Circadian timing, drowsy driving, and health risk behavior in adolescent drivers.

Keating, Daniel; Huntley, Edward; Arendt, J. Todd; Simons-Morton, Bruce · 2016 · ROSA P / Center for Advancing Transportation Leadership and Safety (ATLAS Center)

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Summary

This study investigates the relationship between circadian timing, sleep patterns, and drowsy driving among adolescent drivers, aiming to understand mechanisms contributing to this prevalent health-risk behavior. The research is motivated by the high rate of motor-vehicle crashes among teens, which are often attributed to driver error. The authors propose that a developmental maturity mismatch (DMM)—where reward-seeking neural systems mature faster than cognitive control systems—interacts with circadian factors like chronotype and circadian misalignment to increase vulnerability to behavioral misadventure. Specifically, the study seeks to characterize how chronotype, circadian misalignment, and sleep duration influence drowsy driving and other risky driving behaviors in novice drivers. The researchers utilized data from the Adolescent Health Risk Behavior (AHRB) study, a large-scale cross-sectional survey of 2,017 10th and 12th-grade students recruited from public high schools in southeastern Michigan. Participants completed computer-administered surveys over two consecutive days. Day one assessed psychosocial constructs, including impulsivity (using the Barratt Impulsiveness Scale-Brief) and sensation seeking (using the Brief Sensation Seeking Scale), as well as self-reported health-risk behaviors in the past 12 months. Day two included cognitive tasks, though those data were not used in this specific analysis. Circadian and sleep parameters were measured using the Munich ChronoType Questionnaire, which estimated chronotype (mid-sleep on free days corrected for sleep debt) and circadian misalignment (social jetlag). The primary outcome was the frequency of drowsy driving episodes. Results indicated that 30.5% of participants reported at least one instance of drowsy driving in the past year. While drowsy driving was positively correlated with other risky behaviors, such as distracted driving and driving under the influence, the expected associations with specific circadian factors were not observed. Chronotype and circadian misalignment showed no significant correlation with drowsy driving frequency. However, insufficient sleep was significantly associated with higher frequencies of drowsy driving. An ordinal regression model identified three significant predictors of drowsy driving: sensation seeking, insufficient sleep, and grade level (with 12th graders reporting higher frequencies than 10th graders). Impulsivity was not a significant predictor in this model. The findings suggest that while circadian timing markers like chronotype did not directly predict drowsy driving in this sample, insufficient sleep and high sensation seeking are critical risk factors. The results support the hypothesis that adolescents are vulnerable to acting on sensation-seeking tendencies, which can lead to behavioral misadventure, including driving while drowsy. The study highlights the importance of addressing sleep insufficiency and sensation-seeking traits in preventive interventions for adolescent drivers, rather than focusing solely on circadian phase preferences. These insights contribute to understanding the multifactorial nature of teen driving risks, combining developmental, psychosocial, and biological elements.

Key finding

Sensation seeking, insufficient sleep, and grade level significantly predicted drowsy driving frequency among adolescent drivers, while circadian misalignment and impulsivity did not.

Methodology

survey

Sample size: 2017

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• circadian factors
• shift work driving
• sleep deprivation
• drowsiness
• novice drivers
• passenger effects

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: physiological data