Utilizing quasi-induced exposure methodology to identify high-risk drivers
Author(s): Curry, Allison E.; Metzger, Kristina; Joyce, Nina; Foss, Robert
Publication Date: 11/4/2019
Address: Philadelphia, Pennsylvania
Abstract: Although analyses of crash data have advanced our understanding of motor vehiclecrashes, the vast majority of studies are plagued by an inability to account for driving exposure the extent towhich drivers actually drive and are thus at risk for a crash. As a result, most studies have been unable tovalidly compare crash rates between driver groups or measure changes in rates within individuals over time. Inaddition, we do not have high-quality methods to estimate young drivers exposure to (i.e., frequency ofengagement in) high-risk driving behaviors. To address these two critical gaps, we aimed to establish a costefficientand highly generalizable Quasi Induced Exposure (QIE)-based method that can: (1) identify specific teendriver groups who spend more time driving in high-risk conditions and (2) account for differences in time at risk when estimating teen driver crash risk.
Event: American Public Health Association's 2019 Annual Meeting and Expo