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Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health.
Stern, Hal S; Blower, Daniel; Cohen, Michael L; Czeisler, Charles A; Dinges, David F; Greenhouse, Joel B; Guo, Feng; Hanowski, Richard J; Hartenbaum, Natalie P; Krueger, Gerald P; Mallis, Melissa M; Pain, Richard F; Rizzo, Matthew; Sinha, Esha; Small, Dylan S; Stuart, Elizabeth A; Wegman, David H.
Affiliation
  • Stern HS; Department of Statistics, University of California, Irvine, CA 92697, United States. Electronic address: sternh@uci.edu.
  • Blower D; University of Michigan Transportation Research Institute (Retired), 2901 Baxter Road, Ann Arbor, MI 48109, United States. Electronic address: dfblower@umich.edu.
  • Cohen ML; Committee on National Statistics, National Academies of Sciences, Engineering, and Medicine, 500 5th St NW, Washington, DC 20001, United States. Electronic address: mcohen@nas.edu.
  • Czeisler CA; Division of Sleep Medicine, Harvard Medical School, And Brigham and Women's Hospital, Boston, MA 02115, United States. Electronic address: charles_czeisler@hms.harvard.edu.
  • Dinges DF; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States. Electronic address: dinges@pennmedicine.upenn.edu.
  • Greenhouse JB; Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, United States. Electronic address: joel@stat.cmu.edu.
  • Guo F; Department of Statistics, Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061, United States. Electronic address: feng.guo@vt.edu.
  • Hanowski RJ; Center for Truck and Bus Safety, Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061, United States. Electronic address: rhanowski@vtti.vt.edu.
  • Hartenbaum NP; Occumedix, Inc., P.O. Box 197, Dresher, PA 19025, United States. Electronic address: occumedix@comcast.net.
  • Krueger GP; Krueger Ergonomics Consultants, 4105 Komes Court, Alexandria, VA 22306, United States. Electronic address: jerrykrueg@aol.com.
  • Mallis MM; M3 Alertness Management LLC, 11 Dakota Drive, Dallas, PA 18612, United States. Electronic address: mmallis@m3alertness.com.
  • Pain RF; 11401 Lakin Place, Oakton, VA 22124, United States. Electronic address: rpain@verizon.net.
  • Rizzo M; Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, United States. Electronic address: matthew.rizzo@unmc.edu.
  • Sinha E; Committee on National Statistics, National Academies of Sciences, Engineering, and Medicine, 500 5th St NW, Washington, DC 20001, United States. Electronic address: esinha@nas.edu.
  • Small DS; Department of Statistics, University of Pennsylvania, 400 Huntsman Hall, 3730 Walnut St., Philadelphia, PA 19104, United States. Electronic address: dsmall@wharton.upenn.edu.
  • Stuart EA; Departments of Mental Health, Biostatistics and Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, United States. Electronic address: estuart@jhu.edu.
  • Wegman DH; Department of Work Environment, School of Health and Environment, University of Massachusetts, Lowell, MA 01854, United States. Electronic address: david_wegman@uml.edu.
Accid Anal Prev ; 126: 37-42, 2019 May.
Article in En | MEDLINE | ID: mdl-29530304
ABSTRACT
This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Automobile Driving / Fatigue / Occupational Diseases Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Accid Anal Prev Year: 2019 Document type: Article
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Automobile Driving / Fatigue / Occupational Diseases Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Accid Anal Prev Year: 2019 Document type: Article