Analyzing Predictors Of Drinking And Driving Among Gender Cohorts Within A College Sample
Keywords
Driving under the influence; Gender differences; Low self-control; Social learning
Abstract
The current study focuses on predominant predictors associated with men’s and women’s engagement in driving under the influence (DUI) in an attempt to determine whether gender-specific interventions would be more affective at reducing impaired vehicle operation. A male-only subsample (n = 863) and a female-only subsample (n = 975) from a survey administered at a large Southeastern university containing self-reported measures of DUI were used to evaluate gender differences in motivations and correlates of DUI behavior. A series of logistic regressions containing indicators drawn from theories of deviant behavior (e.g., Akers’ social learning theory (SLT) and Gottfredson and Hirshi’s low self-control (LSC) theory) yield results indicating that differential association and imitation, both factors associated with SLT, are significant predictors for both gender cohorts’ DUI behavior. Low self- control was a significant predictor within female-only models, but not the final male-only models. This suggests that peer associations and modeling may be targets of intervention generally, but that, as it relates to DUIs, women may particularly benefit from programs focused at limiting impulsivity and risk-taking behavior as these are components of Gottfredson and Hirschi’s LSC construct.
Publication Date
12-1-2018
Publication Title
American Journal of Criminal Justice
Volume
43
Issue
4
Number of Pages
754-767
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s12103-017-9431-5
Copyright Status
Unknown
Socpus ID
85039717580 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85039717580
STARS Citation
Hoyle, Justin; Miller, Bryan Lee; Stogner, John M.; Posick, Chad; and Blackwell, Brenda Sims, "Analyzing Predictors Of Drinking And Driving Among Gender Cohorts Within A College Sample" (2018). Scopus Export 2015-2019. 10296.
https://stars.library.ucf.edu/scopus2015/10296