Evaluating Older Drivers' Skills

Chaudhary, Neil K.; Ledingham, Katherine A.; Eby, David W.; Molnar, Lisa J. · 2013 · ROSA P / United States. National Highway Traffic Safety Administration. Office of Behavioral Safety Research

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Summary

This report, commissioned by the National Highway Traffic Safety Administration (NHTSA), addresses the challenge of identifying older drivers at high risk for fatal crashes without relying on age-based license restrictions. While older drivers face increased crash risks, particularly after age 75, most maintain unimpaired driving performance. Consequently, blanket age restrictions are deemed problematic and potentially harmful to older adults' mobility and quality of life. The study aims to evaluate the strengths and weaknesses of various specialist-administered screening and assessment tools, self-screening instruments, and training methods to help Departments of Motor Vehicles (DMVs) and clinicians identify at-risk individuals based on specific functional deficits rather than age alone. The research methodology involved a comprehensive literature review conducted by the University of Michigan Transportation Research Institute (UMTRI), covering databases such as MEDLINE, PSYCHINFO, and TRISonline. The review analyzed the relationship between specific measures and driving outcomes, including crash records, on-road performance, simulator data, and traffic violations. Instruments were categorized into five domains: cognitive measures (visuospatial ability, executive function, selective attention, memory, and mental status), education and training programs, motor measures (range of motion, reaction time, and strength), self-screening tools, and vision assessments. Following the literature review, an expert panel convened in April 2008 to discuss the utility, administration settings, and strengths/weaknesses of these tools. Additionally, a second group of experts completed an online survey to rate the instruments' predictive validity, research priorities, and appropriateness for various settings, such as DMVs or clinical environments. The findings indicate that while numerous instruments show correlations with driving performance, almost all require additional research to definitively document their efficacy in identifying risky drivers. Specific cognitive measures, such as the Trail Making Test (Part B) and the Rey-Osterreith Complex Figures Test, demonstrated significant relationships with crash risk and on-road performance in various studies. However, expert panels noted that many tools are difficult to administer or score, limiting their utility in DMV settings. For instance, the Rey-Osterreith test was considered useful for clinical assessment but impractical for screening due to its complexity. Conversely, simpler tests like the Embedded Figures Test were viewed as easier to administer but lacked sufficient research support for conclusive use. The experts emphasized distinguishing between screening tools, which identify the need for further evaluation, and assessment tools, which determine specific licensing actions. The significance of this report lies in its role as a guide for future research and policy decisions regarding older driver safety. By highlighting tools that are commonly used but inadequately evaluated, as well as those with demonstrated validity, the report helps prioritize research efforts to validate these instruments. It provides a framework for clinicians and licensing agencies to select appropriate measures for identifying unsafe drivers, thereby promoting a shift from age-based restrictions to risk-based evaluations. The report underscores the need for more robust evidence linking specific functional assessments to driving outcomes to ensure that restrictions are applied only to those who genuinely pose a safety risk.

Key finding

Experts indicated that nearly all the assessment instruments reviewed require additional research to document their efficacy in identifying risky drivers.

Methodology

review

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• fitness to drive assessment
• mci dementia driving
• older driver retraining
• cognitive impairment
• useful field of view
• cognitive capacity variation

Information type

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• Methodological Resource: validation psychometrics, measurement protocol
• Theoretical Contribution: computational model