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ournal of Optometry (2014) 7, 22---36

www.journalofoptometry.org

RIGINAL ARTICLE

isual function and color vision in adults withttention-Deficit/Hyperactivity Disorder

oyeon Kima, Samantha Chena, Rosemary Tannocka,b,∗

Department of Applied Psychology & Human Development, University of Toronto, Toronto, CanadaNeurosciences & Mental Health Research Program, Hospital for Sick Children, Toronto, Canada

eceived 1 April 2013; accepted 3 July 2013vailable online 16 August 2013

KEYWORDSVisual function;Adults with ADHD;Color vision;ADHD

AbstractPurpose: Color vision and self-reported visual function in everyday life in young adults withAttention-Deficit/Hyperactivity Disorder (ADHD) were investigated.Method: Participants were 30 young adults with ADHD and 30 controls matched for age andgender. They were tested individually and completed the Visual Activities Questionnaire (VAQ),Farnsworth-Munsell 100 Hue Test (FMT) and A Quick Test of Cognitive Speed (AQT).Results: The ADHD group reported significantly more problems in 4 of 8 areas on the VAQ: depthperception, peripheral vision, visual search and visual processing speed. Further analyses of VAQitems revealed that the ADHD group endorsed more visual problems associated with driving thancontrols. Color perception difficulties on the FMT were restricted to the blue spectrum in theADHD group. FMT and AQT results revealed slower processing of visual stimuli in the ADHDgroup.Conclusion: A comprehensive investigation of mechanisms underlying visual function and colorvision in adults with ADHD is warranted, along with the potential impact of these visual problemson driving performance.© 2013 Spanish General Council of Optometry. Published by Elsevier España, S.L. All rightsreserved.

PALABRAS CLAVEFunción visual;Adultos con TDAH;Visión de color;TDAH

Función visual y visión de color en adultos con trastorno de déficit de atención conhiperactividad

ResumenObjetivo: Se investigó la visión de color y la función visual en la vida cotidiana auto-reportadade los jóvenes adultos con trastorno de déficit de atención con hiperactividad (TDAH).

∗ Corresponding author at: Human Development & Applied Psychology (Room 9-288), The Ontario Institute for Studies in Educa-ion/University of Toronto, 252 Bloor Street West, Toronto, Ontario, Canada M5S 1V6. Tel.: +1 416 978 0924; fax: +1 416 926 4713.

E-mail address: rosemary.tannock@utoronto.ca (R. Tannock).

888-4296/$ – see front matter © 2013 Spanish General Council of Optometry. Published by Elsevier España, S.L. All rights reserved.ttp://dx.doi.org/10.1016/j.optom.2013.07.001

Visual function in ADHD 23

Método: Participaron 30 jóvenes adultos con TDAH y 30 controles equiparados por edad y sexo.Fueron evaluados individualmente, debiendo completar el ‘‘Vision Activities Questionnaire(VAQ)-Cuestionario de Actividades Visuales, la prueba de 100 tonalidades de Farnsworth-Munsell(FMT) y una prueba rápida de velocidad cognitiva (AQT).Resultados: El grupo de TDAH reportó una proporción superior de problemas en 4 de las 8áreas del VAQ: percepción de profundidad, visión periférica, búsqueda visual y velocidad deprocesamiento visual. Los análisis adicionales de las cuestiones del VAQ revelaron que el grupode TDAH reflejó más problemas visuales asociados a la conducción que el grupo de control. Lasdificultades de percepción del color en la prueba FMT se restringieron al espectro del azul enel grupo de TDAH. Los resultados de FMT y AQT revelaron un procesamiento más lento de losestímulos visuales en el grupo de TDAH.Conclusión: Está garantizada una amplia investigación sobre los mecanismos subyacentes de lafunción visual y la visión de color con TDAH, junto con el impacto potencial de estos problemasvisuales sobre la conducción.© 2013 Spanish General Council of Optometry. Publicado por Elsevier España, S.L. Todos losderechos reservados.

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Introduction

Attention-Deficit/Hyperactivity Disorder (ADHD) is one ofthe most frequently diagnosed childhood psychiatric disor-ders, with worldwide prevalence rates estimated at 5.3%.1

A longitudinal study shows that approximately 65% of chil-dren with ADHD continue to show symptoms in adulthood.2,3

While adults with a history of ADHD may not meet the fullcriteria of symptoms listed in the DSM-IV, they continueto exhibit clinically significant symptoms.4 These contin-ued symptoms are costly to society and the individual.5

For example, ADHD individuals were found to engage inhigher risky driving behaviors and have more frequent carcrashes.6---10

Current theories posit that executive function deficitsaccount for poor outcomes in ADHD including driving prob-lems. By contrast, we investigate a novel hypothesis thatpoor visual function might contribute to some of thenegative outcomes. A review of the literature revealedseveral reports of ophthalmological problems in childrenwith ADHD (see Table 1). For example, numerous studiesreport a significantly higher incidence of ADHD among chil-dren with convergence insufficiency.11---13 The ADHD traitwas also found to be common in children with intermit-tent exotropia.14 Various visual function and ocular featuresincluding visual acuity, strabismus and ocular motility, nearpoint of convergence and near point of accommodation werealso tested in children with ADHD.15 The authors report thatchildren with ADHD had a higher frequency of ocular andvisual abnormalities, suggesting an early alteration of thedevelopment of neural and vascular tissues in central ner-vous system. Although Grönlund et al.15 found no effectof stimulant medication on visual function, another studyreported that stimulant treatment seemed to improvedvisual field and best corrected distance visual acuity in chil-dren with ADHD.16

Not only have ophthalmological abnormalities beenreported among individuals with ADHD, but also so havecolor perception deficiencies (see Table 2). Specifically,children with ADHD score poorly on clinical tests of blue

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olor perception, but not red-green.17,18 Furthermore, chil-ren with ADHD show poorer game performance in a virtualnvironment when important on-screen information is dis-layed predominantly in blue-yellow colors compared toed-green colors.19 Several studies show decreased speedn color processing in ADHD population.20,21 Notably, the‘retinal dopaminergic’’ hypothesis of color vision22 spec-lates that a deficiency in central nervous system (CNS)opamine in ADHD may induce a hypo-dopaminergic tone inhe retina, which in turn would have deleterious effects onhort-wavelength (‘‘blue’’) cones. Blue cones are very sen-itive to dopamine (as well as other neurochemical agents)nd relatively scarce in number, so that the purported lowopaminergic tone in ADHD23 may affect blue-yellow colorerception.

Numerous studies have reported possible visual defi-iency including color perception in children with ADHD.owever, it is unknown whether adults with ADHD alsoanifest problems in color vision or whether any visualroblems have any functional impact in their everyday life.ccordingly, the aims of this preliminary study were to inves-igate visual function in everyday activities and color visionn adults with ADHD. Based on the retinal dopaminergicypothesis, we hypothesized that adults with ADHD wouldhow a specific color discrimination problem with blue col-rs.

aterials and methods

articipants

hirty young adults with a previously confirmed diagnosis ofDHD (mean age of 27 years; 47% male) and thirty healthyontrols (mean age of 25 years; 50% male) participated inhe study. Participants with ADHD were recruited from two

ources: a student population registered with a local univer-ity’s accessibilities services, which requires documentedvidence of a confirmed diagnosis, and a national advocacyroup for ADHD. In addition to the previously confirmed

24

S. Kim

et al.

Table 1 Literature summary on visual function in ADHD.

Objective Participants Method Results Conclusions

Granet et al.11 The purpose of the studywas to determine anycorrelation betweenconvergenceinsufficiency (CI) andADHD, as it is not clear ifthese pathologiesco-exist, are inter-causalor are misdiagnosed foreach other.

266 patients with adiagnosis of CI from anacademic pediatricophthalmology practiceparticipated.1705 patients with adiagnosis of ADHD wereidentified from acomputerized review ofthe University ofCalifornia, San Diego(UCSD) Medical Records’database.

A retrospective review of the266 patients with a diagnosis ofCI was obtained from the UCSDRatner Children’s Eye Center’selectronic database wasperformed. Patients withhistory of ADHD wereidentified.A computerized review wasalso performed looking at theconverse incidence of CI inpatients carrying the diagnosisof ADHD.

From the 266 charts ofpatients with CI, 26patients (9.8%) had ahistory of ADHD. Of thepatients with ADHD andCI, 20 (76.9%) were onmedication for ADHD atthe time of diagnosis forCI.The review of computerrecords showed a 15.9%incidence (28 patientsout of 1705) of CI in theADHD population.

The authors report athree-fold greaterincidence of ADHDamong patients with CIwhen compared withincidence of ADHD in thegeneral US population(1.8---3.3%). They alsonote a seemingthree-fold greaterincidence of CI in theADHD population.

Borsting et al.12 The purpose of the studywas to evaluate thefrequency of ADHDbehaviors in school-agedchildren withsymptomaticaccommodativedysfunction or CI.

24 children aged 8---15years (mean age 10.9years), 9 boys and 15girls, with symptomaticaccommodativedysfunction and/or CIparticipated.

One parent of each childcompleted the Connors ParentRating Scale-Revised ShortForm (CPRS-R:S).

On the CPRS-R:S,cognitiveproblem/inattention,hyperactivity, and ADHDindex were significantlydifferent from normativevalues.

The results from thispreliminary studysuggestthat school-agedchildren withsymptomaticaccommodativedysfunction or CI have ahigher frequency ofADHD-like behaviors asmeasured by theCPRS-R:S.

Rouse et al.13 The purpose of the studywas to determine ifchildren withsymptomatic CI withoutthe presence ofparent-reported ADHDhave higher scores onthe academic behaviorsurvey.

212 children (mean age11.8 years) withsymptomatic CIparticipated.The control groupconsisted of 49 childrenwith normal binocularvision (NBV; mean age12.5 years).

Parents/guardians of childrenwith symptomatic CI or NBVcompleted the academicbehavior survey (ABS) andreported whether the child hadADHD.

16% of the CI group and6% of the NBV groupwere classified as ADHDby parental report. TotalABS score forsymptomatic CI withparent report of ADHDgroup was significantlyhigher than thesymptomatic CI withparent report of noADHD group and the NBVgroup.

Children with CI withparent report of noADHD scoredsignificantly higher onthe ABS when comparedto children with NBV.

Visual function

in AD

HD

25

Grönlund et al.15 The purpose of the studywas to investigate visualfunction and ocularfeatures in children withADHD and establishwhether treatment withstimulants is reflected infunctioning of the visualsystem.

42 children andadolescents with ADHDaged 6.3---17.6 years(mean age 12 years), 37boys and 5 girls, whowere being treated withstimulants participated.Children had been onmedications for a meanperiod of 19.5 months.The control groupconsisted of 50 schoolchildren (mean age of11.9 years), 44 boys and6 girls.

Ophthalmologic tests were firstperformed without medication:- Visual acuity (VA)- Strabismus and ocularmotility (heterotropia)- Stereo acuity- Near point of convergence(NPC)- New point of accommodationAfterwards the children weregiven their regular drugs. Afterat least 60 min, all tests wereperformed in the same orderwith medication. In addition,the following tests wereperformed:- Refraction under cyclopegia- Assessment of oculardimensions- Examination of anteriorsegment, media, and ocularfundus- Photography of the ocularfundus for quantitative digitalimage analysis- History taking of visualperception

76% of children withADHD hadophthalmologic findingsincluding subnormal VA,strabismus, reducedstereo vision, absent orsubnormal NPC,refractive errors, smalloptic discs and/or signsof cognitive visualproblems.The children had anincreased proportion ofheterophoria and poorerperformance on visualacuity and convergencetests without, but notwith, stimulants whencompared with controls.

Children with ADHD hada higher frequency ofocular and visualabnormalities.Treatment withstimulants caused nosignificant difference invisual function. Theypresented subtlemorphological changesof the optic nerve andretinal vasculature,indicating an earlydisturbance of thedevelopment of neuraland vascular tissues inthe CNS.

26

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et al.

Table 1 (Continued)

Objective Participants Method Results Conclusions

Martin et al.16 The purpose of this studywas to evaluate visualfunction in children withADHD, to correlate thesedata with themorphology of the opticnerve, and to find out ifand how psychostimulantmedication affects visualfunctions.

18 children aged 6---17years (mean age 11.9years), 16 boys and 2girls, diagnosed withADHD and treated withstimulants participated.Children had been onmedication for a meanperiod of 14.7 months.ADHD diagnoses weredetermined according toDSM-IV criteria by onephysician in all patients.The control groupconsisted of 24 childrenaged 7---18 years (meanage 11.7 years), 15 boysand 9 girls.

Both groups underwent anophthalmological examinationincluding best correcteddistance visual acuity (BCVA),visual field examination, andfundus photography.The ADHD children did not takemedication on the morning ofthe initial examination. Twohours later, the children weregiven their regular drug dosesand the examinations wererepeated. The control groupwas examined twice, at thesame time intervals as theADHD group.

Visual acuity increasedsignificantly in the ADHDgroup after treatment.The difference betweenthe two VF examinationswas significantly largerin the ADHD comparedwith the control group.Significantly more ADHDsubjects had subnormalVF results withoutstimulants, comparedwith controls, but withstimulants thedifference was no longersignificant.

Children with ADHDshowed better VA and VFresults with than withoutpsychostimulantmedication.

Chung et al.14 The purpose of the studywas to investigate thesymptoms of ADHD asreported by parents inchildren withintermittent exotropia[X(T)] and to determinewhether strabismussurgery for X(T) affectsADHD symptoms.

51 children undergoingmuscle surgery for X(T)aged 3---9 years (meanage 5.96 years), 22 boysand 29 girls,participated. All patientshad either divergenceexcess or basic typeX(T).

One parent of each childcompleted the ADHD ratingscale IV (ADHD RS-IV)assessment, based on theDSM-IV home version,consecutively before and oneyear after surgery (symmetriclateral rectus recession onboth eyes).

8 (15.7%) of the 51patients demonstratedthe ADHD trait. ADHDRS-IV scores followingstrabismus surgerysignificantly decreasedin patients with theADHD trait, while theydid not differ in patientswithout the ADHD trait.7 of the 8 patients withthe ADHD trait showedimprovement in theirADHD RS-IV scores aftersurgery.

The ADHD trait wasrelatively common inchildren with X(T), andthe parent-reportedsymptoms of thechildren with the ADHDtrait improved afterstrabismus surgery.

Visual function

in AD

HD

27

Table 2 Literature summary on color vision in ADHD.

Objective Participants Method Results Conclusions

Tannock et al.20 The purpose of thestudy was toinvestigate rapidautomatized naming(RAN) and effects ofstimulant medicationin school-age childrenwith ADHD with andwithout concurrentreading disorder (RD)

67 children with ADHD,21 with ADHD + RD, and27 healthy comparisonchildren participated. Allchildren were between 7and 12 years of age, 80%of which were male.In a second study, asubgroup (n = 47) of thetotal ADHD sampleparticipated in an acutemedication trial, 35belonging to the ADHDgroup, 12 to theADHD + RD group.

The three groups werecompared on: color namingspeed, letter naming speed,phonologic decoding, andarithmetic computation.In the medication trial, thesubgroup of childrencompleted several academicand cognitive measures as wellas three of the RAN Tests:Colors, Letters, and Digits.Each child completed arandomized,placebo-controlled, cross-overtrial with three single doses(10, 15, 20 mg) ofmethylphenidate. The activemedication and placebo wereadministered in a double-blindmanner each morning during a1-week period. Testing underdouble-blind conditionscommenced about 1 h afteringestion of medication andlasted for 2 h.

Both ADHD groups weresignificantly slower in colornaming than controls, but didnot differ from one another,showing evidence of anassociation between deficits incolor naming and ADHD thatcould not be attributed to thecomorbidity with RD.Methylphenidate selectivelyimproved color-naming speedbut had no effect on the speedof naming letters or digits.

The findings of colornaming impairments inADHD challenge thecurrent assumption thatnaming speed deficitsare specific to RD andalso provide somesupport for thepurported processingdifferences underlyingcolor naming and letternaming, of whichcolor-naming speed isimproved by stimulantmedication.

Lawrence et al.21 The purpose of thestudy was to comparechildren’sperformance on bothneuropsychologicaland real-lifemeasures ofexecutive functionand processing speed.

44 boys aged 6---12 years(mean age 9.7 years), 22with a diagnosis of ADHDand 22 controls,participated.

Participants completed theStroop Color---Word Test andWisconsin Card Sorting Task(WCST), which were selectedas neuropsychologicalmeasures, as well as routetasks in a videogame and atthe zoo, which were used toindex real-life measures.

There were no groupdifferences in executivefunction on the Stroop or zootasks, but the ADHD groupexhibited deficits inset-shifting as assessed by theWCST (preservative errors andresponses) and videogame play(fewer challenges completed.The ADHD group wassignificantly slower in colornaming on the Stroop, and alsotook more trials on the WCSTto complete sorting cardsaccording to the first categoryof color.

There is growingevidence of color namingand color processingdeficits in children,adolescents, and adultswith ADHD.

28

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et al.

Table 2 (Continued)

Objective Participants Method Results Conclusions

Banaschewski et al.17 The purpose of thestudy was toinvestigate colorperception inchildren with ADHD,as well as therelationship betweencolor perception andperformance on aconventionalneuropsychologicaltask (Stroop Task)that requires speedednaming of coloredstimuli.

27 children aged8.0---13.0 years,consisting of 14 childrenwith ADHD and 13controls, participated.

Color discrimination ability wasinvestigated using theFarnsworth-Munsell 100 HueTest (FMT). Color visionabnormalities and aptitudewere determined by the abilityof the child to place the colorcaps in order of hue.Children completed theStroop-Color---Word Task.Naming time and errors wererecorded for three subtestsseparately: Stroop-Word,Stroop-Color, andStroop-Color/Word. Anomination score wascalculated in terms of thedifference in reaction times ofreading of color words andcolor naming.

Children with ADHD wereslower in naming the colors ofstimuli on both the Color andColor---Word conditions of theStroop, but did not differ innaming speed on the Wordcondition, nor in Stroopinterference. This deficit wasaccounted for similarly byblue-yellow and red-greendiscrimination abilities.

These findings indicatesubtle problems in theblue-yellow mechanismand changes in retinaldopaminergicmechanisms in childrenwith ADHD. However,performance deficits onStroop color namingseem not to be fullyattributable to colorvision impairment.

Roessner et al.18 The purpose of thestudy is to examinecolor perception inADHD and Chronic TicDisorders (CTD) toclarify which factor(ADHD versus CTD)influences color visionparameters especiallyin the case of thecomorbidity ofADHD + CTD.

69 children aged8.0---12.6 years, 14 witha diagnosis of ADHD, 22with CTD, 19 withADHD + CTD, 14 healthycontrols.

Color discrimination ability wasinvestigated using theFarnsworth-Munsell 100 HueTest (FMT). Color visionabnormalities and aptitudewere determined by the abilityof the child to place the colorcaps in order of hue.Participants also completedthe Stroop-Color---Word Task.Naming time and errors wererecorded for three subtestsseparately: Stroop-Word,Stroop-Color, andStroop-Color/Word.

Color perception deficits, asindexed by the FMT, werefound for both main factors(ADHD and CTD), but therewere no interaction effects. Apreponderance of deficits onthe blue-yellow compared tothe red-green axis wasdetected for ADHD.In the Stroop task only the‘pure’ ADHD group showedimpairments in interferencecontrol and other parametersof Stroop performance.No significant correlationsbetween any FMT variable andcolor naming in the Stroop taskwere found.

Basic color perceptiondeficits in both ADHDand CTD could be found,and these deficits areadditive in the case ofcomorbidity(ADHD + CTD).Performance deficits onthe Stroop task werepresent only in the‘pure’ ADHD group.Hence, the latter may becompensated in thecomorbid group by goodprefrontal capabilities ofCTD. The influence ofcolor perception deficitson Stroop taskperformance might benegligible.

Visual function

in AD

HD

29

Silva and Frère19 The purpose of thestudy was to examineblue-yellow colordiscrimination inADHD individualsusing a virtualenvironment that iscapable ofquantifying theinfluence ofred-green versusblue-yellow colorstimuli on participantperformance.

40 volunteers aged15---25 years, 17 men and23 women, consisting of20 non-ADHD volunteersand 20 volunteers withADHD participated.

An interactive computer gamebased on virtual reality wasdeveloped to evaluate theperformance of the players.Within the game, the playermust find and interpret hintsscattered in differentscenarios. In one version, hintsand information boards werepainted using red and greencolors. In the second version,these objects were paintedusing blue and yellow colors.The ADHD group and controlgroup were divided intosubgroups which played eitherthe red-green version or theyellow-blue version. The timespent to complete each task ofthe game was measured.

Use of blue/yellow instead ofgreen/red colors decreased thegame performance of allparticipants. However, agreater decrease inperformance could be observedwith ADHD participants wheretasks, that require attention,were most affected.

Colors affect theperformance of tasksthat simulate dailyactivities requiringattention in the ADHDpopulation.

30 S. Kim et al.

Table 3 Demographic and clinical characteristics of participants with ADHD and controls.

Measure Controls (N = 30) ADHD (N = 30) F

Age 25.4 (6.6) 27.4 (7.1) 1.18ASRS 3.5 (2.7) 11.6 (4.1) 80.8**

WASI 111.5 (12.6) 108.1 (13.5) 1.03K10 17.2 (6.5) 22.9 (5.8) 12.8*

GenderMale 15 14Female 15 16

DiagnosisADHD --- 20ADHD and Depression --- 4ADHD and Learning disorder --- 4ADHD, Bipolar disorder, Depression --- 1ADHD and Bipolar disorder --- 1

MedicationTaking Stimulants 19Not taking stimulants 11

Note. Standard deviations appear in parentheses beside means.*

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iagnosis of ADHD, current symptoms of ADHD were checkedsing the Adult ADHD Self-Report Scale (ASRS24). Partici-ants were asked to report any comorbid disorders. Controlarticipants were recruited through the same local uni-ersity and community advertisements. Participants werexcluded if they had below average intellectual functioningbelow 80 in WASI-II), any known genetic vision problems,mpaired visual acuity as measured by the Snellen eyehart (despite corrected vision), or current treatment of aevere psychiatric disorder other than ADHD. Participantsith ADHD who were being treated with stimulant medi-ation (n = 19; 63%) were requested to stop any stimulantedication for at least 12 h prior to the study (Table 3).

aterials and method

he study was approved by the Institutional Research Ethicsoard and all participants provided written informed con-ent prior to the testing.

Adult ADHD Self-Report Scale (ASRS v1.124): The ASRSas administered to assess current ADHD symptoms. TheSRS is an instrument consisting of eighteen questions basedn the criteria used for diagnosing ADHD in the DSM-IV-TR.cores for each item were added to calculate a total score.he ASRS is a reliable and valid scale for evaluating ADHD indults.25 It has high internal consistency (Cronbach’s alpha.88 and 0.89, for both patient and rater-administered ver-ions, respectively) and high concurrent validity with theater-administered ADHD Rating Scale.

Wechsler Abbreviated Scale of Intelligence II (WASI-II26):cores from both the Vocabulary and Matrix Reasoning tasks

ere summed to give an estimated IQ score.

Kessler Psychological Distress Scale (K1027): The K-10 wassed to examine recent emotional distress. The K10 is a 10-tem questionnaire based on questions about anxiety and

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epressive symptoms that a person has experienced in theost recent 4-week period. Scores for each item were added

o calculate a global measure of distress.Visual Activities Questionnaire (VAQ28): The VAQ was

onducted to assess perceived visual function in ordinaryctivities. The VAQ is a self-report questionnaire consist-ng of 33 items that are behaviourally based in that theyefer to actual visual activities and tasks. These 33 items fallnto eight areas that are known to be important in carryingut visual activities: Color discrimination, Glare disability,ight/Dark adaptation, Acuity/Spatial vision, Depth percep-ion, Peripheral vision, Visual search, and Visual processingpeed. For the purpose of this study, items pertaining toriving were extracted from the various categories to bexamined separately in a post hoc analysis. The items ofach category are listed in Table 4. Participants respondedy selecting one of the following options: never, rarely,ometimes, often and always, which were coded from 1 to 5,espectively. The sum score for each subscale was used fornalysis; the sum score of all items pertaining to driving werelso computed and analyzed. The VAQ is a reliable and validcale for evaluating visual difficulties.28 It is considered to ben efficient measure for current visual function in disordersuch as glaucoma29 and cataracts, and for self-perceivedisual difficulties related to adverse outcomes such as a vehi-le crash or a fall.28 In addition, scores on certain subscalesuch as peripheral vision have been associated with greaterisual field loss.30

Color Vision Screening Inventory (CVSI31): A 10-item self-eport behavioral inventory was used to assess perceivedolor vision ability. This brief screening inventory is aehaviourally validated instrument that can classify indi-iduals based on their color vision perception. Participants

esponded by selecting one of the following options: never,eldom, occasionally, frequently and always, which wereoded from 1 to 5, respectively. The established cut-off

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Visual function in ADHD

value is 17. Seven out of 10 questions ask if the participanthave difficulty discriminating between certain colors (i.e.

between red and brown), and the other items inquires colornaming difficulty in general.

Farnsworth-Munsell 100 Hue Test (FMT32): The FMTwas used to provide an objective assessment of color

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Table 4 Items of Visual Activities Questionnaire per categories.

Color Discrimination 5 --- ‘‘I tend to confuse colors.’’17 --- ‘‘The color names that I use25 --- ‘‘I have difficulty distinguish

Glare Disability 4 --- ‘‘I have problems with lights a14 --- ‘‘I have trouble driving whenview.’’**

29 --- ‘‘When driving at night in thfrom oncoming cars.’’**

Light/Dark Adaptation 1 --- ‘‘I have problems adjusting torather dim.’’12 --- ‘‘It takes me a long time to

23 --- ‘‘It takes me a long time to

for a lengthy period of time.’’28 --- ‘‘I have trouble adjusting frointo a dark movie theater.’’

Acuity/Spatial Vision 7 --- ‘‘I have problems reading sma10 --- ‘‘I have trouble reading the

15 --- ‘‘I have difficulty reading sm27 --- ‘‘I have difficulty doing any

Depth Perception 9 --- ‘‘When pouring liquid, I have

the level of coffee in a cup.’’21 --- ‘‘Sometimes when I reach fothought.’’32 --- ‘‘I have problem in judging h

Peripheral Vision 2 --- ‘‘I have trouble noticing thing11 --- ‘‘I have trouble seeing movinof me.’’19 --- ‘‘When I‘m walking along, I

26 --- ‘‘I bump into people in a busperipheral vision.’’31 --- ‘‘I find it difficult changing llane.’’**

Visual Search 3 --- ‘‘I have trouble finding a spec6 --- ‘‘I have trouble locating a sig16 --- ‘‘I have problems locating so20 --- ‘‘It takes me a long time to

24 --- ‘‘When driving at night, objeof view.’’**

Visual Processing Speed 8 --- ‘‘I have trouble reading a signa passing bus or truck.’’13 --- ‘‘When I‘m driving, other cauntil the last moment.’’**

18 --- ‘‘I have problems carrying ouattention.’’22 --- ‘‘I have difficulty noticing w30 --- ‘‘When riding in a car, other33 --- ‘‘It takes me a long time to

** VAQ items pertaining to vision and driving.

31

iscrimination ability. The FMT is a widely used color visionest that requires participants to sequence color reference

aps in order of incremental hue variation spanning theisible spectrum. The error scores reflect the number of mis-lacements. Error scores were computed separately for thelue, yellow, red, and green spectra. Total time to complete

disagree with those that other people use.’’ing between colors.’’

round me causing glare when I’m trying to see something.’’ there are headlights from oncoming cars in my field of

e rain, I have difficulty seeing the road because of headlights

bright room lighting, after the room lighting has been

adjust to darkness after being in bright light.’’adjust to bright sunshine after I have been inside a building

m bright to dim lighting, such as when going from daylight

ll print (for example, phone book, newspapers).’’menu in a dimly lit restaurant.’’all print under poor lighting.’’

type of work which requires me to see well up close.’’

trouble judging the level of the liquid in a container, such as

r an object, I find that it is further away (or closer) than I

ow close or far things are from me.’’

s in my peripheral vision.’’g objects coming from the side until they are right in front

have trouble noticing objects off to the side.’’y store because I have problems seeing them in my

anes in traffic because I have trouble seeing cars in the next

ific item on a crowded supermarket shelf.’’n when it is surrounded by a lot of other signs.’’mething when it’s surrounded by a lot of other things.’’

find an item in an unfamiliar store.’’cts from the side unexpectedly appear or pop up in my field

or recognizing a picture when it’s moving, such as an ad on

rs surprise me from the side, because I don’t notice them

t activities that require a lot of visual concentration and

hen the car in front of me is speeding up or slowing down.’’**

cars on the road seem to be going too fast.’’**

get acquainted with new surroundings.’’

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he FMT was also recorded to provide an index of the speedr efficiency of color discrimination. All testing was per-ormed under standard light conditions in the same roomnd at the same place. The illuminance was maintained at65 daylight, 6500 K.

A Quick Test of Cognitive Speed (AQT33): The AQT, aariant of rapid automatized naming, was used to measurepeeded color processing. Other than speeded naming abil-ty, AQT is used to measure rapid cognitive shifts betweenisual stimuli and working memory. The AQT consists ofhree main tasks, each comprised of three subtests. In Task, participants were first required to name color (color-aming: black, yellow, red, and blue), followed by formform-naming: circle, line, triangle, and square), and lastly,

color---form combination in which participants named theolor followed by the form (i.e. blue circle). In Task B,he participant has to name color, number (number-naming:umbers 1---9), and a color---number combination. In Task, participants are required to name color, letter, and aolor---letter combination. Each subtest is presented on aingle page with 8 rows comprised of 5 items. Participantsre instructed to name all 40 items as fast and as accu-ately as they can. Naming time and errors were recordednd combined across each task to give six overall varia-les: color-naming, form/number/letter-naming, and colornd form/number/letter-naming in terms of both error andpeed. AQT has shown high test-retest reliability (r = 0.91o 0.95) and discriminates individuals with ADHD fromontrols.33

esults

emographics

he two groups did not differ in age, sex, IQ (see Table 3).he visual acuity (corrected eye sight) measured with anellen chart were within normal range (20/20) in bothroups and did not differ significantly between the groups.s expected, ADHD participants reported significantly moreymptoms on the ASRS than the comparison group [F(1,8) = 80.8, p < 001], as well as higher emotional distress aseasured using the K10 [F(1, 58) = 12.8, p < 001]. No sex dif-

erences among variables between the groups were found.

isual functioning

ndividuals with ADHD reported more visual difficulties thanhe comparison group on the VAQ (group means and standardeviations of scores on the various subscales are shownn Table 5). A one-way multivariate analysis of varianceMANOVA) was conducted to determine the effect of groupADHD participants versus healthy controls) on self-reportedAQ items. Significant group differences were found on theAQ, Wilks’s � = 0.629, F(9, 51) = 3.34, p = 0.0028, multi-ariate �2 based on Wilks’s � = 0.37. Analysis of varianceANOVA) was conducted on the eight subcategories toollow up the significant result. Specifically, the ADHD group

eported more problems in depth perception (M = 5.15,5% CI [4.57, 5.74]) than the control group (M = 4.23,5% CI [3.64, 4.83]), p = 0.032. Also, the ADHD partici-ants (M = 9.25, 95% CI [8.25, 10.24]) had significantly more

spgv

S. Kim et al.

isual difficulty with peripheral vision than healthy con-rols (M = 7.50, 95% CI [6.50, 8.51]), p = 0.017. In addition,ndividuals with ADHD (M = 14.38, 95% CI [13.11, 15.65])elf-reported more problems in visual search than the com-arison group (M = 9.97, 95% CI [8.67, 11.26]), p < 001. Lastly,he ADHD group (M = 12.61, 95% CI [11.41, 13.81]) endorsedignificantly more difficulties with VAQ items related toisual processing speed than controls (M = 9.60, 95% CI [8.38,0.82]), p < 0.001. Post hoc analysis of the VAQ items relatedo driving revealed a significant main effect of ‘group’, indi-ating that participants with ADHD (M = 11.10, 95% CI [10.26,1.93]) reported more visual problems when driving com-ared to controls (M = 8.95, 95% CI [8.10, 9.80]), p < 0.001.

olor vision

one-way MANOVA yielded no main effect of group on theour color discrimination error scores, Wilks’s � = 0.908, F(4,2) = 1.32, p = 0.27 (see Table 5). To test for a priori hypoth-sis of blue-color perception problems, we proceeded toerform one-way ANOVAs for each color spectrum on theMT error scores. Individuals with ADHD (M = 19.86, 95% CI16.01, 23.72]) committed more errors only when discrimi-ating blue spectrum colors and not in other colors such ased or green compared to normal controls (M = 13.86, 95% CI9.94, 17.78]), p = 0.033. Analysis of the time to completehe FMT also revealed slower color discrimination in theDHD group (M = 7.88, 95% CI [6.76, 8.99]) relative to theomparison group (M = 6.30, 95% CI [5.58, 7.01]), p = 0.016.

isual perceptual speed

one-way MANOVA yielded a main effect group on AQT nam-ng time, Wilks’s � = 0.767, F(6, 53) = 2.69, p = 0.024. Theultivariate �2 based on Wilks’s � was 0.23. Results from

ollow-up ANOVA tests indicated that participants with ADHDere significantly slower in all three naming tasks than con-

rol group (see Table 5). In terms of accuracy scores, ADHDarticipants made more errors than the healthy controls inorm/number/letter-naming (also see Table 5).

nterrelationship amongst visual functioning, colorision, and ADHD symptoms

o determine whether ADHD symptoms were related toisual problems, Pearson correlations were calculatedetween the ASRS scores and those for the five VAQubscales impaired in ADHD. Significant correlations wereound between ASRS and peripheral vision [r(58) = 0.320,

= 0.013], visual search [r(58) = 0.492, p < 0.001], and visualrocessing [r(58) = 0.315, p = 0.014]. Although there wereo group differences in the CVSI, correlational analysesevealed a significant positive correlation between scoresn the CVSI and those on the VAQ color discriminationcale for both groups: ADHD: r(27) = 0.82, p < 0.001; Con-rol: r(28) = 0.78, p < 0.001. Also, in the ADHD group, CVSI

cores correlated with VAQ depth perception [r(27) = 0.48,

= 008]. In the control group, CVSI scores correlated withlare disability [r(28) = 0.47, p = 0.008] and acuity/spatialision [r(28) = 0.44, p = 014].

Visual function in ADHD 33

Table 5 Vision and color vision questionnaire and color vision tests ANOVA results.

Measure Controls N = 30 ADHD N = 30 F Cohen’s d

VAQColor Discrimination 4.43 (1.63) 4.92 (1.97) 1.12 0.27Glare Disability 6.93 (2.66) 8.22 (2.65) 3.59 0.49Light/Dark Adaptation 8.20 (2.04) 9.59 (3.65) 3.33 0.47Acuity/Spatial Vision 6.50 (1.87) 7.70 (2.77) 3.88 0.51Depth Perception 4.23 (1.30) 5.15 (1.90) 4.84* 0.57Peripheral Vision 7.50 (2.60) 9.25 (2.92) 6.07* 0.63Visual Search 9.97 (2.86) 14.38 (4.10) 23.66** 1.25Visual Processing Speed 9.60 (2.98) 12.61 (3.65) 12.40** 0.90Driving 8.95 (2.41) 11.10 (2.23) 12.96** 0.93

CSVI 11.53 (2.62) 12.54 (3.23) 1.70 0.34

FMTTotal Error Score 44.71 (22.15) 66.62 (47.11) 4.99* 0.60Overall Speed 6.30 (1.77) 7.88 (2.70) 6.18* 0.69Red (Error) 4.93 (4.10) 7.72 (7.95) 2.74 0.44Blue (Error) 13.86 (7.30) 19.86 (12.61) 4.80* 0.58Green (Error) 14.50 (7.76) 19.38 (11.03) 3.71 0.51Yellow (Error) 3.39 (3.10) 5.00 (5.67) 1.75 0.35

AQTColor Naming (Error) 0.90 (0.72) 1.19 (1.30) 1.12 0.28Color Naming (Speed) 65.07 (9.84) 72.16 (9.38) 8.16* 0.74Form, Number, and Letter (Error) 0.30 (0.47) 0.72 (0.90) 5.06* 0.59Form, Number, and Letter Naming (Speed) 52.44 (6.61) 57.80 (7.53) 8.59* 0.76Color Number, Form and Letter Naming (Error) 1.50 (1.34) 2.54 (2.09) 5.29* 0.59Color Number, Form and Letter Naming (Speed) 137.24 (20.38) 158.20 (25.70) 12.26** 0.90

VAQ = Visual Activities Questionnaire; CVSI = Color Vision Screening Inventory; FMT = Farnsworth-Munsell 100 Hue; MRM = Mollon-ReffinMinimalist; AQT = A Quick Test of Cognitive Speed.Note. Standard deviations appear in parentheses beside means.

* p ≤ 0.05

dAlibdsatdew

plcmtte

** p ≤ 0.001.

Discussion

This study provides the first evidence of color vision prob-lems and functional visual impairments in adults with ADHD.Specifically, young adults with ADHD exhibited significantlymore visual difficulties, as indicated by self-report on fourout of eight areas in everyday visual activities. Moreover, theADHD group reported more visual difficulties when driving.Also adults with ADHD exhibited specific problems in dis-criminating colors along the blue spectrum, as indicated bytheir performance on the FMT, as well as less efficient colordiscrimination and overall visual processing, as indexed bythe longer time taken to complete the FMT and AQT scores,respectively.

In our study, ADHD individuals reported that theyperceived significantly more difficulties compared to thecontrol group in the following areas on the VAQ: depth per-ception, peripheral vision, visual search, visual processing,and items related to driving. Also, in the ADHD groupself-rating of ADHD symptoms on the ASRS correlated signif-

icantly with VAQ subscales such as peripheral vision, visualsearch and visual processing speed, suggesting that thesevisual difficulties may be related to behavioral symptoms ofinattention. However, those VAQ items pertaining to visual

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ifficulties associated with driving did not correlate withSRS scores. Previous studies have reported driving prob-

ems including risky driving behavior and vehicle collisionsn adults with ADHD.6,7 Our findings on the VAQ, which areased on self-reported problems in visual function in every-ay life, suggest that visual problems reported in previoustudies may have functional consequences in real worldctivities including driving. Considering that visual percep-ion is known to be one of the most important factors inriving, our findings warrants further investigation to delin-ate underlying mechanisms of visual difficulties in ADHD asell as the link between vision, attention and driving.34,35

In terms of color perception, our finding of impaired FMTerformance for the blue spectrum in adults with ADHD, is inine with findings from previous studies using the FMT withhildren with ADHD17,18 (see Table 1). Notably, no impair-ents were found for the red or green spectra, suggesting

hat the difficulty with blue cannot simply be attributableo problems with sustained attention: the latter would bexpected to have an impact on FMT performance across all

f the colors. But how are we to account for the findinghat the hue discrimination problems were restricted to thelue spectrum and did not include problems with the yel-ow spectrum? According to opponent color theory,36 the

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4

lue and yellow visual system may be coupled and showimilar outcome in visual functions. However, an alternateodel of color vision, Dual-Process Theory37 proposed that

he visual system is comprised of two stages. The first stagean be considered as the receptor stage, where the threeetinal photoreceptors (S, M and L cones) traduce physicaltimuli into neural signals. In the second stage, the neuralignals from cones are combined to create two chromaticechanisms: L---M and S---(L + M). The S---(L + M) mechanism

ombines positive inputs from S cones and negative inputsrom the sum of L and M cone signals which lead to ourerception of blue and yellow. Notably, deficiency in cen-ral nervous system (CNS) dopamine in ADHD may induce aypo-dopaminergic tone in the retina, which in turn wouldave deleterious effects on short-wavelength cones. There-ore, we may speculate that this dopaminergic effect mayave an impact on S-cones in the receptor stage, leavingellow perception, which is a product of LM cones in theeceptor level intact. Another possibility, albeit speculation,s that the observed ‘blue-color problem’ in ADHD reflectsn alteration in an opsin/vitamin-A-based photopigment,alled melanopsin, which is maximally sensitive to blue lightnd linked with regulation of circadian rhythms:38,39 circa-ian systems are impaired in ADHD.40

Furthermore, high correlations between CVSI score andeveral categories in VAQ imply possible impact of colorision in daily visual activities. Likewise, evidence of a colorerception deficit is important given the extensive use ofolor in daily life and the use of color stimuli in many of thetandard neuropsychological tests used in the assessment forDHD (e.g. color---word Stroop test, Wisconsin Card Sortingask). For example, one previous study reported an intrigu-ng relationship between performance on the Wisconsin Cardorting Task (number of trials to complete the first cate-ory, which is color) and color naming on the Stroop. Bothasks involve a high proportion of blue stimuli.21 Findingsor color vision were not completely consistent in this study.or instance, self-reports such as the CVSI and the color dis-rimination variable on the VAQ did not indicate any groupifferences in perceived color vision while the FMT resultshowed significant group differences on the blue spectrum.his seemingly inconsistent finding with self-reported ques-ionnaires suggests that color perception deficiency may bepecific to blue colors, as suggested by the retinal dopami-ergic hypothesis.

Finally, we found that the ADHD population were signif-cantly slower in naming speed than the control group inll subscales of the AQT: color naming, form/number/letteraming and color---form/color---number/color---letter nam-ng. Individuals with ADHD were also generally slower onhe color discrimination task (FMT) than the control group.urthermore, ADHD individuals committed more errors thanontrols except for the color naming subscale. This findings somewhat inconsistent with previous studies that foundifferences in color naming speed.17,20 One important fac-or to consider when evaluating the findings from the AQTs that the AQT differs significantly from the Stroop testn that the AQT tasks measure general cognitive and per-

eptual processing speed41 whereas the Stroop color---wordest is believed to be a classic executive function test. Atudy using regional cerebral blood flow has shown thaturing color---form naming task, brain activation in the

DPp

S. Kim et al.

arietal area is increased and activations in fronto-temporalegions are decreased, which indicates that the color---formest may require more perceptual processing than execu-ive functions.42 Along with slower naming speed in FMT,his further reinforces the idea that individuals with ADHDxperience difficulties in visual processing efficiency.

There are several limitations in this preliminary study.irst of all, the sample size is relatively small and involves aarge proportion of college students which makes it difficulto generalize the results to the entire ADHD adult popu-ation. We acknowledge that this preliminary study needso be replicated with a larger, clinical sample for find-ngs to be generalizable to the ADHD population. However,ased on the effect sizes on the visual and color visioneasures of this study that range from medium to large,

he sample provided sufficient statistical power to detectroup differences.43 Secondly, ADHD diagnosis in this studyas determined by previous documentation of diagnosis andomorbidities were self-reported by the participants insteadf a comprehensive diagnostic procedure. Another limita-ion is that visual function problems in daily life were mainlynalyzed with a self-report measure which might entailnformation bias. Subsequent studies should use a morebjective measure of visual function problems in everydayife. In addition, the limitation of using the FMT is thatt requires the participant to arrange the caps in the bestolor order (i.e. from yellowish green to turquoise green).his process involves both accurate movement executionnd sustained attention, which are known to be impairedn ADHD. Future studies might want to give greater con-ideration to the choice of color perception tests and toncorporate other approaches to disaggregate visual atten-ion and color vision. Perhaps display based tests such asolor Assessment and Diagnosis (CADs) should be used inuture studies to investigating RG and YB chromatic sensi-ivity more accurately.

Notwithstanding the study limitations, this study repre-ents the first attempt to investigate the perceived difficultyn daily visual activities, and to test whether a previouslyeported problem in blue color perception in children withDHD also manifests in adults with ADHD. Its interdisci-linary innovation lies in its application of a well-establishedeasure of color vision (FMT) along with a less used measure

f visual functioning to test a novel hypothesis (retinal dopa-inergic hypothesis22) in a prevalent psychiatric condition

ADHD), which is not traditionally linked with visual prob-ems. Our findings highlight the need for further researchn the complex interactions between attention, color per-eption, and visual functioning and underlying explanatoryechanisms. Moreover, our findings indicate the need for

ptometrists, psychiatrists, and other clinicians to investi-ate visual function in the assessment of young adults withDHD. The VAQ appears to be a psychometrically sound mea-ure that may serve as a useful clinical tool for investigatingelf-reported visual function in daily life.

onflicts of interest

r Tannock has served as a consultant for Eli Lilly and Purdueharmaceuticals in the past 3 years, and Pearson-Cogmedrovides software licences without cost for her research on

Visual function in ADHD

working memory training in ADHD college students; neitherMs Kim nor Ms Chen have any conflicts of interest.

Acknowledgements

Special thanks to Heidi Bernhardt, the president andnational director of the Center for ADHD Awareness, Canada(CADDAC) for her help in recruiting ADHD participants. Alsowe appreciate our research assistants Hamed Dar and PalmSoontornsittipong for their help in data collection. This studywas funded in part by the Canada Research Chairs program(RT) and Graduate Funding (SK).

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