The objective of this study was to determine how accurately teens can report miles driven. Participants were 118 drivers in Connecticut (average age 17(1/2) years; average time licensed 11 months). Half had their own vehicle; half shared family vehicles. Teens completed a telephone survey about their preceding week's driving, then completed a daily trip log for the next week and a second survey about the details of the logged week's trips and miles. Teens with their own vehicle provided odometer readings. Summing the miles for every trip was generally consistent with estimates from odometer readings. Overall mileage estimates were 20-30% lower than those from trip-by-trip listings, except for very low estimates for the first week by teens who shared vehicles. The results indicate that single overall estimates frequently understate total miles driven, but that prompted reviews of each trip can provide valid and detailed information.
Implemented January 1, 1998, Minnesota's high-BAC law mandates more severe administrative pre-conviction penalties and more severe post-conviction penalties for offenses with BACs > or = 0.20%. Most notably, the law provides for the administrative impoundment of the license plate of first-time DWI offenders with BACs > or = 0.20. During the three years after the law took effect, a large majority of first-time and repeat offenders with BACs > or = 0.20% did, in fact, receive high-BAC administrative dispositions and/or high-BAC court convictions, which carried more severe penalties. For example, in 1998 85.6% of first offenders with BACs > or = 0.20% received a high-BAC administrative disposition and/or a high-BAC court conviction; 65.0% received both high-BAC administrative and high-BAC court dispositions. The proportion of high-BAC first-time offenders who received the statutory high-BAC dispositions declined from 1998 to 1999 and 2000. Based on survival analysis, the one-year recidivism rate among first offenders arrested in 1998 with BACs > or = 0.20% was significantly lower than for offenders with BACs 0.17-0.19% (who also had relatively high BACs but were not subject to enhanced sanctions), after controlling for age and gender. There were similar, but not significant, results for first offenders arrested in 1999.
A substantial portion of the U.S. population fails to regularly use their safety belts. The explanations for the differential belt use have addressed, for example, socioeconomics, state law, attitudes, and perceived likelihood of being ticketed. The current analyses create predictive models of safety belt use. Using NHTSA's Motor Vehicle Occupant Safety Surveys (Years 1998 and 2000; N = 9577), variables related to belt use were entered into backward stepwise logistic regressions to produce two predictive models (Demographic and Attitudinal) of safety belt use (Always versus Not always). The results indicated that belt use is a complicated issue as there were several interactions between variables. The Demographic predictive model contained main effects for, law types, socioeconomics, population density, a gender-law type interaction, and a three-way interaction between age, marital status, and vehicle type. The Attitudinal model included perceived effectiveness of the belt, fatalistic attitudes, and an interaction between perceived effectiveness of the belt and perceived risk of being ticketed. These models survived a multinomial logistic regression when belt use was parsed into three categories (Always, Part-time, and Infrequent). In addition to variables that affect belt use, the results suggested that the structure of "belt use" as a psychological/behavioral construct is more complicated than once thought. Specifically, a dichotomous breakdown of belt use (Always and Not always) oversimplifies the construct because the predictor factors sometimes affect "part-time" belt users differently than "infrequent" belt users (compared to "full-time" users). Many of the factors included in the models have been previously shown to impact belt use, but the interaction effects--indicating a more complicated relationship between these variables than previously suggested--may contribute to a better understanding of safety belt use.
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