic practices among undergraduate university students. Int J Clin Pract [Internet]. 2018;72(1):e13035. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/ijcp.13035
    5. 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 [Internet]. 2021;96(10):515-20. Available at: https://www.sciencedirect.com/science/article/pii/S2173579421001110
    6. Huapaya Caña YA. Validación del instrumento “Computer Vision Syndrome Questionnaire (CVS-Q)” en el personal administrativo en Lima 2019 [Tesis de maestría]. Lima, Perú: Universidad Peruana Cayetano Heredia; 2020. Available at: https://repositorio.upch.edu.pe/handle/20.500.12866/8531
    7. Custodio Sanchez KL. Trascendencia del síndrome visual informático por exposición prolongada a dispositivos electrónicos: Transcendence of computer vision syndrome due to prolonged exposure to electronic devices. Rev Fac Med Humana [Internet]. 8 de febrero de 2021;21(2). Available at: http://revistas.urp.edu.pe/index.php/RFMH/article/view/3611
    8. Abudawood GA, Ashi HM, Almarzouki NK. Computer Vision Syndrome among Undergraduate Medical Students in King Abdulaziz University, Jeddah, Saudi Arabia. J Ophthalmol [Internet]. 2020;2020:e2789376. Available at: https://www.hindawi.com/journals/joph/2020/2789376/
    9. Jiao J, Yang J, Li J, Li Y, Zhang L. Hypertonic saline and seawater solutions damage sinonasal epithelial cell air-liquid interface cultures. Int Forum Allergy Rhinol. 2020 Ene;10(1):59–68. DOI: https://doi.org/10.7759/cureus.7060
    10. Iqbal M, Elzembely H, Elmassry A, Elgharieb M, Assaf A, Ibrahim O, et al. Computer Vision Syndrome Prevalence and Ocular Sequelae among Medical Students: A University-Wide Study on a Marginalized Visual Security Issue. Open Ophthalmol J [Internet]. 2021;15(1). Available at: https://openophthalmologyjournal.com/VOLUME/15/PAGE/156/FULLTEXT/
    11.Garg S, Mallik D, Kumar A, Chunder R, Bhagoliwal A. Awareness and prevalence on computer vision syndrome among medical students: A cross-sectional study. Asian J Med Sci [Internet]. 2021;12(9):44-8. Available at: https://www.nepjol.info/index.php/AJMS/article/view/37247
    12.Vikanaswari GI, Handayani A. The screening of computer vision syndrome in medical students of udayana university. Bali J Ophthalmol [Internet]. 28 de septiembre de 2018;2(2). Available at: https://balijournalophth.org/index.php/bjo/article/view/20
    13. López-Camones JJ, Rojas-Meza LJ, Osada J, López-Camones JJ, Rojas-Meza LJ, Osada J. Frecuencia de factores ocupacionales asociados a astenopía en trabajadores usuarios de pantallas de visualización de datos de empresas del rubro construcción en Huaraz, 2019. Rev Asoc Esp Espec En Med Trab [Internet]. 2020;29(2):56-66. Available at: https://scielo.isciii.es/scielo.php?script=sci_abstract&pid=S1132-62552020000200010&lng=es&nrm=iso&tlng=es
    14. Arbulú-Paredes M, Chirinos-Saldaña P. Efecto de una emulsión lubricante en la sintomatología, daño a la superficie ocular e inestabilidad de la película lagrimal de pacientes con ojo seco asociado al síndrome visual informático. Acta Médica Peru [Internet]. 2019;36(3):202-8. Available at: http://www.scielo.org.pe/scielo.php?script=sci_abstract&pid=S1728-59172019000300004&lng=es&nrm=iso&tlng=es
    15. INEI. Las Tecnologías de Información y Comunicación en los Hogares: Ene-Feb-Mar 2022 [Internet]. Lima, Perú: INEI; 2022 [citado el 1 de enero de 2023]. Available at: https://www.gob.pe/institucion/inei/informes-publicaciones/3156404-las-tecnologias-de-informacion-y-comunicacion-en-los-hogares-ene-feb-mar-2022
    16. 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 Biannu Peer-Rev Acad J Nepal Ophthalmic Soc NEPJOPH. 2013;5(2):161-8. DOI: 10.3126/nepjoph.v5i2.8707
    17. Kharel Sitaula R, Khatri A. Knowledge, Attitude and practice of Computer Vision Syndrome among medical students and its impact on ocular morbidity. J Nepal Health Res Counc. 2018;16(3):291-6. DOI: https://doi.org/10.3126/jnhrc.v16i3.21426
    18. Belay S, Alemayehu AM, Hussen MS. Prevalence of Computer Vision Syndrome and Associated Factors among Postgraduate Students at University of Gondar, Northwest Ethiopia, 2019. DOI: https://doi.org/10.1155/2021/3384332. eCollection 2021
    19. Noreen K, Ali K, Aftab K, Umar M. Computer Vision Syndrome (CVS) and its Associated Risk Factors among Undergraduate Medical Students in Midst of COVID-19: Doi: 10.36351/pjo.v37i1.1124. Pak J Ophthalmol [Internet]. 2021;37(1). Available at: https://pjo.org.pk/index.php/pjo/article/view/1124
    20. Mendoza Escobar TE. El síndrome visual informático y su influencia en las ametropías en personas de 25 a 34 años En La Ciudadela Universitaria, Babahoyo Los Ríos Primer Semestre 2018 [Internet] [Tesis de grado]. Babahoyo; 2018. Available at: http://dspace.utb.edu.ec/handle/49000/4868
    21. Dostálová N, Vrubel M, Kachlík P. Computer vision syndrome - symptoms and prevention. Cas Lek Cesk. 2021;160(2-3):88-92. Disponible en: https://pubmed.ncbi.nlm.nih.gov/34134500/

http://www.scielo.org.pe/scielo.php?script=sci_serial&pid=2223-2516&lng=en&nrm=iso


¿Quieres dejar tu comentario o sugerencia sobre este artículo?

---> CLICK AQUI <---