Journal ArticleDOI
Some methodological deficiencies in studies on traffic accident predictors
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In this paper, the authors discuss some methodological problems in (psychological) research on traffic accident predictors and review a convenience sample of the literature and identify three methodological aspects as being important: reliability of accident predictor, time period for accidents used as dependent variable, and culpability for accidents.About:
This article is published in Accident Analysis & Prevention.The article was published on 2003-07-01. It has received 72 citations till now. The article focuses on the topics: Poison control.read more
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Long-term effects of training in economical driving: Fuel consumption, accidents, driver acceleration behavior and technical feedback
TL;DR: In this paper, the effects of training in fuelefficient driving for bus drivers in a city environment were evaluated, and three dependent variables, hypothetically associated with such training, were used; fuel and accident data from the bus company and driver acceleration behavior from five buses, over time periods of several years.
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Residual effects of sleep medication on driving ability
TL;DR: Patients treated with benzodiazepine hypnotics or zopiclone should be cautioned when driving a car, and tolerance develops to the impairing effects of hypnotics, but this is a slow process, and impairment may persist.
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Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers
TL;DR: This research suggests that in addition to the individual centered stress-reduction occupational programs, fatigue management interventions aimed to changing some working conditions may reduce risky driving behaviors and promote safety in the professional drivers' jobs and on the road.
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The Manchester Driver Behaviour Questionnaire as a predictor of road traffic accidents
TL;DR: In this paper, the authors used the Driver Behaviour Questionnaire (DBQ) as a predictor of self-reported road traffic accidents and found that the DBQ scale only predicts selfreported accidents, not recorded crashes, despite the higher validity of company data and the higher means of recorded data across these samples.
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Motor vehicle collision risk and driving under the influence of cannabis: Evidence from adolescents in Atlantic Canada
TL;DR: Findings extend the knowledge of DUIC as a socio-legal and public health issue with implications on road safety and effort must be placed on educating new drivers about cannabis use in the context of driving.
References
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Journal ArticleDOI
Behavioral Development and Construct Validity: The Principle of Aggregation
TL;DR: In this article, the authors explore the possibility that many important variables in behavioral development are often due to failures to aggregate, and illustrate the usefulness of this principle in 12 major areas of developmental research in which the issue of negligible correlations figures prominently.
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Driving errors, driving violations and accident involvement
TL;DR: Accident liability was predicted by self-reported tendency to commit violations, but not by tendency to make errors or to have lapses, and each type of behaviour was found to have different demographic correlates.
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Behavioral-correlates of individual-differences in road-traffic crash risk - an examination of methods and findings
TL;DR: Qualitative issues relevant to the study of differential crash involvement and the findings of research in this area are considered and the ways in which research in the area might usefully proceed are reviewed.
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Intention to commit driving violations: An application of the theory of planned behavior
Dianne Parker,Antony Stephen Reid Manstead,Stephen G. Stradling,James T. Reason,James S. Baxter +4 more
TL;DR: This article assessed the ability of the theory of planned behavior to account for drivers' intentions to commit four specific driving violations: drinking and driving, speeding, close following, and overtaking in risky circumstances.
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Visual/cognitive correlates of vehicle accidents in older drivers.
TL;DR: The best predictor of accident frequency as recorded by the state was a model incorporating measures of early visual attention and mental status, which together accounted for 20% of the variance, a much stronger model than in earlier studies.