Related Experiment Video
Updated: Jul 1, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Identifying variables that predict falling asleep at the wheel among long-haul truck drivers
Karen Heaton1, Steven Browning, Debra Anderson
1University of Alabama at Birmingham School of Nursing, Birmingham, AL, USA.
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.
Related Concept Videos
Sleepwalking and Sleep Talking
Factors that increase the likelihood of sleepwalking include sleep deprivation and alcohol consumption. Contrary to common beliefs, it is safe...
Narcolepsy
Insufficient Sleep and Sleep Deprivation
Sleep deprivation is a more severe form of sleep loss...
Substance Use Disorders Affecting Sleep
Understanding the concepts of physical dependence,...
Insomnia
Multiple factors contribute...
Cause and Effect

