Abstract
The areas of driving impairment characteristic of mild cognitive impairment (MCI) remain unclear. This study compared the simulated driving performance of 24 individuals with MCI, including amnestic single-domain (sd-MCI, n = 11) and amnestic multiple-domain MCI (md-MCI, n = 13), and 20 age-matched controls. Individuals with MCI committed over twice as many driving errors (20.0 versus 9.9), demonstrated difficulty with lane maintenance, and committed more errors during left turns with traffic compared to healthy controls. Specifically, individuals with md-MCI demonstrated greater driving difficulty compared to healthy controls, relative to those with sd-MCI. Differentiating between different subtypes of MCI may be important when evaluating driving safety.
Keywords
INTRODUCTION
Driving is a complex task that requires the coordination of multiple cognitive functions, including memory, executive function, attention, and visuospatial ability. All of these cognitive domains can be affected by mild cognitive impairment (MCI). Although most individuals with MCI are safe to drive, some do not maintain the ability to drive safely. Despite this, there are no guidelines or valid tools to help physicians assess the driving safety of their patients. One factor contributing to this issue is that the characterization of driving impairment among patients with MCI remains unclear [1–4].
MCI is a highly heterogeneous condition that can be classified into two broad categories: amnestic MCI (a-MCI), when memory is impaired, and non-amnestic MCI (na-MCI), when memory function is preserved. Individuals within these categories can be further classified as having multiple domain MCI (md-MCI), which manifests as impairment in multiple cognitive domains, or single domain MCI (sd-MCI), which is characterized by impairment in a single cognitive domain [5]. Given the heterogeneous nature of MCI, coupled with the fact that various subtypes have been shown to be at a differential risk for functional decline [6–8], it is critical to investigate the driving performance of different subtypes of MCI. The current study used driving simulator technology to investigate the driving performance of patients with MCI, including patients with amnestic single-domain (sd-MCI) and amnestic multiple-domain (md-MCI) impairment.
MATERIALS AND METHODS
Participants
Twenty-four (24) individuals with amnestic MCI (sd-MCI, n = 11; md-MCI, n = 13) were recruited from the Memory Disorders Clinic at St. Michael’s Hospital. All patients with MCI were formally diagnosed by a geriatric psychiatrist based on a comprehensive patient history as well as clinical neuroimaging and objective cognitive testing, including the Behavioural Neurological Assessment (BNA) [9], the Montreal Cognitive Assessment (MoCA) [10], and the Mini-Mental Status Examination (MMSE) [11]. All patients met the National Institute on Aging-Alzheimer’s Association criteria for MCI [12]. All patient participants classified with sd-MCI demonstrated subjective complaints and impairment in memory only. Patients classified with md-MCI demonstrated subjective complaints and objective impairment in one or more cognitive domains in addition to memory. Twenty (20) age-matched cognitively healthy controls were recruited from the community (e.g., St. Michael’s Hospital, Baycrest Geriatric Hospital, and the University of Toronto Senior Alumni Association). All cognitively healthy controls reported no concerns with changes in memory or cognition and scored ≥26 [10] on the MoCA. All participants provided written informed consent prior to participating. Ethical approval of the study was obtained by the Research Ethics Board at St. Michael’s Hospital.
Driving simulation
Driving performance (STISIM Drive®) was assessed using a portable driving simulator (Logitech G25 model), equipped with a steering wheel, accelerator pedal, brake pedal, and signaling system. The driving conditions ranged in complexity (i.e., straight driving, right turns and left turns, left turns with oncoming traffic). Turning left at intersections with oncoming traffic presented greater cognitive demands [13], as participants were required to accurately judge when to turn safely. Although some studies have suggested that simulators may be less realistic than real-world driving [14], others have reported that simulated driving is reliable and a valid representation of on-road driving performance [15–19].
Cognitive tests
Cognitive tests included: the MoCA [10], the Trail Making Test Part A (TMT-A) and Part B (TMT-B) [20], and the Useful Field of View test (UFOV) [21]. Demographic and cognitive information is reported in the Supplementary Table 1.
Statistical analysis
Analyses comparing patients with MCI and healthy controls were run using an independent samples t-test or the Mann-Whitney U test, depending on whether data conformed to or violated statistical assumptions (e.g., normality). Analyses comparing sd-MCI patients and md-MCI patients with healthy controls were run using a one-way ANOVA or the Kruskal–Wallis H test, followed by post-hoc testing, with Bonferroni corrections for two comparisons (i.e., sd-MCI versus healthy controls, md-MCI versus healthy controls). A secondary correlation analysis was run to determine whether cognitive scores were associated with driving errors.
RESULTS
Driving performance of persons with MCI
Overall, individuals with MCI (sd-MCI + md-MCI) committed significantly more errors overall (i.e., the sum of collisions, center line crossings, road edge excursions, stop signs missed, speed limit exceedances) compared to healthy control drivers (20.0 versus 9.9, U = 137.5, p = 0.016) (Table 1). Persons with MCI committed more center line crossings (5.2 versus 1.9, U = 146.5, p = 0.025) and spent a significantly greater percentage of time out of the legal driving lane (2.1 versus 0.3, U = 132.0, p = 0.011) compared to healthy control drivers. Individuals with MCI committed significantly more errors compared to controls during left turns with oncoming traffic (0.16 versus 0.05 errors per turn; U = 154.0, p = 0.032), but not right or left turns without traffic.
Driving performance of persons with sd-MCI and md-MCI
Results revealed a significant difference between MCI subtypes and healthy controls in the number of total driving errors (Fig. 1), stop signs missed, center line crossings, percentage of time out of the legal driving lane, and errors during left turns with traffic. Post-hoc testing revealed that individuals with sd-MCI did not perform significantly worse than healthy control drivers on any driving variable of interest. In contrast, persons with md-MCI committed significantly more errors overall (24.5 versus 9.9, p = 0.032), had more stop signs missed (2.6 versus 1.0, p = 0.028), more center line crossings (7.4 versus 1.9, p = 0.014), and spent a greater amount of time out of the legal driving lane (3.4 versus 0.3, p = 0.018) compared to controls. Individuals with md-MCI committed significantly more errors than controls during left turns with traffic (0.21 versus 0.05 errors per turn, p = 0.026).
Associations between driving errors and cognitive scores
TMT-A time (rs = 0.453, p = 0.034), TMT-B time (rs = 0.442, p = 0.05), and UFOV Processing Speed (rs = 0.460, p = 0.027) were significantly associated with total driving errors in individuals with MCI. Among persons with sd-MCI, UFOV Processing Speed was significantly associated with total driving errors (rs = 0.773, p = 0.009). In individuals with md-MCI, TMT-A (rs = 0.636, p = 0.019) and TMT-B (rs = 0.559, p = 0.047) were significantly associated with total driving errors (remaining data are reported in the Supplementary Material).
DISCUSSION
Individuals with MCI committed over twice as many driving errors compared to healthy controls. Persons with MCI committed significantly more errors compared to controls during left turns with oncoming traffic, which require greater cognitive demand [13], but not right and left turns without traffic. Furthermore, individuals with MCI demonstrated difficulty with lane control (i.e., centerline crossings, time out of the lane). These findings are consistent with previous research, which found that persons with MCI had a significantly lower global rating of driving performance and lower rating on lane control compared to healthy controls on an on-road assessment [4].
Importantly, the current results revealed that different patterns of driving behavior can emerge between subtypes of MCI. Results revealed that individuals with md-MCI committed 2.46 times the number of overall errors relative to cognitively healthy drivers. Specifically, persons with md-MCI may be at risk of difficulty with lane control. This is supported by the current results, showing that individuals with md-MCI committed over four times as many center line crossings and spent a greater percentage of time out of the legal driving lane compared to controls. The finding of increased difficulty with lane control is particularly important, as Ott and colleagues [22] identified lane maintenance as a factor critical to safe driving during naturalistic driving in older drivers with and without cognitive impairment. Furthermore, persons with md-MCI committed significantly more errors during left turns with traffic compared to controls. Given that the md-MCI group characteristically exhibit widespread cognitive deficits (e.g., attention, executive function, elements that are important for safe driving), it follows that this group may be at particularly high risk of driving difficulty. Furthermore, previous research has suggested that individuals with md-MCI, especially amnestic md-MCI, may be at the greatest risk of functional decline of all subtypes [23].
In the current study, associations between driving and cognitive performances were not consistent across the different subtypes of MCI. This is congruent with the literature, which has identified a great deal of variation across studies. Specifically, some research has supported the predictive utility of TMT-A [3, 25], TMT-B [3, 26–29], and the UFOV[26, 27] in predicting driving performance. Despite this, other studies have reported small or non-significant correlations between driving performance and the TMT-A [26], TMT-B [24, 30], and UFOV [28, 30]. Due to variability in the results of cognitive predictors, there remain no tools [31] with sufficient sensitivity or specificity available to assist healthcare professionals in assessing the driving safety of individuals with AD or MCI.
Although the current study offers important insight into the driving performance of persons with MCI, it has some limitations. Despite separating individuals with sd-MCI and md-MCI, a high degree of within-group variability remained present for both MCI subtypes, particularly the md-MCI group (e.g., the number, areas, and degree of cognitive impairments). Furthermore, the current study had a small sample size and did not include persons with non-amnestic sd-MCI (e.g., executive sd-MCI).
The current results suggest that various subtypes of MCI may have different profiles of driving difficulty. When looking at all MCI patients together, results suggested that patients as a whole may experience driving difficulty. However, the results of the subtype analysis revealed that patients with amnestic md-MCI may be at a greater risk of driving difficulty, particularly during lane maintenance and left turns with traffic, relative to those with amnestic sd-MCI. Discriminating between subtypes of MCI to reduce the inherent variability in the MCI population may serve as an important advancement in the current literature. Future research should expand on the current results by identifying the specific areas and degree of driving impairment that are characteristic of different subtypes of MCI as well as their cognitive correlates. A large-scale longitudinal study would be important to determine the extent to which driving performance may deteriorate over time in patients with MCI, including various subtypes of MCI. This may serve as an important step towards the development of valid tools for driving risk assessment that can be implemented in the clinical setting.
Footnotes
ACKNOWLEDGMENTS
This work was funded by an Alzheimer’s Society Research Program Research Grant from the Alzheimer’s Society of Canada and an Early Researcher Award from the Ontario Ministry of Research and Innovation awarded to Dr. Tom Schweizer; a CIHR Frederick Banting and Charles Best Canada Graduate Scholarship— Master’s awarded to Megan Hird; and the University of Toronto, George, Margaret and Gary Hunt Family Chair in Geriatric Medicine awarded to Dr. Gary Naglie.
