Digital Eye Strain Epidemic Amid COVID-19 Pandemic …

DigitalEyeStrainEpidemicAmidCOVID-19Pandemic

PratyushaGanne1;ShaistaNajeeb1;GanneChaitanya2;AdityaSharma1;NageshaCK3

1DepartmentofOphthalmology,AllIndiaInsDtuteofMedicalSciences,Guntur,AndhraPradesh,India

2EpilepsyandCogniDveNeurophysiologyLab,DepartmentofNeurology,UniversityofAlabamaatBirmingham,AL,USA,35233

3DepartmentofVitreo-ReDna,BWLionsSuperspecialityEyeHospital,Bangalore,India

BACKGROUND

•  Digitaleyestrain(DES)orcomputervisionsyndromeencompassesarangeofvisualand

ocularsymptomsarisingduetotheprolongeduseofdigitalelectronicdevices

•  The corona virus disease (COVID-19) pandemic has necessitated drasDc changes in the

lifestyle,oneofwhichisincreasedexposuretodigitaldevices

•  There has been an enormous increase in the use of gadgets for online classes and

entertainmentduringtheCOVID-19pandemic

•  The current pandemic mimics a real-life experiment to study the effects of this

unprecedentedincreaseintheuseofgadgetsonocularhealth

AIMS

•  ToesDmateprevalenceofDESamongstudentstakingonlineclassesandgeneralpublic

•  TodescribethepaZernofgadgetusage

•  To analyze the risk factors for increased DES during the last fourmonths of COVID-19

pandemicinIndia

CONCLUSION

•  This study calls for a concertedeffort to disseminate informaDon

on reducing the total screen Dme

and on the ergonomic use of

gadgets

•  Special care should be taken bypeople with previous eye diseases

and those whose occupaDon

demands p ro longed s c reen

exposuretoavoidDES

DISCUSSION

•  IndiscriminateuseofdigitaldevicescanpotenDallyleadtoavarietyofocularandnon-ocular

problems like: eye strain, reDnal damage, progression of myopia, sleep disturbances,

musculoskeletalproblems,andbehavioralabnormaliDes

•  The limitaDons of this study include: (i) recall bias (ii) the parDcipants could have given

desirableanswersratherthanthetrueanswers

•  TherecommendaDonsfromthisstudyinclude:

•  (i) limit the totalduraDonofonlineclasses to less than4hoursaday, giveadequate

breaksbetweenclasses,inculcatelecturesonergonomicuseofdigitaldevices

•  (ii)reduceotherscreenrelatedacDvitylikewatchingtelevision,browsingsocialmediato

compensateforthescreenDmespentononlineclassesorworkfromhome.

•  (iii)ergonomicpracDcesthatcanameliorateDESshouldbepracDced

METHODS

•  Across-secDonal,quesDonnaire-based,onlinestudyconductedinApril-July,2020•  Study populaDon: Students and members of the general public aged ≥18 years were

recruited. Electronic devices included televisions, computers, smart phones, e-readers,

tablets,andgamingsystems

•  Survey protocol: The link to the surveywas sent by emails and textmessages and re-

circulatedthereof.

•  Design of the quesDonnaire: Pre-validated computer vision syndrome quesDonnaire

designedbySeguietal*wasusedtoassessthelevelofDESsymptoms.ThequesDonnaire

hadthreeparts:(i)tocapturethedemographicdetails,(ii)tounderstandthepaZernof

gadgetusage,(iii)toassessthedegreeofeyestrainexperienced.

•  Grading of DES was esDmated using the frequency and intensity of 16 symptoms.

Scoringwasasfollows:Frequency:Never(score0),someDmes(score1)(onceaweek,

sporadicepisodes),andalways(score2)(morethan2-3Dmesaweek).Theintensity

was graded asmoderate (score 1) and intense (score 2). The result of (frequency X

intensity)wasre-codedas:0=0;1or2=1;4=2

•  FinalDESscore=∑(1-16)(frequencyXintensity)DESscore≥6wasindicaDveofdigitaleyestrain.

•  Apilotstudywascarriedouton130parDcipants(studentsandthegeneralpublic)•  StaDsDcs:Non-parametrictestsofmedianswereusedtocomparethemedianDESscore,

Chi-squaretesttocomparecategoricalvariables,andbinarylogisDcregressiontofindthe

predictorsofDES.

RESULTS

•  941responsesfromstudentsofonlineclasses(688),teachersofonlineclasses(45),and

generalpopulaDon(208)wereanalyzed

Table1:DemographicprofileoftheparGcipants

Ageinyears(Mean±SD)(Range) 23.4±8.2(18-79)

GenderMale(%) 481(51.1%)Female(%) 460(48.9%)

OccupaDonGeneralpopulaDon

Unskilledworker 7(0.7%)Semi-skilledworker 43(4.6%)Skilledworker 139(14.8%)

Students 752(79.9%)

ParDcipaDoninonlineclasses

Studentsofonlineclasses 688(73.1%)Teachersofonlineclasses 45(4.8%)Restofthegeneralpublic 208(22.1%)

ParDcipantswitheyedisease(%)

Total 253(26.9%)Myopia 154(60.8%)AsDgmaDsm 19(7.5%)Hypermetropia 12(4.7%)UnspecifiedrefracDveerror 46(18.2%)

SeasonalallergicconjuncDviDs 6(2.4%)

Cataract,Keratoconus 3each(1.2%)Glaucoma,reDnaldetachment 2each(0.8%)

ReDniDspigmentosa,colourblindness,dryeye,maculardegeneraDon,squint,amblyopia 1each(0.4%)

RESULTS

PrevalenceofDES

•  Higheramongstudentstakingonlineclassescomparedtothegeneralpublic(50.6%vs.

33.2%;χ2=22.5,df=1,p<0.0001).

•  TheDES scorewashighest among students aZendingonline classes [median score=7,

IQR=6.87-7.7] followed by teachers of online classes [median score=5, IQR=4.37-7.23]

and then the rest of the general public [median score=4, IQR=4.64-6.18] [test

staDsDc=22.5,df=2,p=0.0001](FigA)

PaZernofgadgetuse

•  TheaveragedailyscreenDmeincreasedduringthepandemiccomparedtothatbefore

thepandemic(FigB)

•  TherewasatendencyofyoungerparDcipants(22±5years)tospendgreaterDmewith

gadgetsthantherelaDvelyolderpopulaDon(33±17years)(R2=0.066,p<0.001)(FigC)

RESULTS

•  Greater proporDon of students taking online classes: had a screen Dme >6hours/day

(χ2=33.59, df=2, p&lt;0.0001), never took breaks/ took them infrequently (χ2=8.59, df=2,

P=0.014)andusedgadgets in thedark (χ2=9.4,df=2,p=0.009)compared to teachersand

thegeneralpublic

•  DESscorewashighestamongstudentsaZendingonlineclasses (p<0.0001), in thosewith

eyediseases(p=0.001),greaterscreenDme(p<0.0001),screendistance<20cm(p=0.002),

those who used gadgets in dark (p=0.017) and those who took infrequent/no breaks

(p=0.018)

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AbstractNo:EHCWOP101