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

Toepper, Max; Schulz, Philipp; Beblo, Thomas; Drießen, Martin

doi:10.3233/jad-200943

Cited by 18 publications

(13 citation statements)

References 43 publications

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“…As safe driving requires “the complex interaction of physical, cognitive, perceptual, and psychological skills and abilities” [ 24 ], there is a wide range of combinations, either focusing on cognitive abilities or also capturing vision, motor function and recorded or self-reported driving incidents [ 25 – 27 ]. Of the “cognitive” tests, each might focus on different domains, such as attention, construction/visuospatial skills, memory, executive function, perception or span general mental ability [ 22 , 23 , 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…Large scale validation studies do show that such tools can reliably identify those elderly drivers with a high likelihood of failing on road tests, be it due to dementia [ 43 ], or due to (mild) cognitive or visual impairment [ 33 ]. In addition, off-road screening tools for safe driving in the elderly could be shown to benefit both time- and cost-wise from including also from simple non-cognitive information, such as number of medication taken per day, cervical spine mobility, impaired visual acuity or field of view and avoidance behavior, while maintaining high validity to results from on-road testing [ 26 , 27 , 44 ]. Effective screening tools might promise a possibility to alleviate cost and personnel related issues in relation to on-road tests, such as the MSDT.…”

Section: Discussionmentioning

confidence: 99%

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Strong evidence for age as the single most dominant predictor of medically supervised driving test—mini mental status test outcomes provide only weak but significant moderate additional predictive value

et al. 2022

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Background With age, medical conditions impairing safe driving accumulate. Consequently, the risk of accidents increases. To mitigate this risk, Swiss law requires biannual assessments of the fitness to drive of elderly drivers. Drivers may prove their cognitive and physical capacity for safe driving in a medically supervised driving test (MSDT) when borderline cases, as indicated by low performance in a set of four cognitive tests, including e.g. the mini mental status test (MMST). Any prognostic, rather than indicative, relations for MSDT outcomes have neither been confirmed nor falsified so far. In order to avoid use of unsubstantiated rules of thumb, we here evaluate the predictive value for MSDT outcomes of the outcomes of the standard set of four cognitive tests, used in Swiss traffic medicine examinations. Methods We present descriptive information on age, gender and cognitive pretesting results of all MSDTs recorded in our case database from 2017 to 2019. Based on these retrospective cohort data, we used logistic regression to predict the binary outcome MSDT. An exploratory analysis used all available data (model 1). Based on the Akaike Information Criterion (AIC), we then established a model including variables age and MMST (model 2). To evaluate the predictive value of the four cognitive assessments, model 3 included cognitive test outcomes only. Receiver operating characteristics (ROC) and area under the curve (AUC) allowed evaluating discriminative performance of the three different models using independent validation data. Results Using N = 188 complete data sets of a total of 225 included cases, AIC identified age (p < 0.0008) and MMST (p = 0.024) as dominating predictors for MSDT outcomes with a median AUC of 0.71 (95%-CI 0.57–0.85) across different training and validation splits, while using the four cognitive test results exclusively yielded a median AUC of 0.55 (95%-CI 0.40–0.71). Conclusions Our analysis provided strong evidence for age as the single most dominant predictor of MSDT outcomes. Adding MMST provides only weak additional predictive value for MSDT outcomes. Combining the results of four cognitive test used as standard screen in Swiss traffic medicine alone, proved to be of poor predictive value. This highlights the importance of MSDTs for balancing between the mitigation of risks by and the right to drive for the elderly.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Strong evidence for age as the single most dominant predictor of medically supervised driving test—mini mental status test outcomes provide only weak but significant moderate additional predictive value

et al. 2022

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“…Finally, we would like to consider how our findings can be translated to clinical application. One possible way is an assessment of driving function of individuals with potential mild cognitive impairment (MCI), as their cognitive processing speed is highly associated with driving functions ( Wadley et al, 2020 ; Toepper et al, 2021 ). During driving license renewal for the elderly, questionnaires and driving simulations are typically used to assess their driving function, and no neurophysiological assessments are performed.…”

Section: Discussionmentioning

confidence: 99%

The Effect of Prior Knowledge of Color on Behavioral Responses and Event-Related Potentials During Go/No-go Task

Kubo

Watanabe

Chen

et al. 2021

Front. Hum. Neurosci.

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In daily life, the meaning of color plays an important role in execution and inhibition of a motor response. For example, the symbolism of traffic light can help pedestrians and drivers to control their behavior, with the color green/blue meaning go and red meaning stop. However, we don’t always stop with a red light and sometimes start a movement with it in such a situation as drivers start pressing the brake pedal when a traffic light turns red. In this regard, we investigated how the prior knowledge of traffic light signals impacts reaction times (RTs) and event-related potentials (ERPs) in a Go/No-go task. We set up Blue Go/Red No-go and Red Go/Blue No-go tasks with three different go signal (Go) probabilities (30, 50, and 70%), resulting in six different conditions. The participants were told which color to respond (Blue or Red) just before each condition session but didn’t know the Go probability. Neural responses to Go and No-go signals were recorded at Fz, Cz, and Oz (international 10–20 system). We computed RTs for Go signal and N2 and P3 amplitudes from the ERP data. We found that RT was faster when responding to blue than red light signal and also was slower with lower Go probability. Overall, N2 amplitude was larger in Red Go than Blue Go trial and in Red No-go than Blue No-go trial. Furthermore, P3 amplitude was larger in Red No-go than Blue No-go trial. Our findings of RT and N2 amplitude for Go ERPs could indicate the presence of Stroop-like interference, that is a conflict between prior knowledge about traffic light signals and the meaning of presented signal. Meanwhile, the larger N2 and P3 amplitudes in Red No-go trial as compared to Blue No-go trial may be due to years of experience in stopping an action in response to a red signal and/or attention. This study provides the better understanding of the effect of prior knowledge of color on behavioral responses and its underlying neural mechanisms.

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“…There were a range of driving outcomes for participants attending the driving fitness assessment clinic, with many people continuing driving and a smaller number discontinuing driving. This audit builds on findings from emerging research conducted in research contexts, which describes variability in the driving capabilities of people with a formal diagnosis of MCI, 9,10 by, similarly describing variability in the driving capabilities of people attending a real‐world driving fitness assessment clinic due to cognitive concerns characteristic of MCI.…”

Section: Discussionmentioning

confidence: 99%

“…Studies examining driving safety in simulator 7 or real‐life settings 8 have found that people with MCI demonstrate minor driving difficulties which have minimal impact on safety. Recent studies examining the outcome of on‐road assessment, the predominant approach to informing licensing recommendations in practice, demonstrate variability in performance, with fail rates of 17%–58% in people with MCI compared with 7%–29% of controls 9,10 . However, as these studies were conducted in research contexts, with formal MCI diagnostic criteria, the extent to which they can generalise to clinical settings, where driving safety concerns may exist due to cognitive impairment characteristic of MCI, not a formal diagnosis, is limited.…”

Section: Introductionmentioning

confidence: 99%

Mild cognitive impairment and fitness to drive: An audit of practice in a driving specialist clinic in Australia

et al. 2021

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Objective: To describe current practice and outcomes relating to fitness to drive for people with mild cognitive impairment (MCI) attending a specialist driving clinic. Methods:Retrospective medical record audit from a driving fitness assessment clinic at a tertiary medical centre, South Australia, from 2015 to 2019.Results: Of 100 notes audited, n = 40 had a documented diagnosis of MCI and n = 60 had subjective cognitive concerns characteristic of MCI. Participants mean age was 80.0 years (SD 6.7), and mean Mini-Mental State Examination score was 26.1 (SD 2.1). Medical practitioners completed a comprehensive initial assessment relating to medical fitness to drive, considering scores from a cognitive assessment battery and non-cognitive factors (driving history, current driving needs, vision, physical abilities and collateral from family). After the initial assessment, most participants (84%) were referred for a practical on-road assessment, before receiving a final driving recommendation. Over half of participants continued driving (51%), most with conditions, while 35% ceased driving. Outcomes for the remaining 14% are unknown as we were unable to determine whether the practical assessment (11%) or lessons (3%) were completed. Conclusions:Driving outcomes for people with MCI with questionable driving capabilities are variable, with both cognitive and non-cognitive factors important in guiding medical fitness to drive recommendations. There is a need for more driving clinics to provide in-depth assessment for people with MCI who demonstrate uncertain driving capabilities and improved support for decision-making in other non-driving specialist settings.

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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

Cited by 18 publications

References 43 publications

Strong evidence for age as the single most dominant predictor of medically supervised driving test—mini mental status test outcomes provide only weak but significant moderate additional predictive value

Strong evidence for age as the single most dominant predictor of medically supervised driving test—mini mental status test outcomes provide only weak but significant moderate additional predictive value

The Effect of Prior Knowledge of Color on Behavioral Responses and Event-Related Potentials During Go/No-go Task

Mild cognitive impairment and fitness to drive: An audit of practice in a driving specialist clinic in Australia

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