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

Somatic Factors Predict On-Road Driving Skills in Older Drivers and Drivers with Mild Cognitive Impairment

BACKGROUND

On-road driving skills can be impaired in older drivers and drivers with mild cognitive impairment (MCI) due to different driving-relevant deficits. Among these deficits, somatic factors have received little attention so far.

METHODS

In a prospective observational on-road driving study, we examined whether somatic factors can predict on-road driving skills in a mixed sample of healthy older drivers and drivers with MCI (n = 99) and whether the inclusion of age explains additional variance. Somatic factors included the number of prescribed drugs, visual acuity, peripheral visual field integrity, mobility of the cervical spine, and hearing impairment. A hierarchical regression analysis was used to predict on-road driving skills by adding the somatic factors in the first step and age in the second step.

RESULTS

Results revealed that the combination of somatic factors significantly predicted on-road driving skills (R2adjusted = 0.439). The inclusion of age led to a significant increase of explained variance (R2adjusted = 0.466).

CONCLUSIONS

Our results suggest that somatic factors can accurately predict on-road driving skills in healthy older drivers and drivers with MCI. In addition, our results suggest that there is a significant but rather small effect of age beyond somatic changes.

Alterations in driving ability and their relationship with morphometric magnetic resonance imaging indicators in patients with amnestic mild cognitive impairment and Alzheimer's disease

BACKGROUND

Drivers with dementia are at a higher risk of motor vehicle accidents. The characteristics of driving behaviour of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have not been fully elucidated. We investigated driving ability and its relationship with cognitive function and magnetic resonance imaging (MRI) morphometry indicators.

METHODS

The driving abilities of 19 patients with AD and 11 with amnestic MCI (aMCI) were evaluated using a driving simulator. The association between each driving ability parameter and the Mini-Mental State Examination (MMSE) score or voxel-based specific regional analysis system for AD (VSRAD) was assessed.

RESULTS

Patients with AD made a significantly higher number of operational errors than those with aMCI in attention allocation in the complex task test (P = 0.0008). The number of operational errors in attention allocation in the complex task test significantly and negatively correlated with MMSE scores in all participants (r = -0.4354, P = 0.0162). The decision time in the selective reaction test significantly and positively correlated with the severity and extent of medial temporal structural atrophy (r = 0.4807, P = 0.0372; r = 0.4862, P = 0.0348; respectively).

CONCLUSION

An increase in the operational errors for attention allocation in the complex task test could be a potential indicator of progression from aMCI to AD. Atrophy of the medial temporal structures could be a potential predictor of impaired judgement in driving performance in aMCI and AD. A driving simulator could be useful for evaluating the driving abilities of individuals with aMCI and AD.

Metacognitive Awareness of Older Adult Drivers with Mild Cognitive Impairment: Relationships with Demographics, Subjective Evaluation of Cognition, and Driving Self-Efficacy

(1) Self-regulation of driving is a means of maintaining one's driving identity. The purpose of this study was to investigate the extent to which older drivers with Mild Cognitive Impairment (MCI) are metacognitively aware of the requirements of specific demanding driving conditions and whether this awareness is linked to subjective assessments of cognition. (2) One hundred seventeen (117) older MCI drivers participated in a telephone survey in which they reported their metacognitive experiences in nine driving conditions, listed as an aim of self-regulation. The analyses included the participants' subjective cognitive assessments, both in terms of their cognitive state and their perceived driving self-efficacy. (3) The analyses pointed out a direct and negative effect of age on the formation of the metacognitive feeling of certainty. Furthermore, an indirect effect of sex through driving self-efficacy was established. This effect was negative in the case of the metacognitive feeling of difficulty and the estimation of effort and positive in the case of the metacognitive feeling of certainty. (4) This position points out the need to establish appropriate levels of the perceived self-efficacy of older drivers with MCI, and it raises issues when it moves to fictitious levels.

Australian medical practitioners' perspectives about current practice relating to fitness to drive assessment for older people with dementia and mild cognitive impairment: A qualitative study

OBJECTIVES

To describe the perspectives of Australian medical practitioners about current practice, and the potential benefit of tools and resources to support fitness to drive assessment for older people with dementia and mild cognitive impairment (MCI).

METHODS

Semi-structured interviews with 22 medical practitioners from cognitive/memory clinics, hospitals, general practice and driving fitness assessment services in Australia. Reflexive thematic analysis was conducted.

RESULTS

Two overarching themes were generated: (1) Uncomfortable decisions, describing feelings of discomfort expressed by practitioners about making fitness to drive recommendations, with two subthemes: (a) 'Feeling uncertain' and (b) 'Sticking your neck on the line'; and (2) Easing the discomfort, describing participants' desire for tools/resources to support practitioners to increase comfort with fitness to drive recommendations, with two subthemes: (a) 'Seeking certainty' and (b) 'Focusing on the process' conveying two different perspectives about how this may be achieved. There was a desire for a new in-office assessment tool capable of accurately predicting fitness to drive outcomes and views that an evidence-based clinical pathway could improve practitioners' confidence in decision-making.

CONCLUSIONS

Perceptions of discomfort relating to fitness to drive assessment of older people with dementia and MCI exist amongst medical practitioners from health-care settings across Australia. In the absence of a well-validated in-office assessment tool, practitioners may benefit from an evidence-based clinical pathway to guide driving recommendations.

Parkinson's Disease and Driving Fitness: A Systematic Review of the Existing Guidelines

BACKGROUND

Motor/nonmotor symptomatology and antiparkinsonian drugs deteriorate the driving ability of Parkinson's disease (PD) patients.

OBJECTIVES

Treating neurologists are frequently asked to evaluate driving fitness of their patients and provide evidence-based consultation. Although several guidelines have been published, the exact procedure along with the neurologist's role in this procedure remains obscure.

METHODS

We systematically reviewed the existing guidelines, regarding driving fitness evaluation of PD patients. We searched MEDLINE and Google Scholar and identified 109 articles. After specified inclusion criteria were applied, 15 articles were included (nine national guidelines, five recommendation papers, and one consensus statement).

RESULTS

The treating physician is proposed as the initial evaluator in 8 of 15 articles (neurologist in 2 articles) and may refer patients for a second-line evaluation. The evaluation should include motor, cognitive, and visual assessment (proposed in 15, 13, and 8 articles, respectively). Specific motor tests are proposed in eight articles (cutoff values in four), whereas specific neuropsychological and visual tests are proposed in seven articles each (cutoff values in four and three articles, respectively). Conditional licenses are proposed in 11 of 15 articles, to facilitate driving for PD patients. We summarized our findings on a graphic of the procedure for driving fitness evaluation of PD patients.

CONCLUSIONS

Neurological aspects of driving fitness evaluation of PD patients are recognized in most of the guidelines. Motor, neuropsychological, visual, and sleep assessment and medication review are key components. Clear-cut instructions regarding motor, neuropsychological, and visual tests and relative cutoff values are lacking. Conditional licenses and periodical reevaluation of driving fitness are important safety measures.

A systematic review of the impact of brain tumours on risk of motor vehicle crashes

PURPOSE

Brain tumours are associated with neurocognitive impairments that are important for safe driving. Driving is vital to maintaining patient autonomy, despite this there is limited research on driving capacity amongst patients with brain tumours. The purpose of this review is to examine MVC risk in patients with brain tumours to inform development of clearer driving guidelines.

METHODS

A systematic review was performed using Medline and EMBASE. Observational studies were included. The outcome of interest was MVC or measured risk of MVC in patients with benign or malignant brain tumours. Descriptive analysis and synthesis without meta-analysis were used to summarise findings. A narrative review of driving guidelines from Australia, United Kingdom and Canada was completed.

RESULTS

Three studies were included in this review. One cohort study, one cross-sectional study and one case-control study were included (19,135 participants) across United States and Finland. One study evaluated the incidence of MVC in brain tumour patients, revealing no difference in MVC rates. Two studies measured MVC risk using driving simulation and cognitive testing. Patients found at higher risk of MVC had greater degrees of memory and visual attention impairments. However, predictive patient and tumour characteristics of MVC risk were heterogeneous across studies. Overall, driving guidelines had clear recommendations on selected conditions like seizures but were vague surrounding neurocognitive deficits.

CONCLUSION

Limited data exists regarding driving behaviour and MVC incidence in brain tumour patients. Existing guidelines inadequately address neurocognitive complexities in this group. Future studies evaluating real-world data is required to inform development of more applicable driving guidelines.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO 2023 CRD42023434608.

Baseline Differences in Driving Frequency as a Predictor of Cognitive Decline and Alzheimer's Disease

OBJECTIVE

To extend prior research by examining daily driving frequency as a predictor of cognitive decline and later diagnosis of Alzheimer's disease.

METHODS

1,426 older adults completed batteries of questionnaires and neuropsychological tests at baseline and yearly follow-ups (M = 6.8, SD = 4.9). Linear mixed effects models were estimated to examine whether daily driving frequency at baseline was predictive of cognitive decline while accounting for IADLs, mobility, depression, and demographics. Cox regression was used to examine driving frequency as a predictor of Alzheimer's disease diagnosis.

RESULTS

Less daily driving frequency was associated with greater decline in all cognitive domains over time except for working memory. Although driving frequency was associated with these changes in cognition, it did not uniquely predict the development of Alzheimer's disease when accounting for other factors (eg, other IADLs).

CONCLUSIONS

Our findings extend prior research linking driving cessation to greater levels of cognitive decline. Future work might benefit from examining the utility of driving habits (especially changes in driving) as measures of everyday functioning in older adult evaluations.

Using Serial Trichotomization to Determine Fitness to Drive in Medically At-Risk Drivers

IMPORTANCE

Clinical tests that identify fit and unfit drivers with 100% sensitivity and specificity would reduce uncertainty and improve efficiency of occupational therapists performing comprehensive driving evaluations (CDEs).

OBJECTIVE

To examine whether serial trichotomization of clinical tests predicts pass-fail outcomes with 100% sensitivity and specificity in a sample of medically at-risk drivers and in drivers with and without cognitive impairment (CI) referred for a CDE.

DESIGN

Retrospective data collection and analysis of scores on the Montreal Cognitive Assessment; Trail Making Test, Part A and Part B; and the Useful Field of View® Subtests 1 to 3 and outcomes on the CDE (pass-fail or indeterminate requiring lessons and retesting). Receiver operating characteristic curves of clinical tests were performed to determine 100% sensitivity and specificity cut points in predicting CDE outcomes. Clinical tests were arranged in order from most to least predictive to identify pass-fail and indeterminate outcomes.

SETTING

A driving assessment clinic.

PARTICIPANTS

Among 142 medically at-risk drivers (M age = 69.2 yr, SD = 14.1), 66 with CI, 46 passed and 39 failed the CDE; 57 were indeterminate.

OUTCOMES AND MEASURES

On-road pass-fail outcomes.

RESULTS

Together, the six clinical tests predicted 62 pass and 49 fail outcomes in the total sample; 21 pass and 34 fail outcomes in participants with CI; and 58 pass and 14 fail outcomes in participants without CI.

CONCLUSIONS AND RELEVANCE

Serial trichotomization of clinical tests increases the accuracy of making informed decisions and reduces the number of drivers undergoing unnecessary on-road assessments. Plain-Language Summary: Clinical tests and their cut points that identify fit and unfit drivers vary substantially across settings and research studies. Serial trichotomization is one method that could help control for this variation by combining clinical test scores showing 100% sensitivity and specificity to identify pass (fit drivers) and fail outcomes (unfit drivers) and to reduce the number of drivers undergoing unnecessary on-road assessments.

New Community and Sociohealth Challenges Arising from the Early Diagnosis of Mild Cognitive Impairment (MCI)

Population aging increases the risk of developing neurodegenerative diseases that cause cognitive impairment. Advances in clinical practice and greater social awareness of the importance of cognitive impairment have led to an increase in the number of people with early diagnosis, predementia. Increasing access to biomarkers to assess whether Alzheimer's disease (AD) is the underlying cause of mild cognitive impairment (MCI) has undoubted clinical benefits (access to potentially disease-modifying treatments, among others) but is also responsible for new social-health care challenges. Understanding the psychosocial impact of a diagnosis of MCI due to AD or another neurodegenerative disease is essential to create future strategies to reduce the emotional overload of patients, their risk of discrimination and stigmatization, and to favor their social inclusion. We present a narrative review of the diagnostic process of mild cognitive impairment in clinical practice, with a holistic person-centered approach, and discuss the implications of such diagnosis (benefits and risks) and strategies on how to address them.

Driving Assessment for Persons with Dementia: How and when?

Dementia is a progressive neurodegenerative disease leading to deterioration in cognitive and physical skills. Driving is an important instrumental activity of daily living, essential for independence. However, this is a complex skill. A moving vehicle can be a dangerous tool in the hand of someone who cannot maneuver it properly. As a result, the assessment of driving capacity should be part of the management of dementia. Moreover, dementia comprises of different etiologies and stages consisting of different presentations. As a result, this study aims to identify driving behaviors common in dementia and compare different assessment methods. A literature search was conducted using the PRISMA checklist as a framework. A total of forty-four observational studies and four meta-analyses were identified. Study characteristics varied greatly with regards to methodology, population, assessments, and outcome measures used. Drivers with dementia performed generally worse than cognitively normal drivers. Poor speed maintenance, lane maintenance, difficulty managing intersections and poor response to traffic stimuli were the most common behaviors in drivers with dementia. Naturalistic driving, standardized road assessments, neuropsychological tests, participant self-rating and caregiver rating were the most common driving assessment methods used. Naturalistic driving and on-road assessments had the highest predictive accuracy. Results on other forms of assessments varied greatly. Both driving behaviors and assessments were influenced by different stages and etiologies of dementia at varying degrees. Methodology and results in available research are varied and inconsistent. As a result, better quality research is required in this field.

Risks of organ failures and deaths associated with young-onset dementia after hospitalizations for motor vehicle crash injuries: a nationwide population-based retrospective cohort study

Patients with dementia are at increased risks of adverse consequences associated with motor vehicle crash injury (MVCI). However, studies of the association for patients with young-onset dementia (YOD) are limited. Therefore, we aim to investigate whether YOD was associated with adverse outcomes after hospitalization for MVCI. In this retrospective cohort study, we identified 2052 MVCI patients with YOD (aged 40-64 years) between 2006 and 2015 and included 10 260 matched MVCI patients without YOD (matching ratio: 1:5) from Taiwan's National Health Insurance Research Database and the Taiwan Police-Reported Traffic Accident Registry. We evaluated the intensive care unit (ICU) admission, organ failure, in-hospital and 30-day mortalities, length of hospital stay, and hospital costs. Compared with participants without dementia, patients with YOD had higher rates of ICU admission (34.31% vs. 20.89%) and respiratory failure (6.04% vs. 2.94%), with a covariate-adjusted odds ratio of 1.50 (95% CI 1.33-1.70) and 1.63 (95% CI 1.24-2.13), respectively. The patients also exhibited higher in-hospital mortality (4.73% vs. 3.12%) and 30-day mortality (5.12% vs. 3.34%) than their non-YOD counterparts, but the risk ratio was not significant after adjusting for transport mode. Moreover, the log means of hospital stay and cost were higher among patients with YOD (0.09 days; 95% CI 0.04-0.14 and NT$0.17; 95% CI 0.11-0.23, respectively). This cohort study determined that YOD may be adversely associated with hospital outcomes among MVCI patients. However, the association between YOD and mortality risk may depend on transport mode.

Clinical Tests Predicting On-Road Performance in Older Drivers with Cognitive Impairment

Background. The Trail Making Test Part B (Trails B) and Useful Field of View® (UFOV) can predict on-road outcomes in drivers with cognitive impairment (CI); however, studies have not included drivers referred for comprehensive driving evaluations (CDEs), who typically have more severe CI. Purpose. We determined the predictive ability of Trails B and UFOV on pass/fail on-road outcomes in drivers with CI (Montreal Cognitive Assessment <26) referred for CDEs. Method. Retrospective data collection from two driving assessments centers (N  =  100, mean age  =  76.2  ±  8.8 years). Findings. The Trails B (area under the curve [AUC]  =  .70) and UFOV subtests 2 (AUC  =  .73) and 3 (AUC  =  .76) predicted pass/fail outcomes. A cut-point ≥467 ms on UFOV subtest 3 better-predicted pass/fail outcomes with 78.9% sensitivity and 73.5% specificity. In comparison, a cut-point ≥3.58 min on Trails B had lower sensitivity (73.7%) and specificity (61.8%). Implications. The UFOV subtest 3 may be more useful than the Trails B for predicting pass/fail outcomes in drivers with more severe CI referred for CDEs.

Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score

Several recent studies indicate that atypical changes in driving behaviors appear to be early signs of mild cognitive impairment (MCI) and dementia. These studies, however, are limited by small sample sizes and short follow-up duration. This study aims to develop an interaction-based classification method building on a statistic named Influence Score (i.e., I-score) for prediction of MCI and dementia using naturalistic driving data collected from the Longitudinal Research on Aging Drivers (LongROAD) project. Naturalistic driving trajectories were collected through in-vehicle recording devices for up to 44 months from 2977 participants who were cognitively intact at the time of enrollment. These data were further processed and aggregated to generate 31 time-series driving variables. Because of high dimensional time-series features for driving variables, we used I-score for variable selection. I-score is a measure to evaluate variables' ability to predict and is proven to be effective in differentiating between noisy and predictive variables in big data. It is introduced here to select influential variable modules or groups that account for compound interactions among explanatory variables. It is explainable regarding to what extent variables and their interactions contribute to the predictiveness of a classifier. In addition, I-score boosts the performance of classifiers over imbalanced datasets due to its association with the F1 score. Using predictive variables selected by I-score, interaction-based residual blocks are constructed over top I-score modules to generate predictors and ensemble learning aggregates these predictors to boost the prediction of the overall classifier. Experiments using naturalistic driving data show that our proposed classification method achieves the best accuracy (96%) for predicting MCI and dementia, followed by random forest (93%) and logistic regression (88%). In terms of F1 score and AUC, our proposed classifier achieves 98% and 87%, respectively, followed by random forest (with an F1 score of 96% and an AUC of 79%) and logistic regression (with an F1 score of 92% and an AUC of 77%). The results indicate that incorporating I-score into machine learning algorithms could considerably improve the model performance for predicting MCI and dementia in older drivers. We also performed the feature importance analysis and found that the right to left turn ratio and the number of hard braking events are the most important driving variables to predict MCI and dementia.

Driving Errors Predicting Pass/Fail On-Road Assessment Outcomes Among Cognitively Impaired Older Drivers

Older drivers with cognitive impairment (CI)/dementia make significantly more driving errors than healthy controls; however, whether driving errors are predictive of pass/fail outcomes in older drivers with CI/dementia are unclear. This study determined the driving errors that predicted failing an on-road assessment in drivers with CI. We retrospectively collected comprehensive driving evaluation data of 80 participants (76.1 ± 9.3 years) from an Ontario driving assessment center. Adjustment to stimuli (area under the curve [AUC] = 0.88), lane maintenance (AUC = 0.84), and speed regulation errors (AUC = 0.85) strongly predicted pass/fail outcomes. Worse performance on the Trails B (time) and Useful Field of View® (Subtest 2, Subtest 3, and risk index) were significantly correlated with adjustment to stimuli (p < .05), lane maintenance (p < .05), and speed regulation errors (p < .05). Adjustment to stimuli, lane maintenance, and speed regulation errors may be critical indicators of failing an on-road assessment in older drivers with CI. Prioritizing these errors may help identify at-risk drivers.

Association of falls and fear of falling with objectively-measured driving habits among older drivers: LongROAD study

OBJECTIVE

Falls in older adults are associated with increased motor vehicle crash risk, possibly mediated by driving behavior. We examined the relationship of falls and fear of falling (FOF) with subsequent objectively measured driving habits.

METHODS

This multi-site, prospective cohort study enrolled 2990 active drivers aged 65-79 (53% female). At enrollment, we assessed falls in the past year and FOF (Short Falls Efficacy Scale-International). Driving outcomes included exposure, avoidance of difficult conditions, and unsafe driving during one-year follow-up, using in-vehicle Global Positioning System devices.

RESULTS

Past-year falls were associated with more hard braking events (HBE). High FOF was associated with driving fewer days, miles, and trips, driving nearer home and more HBE. Differences were attenuated and not significant after accounting for health, function, medications and sociodemographics.

DISCUSSION

Differences in objectively measured driving habits according to past-year fall history and FOF were largely accounted for by differences in health and medications. Rather than directly affecting driving, falls and FOF may serve as markers for crash risk and reduced community mobility due to age-related changes and poor health.

Visual disorders and driving ability in persons with dementia: A mini review

Background

Impaired driving ability in patients with Alzheimer’s disease (AD) is associated with a decline in cognitive processes and a deterioration of their basic sensory visual functions. Although a variety of ocular abnormalities have been described in patients with AD, little is known about the impact of those visual disorders on their driving performance.

Aim

Aim of this mini-review is to provide an update on the driving ability of patients with dementia and summarize the primary visual disorders affecting their driving behavior.

Methods

Databases were screened for studies investigating dementia, associated visual abnormalities and driving ability.

Results

There is consistent evidence that dementia affects driving ability. Patients with dementia present with a variety of visual disorders, such as visual acuity reduction, visual field defects, impaired contrast sensitivity, decline in color vision and age-related pathological changes, that may have a negative impact on their driving ability. However, there is a paucity in studies describing the impact of oculovisual decline on the driving ability of AD subjects. A bidirectional association between cognitive and visual impairment (VI) has been described.

Conclusion

Given the bidirectional association between VI and dementia, vision screening and cognitive assessment of the older driver should aim to identify at-risk individuals and employ timely strategies for treatment of both cognitive and ocular problems. Future studies should characterize the basic visual sensory status of AD patients participating in driving studies, and investigate the impact of vision abnormalities on their driving performance.

Can executive functions of the brain predict official driving test success?

Human factors, including the level of cognitive functioning, are the most influential factors in road traffic crashes. Among cognitive abilities, executive functions (EFs) of the brain play a pivotal role in driving performance and outcomes, including crash numbers. The current study was aimed to explore, for the first time, the ability of EF tests to predict success on the official driving tests in applicants of driving license in Iran. We administered a relevant set of commonly used EF tests, including a computerized Stroop test and six tests from the Delis-Kaplan Executive Function System (D-KEFS) and the Behavioral Assessment of the Dysexecutive Syndrome (BADS), to 87 healthy new drivers applying for a driver's license (Mage = 25.9 years, SD = 8.2; 43 female). We also administered a series of demographic and psychological questionnaires. The data regarding the participants' official driving tests were extracted from the official records. To determine the relations of the EF tests with success on the driving tests, several correlation and regression analyses were conducted. Most of the EF measures had significant correlations with the road test success, while having no significant relations with the theory test success. Moreover, in our regression analyses, The EF measures predicted success on the official driving road test, but not success on the driving theory test, even after controlling for the effects of previous unlicensed driving experience and stress symptoms. The results demonstrate the predictability of the driving road test success from executive functioning.

Ecological validity of executive function tests in predicting driving performance

Almost all of our everyday activities depend on executive function (EF) skills. In line with the increasing attention to the ecological validation of neuropsychological assessment and intervention methods, this study aimed to explore the ecological validity of a relevant set of widely used EF tests, mostly from well-known paradigms of EF assessment, in predicting driving ability. Ninety-six healthy novice drivers (Mage = 26.2 years, SD = 8.4; 48 female) completed four stages of our data collection including psychological, EF, and driving assessments. For the psychological assessment, validated measures of sensation-seeking, risk-taking, personality traits, ADHD symptoms, depression, anxiety, and stress were administered. For the EF assessment, selected tests from the Delis-Kaplan Executive Function System (D-KEFS: Trail Making, Design Fluency, and Tower) and the Behavioral Assessment of the Dysexecutive Syndrome (BADS: Key Search, Zoo Map, and Modified Six Elements) along with a computerized Stroop test were administered. For the driving assessment, we used a simulated driving test comprising of 14 key dimensions of driving skills. Several correlations and multiple regression analyses were conducted. Significant correlations were found between all the EF measures and driving performance. Moreover, the EF measures predicted the driving ability over and above the effects of previous driving experience and the psychological variables. These results provide supporting evidence for the ecological validity of the EF tests in predicting driving performance. The incorporation of assessment and intervention targeting multiple domains of EF into driving rehabilitation and education programs could be a focus of future research.

White matter alterations in the dorsal attention network contribute to a high risk of unsafe driving in healthy older people

Aim

Healthy older drivers may be at high risk of fatal traffic accidents. Our recent study showed that volumetric alterations in gray matter in the brain regions within the dorsal attention network (DAN) were strongly related to the risk of unsafe driving in healthy older people. However, the relationship between white matter (WM) structural connectivity and driving ability in healthy older people is still unclear.

Methods

We used diffusion tensor imaging to examine the association between microstructural alterations in the DAN and the risk of unsafe driving among healthy older people. We enrolled 32 healthy older individuals aged over 65 years and screened unsafe drivers using an on-road driving test. We then determined the pattern of WM aberrations in unsafe drivers using tract-based spatial statistics.

Results

The analysis demonstrated that unsafe drivers had significantly higher axial diffusivity values in nine WM clusters compared with safe drivers. These results were primarily observed bilaterally in the dorsal superior longitudinal fasciculus, which is involved in the DAN. Furthermore, correlation analyses showed that higher axial diffusivity values in the superior longitudinal fasciculus were associated with lower Trail Making Test A scores within unsafe drivers. This result suggests that functionally, WM microstructural alterations in the DAN are associated with attention problems, which may contribute to the risk of unsafe driving among healthy older people.

Conclusion

Our findings may elucidate the neurobiological mechanisms underlying the increased risk of unsafe driving in healthy older people, potentially facilitating the development of new interventions to prevent fatal accidents.

The ecological validity of the Uniform Data Set 3.0 neuropsychological battery in individuals with mild cognitive impairment and dementia

Objective: Ecological validity refers to the ability of neuropsychological measures to predict real world performance. Questions remain as to the ecological validity of commonly used measures, particularly regarding their relationships to global versus specific activities of daily living among those with neurodegenerative disease. We explored these issues through the lens of the Uniform Data Set 3.0 Neuropsychological battery (UDS3NB) in individuals with mild cognitive impairment and dementia. Method: UDS3NB and informant rated Functional Activities Questionnaire scales were evaluated from 2,253 individuals with mild cognitive impairment and dementia. Ordinal regression equations were used to explore the relationships of demographic and cognitive variables with overall and specific instrumental activities of daily living. Results: Delayed recall for visual and verbal material, and performance on trail making tests were consistent predictors of global and specific functions. Specific skills (i.e. naming or figure copy) showed differential relationships with specific activities, while phonemic fluency was not related to any particular activity. Conclusions: Measures in the UDS3NB predicted activities of daily living in individuals with MCI and dementia, providing initial support for the ecological validity of these tests. Specifically, measures that tap core deficits of Alzheimer's disease, such as delayed recall and sequencing/shifting, are consistent predictors of performance in daily tasks.

An innovative therapeutic educational program to support older drivers with cognitive disorders: Description of a randomized controlled trial study protocol

Older drivers face the prospect of having to adjust their driving habits because of health problems, which can include neurocognitive disorders. Self-awareness of driving difficulties and the interaction between individual with neurocognitive disorders and natural caregiver seem to be important levers for the implementation of adaptation strategies and for the subsequent voluntary cessation of driving when the cognitive disorders become too severe. This study aims to evaluate an educational program for patient/natural caregiver dyads who wish to implement self-regulation strategies in driving activity, and to improve self-awareness of driving ability. The ACCOMPAGNE program is based on seven group workshops, which target the dyad. The workshops deal with the impact of cognitive, sensory and iatrogenic disorders on driving. They tackle questions about responsibility, and about autonomy and social life. They also provide alternative solutions aimed at maintaining outward-looking activities even if driving is reduced or stopped. A randomized controlled trial is planned to evaluate the effectiveness of the program 2 months and 6 months after inclusion, and to compare this to the effectiveness of conventional approaches. The main outcome of this trial (i.e., the implementation of self-regulated driving strategies), will be measured based on scores on the “Current Self-Regulatory Practices” subscale of the Driver Perception and Practices Questionnaire. The Driving Habits Questionnaire will be used to measure secondary outcomes (indicators of driving changes; indicators of changes in mood, quality of life and caregiver burden; and self-awareness of driving abilities). Indicators will be collected for both patients and natural caregivers. This cognitive, social and psychological program should allow older individuals with cognitive disorders to drive more safely, and help to maintain the quality of life and mood of both patient and natural caregiver despite driving limitations. The patient's care path would be optimized, as he/she would become an actor in the process of giving up driving, which will, most certainly, be needed at some point in the progress of neurocognitive disorders. This process ranges from becoming aware of driving difficulties, to implementing self-regulation strategies, through to complete cessation of driving when necessary.

Clinical trial registration number

NCT04493957.

Associations between Post-Traumatic stress disorder symptoms and automobile driving behaviors: A review of the literature

Human factors are responsible for most motor vehicle accidents that occur on the road. Recent work suggests that symptoms of posttraumatic stress disorder (PTSD) are linked to reduced driving safety, yet none have provided a comprehensive review of this small, emerging literature. The present review identified twenty-two studies reporting associations between PTSD and driving behaviors. Among these, longitudinal designs (k = 3) and studies using objective driving performance measures (e.g., simulators) (k = 2) were rare. Most studies (k = 18) relied on brief screener measures of PTSD status/symptoms or a prior chart diagnosis, while few used a standardized structured interview measure to determine PTSD status (k = 4), and only a small number of studies assessed PTSD symptom clusters (k = 7). PTSD was most frequently associated with increased rates of hostile driving behaviors (e.g., cutting off others), unintentional driving errors (e.g., lapses in attention) and negative thoughts and emotions experienced behind the wheel. Findings regarding risk of motor vehicle accident and driving-related legal issues were variable, however relatively few studies (k = 5) explored these constructs. Future directions are discussed, including the need for work focused on concurrent PTSD symptom/driving-related changes, more comprehensive PTSD and driving assessment, and consideration of the contributions of comorbid traumatic brain injury history and other neurological and psychiatric conditions on driving outcomes.

Usability of Norm Values on Results from a Simulator Device and Cognitive Tests in Traffic Medicine

Introduction

Driving is an essential everyday task for most adults, and fitness to continue car-driving after a brain injury/disease is a common issue in rehabilitation settings. There is no consensus on how this assessment should be performed and thus further research and development are of great value. The aim was to study the usability of cut-off values, based on recently developed norm values for a driving simulator device (CyberSiM), as well as cognitive tests, for patients already considered fit-to-drive after a standardized traffic medical investigation.

Methods

The study had a retrospective case-control design. Norm results (n = 129) were compared with patient results (n = 126) divided into two age groups (≤59 years and ≥60 years). Results from Useful Field of View, Trail Making Test, Nordic Stroke Driver Screening Assessment as well as a simulator device (CyberSiM) were compared.

Results

The group of patients considered fit-to-drive after a traffic medicine assessment had worse results on all cognitive tests compared with norms. Results on CyberSiM subtests II and III did not differ from norms. The proportion of patients within suggested cut-off limits (mean±2SD norm) and considered fit to drive (mean±2SD norm) were highest (75–95%) for all three subtests of CyberSiM and for Useful Field of View in both age groups.

Conclusion

Availability of norm values in decision on continued driving is of value when interpreting the results of cognitive assessments sensitive to age, but it must be handled with care because many factors are important for individuals’ ability to drive.

Driving Performance in Older Adults: Current Measures, Findings, and Implications for Roadway Safety

Background and Objectives

Over 10,000 people a day turn 65 in the United States. For many older adults, driving represents an essential component of independence and is one of the most important factors in overall mobility. Recent survey studies in older adults suggest that up to 60% of older adult drivers with mild cognitive impairment, and up to 30% with dementia, continue to drive. The purpose of this review is to provide a comprehensive and detailed resource on the topics of cognition and driving for clinicians, researchers, and policymakers working on efforts related to older adult drivers.

Research Design and Methods

Publications on PubMed and Medline and discussions with experts working in geriatrics, technology, driving policy, psychology, and diverse aspects of driving performance were utilized to inform the current review.

Results

Research indicates that there is a complex and inverse correlation between multiple cognitive measures, driving performance, and risky driving behaviors. The fragmented nature of available peer-reviewed literature, and a reliance on correlative data, do not currently allow for the identification of the temporal and reciprocal nature of the interplay between cognition and driving endpoints.

Discussion and Implications

There are currently no widely accepted definitions, conceptual models, or uniform set of analyses for conducting geriatric research that is focused on driving. Establishing conventions for conducting research that harmonizes the fields of geriatrics, cognition, and driving research is critical for the development of the evidence base that will inform clinical practice and road safety policy.

Verbal Learning as a predictor of risks of accidents in elderly drivers

BACKGROUND

Age-related cognitive decline impacts cognitive abilities essential for driving.

OBJECTIVE

We aimed to measure main cognitive functions associated with a high number of traffic violations in different driving settings.

METHODS

Thirty-four elderly individuals, aged between 65 and 90 years, were evaluated with a driving simulator in four different settings (Intersection, Overtaking, Rain, and Malfunction tasks) and underwent a battery of cognitive tests, including memory, attention, visuospatial, and cognitive screening tests. Individuals were divided into two groups: High-risk driving (HR, top 20% of penalty points) and normal-risk driving (NR). Non-parametric group comparison and regression analysis were performed.

RESULTS

The HR group showed higher total driving penalty score compared to the NR group (median=29, range= 9-44 vs. median=61, range= 47-97, p<0.001). The HR group showed higher penalty scores in the Intersection task (p<0.001) and the Overtaking and Rain tasks (p<0.05 both). The verbal learning score was significantly lower in the HR group (median=33, range=12-57) compared with the NR group (median=38, range=23-57, p<0.05), and it was observed that this score had the best predictive value for worse driving performance in the regression model. General cognitive screening tests (Mini-Mental State Examination and Addenbrooke's Cognitive Evaluation) were similar between the groups (p>0.05), with a small effect size (Cohen's d=0.3 both).

CONCLUSION

The verbal learning score may be a better predictor of driving risk than cognitive screening tests. High-risk drivers also showed significantly higher traffic driving penalty scores in the Intersection, Overtaking, and Rain tests.

Medicolegal Implications of Mild Neurocognitive Disorder

INTRODUCTION

The syndromes of mild cognitive impairment (MCI) or mild neurocognitive disorder (MiND), often prodromal to dementia (Major Neurocognitive Disorder), are characterized by acquired clinically significant changes in one or more cognitive domains despite preserved independence. Mild impairment has significant medicolegal consequences for an affected person and their care system. We review the more common etiologies of MiND and provide a systematic review of its medicolegal implications.

METHODS

We conducted a systematic review of the peer-reviewed English literature on medicolegal aspects of MCI or MiND using comprehensive search terms and expanding our review to include sources cited by these reports.

RESULTS

Impairment of memory, executive function, social cognition, judgment, insight or abstraction can alter an individual's abilities in a variety of areas that include decision making, informed consent, designation of a surrogate decision-maker such as a health care proxy, understanding and management of financial affairs, execution of a will, or safe driving.

CONCLUSION

Even mild cognitive impairment can have significant behavioral consequences. Clinicians can assist care partners and persons with MCI or MiND by alerting them to the medicolegal concerns that often accompany cognitive decline. Early recognition and discussion can help a care system manage medicolegal risk more effectively and promote thoughtful advance planning.

Effect of Apolipoprotein E4 on the Driving Behavior of Patients with Amnestic Mild Cognitive Impairment or Mild Alzheimer's Disease Dementia

BACKGROUND

The driving behavior of patients with mild Alzheimer's disease dementia (ADD) and patients with mild cognitive impairment (MCI) is frequently characterized by errors. A genetic factor affecting cognition is apolipoprotein E4 (APOE4), with carriers of APOE4 showing greater episodic memory impairment than non-carriers. However, differences in the driving performance of the two groups have not been investigated.

OBJECTIVE

To compare driving performance in APOE4 carriers and matched non-carriers.

METHODS

Fourteen APOE4 carriers and 14 non-carriers with amnestic MCI or mild ADD underwent detailed medical and neuropsychological assessment and participated in a driving simulation experiment, involving driving in moderate and high traffic volume in a rural environment. Driving measures were speed, lateral position, headway distance and their SDs, and reaction time. APOE was genotyped through plasma samples.

RESULTS

Mixed two-way ANOVAs examining traffic volume and APOE4 status showed a significant effect of traffic volume on all driving variables, but a significant effect of APOE4 on speed variability only. APOE4 carriers were less variable in their speed than non-carriers; this remained significant after a Bonferroni correction. To further examine variability in the driving performance, coefficients of variation (COV) were computed. Larger headway distance COV and smaller lateral position COV were observed in high compared to moderate traffic. APOE4 carriers had smaller speed COV compared to non-carriers.

CONCLUSION

The lower speed variability of APOE4 carriers in the absence of neuropsychological test differences indicates reduced speed adaptations, possibly as a compensatory strategy. Simulated driving may be a sensitive method for detecting performance differences in the absence of cognitive differences.

Driving and Alzheimer's dementia or mild cognitive impairment: a systematic review of the existing guidelines emphasizing on the neurologist's role

BACKGROUND

Driving is a complex task requiring the integrity and the cooperation of cognition, motor, and somatosensory skills, all of which are impacted by neurological diseases.

OBJECTIVE

Identification of neurologist's role when assessing fitness to drive of cognitively impaired individuals.

METHODS

We performed a systematic review of the guidelines/recommendations (G/Rs) regarding the evaluation of driving fitness of patients with mild cognitive impairment (MCI) and/or dementia. Emphasis was put on the neurological and neuropsychological aspects of the evaluation.

RESULTS

Eighteen G/Rs were included in the review (9 national guidelines, 5 recommendation papers, 3 consensus statements, and 1 position paper). All G/Rs referred to drivers with dementia and 9/18 referred to drivers with MCI. A common approach among G/Rs is the initial trichotomization of patients in safe to drive, unsafe to drive, and undetermined cases, which are referred to a second-line evaluator. First-line evaluators are general practitioners in 10/18 G/Rs; second-line evaluators are neurologists in 7/18 G/Rs. Specific neuropsychological tests are proposed in 11/18 G/Rs and relative cut-off values in 7/18. The most commonly used tests are the MMSE, TMT, and CDT. A thorough neurological examination is proposed in only 1/18 G/R.

CONCLUSION

Although extensive multi-disciplinary research has provided useful information for driving behavior of cognitively impaired individuals, we are still far from a widely accepted approach of driving ability evaluation in this increasing population. A comprehensive assessment from a multi-disciplinary team in which the neurologist plays a critical role seems to be required, although this has not yet been implemented in any G/Rs.

Predicting On-Road Driving Skills, Fitness to Drive, and Prospective Accident Risk in Older Drivers and Drivers with Mild Cognitive Impairment: The Importance of Non-Cognitive Risk Factors

BACKGROUND

On-road driving behavior can be impaired in older drivers and particularly in drivers with mild cognitive impairment (MCI).

OBJECTIVE

To determine whether cognitive and non-cognitive risk factors for driving safety may allow an accurate and economic prediction of on-road driving skills, fitness to drive, and prospective accident risk in healthy older drivers and drivers with MCI, we examined a representative combined sample of older drivers with and without MCI (N = 74) in an observational on-road study. In particular, we examined whether non-cognitive risk factors improve predictive accuracy provided by cognitive factors alone.

METHODS

Multiple and logistic hierarchical regression analyses were utilized to predict different driving outcomes. In all regression models, we included cognitive predictors alone in a first step and added non-cognitive predictors in a second step.

RESULTS

Results revealed that the combination of cognitive and non-cognitive risk factors significantly predicted driving skills (R2adjusted = 0.30) and fitness to drive (81.2% accuracy) as well as the number (R2adjusted = 0.21) and occurrence (88.3% accuracy) of prospective minor at-fault accidents within the next 12 months. In all analyses, the inclusion of non-cognitive risk factors led to a significant increase of explained variance in the different outcome variables.

CONCLUSION

Our findings suggest that a combination of the most robust cognitive and non-cognitive risk factors may allow an economic and accurate prediction of on-road driving performance and prospective accident risk in healthy older drivers and drivers with MCI. Therefore, non-cognitive risk factors appear to play an important role.

Fitness to drive after acquired brain injury: Results from patient cognitive screening and on-road assessment compared to age-adjusted norm values

Fitness to drive after acquired brain injury or disease is a common question in rehabilitation settings. The aim of the study was to compare age-matched norms with patient cognitive test results used to predict fitness to drive. A second aim was to analyze the contribution from an on-road assessment to a final decision on resumption of driving after an acquired brain injury. Retrospective cognitive test results from four traffic medicine units (n = 333) were compared with results from a healthy norm population (n = 410) in Sweden. Patients were dichotomized according to the final decision as fit or unfit to drive made by the traffic medicine team. The norm group had significantly better results in all age groups for all cognitive tests compared with the patients considered unfit to drive and fit to drive. A binary regression analysis for the patient group showed an explained value for fit to drive/unfit to drive of 88%, including results for the Nordic Stroke Driver Screening Assessment total score, Useful Field of View total score and the final outcome from an on-road assessment. Results from the present study illustrate the importance of using several tests, methods and contexts for the final decision regarding fitness to drive.

Driving Performance and Its Correlation with Neuropsychological Tests in Senior Drivers with Cognitive Impairment in Japan

BACKGROUND

With the rapid aging of the population, the issue of driving by dementia patients has been causing increasing concern worldwide.

OBJECTIVE

To investigate the driving difficulties faced by senior drivers with cognitive impairment and identify the specific neuropsychological tests that can reflect specific domains of driving maneuvers.

METHODS

Senior drivers with cognitive impairment were investigated. Neuropsychological tests and a questionnaire on demographic and driving characteristics were administered. Driving simulator tests were used to quantify participants' driving errors in various domains of driving.

RESULTS

Of the 47 participants, 23 current drivers, though they had better cognitive functions than 24 retired drivers, were found to have impaired driving performance in the domains of Reaction, Starting and stopping, Signaling, and Overall (wayfinding and accidents). The parameters of Reaction were significantly related to the diagnosis, and the scores of MMSE, TMT-A, and TMT-B. As regards details of the driving errors, "Sudden braking" was associated with the scores of MMSE (ρ= -0.707, p < 0.01), BDT (ρ= -0.560, p < 0.05), and ADAS (ρ= 0.758, p < 0.01), "Forgetting to use turn signals" with the TMT-B score (ρ= 0.608, p < 0.05), "Centerline crossings" with the scores of MMSE (ρ= -0.582, p < 0.05) and ADAS (ρ= 0.538, p < 0.05), and "Going the wrong way" was correlated with the score of CDT (ρ= -0.624, p < 0.01).

CONCLUSION

Different neuropsychological factors serve as predictors of different specific driving maneuvers segmented from driving performance.

Protocol for the conceptualization and evaluation of a screening-tool for fitness-to-drive assessment in older people with cognitive impairment

Introduction

Due to aging and health status people may be subjected to a decrease of cognitive ability and subsequently also a decline of driving safety. On the other hand there is a lack of valid and economically applicable instruments to assess driving performance.

Objective

The study is designed to develop a valid screening-tool for fitness-to-drive assessment in older people with cognitive impairment externally validated on the basis of on-road driving performance.

Methods

In a single-centre, non-randomized cross-sectional trial cognitive functioning and on-road-driving-behavior of older drivers will be assessed. Forty participants with cognitive impairment of different etiology and 40 healthy controls will undergo an extensive neuropsychological assessment. Additionally, an on-road driving assessment for external validation of fitness to drive will be carried out. Primary outcome measures will be performance in attention, executive functions and visuospatial tasks that will be validated with respect to performance on the on-road-driving-test. Secondary outcome measures will be sociodemographic, clinical- and driving characteristics to systematically examine their influence on the prediction of driving behavior.

Discussion

In clinical practice counselling patients with respect to driving safety is of great relevance. Thus, having valid, reliable, time economical and easily interpretable screening-tools on hand to counsel patients is of great relevance for practitioners.

Ethics and dissemination

Ethics approval was obtained from the Ethics Committee at the Ludwig-Maximilians-University Munich. The trial results will be disseminated through peer-reviewed publications and various conferences.

Trial registration

18–640.

Trial registration: German Clinical Trials Register.

Registration number: DRKS00023549.

Occupational Therapy Interventions to Improve Driving Performance in Older People With Mild Cognitive Impairment or Early-Stage Dementia: A Systematic Review

IMPORTANCE

For a person with mild cognitive impairment (MCI) or early-stage dementia, driving is important for independence. However, driving presents safety concerns for both the person and family members. It is important to determine whether occupational therapy interventions can prolong safe driving for this population.

OBJECTIVE

To determine the effectiveness of occupational therapy interventions to improve driving performance in older people with MCI or early-stage dementia.

DATA SOURCES

We conducted a search of MEDLINE, PsycINFO, CINAHL, and gray literature using Google Scholar. Study Selection and Data Collection: Studies were included if they evaluated interventions that (1) aimed to improve the driving performance of older people (M age ≥60 yr) with MCI or early-stage dementia and (2) could be designed or delivered by an occupational therapy practitioner who specializes in driving. Citations were reviewed independently by two authors, and quality appraisal was conducted using the Cochrane risk-of-bias guidelines.

FINDINGS

One Level I randomized controlled trial (RCT) and 4 Level III quasi-experimental studies were included; these studies had 231 participants in total with reported M ages of 65.6-72.5 yr. One study evaluated a compensatory approach, whereas the others evaluated a remedial approach. The studies used different measures to assess outcomes and reported mixed effects.

CONCLUSIONS AND RELEVANCE

Low strength of evidence suggests that occupational therapy interventions may improve the driving performance of older people with MCI or early-stage dementia. More RCTs are needed that include long-term follow-up measures and address clinically important outcomes. What This Article Adds: In the absence of conclusive evidence from research studies and best practice guidelines, occupational therapy practitioners must rely on their clinical experience and their clients' abilities. Development of evidence and guidelines in this area is critical. It is also important for practitioners to work closely with clients, families, and interdisciplinary team members to carefully monitor fitness to drive.

GPS driving: a digital biomarker for preclinical Alzheimer disease

BACKGROUND

Alzheimer disease (AD) is the most common cause of dementia. Preclinical AD is the period during which early AD brain changes are present but cognitive symptoms have not yet manifest. The presence of AD brain changes can be ascertained by molecular biomarkers obtained via imaging and lumbar puncture. However, the use of these methods is limited by cost, acceptability, and availability. The preclinical stage of AD may have a subtle functional signature, which can impact complex behaviours such as driving. The objective of the present study was to evaluate the ability of in-vehicle GPS data loggers to distinguish cognitively normal older drivers with preclinical AD from those without preclinical AD using machine learning methods.

METHODS

We followed naturalistic driving in cognitively normal older drivers for 1 year with a commercial in-vehicle GPS data logger. The cohort included n = 64 individuals with and n = 75 without preclinical AD, as determined by cerebrospinal fluid biomarkers. Four Random Forest (RF) models were trained to detect preclinical AD. RF Gini index was used to identify the strongest predictors of preclinical AD.

RESULTS

The F1 score of the RF models for identifying preclinical AD was 0.85 using APOE ε4 status and age only, 0.82 using GPS-based driving indicators only, 0.88 using age and driving indicators, and 0.91 using age, APOE ε4 status, and driving. The area under the receiver operating curve for the final model was 0.96.

CONCLUSION

The findings suggest that GPS driving may serve as an effective and accurate digital biomarker for identifying preclinical AD among older adults.

Using Video Replay of Simulated Driving to Estimate Driving Safety and Cognitive Status

Cognitive decline resulting from Dementia of Alzheimer’s Type (DAT) can lead to reduced ability to perform complex daily tasks required for independent living, including driving an automobile. This study explores the ability of untrained observers to classify driving safety using short video clips of simulated driving through intersections; it also examined whether untrained observers could predict whether the driver was cognitively healthy or cognitively impaired. Participants (n = 54) were shown a series of 30 video clips arranged in an online survey and asked to answer questions following each clip regarding the safety of the maneuver and the cognitive status of the driver. Results showed that participants’ subjectively rated DAT drivers as significantly less safe in comparison to control drivers, F (1, 52) = 228.44, p < 0.001. Participant’s classification of DAT drivers and controls was also significantly higher than chance (i.e., >50% correct). Findings provide preliminary support for the development of a clinical decision-making aid using video replay of driving simulator performance in fitness-to-drive assessments for individuals with cognitive impairment.

Trail Making Test Normative Data for the German Older Population

OBJECTIVE

We provide normative data for the Trail Making Test (TMT)-A and B and the derived scores B - A and B/A, for the German general population aged 57-84 years.

METHODS

Data were derived from the third examination of the population-based Heinz Nixdorf Recall study. We excluded participants with a history of dementia or stroke, a depression score above cutoff (CES-D Center for Epidemiologic Studies Depression Scale score ≥ 18), or mild cognitive impairment according to a neurocognitive test battery. The normative sample (n = 2,182) was stratified by age, using the interval superposition approach, and by three levels of educational attainment (up to 10 years of schooling; >10 years of schooling; and university degree).

RESULTS

We tabulated test performance scores at percentage rank thresholds 5, 10, 15, 20, 25, 50, 75, and 90. In multiple linear regression, TMT-A performance declined by 1 s each year of life, and TMT-B performance by 3 s; educational level had an impact of up to 30 s in TMT-B. TMT-B/A was only weakly associated with age and education. TMT-B and B - A correlated r = 0.96. Completion of the TMT-B within the time limit of 300 s was not achieved by 10.9% of participants >74 years, and especially by those >74 years who were on the lowest educational level (13.9%).

CONCLUSIONS

For TMT-A, TMT-B, and B - A, the narrow age categorization and distinction between three educational levels proved meaningful. The 300 s limit for the TMT-B impedes the identification of thresholds for very low performance in this age group and needs reconsideration.

Driving exposure, patterns and safety critical events for older drivers with and without mild cognitive impairment: Findings from a naturalistic driving study

OBJECTIVE

The aim of the study is to compare driving exposure, patterns and factors associated with safety critical events between drivers with MCI and a comparison group without cognitive impairment.

DESIGN, SETTING, PARTICIPANTS

Naturalistic driving data using an in-vehicle monitoring device were collected from 36 older drivers with MCI and 35 older drivers without cognitive impairment over a two-week period in Western Australia.

MEASUREMENTS

Naturalistic driving exposure, patterns (eg. night-time trips, peak-hour trips) and safety critical events (harsh acceleration, harsh braking and harsh cornering).

RESULTS

Drivers with MCI had a lower number of safety critical events (mean = 7.20, SD = 11.44) compared to drivers without cognitive impairment (mean = 10.89, SD = 23.30) however, this was not statistically significantly. There were also no statistically significant differences between drivers with and without MCI for measures of driving exposure or any of the driving patterns including weekday trips, night-time trips and trips on highways/freeways. The results of the multivariable modelling found only binocular contrast sensitivity was associated with the rate of safety critical events. For every increase of 0.1 log units in contrast sensitivity (better contrast sensitivity) the rate of safety critical events significantly decreased by 30 % (IRR = 0.70, 95 % CI = 0.50-0.98, p = 0.04).

CONCLUSION

Drivers with MCI were found to have similar driving exposure and patterns compared to older drivers without cognitive impairment, however drivers with better contrast sensitivity experienced fewer safety critical events. Future research should consider a longitudinal study design with an extended driving monitoring period and a larger sample with a clinical diagnosis of MCI to assess changes in cognition and its impact on driving.

Clinical Utility of Two- and Three-Dimensional Visuoconstructional Tasks in Mild Cognitive Impairment and Early Alzheimer's Disease

OBJECTIVE

The aim of this study was to investigate whether different types of visuoconstructional abilities are useful to distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy controls (HCs).

METHOD

We selected 20 patients with MCI and 14 with AD diagnosis based on standard criteria. The neuropsychological performance of MCI and AD groups were compared with that of a group of 11 HCs using a standard neuropsychological battery and visuoconstructional tasks that differed difficulty and type of implicated skills (graphomotor vs. non-graphomotor): two-dimensional (Clock Drawing Test, CDT; Block Design, BD; and Visual Puzzles, VP) and three-dimensional Block Construction (TBC).

RESULTS

AD group scored significantly lower than HCs in BD, VP and TBC tasks, but no significant differences were found between HCs and MCI. CDT (copy condition) scores did not differ significantly among the groups. The receiver operating characteristic analysis showed that BD [sensitivity (se) = .85, specificity (sp) = .90, Youden index (J) = .76], VP (se = .78 and sp = .72, J = .51) and TBC (se = .71, sp = 100, J = .71) were accurate tasks to discriminate between AD and HCs. Moreover, BD tasks (se = .85, sp = .70, J = .55) and TBC (se = .71, sp = .80, J = .51) showed fair accuracy to differentiate between MCI and AD groups.

CONCLUSIONS

These findings indicate that non-graphomotor visuoconstructional tasks are already impaired in the early stages of AD, but are preserved in MCI individuals when compared with HCs.

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.

Assessing fitness to drive in older adults: Validation and extension of an economical screening tool

OBJECTIVES

Due to demographic change, the number of older drivers with impaired driving skills will increase in the next decades. The current study aimed at the validation and extension of the screening tool Safety Advice For Elderly drivers (SAFE) that allows a cost-efficient assessment of driving-related risk factors in older drivers.

METHOD

Seventy-four older drivers aged ≥65 years (M = 77 years) recruited from the general population were included in this prospective observational study. Receiver operating characteristic curve (ROC) and hierarchical logistic regression analyses were utilized to examine whether the SAFE and further evidence-based driving-related factors may allow the differentiation between fit and unfit older drivers assessed in standardized on-road driving assessments.

RESULTS

ROC analyses revealed significant diagnostic accuracy of the number of SAFE risk factors in differentiating between fit and unfit older drivers (AUC = 0.71). A stepwise logistic regression model revealed that adding further evidence-based risk factors into the SAFE clearly improved diagnostic accuracy (AUC = 0.85).

DISCUSSION

The current study shows that the risk assessed by the SAFE predicts on-road driving fitness in older adults. However, the results also suggest a need for a modification of the SAFE by the inclusion of additional evidence-based risk factors. With sensitivity and specificity scores of about 90 % and 75 %, this modified version may be more suitable for clinical use.

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

In developed countries, the number of traffic accidents caused by older drivers is increasing. Approximately half of the older drivers who cause fatal accidents are cognitively normal. Thus, it is important to identify older drivers who are cognitively normal but at high risk of causing fatal traffic accidents. However, no standardized method for assessing the driving ability of older drivers has been established. We aimed to establish an objective assessment of driving ability and to clarify the neural basis of unsafe driving in healthy older people. We enrolled 32 healthy older individuals aged over 65 years and classified unsafe drivers using an on-road driving test. We then utilized a machine learning approach to distinguish unsafe drivers from safe drivers based on clinical features and gray matter volume data. Twenty-one participants were classified as safe drivers and 11 participants as unsafe drivers. A linear support vector machine classifier successfully distinguished unsafe drivers from safe drivers with 87.5% accuracy (sensitivity of 63.6% and specificity of 100%). Five parameters (age and gray matter volume in four cortical regions, including the left superior part of the precentral sulcus, the left sulcus intermedius primus [of Jensen], the right orbital part of the inferior frontal gyrus, and the right superior frontal sulcus), were consistently selected as features for the final classification model. Our findings indicate that the cortical regions implicated in voluntary orienting of attention, decision making, and working memory may constitute the essential neural basis of driving behavior.

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.

Avoidance Behavior Is an Independent Indicator of Poorer On-road Driving Skills in Older Adults

OBJECTIVES

The aim of the current work was to investigate the relationship between avoidance of specific driving situations and on-road driving skills in older drivers considering factors found to be related to both avoidance behavior and driving skills.

METHOD

Seventy-two older drivers (M = 76 years) from the general population were included in this study. Self-reported avoidance behavior, driving practice, perceived driving difficulties, driving-related cognitive functions, as well as medical conditions were assessed within two sessions. Standardized on-road assessments served for assessing on-road driving skills in a third session.

RESULTS

Self-reported avoidance behavior was associated with reduced driving skills (r = -.41), and this relationship remained significant beyond the influence of cognitive skills, self-reported health, driving practice, and perceived driving difficulties. Specifically, avoidance of driving in bad weather, poor visibility and complicated parking was found to be associated with reduced driving skills.

DISCUSSION

This study suggest that avoidance behavior is an independent indicator of impaired driving skills in older drivers. Our results argue against the assumption that avoidance behavior may be a reasonable strategy for safe traffic participation. Longitudinal studies are urgently needed to get more evidence on safety aspects of avoidance behavior.

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.

Buckle up!

Die Verkehrsmedizin als Teil der Rechtsmedizin erfüllt in der Schweiz eine wichtige präventive Aufgabe in der Sicherung aller Verkehrsteilnehmer: Sie begutachtet die medizinisch basierte Fahrfähigkeit und Fahreignung. Als empirisch konsolidiertes Querschnittsfach hat sie Informationen aus einer Vielzahl von medizinischen Fachgebieten. Wie reagiert die Verkehrsmedizin aber auf den vermehrten Anspruch evidenzbasierter Gutachten und auf anstehende Herausforderungen?

Über einen historischen Abriss motivierten wir die Vorteile und das Potential einer teilweise durch Fahrsimulation ergänzten Untersuchung und einer dediziert auf Fahrsimulation basierenden, klinisch-prospektiven Forschung.

Neben vorhandener Literatur stützen sich historische Aspekte u.a. auf vorhandene Expertise. Die Bewertung der Fahrsimulation für die Verkehrs- bzw. Rechtsmedizin der Schweiz stützt sich auf die Diskussion selektierter Literatur.

Auftrag und Anspruch der Verkehrsmedizin haben sich mehrfach verändert. Eine übersichtsartige Betrachtung existenter Literatur legt nahe, dass massgeschneiderte Fahrsimulatoren Teil einer modernisierten Verkehrsmedizin sein können, um anstehende Herausforderungen adäquat adressieren zu können. Bisher existiert kein derartiges dediziertes Forschungsinstrument in der Schweiz.

Eine auf verkehrsmedizinische Fragestellungen massgeschneiderte, realitätsnahe und niedrigschwellige Fahrsimulation als Werkzeug für klinische Studien und Individualuntersuchungen verspricht neben einer wissenschaftlichen Produktivität einen umsetzbaren und vermittelbaren Mehrwert für das übergeordnete Ziel der Sicherheit aller Verkehrsteilnehmer.

Decisions on driving after brain injury/disease: Feasibility and construct validity of a new simulator assessment tool

Introduction

Driving is a complex activity involving a high level of cognitive abilities and thus might be affected after a brain injury/disease. The aim of this research was to evaluate the feasibility and construct validity of a driving simulator tool as a complement to existing driving assessments of patients with cognitive dysfunctions after a brain injury/disease.

Method

A descriptive and prospective research design was achieved. For construct validation, decisions were based on results from the Useful Field of View, Nordic Stroke Driver Screening Assessment, Trail Making Test and, when necessary for the decision, an on-road observation. Results from the simulator tool were not included in the clinical decision process.

Results

A total of 129 patients from four different rehabilitation services were included. The results showed a significant difference in test results between those who were considered medically fit versus unfit to drive. A factor analysis revealed four components, all including attention in combination with processing speed, visuospatial function, simultaneous capacity and executive function; these are all represented in the simulator tool. A correlation analysis showed that simulator subtest 3 (response/divergent response to stimuli) had the strongest correlation with most of the other tests included.

Conclusions

The simulator was found to be feasible and valid and found to include components other than those measured in the other tests.

Machine-learning approach to predict on-road driving ability in healthy older people

AIM

In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who are cognitively normal but at high risk of having fatal traffic accidents. However, a standardized method for assessing the driving ability of older drivers has not yet been established. We thus aimed to identify a new sensing method for the evaluation of the on-road driving ability of healthy older people on the basis of vehicle behaviors.

METHODS

We enrolled 33 healthy older individuals aged over 65 years and utilized a machine-learning approach to dissociate unsafe drivers from safe drivers based on cognitive assessments and a functional visual acuity test.

RESULTS

The linear support vector machine classifier successfully dissociated unsafe drivers from safe drivers with accuracy of 84.8% (sensitivity of 66.7% and specificity of 95.2%). Five clinical parameters, namely age, the first trial of the Rey Auditory Verbal Learning Test immediate recall, the delayed recall of the Rey-Osterrieth Complex Figure Test, the result of the free-drawn Clock Drawing Test, and maximal visual acuity, were consistently selected as essential features for the best classification model.

CONCLUSION

Our findings improve our understanding of clinical risk factors leading to unsafe driving and may provide insight into a new intervention that prevents fatal traffic accidents caused by healthy older people.

Predictors of accidents in people with mild cognitive impairment, mild dementia due to Alzheimer's disease and healthy controls in simulated driving

OBJECTIVES

To examine the driving variables that predict accident probability in mild dementia due to Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy older control drivers in simulated driving. To compare the three groups in mean performance and in frequency of scores exceeding 1.5 SD from the mean.

METHODS/DESIGN

Participants were 37 drivers with MCI, 16 drivers with AD, and 21 control drivers over the age of 52. Driving measures were derived from four rural driving conditions: moderate traffic without and with distraction and high traffic without and with distraction. The measures were z-transformed based on the performance of 90 control drivers of different ages. Two unexpected incidents occurred per condition, requiring the sudden breaking to avoid an accident.

RESULTS

Drivers with AD showed significantly lower average speed, speed variability, greater headway distance, headway variability and average reaction time (RT) than control drivers. Drivers with MCI showed significantly lower average speed, greater headway distance and average RT than control drivers in the two conditions of distraction. No differences were found in accident probability. Drivers with AD had more deviant scores than both control drivers and drivers with MCI in most comparisons. Predictors of accident probability were average RT, speed variability and lateral position variability but MCI and AD status were not significant predictors in any of the regression models.

CONCLUSIONS

Despite significant differences in performance, drivers with MCI and AD did not differ in accident probability from control drivers. An individualized approach of examining individual driving performance is recommended.