Personality and behavioral predictors of traffic accidents: testing a contextual mediated model.

A contextual mediated model was proposed to distinguish the distal (i.e. personality factors) and proximal (i.e. aberrant driving behaviors) factors in predicting traffic accident involvement. Turkish professional drivers (N=295) answered a questionnaire including various measures of personality factors, driver behaviors, and accident history. Results of the latent variable analysis with LISREL indicated that latent variables in the distal context (i.e. psychological symptoms, sensation seeking, and aggression) predicted at least one of the proximal elements (i.e. aberrant behaviors, dysfunctional drinking, and preferred speed) with relatively high path coefficients. While aberrant driver behaviors yielded a direct effect on accident involvement, psychological symptoms yielded an indirect effect mediated by driver behaviors. Further analyses revealed that personality factors had an impact on road accidents via their effects on actual driving-related behaviors although the path coefficients in predicting accidents were relatively weaker than those predicting risky driving behaviors and habits. Results were discussed considering the implications for classifying the accident correlates in a contextual framework and binominal-poisson distribution of self-reported accidents.