Published in

Elsevier, Accident Analysis & Prevention, (54), p. 73-80

DOI: 10.1016/j.aap.2013.02.011

Links

Tools

Export citation

Search in Google Scholar

How reinforcement sensitivity and perceived risk influence young drivers’ reported engagement in risky driving behaviors

Journal article published in 2013 by Emma Louise Harbeck ORCID, A. Ian Glendon
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Gray’s reinforcement sensitivity theory (RST), implementing Carver and White’s behavior inhibition system (BIS) and behavior approach system (BAS) scales, was used to predict reported engagement in 10 risky driving behaviors: speeding (2 levels), driving under the influence of alcohol, racing other vehicles, cell phone use (hand-held and hands free), tailgating, unsafe overtaking, driving while fatigued, and not wearing a seatbelt. Participants were 165 young male and female (n = 101) drivers aged 17-25 years who held a valid Australian driver’s license. Effects of the explanatory variables and specific risk perceptions upon engagement in the reported risky driving behaviors were examined using SEM analyses. Also of interest was whether perceived risk mediated the relationship between the personality variables and reported engagement in risky driving behaviors. RST variables, negative reactivity, reward responsiveness and fun seeking, accounted for unique variance in young drivers’ perceived risk. Reward responsiveness and perceived risk accounted for unique variance in young drivers’ reported engagement in risky driving behaviors. Negative reactivity was completely mediated by perceived risk in its negative relationship with reported engagement. To better understand driving related risk decision making, future research could usefully incorporate drivers’ motivation systems. This has the potential to lead to more tailored approaches to identifying risk-prone drivers and provide information for the development and implementation of media campaigns and educational programs.