9 resultados para Accident risk forecasting.

em University of Queensland eSpace - Australia


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Sleep-disordered breathing and excessive sleepiness may be more common in commercial vehicle drivers than in the general population. The relative importance of factors causing excessive sleepiness and accidents in this population remains unclear. We measured the prevalence of excessive sleepiness and sleep-disordered breathing and assessed accident risk factors in 2,342 respondents to a questionnaire distributed to a random sample of 3,268 Australian commercial vehicle drivers and another 161 drivers among 244 invited to undergo polysomnography. More than half (59.6%) of drivers had sleep-disordered breathing and 15.8% had obstructive sleep apnea syndrome. Twenty-four percent of drivers had excessive sleepiness. Increasing sleepiness was related to an increased accident risk. The sleepiest 5% of drivers on the Epworth Sleepiness Scale and Functional Outcomes of Sleep Questionnaire had an in-creased risk of an accident (odds ratio [OR] 1.91, p = 0.02 and OR 2.23, p < 0.01, respectively) and multiple accidents (OR 2.67, p < 0.01 and OR 2.39, p = 0.01), adjusted for established risk factors. There was an increased accident risk with narcotic analgesic use (OR 2.40, p < 0.01) and antihistamine use (OR 3.44, p = 0.04). Chronic excessive sleepiness and sleep-disordered breathing are common in Australian commercial vehicle drivers. Accident risk was related to increasing chronic sleepiness and antihistamine and narcotic analgesic use.

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Purpose. Drivers adopt smaller safety margins when pulling out in front of motorcycles compared with cars. This could partly account for why the most common motorcycle/car accident involves a car violating a motorcyclist's right of way. One possible explanation is the size-arrival effect in which smaller objects are perceived to arrive later than larger objects. That is, drivers may estimate the time to arrival of motorcycles to be later than cars because motorcycles are smaller. Methods. We investigated arrival time judgments using a temporal occlusion paradigm. Drivers recruited from the student population (n = 28 and n = 33) saw video footage of oncoming vehicles and had to press a response button when they judged that vehicles would reach them. Results. In experiment 1, the time to arrival of motorcycles was estimated to be significantly later than larger vehicles (a car and a van) for different approach speeds and viewing times. In experiment 2, we investigated an alternative explanation to the size-arrival effect: that the smaller size of motorcycles places them below the threshold needed for observers to make an accurate time to arrival judgment using tau. We found that the motorcycle/car difference in arrival time estimates was maintained for very short occlusion durations when tau could be estimated for both motorcycles and cars. Conclusions. Results are consistent with the size-arrival effect and are inconsistent with the tau threshold explanation. Drivers estimate motorcycles will reach them later than cars across a range of conditions. This could have safety implications.

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Although perceived health risk plays a prominent role in theories of health behavior. its empirical role in risk taking is less clear. In Study 1 (N = 129), 2 measures of drivers' risk-taking behavior were found to be unrelated to self-estimates of accident concern but to be related to self-ratings of driving skill and the perceived thrill of driving. In Study 2 (N = 405), out of a wide range of potential influences, accident concern had the weakest relationship with risk taking. The authors concluded that although health risk is a key feature in many theories of health behavior and a central focus for researchers and policy makers, it may not be such a prominent factor for those actually taking the risk.

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Older adults make up an increasing propordon of automobile drivers in Australia. Despite the fact that older drivers generally drive much less than younger drivers, there is a disdnct increase in accidents, fatalides and injuries in drivers over age 65 (per actual kilometres driven). Accurate means of screening older adults to idendfy those at increased risk of motor vehicle accidents have proved elusive. Neuropsychological assessment and clinical examinadon are not well-correlated with accident risk. On-road tesdng, which is more highly correlated with accident risk, is expensive and dme-consuming, as well as being less suitable as a screening process. Hazard percepdon methods have been used as an effecdve screening method for idendfying younger adults at increased risk of accidents. A brief video-based hazard percepdon screening test involving footage of genuine traffic hazards for use on older individuals will be presented.

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The desire to know the future is as old as humanity. For the tourism industry the demand for accurate foretelling of the future course of events is a task that consumes considerable energy and is of great significance to investors. This paper examines the issue of forecasting by comparing forecasts of inbound tourism made prior to the political and economic crises that engulfed Indonesia from 1997 onwards with actual arrival figures. The paper finds that current methods of forecasting are not able to cope with unexpected crises and other disasters and that alternative methods need to be examined including scenarios, political risk and application of chaos theory. The paper outlines a framework for classifying shocks according to a scale of severity, probability, type of event, level of certainty and suggested forecasting tools for each scale of shock. (C) 2003 Elsevier Science Ltd. All rights reserved.

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There is a substantial body of work in the scientific literature discussing the role of risk-taking behavior in the causation of injury. Despite the quantity of diverse writings on the subject most is in the form of theoretical commentaries. This review was conducted to critically assess the empirical evidence supporting the association between injury and risk-taking behavior. The review found six case-control studies and one retrospective cohort study, which met all the inclusion criteria. Meta-analysis was not possible due to the diversity of the independent and outcome variables in each of the studies reviewed. Overall the review found that risk-taking behavior, however it is measured, is associated with an increased chance of sustaining an injury except in the case of high skilled, risk-taking sports where the effect may be in the other direction. Drawing specific conclusions from the research presented in this review is difficult without an agreed conceptual framework for examining risk-taking behavior and injury. Considerable work needs to be done to provide a convincing evidence base on which to build public health interventions around risk behavior. However, sufficient evidence exists to suggest that effort in this area may be beneficial for the health of the community. (C) 2003 Elsevier Science Ltd. All rights reserved.

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Different components of driving skill relate to accident involvement in different ways. For instance, while hazard-perception skill has been found to predict accident involvement, vehicle-control skill has not. We found that drivers rated themselves superior to both their peers and the average driver on 18 components of driving skill (N = 181 respondents). These biases were greater for hazard-perception skills than for either vehicle-control skills or driving skill in general. Also, ratings of hazard-perception skill related to self-perceived safety after overall skill was controlled for. We suggest that although drivers appear to appreciate the role of hazard perception in safe driving, any safety benefit to be derived from this appreciation may be undermined by drivers' inflated opinions of their own hazard-perception skill. We also tested the relationship between illusory beliefs about driving skill and risk taking and looked at ways of manipulating drivers' illusory beliefs.

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Study objective: UK government policy mandates the introduction of 'intermediate care services' to reduce emergency admissions to hospital from the population aged 75 years or more. We evaluated one of these initiatives-the Keep Well At Home (KWAH) Project-in a West London Primary Care Trust. Design: KWAH involves a two-phase screening process, including a home visit by a community nurse. We employed cohort methods to determine whether KWAH resulted in fewer emergency attendances and admissions to hospital in the target population, from October 1999 to December 2002. Results: estimated levels of coverage in the two phases of screening were 61 and 32%, respectively. The project had not maintained records of which additional health and social care services had been delivered following screening. The rates of emergency admissions to hospital in the 9 months before screening were similar in practices that did and did not join the project (rate ratio (RR) = 1.05; 95% CI 0.95-1.17), suggesting absence of volunteer bias. Over the first 37 months of the project, there was no significant impact on either attendances at Accident & Emergency departments (RR = 1.02; 95% CI 0.97-1.06) or emergency admissions of elderly patients (RR = 0.98; 95% CI 0.93-1.05). Conclusion: the KWAH Project has been ineffective in reducing emergency admissions among the elderly. Significant questions arise in relation to selection of the screening instruments, practicality of achieving higher coverage of the eligible population, and creation of a new postcode lottery.

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The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.