Self-reported Drowsiness and Safety Outcomes While Driving After an Extended Duration Work Shift in Trainee Physicians

Anderson, Clare; Ftouni, Suzanne; Ronda, Joseph M.; Rajaratnam, Shantha M. W.; Czeisler, Charles A.; Lockley, Steven W. · 2017 · OpenAlex-citations

DOI: 10.1093/sleep/zsx195

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Summary

This study investigates the relationship between self-reported drowsiness and safety outcomes in trainee physicians driving after extended duration work shifts (EDWSs), defined as shifts lasting 24 hours or more. The research was motivated by the known increased risk of motor vehicle crashes among medical residents following marathon shifts and the ongoing debate regarding drivers’ ability to accurately self-assess their level of impairment. The authors aimed to determine if pre-drive self-reported sleepiness predicts adverse driving events, which has significant implications for legal accountability and safety interventions. The study employed a repeated-measures design involving 16 resident physicians from seven hospitals in the Boston metropolitan area. Participants provided data from 438 driving sessions, including commutes to and from both day shifts and six consecutive EDWSs. Data collection included daily logs for sleep and work hours, driving logs completed after each commute to record adverse events, and objective measures of drowsiness using infrared reflectance oculography (Johns Drowsiness Score). Self-reported sleepiness was measured using the Karolinska Sleepiness Scale (KSS) at the beginning and end of each drive. Statistical analyses included Pearson correlations, binary logistic regression, and receiver-operator characteristic curves to evaluate the predictive capacity of pre-drive KSS scores for subsequent adverse events. Results indicated that self-reported sleepiness and objective drowsiness were positively correlated and significantly elevated following EDWSs. Driving home after an EDWS was associated with more than double the self-reported adverse outcomes compared to driving to work, with odds ratios ranging from 3.32 to 5.39 for hazardous, violation, inattention, and sleep-related events, respectively. In contrast, day shifts did not show increased odds of adverse events. Predrive KSS scores predicted the number and type of adverse events in a dose-dependent manner; each one-point increase in KSS raised the odds of a sleep-related event by 2.39 times. A pre-drive KSS rating of ≥6 demonstrated 91% sensitivity and 69% specificity for predicting sleep-related adverse events. Ten near-crash events were reported, with eight occurring after EDWSs. The findings conclude that driving after an EDWS poses an avoidable and unnecessary risk to resident physicians and other road users. Crucially, the study provides evidence that drivers are aware of their drowsiness levels prior to driving, and this self-assessment accurately predicts subsequent on-road adverse events. The authors suggest that drivers should proactively evaluate their drowsiness before commencing a journey to mitigate the significant risks associated with drowsy driving, highlighting the potential for self-assessment to inform legal accountability and safety strategies.

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Topics

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• drowsiness
• shift work driving
• sleep deprivation
• truck driver fatigue
• time on task
• drowsiness detection algorithms

Information type

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• Empirical Findings: physiological data