title: Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program.
abstract: BACKGROUND
  This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).
  
  
  METHODS
  Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.
  
  
  RESULTS
  There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.
  
  
  CONCLUSIONS
  Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers' gender and age, for improving driving behaviors.
authors.affiliation: weizhang1217@gmail.com
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.forename: Konstantina
authors.initials: K
authors.lastname: Gkritza
authors.forename: Nir
authors.initials: N
authors.lastname: Keren
authors.forename: Shashi
authors.initials: S
authors.lastname: Nambisan
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000328:Adult; D000367:Age Factors; D001334:Automobile Driving / Q000331:legislation & jurisprudence / Q000592:standards* / Q000706:statistics & numerical data; D001336:Automobiles / Q000706:statistics & numerical data*; D016009:Chi-Square Distribution; D004521:Educational Measurement; D004522:Educational Status; D005260:Female; D006801:Humans; D007484:Iowa; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015397:Program Evaluation / Q000706:statistics & numerical data*; D012737:Sex Factors