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Identifying variables that predict falling asleep at the wheel among long-haul truck drivers.

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)379-385
Number of pages7
JournalAAOHN journal : official journal of the American Association of Occupational Health Nurses
Volume56
Issue number9
DOIs
StatePublished - 2008

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Nursing (miscellaneous)

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