Predictability of clinical assessments for driving performance

Abstract

PROBLEM: As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. METHOD: Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors ( RESULTS: Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. DISCUSSION: The domains of vision, cognitive, and motor performance were represented in the predictive model. SUMMARY: Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. IMPACT ON INDUSTRY: By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers