Annals of Advances in Automotive Medicine © The Relationship between Older Drivers' Performance on the Driving Observation Schedule (eDOS) and Cognitive Performance

Sjaan Koppel, Judith Charlton, Jim Langford, Zafiroula Vlahodimitrakou, Monash University Accident Research Centre, Monash University, Australia

Marilyn Di Stefano, Wendy Macdonald, La Trobe University, Australia

Barbara Mazer, Isabelle Gelinas, McGill University, Canada

Brenda Vrkljan, McMaster University, Canada

Shawn Marshall, Ottawa Hospital Research Institute, Canada

__________________________________ ABSTRACT – Research question/Objective: The Driving Observation Schedule (eDOS) was developed for use in the Candrive/Ozcandrive five-year prospective study of older drivers to observe the driving behavior of older drivers and monitor changes in driving behaviors over time. The aim of this study is to describe participants’ driving performance during the eDOS driving task and investigate the association between driving performance and cognitive measures. Methods: A subset of Ozcandrive participants (n = 144, 104 male [72%], 40 female [28%], Mean age = 81.49 years, SD = 3.58 years, Range: 76 – 96 years) completed the eDOS driving task. Participants drove to their selected destinations (up to 4 locations), with observations of driving behaviors (both inappropriate and appropriate) recorded for specific driving maneuvers: intersection negotiation, lane-changing, merging, low speed maneuvers and maneuver-free driving. Driving behaviors (e.g. signalling, speed regulation, gap acceptance, lane position, ‘critical errors’) were scored by a trained observer and participants received an overall eDOS driving task score (Maximum = 100 points). Participants also completed a series of cognitive assessments as part of the Year 2 Candrive/Ozcandrive assessment protocols. Results: The overall eDOS driving task score was very high (M = 95.77; SD = 5.15; Range = 65.63 - 100). Detailed analyses of participants’ driving behavior revealed a high level of appropriate driving behavior (96%, n = 5,935 maneuvers), with few errors (4%, n = 252 maneuvers). While most participants’ performance on the cognitive assessments was high, some scores were below the criteria for cogntive impairment (BIC) according to conventional benchmarks: (MoCA: M = 26.56, SD = 2.12, Range = 19 – 30, % BIC = 28%; MMSE: M = 29.10, SD = 1.01, Range = 26-30, %BIC = 0%; Trails B: M = 111.66, SD = 43.53, Range = 50 - 301, %BIC = 6%). There was no significant relationship observed between participants’ overall eDOS driving task scores and age (r (144) = -0.17, p > 0.05), and performance on various cognitive assessments including: MoCA (r (144) = 0.07, p > 0.1), MMSE (r (144) = 0.03, p > 0.5), Trail Making Test B (r (144) = 0.09, p > 0.1). Implications: Preliminary analyses of the eDOS driving task revealed a high level of appropriate driving behavior among Ozcandrive older drivers. Despite some participants’ cognitive performance suggesting impairment, participants’ overall eDOS driving task scores were not significantly related to cognitive performance. This finding is consistent with previous research suggesting some older drivers are able to compensate well for age-related cognitive impairment.

__________________________________ INTRODUCTION Older Drivers Over the next five decades, there will be a substantial increase in both the number and proportion of older people in most industrialized countries (OECD, 2001). With the ageing of the population, it is also anticipated that there will be an increase in older drivers’ licensing rates (Sivak & Schoettle, 2011). Further, the private motor vehicle is likely to remain the principal mode of transport for the emerging cohorts of older drivers who, it is predicted, will be more mobile, travel more frequently, travel greater distances, and will have higher expectations with regard to maintaining personal mobility compared with earlier cohorts (OECD, 2001). Demographic growth, increased licensing rates, and increased motor vehicle use will combine to produce a marked increase in the number of older drivers on the road. While current figures show that older drivers are involved in few crashes in terms of absolute numbers, they represent one of the highest risk categories for

crashes involving serious injury and death per number of drivers and per distance travelled (Langford & Koppel, 2006; Koppel, Bohensky, Langford & Taranto, 2011), largely due to their physical fragility and hence increased vulnerability to injury (Augenstein, 2001; Dejeammes & Ramet, 1996; Evans, 1991; Li, Braver & Chen, 2003; Mackay, 1998; Padmanaban, 2001; Viano, Culver, Evans, Frick, & Scott, 1990). In addition, the high prevalence of age-related medical conditions and functional impairments among older drivers also contributes to their heightened crash risk (Marshall, 2008), and thus there is a need for accurate assessments, policies and guidelines regarding fitness to drive in the context of age, as well as specific medical conditions (Vlahodimitrakou, Charlton, Langford, Koppel, Di Stefano, Macdonald, Smith, Porter, Gelinas, Mazer, Vrkljan, & Marshall, In Press). This is a complex policy topic; not all older drivers are unsafe, and while the crash risk associated with ageing may have implications for older drivers at a population level, this may not be reflected at an individual level (Anstey, Wood, Lord, & Walker,

57th AAAM Annual Conference Annals of Advances in Automotive Medicine September 22-25, 2013

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Vol 57 • September 2013 2004). The current paper describes the baseline driving behavior of a cohort of older drivers, using an on-road driving task, the Driving Observation Schedule (eDOS) and investigates the association between driving performance on the eDOS driving task and cognitive measures from the Candrive/Ozcandrive assessment protocols. The Candrive/Ozcandrive Cohort Study The Candrive/Ozcandrive study is a five year, multicentre international research program with the core objective of promoting older drivers’ safe mobility (see Marshall, Man-Son-Hing, Bédard, Charlton, Gagnon, Gélinas, Koppel, Korner-Bitensky, Langford, Naglie, Rapoport, Mazer, Myers, Polgar, Porter, Tuokko, Vrkljan, In Press). The Candrive/Ozcandrive study involves 928 drivers aged 70 years and over in Canada and 302 drivers aged 75 years and older in Australia and New Zealand. Using a longitudinal study design, the project is tracking this cohort of older drivers for up to five years, assessing changes in their functional abilities, driving patterns and driving performance. The primary purpose is to determine and validate a screening test (Decision Rule) to identify potentially at-risk drivers (Marshall et al., In Press). Participants’ driving behavior, including trip duration and distance, is recorded through an in-car recording device (ICRD) installed in the participant’s own vehicle at the beginning of the study. In addition, a range of psychometric measures of functional ability, medical conditions and abilities related to driving are documented annually. The eDOS driving task will be used to study driving behaviors of the Ozcandrive cohort (n = 250 in Australia) and a sub-sample (up to 150) of Candrive participants. Driver Observation Schedule (eDOS) The Driver Observation Schedule (eDOS) is an onroad driving task, designed initially for use in the Ozcandrive study, to evaluate older drivers’ driving behavior in order to monitor changes in individual driving behaviors over time (Koppel, Charlton, Langford, Di Stefano, Macdonald, Mazer, Gelinas, Vrkljan & Marshall, 2012; Vlahodimitrakou, et al., In Press). Additionally, it was expected that such a tool could supplement the (potentially rare) primary outcome measures of crashes (and police-recorded infringements/violations of traffic safety rules and regulations) for validation of the screening test. In developing the eDOS driving task, key criteria were that it should reflect drivers’ everyday driving and be feasible (in light of both time and resources) to sustain within the multi-site, longitudinal study. More specifically, eDOS driving task requirements were: •

observation of ‘natural’ driving with intervention/instruction by the observer;

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no

•

conducted in driver’s own vehicle since Lundberg & Hakamies-Blomquist (2003) found significant differences in driving test outcomes for drivers doing an on-road test using a test vehicle versus their own car); • conducted over routes familiar to and chosen by the older driver; • takes approximately 20-25 minutes to complete; • rates behaviors specifically associated with older driver safety. The Person-Environment (P-E) Fit theory of driving competence (Willis, 2000) and Michon’s Model of Driver Behavior (Michon, 1985) were influential in determining the nature of the eDOS driving task, particularly its emphasis on driver-selected, familiar routes to afford the possibility of observing drivers’ competency in environments presenting the types and levels of demand encountered in their everyday driving (see Vlahodimitrakou, et al., In Press). In addition, item selection and operationalization of the eDOS driving task was based on older driver crash epidemiology (e.g., Catchpole, et al., 2005; Fildes, et al., 1994; Korner-Bitensky, et al., 2006; Langford & Koppel, 2006), older driver self-regulatory behavior (e.g., Charlton, et al., 2006; Baldock, et al., 2006), and published driving measures (e.g., Di Stefano & Macdonald, 2003; 2006; Dobbs, et al., 1998; Galski, et al., 1992; Hunt, et al., 1997; Justiss, 2005; Kowalski, et al., 2010; Malloon & Wood, 2004; Odenheimer, et al., 1994; Ott, et al., 2012). Based on these findings, six categories of driving behaviors were identified for inclusion in the final eDOS driving task: a) Observation of Road Environment; b) Signaling; c) Speed Regulation; d) Gap Acceptance; e) Road-Rule Compliance; and f) Vehicle/Lateral Lane Positioning. The behaviors are scored during driving maneuvers, as appropriate or inappropriate: intersection negotiation, lane-changing, merging, low speed maneuvers and maneuver-free driving (i.e., straight travel path). Vlahodimitrakou and colleagues (In Press) evaluated the inter-rater reliability, feasibility and acceptability of the eDOS driving task on a sub-sample of thirtythree Ozcandrive participants (20 male [61%], 13 female [39%], Mean age = 80.12 years, SD = 3.39, Range: 75-88 years). The authors reported that the eDOS driving task was possible to implement in participants’ own vehicles, could be scored reliably and consistently (ICC = 0.905, CI 95% 0.747-0.965, p < 0.0001; r (18) = .83, p 180 secs have been associated with increased crash risk [see Staplin, Gish, & Wagner, 2003]) from the Candrive/Ozcandrive protocol were used to investigate the relationship between cognitive performance and driving performance on the eDOS driving task. Procedure Ethics Approval was obtained from the Monash University Human Research Ethics Committee (MUHREC), and all participants provided written informed consent. All participants underwent an annual assessment that incorporated a range of psychometric measures of functional ability, medical conditions and abilities related to driving (see Marshall et al., In Press). The annual assessment was conducted up to eight months before participants completed the eDOS driving task. The eDOS driving task was implemented by a single trained observer who underwent six hours of training with an Occupational Therapist Driving Expert in

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both classroom and on-road environments. Training included familiarization with the eDOS observation and recording procedures, general principles of driving assessment and the video recording equipment setup and installation. The eDOS driving task commenced from each participant’s home and was conducted on routes familiar to and chosen by the participants. Prior to commencement of the trip, participants were asked to nominate up to four nearby locations to which they regularly drive, and to devise a driving route commencing and ending at home and linking the nominated destinations within a 20-25 minute round trip. Throughout the eDOS driving task, the observer documented driving behavior for maneuvers specified in the eDOS driving task as they occurred during the agreed route, scoring these against the eDOS driving task criteria. The observations were conducted in the participants’ vehicle with the observer seated in the rear left seat (i.e., behind the front passenger seat) to ensure that critical aspects of driving behavior were observable (see Fox, Bowden, & Smith, 1998). The eDOS driving task was designed to study driving behaviors that reflect everyday driving, so drivers were encouraged to behave as they normally would, including listening to the radio or music etc. They were also permitted to have their regular passenger travel with them, if they so chose, and such passengers were allowed to assist with navigation. In addition, several eDOS driving task appointments were rescheduled due to bad weather when the participant(s) reported that they never drove in bad weather (e.g., rain, hail, etc.). RESULTS eDOS driving task descriptives The average duration for the eDOS driving task for all participants was 24 min, 54 s (SD = 7 min 59 s, range 12 min, 39 sec – 1 hour, 5 min, 57 sec), with the majority of participants completing the eDOS driving task within 5 minutes of the target range of 20-25 minutes (90%), and the average distance driven during the eDOS driving task was 13.32 km (SD = 5.25, Range = 5 km – 29 km) (Note: Due to technical difficulties with tablet, driving distance was only available for n = 92 participants). Most participants drove to one or two nominated nearby destinations (1 destination = 47%, 2 destinations = 36%, 3 destinations = 15%, 4 destinations = 2%), with many participants nominating a shopping centre or local shopping strip as one of their destinations (46%). Participants also nominated sports/hobbies (25%), family or friends’ houses (14%), their medical centers or practices (5%), and their Church (3%).

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Gap acceptance

eDOS driving task performance The average eDOS driving task score (Maximum = 100) was high (M = 95.77; SD = 5.15; Range = 65.63 - 100). A summary of the frequency of driving maneuvers observed during the eDOS driving task, including intersection negotiation, lane changing and merging, is presented in Table 2. Table 2 – Summary of observed driving maneuvers during the eDOS driving task Mean (SD) Observed Intersections (all) Traffic lights (with arrow) Turning left Turning right Traffic lights (no arrow) Turning left Turning right Straight through Controlled Intersection (No traffic light) Turning left Turning right Straight through Uncontrolled Intersection Turning left Turning right Straight through Roundabout (any maneuver) U-turn, any intersection Lane Changes Merges

Range Observed

0.19 (0.43) 1.24 (1.12)

0-2 0-5

1.03 (1.08) 0.99 (0.99) 12.41 (8.74)

0-4 0-4 0-47

2.19 (1.43) 0.98 (0.96) 0.22 (0.53)

0-7 0-5 0-2

3.68 (2.31) 3.24 (1.88) 0.03 (0.16) 3.34 (3.31) 0.21 (0.44) 7.98 (4.95) 1.44 (1.13)

0-13 0-8 0-1 0-18 0-2 1-31 0-4

Preliminary analyses of participants’ driving behavior during intersection negotiation, lane changing and merging is presented below. Intersection negotiation. The driving behavior, including both appropriate and inappropriate behavior, observed during intersection negotiation is shown in Table 3. Table 3 – Instances of appropriate and inappropriate driving behavior observed during intersection negotiation Intersection Negotiation Behavior Total Intersections Appropriate Behavior Inappropriate Behavior Frequency of Inappropriate Behavior observed: Inappropriate Signaling Speed regulation Too fast Too slow Lateral lane position Out of lane Hitting curb Observation of road No mirror use environment No looking

Annals of Advances in Automotive Medicine

Percentage (Number) n = 4, 312 97 (4,181) 3 (131) 64 34 0 7 19 1

Road rule compliance

Missed opportunity Unsafe gap Failure yielding Non compliance lights/signs Crossing pavement

3 6 0 11 0

As shown in Table 3, the most common errors observed during intersection negotiation included: inappropriate signaling (n = 64), driving too fast (n = 34), hitting the curb (n = 19) or non compliance with road rules (n = 11). The driving behavior, including both appropriate and inappropriate behavior, observed during different intersection types is shown in Table 4. Due to technological difficulties, intersection type was only available for 98 percent of the intersections observed (n = 4,312). Table 4 – Instances of appropriate and inappropriate driving behavior observed during different intersection types Intersection Type

Traffic lights (with arrow) Turning left Turning right Traffic lights (no arrow) Turning left Turning right Straight through Controlled Intersection (No traffic light) Turning left Turning right Straight through Uncontrolled Intersection Turning left Turning right Straight through Roundabout (any maneuver) U-turn, any intersection Total

Percentage Appropriate (Number)

Percentage Inappropriate (Number)

89 (25) 98 (175)

11 (3) 2 (4)

100 (150) 97 (140) 100 (1794)

0 (0) 3 (5) 0 (8)

93 (294) 96 (135) 97 (31)

7 (21) 4 (6) 3 (1)

95 (508) 98 (461) 100 (4) 91 (437) 90 (27) 97 (4,181)

5 (24) 2 (11) 0 (0) 9 (45) 10 (3) 3 (131)

As shown in Table 4, participants were most likely to make errors while turning left at a traffic light with an arrow (11%), making a U-turn (10%), negotiating a roundabout (9%) and turning left at a controlled intersection (e.g., stop sign or giveway/yield sign, 7%). Note, in Australia, right turns are made across traffic. Lane changing. The driving behavior, including both appropriate and inappropriate behavior, observed during lane changes is shown in Table 5. Table 5 – Instances of appropriate and inappropriate driving behavior observed during lane changes

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Vol 57 • September 2013 Lane Changing Behavior Total Lane changes coded Appropriate Behavior Inappropriate Behavior Frequency of Inappropriate Behavior observed: Inappropriate Signaling Speed regulation Too fast Too slow Vehicle positioning Out of lane Hitting curb Inappropriate following distance Observation of road No mirror use environment No looking Gap acceptance Missed opportunity Unsafe gap Failure yielding

Percentage (Number) n = 1,149 93 (1,074) 7 (77) 69 2 0 1 0 0

Relationship between driving performance on eDOS driving task and cognitive measures.

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Participants’ performance on cognitive measures from the Candrive/Ozcandrive assessment protocol was quite high according to conventional benchmarks for cognitive impairment (see Table 7).

3 0 1 0

As shown in Table 5, the most common errors observed during lane changes included: signaling (n = 69), not looking (n = 3) or driving too fast (n = 2). Merging. The driving behavior, including both appropriate and inappropriate behavior, observed during merging is shown in Table 6. Table 6 – Instances of appropriate and inappropriate driving behavior observed during merges Merging Behavior Total Merges coded Appropriate Behavior Inappropriate Behavior Frequency of Inappropriate Behavior observed: Inappropriate Signaling Speed regulation Too fast Too slow Vehicle positioning Out of lane Hitting curb Inappropriate following distance Observation of road No mirror use environment No looking Gap acceptance Missed opportunity Unsafe gap Failure yielding

Percentage (Number) n = 207 90 (187) 10 (20) 16 0 0 0 0 0 0 2 0 2 0

As shown in Table 6, errors observed during merging included: inappropriate signaling (n = 16), not looking (n = 2) or choosing an unsafe gap (n = 2). Critical Errors. Seven critical errors were observed across the 144 eDOS drives: - One participant backed into the mailbox while reversing out of his driveway; this participant also drifted out of his lane, almost colliding with another car while trying to shut his door on the freeway and performed an illegal U-turn within the central business district (CBD) while waiting on tram lines;

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- Two participants performed unsafe merges by speeding up and forcing other cars to slow down and give them right of way; - One participant performed a lane change in an unsafe gap, and - One participant failed to notice a pedestrian behind his car while reversing out of a car park at a shopping centre. The pedestrian took evasive action to avoid a collision.

Table 7 – Participants’ performance on selected cognitive measures Cognitive measure

Mean (SD)

Range

Benchmark for cognitive impairment

% (N) below impariment criteria

MOCA

26.56 (2.22)

19 - 30

< 26

28% (41)

MMSE

29.10 (1.01)

26 - 30

< 24

0% (0)

Trails B

111.66 sec (43.53)

50 - 301 sec

> 180 sec

6% (9)

A series of bivariate correlations were undertaken to investigate the relationship between driving performance on eDOS driving task and age and cognitive measures. There was no significant relationship observed between participants’ overall eDOS driving task scores and age (r (144) = -0.17, p > 0.05), and their performance on various cognitive measures including: MoCA (r (144) = 0.07, p > 0.1), MMSE (r (144) = 0.03, p > 0.5), and Trail Making Test B (r (144) = 0.09, p > 0.1). In addition, there was no significant difference in overall eDOS driving task scores for participants who scored above and below the cognitive impairment criteria for the MoCA (Above: M = 96.06, SD = 5.34; Below: M = 95.03, SD = 4.63, t(142) = -1.084, p > 0.1). Post-drive Survey. When asked about their driving performance during the eDOS driving task compared with their everyday driving (where 1 = much better, 3 = about the same, 5 = much worse), most participants rated their eDOS driving task performance as ‘about the same’ as their everyday driving (97%). Several participants (3%, n = 3) indicated that their driving performance was ‘better’ during the eDOS driving task. Participants were then asked to rate the difficulty of the eDOS driving task compared with the difficulty of their everyday driving (where 1 = much less difficult, 3 = about the same, 5 = much more difficult). Most participants rated the difficulty of the eDOS driving

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task as ‘about the same’ as their everyday driving (74%). Interestingly, 21 percent of participants rated the eDOS driving task as ‘a little less difficult’ and five percent rated the eDOS driving task as ‘a little more difficult’ compared with their everyday driving. Participants were asked to rate their level of familiarity with the route undertaken during the eDOS driving task (where 5 = completely familiar, 3 = neither familiar or unfamiliar, 1 = completely unfamiliar). Most participants reported that they were ‘highly familiar’ (94%) or ‘familiar’ (6%) with the eDOS route. Finally, participants were asked to rate their level of comfort with being observed during the eDOS driving task (where 5 = completely at ease, 1 = completely uneasy). Most participants reported that they were ‘completely at ease’ (73%) being observed during the eDOS driving task and the remaining participants reported that they were ‘at ease’ (27%). DISCUSSION The aim of this study was to describe participants’ driving performance during the eDOS driving task and investigate the association between driving performance on the eDOS driving task and cognitive measures from the Candrive/Ozcandrive assessment protocol. The findings of the current study demonstrate that a suitable eDOS driving task could be formulated from drivers’ self-nominated destinations (Mean duration of eDOS driving task: 24 min, 54 s, SD = 7 min 59 s), with the majority of drivers completing the eDOS driving task within five minutes of the targeted range of 20-25 minutes (90%) and almost half of the destinations nominated by participants included shopping centers (46%). Consistent with the findings of the pilot study described by Vlahodimitrakou and colleagues (In Press), overall eDOS driving task scores (Maximum = 100) for a sample of Ozcandrive participants (n = 144) was very high (M = 95.77; SD = 5.15). Detailed analyses of participants’ driving behaviour revealed high levels of appropriate driving behaviour during intersection negotiation (97%), lane changing (93%) and merging (90%). Compared with other studies (e.g. Di Stefano & Macdonald, 2003) drivers’ error rates were very low. This difference may reflect the relatively better health of the present sample compared with that of Di Stefano and Macdonald (2003), in which drivers had been referred to the licensing authority for review because their driving competence was in question. Interestingly, the majority of inappropriate behaviours observed in the current study across all driving manoeuvres were signalling errors. A proportion of behaviours could potentially impact more on safety, including poor gap

Annals of Advances in Automotive Medicine

choices at intersections and inappropriate speed choices (too fast) for all three manoeuvre categories. In terms of intersection negotiation, the most common errors observed included: inappropriate signalling, driving too fast or hitting the curb. The types of errors observed at intersections in the current study are consistent with those observed in other recent intersection error studies with younger, middle-aged and older drivers (Gstalter & Fastenmeier, 2010; Young, Salmon & Lenne, 2012). When driving errors were compared across intersection types, participants in the current study were most likely to make errors while turning left at a traffic light with an arrow (11%), making a U-turn (10%), negotiating a roundabout (9%) and turning left at a controlled intersection (e.g., stop sign or giveway/yield sign, 7%). This finding is somewhat consistent with the findings recently reported by Gstalter and Fastenmeier (2010) who reported that the highest errors occurred for non-signalised intersections and roundabouts for all drivers. In particular, the authors noted that older drivers were most likely to commit inappropriate signalling errors (false or missing) at roundabouts, especially at the exit. Undergoing a driving ‘evaluation’ in which driving performance is scrutinized can often be very stressful for older individuals. Therefore, ensuring that drivers are at ease with being observed and comfortable with demands of the route is a key requirement for eDOS driving task acceptability (Vlahodimitrakou et al., In Press). From a road safety viewpoint, it is also desirable that the eDOS driving task reflect everyday driving. While the researchers were careful to emphasize to participants that the eDOS driving task was not a test, we were conscious that the task was somewhat contrived in its destination-chaining requirements (primarily to ensure that trip duration was not excessive), and that presence of an observer may cause discomfort and/or alter performance. Results of the post-drive survey showed that most participants rated their overall driving during the eDOS driving task as ‘about the same when compared with their normal driving’ (97%) and that, even though they knew they were being observed, they were ‘completely at ease’ (73%). It seems likely that the use of drivers’ own vehicles contributed to their feelings of ‘ease’ with the eDOS driving task procedure, although there is no direct evidence of this. Research by Lundberg and Hakamies-Blomqvist (2003) reported higher fail rates for medically-referred drivers using a test vehicle compared with drivers using their own vehicles. The authors attributed the result to drivers’ need to adapt to an unfamiliar vehicle, which imposed an additional cognitive load that compromised their driving ability. Overall, present findings suggest that the participants believed that their performance on the eDOS driving task was representative of their everyday driving. This suggests

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Vol 57 • September 2013 that eDOS driving task has a high level of face validity in reflecting drivers’ everyday driving. Given the increasing international interest and use of modified (local area) licenses (Langford & Koppel, 2011), the eDOS driving task also offers a promising approach for test construction. Participants’ overall eDOS driving task scores were not significantly related to their age or their performance on selected cognitive measures from the Candrive/Ozcandrive assessment protocol. This is not surprising, given that only a small proportion of the sample’s performance may be suggestive of cognitive impairment according to conventional benchmarks (e.g., 28% scored < 26 on the MoCA [Nasreddine et al., 2005]; 0% scores < 24 on the MMSE [Folstein et al., 1995]; 6% scored > 180 sec on Trails Making Part B [Staplin et al., 2003]). It will be important to explore the potential relationship between performance on the eDOS driving task and cognitive performance with the full sample (n = 250), as well as to explore potential age-related cognitive changes over the 5 year period of the cohort study. In addition, as noted by Vlahodimitrakou and colleagues (In Press), several issues relating to the coding and computation of eDOS driving task scores need further investigation. First, coding of appropriate/inappropriate performance for the driving maneuvers within the eDOS driving task relied on subjective judgments of the trained observer. However, we provided a detailed data dictionary and instruction manual to guide the coding of observations and to improve objectivity of judgments. Inter-rater reliability of the eDOS driving task is currently being explored. Second, the computation of the total eDOS driving task score was adapted from an approach commonly employed in driving assessment research (see Di Stefano & Macdonald, 2003; Odenheimer et al., 1994). Weighting of errors is controversial due to the multitude of factors that contribute to the level of “severity” assigned to a given error and the possible range of safety implications resulting from the error (Dobbs et al, 1998, Di Stefano & Macdonald, 2006). For example, Justiss and Stav (2006) and others (e.g., Dobbs et al., 1998) used a more complex rating of errors and applied heavier penalty to critical errors. It should be noted that only seven critical errors were observed and therefore, regardless of the weighting assigned here, its contribution to overall eDOS driving task scores in the current study was minimal. Future research is proposed to explore weighting of errors and implications for safety, as discussed below. Third, a limitation of the total eDOS driving task score is that it can be interpreted only in relative terms, meaning that any given driver has demonstrated more or fewer errors over time (e.g., over the duration of the Ozcandrive/Candrive study),

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or more/fewer errors than another driver. It is also possible to use eDOS driving task observations to describe driver performance in terms of patterns of maneuvers made and types of errors (e.g., gap acceptance, signaling). In addition, there is an opportunity for refinement of the current scoring approach to enable determination of how much a given difference in scores matters from a safety viewpoint. Recent work by Classen and colleagues (Classen, Shechtman, Awadzi, Joo, & Lanford, 2010) demonstrated a hierarchy of importance of errors in predicting crash-related injury with highest probability for injury associated with lane maintenance, yielding, and gap acceptance errors; moderate associations with speed regulation; and vehicle positioning and adjustment to stimuli conferring a low probability. Their findings will be useful for advancing the measurement of driving errors and associated safety effects. It will be important that further analyses are conducted to explore the potential refinement of the present scoring system before application to the rest of the sample. CONCLUSION Preliminary analyses of the eDOS driving task revealed a high level of appropriate driving behavior among Ozcandrive older drivers (96%). Despite some participants’ cognitive performance suggesting cognitive impairment, participants’ overall eDOS driving task scores were not significantly related to cognitive performance. This finding is consistent with previous research which suggests that at least some older drivers are able to compensate well for agerelated cognitive impairment. It should be noted that these findings are based on a subsample of Ozcandrive participants. Future analyses are planned, including: 1) using a range of measures collected through the Candrive/Ozcandrive annual assessments to investigate whether changes in functional performance or health might predict changes in individuals’ driving performance on the eDOS driving task over time, and 2) using participants’ real-world driving data to investigate whether their driving performance during the eDOS driving task is representative of their everyday driving performance. ACKNOWLEDGEMENTS The Candrive II study was funded by a Team Grant from the Canadian Institutes of Health Research (CIHR) entitled “The CIHR Team in Driving in Older Persons (Candrive II) Research Program” (grant 90429). The Candrive eDOS subproject is funded by AUTO21 – A Network of Centres of Excellence (NCE). Ozcandrive (including the Ozcandrive eDOS subproject) is funded by an Australian Research Council Linkage Grant (LP 100100078) to the Monash University in partnership with La Trobe University, VicRoads, Victorian Government Department of Justice and Victoria Police, the

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Transport Accident Commission, Road Safety Trust New Zealand and Eastern Health. The authors gratefully acknowledge the invaluable contribution of Amy Allen, Lorraine Atkinson, Louise Beasley, Russ Boag, Matthew Catchlove, Cara Dawson, Johan Davydov, Yik-Xiang Hue, Elizabeth Jacobs, Duncon Joiner, Jason Manakis, Kevin Mascarenhas and Jarrod Verity, who assisted with the Ozcandrive data collection, as well as the eDOS and camera implementation. We thank the Candrive/Ozcandrive teams and the older driver participants, without whose valuable input and commitment, this research would not be possible. REFERENCES Anstey, K.J., Wood, J., Lord, S., Walker, J.G. Cognitive, sensory and physical factors enabling driving safety in older adults. Clinical Psychology Review, 25: 45-65, 2004 Augenstein, J. Differences in clinical response between the young and the elderly. Paper presented at the Aging and Driving Symposium, Association for the Advancement of Automotive Medicine, Des Plaines, IL, 2001 Austroads. Assessing fitness to drive for commercial and private vehicle drivers. Medical standards for licensing and clinical management guidelines. A resource for health professionals in Australia, Sydney, Australia, 2006 Baldock MRJ, Mathias J, McLean J, Berndt A. Self-Regulation of Driving and Older Drivers' Functional Abilities. Clinical Gerontologist 30: 53-70, 2006 Ball, K.K., Roenker, D.L., Wadley, V.G., Edwards, J.D., Roth, D.L., McGwin, G. Jr., Raleigh, R., Joyce, J.J., Cissell, G.M., Dube T. Can high-risk older drivers be identified through performance-based measures in a Department of Motor Vehicles setting? Journal of American Geriatric Society 54: 77–84, 2006 Catchpole J, Styles T, Pyta V, Imberger K. Exposure and accident risk among older drivers (Report No. 366) Australia: ARRB Group Ltd, 2005 Charlton, J.L., Oxley, J., Fildes, B., Oxley, P., Newstead, S., Koppel, S., & O’Hare, M. Characteristics of older drivers who adopt self-regulatory driving behaviours. Transportation Research Part F: Traffic Psychology and Behaviour 9(5): 363373, 2006 Classen, S., Shechtman, O., Awadzi, K. D., Joo, Y., & Lanford, D. N. Traffic violations versus driving errors of older adults: Informing clinical practice. American Journal of Occupational Therapy, 64: 233–241, 2010 Davey, R.J., Jamieson, S. The validity of using the mini mental state examination in NICE dementia guidelines. Journal of Neurology, Neurosurgery and Psychiatry 75(2): 343–344, 2004 Dejeammes, M., & Ramet, M. Aging process and safety enhancement of car occupants. Paper presented at the 15th International Technical Conference on the Enhanced Safety of Vehicles, Melbourne, Australia, 1996

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