Evidence map›Paper›PMID 26954762›Full record

ArticleAccident; analysis and prevention2016

The influence of daily sleep patterns of commercial truck drivers on driving performance.

Guang Xiang Chen, Youjia Fang, Feng Guo, Richard J Hanowski

Open access · greenAbstract read
In one paragraph

Article in Accident; analysis and prevention, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
10.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 93 citations in OpenAlex.

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  8. Article
  9. Association between sleep disturbance and occupational injury among Korean employees.Annals of occupational and environmental medicine · 2021
    Article
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  15. Shift Work and Sleep: Medical Implications and Management.Sleep medicine and disorders : international journal · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Guang Xiang ChenCenters for Disease Control and Prevention, National Institute for Occupational Safety and Health, Division of Safety Research, 1095 Willowdale Road, Morgantown, WV 26505, United States. Electronic address: gchen@cdc.gov.
Youjia FangVirginia Tech Transportation Institute, Virginia Tech, 3500 Transportation Research Dr., Blacksburg, VA 24061, United States. Electronic address: youjia@vt.edu.
Feng GuoVirginia Tech Transportation Institute, Virginia Tech, 3500 Transportation Research Dr., Blacksburg, VA 24061, United States; Department of Statistics, Virginia Tech, 406A Hutcheson Hall, Blacksburg, VA 24061, United States. Electronic address: feng.guo@vt.edu.
Richard J HanowskiVirginia Tech Transportation Institute, Virginia Tech, 3500 Transportation Research Dr., Blacksburg, VA 24061, United States. Electronic address: RHanowski@vtti.vt.edu.
Virginia Tech · USNational Institute for Occupational Safety and Health · USVirginia Tech Transportation Institute

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

Fatigued and drowsy driving has been found to be a major cause of truck crashes. Lack of sleep is the number one cause of fatigue and drowsiness. However, there are limited data on the sleep patterns (sleep duration, sleep percentage in the duration of non-work period, and the time when sleep occurred) of truck drivers in non-work periods and the impact on driving performance. This paper examined sleep patterns of 96 commercial truck drivers during non-work periods and evaluated the influence these sleep patterns had on truck driving performance. Data were from the Naturalistic Truck Driving Study. Each driver participated in the study for approximately four weeks. A shift was defined as a non-work period followed by a work period. A total of 1397 shifts were identified. Four distinct sleep patterns were identified based on sleep duration, sleep start/end point in a non-work period, and the percentage of sleep with reference to the duration of non-work period. Driving performance was measured by safety-critical events, which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Negative binomial regression was used to evaluate the association between the sleep patterns and driving performance, adjusted for driver demographic information. The results showed that the sleep pattern with the highest safety-critical event rate was associated with shorter sleep, sleep in the early stage of a non-work period, and less sleep between 1 a.m. and 5 a.m. This study also found that male drivers, with fewer years of commercial vehicle driving experience and higher body mass index, were associated with deteriorated driving performance and increased driving risk. The results of this study could inform hours-of-service policy-making and benefit safety management in the trucking industry.

Indexed as

Automobile DrivingSleepAccidents, TrafficAdultAgedBinomial DistributionCluster AnalysisFatigueFemaleHumansMaleMiddle AgedMotor VehiclesSafetySafety ManagementSleep StagesCluster analysisNaturalistic driving studyNegative binomial regressionSleep patternTruck driver safety

Identifiers

PMID26954762
PMCPMC4828254
OpenAlexW2291687153

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.