Automated vehicles for older adults with cognitive impairment: a survey study

As the population is ageing, the number of older adults with cognitive impairment (CI) is increasing. Automated vehicles (AVs) can improve independence and enhance the mobility of these individuals. This study aimed to: (1) understand the perception of older adults (with and without CI) and stakeholders providing services and supports regarding care and transportation about AVs, and (2) suggest potential solutions to improve the perception of AVs for older adults with mild or moderate CI. A survey was conducted with 435 older adults with and without CI and 188 stakeholders (e.g. caregivers). The results were analysed using partial least square - structural equation modelling and multiple correspondence analysis. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided recommendations to improve older adults' perception of AVs including education and adaptive driving simulation-based training.Practitioner summary: This study investigated the perception of older adults and other stakeholders regarding AVs. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided guidelines to improve older adults' perception of AVs.

Driving Automation for Older Adults with Preclinical Alzheimer's Disease

INTRODUCTION

Older adults with preclinical Alzheimer's disease (AD) show changes in on-road driving performance. The impact of preclinical AD on using automated vehicle (AV) technology is unknown. The aim was to evaluate safety and cognitive workload while operating AV technology in drivers with preclinical AD.

INTRODUCTION

This cross-sectional study included 40 participants: 19 older adults (age 74.16 ± 4.78; MOCA scores 26.42 ± 2.52) with preclinical AD, evidenced by elevated cortical beta-amyloid; and 21 controls (age 73.81 ± 5.62; MOCA scores 28.24 ± 1.67). All participants completed two scenarios in a driving simulator. Scenario 1 included conditional automation with an emergency event that required a manual take-over maneuver. Scenario 2 was identical but with a cognitive distractor task. Emergency response time was the main safety outcome measure. Cognitive workload was calculated using moment-to-moment changes in pupillary size and converted into an Index of Cognitive Activity (ICA). Mann-Whitney U and independent t tests were used to compare group differences.

RESULTS

Emergency response times were similar between drivers with preclinical AD and controls in scenario 1 (20.85 s ± 1.08 vs. 20.52 s ± 3.18; p = 0.83) and scenario 2 (14.83 s ± 7.37 vs. 13.45 s ± 10.43; p = 0.92). Likewise, no differences were found in ICA between drivers with preclinical AD and controls in scenario 1 (0.34 ± 0.08 vs. 0.33 ± 0.17; p = 0.74) or scenario 2 (0.30 ± 0.07 vs. 0.29 ± 0.17; p = 0.93).

CONCLUSIONS

Older drivers with preclinical AD may safely operate AV technology, without increased response times or cognitive workload. Future on-road studies with AV technology should confirm these preliminary results in drivers with preclinical AD.

Age-Related Diseases and Driving Safety

Due to demographic changes, the number of older drivers is steadily increasing. Mobility is highly relevant for leading an independent life in the elderly. It largely depends on car driving, which is a complex task requiring a multitude of cognitive and motor skills vulnerable to age- related functional deterioration. The almost inevitable effects of senescence may be potentiated by age-related diseases, such as stroke or diabetes mellitus. Respective pharmacological treatment may cause side effects, additionally affecting driving safety. The present article reviews the impact of age-related diseases and drug treatment of these conditions on driving fitness in elderly drivers. In essence, we focus on diseases of the visual and auditory systems, diseases of the central nervous system (i.e., stroke, depression, dementia and mild cognitive disorder, and Parkinson's disease), sleep disorders, as well as cardiovascular diseases, diabetes mellitus, musculoskeletal disorders, and frailty. We will outline the role of functional tests and the assessment of driving behavior (by a driving simulator or in real traffic), as well as the clinical interview including questions about frequency of (near) accidents, etc. in the evaluation of driving fitness of the elderly. We also address the impact of polypharmacy on driving fitness and end up with recommendations for physicians caring for older patients.

Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial

Background

Physicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports.

Objective

The aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators.

Methods

The study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm.

Results

A total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ between the intervention and the control groups (50% vs 49%; Z=−0.19, P=.85). Two variables predicted algorithm-based reporting—caregiver concern (odds ratio [OR]=5.8, 95% CI 2.5-13.6, P<.001) and abnormal clock drawing (OR 6.1, 95% CI 3.1-11.8, P<.001).

Conclusions

On the basis of this quantitative analysis, in-office abnormal clock drawing and expressions of concern about driving from caregivers substantially influenced physicians to report patients with mild dementia or mild cognitive impairment to transportation administrators, but the DD-DT tool itself did not increase such reports among these expert physicians.

Trial Registration

ClinicalTrials.gov NCT02036099; https://clinicaltrials.gov/ct2/show/NCT02036099 (Archived by WebCite at http://www.webcitation.org/6zGMF1ky8)

Mandatory Physician Reporting of At-Risk Drivers: The Older Driver Example

Purpose of the Study

In a number of states, physicians are mandated by state law to report at-risk drivers to licensing authorities. Often these patients are older adult drivers who may exhibit unsafe driving behaviors, have functional/cognitive impairments, or are diagnosed with conditions such as Alzheimer's disease and/or seizure disorders. The hypothesis that mandatory physician reporting laws reduce the rate of crash-related hospitalizations among older adult drivers was tested.

Design and Methods

Using retrospective data (2004-2009), this study identified 176,066 older driver crash-related hospitalizations, from the State Inpatient Databases. Three age-specific negative binomial generalized estimating equation models were used to estimate the effect of physician reporting laws on state's incidence rate of crash-related hospitalizations among older drivers.

Results

No evidence was found for an independent association between mandatory physician reporting laws and a lower crash hospitalization rate among any of the age groups examined. The main predictor of interest, mandatory physician reporting, failed to explain any significant variation in crash hospitalization rates, when adjusting for other state-specific laws and characteristics. Vision testing at in-person license renewal was a significant predictor of lower crash hospitalization rate, ranging from incidence rate ratio of 0.77 (95% confidence interval 0.62-0.94) among 60- to 64-year olds to 0.83 (95% confidence interval 0.67-0.97) among 80- to 84-year olds.

Implications

Physician reporting laws and age-based licensing requirements are often at odds with older driver's need to maintain independence. This study examines this balance and finds no evidence of the benefits of mandatory physician reporting requirements on driver crash hospitalizations, suggesting that physician mandates do not yet yield significant older driver safety benefits, possibly to the detriment of older driver's well-being and independence.

The Impact of Advanced Age on Driving Safety in Adults with Medical Conditions

BACKGROUND

Adults aged 85 and older, often referred to as the oldest-old, are the fastest-growing segment of the population. The rapidly increasing number of older adults with chronic and multiple medical conditions poses challenges regarding their driving safety.

OBJECTIVE

To investigate the effect of advanced age on driving safety in drivers with medical conditions.

METHODS

We categorized 3,425 drivers with preexisting medical conditions into four age groups: middle-aged (55-64 years, n = 1,386), young-old (65-74 years, n = 1,013), old-old (75-84 years, n = 803), or oldest-old (85 years and older, n = 223). All underwent a formal driving evaluation. The outcome measures included fitness to drive recommendation by the referring physician, comprehensive fitness to drive decision from an official driving evaluation center, history of motor vehicle crashes (MVCs), and history of traffic violations.

RESULTS

The oldest-old reported more cardiopulmonary and visual conditions, but less neurological conditions than the old-old. Compared to the middle-aged, the oldest-old were more likely to be considered unfit to drive by the referring physicians (odds ratio [OR] = 4.47, 95% confidence interval [CI] 2.20-9.10) and by the official driving evaluation center (OR = 2.74, 95% CI 1.87-4.03). The oldest-old reported more MVCs (OR = 2.79, 95% CI 1.88-4.12) compared to the middle-aged.

CONCLUSION

Advanced age adversely affected driving safety outcomes. The oldest-old are a unique age group with medical conditions known to interfere with safe driving. Driving safety strategies should particularly target the oldest-old since they are the fastest-growing group and their increased frailty is associated with severe or fatal injuries due to MVCs.

Comparison of Unsafe Driving Across Medical Conditions

OBJECTIVE

To compare risks of unsafe driving in patients with medical conditions.

METHODS

This large population-based study included all patients who were referred for a fitness-to-drive evaluation at an official driving evaluation center in 2013 and 2014. Risks of unsafe driving included physician's fitness-to-drive recommendation, comprehensive fitness-to-drive decision, motor vehicle crash history, and traffic violation history.

RESULTS

A total of 6584 patients were included in the study. Risks of unsafe driving were significantly different across medical conditions (P<.001 for all outcome measures). Patients with neurological conditions comprised the majority of the database (4837; 74%), but were not at the highest risk for unsafe driving. Patients with psychiatric conditions or substance abuse did worse on most driving safety outcomes, despite their low representation in the total sample (359 [6%] and 46 [1%], respectively).

CONCLUSION

The risk of unsafe driving varied greatly across medical conditions. Sensitization campaigns, education, and medical guidelines for physicians and driver licensing authorities are warranted to identify patients at risk, especially for those with psychiatric conditions and substance abuse problems.

Driving and dementia: a clinical update for mental health professionals

Most people with mild dementia can continue to drive, but dementia is progressive and many patients and clinicians will be faced with questions about driving safety in the course of their illness. Determining when this happens is a complex decision, with risks of personal and public safety needing to be weighed against individual patient benefits of driving in terms of autonomy, independence and well-being. Decisions need to make reference to cognitive abilities, as well as other factors including physical comorbidity, vision, mobility, insight and history of driving errors and accidents. Deciding to stop driving, or being required to stop driving is often difficult for patients to accept and can be a particularly problematic consequence of a dementia diagnosis. Legal frameworks help in decision-making but may not provide sufficient detail to advise individual patients. We review the current guidelines and evidence relating to driving and dementia to help clinicians answer questions about driving safety and to consider the full range of assessment tools available.