Retrospective analysis of driving risk among teens and adults with various daytime drowsiness levels using the Strategic Highway Research Program 2
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Despite the fact that persons 1620 made up 5.7% of licensed drivers in 2014, 9% of fatal victims from motor vehicle crashes in the same year were teenagers. An analysis of behavioral disparities between teenagers and adults can help identify unsafe driving behaviors and shed light on what about teenage driving leads to adverse outcomes. The Strategic Highway Research Program 2 (SHRP2) driving database offers a chance to explore driving patterns on a scope and scale not normally studied in small naturalistic studies. I obtained a subset of the SHRP2 dataset, and quantified driving and sleepiness risk using self-reported measures of driving histories in conjunction with The Epworth Sleepiness Scale (ESS). Multiple imputation techniques were used to predict responses for participants who left one or more questions blank on the Epworth Questionnaire. A logistic regression was performed to predict driving risk using age, sleepiness, and other covariates. Among teenagers who were considered high risk on ESS, 15.7% were risky drivers; among adults who were considered high risk on ESS, 18.2% were risky drivers. The data failed to show a statistically significant difference in the distribution of adverse outcomes across age groups when stratified by sleepiness; however, I maintained the main effects of these terms in the final model because their slopes were significantly different from zero. On a larger scale, the public health implications of these results demonstrate the need for more research analyzing the source of driving risk disparities among teens and adults.
Franklin and Marshall College Archives, Undergraduate Honors Thesis 2017
- F&M Theses Collection