Accident Analysis and Prevention 70 (2014) 7483

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Accident Analysis and Prevention

jou rn al hom ep age: www.elsev ier .com/ locate /aap

Cogniti m

Nicole A.School of Psych

a r t i c l

Article history:Received 13 AReceived in reAccepted 11 MAvailable onlin

Keywords:Useful Field ofDrivingOlder adultsAttentionCognitionVisionInspection TimProcessing speChange detect

adulted toeral m), croectiow tesivideFOV al acpeed

no eore c

1. Introduction

Older adults comprise a rapidly growing section of the popula-tion in AusStatistics, 2is expectedaged over 8operation aDriving wilof these peoolder drivercle accidensecond mosonly to thoand Regionolder adultsor killed in tand McLean

Current medical ancedures is jurisdictionous acciden

CorresponE-mail add

age-based tness to drive testing (Langford et al., 2004a,b). More-over, the proportion of older drivers with self-reported cognitiveand/or visual decits appears to be comparable across jurisdictions,

http://dx.doi.o0001-4575/ tralia and throughout the world (Australian Bureau of008; United Nations, 2011). By 2035, one in four people

to be aged over 65, and by 2050 the number of people0 is expected to triple (Organisation for Economic Co-nd Development (OECD), 2001; United Nations, 2011).l remain the preferred method of transport for mostple (OECD, 2001). This is of potential concern becauses are a higher risk group for involvement in motor vehi-ts. In Australia, people aged 70 years or older are thet likely group to be involved in a fatal accident, secondse aged 1725 (Beaureau of Infrastructure, Transportal Economics (BITRE), 2011). Additionally, the frailty of

means that they are more likely to be seriously injuredhe event of a crash (OECD, 2001; Li et al., 2003; Baldock, 2006).licensing procedures for older drivers typically rely ond visual assessments, but the validity of existing pro-questionable. For example, comparison of Australians found no reliable differences for crash data and seri-ts between jurisdictions with and without mandatory

ding author. Tel.: +61 422545271.ress: nicole.matas@adelaide.edu.au (N.A. Matas).

irrespective of whether mandatory aged-based testing applies ornot (Ross et al., 2011). Thus, there is a need to develop proce-dures to better identify older drivers who may be at elevated riskfor crash involvement. Investigation of the specic factors empiri-cally related to poorer driving outcomes will assist development oftargeted tness to drive assessments that evaluate relevant func-tional abilities (OECD, 2001; Fildes, 2008; Anstey et al., 2012). Ageitself does not reliably impact tness to drive but declining medical,physical and cognitive functions typically associated with ageinghave been found to increase crash risk (Janke, 1994; Charman,1997; Daigneault et al., 2002; Anstey et al., 2005; Mathias and Lucas,2009).

The most commonly investigated cognitive functions haveincluded attention, processing speed, executive functioning, visuo-spatial skills, vision, and mental status; and several tests based onthese abilities have been proposed as predictors of safe driving abil-ity in older adults. One of the most successful tness to drive tests isthe Useful Field of View (UFOV) test (Ball and Owsley, 1993). UFOVperformance has been shown to predict retrospective and prospec-tive crash involvement, on-road driving performance, and drivingsimulator performance (Clay et al., 2005; Mathias and Lucas, 2009;Gentzler and Smither, 2012). UFOV subtest 2 has been found tobe particularly sensitive to driving outcomes. Subtest 2, designedto assess processing speed for a divided attention task, is highly

rg/10.1016/j.aap.2014.03.0112014 Elsevier Ltd. All rights reserved.ve and visual predictors of UFOV perfor

Matas , Ted Nettelbeck, Nicholas R. Burnsology, University of Adelaide, South Australia 5005, Australia

e i n f o

ugust 2013vised form 25 February 2014arch 2014e 2 April 2014

View Test

eedion

a b s t r a c t

Eighty two community dwelling oldertery of cognitive and visual tests selecvisual acuity, contrast sensitivity, genprocessing speed (Inspection Time, ITProcessing, ProPerVis) and change detperformance on the Useful Field of Viesubtests for (i) processing speed; (ii) dregression analyses conrmed that Uthat subtest (i) primarily reects visuby change detection and processing strast sensitivity. Unexpectedly, givensignicantly to performance on the mance in older adults

ts (52 females) aged 6292 years (mean = 75) completed a bat- assess functions relevant to driving performance. These wereental competence (Mini Mental State Examination, MMSE),

wding across the visual eld (Prociency of Peripheral Visionn (DriverScan). These six tasks provided predictor variables fort (UFOV), a well validated test of tness to drive that includesd attention; and (iii) selective attention. Relative importance

is sensitive to attentional and speed processes but suggesteduity and contrast sensitivity; subtest (ii) is better explained; and subtest (iii) predominantly reects crowding and con-vidence of substantial cognitive decline, MMSE contributedomplex subtests (ii) and (iii).

2014 Elsevier Ltd. All rights reserved.

N.A. Matas et al. / Accident Analysis and Prevention 70 (2014) 7483 75

correlated with the Digit Symbol Substitution task which assessesvisual processing speed (Edwards et al., 2006). Of the three subtests,subtest 2 is most related to crashes (Owsley et al., 1998; Oxley et al.,2005; Ball et al., 2006), on-road driving (Bowers et al., 2013) andsimulated dtherefore ofet al., 2006)

The testdifculties preted as as1988, 1990tion, localisthe visual that requirea periphera2005). All sjustifying tspeed of pr(Edwards e

Ball andreects thesalient featprocessing,1990; Ball, three subteprocessing stimuli presand (iii) depresent in additive eff

UFOV hatheories of test was 2011). ReceUFOV perfotrol processability to shso), rather in the visuais also possprocessing this suggestof processin(Edwards etwith the diilar trajecto2008).

Recent also relatedselective atobjectively a widely stuwhen a vismaterials (Bhas generawork sugge(He et al., 1the visual visual perfothat has be1994; CarraVis, a test ospeed. Thisunanked scrowding cowith UFOV

that performance on the crowding component declines with age,such that older adults nd it much more difcult to extract infor-mation from a crowded visual eld, especially when the stimuliof interest are presented in peripheral vision (Burns et al., 2005;

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ts as and ed teonly a tesped patiatestsd thd duf prosing ion r (or w ofriving performance (Molnar et al., 2007). Subtest 2 isten considered on its own for purposes of brevity (Ball.

was originally developed to assess everyday visualencountered by older adults and has since been inter-sessing visual attention and processing speed (Ball et al.,, 1993; Owsley, 1994). The UFOV test involves detec-ation, and identication of stimuli located throughouteld and comprises three subtests of increasing difculty

identication of a central stimulus and localisation ofl stimulus under different conditions (Edwards et al.,ubtests involve visual processing under limited time,he conclusion that UFOV measures an individualsocessing across increasingly complex visual displayst al., 2005, p. 530).

colleagues have proposed that UFOV performance ability to rapidly scan the visual eld and focus onures and that this in turn depends on speed of visual

divided attention, and selective attention (Ball et al.,1997). These three components are measured by thests of UFOV which assess quality of performance when(i) brief stimuli located in central vision; (ii) similarented concurrently in central and peripheral locationstecting peripheral stimuli when distractors are alsothe visual eld. Each subtest has an independent andect on overall UFOV performance (Ball et al., 1990).s undergone only limited psychometric evaluation, andvisual attention have changed substantially since therst developed (Wolfe and Horowitz, 2004; Carrasco,ntly, Cosman et al. (2012) have suggested that poorrmance may be caused by decits in attentional con-es, specically reduced attentional disengagement (theift the focus of attention rapidly when required to do

than a reduction in attentional breadth; i.e. the areal eld that can be searched within a single xation. Itible that UFOV primarily reects speed of information(Lunsman et al., 2008). Indeed, supporting evidence forion is correlation of UFOV performance with measuresg speed, including WAIS-R digit symbol substitution

al., 2006) and the Road Sign Test (Edwards et al., 2005),git symbol substitution test and UFOV showing a sim-ry of decline accompanying older age (Lunsman et al.,

work has shown that other cognitive variables are to UFOV performance. Burns et al. (2005) found thattentional aspects of UFOV performance might morebe dened in terms of crowding across the visual eld,died phenomenon whereby visual interference occursually off-centre primary target is anked by similarouma, 1970; Pelli et al., 2004; Levi, 2008). Crowding

lly been considered a visual phenomenon but recentsts it may also involve limits to attentional resolution996; Levi, 2008). Thus, a measure of crowding acrosseld has potential for more clearly identifying aspects ofrmance currently ascribed to visual attention, a termen widely applied to diverse functions (Plude et al.,sco, 2011). Burns and White (2007) developed ProPer-f crowding across the visual eld and visual processing

test involves identifying briey-presented anked ortimuli in central, peripheral, and parafoveal vision. Themponent of this test was found to be highly correlatedsubtest 3 (Burns et al., 2005). Results have also shown

WerneHof

(Driverblank sof thatchangecondit(Rensindetectit has bworld vigilantrafc and thevigilanfunctio2001, 2on chato suggtional et al. (2was hi(r = .50a modspeed,attentidrivingDriverappear

Ansof cogndrivingtest. Faexecutmemoicantlymemo40% of detectperform

Thuof cogntioningof attevisual educat2006).

Tescomesincludcommdrive; develovisuosnitive (IT), anselectesure oprocesa decisshortea revie08). et al. (2006) developed a visual change detection task) for older adults based on the icker paradigm where an in displayed between an image and an altered versione, thereby masking luminance cues to the location of thesink et al., 1997). Rapid detection of change under theserequires focused attention to the area being changed

al., 1997; Rensink, 2002). The DriverScan task involveshanges in real world driving scenes and on this basisaccepted as having ecological validity as a test for real-ng skills, where drivers are required to be constantly

important changes in the environment like changes tos, position and velocity of other vehicles on the road,den presence of potential hazards. Along with sustaineduccessful detection of change also involves executive, working memory, and processing speed (Pringle et al.,; Hoffman et al., 2006; Rizzo et al., 2009). Performanceetection tasks is related to UFOV performance, leadingns that change detection reects the breadth of atten-

(Pringle et al., 2001, 2004; Veiel et al., 2006). Hoffman) found that performance on the change detection taskcorrelated with performance on UFOV divided attention

selective attention (r = .57) subtests. Furthermore, inorporating measures of visual impairment, processing

attention, both change detection and UFOV dividedad independent signicant direct effects on simulatedormance. These results therefore suggest that, althoughand UFOV subtest 2 (divided attention) are related, theyly on separate attentional processes.t al. (2012) investigated the contribution of a battery

and visual tests to UFOV and two other tests of safeacity: a hazard perception test and a change detection

analysis on the battery of tests revealed ve factors:peed, vision, spatial ability, visual closure, and workingeir results showed that UFOV performance was signif-

ted to the executive/speed, spatial ability, and workingtors. Cognitive and visual factors together accounted forariance in UFOV performance, 44% of variance in changeerformance, and 30% of variance in hazard perceptione.OV performance has been shown to be related to a range

predictors including working memory, executive func-cessing speed, visuospatial ability, and specic aspects

including attentional search and crowding across the Furthermore, UFOV performance is also related to age,vision, and eye health (Ball et al., 1993, Edwards et al.,

sessing variables found to be relevant to driving out-UFOV performance in older adults were selected. Thesests of visual acuity and contrast sensitivity that areused by licensing authorities to determine tness tot of global cognitive functioning; and several recentlycognitive tests tapping attention, processing speed,l skills and executive functioning. Specically, the cog-

selected were DriverScan, ProPerVis, Inspection Timee Snellgrove Maze Test. DriverScan and ProPerVis weree to their reported correlations with UFOV. IT is a mea-cessing speed and was included to verify the reportedspeed component of UFOV. The IT task involves makingabout which of two rapidly presented vertical lines islonger). IT is notable for its high correlation to IQ, with

over 90 studies showing that the shared variance is

76 N.A. Matas et al. / Accident Analysis and Prevention 70 (2014) 7483

around 25% (Grudnik and Kranzler, 2001). IT has been investigatedas a biomarker for general cognitive decline (Gregory et al., 2008,Deary et al., 2010). IT predicts future results on tests of uid rea-soning, perceptual speed, and working memory, and changes in ITare predictiSnellgrove assessmentattention (Solder driverthan 60 s tofail an on-rversions ofability, espeor dementi2008; Carr et al., 2013measure of sensitivity wis often asspresent stutive, visual,healthy olddicted that to visual ethe largest

2. Materia

2.1. Particip

Participafemales) liv75 years. IncommunityParticipantsnewspapergymnasiumand no reim

All particurrent Soulonger drovdriving in s

2.2. Cogniti

2.2.1. VisuaVisual ac

(Bach, 1996E optotyperesponded of the optocurrent estbest Param1996). Thertrial where rent estimaof the Minirepresentin

2.2.2. ContrContrast

trast sensitirows of six trast of the viewed thenormal visi

letters on the chart as far down as they could and were encour-aged to guess if they were uncertain. The outcome was log contrastsensitivity, which was measured according to the faintest group ofthree letters for which the participant correctly identied two of

ee le indic

Mini Min

globgniticcorlloy ng shonal tiong actf cogbe nsi et a

Snell Sneed fomenentio

Oldetia wlikely

The ing tete thas poatch

Inspeeasu

ontrat onr linecessd or espocentrask ract

et (83wer 1ems en tacuraer, 20

DriveverScon st use1997ompred adects (chanon i

. . ete blave of future cognitive decline (Gregory et al., 2008). TheMaze Test was included as quick, easy to administer

of executive function, visuoconstructional skills, andnellgrove, 2005). In a sample of cognitively-impaireds, Snellgrove (2005) found that drivers who took longer

complete the task were signicantly more likely tooad driving test. The Snellgrove Maze Test and other

Maze Tests have been found to be related to drivingcially in older drivers with mild cognitive impairmenta (Ott et al., 2003; Whelihan et al., 2005; Ott et al.,et al., 2011; Krishnasamy and Unsworth, 2011; Staplin). The MMSE was included as a screening tool and as aglobal cognitive functioning. Visual acuity and contrastere included for use as covariates and because vision

essed as part of licensing procedures. The aim of thedy was to investigate the contribution of a set of cogni-

and demographic variables to performance on UFOV iner adults. On the basis of previous research it was pre-the cognitive tests tapping change detection, responseld crowding, and visual processing speed would makecontribution to UFOV performance.

ls and methods

ants

nts were 82 community dwelling older adults (52ing in Adelaide, South Australia, age 6292 years, meanclusion criteria were age over 60 years, living in the, and free of severe mental impairment (MMSE > 24).

were recruited via advertisements placed in locals and locations frequented by older adults, includings and community centres. Participation was voluntarybursement was offered.

cipants were or had been drivers and 80 (95.1%) held ath Australian license, six (7.3%) reported that they noe a motor vehicle, 16 (19.5%) reported restricting theirome way, and 62 (73.2%) reported unrestricted driving.

ve and visual measures

l acuityuity was assessed using the Freiburg Visual Acuity Test). Participants indicated the orientation of a Tumbling. Participants sat 1.65 m from a computer screen andusing the arrows on the computer keyboard. The sizetype presented varied on each trial depending on theimated threshold of the participant, calculated via theeter Estimate by Sequential Testing procedure (Bach,e were 30 trials, with every sixth trial being an easythe optotype size was signicantly larger than the cur-ted threshold. Acuity was recorded as the logarithmmum Angle of Resolution (log MAR), with lower scoresg better visual acuity.

ast sensitivity sensitivity was assessed using the Pelli-Robson con-vity chart (Pelli et al., 1988). The chart consists of eightletters, arranged into groups of three letters. The con-letters reduces for each subsequent triplet. Participants

chart at eye level from a distance of 1 m while wearingon correction. Participants were instructed to read the

the thrscores

2.2.3. The

test ofany cotered aby Moassessistructiinstrucforminstate ocould (Verte

2.2.4. The

designimpairon attspeed.demenmore 2005).indicatcomplerrors a stopw

2.2.5. IT m

high-ca targeshortefor proreduceing to rin the by a mof 10 peach sto ans9/10 itbetwe79% acKranzl

2.2.6. Dri

attentiThe teset al. (on a can altebeen mof objesignal sentatiblank.and thtters. Possible scores range from 0 to 2.25, with higherating better contrast sensitivity.

Mental State Examination (MMSE)i Mental State Examination (MMSE) is a short, simpleal cognitive function used to estimate the extent ofve impairment (Folstein et al., 1975). It was adminis-ding to standardised instructions and scoring proposedand Standish (1997). Participants answer questionsort-term memory, orientation in space and time, con-ability, executive functioning, and ability to follow

s. Participants answer verbally, in writing, and by per-ions when requested. The MMSE is scored out of 30 andnitive impairment can be interpreted as follows: 2630,ormal; 2025, mild; 1019, moderate; 09, severel., 2001).

grove Maze Testllgrove Maze test is a simple pencil and paper mazer use with people with dementia and mild cognitivet (Snellgrove, 2005). Performance on the task dependsnal skills, executive functioning, and psychomotorr drivers with mild cognitive impairment and earlyho took longer than 60 s to complete the maze were

to fail an on-road driving assessment (Snellgrove,maze was presented in black on A4 paper with arrowshe entry and exit points. Participants used a pencil toe maze as quickly as they could while making as fewssible. Time to complete the maze was recorded using

in seconds.

ction Time (IT)res processing speed (Burns and Nettelbeck, 2003). Twost lines, one markedly shorter than the other, appear as

a computer screen. Participants indicate whether the was located left or right of a focal point. Time availableing is limited by a backward masking procedure andextended using an adaptive staircase algorithm accord-nse accuracy. Targets are preceded by a warning cue (+e of the screen, 370 ms) and are immediately followedshaped like two lightning bolts. There were three setsice trials with decreasing target presentation time for5 ms, 420 ms, and 250 ms). Participants were requires0/10 items correctly for the rst and second set, and

for the third set. IT was measured in ms as the durationrget onset and mask onset at which the viewer achievescy. Testretest reliability for adults is .81 (Grudnik and01).

rScanan is a change detection task designed to assess visualkills needed for safe driving (Hoffman et al., 2005).s the change detection paradigm proposed by Rensink). Real world images of driving scenes (A) presenteduter screen were alternated with a blank screen andversion of the image (A) to which a small change has, creating a blinking effect. Changes included deletione.g. cars), colour/lettering changes (e.g. road signs), andges (e.g. trafc lights, brake lights). The pattern of pre-s A, blank, A, blank, A, blank, A, blank, A, blank, A,c., with the images (A, A) being presented for 280 msnk screen being presented for 80ms. There were four

N.A. Matas et al. / Accident Analysis and Prevention 70 (2014) 7483 77

Fig. 1. ProPersix target stim

practice triadid not ansals were repwas presenipants viewbetween A they detectthe experimand these tiparticipant cation of Ite1970, Hoffmresponse (