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:
  Advertising Campaigns Attitudes Behavior College Students Drunk Drivers Impaired Drivers
• 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.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:c97aaa80d0b89a436ff5c72514c75eabce9d77f013c9e88b23a6cb9e5c328d6a
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29556/dot_29556_DS1.pdf
• File Type:
  [PDF - 916.08 KB ]