CROSSMARK_Color_Squarehttps://doi.org/10.35845/kmuj.2023.23402                             ORIGINAL ARTICLE

 

Impact of screen time on digital eye strain and visual acuity among medical students in Peshawar, Pakistan

Iqbal Haider1, Muhammad Osama2, Nazli Gul3 Description: Description: Description: C:\Users\Asghars\Downloads\email corrspondence.gif, Asad Rehman Khattak4

 

1: Department of Medicine, Khyber Medical College, Peshawar, Pakistan

2: House Officer, Khyber Teaching Hospital, Peshawar, Pakistan

3: Department of Ophthalmology, Khyber Medical College, Peshawar, Pakistan

4: Final Professional MBBS Student, Khyber Medical College, Peshawar, Pakistan

 

Email Description: Description: Description: C:\Users\Asghars\Downloads\email corrspondence.gif: drnazli83@gmail.com

Contact #: +92-333-9428038

Date Submitted: July11, 2023

Date Revised: November15, 2023

Date Accepted: November 17, 2023

THIS ARTICLE MAY BE CITED AS: Haider I, Osama M, Gul N, Khattak AR. Impact of screen time on digital eye strain and visual acuity among medical students in Peshawar, Pakistan. Khyber Med Univ J 2023;15(4):229-34. https://doi.org/10.35845/kmuj.2023.23402

 

ABSTRACT:

OBJECTIVES:         To determine the impact of screen time with digital eye strain (DES), visual acuity, and near point of accommodation (NPA).

METHODS: This cross-sectional study was conducted at Khyber Medical College Peshawar, Pakistan. This study included 244 students of 3rd year to 5th year MBBS, who consented to participate. A Snellen chart and Royal Air Force (RAF) rule were used to assess the visual acuity, and NPA. Chi-Square, Pearson Correlation, and multiple regression analyses were conducted using SPSS software.

RESULTS: Out of 244 participants, 181 (74.1%) reported at least one symptom of digital eye strain. Headache (n=87;35.6%) and eye pain (n=64; 26.22%) were the most common reported symptoms. Refractive error was reported in 98 (40.16%) students, including myopia (n=86; 35.25%), hyperopia (n=12; 4.92%), and astigmatism (n=12; 4.92%). Mobile (n=244; 100%) and Laptop (n=212; 86.90%) were the main electronic gadgets used by participants. Headache, eye pain, tearing of the eyes, eye redness, and itching of the eyes were significantly associated with screen time (p<0.05). Headache, blurred vision, itching of eyes, and eye pain were significantly associated with refractive error (p<0.05). Multiple regression analysis explains a 32.9% variance in the digital eye strains.

CONCLUSION: This study reveals a concerning 74.1% prevalence of DES among medical students in Peshawar, Pakistan, emphasizing the impact of prolonged screen time on ocular health. Our study reveals a significant link between screen time and DES, with headache & eye pain being the prevalent symptoms. Associations between symptoms, screen time, and refractive errors emphasize the relevance of these factors.

KEYWORDS: Asthenopia (MeSH); Accommodation (Non-MeSH); Ocular (Non-MeSH); Screen Time (MeSH); Visual Acuity (MeSH); Vision, Ocular (MeSH); Refractive Errors (MeSH); Headache (MeSH); Eye Pain (MeSH).

INTRODUCTION

Electronic displays are integral to our daily routines, whether at home, work, during travel, or for leisure. The ubiquity of desktops, laptops, tablets, smartphones, electronic reading devices, and similar digital gadgets in the modern world is undeniable.1Prolonged usage of such devices may increase eye discomfort andvision problems. Factors such as screen glare, poor sitting posture, inadequate lighting, and incorrectviewing distances exacerbate the detrimental effects. Blurry vision, dry eyes, neck/shoulder pain, and eye strain have been reported due to increased screen time. These issues are described ascomputer vision syndrome (CVS)/ digital eye strain (DES), and increased device usage cause these symptoms to worsen over time.2

A survey including 10,000 respondents in the US pointed out that 65% of people, the majority of females, had self-reported symptoms of DES, with people using two or more devices simultaneously affected more frequently.3 A cross-sectional study in Spain reported that 76% of students had CVS, with headache and itchingbeing the most common symptoms.4 Another study in Malaysia identified a prevalence of 89.9% amongst university students, with headache and eye strain being the most frequently reported. Moreover, significantly more symptoms were felt by those on their computer for over 2 hours a day.5Similarly, 67.8% and 48% of Pakistani medical students suffered from headaches and eye strain,respectively. A positive association was found between screen time and difficulty in refocusing eyes and eye redness, whereas no association with any other symptoms was found.6 A descriptive study in Peshawar ranked tired eyes (71.8%), neck/back pain (70.1%), and headache (42.3%) as the top three most common complaints amongst university students, all of which had a significant association with screen usage of more than 5 hours a day.7

This study, focusing on uncovering the magnitude of DES and exploring its impact on screen time, near-point accommodation, and visual acuity, addresses a notable gap in the literature. While existing research acknowledges the link between electronic device usage and DES prevalence, particularly in the South Asian population, including Pakistan, there is a scarcity of local studies investigating the impact of screen time with DES and visual parameters. By providing research and statistical evidence, this study aims to enhance the understanding of the widespread issue of DES exacerbated by prolonged screen time. It also lays the groundwork for future local and international studies on related concepts.

METHODS

This cross-sectional study was conductedfrom May 20, 2023 to July 1, 2023, at Khyber Medical College Peshawar, Pakistan.Third-year to Final-year MBBS studentswere enrolled using a convenient consecutive sampling technique.Based on prior research carried out in Karachi,8a sample size of 244 students was determined utilizing the sample size calculator of Calculator.net with a population proportion of 67.2%, a confidence interval of 95%, and amargin of error of 5%. Participants of this study comprisedof third- to final-year MBBS students who were free from any chronic ophthalmic diseases and consented to be included in the study.

Participants who declined to participate or had conditions such as glaucoma, myasthenia gravis, retinitis pigmentosa, chronic diabetes, chronic renal disease, or hypertension were excluded from the study. While we implemented rigorous exclusion criteria to maintain focus on investigating DES, we acknowledge that this approach might introduce bias. Recognizing that this selection criterion could limit the generalizability of our findings, future research may consider including participants with these medical conditions to enhance understanding of DES across diverse health profiles.

Ethical approval was obtained from The Ethical Board of Khyber Medical College Peshawar (Ref# 298/DME/KMC; Dated 22-5-2023).The Snellen Optometric chart (working distance 20 feet(6.1m), size: 23x35.5, approximate thickness 0.8 to 1.0mm) (Gima S.p.A. Via Marconi, 1-20060 Gessate) was used to assess the best corrected visual acuity, at KTH, Peshawar by an ophthalmologist having a minimum 5-year post-graduate experience. Royal Air Force (RAF) rule(2023 Bernell Corporation. 4016 North Home Street, Mishawaka, IN, 46545 USA) (consisting of a 50cm long rule with a slider holding a rotating four-sided cube) was used to measure NPA (Near point of accommodation).The NPA was measured using the RAF Rule and standard targets such as the Times Roman Typeface, Reduced Snellen chart, etc. The measurement was carried out with full refractive correction in normal room illumination, where the examiner placed the cheek rest on the inferior orbital margin while holding the ruler. Afterthis, the patients were requested to focus on the target, and the examiner gradually pushedthe drum towards the patients’ eyes at a stable rate of about 1-2 cm per second.9,10

Information regarding participants' biodata, screen time, and DES symptoms was gathered through a meticulously crafted self-administered questionnaire. To ensure the questionnaire's content validity, a pilot study involving ten students was conducted, and these participants were subsequently excluded from the main study to minimize potential biases. Construct validity was assessed using Lynn criteria, involving six subject experts and a predefined threshold of 0.80. Data analysis was performed utilizing IBM SPSS Statistics software (Version 26.0), employing statistical tests such as Chi-square, Pearson correlation, and multiple regression analyses.

RESULTS

 

Out of 244 participants, 164 (67.2%) were males and 80 (32.8%) were females. Mean age of male and female students was 22.00±1.41 and 21.96±1.43 years respectively.

Most of the study participants were from 3rd year of MBBS (n=131; 53.69%), followed by 5thyear MBBS (n=67; 27.46%), and 4th-year MBBS (n=46; 18.85%).Three (1.20%) study participants had ocular diseases (one each having amblyopia, color blindness, and keratoconus), while the remaining all (n=241; 98.80%) were not having any ocular disease.Refractive error was reported in 98 (40.16%) students, including 86 (35.25%) cases of myopia, 12 (4.92%) cases of hyperopia, and 12 (4.92%) cases of astigmatism (Individuals with astigmatism have coexisting myopia or hyperopia, which is why their count does not add up to the total of refractive errors).

Mobile (n=244; 100%), Laptop (n=212; 86.90%), Television (n=93; 38.10%), and tablet as (n=18; 7.40%) were the main electronic gadgets used by participants.

Out of 244 students, 181(74.1%) individuals reported at least one symptom of DES. Amongst the symptoms, 87(35.6%) participants reported headache as the main symptom. Headache, eye pain, tearing of the eyes, eye redness, and itching of the eyes were significantly associated with screen time(P<0.05)(Table I).

 

Table I: Screen time association with digital eye strain symptoms

Symptoms

Response

Number of hours daily

Chi-Square

P-value

1-4

(n=63)

5- 8

(n=149)

Above 8

(n= 32)

Total (n=244)

Headache

Yes

5 (7.9%)

70 (46.9%)

12 (37.5%)

87 (35.65%)

<0.001

No

58 (92.06%)

79 (53.02%)

20 (62.5%)

157 (64.34%)

Eye pain

Yes

3 (4.7%)

47 (31.5%)

14 (56.25%)

64 (26.22%)

<0.001

No

60 (95.23%)

102 (68.45%)

18 (56.25%)

180 (73.77%)

Itching of eyes

Yes

5 (7.9%)

33 (22.14%)

9 (28.12%)

47 (19.26%)

0.022

No

58 (92.06%)

116 (77.85%)

23 (71.87%)

197 (80.73%)

Eye redness

Yes

3 (4.7%)

33 (22.14%)

10 (31.25%)

46 (18.85%)

0.002

No

60 (95.23%)

116 (77.85%)

22 (68.75%)

198 (81.14%)

Blurring of vision

Yes

4 (6.3%)

28 (18.7%)

8 (25%)

40 (16.39%)

0.3

No

59 (93.65%)

121 (81.20%)

24 (75%)

204 (83.60%)

Burning of eyes

Yes

3 (4.7%)

22 (14.7%)

4 (12.5%)

29 (11.88%)

0.12

No

60 (95.23%)

127 (85.23%)

28 (87.5%)

215 (88.11%)

Shoulder pain

Yes

4 (6.3%)

21 (14.03%)

2 (6.25%)

27 (11.06%)

0.168

No

59 (93.65%)

128 (85.90%)

30 (93.75%)

217 (88.93%)

Tearing of eyes

Yes

3 (4.7%)

14 (9.3%)

7 (21.87%)

24 (9.8%)

0.029

No

60 (95.23%)

135 (90.60%)

25 (78.12%)

220 (90.16%)

Double vision 

Yes

0 (0%)

4 (2.6%)

0 (0%)

4 (1.6%)

0.274

No

63 (100%)

145 (97.31%)

32 (100%)

240 (98.36%)

 

The frequency of DES symptoms was higher in 131 (53.6%) students with a screen time of 5-8 hours compared to 33 (13.52%) and 17 (6.9%) participants with screen times above 8 hours and below 4 hours, respectively. However, no significant association was found between visual acuity and screen time (p>0.05)[Table II].

Table II: Screen time association with visual acuity

Visual Acuity

Screen Time

Chi-Square

P-value

Number of hours daily

1-4

(n=63)

5- 8

(n=149)

Above 8

 (n=32)

Total (n=244)

Right Visual

Acuity

Low

11 (17.4%)

27 (18.12%)

9 (28.12%)

47 (19.26%)

0.392

Normal

52 (82.6%)

122 (81.88%)

23 (71.88%)

197 (80.74%)

Left Visual

Acuity

Low

11 (17.4%)

28 (18.79%)

9 (28.12%)

48 (19.67%)

0.424

Normal

52 (82.6%)

121 (81.21%)

23 (71.88%)

196 (80.33%)

Duration in Years

Chi-Square

P-value

1-5

(n=57)

6-10 (n=153)

More than 10 (n=34)

Total

(n= 244)

Right Visual

Acuity

Low

15 (26.31%)

25 (16.33%)

7 (20.58%)

47 (19.26%)

0.259

Normal

42 (73.69%)

128 (83.67%)

27 (79.42%)

197 (80.74%)

Left Visual

Acuity

Low

15 (26.31%)

25 (16.33%)

8 (23.52%)

48 (19.67%)

0.225

Normal

42 (73.69%)

128 (83.67%)

26 (76.48%)

196 (80.33%)

 

The Pearson correlation between screen time and NPA, considering both total daily duration (0.044) and total monthly duration (0.016), revealed a positive correlation. However, the correlation was not statistically significant (p>0.05). Notably, headache, blurring of vision, itching of eyes, and eye pain showed a significant association with refractive error (p<0.05)(Table III).

 

Table II: Digital eye strainsymptoms association with refractive errors

 Digital Eye Strain Symptoms

Response

Refractive Errors

Chi-square

P-value

Yes

No 

Headache

Yes

46 (46.93%)

41(28.08%)

0.007

No

52 (53.06%)

105 (71.91%)

Eye Pain

Yes

39 (39.79%)

25(17.12%)

<0.001

No

59 (60.20%)

121 (82.87%)

Itching of eyes

Yes

13 (13.26%)

34 (23.28%)

0.049

No

85 (86.73%)

112 (76.71%)

Eye Redness

Yes

17 (17.34%)

29 (19.86%)

0.605

No

81 (82.65%)

117 (80.13%)

Blurring of Vision

Yes

25 (25.51%)

15 (10.27%)

0.002

No

73 (74.48%)

131 (89.72%)

Burning of Eyes

Yes

14 (14.28%)

15(10.72%)

0.506

No

84 (85.71%)

131 (89.72%)

Shoulder Pain

Yes

14(14.28%)

13(8.90%)

0.102

No

84 (85.71%)

133 (91.09%)

Tearing of eyes

Yes

12 (12.24%)

12(8.21%)

0.167

No

86 (87.75%)

134 (91.78%)

Double vision

Yes

2 (2.04%)

2(1.36%)

0.772

No

96 (97.95%)

144 (98.63%)

 

The majority of students, constituting 114 (46.72%), indicated that when they experienced these symptoms, their preferred action was to take a short rest. In contrast, 82 (33.6%), 63 (25.81%), 45 (18.4%), and 11 (4%) chose options such as doing nothing, massaging their eyes and head, frequent blinking of eyes, and consulting doctors, respectively. Among the participants, 58 students (23.7%) had consulted an ophthalmologist due to DES symptoms, and 115 students (47.13%) regarded these symptoms as problematic. Conversely, 129 students (52.88%) did not view these symptoms as a serious problem.

The multiple regression model indicated that gender, refractive error, and daily screen time (in hours) demonstrated significant predictability for the dependent variable, DES, F(4,237) = 30.680, (p < 0.001). Moreover, the adjusted R square of 0.329 suggests that the model accounts for 32.9% of the variance in DES(Table IV).

Table IV: Multiple regression analysis of digital eye strain with associated factors

Associated variables

Unstandardized Coefficients

Standardized Coefficients

T

P value

B

SE

Beta

(Constant)

0.775

0.404

1.920

0.056

Age

-0.16

0.017

-0.053

-0.976

0.330

Gender

-0.108

0.050

-0.118

-2.150

0.033

Refractive Error

-0.150

0.047

-0.170

-3.211

0.002

Screen time(hrs)

0.382

0.038

0.540

10.122

0.001

Dependent Variable: Digital eye strain; R2 = 0.340; F(4,237)= 30.680

 

DISCUSSION

The prevalence of DES symptoms in our study conducted amongst medical students of Peshawar was 74.1%. According to some of the metanalysis, the pooled prevalence of DES was 66%,1174.4%,12and 73.21%.13 According to a study conducted among health students in Saudi Arabia,97.3% of them had at least one symptom.14 Other studies, including those conducted in Spain, Ethiopia, andIndia, showed a prevalence of 76.6%,470.4%,15and 83%16 respectively.

In our study, headache was the most common symptom reported (35.6%). Other studies reportedTeary Eyes (40.06%)17and headache (61.4%)18and(66.5%)19 as the most common symptom.Multiple variables are involved in the causation of headaches. Some studies hypothesized that prolonged and recurrent adjustments made by the eyes and extraocular musculature result in muscular stress and ocular fatigue, ultimately resulting in headaches.20

Our study had a significant association ofscreen time withheadache, eye pain, tearing of the eyes, eye redness, and itching of the eyes. According to a study conducted in Saudi Arabia, using video display terminal devices for longer than 5 hours was associated with experiencing CVS symptoms.21Another study has shown a positive association between high screen time and difficulty in refocusing and eye redness, while there was no significant association between high screen time and headache, blurred vision, eye strain, etc.6Another study conducted onundergraduate medical and dental students of Karachi also found a significant association between screen time and CVS.8

In our study, screen time and NPAwere positively correlated but not statistically significant. Close to eyes screen work can cause ciliary muscle spasms, leading to degraded accommodative functions.22

This study did not find significant impact between screen time and visual acuity. One of the studies conducted in China also deniedan association between these two variables.23 This research document that headache, blurring of vision, and eye pain were significantly associated with refractive error, whereas one study in Saudi Arabiadisproved the association between refractive error and DES symptoms.24Studies have shown that people with myopia have higherscreen time relative to those who don’thave myopia.25This finding is also documented in the current study.

Being a cross-sectional study,we cannot establish the causal association between the identified risk factors and DES. This study was conducted among medical students of a single medical college which may limit the generalizability of the findings to a broader population and limit the applicability of the findings to different demographic groups. DES symptoms were self-reported which may introduce subjective bias. In the future, longitudinal studies must be designed to establish the cause-effect association.Expanding the scope of the research could involve conducting multicenter prospective cohorts.National and local Ophthalmology Societies should come forward to develop and implement guidelines for the effective management of DES in our setup to reduce its burden. 

It is necessary to guarantee ergonomic environments as a precautionary measure against DES.26It is recommended to follow the rule of 20,20,20, which says that after every 20 minutes, one should rest for 20 seconds byfocusing on an object 20 feet away.21

DES is a common problem in medical students and is associated with high screen time and refractive error. It is the need of the hour to increase awareness, especially among the younger generations. In a digitalized world, it is of the utmost importance to focus on preventive measures to alleviate the negative effects of excessive screen time. Students should take DES seriously, consider consulting a doctor on time for these symptoms, and are advised to incorporate preventive steps like the 20/20/20 rule into their daily routine.

CONCLUSION

This study reveals a notable 74.1% prevalence of digital eye strain symptoms among medical students in Peshawar, Pakistan, highlighting the influence of prolonged screen time on ocular health. Headache emerged as the predominant symptom, and a significant association was identified between screen time and various DES symptoms. While positive correlations with near point of accommodation were noted,they lacked statistical significance, as did associations between screen time and visual acuity. Despite its limitations, the research emphasizes the complex aspects of DES and the need for increased awareness. Further research is required to provide comprehensive insights into DES, improve its effective management, and advance our understanding of ocular health among students and scholars who engage in prolonged screen time.

ACKNOWLEDGEMENT

The authors acknowledge the contribution of Mr. Muhammad Ibrahim, Institute of Public Health and Social Sciences, Khyber Medical University, Peshawar, Pakistan in the data analysis of this research

 

REFERENCES

 

1.      Rosenfield M, Howarth PA, Sheedy JE, Crossland MD. Vision and IT display a whole new visual world. Ophthalmic Physiol Opt 2012;32(5):363-6. https://doi.org/10.1111/j.1475 1313.2012.00936.x

2.  American Optometric Association. Computer vision syndrome [Internet]. Accessed on:July 04, 2023. Available from URL: https://www.aoa.org/healthy-eyes/eye-and-vision-conditions/computer-vision-syndrome

3.  Council V. Eyes overexposed: The digital device dilemma. Alexandria, VA: The Vision Council.2016.Accessed on: July 04, 2023. Available from URL:https://www.kodaklens.us/wp-content/uploads/2017/03/TheVisionCouncil_2016EyeStrain_Report_WEB.pdf

4.  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 2021;75(3):e13681. https://doi.org/10.1111/ijcp.13681. Erratum in: Int J Clin Pract 2021;75(12):e15017. https://doi.org/10.1111/ijcp.15017

5.  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(2):161-8. https://doi.org/10.3126/nepjoph.v5i2.8707

6.  Nisar N, Salman R, Farooq S. Screen Time and its Relation with Ophthalmic Problems among Medical Students. Pak J Med Health Sci 2022;16(12):295-9.https://doi.org/10.53350/pjmhs20221612295

7.  Hadi KN, Rehman MH, Toru HK, Orakzai AA, Khalid S, Iftikhar B. Assessment of Computer Vision Syndrome in University Students in Peshawar: A Descriptive Cross-Sectional Study. Stetho 2021; 2(6):6-14.

8.  Tehreem F, Tahira Z. Prevalence of Computer Vision Syndrome and Its Associated Risk Factors among Under Graduate Medical Students of Urban Karachi. Pak J Ophthalmol 2016;32(3):106. https://doi.org/10.36351/pjo.v32i3.106

9.  Goyal A, Mandawat N, Joshi A. RAF RULE: A Double Edge Weapon. Global JRes Anal 2020;9 (8):21-2. https://doi.org/10.36106/gjra

10.  Hashemi H, Pakbin M, Ali B, Yekta A, Ostadimoghaddam H, Asharlous A, et al. Near Points of Convergence and Accommodation in a Population of University Students in Iran. J Ophthalmic Vis Res 2019;14(3):306-14. https://doi.org/10.18502/jovr.v14i3.4787

11.  Anbesu EW, Lema AK. Prevalence of computer vision syndrome: a systematic review and meta-analysis. Sci Rep 2023;13(1):1801. https://doi.org/10.1038/s41598-023-28750-6

12.  Dimitrijević V, Todorović I, Viduka B, Lavrnić I, Viduka D. Prevalence of computer vision syndrome in computer users: A systematic review and meta-analysis. Vojnosanit Pregl 2023;80(10):860-70.https://doi.org/10.2298/VSP220301024D

13.  Adane F, Alamneh YM, Desta M. Computer vision syndrome and predictors among computer users in Ethiopia: a systematic review and meta-analysis. Trop Med Health 2022;50(1):26. https://doi.org/10.1186/s41182-022-00418-3

14.  Altalhi A, Khayyat W, Khojah O, Alsalmi M, Almarzouki H. Computer Vision Syndrome Among Health Sciences Students in Saudi Arabia: Prevalence and Risk Factors. Cureus2020;12(2):e7060. https://doi.org/10.7759/cureus.7060

15.  Zenbaba D, Sahiledengle B, Bonsa M, Tekalegn Y, Azanaw J, Kumar Chattu V. Prevalence of Computer Vision Syndrome and Associated Factors among Instructors in Ethiopian Universities: A Web-Based Cross-Sectional Study. Scientific World J 2021;2021:3384332. https://doi.org/10.1155/2021/3384332

16.  Garg S, Mallik D, Kumar A, Chunder R, Bhagoliwal A. Awareness and prevalence of computer vision syndrome among medical students: A cross-sectional study. Asian J Med Sci 2021:12(9):44-8. https://doi.org/10.3126/ajms.v12i9.37247

17.  Akowuah PK, Nti AN, Ankamah-Lomotey S, Frimpong AA, Fummey J, Boadi P, et al. Digital device use, computer vision syndrome, and sleep quality among an African undergraduate population. Adv Public Health 2021;2021:1-7.https://doi.org/10.1155/2021/6611348

18.  Nwankwo B, Mumueh K, Olorukooba A, Usman N. Computer vision syndrome:prevalence and associated risk factors among undergraduates in a tertiary institution in northwestern Nigeria. Kanem J Med Sci 2021;15(1):1-8.https://doi.org/10.36020/kjms.2021.1501.003

19.  Arshad S, Qureshi MF, Ali M, Piryani K, Shafqat K, Mateen M, et al. Computer vision syndrome: prevalence and predictors among students. Ann Psychophysiol 2019;6(1):15-22.https://doi.org/10.29052/2412-3188.v6.i1.2019.15-22

20.  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. https://doi.org/10.1186/s13104-016-1962-1

21.  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. https://doi.org/10.1177/1120672118815110

22.  Kang JW, Chun YS, Moon NJ. A comparison of accommodation and ocular discomfort change according to display size of smart devices. BMC Ophthalmol 2021;44(1):1-9.https://doi.org/10.1186/s12886-020-01789-z

23.  Chen Y, Chen YA, Gui Z, Bao W, Zhang J, Tan K, et al.  Association of sedentary behaviors with visual acuity among primary school students: a cohort study. Chinese J School Health 2021;42(8):1144-7. https://doi.org/10.16835/j.cnki.1000-9817.2021.08.006

24.  Abudawood GA, Ashi HM, Almarzouki NK. Computer vision syndrome among undergraduate medical students in King Abdulaziz University, Jeddah, Saudi Arabia. J Ophthalmol 2020;2020:1-7.https://doi.org/10.1155/2020/2789376

25.  Moon JH, Kim KW, Moon NJ. Smartphone use is a risk factor for pediatric dry eye disease according to region and age: a case-control study. BMC Ophthalmol 2016;16(1):188. https://doi.org/10.1186/s12886-016-0364-4

26.  Coles-Brennan C, Sulley A, Young G. Management of digital eye strain. Clin Exp Optom 2019;102(1):18-29. https://doi.org/10.1111/cxo.12798

 

AUTHORS' CONTRIBUTIONS

Following author have made substantial contributions to the manuscript as under:

IH: Concept and study design, acquisition, analysis and interpretation of data, drafting the manuscript, critical review, approval of the final version to be published

MO& AR: Acquisition of data, drafting the manuscript, approval of the final version to be published

NG: Concept and study design, analysis and interpretation of data, critical review, approval of the final version to be published

Authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

 

CONFLICT OF INTEREST

Authors declared no conflict of interest, whether financial or otherwise, that could influence the integrity, objectivity, or validity of their research work.

GRANT SUPPORT AND FINANCIAL DISCLOSURE

Authors declared no specific grant for this research from any funding agency in the public, commercial or non-profit sectors

 

DATA SHARING STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request

 

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