Computer-digital Vision Syndrome Among University Students of Lima City

Elian Fernando Lindo-Cano1
, Vania Andrea García-Monge1
, Kevin Junior Castillo-Cadillo1
, Evelyn Andrea Sánchez-Tirado1
, Ingry Marilyn Távara1
, Juan Morales2, *

1 University of Sciences and Humanities, Faculty of Health Sciences, Lima, Peru
2 University of Sciences and Humanities, E-Health Research Center, Lima, Peru

Article Metrics

CrossRef Citations:
Total Statistics:

Full-Text HTML Views: 164
Abstract HTML Views: 71
PDF Downloads: 121
ePub Downloads: 54
Total Views/Downloads: 410
Unique Statistics:

Full-Text HTML Views: 103
Abstract HTML Views: 54
PDF Downloads: 79
ePub Downloads: 41
Total Views/Downloads: 277

Creative Commons License
© 2022 Lindo-Cano et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the University of Sciences and Humanities, E-Health Research Center. Lima, Address: Av. Universitaria 5175, Los Olivos (P.O. box 15304)., Lima, Peru; Tel: (+511) 989521832; E-mail:



Computer-digital vision syndrome (CVS) is a common occupational disease.


This study aims to determine the frequency of CVS and its associated factors in students of a private university located in the north of Lima City.


The study was an observational, descriptive, and cross-sectional one. The study variable was CVS, which was assessed using the Computer Vision Syndrome Questionnaire (CVS-Q).


The analysis was carried out on 709 participants with a mean age of 22.41 years (SD: 4.5; range: 16 to 60). The most frequently used devices were the smartphone and laptop, representing 96.8% (n=686) and 64.7% (n=459), respectively. Of the students exposed to the use of display devices, 58% (n= 413) had CVS. The CVS occurred more frequently in females (p= 0.003), in the 20 to 24-year-old age group (p= 0.022), and in students who were in the first and second academic year (p=0.071). CVS was also found more frequently in lens wearers (p<0.001), in students exposed to screens for 7 to 10 hours and 4 to 6 hours a day (p<0.001), and in students who used two and three electronic devices (p<0.001). CVS occurred mainly in students who used smartphones, and laptops (p<0.05).


CVS is common among university students. The use of a variety of electronic devices, mainly smartphones and laptops, as well as the exposure time, plays an important role. Therefore, it is recommended to carry out prevention and promotion activities of vision care at the beginning of the academic period.

Keywords: Asthenopia, Eye fatigue, Fatigue visual, Eyestrain, Peru (Source. MeSH NLM), Syndrome.


The 21st century has given way to a global society increasingly dependent on a variety of technologies in personal, occupational, and institutional settings [1]. The use of electronic devices in the population is massive, mobile telephony is growing in a generalized way in both developed and developing countries, with an estimated 128.9 lines / 100 inhabitants and 103.8 lines / 100 inhabitants, respectively. Regarding the possession of computers, worldwide, 49.7% have at least one computer, 78% in Europe, 65.7% in America, and 10.7% in Africa. Television continues to be the technological equipment present in a high proportion of homes [2]. In Peru, 98.4% of households have at least one information and communication technology, in 97.7% of households, there is at least one member with a cell phone. In Lima, 45.8% of households have at least one computer, 61.7% have Internet service, and access in both cases is lower in the rest of the urban and rural areas [3].

At the beginning of 2020, of the 7.75 billion total population, 67% (5.19 billion) are unique mobile phone users, 59% (4.54 billion) are Internet users, and 49% (3.8 billion) are active social media users. The average Internet user spends 6 hours and 43 minutes online every day, it varies by country, in the Philippines users spend an average of 9 hours and 45 minutes per day, compared to Japan where users spend only 4 hours and 22 minutes per day [4]. In Peru, 96% of the population with university education access the Internet, and 94.1% access the Internet through mobile phones [3].

The use of electronic devices has multiple benefits in our lives; however, they are not free from side effects and can affect health [5, 6]. Computer-digital vision syndrome (CVS), also referred to as digital eye strain, describes a group of the eye- and vision-related problems that result from prolonged computer, tablet, e-reader, and cell phone use [7].

The CVS is recognized by the International Labor Organization (ILO) within the group of occupational diseases [8]. CVS is a common problem, globally nearly 60 million people suffer from CVS; in Sri Lanka, the 1-year prevalence of CVS is 67.4% [9]. In the United States, it affects 65% of adults, and in Spain, the prevalence is 53% [10].

Among students, a high prevalence of CVS was observed, in which 95% reported at least one symptom during studying using computers [11]. In university students from Saudi Arabia, the acute and chronic presentation of CVS was 72% and 28% respectively [12].

In Peru, there are limited works on the CVS [13, 14]. On the other hand, the Covid-19 pandemic has generated a set of changes both in the work and academic context. In universities, face-to-face classes were replaced by virtual classes making use of electronic devices and therefore, greater exposure to screens, which is expected to increase the frequency of CVS. The objective of this study is to determine the frequency of computer digital vision syndrome and its associated factors in students of a private university located in the north of Lima City.


2.1. Design

The study was an observational, descriptive, and cross-sectional. It was held between November and December 2020 at the University of Sciences and Humanities (UCH), located in the north of Lima City

2.2. Population and Samples

The population consisted of 2623 students registered in the second semester of 2020 at the UCH. Students from all faculties and all academic cycles participated, 661 from the Faculty of Health Sciences, 721 from the Faculty of Humanities and Social Sciences, 526 from the Faculty of Sciences and Engineering, and 715 from the Faculty of Accounting and Economic Sciences and Financial (Table 1).

The sample size was calculated using n = [N * Za2 * p * q] / [d2 * (N-1) + Za2 * p * q], considering a confidence level of 95% (Za=1.96), N = 2623, p = 0.5, q = 0.5 and d=5%, with an expected proportion of losses of 10%. The minimum sample calculated was 372 students. In the period covered by the study, 717 participants were recruited.

All subjects who met the following criteria were included: students of both sexes, who voluntarily agreed to participate in the study, and who answered the virtual questionnaire adequately. Participants with incomplete data were excluded.

2.3. Study Variables

Computer vision syndrome (CVS): According to the American Optometric Association, Computer Vision Syndrome describes a group of the eye- and vision-related problems that result from prolonged computer, tablet, e-reader, and cell phone use. The most common symptoms associated with CVS are poor lighting, glare on a digital screen, improper viewing distance, poor seating posture, uncorrected vision problems, and a combination of these factors [7].

Comparison variables: Age, sex, use of glasses, technological devices used, and the number of hours/day dedicated to the use of such devices were considered.

2.4. Instruments and Measurement Techniques

The instrument used was the “Computer Vision Syndrome Questionnaire” (CVS-Q), developed and validated by Seguí et al. [15]. The CVS-Q was also validated in the Peruvian context [13], and applied to graduate university students [14].

CVS-Q assesses the frequency and intensity of 16 symptoms: burning eyes, itching, foreign body sensation, tearing, excessive blinking, eye redness, eye pain, eyelid heaviness, dry eye, blurred vision, double vision, difficulty focusing in near vision, increased sensitivity to light, colored halos around objects, feeling of seeing worse, and headache. The frequency is quantified as never = 0, occasionally = 1, often or always = 2. The intensity of the symptoms has been rated as moderate = 1 and intense = 2. The severity was determined from the product of the frequency and intensity, later the product was recorded as 0=0, 1 or 2=1, and 4=2. For the final score of the CVS, the sum of the recorded severity scores was used; scores of 6 or higher were considered to have CVS.

The technique used was the survey. The instrument used was a self-administered virtual questionnaire.

2.5. Procedure for Data Collection

CVS-Q was applied virtually through the Google Drive® platform. In the process of disseminating the link to access the questionnaire, we have received the support of the classroom delegates and coordinators of the different faculties of the university. The data of the participants was autogenerated automatically in Excel® format, anonymously.

Table 1. General characteristics of university students in the north of Lima City, 2020.
Characteristics n %
Total 709 100
Female 370 52.2
Male 339 47.8
Age Group
< 20 197 27.8
20 to 24 362 51.1
≥ 25 150 21.2
Academic Year
First 218 30.7
Second 180 25.4
Third 158 22.3
Fourth 121 17.1
Fifth 32 4.5
Health Sciences 174 24.5
Humanities and social sciences 101 14.2
Science and Engineering 223 31.5
Accounting and Financial sciences 211 29.8
Wearing Glasses
No 366 51.6
Yes 343 48.4
Glasses Type
Glasses 305 43.0
Contact lenses 38 5.4
Reason for Wearing Glasses
Improve visual defect 224 31.6
Avoid eyestrain 119 16.8
Number of Electronic Devices Used
One 54 7.6
Two 221 31.2
Three 282 39.8
Four 117 16.5
Five 35 4.9

2.6. Statistical Analysis

The self-generated database was exported to the SPSS version 26 program. Before the analysis, the data was cleaned according to the study criteria. The valid data of the variables was distributed in frequency tables. The frequency of the CVS was estimated, and to establish its association with the comparison variables, the data was represented in crossed tables. To evaluate the association of the variables, the Chi-square statistic was used, considering p-value ​​<0.05 as significant.


A total of 717 students of both sexes participated; eight were excluded due to incomplete data. The analysis was carried out with 709 participants with a mean age of 22.41 years (SD: 4.5; range: 16 to 60). Of the sample, 52.2% (n=370) were male, 51.1% (n=362) were between the ages of 20 and 24 years, and the majority were from the first and second academic year. Of the total participants, 48.4% (n=343) reported wearing glasses, of which 31.6% (n=224) improved a visual defect. According to gender, there was a significant difference in the use of glasses, 55.7% (n=206) in women and 40.4% (n=137) in men (p<0.001). Regarding the use of electronic devices, 39.8% (n=282) used three electronic devices, and 31.2% (n=221) two devices (Table 1).

Among the participating students, the most frequently used devices were the Smartphone and laptop, representing 96.8% (n=686) and 64.7% (n=459), respectively. Other devices such as computers, televisions, and tablets were used in a lower percentage. Regarding the exposure time, 45.6% (n=323) were exposed to some information and communication technologies (ICT) between 7 and 10 hours and 30.2% (n=214) between 4 and 6 hours. Of the students exposed to display devices, 58% (n=413) had digital computer vision syndrome. Likewise, among the most frequently reported ocular and extraocular symptoms were burning, headache, tearing, increased sensitivity to light, and itching (Table 2). Symptoms such as heavy eyelids, blurred vision, double vision, difficulty focusing for near vision, feeling that sight is worsening, and headache occurred more frequently among women (p<0.05); according to age, tearing, and excessive blinking appeared mainly between 20 and 24 years old (p<0.05).

Regarding the factors associated with computer vision syndrome. The CVS was more frequent in females, 56.9% (n=235) versus 43.1% (n=178) in males (p=0.003), it was also more frequent in the age group of 20 to 24 years (50.4%), compared to other age groups (p=0.022). Students from the accounting and financial sciences, and science and engineering faculties presented CVS in a higher percentage (p=0.005), as did the students who were in the first and second academic years (p=0.071). The participants who wore glasses presented CVS in a higher proportion, 63.4% (n=262) compared to 36.6% (n=151) who did not use glasses (p<0.001). According to the number of hours exposed to the use of ICT, CVS occurred in a higher proportion among users from 7 to 10 hours and 4 to 6 hours a day (p<0.001). Likewise, CVS also appeared in a higher percentage of students who used two and three devices (p<0.001) (Table 3).

When evaluating the type of device used, it was found that students who used a smartphone and laptop had a higher frequency of CVS. In Smartphone users, CVS was present in 95.4% (n=394) (p=0.016), and among laptop users in 69.7% (n=288) (p=0.001). The electronic devices that had the least presence of CVS were tablet, computer, and television (p=0.05) (Table 4).

Table 2. Electronic devices used and the presence of computer digital vision syndrome (CVS) among university students in the north of Lima City, 2020.
An Electronic Device Used and CVS n %
Total 709 100
Electronic Device Used
Smartphone 686 96.8
Tablet 140 19.7
Laptop 459 64.7
Computer 352 49.6
Television 348 49.1
Hours/Day Exposed to Devices
1 a 3 33 4.7
4 a 6 214 30.2
7 a 10 323 45.6
>10 139 19.6
Presence of CVS
No 296 41.7
Si 413 58.3
Ocular and Extraocular Symptoms
Burning 63 8.9
Headache 63 8.9
Tearing 60 8.5
Increased sensitivity to light 54 7.6
Itching 51 7.2
Eye redness 39 5.5
Blurred vision 38 5.4
A feeling of a foreign body 37 5.2
Excessive blinking 25 3.5
Feeling that sight is worsening 25 3.5
Difficulty focusing for near vision 23 3.2
Heavy eyelids 22 3.1
Colored halos around objects 22 3.1
Eye pain 17 2.4
Dryness 10 1.4
Double vision 8 1.1

Table 3. Computer-digital vision syndrome according to the characteristics of university students in the north of Lima City, 2020.
Characteristics CVS Absent CVS Present p-value
n % n %
Total 296 100 413 100 -
Female 135 45.6 235 56.9 0.003
Male 161 54.4 178 43.1
Age Group
< 20 93 31.4 104 25.2 0.022
20 to 24 154 52.0 208 50.4
≥ 25 49 16.6 101 24.5
Health Sciences 86 29.1 88 21.3 0.005
Humanities and social sciences 50 16.9 51 12.3
Science and Engineering 89 30.1 134 32.4
Accounting and financial sciences 71 24.0 140 33.9
Academic Year
First 107 36.1 111 26.9 0.071
Second 74 25.0 106 25.7
Third 62 20.9 96 23.2
Fourth 43 14.5 78 18.9
Fifth 10 3.4 22 5.3
Wearing Glasses
No 215 72.6 151 36.6 < 0.001
Yes 81 27.4 262 63.4
Hours/Day Exposed to Devices
1 a 3 19 6.4 14 3.4 < 0.001
4 a 6 70 23.6 144 34.9
7 a 10 171 57.8 152 36.8
>10 36 12.2 103 24.9
Number of Electronic Devices Used
One 20 6.8 34 8.2 < 0.001
Two 64 21.6 157 38.0
Three 123 41.6 159 38.5
Four 65 22.0 52 12.6
Five 24 8.1 11 2.7


Among college students exposed to electronic devices, 58% had digital computer vision syndrome. These findings are consistent with the results obtained in graduate students from a private university in Lima, where CVS was found in 61% of the students [14]. CVS is a common problem. In Saudi Arabia, 97.3% of health science students had at least one CVS symptom [16]. In computer users, the prevalence of CVS is 69.5% (95% CI: 65.6 to 73%) [17].

It is likely that the change in classes from face-to-face to virtual mode has generated an increase in the use of electronic devices and a longer exposure time to screens. Likewise, factors such as inadequate lighting, inadequate posture, and glare emitted by the screens of digital devices could have contributed to the development of CVS.

The CVS was detected mainly among women, in students belonging to the age group of 20 to 24 years, students from science-engineering and accounting financial faculties, and students who were in the first and second academic year. In the present study, the sample was predominantly made up of women and young people between 20 and 24 years of age.

On the other hand, students from the aforementioned faculties have greater exposure to these devices both in classes and in preprofessional practice. Students from other fields, such as the health sciences, find themselves in a different scenario since they participate in virtual classrooms and spend more time engaging in preprofessional practise while spending less time in front of screens. In the case of the students of the first year, they do not carry out preprofessional practices; therefore they have a greater number of virtual classes. The students who wear glasses and those who used two to three electronic devices had a higher frequency of CVS. Likewise, a higher percentage of CSV was found in students who used smartphones and laptops.

Table 4. Computer-digital vision syndrome according to the type of electronic device used by university students in the north of Lima City, 2020.
Characteristics CVS Absent CVS Present p-value
n % n %
Total 296 100 413 100 -
No 4 1.4 19 4.6 0.016
Yes 292 98.6 394 95.4
No 218 73.6 351 85.0 < 0.001
Yes 78 26.4 62 15.0
No 125 42.2 125 30.3 0.001
Yes 171 57.8 288 69.7
No 136 45.9 221 53.5 0.047
Yes 160 54.1 192 46.5
No 100 33.8 261 63.2 < 0.001
Yes 196 66.2 152 36.8

The major factors associated with CVS were either environmental (improper lighting, display position, and viewing distance) and/or dependent on the user's visual abilities (uncorrected refractive error, oculomotor disorders, and tear film abnormalities) [18]. The fact that in our study women had a higher frequency of CVS may indicate the preexistence of an eye problem, or they were the ones who most perceived ocular and extraocular symptoms. The main contributor to computer vision syndrome symptoms appears to be dry eye [19], and the prevalence of dry eye in women is higher compared to men [20].

In Saudi Arabia, CVS was reported mostly in female students and eyeglass wearers [16]. Workers who wear contact lenses and are exposed to the computer for more than 6 h a day are more likely to suffer CVS than nonlens wearers working at the computer for the same amount of time (OR = 4.85; 95% CI, 1.25-18.80; p = 0.02) [21]. Due to their easy portability, both smartphones and laptops are the devices most used by students. Advances in technology have led to the increased use of hand-held devices [18].

The CVS is a frequent entity in university students, so it requires intervention and preventive measures regarding the work environment and devices. The 20/20/20 guideline is recommended for use with electronic devices like computers and calls for 20 minutes spent in front of the screen followed by 20 seconds of fixed-point observation at a distance of 20 feet [22]. We take into consideration the study's cross-sectional design, the fact that only students from one university participated, and the fact that the results were derived from a virtual self-report as limitations. The use of glasses among students is high and appears to improve a visual defect; however, these defects were not confirmed. The use of glasses may have been to protect or alleviate symptoms caused by exposure to electronic device screens, and not necessarily to correct a visual defect. The strength of the study lies in the adequate size of the sample, whose results can approximate the real magnitude of the problem in the university population.


In university students, there is a high frequency of digital computer-digital vision syndrome, and they occur mainly in women, in students of the first year of study, and those who use two to three electronic devices. The electronic devices associated with the CVS were smartphones and laptops. Vision care prevention and promotion activities are recommended at the beginning of the academic period.


CVS = Computer-digital Vision Syndrome
CVS-Q = Computer Vision Syndrome Questionnaire
ILO = International Labor Organization


The research protocol was evaluated and approved by the Ethics Committee of the University of Sciences and Humanities (ID Code-118-20, CEI Act No. 118-2020).


No animals were used for studies that are the basis of this research. All human procedures followed were in accordance with the guidelines of the Helsinki Declaration of 1975.


Informed consent was obtained from all participants of this study.


STROBE guidelines were followed in this study.


The data supporting the finding ofThe data that support the findings of this study are available from the corresponding author [J.M.] on special request.




The authors declares no conflict of interest financial or otherwise.


Declared none.


[1] Mehra D, Galor A. Digital Screen Use and Dry Eye: A Review. Asia Pac J Ophthalmol (Phila) 2020; 9(6): 491-7.
[2] Gobierno de España. Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información. La Sociedad en Red. Transformación digital en España. Informe anual 2019, edición 2020. Vol. 7, Global media journal. Madrid; 2013. Available from:
[3] Instituto Nacional de Estadística e Informática. Informe Técnico. Estadísticas de las Tecnologías de Información y Comunicación en los Hogares. Vol. 4, Instituto Nacional De Estadistica Informatica. Lima, Perú; 2020. Available from: MenuRecursivo/boletines/04-informe-tecnico-tic-iii-trimestre2020.pdf
[4] Kemp S. A global digital overview [Internet]. We are Social, Hootsuite, Jan. 2020. Available from: orts/digital-2020-global-digital -overview
[5] Small GW, Lee J, Kaufman A, et al. Brain health consequences of digital technology use
. Dialogues Clin Neurosci 2020; 22(2): 179-87.
[6] Stiglic N, Viner RM. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open 2019; 9(1): e023191.
[7] American Optometric Association. Computer-digital vision syndrome [Internet]. [Cited 2021 Mar 21]. Available from: healthy-eyes/eye-and-vision-conditions/computer-vision-syndrome?sso=y
[8] Prado A, Morales Á, Molle JN. Síndrome de Fatiga ocular y su relación con el medio laboral. Med Segur Trab (Madr) 2017; 63(249): 345-61.
[9] Ranasinghe P, Wathurapatha WS, Perera YS, 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(1): 150.
[10] Sheppard AL, Wolffsohn JS. Digital eye strain: prevalence, measurement and amelioration. BMJ Open Ophthalmol 2018; 3(1): e000146.
[11] Abudawood GA, Ashi HM, Almarzouki NK. Computer Vision Syndrome among Undergraduate Medical Students in King Abdulaziz University 2020. Article id 2789367.
[12] 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) 2017; 11(5): 17-9.
[13] Huapaya YA. Validación del Instrumento “Computer Vision Syndrome Questionnaire (CVS-Q)” En el Personal Administrativo en Lima 2019 [Internet]. Universidad Peruana Cayetano Heredia; 2020. Available from: /20.500.12866 /8531/Validacion_HuapayaCana_Yessenia.pdf?sequence=1&isAllowed=y
[14] Fernandez DE. Prevalencia del síndrome visual informático en estudiantes universitarios de postgrado de una universidad privada Lima - 2019 [Internet]. Universidad Peruana Union; 2019. Available from: .pe/handle/UPEU/1633
[15] Seguí MM, Cabrero-García J, Crespo A, Verdú J, Ronda E. A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace. J Clin Epidemiol 2015; 68(6): 662-73.
[16] Altalhi AA, 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.
[17] Dessie A, Adane F, Nega A, Wami SD, Chercos DH. Computer vision syndrome and associated factors among computer users in Debre Tabor town, Northwest Ethiopia. J Environ Public Health 2018; 2018: 1-8.
[18] Gowrisankaran S, Sheedy JE. Computer vision syndrome: A review. Work 2015; 52(2): 303-14.
[19] Blehm C, Vishnu S, Khattak A, Mitra S, Yee RW. Computer vision syndrome: a review. Surv Ophthalmol 2005; 50(3): 253-62.
[20] Truong S, Cole N, Stapleton F, Golebiowski B. Sex hormones and the dry eye. Clin Exp Optom 2014; 97(4): 324-36.
[21] Tauste A, Ronda E, Molina MJ, Seguí M. Effect of contact lens use on Computer Vision Syndrome. Ophthalmic Physiol Opt 2016; 36(2): 112-9.
[22] Echeverri Saldarriaga S, Giraldo Ochoa D, Lozano García L, Mejía Cardona P. Montoya LLano L, Vásquez Trespalacios E. Síndrome de visión por computador: una revisión de sus causas y del potencial de prevención. Rev CES Salud Pública 2012; 3(2): 193-201.