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Article
Identifying Variables That Predict Falling Asleep at the Wheel Among Long-Haul Truck Drivers
AAOHN Journal (2008)
  • Karen Heaton, University of Alabama
  • Steven R Browning, University of Kentucky
  • Debra Anderson, University of Kentucky
Abstract
Analysis of data from 843 long-haul truck drivers was conducted to determine the variables that predicted falling asleep at the wheel. Demographics, sleep-specific questions, and the Epworth Sleepiness Scale were used for analysis. More than 25% of the participants (n = 247) scored 10 or higher on the Epworth Sleepiness Scale, indicating chronic sleepiness. Eight initial predictor variables were included in the logistic regression analysis. Four of the eight original variables were retained in the final model to predict falling asleep at the wheel within the past 12 months. Four variables were retained in the final model to predict falling asleep at the wheel within the past 30 days. Screening for excessive sleepiness using the Epworth Sleepiness Scale and an extensive history of medication use should be conducted for all long-haul truck drivers.
Keywords
  • Traffic accidents,
  • Fatigue,
  • Kentucky,
  • Risk assessment,
  • Sleep disorders
Disciplines
Publication Date
September, 2008
DOI
https://doi.org/10.3928/08910162-20080901-05
Citation Information
Karen Heaton, Steven R Browning and Debra Anderson. "Identifying Variables That Predict Falling Asleep at the Wheel Among Long-Haul Truck Drivers" AAOHN Journal Vol. 56 Iss. 9 (2008) p. 379-385 ISSN: 0891-0162
Available at: http://works.bepress.com/steven_browning/11/