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J Safety Res ; 78: 270-275, 2021 09.
Article in English | MEDLINE | ID: mdl-34399923

ABSTRACT

OBJECTIVE: Our study investigated risk factors in survival among a subpopulation of drivers in North Dakota's 24/7 Sobriety Program. Participants mandated for a second driving-under-the-influence of alcohol (DUI) arrest were studied for a three-year interval that commenced with the start date for a 360-day enrollment. METHOD: A Stratified Cox regression model was developed to compute the hazard ratios for survival. A subsequent DUI-related offense as event of interest. Relation to the explanatory variable array that could be construed from administrative records were investigated. RESULTS: Older drivers were 6.31 times more likely to reoffend than the younger driver cohort of 18-35-years. The survival curve slope showed the fastest decline in the 361-day to 730-day interval. Neither gender nor residence region was a significant predictor in DUI reoffense over the three-year monitoring interval. Preliminary work suggests reoffense was more likely if an individual had program history prior to this court mandated 360-day term in the 24/7 Sobriety Program for a second DUI. The program experience finding was unexpected but could not be studied in greater detail due to data and resource limitations. CONCLUSIONS: Administrative records access created a novel opportunity to explore an evolving impaired driving prevention strategy that has shown early promise. Individual driver survival in and after the 24/7 Sobriety Program was studied for three-years. Findings show age, post-program time interval, and possibly program history as areas to explore to improve survival rates. Driver DUI offense were most common shortly after program completion. Although limited to a single state, findings increase knowledge for refining strategies designed to impact driver subpopulations at higher risk for reoffense.


Subject(s)
Automobile Driving , Driving Under the Influence , Ethanol , Humans , Law Enforcement , Proportional Hazards Models , Risk Factors
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