Predictors of driving outcomes including both crash involvement and driving cessation in a prospective study of Japanese older drivers

Effect of Fitness-To-Drive and Metacognition on Road Traffic Injury Among Older Taxi Drivers: Hierarchical Modeling

Age-related cognitive and somatic motor skills changes have been linked to impaired driving abilities. Taxi drivers play an important role in providing public transportation services and security. This study aimed to examine the level of fitness-to-drive (FTD) and identify the predictors of self-reported traffic injury among the older taxi drivers. Taxi drivers 60 years and older in Bangkok and the metropolitan area were enrolled. Hierarchical regression models were carried out to examine the effects of demographics, FTD, and metacognition towards self-reported road traffic injury. Totally, 46.1% of the respondents were classified as at-risk drivers. Drivers with alcohol consumption and low risk perception toward road safety were more likely to experience road traffic injury. Regular assessment of physical and psychometric capacity among older taxi drivers could provide another empirical basis to improve public safety transport.

Non-cognitive factors associated with driving cessation among older adults: An integrative review

Exploring the factors that affect driving cessation is crucial, because sustained mobility plays an important role in successful aging. This study aimed to collect evidence on the non-cognitive factors associated with driving cessation among older adults. The method used in this study was an integrated review of published research on the factors affecting driving cessation. A comprehensive search was performed using electronic databases including PubMed, Web of Science, Scopus, CINHAL, ProQuest, EBSCO, and Google Scholar. The results revealed six main categories (physical health, psychological health, interpersonal influence, transportation support, policies, and sociodemographic characteristics) and 24 subcategories for driving cessation. Given the potentially serious consequences of driving cessation in the older adult population, exploring the predictors of driving cessation can be used to design interventions for optimizing drivers' health, rehabilitating the functional limitations that affect driving ability, creating a safer driving environment, and optimizing vehicles to meet the needs of older drivers.

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.

Characteristics of driving self-assessments and factors related to inaccurate self-assessment in Japanese older adults

Older adults are considered to decide their driving behaviors based their own assessment of their driving performance, and thus it is important that these self-assessments be accurate. Therefore, this study aimed to clarify how older drivers assess their driving performance and examine factors related to the level of inaccuracy in their self-assessments. Japanese drivers aged 70 years or older (N = 181) were asked to assess their own driving performance by questionnaire and then to drive on a public road while wearing an electronic device that measured their actual driving behaviors. They were accompanied by a driving instructor who sat in the passenger seat and assessed their driving performance. The results showed that older drivers' self-assessments were significantly higher than the experts' assessments of their driving performance. This tendency applied to all driving competencies, including overall rating, speed, and scanning. In addition, there were greater discrepancies between self-assessments and expert assessments for drivers who were rated poorly by experts compared with those who were highly rated. Drivers with a greater rating discrepancy were likely to drive faster around an intersection with a stop sign. This discrepancy was also related to a low entropy rate (low randomness in head rotation) around a signalized T-junction. These findings based on on-road driving assessments provide credible evidence of performance overestimation by older drivers. Furthermore, the results suggest that making older drivers recognize the evaluative criteria might be effective for reducing the discrepancy between self-assessments and expert assessments. It was also suggested that improving the accuracy of one's self-assessment had the potential to improve driving behaviors such as choice of speed and scanning behavior.

Assessment of cognitive screening tests as predictors of driving cessation: A prospective cohort study of a median 4-year follow-up

BACKGROUND

Assessing fitness to drive and predicting driving cessation remains a challenge for primary care physicians using standard screening procedures. The objective of this study was to prospectively evaluate the properties of neuropsychological screening tests, including the Trail Making Test (TMT), Clock Drawing Test (CDT), Montreal Cognitive Assessment (MoCA), Useful Field of View (UFOV), and Timed Up and Go (TUG) test, in predicting driving cessation for health reasons in drivers older than 70 years of age.

DESIGN AND METHODS

This prospective cohort study, with a median follow-up of 4 years for drivers of 70 years old or older with an active driving license in Switzerland, included 441 participants from a driving refresher course dedicated to volunteer senior drivers. Cases were drivers reported in the national driving registry who lost their license following a health-related accident, who were reported as unfit to drive by their physician or voluntarily ceased driving for health reasons. Survival analysis was used to measure the hazard ratio of driving cessation by adjusting for age and sex and to evaluate the predictive value of combining 3 or more positive tests in predicting driving cessation during a 4-year follow-up.

RESULTS

A total of 1738 person-years were followed-up in the cohort, with 19 (4.3%) having ceased driving for health reasons. We found that participants with a TMT-A < 54 sec and TMT-B < 150 sec at baseline had a significantly lower cumulative hazard of driving cessation in 4 years than those with slower performance (adjusted HR 3, 95% CI: 1.16-7.78, p = 0.023). Participants who performed a CDT ≥ 5 had a significantly lower cumulative hazard of driving cessation (adjusted HR 2.89, 95% CI: 1.01-7.71, p = 0.033). Similarly, an MoCA score ≥ 26, TUG test <12 sec or a UFOV of low risk showed a lower but not significant cumulative risk at a median follow-up of 4 years. When using tests as a battery, those with three or more positive tests out of five were 3.46 times more likely to cease driving (95% CI: 1.31-9.13, p = 0.012).

CONCLUSIONS

The CDT and the TMT may predict driving cessation in a statistically significant way, with a better performance than the UFOV and MoCA tests during a median 4-year follow-up. Combining tests may increase the predictability of driving cessation. Although our results are consistent with current evidence, they should be interpreted with precaution; more than 95% of the participants above the set threshold were able to continue driving for 4 years without any serious incident.

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.

The Predictors of Driving Cessation among Older Drivers in Korea

Background: As the elderly population and the number of older drivers grow, public safety concerns about traffic accidents involving older drivers are increasing. Approaches to reduce traffic accidents involving older drivers without limiting their mobility are needed. This study aimed to investigate the driving cessation (DC) rate among older Korean adults and predictors of DC based on the comprehensive mobility framework. Method: In this cross-sectional study, data from 2970 to 10,062 older adults over 65 years old from the 2017 National Survey of Elderly People were analyzed in April 2020. Multivariate logistic regression analyses were conducted to identify the predictors of DC. Results: Residential area, an environmental factor, was a strong predictor of DC (Odds Ratio (OR) 2.21, 95% Confidential Interval (CI) 1.86–2.62). Older drivers living in an area with a metro system were 2.21 more likely to stop driving than those living in an area without a metro system. Other demographic, financial, psychosocial, physical, and cognitive variables also predicted DC. Conclusion: Environmental factors were strong predictors of older adults’ DC. Therefore, political and environmental support, such as the provision of accessible public transportation, is essential to increase the DC rate among older adults to increase public safety without decreasing their mobility.

Mapping the knowledge domain of road safety studies: A scientometric analysis

As a way of obtaining a visual expression of knowledge, mapping knowledge domain (MKD) provides a vision-based analytic approach to scientometric analysis which can be used to reveal an academic community, the structure of its networks, and the dynamic development of a discipline. This study, based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles on road safety, employs the bibliometric tools VOSviewer and CitNetExplorer to create maps of author co-citation, document co-citation, citation networks, analyze the core authors and classic documents supporting road safety studies and show the citation context and development of such studies. It shows that road safety studies clustered mainly into four groups, whose we will refer to as "effects of driving psychology and behavior on road safety", "causation, frequency and injury severity analysis of road crashes", "epidemiology, assessment and prevention of road traffic injury", and "effects of driver risk factors on driver performance and road safety", respectively. Through our analysis, the core publications and their citation relationships were quickly located and explored, and "crash frequency modeling analysis" has been identified to be the core research topic in road safety studies, with spatial statistical analysis technique emerging as a frontier of this topic.