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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 33  |  Issue : 3  |  Page : 263-268

Ocular morbidity due to the usage of handheld digital devices: A population-based cross-sectional study using a validated questionnaire


Department of Ophthalmology, Thrikkakara Municipal Co-operative Hospital, Ernakulam, Kerala, India

Date of Submission30-Dec-2020
Date of Decision06-Feb-2021
Date of Acceptance23-Mar-2021
Date of Web Publication08-Dec-2021

Correspondence Address:
Dr. M Manju
Department of Ophthalmology, Thrikkakara Municipal Co-operative Hospital, Seaport Airport Road, Near Collectorate Kakkanad (PO), Ernakulam - 682 030, Kerala
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/kjo.kjo_211_20

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  Abstract 


Purpose: To study the ocular morbidity exclusively due to the usage of handheld digital devices (HHDD). Materials and Methods: It is a population-based cross-sectional study using survey method. A questionnaire was prepared, and face validity was established. Pilot study with 25 participants was used to validate the questionnaire. Data were collected from 534 participants and data of 207 participants were excluded from the analysis based on the exclusion criteria. Thus, data of 327 participants were considered for the analysis purpose. Data set was divided into two depending on whether the participant used HHDD for 2 h on a day or more. Then these two groups were compared regarding the ocular morbidities. Data were analyzed using SPSS 26.0 version. Results: Out of 327 participants, 181 participants (55.4%) were males and 146 participants (44.6%) were female. Eye strain (P = 0.0252), Neck pain (P = 0.0006) and Watering of eyes (P = 0.0069) had statistically significant association with the usage of HHDD. Participants who use HHDD for more than 2 h/day were at 1.95 times of higher risk and participants with continuous usage of HHDD for >2 h/day were at 1.86 times higher risk of getting ocular morbidities than others. In HHDD users asthenopic symptoms were more compared to ocular surface-related problems. Conclusion: This study demonstrates that the long and continuous usage of HHDD has a significant association with ocular morbidity. Further studies are needed to analyze and ascertain whether the existing treatment algorithm and ocular ergonomics for computer users are enough for individual or combined usage of HHDD.

Keywords: Computer vision syndrome, handheld digital devices, ocular morbidity


How to cite this article:
Manju M. Ocular morbidity due to the usage of handheld digital devices: A population-based cross-sectional study using a validated questionnaire. Kerala J Ophthalmol 2021;33:263-8

How to cite this URL:
Manju M. Ocular morbidity due to the usage of handheld digital devices: A population-based cross-sectional study using a validated questionnaire. Kerala J Ophthalmol [serial online] 2021 [cited 2022 Jan 19];33:263-8. Available from: http://www.kjophthal.com/text.asp?2021/33/3/263/331944




  Introduction Top


Digital devices (DD) has become an integral part of our life owing to their ever-increasing significance in making our life easier. Most used DD are mobile phones, computers (desktops and laptops), E-Readers, Game consoles, etc.[1] DD could be broadly classified into two types – hand held DD (HHDD) which are usually used within 30 cm from the eye and non HHDD (NHHDD) which are used at a distance of more than 30 cm from the eye.[2]

Digital eye strain (DES) is a condition characterized by visual disturbance, ocular discomfort caused by DD. Symptoms of DES include ocular fatigue, watering of eyes, blurring of vision, burning sensation, redness, and double vision.[3] The prevalence of DES is estimated to range from 20% to 90% among visual display unit users.

Due to the recent technological advancements, HHDD are able do most of the things previously done by NHHDD. This would have a profound effect on ocular health, in general, owing to the significant reduction in the distance from the eye to the screen. Most of the initial research in relation to the usage of DD were based on computers (NHHDD). HHDD differs from computers in many parameters like viewing position and distance, font size, luminance, pattern of use, etc.[4] Hence, there can be a difference in the morbidity profile of HHDD in comparison to NHHDD. Thus, it is important to exclusively study the ocular morbidity profile of HHDD, to design specific ergonomic practices and treatment protocols. The authors evaluated available literature for the effects of HHDD on binocular vision, blinking, and ocular surface to consider potential aetiologies.


  Materials and Methods Top


Study population

The general population above 15 years of age willing to participate in the study were considered irrespective of their nativity, race, or gender.

Study design

Population-based study using a validated survey questionnaire

The sample size was calculated using the formula



where Z1–α/2 = 1.96

p = Expected proportion

d = Absolute precision.

The sample size obtained was –310

Inclusion criteria

Participants from the general population who voluntarily filled the questionnaire.

Exclusion criteria

  • Participants under the age of 15
  • Participants who were using computers for more than 2 h a day.


Data were collected using an online questionnaire with 13 multiple choice questions related to the usage of the DD. The questionnaire was circulated in social media and the resulting data maintained in a spreadsheet.

Validation of the questionnaire

Validation of questionnaire was done by 6 step validation method.

  1. Face validity of the questionnaire was established by 2 independent evaluators-a subject expert and a statistician. They ensured that the survey does not contain any errors such as leading, confusing, or double-barrelled questions
  2. Pilot study was done using 25 participants
  3. Data obtained in a spreadsheet was checked for any inconstancies
  4. Principal components analysis (PCA) was done to identify underlying components and themes that are being measured by survey questions. Kaiser-Meyer-Olkin Measure of Sampling Adequacy value obtained was 0.62. Since the PCA value was above 0.6, it was accepted
  5. Internal consistency was checked by the test-retest method. Done with 50 participants and the reliability of the questions were established by statistical analysis
  6. Revision of the questions and extension of the survey was done.


The data collected from the patients were recorded and analyzed. Descriptive analysis of the population's characteristics was carried out. Categorical variables were expressed as counts and percentages. Univariate analysis using Chi-square test was done to find out the association between the various determinants of different kinds of morbidities. Data set was divided into two depending on whether the participant used HHDD for 2 h on a day or more. Then these two groups were compared regarding the ocular morbidities. Odds ratio and 95% confidence interval were measured. Data were analyzed using IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp [Table 1].
Table 1: Validated questionnaire

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  Results Top


Demographic characteristics of the population

534 participants enrolled in the study out of which those who use laptops or desktops for more than 2 h were excluded. Data from the remaining 327 participants was analyzed. 181 participants (55.4%) were males and 146 participants (44.6%) were females. 152 participants (46%) were of the 26–35 years age group. 195 participants (59%) had any one of the ocular morbidities studied.

Participants in the age group 26–35 years constituted 47% of the morbidity reported. Among the participants with morbidities 59% were male and 41% were female. The maximum number of participants had neck pain (20%) followed by eye strain or fatigue (19%). 73% of the participants with morbidities were using HHDD for more than 2 h a day [Table 2].
Table 2: Sub group analysis

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About 48% of the participants with morbidity were not aware about the type of screen available in their HHDD. 27% of the participants with morbidity were using HHDD with LCD screens [Figure 1]. Among the participants with morbidities 45% of them had refractive errorr as a co-morbidity.
Figure 1: Pie chart comparing screen type versus ocular morbidities

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Participants with cumulative HHDD use for >2 h/day were at 1.95 times of higher risk and participants with continuous usage of HHDD for >2 h/day were at 1.86 times higher risk of getting ocular morbidities than others.

The usage of HHDD for more than 6 years showed an increase in morbidities, although the P value is not statistically significant. 80% of the participants with morbidities used HHDD for working and social media usage. Eye-related problems were more prevalent among those who used HHDD for working and reading than those who used it for watching videos and playing games. 63% of the participants in the study were using HHDD with a brightness <50%. Those participants who were using HHDD at a reduced brightness level (0–50%) had more morbidities than the others though the P value is not statistically significant. Usage of protective spectacles did not show any association to ocular morbidities.

Participants who use HHDD for more than 2 h were at 2.23 times of higher risk of having eye strain or fatigue compared to those who use HHDD for <2 h. Participants who use HHDD for more than 2 h were at 3.51 times of higher risk of getting neck or shoulder pain compared to those who use HHDD for less than 2 h [Table 3]. Participants who use HHDD for more than 2 h were at 5.31 times of higher risk of getting watering in the eyes compared to those who use HHDD for <2 h. These 3 symptoms had a direct causative association with usage of HHDD which was statistically significant 0.20% of those with morbidities had shoulder pain and 18% had eye strain or fatigue [Figure 2].
Figure 2: Pie chart showing incidence of ocular morbidities (%)

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Table 3: Analysis of ocular morbidities

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  Discussion Top


Demographic features

Analysis of 327 participants were made and 152 (46%) participants were in the age group of 26–35 years. 181 (55.4%) participants were males and 146 (44.6%) were females. 195 (0.59%) participants had either one of the ocular morbidities. Maximum morbidity (47%) seen in the age group 26–35 years. The usage of smartphones is more in younger age groups and according to a study by Coles-Brennan et al. younger individuals do more complicated tasks in smartphones. This may be a cause for more symptoms in the younger age groups.[5]

Hand held digital devices and asthenopic symptoms

When the symptomatic profile of HHDD users were analyzed, greater number of participants were having asthenopic symptoms compared to ocular surface-related symptoms. According to Jaiswal et al. HHDD has short viewing distance, small font size, which can cause more asthenopic symptoms. Furthermore, smartphone and tablet use results in reduced fusional convergence and possibly a receded near point of convergence which can result in a greater incidence of asthenopic symptoms. Reddy et al. in their study in university students found out that 19.7% had head ache and 16.4% had irritation while using DD.[6] 20% of the participants were having neck or shoulder pain. According to Al-Khlaiwi and Meo people tilt their heads at odd angles, or they bend toward the screen to see it clearly.[7] These postures can result in muscle spasms or pain in the neck or shoulder.

Hand held digital devices and ocular surface symptoms

Among the participants with morbidities ocular surface symptoms were less compared to asthenopic symptoms. According to Jaiswal et al. the available literature does not conclusively link visual discomfort symptoms or reduced blink rate with HHDD use.[4] Moon et al. did a study on primary school children in Korea and found that the dry eye symptoms were directly proportional to mobile phone usage.[8]

Participants who were using HHDD for more than 6 years had more ocular symptoms. Participants who used HHDD >2 h a day as well as its Continuous usage both showed increase in ocular morbidity. Ranasinghe et al. reported that the visual symptoms increased significantly in individuals who spent >4 h daily working on video display terminals.[2] According to AOA, symptoms occur because the visual demands of the task exceed the visual abilities of the individual to comfortably perform the task.

Participants using HHDD for watching videos and playing games was observed to be negligible in the study population. According to Parihar et al. watching videos and playing games needs more of binocular functions, accommodation, and convergence which can result in more ocular morbidities.[9] For conclusive evidence, we need studies with equal participation from all three groups. Participants using HHDD with LCD screens were found to have more mordidity than the others. Even though both LCD and LED are liquid displays, LEDs can be dimmed dramatically improving the picture quality due to high contrast ratio and may reduce the ocular symptoms.

Those participants who were using HHDD at a reduced brightness level (0–50%) had more morbidities than those using higher brightness levels. According to Jaiswal et al. it is advisable to adjust screen brightness to match the level of surrounding light.[4] In this study 30% of the participants used various types of protective glasses and it had no significant correlation to eye symptoms. According to Johansen et al. blue light cutting spectacles helps reduce exposure to Blue Light emitted from DD.[10]

Future dimensions of the study

The specific symptomatology due to the usage of HHDD was analyzed in the study. Comparative studies between the users of HHDD and Computers should be encouraged to differentiate the symptomatic profile of both and to understand the cumulative effects of their simultaneous usage. The higher incidence of asthenopic symptoms in HHDD usage warrants the development of ergonomic practices specifically for HHDD users. The various adjustments in HHDD like brightness, screens, and protective glasses should be studied thoroughly to minimize ocular morbidity.

What was known

  1. The usage of tablets and mobile phones may cause ocular symptoms
  2. A wide variety of screens are available for hand held devices like LCD, LED, OLED etc.
  3. Antiglare and blue cut spectacles are available in the market to protect eyes during usage of DD
  4. Ocular comorbidities may increase the incidence of ocular symptoms in DD users
  5. Those who are using DD can have DES.


What this study adds

  1. Longer duration (>2 h) and continuous usage (>2 h) of HHDD usage causes asthenopic symptoms more than ocular surface-related symptoms
  2. Usage of HHDD with LCD screens may cause more ocular symptoms in comparison to LED screens
  3. Protective spectacles may not necessarily reduce ocular symptoms in HHDD users
  4. Refractive error is the co-morbidity that is most associated with ocular symptoms while using HHDD
  5. Visual morbidities due to HHDD and NHHDD can have difference in their morbidity profiles with HHDD users having more of asthenopic symptoms.



  Conclusion and Recommendations Top


The continuous and constant usage of HHDD can induce ocular symptoms which has a specific profile and it may be different from the extensively studied one for computer vision syndrome (CVS). In our study of HHDD usage, we could demonstrate that Asthenopic symptoms had a significant causative association when compared to ocular surface symptoms.

Focused study examining different ocular protection features, ambient room brightness, and light reflection metrics is required to ascertain specific features of HHDD induced ocular symptoms and to establish control factors which could differentiate with the existing studies related to the usage of CVS. Further research is needed for better understanding symptoms and etiology to develop treatment algorithms and ocular ergonomics specifically made for HHDD users.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
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. 1
    
2.
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. 2
    
3.
Mashalla YJ. Impact of computer technology on health: Computer vision syndrome (CVS). Med Pract Rev 2014;5:20-30.  Back to cited text no. 3
    
4.
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. 4
    
5.
Coles-Brennan C, Sulley A, Young G. Management of digital eye strain. Clin Exp Optom 2019;102:18-29.  Back to cited text no. 5
    
6.
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. 6
    
7.
Al-Khlaiwi T, Meo SA. Association of mobile phone radiation with fatigue, headache, dizziness, tension and sleep disturbance in Saudi population. Saudi Med J 2004;25:732-6.  Back to cited text no. 7
    
8.
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;16:188.  Back to cited text no. 8
    
9.
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. 9
    
10.
Johansen LA, Diffendaffer P, inventors; SunTiger Inc, assignee. Ultraviolet radiation and blue light blocking polarizing lens. United States patent US 4,878,748. 1989 Nov 7.  Back to cited text no. 10
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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