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 Table of Contents    
ORIGINAL ARTICLE
Year : 2022  |  Volume : 15  |  Issue : 1  |  Page : 73-77  

Awareness and practice regarding use of digital devices and ocular health among Saudi adolescents


Department of Surgery, College of Medicine, Prince Sattam Bin Abdulaziz University, AlKharj, Saudi Arabia

Date of Submission29-Sep-2021
Date of Decision20-Dec-2021
Date of Acceptance03-Jan-2022
Date of Web Publication02-Mar-2022

Correspondence Address:
Dr. Abdulrahman AlDarrab
Department of Surgery, College of Medicine, Prince Sattam Bin Abdulaziz University, AlKharj
Saudi Arabia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ojo.ojo_283_21

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   Abstract 


PURPOSE: To review the knowledge of ocular health and practices of digital device usage among adolescent Saudi Arabia population.
METHODS: This cross-sectional web-based survey was conducted in 2021 at a university in central Saudi Arabia. We asked questions regarding demographics, knowledge related to computer vision syndrome (CVS), and the use of digital devices for participants' daily activities. The acceptable grades of knowledge (”excellent” and “good”) and practice scores were associated with the determinants using the nonparametric method of analysis.
RESULTS: Of 521 participating students, knowledge about CVS and its relation to digital device usage were excellent in 41 students (7.9%), good in 161 (39%), poor in 300 (57.6%), and very poor in 19 (3.6%). Twenty-eight (5.4%) students scored an “excellent” grade on practices for digital device usage, 216 (41.4%) scored “good,” and 277 (53.2%) scored “poor.” The knowledge score median was 1.0 (interquartile range 1.0; 2.0), and the practice score median was 6.0 (4.0; 9.0). Health studies students had better knowledge than other students (P = 0.004). Smartphone users had worse knowledge than users of other devices (P = 0.017). Females (P < 0.001) and health studies students (P = 0.004) were significantly associated with acceptable practices of using digital devices.
CONCLUSIONS: Awareness of ocular health because of abuse of digital devices was poor among participating students. The practice of digital device use was not healthy and needed improvement through preventive measures and counseling.

Keywords: Adolescent health, computer vision syndrome, digital devices, knowledge and practice


How to cite this article:
AlDarrab A. Awareness and practice regarding use of digital devices and ocular health among Saudi adolescents. Oman J Ophthalmol 2022;15:73-7

How to cite this URL:
AlDarrab A. Awareness and practice regarding use of digital devices and ocular health among Saudi adolescents. Oman J Ophthalmol [serial online] 2022 [cited 2022 May 26];15:73-7. Available from: https://www.ojoonline.org/text.asp?2022/15/1/73/338880




   Introduction Top


Eye and vision-related problems due to prolonged use of computer, tablet, e-reader, and cell phone is called computer vision syndrome (CVS). Its rapidly increasing magnitude, especially in the younger population, is a public health challenge.[1],[2] This is more of an occupational hazard for employers in information technology and radiology and for those compelled to work in front of a computer for long hours.[3],[4],[5] Excessive use of digital devices is a major risk factor for CVS.[6] The lockdown during the COVID-19 pandemic further accentuated the problem of CVS.[7]

We recommend several preventive measures to reduce the risk of CVS and the progression of the condition. They include frequent breaks while working with digital devices, using the optimum distance between digital devices and the eye, ensuring an ideal angle for the viewing device, appropriate sitting arrangements, ambient lighting, and the use of lubricating eye drops.[8],[9]

To implement these preventive measures, awareness of the population, especially high-risk groups, needs improvement; and their attitudes and practices for using digital devices need to be studied and, if needed, altered. This will be possible if baseline information on awareness and current practices for using digital devices are known. The literature includes numerous studies in different areas to estimate levels of awareness and practices.[9],[10],[11],[12],[13],[14],[15] However, standard assessment tools are debatable, rendering comparison a challenge.[16] Therefore, we recommend baseline assessment in different study areas before implementing a public health approach to address this issue.

Our university has a population of 25,000 students and is in a semiurban area of central Saudi Arabia.[17] To the best of our knowledge, no study has been done that focuses on the adolescent population during the COVID pandemic to assess the underlying causes of CVS. Our study estimated the level of awareness of CVS and causes and current practices using digital devices and their determinants among university students.


   Methods Top


The institution's ethical committee approved this survey. It was conducted from June 2020 to August 2020, and all students at our university were invited to participate through department e-mails. Those providing informed written consent were included in the survey. All the ethical principles of the Declaration of Helsinki were strictly followed.

To calculate the sample for the proposed survey, we assumed that the level of awareness of acceptable quality would be approximately 34.1% of a total population of 25,000 university students (12). To achieve a 95% confidence interval and 5% acceptable margin of error with a clustering effect of 1.5, we needed to survey 511 students. We used OpenEpi software to calculate a sample size for this cross-sectional survey.[18] We used a Google platform for this web-based survey. The questionnaire included demographic information such as gender, age, and department enrolment. There were three questions on knowledge related to CVS, the effect of using digital devices on ocular health, and following the 20-20-20 rule to avoid CVS. There were 11 questions on each student's practices using digital devices [Appendix 1]. For a correct answer, a score of 1 was awarded, and for an incorrect or “do not know” answer, a score of 0 was assigned. If the student's response was “never,” “occasionally,” “frequently,” or “always,” a score of 0–3 was assigned. The sum of knowledge-related responses and the sum of practice-related responses for each participant were graded as very poor, poor, good, and excellent. Scores of good and excellent were considered acceptable. The knowledge and practice score-based grades were associated with independent determinants such as gender, age, department, the main digital device used, and the purpose of device use. We used a Statistical Package for the Social Studies SPSS 25 (IBM, NY, USA to undertake univariate parametric analysis. For qualitative variables, we presented number and percentage proportions. For quantitative variables, we calculated the median and interquartile range. The group of acceptable versus poor knowledge and practices was validated by estimating the odds ratio, its 95% confidence interval, and two-sided P value. A P < 0.05 was considered statistically significant.




   Results Top


In this survey, a total of 521 students participated with a mean age of 21.8 ± 2.7 years. The profile is presented in [Table 1]. Gender and age group distribution were fair. Students in health studies programs and students without spectacles were one-third of the surveyed population.
Table 1: Profile of Saudi college students surveyed for awareness and practices for preventing computer vision syndrome related to usage of digital devices

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The median score for knowledge of CVS and relation to digital device use was 1.0 (IQR 1.0; 2.0). [Figure 1] shows the level of awareness based on these scores. More than half of the students had poor knowledge of CVS. The participants with either acceptable or poor knowledge grades were associated with different independent determinants. [Table 2] shows that students in health studies had better knowledge than other students (P = 0.004). Smartphone users had poorer knowledge than users of other devices (P = 0.017).
Figure 1: Distribution of surveyed college students by the grades of knowledge about computer vision syndrome related to usage of digital devices. The total score of knowledge related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score

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Table 2: Determinants of knowledge score grade of digital device use and computer vision syndrome among Saudi college students

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The median practice score for digital device usage was 6.0 (4.0; 9.0). The grade of practice is shown in [Figure 2], based on scores. More than half of the surveyed students did a poor job protecting their eyes from CVS while using their digital devices. The participants with either acceptable or poor practice grades were associated with different independent determinants. [Table 3] shows that females (P < 0.001) and students in health studies (P = 0.004) were more significantly associated with acceptable practices for using digital devices.
Figure 2: Distribution of surveyed college students by grades of practices for preventing computer vision syndrome while using digital devices. The total score of Practice related responses on comparison to the gold standard were grades in 25% percentile. Excellent ≥75% score, good = 51%–75% score, poor = 26%–50% score and very poor = 0–25 score

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Table 3: Determinants of practice score grade of digital device usage and computer vision syndrome among Saudi college students

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   Discussion Top


Highlight of results

The awareness of and practices for using digital devices and preventing CVS were poor in more than half of the college students in the study. Health students had better knowledge than other students. Those using a smartphone as their main device had worse knowledge than users of other devices. The digital device usage norms showed better practices by females and health students than males and students in other departments.

Strength of the study

The study shows adolescents' knowledge of CVS and practices using digital devices in a semiurban area of Saudi Arabia. Relatively less awareness and poor practices were reflected in a high prevalence of CVS in this population. The study findings indicate that urgent remedial actions are needed to improve knowledge and adopt better practices while using digital devices to prevent the progression of CVS.

Knowledge about computer vision syndrome

Knowledge of CVS in the study was poor in more than half of the surveyed students. This is better than the 82.7% with poor knowledge among IT professionals and college students in Karnataka, India, but similar to the knowledge noted in students in Kenya.[13],[19] In a study in Western India, nearly 23% of medical students had little knowledge of CVS and the norms of using digital visual terminals (DVTs).[12] This supports the need for urgent health promotion to improve knowledge among young populations to address CVS and its negative effects on human working capabilities.

Practice of using digital devices and eye health

There are several standard norms established to work with digital devices to reduce CVS. Among the studied population, the level of practice was also poor in more than half of the students surveyed. A study in Kenya showed that four in ten students also had poor practices while working with DVTs.[20] One explanation for these poor practices is the lockdown during the COVID pandemic because limited socialization and spending more time in isolation increased the use of DVTs as the only means of interacting with friends, teachers, and colleagues.[15] It will be interesting to assess practices of the same cohort after mobility restrictions are lifted.

Level of awareness for using digital devices

There is a difference in the level of awareness and practices for using DVTs among health studies students compared with those of other departments in our study. George et al. also noted average-level knowledge among as many as 70% of surveyed engineering students.[20] Even the staff working in a hospital had inadequate knowledge of CVS in Nepal.[21] This indicates that health promotion material to improve awareness and practices to prevent CVS should be target specific.

Devices and computer vision syndrome

Students using a smartphone as their primary digital device compared with other devices such as tablets, desktop computers, and laptops had poorer awareness and practices. This could be because of the ease of holding a smartphone in inappropriate positions, the angle of viewing, and ease of use in poor ambient light. While working on other devices, the user is often forced to sit in a workplace in which standard norms are followed regarding distances from digital devices, illumination, and larger fonts. Smartphones are used for a longer duration in a day than other devices, leading to poorer safety practices that result in a higher risk of CVS in people using smartphones more than other devices.[22]

Limitations

There were few limitations in our study. The study included participants of one university of central Saudi Arabia. The participants being computer literate may not represent population without such facilities (which is rare in KSA). Therefore, extrapolation of our study outcomes to the entire adult population of Saudi Arabia should be done with a caution. Environmental factors while using digital devices were not documented. Hence, known risk factors such as illumination, timing of working on digital devices impact of air conditioning in room could not be studied.


   Conclusions Top


The positive impact of a structured teaching program was noted in improving awareness and digital device use among secondary school students.[14] Using personal protective measures and refractive corrections were recommended to the health staff in Nepal to reduce CVS by adopting healthy practices while using digital devices.[21] The level of knowledge also improved from 3% to 68.3% among medical coding trainees after they participated in video teaching programs.[23] These programs suggest some of the known and accepted measures to address CVS, including taking frequent breaks while working with digital devices, blinking while working, using the correct strength of computer eyewear, maintaining a standard distance between the visual display screen and the eye, following the 20-20-20 rule, having adequate lighting while working with digital devices, and using lubricating eye drops. We also suggested these interventions to students, and after these training sessions, students evaluated their impact on awareness and safety practices.

Acknowledgments

We thank the administrators as well as faculty members for their support in mobilizing the college students to participate in this study

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Randolph SA. Computer vision syndrome. Workplace Health Saf 2017;65:328.  Back to cited text no. 1
    
2.
Mylona I, Deres ES, Dere GS, Tsinopoulos I, Glynatsis M. The impact of internet and videogaming addiction on adolescent vision: A review of the literature. Front Public Health 2020;8:63.  Back to cited text no. 2
    
3.
Chawla A, Lim TC, Shikhare SN, Munk PL, Peh WC. Computer vision syndrome: Darkness under the shadow of light. Can Assoc Radiol J 2019;70:5-9.  Back to cited text no. 3
    
4.
Boadi-Kusi SB, Adueming PO, Hammond FA, Antiri EO. Computer vision syndrome and its associated ergonomic factors among bank workers [published online ahead of print, 2021 Apr 5]. Int J Occup Saf Ergon 2021;1-8.  Back to cited text no. 4
    
5.
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.  Back to cited text no. 5
    
6.
Parihar JK, Jain VK, Chaturvedi P, Kaushik J, Jain G, Parihar AK. Computer and visual display terminals (VDT) vision syndrome (CVDTS). Med J Armed Forces India 2016;72:270-6.  Back to cited text no. 6
    
7.
Li R, Ying B, Qian Y, Chen D, Li X, Zhu H, Liu H. Prevalence of Self-Reported Symptoms of Computer Vision Syndrome and Associated Risk Factors among School Students in China during the COVID-19 Pandemic. Ophthalmic Epidemiol 2021:1-11.  Back to cited text no. 7
    
8.
Rosenfield M. Computer vision syndrome: a review of ocular causes and potential treatments. Ophthalmic Physiol Opt 2011;31:502-15.  Back to cited text no. 8
    
9.
Jaiswal S, Asper L, Long J, Lee A, Harrison K, Golebiowski B. Ocular and visual discomfort associated with smartphones, tablets and computers: what we do and do not know. Clin Exp Optom 2019;102:463-77.  Back to cited text no. 9
    
10.
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;11:17-9.  Back to cited text no. 10
    
11.
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.  Back to cited text no. 11
    
12.
Patil A,Bhavya, Chaudhury S, Srivastava S. Eyeing computer vision syndrome: Awareness, knowledge, and its impact on sleep quality among medical students. Ind Psychiatry J 2019;28:68-74.  Back to cited text no. 12
[PUBMED]  [Full text]  
13.
Mondal A, Shirin A. Assessment of Knowledge and Awareness About Computer Vision Syndrome Among IT Professionals and College Students. RGUHS Journal of Allied Health Sciences 2021;1:11-9.  Back to cited text no. 13
    
14.
Upadhyaya A, Joshi R. An evaluation of knowledge and attitude amongst adolescents of Ahmedabad towards computer vision syndrome and effectiveness of structured teaching programme. Int J Health Sci Res (IJHSR) 2014;4:191-8.  Back to cited text no. 14
    
15.
Cacodcar JA, Raiturcar TP, Fernandes RR, Dessai SR, Kantak VS, Naik R. Knowledge, attitudes and practices of computer vision syndrome among medical students in Goa. Epidemiol Int 2021;6:9-14.  Back to cited text no. 15
    
16.
Seguí Mdel M, 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;68:662-73.  Back to cited text no. 16
    
17.
Prince Sattam bin Abdulaziz University, Al Karj, Riyadh, Saudi Arabia. Available from: https://www.psau.edu.sa/en. [Last accessed on 2021 Sep 20].  Back to cited text no. 17
    
18.
Dean AG, Sullivan KM, Soe MM. OpenEpi: Open Source Epidemiologic Statistics for Public Health, Version. Available from: https://www.OpenEpi.com. [Last accessed on 2021 Sep 20; Last updated on 2013 Apr 06].  Back to cited text no. 18
    
19.
Muma S, Aduda DO, Onyango PO. Uptake of conventional interventions, level of awareness and perception on computer vision syndrome: a cross-sectional study among University students, Kenya. Ophthalmology Journal 2021;6:1-9.  Back to cited text no. 19
    
20.
George A, Thomas A, Nair AS, Varghese B, Joseph J, Subash M, et al. A study to assess the level of knowledge regarding computer vision syndrome among engineering students in a selected college at Kottayam. Int J Nurs Educ Res 2021;9:226-9.  Back to cited text no. 20
    
21.
Gautam PS, Prakash UC, Dangol S. Study on knowledge and prevalence of computer vision syndrome among computer operators in Nobel medical college teaching hospital, Biratnagar, Nepal. J Nobel Med Coll 2020;9:45-9.  Back to cited text no. 21
    
22.
Loebis R, Subakti Zulkarnain B, Zahra N. Correlation between the exposure time to mobile devices and the prevalence of evaporative dry eyes as one of the symptoms of computer vision syndrome among senior high school students in east Java, Indonesia. J Basic Clin Physiol Pharmacol 2021;32:541-5.  Back to cited text no. 22
    
23.
Mohan Kumar BK, Thiruvalluvan GT, Arjunan MK. Effectiveness on knowledge about computer vision syndrome among medical coding trainee in medical coding training institute in urban Chennai, Tamil Nadu – A cross- sectional study. J Family Med Prim Care 2021;10:228-31.  Back to cited text no. 23
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    Figures

  [Figure 1], [Figure 2]
 
 
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  [Table 1], [Table 2], [Table 3]



 

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