Predicting at-fault car accidents of older drivers.
Considerable research shows car accidents are difficult to predict using screening tests. The objective of this exploratory study is to determine whether detailed accident analysis taking into account the specific accident type might enhance the predictive power of a standardised road test and a set of selected neuropsychological tests. Moreover, this study addresses the validity and reliability of performance-based driving evaluation. The sample consisted of 84 older drivers between 65 and 96 years of age who were referred for a fitness-to-drive evaluation. Using discriminant analyses, the subjects were classified as drivers with and without at-fault accidents. We compared the accuracy of neuropsychological tests and a road test for postdicting all accidents, accidents classified into two categories and accidents classified into four different categories. The percentages of correctly classified subject were highest at the level of the most detailed classification. These results suggest that, although accident prediction is difficult, the predictability of car accidents by neurocognitive measurements and a road test increases when the kind of accident is specified.
De Raedt
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Department of Developmental and Lifespan Psychology, Free University of Brussels, Belgium. Rudi.De.Raedt@vub.ac.be
Ponjaert-Kristoffersen
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D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D001333:Automobile Driver Examination; D001530:Belgium; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D009483:Neuropsychological Tests; D018570:Risk Assessment; D012449:Safety