Medical Conditions and Crash Risk in Commercial Motor Vehicle (CMV) Drivers

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Alexander M. Crizzle ◽  
Ryan Toxopeus ◽  
Khrisha Alphonsus
1996 ◽  
Vol 28 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Claire Laberge-Nadeau ◽  
Georges Dionne ◽  
Urs Maag ◽  
Denise Desjardins ◽  
Charles Vanasse ◽  
...  

Author(s):  
C.D. Wylie ◽  
T. Shultz ◽  
J.C. Miller ◽  
M.M. Mitler ◽  
R.R. Mackie

2021 ◽  
Vol 11 (13) ◽  
pp. 5822
Author(s):  
Dong-Seok Shin ◽  
Byung-Yong Jeong

The shortage and aging of drivers are not problems limited to the truck industry, but are common in the broader commercial motor vehicle (CMV) industry of Korea. This study investigates the relationships between work situation, work–family conflict, depression, and work engagement of taxi, bus, and truck drivers. We extracted 512 CMV drivers from the 5th Korea Working Conditions Survey. A structural equation model (SEM) was used to investigate the impact of a work situation or work–family conflict on depression and work engagement. Results showed that 38.9% of all respondents had symptoms of depression. In the SEM, a poor work situation (standardized path coefficient = 0.250) and work–family conflict (0.117) significantly affected depression. ‘Enough time’ and ‘feeling well’ were influential variables of work situation. ‘Responsibility’ and ‘concentration’ were influential variables of work–family conflict. Additionally, depression affected work engagement (0.524). ‘Vigor’ and ‘dedication’ were influential variables of work engagement. These results show that the relationships between work situation, work–family conflict, depression, and work engagement of CMV drivers are intricately linked.


2004 ◽  
Vol 13 (2) ◽  
pp. 177-178 ◽  
Author(s):  
Nathaniel S. Marshall ◽  
Warren Bolger ◽  
Philippa H. Gander

2021 ◽  
Vol 23 ◽  
pp. 101286
Author(s):  
Sjaan Koppel ◽  
Marilyn Di Stefano ◽  
Bleydy Dimech-Betancourt ◽  
Mohammed Aburumman ◽  
Rachel Osborne ◽  
...  

2017 ◽  
pp. 141-156 ◽  
Author(s):  
Richard J. Hanowski ◽  
Rebecca L. Olson ◽  
Jeffery S. Hickman ◽  
Joseph Bocanegra

2009 ◽  
Vol 7 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Mike Males

Teenagers’ high rates of motor vehicle crashes, accounting for 40% of external deaths among 16-19 yearolds, have been ascribed largely to inherent “adolescent risk-taking” and developmental hazards. However, the fact that compared to adults 25 and older, teenagers are twice as likely to live in poverty and low-income areas, risk factors for many types of violent death, has not been assessed. This paper uses Fatality Analysis Reporting System data on 65,173 fatal motor vehicle crashes by drivers in California’s 35 most populous counties for 1994-2007 to analyze fatal crash involvements per 100 million miles driven by driver age, county, poverty status, and 15 other traffic safety-related variables. Fatal crash rates were substantially higher for every driver age group in poorer counties than in richer ones. Multivariate regression found socioeconomic factors, led by the low levels of licensing and high unemployment rates prevalent in low-income areas, were associated with nearly 60% of the variance in motor vehicle crash risks, compared to 3% associated with driver age. The strong association between fatal crash risk and poverty, especially for young drivers who are concentrated in high-poverty brackets and low-income areas, suggests that factors related to poorer environments constitute a major traffic safety risk requiring serious attention.


Author(s):  
Yi Wang ◽  
Christopher M. Monsere ◽  
Chen Chen ◽  
Haizhong Wang

Methods for identifying and prioritizing high-crash locations for safety improvements are generally crash-based. There are fewer reported crashes involving non-motorized users and, in most states, reported crashes must involve a motor vehicle. This means that minor, non-injury events are not reported and those crashes that are reported tend to be more severe. Selecting projects based only on crash performance is sometimes limiting for these crash types and predicting where these crashes will occur next is also a challenging task. An alternative to crash-based selection is to develop risk-based criteria and methods. This paper presents the results of a research effort to develop a risk-scoring method with weights derived from data for use in project screening and selection in Oregon. To develop the risk model, data were collected from 188 segments and 184 intersections randomly selected on both state and non-state roadways. Geometric, land use, volume, and crash data were collected from Google Earth, EPA’s Smart Location Database, and the Oregon Department of Transportation crash database from 2009 to 2013. The sample included 213 bicycle and pedestrian crashes on the segments and 238 at intersections. Logistic regression models were developed and the outputs used to create pedestrian and bicycle risk-scoring tools for segments and intersections. The risk-scoring tool was applied to safety projects identified in the 2015 All Roads Transportation Safety (ARTS) project lists from Oregon. The risk scores for the case study applications aligned reasonably well with the project’s benefits-costs estimates.


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