Abstract

Certain driving errors are predictive of crashes, but whether the type of errors evaluated during on-road assessment is similar to traffic violations that are associated with crashes is unknown. Using the crash data of 5,345 older drivers and expert reviewers, we constructed a violation-to-error classification based on rater agreement. We examined the effects of predictor variables on crash-related injuries by risk probability using logistic regression. Drivers’ mean age was 76.08 (standard deviation = 7.10); 45.7% were women. Of drivers, 44.6% sustained crash-related injuries, and female drivers had a higher injury probability (44%) than male drivers (29%). Lane maintenance, yielding, and gap acceptance errors predicted crash-related injuries with almost 50% probability; speed regulation (34%), vehicle positioning (25%), and adjustment-to-stimuli (21%) errors predicted crash-related injuries to a lesser degree. We suggest injury prevention strategies for clinicians and researchers to consider for older drivers, especially older women.

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