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 (Organization for Economic Cooperation and Development [OECD], 2001). With the aging of the population, an increase is also anticipated in older drivers’ licensing rates (Sivak & Schoettle, Reference Sivak and Schoettle2011). Further, the private motor vehicle is likely to remain the principal mode of transport for the emerging cohorts of older drivers who will be more mobile, and travel more frequently and at greater distances when 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.

Although there is strong support around the world for older people to maintain independent vehicular mobility for as long as possible, their safety is also a serious community concern necessitating development of innovative measures to reduce crash and injury risk (Langford & Koppel, Reference Langford and Koppel2006). While current figures show that older drivers are involved in few crashes in terms of absolute numbers, they represent one of the highest risk groups for crashes involving serious injury and death per number of drivers and per distance travelled (Koppel, Bohensky, Langford, & Taranto, Reference Koppel, Bohensky, Langford and Taranto2011; Langford & Koppel, Reference Langford and Koppel2006).

Older Driver Risk Factors

Much of the older driver crash profile has been attributed to older drivers’ greater frailty and reduced tolerance to injury (OECD, 2001). The energy required to cause injury reduces as a person ages (Augenstein, Reference Augenstein2001): Older adults’ biomechanical tolerances to injury are lower than those of younger persons (Mackay, Reference Mackay1998; Viano, Culver, Evans, Frick, & Scott, Reference Viano, Culver, Evans, Frick and Scott1990), primarily due to reductions in bone and muscular strength and fracture tolerance (Dejeammes & Ramet, Reference Dejeammes and Ramet1996; Padmanaban, Reference Padmanaban2001). For example, according to Evans (Reference Evans2004), in crashes of equal severity, consider these statistics: A 79-year-old man is 3.2 times more likely to die as a 32-year-old man; a 79-year-old woman is 2.7 times more likely to die as a 32-year-old woman; and one-half of the deaths to those aged 70 and older would not occur if the individuals were as robust as those aged 69 and younger. Li, Braver, and Chen (Reference Li, Braver and Chen2003) used the U.S. Fatality Analysis Reporting System (FARS) and a national probability sample of all crashes (both non-casualty and casualty) to compute the role of frailty in older driver crashes. After due statistical correction, the authors reported that older drivers’ (and especially older female drivers’) overrepresentation in fatalities could be explained mainly by frailty, accounting for around 60 to 90 per cent of the fatalities.

In addition to the frailty factor, older drivers’ crash risk has been attributed to their age-related sensory, cognitive, and physical impairments. Although there are many individual differences in the aging process, even relatively healthy older adults are likely to experience some level of functional decline in sensory, cognitive, and physical abilities. These include a decline in visual acuity and/or contrast sensitivity; visual field loss; reduced dark adaptation and glare recovery; loss of auditory capacity; reduced perceptual performance; reductions in motion perception; a decline in attentional and/or cognitive processing ability; reduced memory functions; neuromuscular and strength loss; postural control and gait changes, and slowed reaction time (Janke, Reference Janke1994; Stelmach & Nahom, Reference Stelmach and Nahom1992). Of relevance to older drivers is how the declines in these abilities relate to skills required for safe driving and whether skill changes put them at an increased risk of crash-related injuries and/or death.

Current evidence for causal relationships between specific medical conditions and increased crash risk is limited (Charlton et al., Reference Charlton, Koppel, Odell, Devlin, Langford and O’Hare2010; Dobbs, Reference Dobbs2001; Marshall, Reference Marshall2008). Clearly, not all medical conditions affect injury risk in the road system to the same extent, and not all individuals with the same condition will be affected in the same way (Charlton et al., Reference Charlton, Koppel, Odell, Devlin, Langford and O’Hare2010). The severity of the condition and other characteristics of the disorder are likely to be important determinants of crash risk. Notwithstanding the paucity of evidence linking health, medical conditions, and driving, there is mounting evidence that a number of age-related functional impairments may be of sizable concern to road safety. Importantly, it is not necessarily the medical condition and/or medical complications per se that affect driving, but rather the functional impairments that may be associated with these conditions. In discussing the merits of focussing on impairments in assessing risk, Marottoli (2001) noted that functional impairments are “the common pathway through which … medical conditions affect driving capability and … can be relatively easy to test” (p. 11). Moreover, the extent to which individuals may be able to adapt or compensate for their impairment while driving will undoubtedly have some bearing on their likelihood of crash involvement (Charlton et al., Reference Charlton, Oxley, Fildes, Oxley, Newstead and Koppel2006).

Indeed, Meyer (Reference Meyer2004) has proposed that drivers can be highly adaptive and can compensate for deficiencies in certain areas by adapting their behaviour (i.e., changing the conditions in which they drive, using different driving techniques, or using in-vehicle technologies to assist with some of their deficiencies) to minimise their crash risk. Older drivers’ capacity to moderate their risk is a crucial element in determining their safety. Many older drivers become aware of their declines in functional capacities and adapt their driving patterns to match these changes by self-regulating when, where, and how they drive (Baldock, Mathias, McLean, & Berndt, Reference Baldock, Mathias, McLean and Berndt2006; Blanchard, Myers, & Porter, Reference Blanchard, Myers and Porter2010; Charlton et al., Reference Charlton, Oxley, Fildes, Oxley, Newstead and Koppel2006; Molnar & Eby, Reference Molnar and Eby2008). For example, older adults may reduce their exposure by driving fewer annual kilometres, making shorter trips, and making fewer trips by destination chaining (i.e., linking multiple trips together) (Benekohal, Michaels, Shim, & Resende, Reference Benekohal, Michaels, Shim and Resende1994). Older drivers have also been found to do the following: avoid complex traffic maneuvers that are cognitively demanding (Ball et al., Reference Ball, Owsley, Stalvey, Roeneker, Sloane and Graves1998; Hakamies-Blomqvist & Wahlstrom, Reference Hakamies-Blomqvist and Wahlstrom1998); limit their peak hour and night driving; restrict long-distance travel; take more frequent breaks; and drive only on familiar and well-lit roads (Ernst & O’Connor, Reference Ernst and O’Connor1988; Smiley, Reference Smiley1999).

Several studies have also shown that most older drivers recognize that good vision is one of the most important elements for safe driving and often cite poor vision as a major determinant for reducing their driving at night or in poor weather (Kostyniuk & Shope, Reference Kostyniuk and Shope1998; Marottoli et al., Reference Marottoli, Ostfield, Merril, Perlman, Foley and Cooney1993; Persson, Reference Persson1993). This evidence suggests that at least some older adults are able to compensate well for limitations in their abilities in such a way that is likely to minimise exposure to difficult driving situations to reduce their crash risk.

In addition, recent research has demonstrated a link between psychosocial factors (e.g., attitudes, beliefs, and perceptions) and older driver self-regulation (Tuokko et al., Reference Tuokko, Myers, Jouk, Marshall, Man-Son-Hing and Porter2013). For example, measures of these constructs specific to the context of driving have been linked to self-reported restrictions in older drivers (Blanchard & Myers, Reference Blanchard and Myers2010; MacDonald, Myers, & Blanchard, Reference MacDonald, Myers and Blanchard2008; Myers, Paradis, & Blanchard, Reference Myers, Paradis and Blanchard2008; Webber, Porter, & Menec, Reference Webber, Porter and Menec2010), as well as objectively measured restrictions in driving exposure (i.e., distance, duration) and patterns (i.e., radius from home, driving at night and in bad weather) (Blanchard & Myers, Reference Blanchard and Myers2010; Myers, Trang, & Crizzle, Reference Myers, Trang and Crizzle2011; Myers et al., Reference Myers, Paradis and Blanchard2008).

On-road Assessments

On-road assessments have been described by driving rehabilitation specialists as the “gold standard” for determining a driver’s true driving ability and for identifying potential remediable elements (Justiss, Reference Justiss2005; Marcotte & Grant, Reference Marcotte and Grant2009; McCarthy, Reference McCarthy2005). Despite the potential importance of on-road assessments for determining older drivers’ fitness to drive, there is a paucity of research in this area.

Within the limited number of studies that have been conducted in this area, most researchers acknowledge the value of standardizing on-road assessments to allow objective measurement of driving performance (e.g., Di Stefano & Macdonald, Reference Di Stefano and Macdonald2010; Korner-Bitensky, Bitensky, Sofer, Man-Son-Hing, & Gelinas, Reference Korner-Bitensky, Bitensky, Sofer, Man-Son-Hing and Gelinas2005; Withaar, Brouwer, & Van Zomeren, Reference Withaar, Brouwer and Van Zomeren2000). On-road assessments are standardized by developing geographically replicable pre-determined maneuvers rated on explicit criteria on fixed routes (Kowalski & Tuokko, Reference Kowalski and Tuokko2007). Moreover, it has been argued that when a representative range of traffic conditions at an appropriate level of difficulty are performed by the driver, driving competence is more accurately evaluated, as the assessor is able to observe critical aspects of driver performance (Di Stefano & Macdonald, Reference Di Stefano and Macdonald2003). Consequently, researchers have developed a wide range of psychometrically sound standardised on-road assessments that can be applied to specific populations with specialised conditions and broader populations of older drivers (Kowalski & Tuokko, Reference Kowalski and Tuokko2007).

Although standardised on-road assessments serve a vital purpose in distinguishing safe from unsafe older drivers (MacDonald, Pellerito, & Di Stefano, Reference MacDonald, Pellerito, Di Stefano and Pellerito2006), there are circumstances where a less-structured assessment route and protocol may be justified. The appropriateness and value of assessments conducted over routes familiar to and chosen by the older driver have been asserted by driving rehabilitation specialists and researchers (Justiss, Reference Justiss2005; Withaar et al., Reference Withaar, Brouwer and Van Zomeren2000). These on-road assessments, commonly referred to as personalised assessments, are inherently non-standardised (MacDonald et al., Reference MacDonald, Pellerito, Di Stefano and Pellerito2006). Although, in theory, all drivers are expected to deal with any environmental demands, in practice the intensity and quantity of environmental demand experienced are unique to each driver (Nasvadi, Reference Nasvadi2007). The core assumption behind the utilisation of non-standardised tests is that customised assessments provide more ecological validity in terms of matching assessment requirements to the specific real-world driving needs of the driver (Nasvadi, Reference Nasvadi2007).

It has been noted that personalised non-standardised tests could be appropriate where geographic licensing restrictions are available (Justiss, Reference Justiss2005). Indeed, some research suggests that driving restrictions may be an effective measure for reducing crash risk for some older drivers, thus prolonging their continued independence and mobility (Nasvadi & Vavrik, Reference Nasvadi and Vavrik2007). Furthermore, it has been argued that personalised, non-standardised assessments more closely resemble drivers’ everyday driving and provide greater ecological validity (Withaar et al., Reference Withaar, Brouwer and Van Zomeren2000).

A major consideration for on-road assessments is whether to use the driver’s own vehicle, or an instrumented, dual-control test vehicle. Using the same instrumented vehicle with dual-control brakes for each assessment enhances the standardization of the evaluation by ensuring that the mechanical conditions of the vehicle are the same for each driver. This also has the simultaneous benefit of improving passenger (assessor) safety (Fox, Reference Fox1989; Kowalski & Tuokko, Reference Kowalski and Tuokko2007). However, research has shown that the processes involved in adapting to an unfamiliar vehicle may be problematic for driving performance in older drivers, and thus compromise the validity of the overall assessment (Lundberg & Hakamies-Blomqvist, Reference Lundberg and Hakamies-Blomqvist2003). Indeed, research has demonstrated that for older drivers, simple motor components of the driving task, such as manual gear shifting, are not easily automated and can impair driving performance, until familiarised (Lundberg & Hakamies-Blomqvist, Reference Lundberg and Hakamies-Blomqvist2003). Moreover, Lundberg and Hakamies-Blomqvist (Reference Lundberg and Hakamies-Blomqvist2003) suggested that various features of compensatory behaviour will not emerge unless the driver can make strategic decisions regarding the choice of the vehicle.

Candrive/Ozcandrive Study

The Candrive/Ozcandrive study is a longitudinal, multi-centre international research program with the core objective of identifying solutions to promote older drivers’ safe mobility (Marshall et al., Reference Marshall, Man-Son-Hing, Bédard, Charlton, Gagnon and Gélinas2013). The Candrive/Ozcandrive study involves 928 drivers aged 70 and over in Canada and 302 drivers aged 75 and older in Australia and New Zealand (Australia: n = 257; New Zealand: n = 45). Using a longitudinal study design, the project is tracking this cohort of older drivers for up to six years, assessing changes in their functional abilities, driving practices (e.g., exposure and patterns), as well as crashes and citations. The primary purpose is to determine and validate a screening test (Decision Rule) to identify potentially at-risk drivers (Marshall et al., Reference Marshall, Man-Son-Hing, Bédard, Charlton, Gagnon and Gélinas2013). Participants’ usual (or naturalistic) driving practices (e.g., trip distance, duration, type of road, speed) are recorded through an in-car recording device installed in the participant’s own vehicle, and measures of participants’ functional ability, medical conditions, and self-reported driving-related abilities and practices are documented annually. In addition, participants’ driving behaviour is evaluated annually through an on-road driving task.

electronic Driver Observation Schedule (eDOS)

The eDOS is an on-road driving task, designed initially for use in the Ozcandrive study to evaluate older drivers’ driving behaviour in order to monitor changes in individual driving behaviours over time (Koppel et al., Reference Koppel, Charlton, Langford, Vlahodimitrakou, Di Stefano and Macdonald2013; Vlahodimitrakou et al., Reference Vlahodimitrakou, Charlton, Langford, Koppel, Di Stefano and Macdonald2013). Additionally, it was expected that such a tool could supplement the (relatively 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, the five eDOS driving task requirements were as follows:

• • observation of “natural” driving with no intervention/instruction by the observer;

• • conducted in driver’s own vehicle (following positive effects reported by Lundberg & Hakamies-Blomquist (Reference Lundberg and Hakamies-Blomqvist2003) as noted above);

• • conducted over routes familiar to and chosen by the older driver;

• • took approximately 20–25 minutes to complete;

• • rated behaviours specifically associated with older driver safety.

The Person-Environment (P-E) Fit theory of driving competence (Willis, Reference Willis2000) and Michon’s Model of Driver Behaviour (Michon, Reference Michon1989) were influential in determining the nature of the eDOS driving task. Consequently, the eDOS driving task was designed to be undertaken on driver-selected routes to observe drivers’ competency in environments encountered in their everyday driving. In addition, item selection and operationalization of the eDOS driving task was based on three factors: (a) older-driver crash epidemiology (e.g., Catchpole, Styles, Pyta, & Imberger, Reference Catchpole, Styles, Pyta and Imberger2005; Fildes et al., Reference Fildes, Corben, Kent, Oxley, Le and Ryan1994; Langford & Koppel, Reference Langford and Koppel2006), (b) older driver self-regulatory behaviour (e.g., Baldock et al., Reference Baldock, Mathias, McLean and Berndt2006; Charlton et al., Reference Charlton, Oxley, Fildes, Oxley, Newstead and Koppel2006), and (c) published driving measures (Di Stefano & Macdonald, Reference Di Stefano and Macdonald2003; Dobbs, Heller, & Schopflocher, Reference Dobbs, Heller and Schopflocher1998; Galski, Bruno, & Ehle, Reference Galski, Bruno and Ehle1993; Hunt et al., Reference Hunt, Murphy, Carr, Duchek, Buckles and Morris1997; Justiss, Reference Justiss2005; Kowalski & Tuokko, Reference Kowalski and Tuokko2007; Ott, Papandonatos, Davis, & Barco, Reference Ott, Papandonatos, Davis and Barco2012). Based on these findings, we identified six categories of driving behaviours for inclusion in the final eDOS driving task: (a) observation of road environment; (b) signalling; (c) speed regulation; (d) gap acceptance; (e) road-rule compliance; and (f) vehicle/lateral lane positioning (see Table 1 for the definitions for inappropriate driving behaviours). We scored the behaviours during driving maneuvers, as appropriate or inappropriate: intersection negotiation, lane-changing, merging, low-speed maneuvers, and maneuver-free driving (i.e., straight travel path).

Table 1:

Definitions for inappropriate driving behaviour

The eDOS was initially developed with a paper-based evaluation form. Vlahodimitrakou et al. (Reference Vlahodimitrakou, Charlton, Langford, Koppel, Di Stefano and Macdonald2013) evaluated the inter-rater reliability, feasibility, and acceptability of the eDOS driving task on a sub-sample of 33 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 (r [18] = .83, p < 0.05), was practical in terms of duration, and was acceptable to participants. Koppel et al. (Reference Koppel, Charlton, Langford, Di Stefano, Macdonald and Mazer2012) revised the eDOS driving task, including (a) an electronic score sheet to record and score driving behaviour, and (b) installation of video recording equipment in participants’ vehicles to capture images of the driver and the forward driving environment throughout the drive. Based on a sub-sample of 96 Ozcandrive participants, the authors reported that it was possible to observe and score detailed driving behaviour during intersection negotiation, lane-changing, merging, and maneuver-free driving, and that the revised (eDOS) driving task demonstrated practicality and high user acceptance. Koppel et al. (Reference Koppel, Charlton, Langford, Vlahodimitrakou, Di Stefano and Macdonald2013) then investigated the relationship between participants’ driving performance during the eDOS driving task and their cognitive performance for a subset of 144 Ozcandrive participants (104 male [72%], 40 female [28%], mean age = 81.49 years, SD = 3.58 years, range: 76–96 years).

Preliminary analyses of the eDOS driving task revealed a high level of appropriate driving behaviour among Ozcandrive older drivers. The authors reported that there was no significant relationship observed between participants’ overall eDOS driving task scores and age, and participants’ performance on various cognitive assessments. However, the authors suggested that it would be important to explore the potential relationship between performance on the eDOS driving task and cognitive performance with the full sample (n = 227), as well as to explore the potential relationship between participants’ performance on the eDOS driving task and other functional performance measures, as well as participants’ perceptions of driving comfort and abilities.

Aims

The aim of this study was to examine a cohort of older drivers using the eDOS driving task and investigate the relationship between performance on the task and (1) driver characteristics (e.g., age, gender, frequency of driving, etc.); (2) functional abilities; (3) perceptions of driving comfort and abilities; and (4) self-reported driving restrictions using a number of measures from the Candrive/Ozcandrive assessment protocol (Marshall et al., Reference Marshall, Man-Son-Hing, Bédard, Charlton, Gagnon and Gélinas2013).