Crime and risky behavior in traffic: An example of cross-situational consistency

This study looks at the relationship between risky behavior in traffic and criminal behavior Analyses were based on a random sample of 1531 persons in volved in traffic accidents. The data came from two independent police data bases: the accident registration system and a national database on offendin g. Descriptions of the accidents by the police were used to identify indivi duals who had displayed risky traffic behavior contributing to or causing a n accident; evidence of offending was based on a register of contacts with police. This methodology meant that there was no self-selection bias or sel f-report bias as may occur in survey data. Exposure to traffic accident ris k was controlled for Log-linear analyses, controlling for gender and age, r evealed that persons who displayed risky traffic behavior leading to the ac cident had an odds ratio of 2.6 for having a police record for violent crim e; of 2.5 for vandalism, 1.5 for property crime, and 5.3 for having been in volved in traffic crime. The results were consistent with the idea of a com mon factor underlying risky behavior in traffic and criminal behavior This underlying trait may represent a general disregard for the long term advers e consequences of one's actions and could be labeled risk-taking, impulsive ness, or lack of self-control.