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Traffic Inj Prev ; 13(5): 468-75, 2012 Sep.
Article in English | MEDLINE | ID: mdl-22931176

ABSTRACT

OBJECTIVE: Distracted driving is a known contributor to traffic accidents, and many states have banned texting while driving. However, little is known about the potential accident risk of other common activities while driving, such as eating. The objective of the current study was to examine the adverse impact of eating/drinking behavior relative to texting and nondistracted behaviors on a simulated driving task. METHODS: A total of 186 participants were recruited from undergraduate psychology courses over 2 semesters at Kent State University. We utilized the Kent Multidimensional Assessment Driving Simulation (K-MADS) to compare simulated driving performance among participants randomly assigned to texting (N = 45), eating (N = 45), and control (N = 96) conditions. Multivariate analyses of variance (MANOVA) were conducted to examine between-group differences on simulated driving indices. RESULTS: MANOVA analyses indicated that groups differed in simulated driving performance, F(14, 366) = 7.70, P < .001. Both texting and eating produced impaired driving performance relative to controls, though these behaviors had approximately equal effect. Specifically, both texting and eating groups had more collisions, pedestrian strikes, and center line crossings than controls. In addition, the texting group had more road edge excursions than either eating or control participants and the eating group missed more stop signs than controls. CONCLUSIONS: These findings suggest that both texting and eating are associated with poorer simulated driving performance. Future work is needed to determine whether these findings generalize to real-world driving and the development of strategies to reduce distracted driving.


Subject(s)
Accidents, Traffic/statistics & numerical data , Attention , Automobile Driving/psychology , Eating , Task Performance and Analysis , Text Messaging/statistics & numerical data , Adolescent , Computer Simulation , Female , Humans , Male , Multivariate Analysis , Risk Factors , Young Adult
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