894 resultados para On-road driving assessment


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Objective: A literature review to examine the incorporation of respiratory assessment into everyday surgical nursing practice; possible barriers to this; and the relationship to patient outcomes. Primary argument: Escalating demands on intensive care beds have led to highly dependent patients being cared for in general surgical ward areas. This change in patient demographics has meant the knowledge and skills required of registered nurses in these areas has expanded exponentially. The literature supported the notion that postoperative monitoring of vital signs should include the fundamental assessment of respiratory rate; depth and rhythm; work of breathing; use of accessory muscles and symmetrical chest movement; as well as auscultation of lung fields using a stethoscope. Early intervention in response to changes in a patient's respiratory health status impacts positively on patient health outcomes. Substantial support exists for the contention that technologically adept nurses who also possess competent respiratory assessment skills make a difference to respiratory care. Conclusions: Sub-clinical respiratory problems have been demonstrated to contribute to adverse events. There is a paucity of research knowledge as to whether respiratory education programs and associated inservice make a difference to nursing clinical practice. Similarly, the implications for associated respiratory educational needs are not well documented, nor has a research base been sufficiently developed to guide nursing practice. Further research has the potential to influence the future role and function of the registered nurse by determining the importance of respiratory education programs on post-operative patient outcomes.

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A range of risk management initiatives have been introduced in organisations in attempt to reduce occupational road incidents. However a discrepancy exists between the initiatives that are frequently implemented in organisations and the initiatives that have demonstrated scientific merit in improving occupational road safety. Given that employees’ beliefs may facilitate or act as a barrier to implementing initiatives, it is important to understand whether initiatives with scientific merit are perceived to be effective by employees. To explore employee perceptions pertaining to occupational road safety initiatives, a questionnaire was administered to 679 employees sourced from four Australian organisations. Participants ranged in age from 18 years to 65 years (M = 42, SD = 11). Participants rated 35 initiatives based on how effective they thought they would be in improving road safety in their organisation. The initiatives perceived by employees to be most effective in managing occupational road risks comprised: making vehicle safety features standard e.g. passenger airbags; practical driver skills training; and investigation of serious vehicle incidents. The initiatives perceived to be least effective in managing occupational road risks comprised: signing a promise card commitment to drive safely; advertising the organisation’s phone number on vehicles for complaints and compliments; and consideration of driving competency in staff selection process. Employee perceptions were analysed at a factor level and at an initiative level. The mean scores for the three extracted factors revealed that employees believed occupational road risks could best be managed by the employer implementing engineering and human resource methods to enhance road safety. Initiatives relating to employer management of identified risk factors were perceived to be more effective than feedback or motivational methods that required employees to accept responsibility for their driving safety. Practitioners can use the findings from this study to make informed decisions about how they select, manage and market occupational safety initiatives.

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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

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Reliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12-50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.

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Driving on an approach to a signalized intersection while distracted is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. Given the prevalence and importance of this particular scenario, the decisions and actions of distracted drivers during the onset of yellow lights are the focus of this study. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of Iowa - National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examination has been conducted from a traditional regression-based approach, which does not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that novice (16-17 years) and young drivers’ (18-25 years) have heightened yellow light running risk while distracted by a cell phone conversation. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Overall, distracted drivers across most tested groups tend to reduce the propensity of yellow light running as the distance to stop line increases, exhibiting risk compensation on a critical driving situation.

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Background: When experiencing sleep problems for the first time, consumers may often approach community pharmacists for advice as they are easily accessible health care professionals in the community. In Australian community pharmacies there are no specific tools available for use by pharmacists to assist with the assessment and handling of consumers with sleep enquiries. Objective: To assess the feasibility of improving the detection of sleep disorders within the community through the pilot of a newly developed Community Pharmacy Sleep Assessment Tool (COP-SAT). Method: The COP-SAT was designed to incorporate elements from a number of existing, standardized, and validated clinical screening measures. The COP-SAT was trialed in four Australian community pharmacies over a 4-week period. Key findings: A total of 241 community pharmacy consumers were assessed using the COP-SAT. A total of 74 (30.7%) were assessed as being at risk of insomnia, 26 (10.7%) were at risk of daytime sleepiness, 19 (7.9%) were at risk of obstructive sleep apnea, and 121 (50.2%) were regular snorers. A total of 116 (48.1%) participants indicated that they consume caffeine before bedtime, of which 55 (47%) had associated symptoms of sleep onset insomnia. Moreover, 85 (35%) consumed alcohol before bedtime, of which 50 (58%) experienced fragmented sleep, 50 (58%) were regular snorers, and nine (10.6%) had apnea symptoms. The COP-SAT was feasible in the community pharmacy setting. The prevalence of sleep disorders in the sampled population was high, but generally consistent with previous studies on the general population. Conclusion: A large proportion of participants reported sleep disorder symptoms, and a link was found between the consumption of alcohol and caffeine substances at bedtime and associated symptoms. While larger studies are needed to assess the clinical properties of the tool, the results of this feasibility study have demonstrated that the COP-SAT may be a practical tool for the identification of patients at risk of developing sleep disorders in the community.

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between mid 2010 and early 2011, Queensland road related infrastructures were devastated by flood and cyclone related natural disasters. Responding to these recent events and in preparing for more regular and intense climate-change induced events in future, the Queensland Government is now reviewing how post-disaster road infrastructure recovery projects are planned and delivered. In particular, there is awareness that rebuilding such infrastructure need sustainable strategies across economic, environmental and social dimensions. A comprehensive sustainability assessment framework for pre and post disaster situations can minimize negative impact on our communities, economy and environment. This research is underway to develop a comprehensive sustainability element frame work for post disaster management in road infrastructures in Queensland, Australia. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of natural disasters. This research can contribute to strategic planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes in Queensland. Within this context, this paper provides an overview of the qualitative mixed-method research approach involving literature reviews and case studies to explore and evaluate a number of sustainability elements with a view to develop operational strategies for disaster recovery road projects.

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As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

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Drink driving is a major public health issue and this report examines the experiences of convicted offenders who participated in an established drink driving rehabilitation program Under the Limit (UTL). Course completers were surveyed at least three months after they had finished the 11-week UTL course. The aim of this study was to examine whether the UTL program reduced the level of alcohol consumption either directly as a result of participation in the UTL drink driving program or through increased use of community alcohol program by participants. The research involved a self-report outcome evaluation to determine whether the self-reported levels of alcohol use after the course had changed from the initial alcohol use reported by offenders. The findings are based on the responses of 30 drink-driving offenders who had completed the UTL program (response rate: 20%). While a process evaluation was proposed in the initial application, the low response rate meant that this follow up research was not feasible. The response rate was low for two reasons, it was difficult to: recruit participants who consented to follow up, and subsequently locate and survey those who had consented to involvement.

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The growing national and international awareness of the increased representation of serious injuries and fatalities in rural and remote areas is the focus of this paper. Australia was one of the earliest countries to try to address this issue with a targeted national action plan in 1996. This was an important document but the most recent national plan fails to dedicate attention to developing countermeasures for the particular problems of improving road safety in these regions. The findings of a major program of research in Northern Queensland are discussed to stimulate interest and research into potential countermeasures. Specifically, the need to monitor clusters of crashes as a focus for intervention and local ownership is advocated. Taking action towards a national reduction of speed limits on rural roads and investment in proactive research based trials of drink driving countermeasures such as courtesy buses is strongly advocated.

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Self reported driving behaviour in the occupational driving context has typically been measured through scales adapted from the general driving population (i.e. the Manchester Driver Behaviour Questionnaire (DBQ)). However, research suggests that occupational driving is influenced by unique factors operating within the workplace environment, and thus, a behavioural scale should reflect those behaviours prevalent and unique within the driving context. To overcome this limitation, developed the Occupational Driver Behaviour Questionnaire (ODBQ) which utilises a relevant theoretical model to assess the impact of the broader workplace context on driving behaviour. Although the theoretical argument has been established, research is yet to examine whether the ODBQ or the DBQ is a more sensitive measure of the workplace context. As such, this paper identifies selected organisational factors (i.e. safety climate and role overload) as predictors of the DBQ and the ODBQ and compares the relative predictive value in both models. In undertaking this task, 248 occupational drivers were recruited from a community-oriented nursing population. As predicted, hierarchical regression analyses revealed that the organisational factors accounted for a significantly greater proportion of variance in the ODBQ than the DBQ. These findings offer a number of practical and theoretical applications for occupational driving practice and future research.

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An increasing body of research is highlighting the involvement of illicit drugs in many road fatalities. Deterrence theory has been a core conceptual framework underpinning traffic enforcement as well as interventions designed to reduce road fatalities. Essentially the effectiveness of deterrence-based approaches is predicated on perceptions of certainty, severity, and swiftness of apprehension. However, much less is known about how the awareness of legal sanctions can impact upon the effectiveness of deterrence mechanisms and whether promoting such detection methods can increase the deterrent effect. Nevertheless, the implicit assumption is that individuals aware of the legal sanctions will be more deterred. This study seeks to explore how awareness of the testing method impacts upon the effectiveness of deterrence-based interventions and intentions to drug drive again in the future. In total, 161 participants who reported drug driving in the previous six months took part in the current study. The results show that awareness of testing had a small effect upon increasing perceptions of the certainty of apprehension and severity of punishment. However, awareness was not a significant predictor of intentions to drug drive again in the future. Importantly, higher levels of drug use were a significant predictor of intentions to drug drive in the future. Whilst awareness does have a small effect on deterrence variables, the influence of levels of drug use seems to reduce any deterrent effect.

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Background: There is a well developed literature on research investigating the relationship between various driving behaviours and road crash involvement. However, this research has predominantly been conducted in developed economies dominated by western types of cultural environments. To date no research has been published that has empirically investigated this relationship within the context of the emerging economies such as Oman. Objective: The present study aims to investigate driving behaviour as indexed in the Driving Behaviour Questionnaire (DBQ) among a group of Omani university students and staff. Methods: A convenience non-probability self- selection sampling approach was utilized with Omani university students and staff. Results: A total of 1003 Omani students (n= 632) and staff (n=371) participated in the survey. Factor analysis of the BDQ revealed four main factors that were errors, speeding violation, lapses and aggressive violation. In the multivariate logistic backward regression analysis, the following factors were identified as significant predictors of being involved in causing at least one crash: driving experience, history of offences and two DBQ components i.e. errors and aggressive violation. Conclusion: This study indicates that errors and aggressive violation of the traffic regulations as well as history of having traffic offences are major risk factors for road traffic crashes among the sample. While previous international research has demonstrated that speeding is a primary cause of crashing, in the current context, the results indicate that an array of factors is associated with crashes. Further research using more rigorous methodology is warranted to inform the development of road safety countermeasures in Oman that improves overall traffic safety culture.

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This report discusses the geologic framework and petroleum geology used to assess undiscovered petroleum resources in the Bohaiwan basin province for the 2000 World Energy Assessment Project of the U.S. Geological Survey. The Bohaiwan basin in northeastern China is the largest petroleum-producing region in China. Two total petroleum systems have been identified in the basin. The first, the Shahejie–Shahejie/Guantao/Wumishan Total Petroleum System, involves oil and gas generated from mature pods of lacustrine source rock that are associated with six major rift-controlled subbasins. Two assessment units are defined in this total petroleum system: (1) a Tertiary lacustrine assessment unit consisting of sandstone reservoirs interbedded with lacustrine shale source rocks, and (2) a pre-Tertiary buried hills assessment unit consisting of carbonate reservoirs that are overlain unconformably by Tertiary lacustrine shale source rocks. The second total petroleum system identified in the Bohaiwan basin is the Carboniferous/Permian Coal–Paleozoic Total Petroleum System, a hypothetical total petroleum system involving natural gas generated from multiple pods of thermally mature coal beds. Low-permeability Permian sandstones and possibly Carboniferous coal beds are the reservoir rocks. Most of the natural gas is inferred to be trapped in continuous accumulations near the center of the subbasins. This total petroleum system is largely unexplored and has good potential for undiscovered gas accumulations. One assessment unit, coal-sourced gas, is defined in this total petroleum system.