Predicting On-Road Driving Performance and Safety in Cognitively Impaired Older Adults

Older adult driving performance assessed under simulated and on-road conditions

Simulated driving offers a convenient test of driving ability for older drivers, although the viability of using simulated driving with this population is mixed. The relative weighting of the relevant perceptual, cognitive, and physical factors may vary between simulated and on-road driving. The current study was designed to assess this possibility. We conducted simulated and on-road driving tests of 61 older adults aged 66-92 years. To ensure that the driving performance was measured similarly between the two driving modalities, we employed the Record of Driving Errors (RODE) driving assessment system during both driving tests. Correlation and random weights analysis (RWA) results indicated only modest evidence of correspondence between the simulated and on-road driving performances. The primary factors operative in both simulated and on-road driving was Useful Field of View and a measure of basic cognition. Unique factors for simulated driving included a measure of physical mobility (Time-Up-and-Go) and spatial reasoning (Line), and for on-road driving included chronological age and sensorimotor processing (Trail-Making Task A). Chronological age was correlated primarily the on-road rather than simulated test, was greatly reduced with the inclusion of additional explanatory factors, and likely reflects driving efficiency rather than driving safety. We conclude that simulated driving in healthy older drivers can be beneficial for research purposes to assess cognitive and perceptual factors that underly driving effectiveness, although it cannot serve as a clear proxy for on-road driving.

Neuropsychological domains and fitness to drive in mild cognitive impairment or Alzheimer's disease

Cognitive deficits associated with mild cognitive impairment (MCI) or Alzheimer's disease (AD) can impact driving. This integrative review investigated which cognitive domains were associated with poor driving performance or unfitness to drive in studies with outcomes measured in simulator or on-road driving in patients with MCI or AD. The review was conducted by searching for articles published between 2001 and 2020 in the MEDLINE (via PubMed), EMBASE, and SCOPUS databases. Studies addressing patients with other dementias (e.g., vascular or mixed dementia, Lewy body dementia, Parkinson's disease) were excluded. Of 404 articles initially selected, 17 met the eligibility criteria for this review. Based on the findings of this integrative review, attentional capacity, processing speed, executive functions and visuospatial skills were the functions whose declines were most frequently reported in a context of unsafe driving by older adults with MCI or AD. Reports were remarkably heterogeneous in methodological aspects whereas quite limited in cross-cultural coverage and in sample recruited, what prompts for further trials in the field.

Inability of the Mini-Mental State Exam (MMSE) and high-contrast visual acuity to identify unsafe drivers

BACKGROUND/OBJECTIVES

To examine the validity of high-contrast visual acuity and the Mini-Mental State Exam (MMSE) as tools for identifying at-risk older drivers.

DESIGN

Prospective multi-site observational cohort study.

SETTING

Community sample drawn from cities of Brisbane and Canberra, Australia.

PARTICIPANTS

560 licensed drivers aged 65-96 years recruited between 2013 and 2016, from the community, an optometry clinic and driver referral service.

MEASUREMENTS

50-minute standardized on-road driving test conducted on a standard urban route in a dual-brake vehicle with a driver trained Occupational Therapist assessor masked to participants' cognitive, visual and medical status.

RESULTS

Of 560 participants who completed the on-road test, 68 (12%) were classified as unsafe. Binary logistic regression models adjusted for age, gender, site, comorbidity and driving exposure indicated that a 1-point decrease in MMSE score was associated with a 1.35 (95%CI: 1.12-1.63) increase in odds of unsafe driving, and for each line reduction in binocular visual acuity (increase of 0.1 logMAR) was associated with 1.39 (95%CI: 1.07-1.81) increased odds of unsafe driving. However, Receiver Operating Characteristic (ROC) analysis showed low discriminative power for both measures (MMSE: AUC = 0.65 (95%CI: 0.58-0.73), visual acuity: AUC = 0.65 (95%CI: 0.59-0.72)) and typical cut-offs were associated with very low sensitivity for identifying unsafe drivers (MMSE <24/30: 2%; visual acuity worse than 6/12 Snellen (logMAR >0.30): 3%).

CONCLUSION

The MMSE and high-contrast visual acuity tests do not reliably identify at-risk older drivers. They have extremely low sensitivity for detecting unsafe drivers, even when used together, and poor prognostic properties relative to validated screening instruments that measure cognitive, vision and sensorimotor functions relevant to driving. Clinicians should select alternate validated driver screening tools where possible.

The SIMARD-MD is not an Effective Driver Screening Tool for Determining Fitness-To-Drive

Background

Studies have reported poor sensitivity and specificity of the Screen for the Identification of Cognitively Impaired Medically At-Risk Drivers, a modification of the DemTech (SIMARD-MD) to screen for drivers with cognitive impairment. The purpose of this study was to determine whether the SIMARD-MD can accurately predict pass/fail on a road test in drivers with cognitive impairment (CI) and healthy drivers.

Methods

Data from drivers with CI were collected from two comprehensive driving assessment centres (n=86) and compared with healthy drivers (n=30). All participants completed demographic measures, clinical measures, and a road rest (pass/fail). Analyses consisted of correlations between the SIMARD-MD and the other clinical measures, and a receiver-operating-characteristic (ROC) curve to determine the predictive ability of the SIMARD-MD.

Results

All healthy drivers passed the road test compared with 44.2% of the CI sample. On the SIMARD-MD, the CI sample scored significantly worse than healthy drivers (p < .001). The ROC curve showed the SIMARD-MD, regardless of any cut-point, misclassified a large number of CI individuals (AUC=.692; 95% CI = 0.578, 0.806).

Conclusions

Given the high level of misclassification, the SIMARD-MD should not be used with either healthy drivers or those with cognitive impairment for making decisions about driving.

Medical referral and license disposition for drivers in Iowa

INTRODUCTION

Driver retirement and determination of fitness-to-drive are important aspects of reducing the risk of motor-vehicle collision for an older driver. A lack of information about the review process may lead to poor evaluation of drivers or an increased testing burden to referred drivers.

METHODS

This paper evaluates the license review process for the state of Iowa. We evaluated data from January 2014 to January 2018 and described the source of referral, testing process, and ultimate license disposition. Cox proportional hazards for competing risk were used to determine the risk of having a change in restrictions on the license and the risk of license denial.

RESULTS

20,742 individuals were followed through the medical referral process. The most common source of referrals was licensing officials (39.7%). Drivers referred by licensing officials were less likely to be denied their license when compared to drivers from other sources (HR = 0.92 95%CI: 0.87-0.98); however, licensing official referrals were more likely to result in license restrictions compared to other sources (HR = 1.91, 95%CI: 1.82-2.00). Drivers referred by either law enforcement or a physician were more likely to ultimately have their license denied.

CONCLUSIONS

Physician and law enforcement referred the drivers most likely to have their license denied. A smaller proportion of drivers were referred by physicians and law enforcement compared to licensing officials. Practical Applications: Licensing agencies should work with physicians and law enforcement to identify drivers who may need a review of their license. Comprehensive tracking of all medical referrals for a driver's license review is important for individual states to understand the burden of their driver referral process and for identifying referral sources with a high proportion of referrals with no licensing change for targeted outreach and education.

The Medical Referral Process and Motor-Vehicle Crash Risk for Drivers with Dementia

Cognitive and physical impairment can occur with dementia and reduce driving ability. In the United States, individual states have procedures to refer and evaluate drivers who may no longer be fit to drive. The license review process is not well understood for drivers with dementia. This study uses comprehensive data from the Iowa Department of Transportation to compare the referral process for drivers with and without dementia from January 2014 through November 2019. The likelihood of failing an evaluation test was compared between drivers with and without dementia using logistic regression. The risk of motor-vehicle crash after referral for review of driving ability was compared using a Cox proportional hazard model. Analysis controlled for the age and sex of the referred driver. Drivers with dementia performed worse on all tests evaluated except the visual screening test. After the referral process, the risk of crash was similar between those with and without dementia. Drivers with dementia were denied their license more frequently than referred drivers without dementia. However, drivers with dementia who successfully kept their license as a result of the license review process were not at an increased risk of crash compared to other referred drivers.

Diagnosed dementia and the risk of motor vehicle crash among older drivers

Older adults are an active and growing segment of drivers in the United States. We compared the risk of motor vehicle crash among older licensed drivers diagnosed with dementia to crash risk among older licensed drivers without diagnosis of dementia. This retrospective cohort study used data from Group Health (GH), a Washington State health maintenance organization. Research participants were members of GH, aged 65-79 during the study who lived in Washington State from 1999-2009. Participant health records were linked with police-reported crash and licensure records. We estimated the risk of crash for older drivers diagnosed with dementia compared to older drivers without diagnosis of dementia using a Cox proportional hazards model with robust standard errors, accounting for recurrent events (crashes). Multivariable models were adjusted for age, sex, history of alcohol abuse or depression, comorbidities, and medications. There were 29,730 eligible individuals with an active driving license. Approximately 6% were diagnosed with dementia before or during the study. The police-reported crash rate was 14.7 per 1000 driver-years. The adjusted hazard ratio of crash among older drivers with diagnosed dementia was 0.56 (95% CI 0.33, 0.95) compared to those without diagnosed dementia. On-road and simulator-based research showed older adults with dementia demonstrated impaired driving skill and capabilities. The observed lower crash risk in our study may result from protective steps to limit driving among older adults diagnosed with dementia. Future research should examine driving risk reduction strategies at the time of dementia diagnosis and their impact on reducing crash risk.

A Systematic Review and Meta-Analysis of On-Road Simulator and Cognitive Driving Assessment in Alzheimer's Disease and Mild Cognitive Impairment

BACKGROUND

Many individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) are at an increased risk of driving impairment. There is a need for tools with sufficient validity to help clinicians assess driving ability.

OBJECTIVE

Provide a systematic review and meta-analysis of the primary driving assessment methods (on-road, cognitive, driving simulation assessments) in patients with MCI and AD.

METHODS

We investigated (1) the predictive utility of cognitive tests and domains, and (2) the areas and degree of driving impairment in patients with MCI and AD. Effect sizes were derived and analyzed in a random effects model.

RESULTS

Thirty-two articles (including 1,293 AD patients, 92 MCI patients, 2,040 healthy older controls) met inclusion criteria. Driving outcomes included: On-road test scores, pass/fail classifications, errors; caregiver reports; real world crash involvement; and driving simulator collisions/risky behavior. Executive function (ES [95% CI]; 0.61 [0.41, 0.81]), attention (0.55 [0.33, 0.77]), visuospatial function (0.50 [0.34, 0.65]), and global cognition (0.61 [0.39, 0.83]) emerged as significant predictors of driving performance. Trail Making Test Part B (TMT-B, 0.61 [0.28, 0.94]), TMT-A (0.65 [0.08, 1.21]), and Maze test (0.88 [0.60, 1.15]) emerged as the best single predictors of driving performance. Patients with very mild AD (CDR = 0.5) mild AD (CDR = 1) were more likely to fail an on-road test than healthy control drivers (CDR = 0), with failure rates of 13.6%, 33.3% and 1.6%, respectively.

CONCLUSION

The driving ability of patients with MCI and AD appears to be related to degree of cognitive impairment. Across studies, there are inconsistent cognitive predictors and reported driving outcomes in MCI and AD patients. Future large-scale studies should investigate the driving performance and associated neural networks of subgroups of AD (very mild, mild, moderate) and MCI (amnestic, non-amnestic, single-domain, multiple-domain).

Hazard Perception in Driving

Hazard perception in driving refers to a driver’s ability to anticipate potentially dangerous situations on the road ahead and has been the subject of research for over 50 years. It is typically measured using computer-based hazard-perception tests and has been associated with both retrospective and prospective crash risk, as well as key crash-risk factors such as distraction, fatigue, alcohol consumption, speed choice, and age-related declines. It can also differentiate high- and lower-risk driver groups. The problem is that it is also a skill that appears to take decades of driving experience to acquire. This raises the question of whether it is possible and practical to accelerate this learning process via assessment and training in order to improve traffic safety. We have evidence that, in contrast to most driver education and assessment interventions, hazard-perception testing and training appear to have the capability to reduce crash risk. For example, the inclusion of a hazard-perception test in the UK driver licensing process has been estimated to reduce drivers’ non-low-speed public-road crash rates by 11.3% in the year following their test.