The relationship between cognitive/neuropsychological factors and car driving performance in older adults.
OBJECTIVE
Because demographic changes produce a society with a growing number of older people, seniors constitute the fastest growing segment of car drivers. The objective of this research project was to identify cognitive factors related to driving problems in older adults. A top-down approach has been used, testing theory-driven hypotheses.


METHODS
Correlational study.


METHODS
Fitness-to-Drive Assessment Centre of the Belgian Road Safety Institute.


METHODS
The research sample consisted of 84 car drivers aged over 65 years, who were referred for a general fitness-to-drive evaluation.


METHODS
The relations between seven specific neuropsychological tests and self-reported accidents were investigated. Furthermore, the relations between these same tests and a road test, independently assessed using a detailed evaluation grid, were analyzed in depth. These analyses were followed by stepwise multiple regression analyses.


RESULTS
In a stepwise regression model, four neuropsychological tests could account for 64% of the variance of the score on the road test. Moreover, it could be demonstrated that specific cognitive subskills share common variance with specific real-world situations. However, neuropsychological tests could explain only 19% of the variance of self-reported at fault car accidents.


CONCLUSIONS
The initial results of this study indicate the relevance of a cognitive/neuropsychological approach to the driving ability of older people. However, the link with accident risk seems more complex. Consequently, neuropsychological screening procedures are in need of a broader perspective to prevent an overemphasis on unidimensional screening procedures focusing mainly on deficit and less on capacities for safe behavior.
De Raedt
R
R
Department of Developmental and Lifespan Psychology, Free University of Brussels, Belgium.
Ponjaert-Kristoffersen
I
I
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000368:Aged / Q000502:physiology* / Q000523:psychology*; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001333:Automobile Driver Examination; D001334:Automobile Driving / Q000523:psychology* / Q000706:statistics & numerical data*; D003071:Cognition / Q000502:physiology*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods / Q000592:standards; D009483:Neuropsychological Tests / Q000592:standards*; D011597:Psychomotor Performance; D012044:Regression Analysis; D012307:Risk Factors