Investigating the decision-making processes that contribute to impaired driving.

Details

• Creators:
  Duckworth, M. P. ; Renqvist, J. G. ; Dahir, V. B.
• Corporate Creators:
  University of Nevada, Reno
• Subject/TRT Terms:
  • Impaired drivers
  • Drunk drivers
  • Behavior
  • Attitudes
  • College students
  • Advertising campaigns
• Publication/ Report Number:
  514-13-803
• Resource Type:
  Tech Report
• Geographical Coverage:
  Nevada
• Corporate Publisher:
  Nevada. Dept. of Transportation
• Abstract:
  Alcohol-impaired (AI) driving continues to cause a disproportionate number of fatalities within the college and ; young adult populations, indicating optimal prevention programs for AI driving have yet to be developed. The ; current study tested the efficacy of two theoretically- and empirically-based online video advertisements at ; reducing AI driving willingness and behavior in a sample of 108 college students at high risk for future AI ; driving. The relations of AI driving risk factors to AI driving willingness and behavior in a larger sample of 600 ; college students was also tested. Findings revealed that students who viewed either advertisement reported ; decreases in general willingness to drive after drinking, while participants who did not view an advertisement ; reported increases in general willingness to drive after drinking. While viewing an advertisement was not ; associated with decreased AI driving, study participants reported a significant decrease in AI driving overall. ; Findings revealed AI driving risk and decision-making factors to have both shared and unique relations to driving ; after “perhaps too much to drink” and driving “shortly after three or more drinks.” Findings from the current ; study provide preliminary support for the efficacy of both advertisements in reducing general willingness to drive ; after drinking within the subgroup of the college population most at risk for AI driving. Additionally, this study ; takes one of the first steps in developing an AI driving model that accounts for the influence of sociodemographic, ; dispositional, historical, and current AI driving risk factors as well as rational and emotional decision-making ; factors.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29556/dot_29556_DS1.pdf
• File Type:
  [PDF - 916.08 KB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:c97aaa80d0b89a436ff5c72514c75eabce9d77f013c9e88b23a6cb9e5c328d6a