983 resultados para road crash injury
Resumo:
Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.
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THE DRINKING DRIVER is a guide for listeners to the Adult Education radio series ONE FOR THE ROAD, a five-part series on drink-driving and Australia’s road toll. ONE FOR THE ROAD was produced by Lee Parker and Julie Levi, with assistance from the Federal Office of Road Safety in Canberra. The five programs, presented by Lee Parker were first broadcast on ABC Radio National in January 1989, and repeated on Radio National and Regional Stations across Australia in April/May 1989. THE DRINKING DRIVER was written by Mark King, Senior Project Officer with the Road Safety Division of the South Australian Department of Transport.
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When an older driver has a crash with tragic consequences, there are calls for stricter licensing controls to detect “unfit” drivers and take their licences away, typically focusing on those aged 75 or over. When the crash records for older drivers are compared across jurisdictions, however, there is no observable impact of any restrictions. This includes compulsory re-testing, which is strongly advocated by the public but is not supported by the research.
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BACKGROUND: Injuries occurring in the workplace can have serious implications for the health of the individual, the productivity of the employer and the overall economic community. OBJECTIVE: The objective of this paper is to increase the current state of understanding of individual demographic and psychosocial characteristics associated with extended absenteeism from the workforce due to a workplace injury. METHODS: Studies included in this systematic literature review tracked participants' return to work status over a minimum of three months, identified either demographic, psychosocial or general injury predictors of poor return to work outcomes and included a heterogeneous sample of workplace injuries. RESULTS: Identified predictors of poor return to work outcomes included older age, female gender, divorced marital status, two or more dependent family members, lower education levels, employment variables associated with reduced labour market desirability, severity or sensitive injury locations, negative attitudes and outcome perceptions of the participant. CONCLUSIONS: There is a need for clear and consistent definition and measurement of return to work outcomes and a holistic theoretical model integrating injury, psychosocial and demographic predictors of return to work. Through greater understanding of the nature of factors affecting return to work, improved outcomes could be achieved.
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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.
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This study identified the areas of poor specificity in national injury hospitalization data and the areas of improvement and deterioration in specificity over time. A descriptive analysis of ten years of national hospital discharge data for Australia from July 2002-June 2012 was performed. Proportions and percentage change of defined/undefined codes over time was examined. At the intent block level, accidents and assault were the most poorly defined with over 11% undefined in each block. The mechanism blocks for accidents showed a significant deterioration in specificity over time with up to 20% more undefined codes in some mechanisms. Place and activity were poorly defined at the broad block level (43% and 72% undefined respectively). Private hospitals and hospitals in very remote locations recorded the highest proportion of undefined codes. Those aged over 60 years and females had the higher proportion of undefined code usage. This study has identified significant, and worsening, deficiencies in the specificity of coded injury data in several areas. Focal attention is needed to improve the quality of injury data, especially on those identified in this study, to provide the evidence base needed to address the significant burden of injury in the Australian community.
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Background and Aims Considerable variation has been documented with fleet safety interventions’ abilities to create lasting behavioural change, and research has neglected to consider employees’ perceptions regarding the effectiveness of fleet interventions. This is a critical oversight as employees’ beliefs and acceptance levels (as well as the perceived organisational commitment to safety) can ultimately influence levels of effectiveness, and this study aimed to examine such perceptions in Australian fleet settings. Method 679 employees sourced from four Australian organisations completed a safety climate questionnaire as well as provided perspectives about the effectiveness of 35 different safety initiatives. Results Countermeasures that were perceived as most effective were a mix of human and engineering-based approaches: - (a) purchasing safer vehicles; - (b) investigating serious vehicle incidents, and; - (c) practical driver skills training. In contrast, least effective countermeasures were considered to be: - (a) signing a promise card; - (b) advertising a company’s phone number on the back of cars for complaints and compliments, and; - (c) communicating cost benefits of road safety to employees. No significant differences in employee perceptions were identified based on age, gender, employees’ self-reported crash involvement or employees’ self-reported traffic infringement history. Perceptions of safety climate were identified to be “moderate” but were not linked to self-reported crash or traffic infringement history. However, higher levels of safety climate were positively correlated with perceived effectiveness of some interventions. Conclusion Taken together, employees believed occupational road safety risks could best be managed by the employer by implementing a combination of engineering and human resource initiatives to enhance road safety. This paper will further outline the key findings in regards to practice as well as provide direction for future research.
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Purpose To examine the effects of optical blur, auditory distractors and age on eye movement patterns while performing a driving hazard perception test (HPT). Methods Twenty young (mean age 27.1 ± 4.6 years) and 20 older (73.3 ± 5.7 years) drivers with normal vision completed a HPT in a repeated-measures counterbalanced design while their eye movements were recorded. Testing was performed under two visual (best-corrected vision and with +2.00DS blur) and two distractor (with and without auditory distraction) conditions. Participants were required to respond to road hazards appearing in the HPT videos of real-world driving scenes and their hazard response times were recorded. Results Blur and distractors each significantly delayed hazard response time, by 0.42 and 0.76s respectively (p<0.05). A significant interaction between age and distractors indicated that older drivers were more affected by distractors than young drivers (response with distractors delayed by 0.96 and 0.60s respectively). There were no other two- or three-way interaction effect on response time. With blur, both groups fixated significantly longer on hazards before responding compared to best-corrected vision. In the presence of distractors, both groups exhibited delayed first fixation on the hazards and spent less time fixating on the hazards. There were also significant differences in eye movement characteristics between groups, where older drivers exhibited smaller saccades, delayed first fixation on hazards, and shorter fixation duration on hazards compared to the young drivers. Conclusions Collectively, the findings of delayed hazard response times and alterations in eye movement patterns with blur and distractors provide further evidence that visual impairment and distractors are independently detrimental to driving safety given that delayed hazard response times are linked to increased crash risk.
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During the last decade, developing countries such as India have been exhibiting rapid increase in human population and vehicles, and increase in road accidents. Inappropriate driving behaviour is considered one of the major causes of road accidents in India as compared to defective geometric design of pavement or mechanical defects in vehicles. It can result in conditions such as lack of lane discipline, disregard to traffic laws, frequent traffic violations, increase in crashes due to self-centred driving, etc. It also demotivates educated drivers from following good driving practices. Hence, improved driver behaviour can be an effective countermeasure to reduce the vulnerability of road users and inhibit crash risks. This article highlights improved driver behaviour through better driver education, driver training and licensing procedures along with good on-road enforcement; as an effective countermeasure to ensure road safety in India. Based on the review and analysis, the article also recommends certain measures pertaining to driver licensing and traffic law enforcement in India aimed at improving road safety.
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The purpose of the present work was to investigate if a hierarchy of aetiology exists which would influence attitudes towards survivors of brain injury. An independent groups design utilised four independent variables; aetiology (measured at five levels: ‘Road Traffic Accident’ (RTA), ‘Alcohol’, ‘Drug Use’, ‘Aneurism’ and ‘Recreation’), blame (blame and no-blame), group (psychology students and members of the public) and gender to explore attitudes towards survivors of brain injury. The dependent variables were measured using the Prejudicial Evaluation Scale (PES) and Social Interaction Scale (SIS). Three hundred and twenty-five participants (173 students and 152 members of the public) were randomly allocated to one of ten possible conditions. Among individuals who contributed to receiving their injury greater prejudice was displayed towards those in the ‘Drugs’ condition followed by ‘Recreation’, ‘RTA’, ‘Alcohol’ and ‘Aneurism’. Findings suggest that a hierarchy of aetiology exists, which results in prejudicial attitudes, and is influenced by issues of blame. Key words: prejudice, blame, brain injury
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Objectives To compare risk of fatal injury in elderly road users (drivers, passengers, pedestrians) with that of younger age groups and to assess the contribution of elderly road users to the number of reported fatalities in the population. Design Fatality age was categorized as 21 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, or 70 and older, and road user was categorized as driver, passenger, or pedestrian. Estimated number of trips made by each age group was used to adjust for exposure and to measure individual risk. Setting Fatalities recorded in Britain between 1989 and 2009. Participants Population-wide fatal injury counts in Britain. Measurements Age of fatally injured drivers, passengers, and pedestrians. Estimated number of trips made per year by drivers, passengers, and pedestrians. Results Risk of fatal injury, but not fatality numbers in the population, were higher for older adult (=70) drivers than for younger age groups. Risk of fatal injury was also high for older adult passengers and pedestrians, who represented the majority of older adult fatalities. Conclusion Previous emphasis on driver impairment in older age has unduly focussed attention on elderly drivers, who represent a minority of all driver fatalities. Older adults represent a much larger proportion of passenger and pedestrian fatalities. Additional policy schemes and initiatives should be targeted at safeguarding older adult passengers and making the road environment safer for elderly pedestrians. © 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.
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Young and elderly drivers are reported to have markedly greater crash rates than drivers of other ages, but they travel less frequently and represent a minority of road users. Consequently, many crashes involving young or elderly drivers also involve drivers of middle age ranges who travel more frequently.
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In this article the multibody simulation software package MADYMO for analysing and optimizing occupant safety design was used to model crash tests for Normal Containment barriers in accordance with EN 1317. The verification process was carried out by simulating a TB31 and a TB32 crash test performed on vertical portable concrete barriers and by comparing the numerical results to those obtained experimentally. The same modelling approach was applied to both tests to evaluate the predictive capacity of the modelling at two different impact speeds. A sensitivity analysis of the vehicle stiffness was also carried out. The capacity to predict all of the principal EN1317 criteria was assessed for the first time: the acceleration severity index, the theoretical head impact velocity, the barrier working width and the vehicle exit box. Results showed a maximum error of 6% for the acceleration severity index and 21% for theoretical head impact velocity for the numerical simulation in comparison to the recorded data. The exit box position was predicted with a maximum error of 4°. For the working width, a large percentage difference was observed for test TB31 due to the small absolute value of the barrier deflection but the results were well within the limit value from the standard for both tests. The sensitivity analysis showed the robustness of the modelling with respect to contact stiffness increase of ±20% and ±40%. This is the first multibody model of portable concrete barriers that can reproduce not only the acceleration severity index but all the test criteria of EN 1317 and is therefore a valuable tool for new product development and for injury biomechanics research.
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In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.
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RESUMO - Objetivos: Anualmente morrem cerca de 1,3 milhões de pessoas, a nível mundial, devido aos acidentes de viação. Também mais de 20 milhões de pessoas sofrem ferimentos ligeiros ou graves devido aos acidentes de viação que resultam em incapacidade temporária ou permanente. Desta forma, consideram-se os acidentes de viação, um grave problema de saúde pública, com custos elevados para as sociedades afetando a saúde das populações e economias de cada país. Este estudo pretendeu descrever e caracterizar os condutores de veículos ligeiros, residentes em Portugal Continental, abrangendo características sociodemográficas, experiência de condução e questões relativas a atitudes, opiniões e comportamentos. Por outro lado procurou-se analisar a associação entre as opiniões, atitudes e comportamentos, auto reportados e a ocorrência de um acidente de viação nos últimos três anos a fim de construir um modelo final preditivo do risco de sofrer um acidente de viação. Método: Foi realizado um estudo observacional analítico transversal baseado num questionário traduzido para a língua portuguesa e com origem no projeto europeu SARTRE 4. A população-alvo foram todos os condutores de veículos ligeiros possuidores de uma licença de condução e residentes em Portugal Continental, baseado numa amostra de igual dimensão à definida no estudo europeu SARTRE 4 (600 condutores de veículos ligeiros). Das 52 perguntas existentes, selecionaram-se pela análise de componentes principais (ACP) variáveis potencialmente independentes e complementares para as componentes opiniões, atitudes e comportamentos. Para além das medidas descritivas usuais, recorreu-se à regressão logística binária para analisar associações e obter um modelo que permitisse estimar a probabilidade de sofrer um acidente rodoviário em função das variáveis selecionadas referentes às opiniões, atitudes e comportamentos auto reportados. Resultados: Dos 612 condutores inquiridos, 62,7% (383) responderam não ter sofrido nenhum acidente de viação nos últimos três anos enquanto 37,3% (228) respondeu ter estado envolvido em pelo menos um acidente de viação com danos materiais ou feridos, no mesmo período. De uma forma geral, o típico condutor que referiu ter sofrido um acidente nos últimos três anos é homem com mais de 65 anos de idade, com o 1º ensino básico, viúvo e sem filhos, não empregado e reside numa área urbana. Os condutores residentes numa área suburbana apresentaram um risco 5,368 mais elevado de sofrer um acidente de viação em relação aos condutores que habitam numa zona rural (IC 95%: 2,344-12,297; p<0,001). Os condutores que foram apenas submetidos uma vez a um controlo de álcool, nos últimos três anos, durante o exercício da condução apresentaram um risco 3,009 superior de sofrer um acidente de viação em relação aos condutores que nunca foram fiscalizados pela polícia (IC 95%: 1,949-4,647, p<0,001). Os condutores que referiram muito frequentemente parar para dormir quando se sentem cansados a conduzir têm uma probabilidade inferior de 81% de sofrer um acidente de viação em relação aos condutores que nunca o fazem (IC 95%: 0,058-0,620; p=0,006). Os condutores que quando cansados raramente bebem um café/bebida energética têm um risco de 4,829 superior de sofrer um acidente de viação do que os condutores que sempre o referiram fazer (IC 95%:1,807-12,903; p=0,002). Conclusões: Os resultados obtidos em relação aos fatores comportamentais vão ao encontro da maioria dos fatores de risco associados aos acidentes de viação referidos na literatura. Ainda assim, foram identificadas novas associações entre o risco de sofrer um acidente e as opiniões e as atitudes auto reportadas que através de estudos de maiores dimensões populacionais poderão vir a ser mais exploradas. Este trabalho vem reforçar a necessidade urgente de novas estratégias de intervenção, principalmente na componente comportamental, direcionadas aos grupos de risco, mantendo as existentes.