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Chinese Journal of Traumatology =... Mar 2021To determine the trends with fatally or otherwise injured pedestrians lying on the road and the relationship to hit-and-run incidents in Japan.
PURPOSE
To determine the trends with fatally or otherwise injured pedestrians lying on the road and the relationship to hit-and-run incidents in Japan.
METHODS
We extracted data for 2012-2016 from the records of the Institute for Traffic Accident Research and Data Analysis, Japan, a nationwide traffic accident database. All the injured and fatally injured pedestrians were selected. We examined the levels of pedestrian injury, vehicle speed immediately before the collision, whether or not the pedestrian was lying on the road, and hit-and-run incidents. Chi-square test was employed to make a statistical comparison between the two groups.
RESULTS
The database contained data on 286,383 pedestrian casualties and 7256 fatalities; 8.3% of fatalities (602 persons) and 0.6% of casualties (1827 persons) involved pedestrians lying on the road. The rates of fatalities and severe injuries were significantly higher for pedestrians who were lying on the road than for those who were not. Hit-and-run incidents were evident in 4.0% of casualties and 7.3% of fatalities. The rate of hit-and-run cases was also significantly higher among pedestrians who were lying on the road. Among fatally injured pedestrians not lying on the road, the rates with speeds of ≥30 km/h did not differ significantly between hit-and-run and other cases. However, when the pedestrians were lying on the road, the rate was significantly increased in hit-and-run cases.
CONCLUSION
This is the first report to focus on pedestrians lying on the road and being involved in hit-and-run incidents. In addition to preventing hit-and-run incidents, prevention of pedestrians lying on the road could also decrease fatalities.
Topics: Accidental Injuries; Accidents, Traffic; Adult; Crime Victims; Databases, Factual; Female; Humans; Japan; Male; Pedestrians; Posture; Time Factors; Trauma Severity Indices
PubMed: 33317929
DOI: 10.1016/j.cjtee.2020.11.008 -
Journal of Safety Research Jun 2022This study develops an empirical test of two theoretical models using the approach of Structural Equation Model (SEM) to test the relationships between specific...
INTRODUCTION
This study develops an empirical test of two theoretical models using the approach of Structural Equation Model (SEM) to test the relationships between specific organizational factors of safety management system (SMS) and specific risk variables.
METHOD
Two SEM models with two and four latent variables, respectively, and 10 observed risk variables were used to identify the strongest relationships that may lead to an accident on site. A random sample of 474 construction sites were visited and assessed in Spain from 2003 to 2010. Most of the samples were small and medium sized enterprises (SMEs), which is the predominant type of company in the Spanish construction industry. To assess the risk on sites and get the measurements of the variables included in the models, the validated method CONSRAT (Construction Sites Risk Assessment Tool) was used. After estimating the proposed models, an adequate fit was obtained for both of them.
RESULTS
Results provide empirical evidence that: (a) the factor "Resources on site" is more determinant in explaining influences on risk variables because of their influence on all risk variables (Model 1); (b) the factor "Site structure complexity" (which includes structure and organization, and safety resources available on site) has a stronger effect on risk variables than other factors related to intrinsic characteristics of the work, site, or companies (Model 2).
CONCLUSIONS
These results mean that the complexity and resource factors that depend on companies are those that have the greatest impact on risks, which makes it possible for companies to undertake the appropriate risk control measures.
PRACTICAL APPLICATION
These results can help construction firms obtain earlier information about which organizational elements can affect future safety conditions on site, improve those elements for preventing risks, and consequently, avoid accidents before they occur.
Topics: Accidents, Occupational; Construction Industry; Humans; Occupational Health; Organizational Culture; Safety Management; Spain; Workplace
PubMed: 35589298
DOI: 10.1016/j.jsr.2022.03.004 -
Bundesgesundheitsblatt,... Oct 2022Almost every day, the media report that emergency services at accident sites are hindered by rubberneckers. Such behaviors are criticized by firefighters, rescue service... (Review)
Review
Almost every day, the media report that emergency services at accident sites are hindered by rubberneckers. Such behaviors are criticized by firefighters, rescue service employees, and the general public and regarded as "unethical," "irresponsible," or even as an expression of social brutalization. Emotionally, the topic is highly charged.This article gives an overview of the hypotheses and theories that can be used to explain watching behavior. A literature search was conducted to identify biological, ethological, individual, and social psychological explanatory approaches for watching behavior at accident sites. These individual approaches are brought together in an integrative framework model.It turns out that watching behavior at accident sites is by no means solely due to "curiosity" and "desire to look." Rather, a complex combination of biological, individual, and social psychological motives with social, event, and personal moderator variables must be assumed. The blanket designation of spectators at accident sites as rubbernecks thus does not do justice to the complexity of the phenomenon. Watching behavior at accident sites is individual and multifactorially justified. Only a correspondingly comprehensive understanding of the problem provides a solid basis for the derivation of suitable prevention and intervention strategies.
Topics: Accidents; Germany; Humans; Motivation
PubMed: 36121462
DOI: 10.1007/s00103-022-03585-0 -
International Journal of Environmental... Apr 2021Major accidents occurred frequently in the road transportation industry, and the resulting harm to drivers, property loss, and traffic interruption are very serious....
Major accidents occurred frequently in the road transportation industry, and the resulting harm to drivers, property loss, and traffic interruption are very serious. This study investigated 11 particularly major accidents involving commercial vehicles in China, and performed analysis on accident characteristics regarding the time, location, types of vehicles, and accident causation at different levels based on the 24Model. Large buses and dangerous goods vehicles were involved in 10 accidents and they all occurred on a freeway. The months from May to August, especially during the time periods of 2:00-4:00 and 14:00-16:00 every day, were the most prone to accidents. The driver's speeding and fatigued driving, and vehicle failure were the direct causes of most of the accidents. The defects in organizational safety management involved 12 system elements, such as safety accountability, education and training, etc. Procedures are of no use if they were not followed, and there was often no effective process to assess the implementation of procedures in many organizations. The weaknesses in organizational safety culture were the source of accidents, which was mainly manifested in members' inadequate cognition of key elements in the aspects of safety importance, safety commitment, safety management system, etc. Understanding the characteristics and root causes of accidents can help to prevent the recurrence of similar mistakes and strengthen preventative measures in road transportation enterprises.
Topics: Accidents, Traffic; Automobile Driving; China; Motor Vehicles; Transportation
PubMed: 33917131
DOI: 10.3390/ijerph18083878 -
International Journal of Environmental... Jun 2022Storm disasters are the most common cause of accidents in offshore oil and gas industries. To prevent accidents resulting from storms, it is vital to analyze accident...
Storm disasters are the most common cause of accidents in offshore oil and gas industries. To prevent accidents resulting from storms, it is vital to analyze accident propagation and to learn about accident mechanism from previous accidents. In this paper, a novel risk analysis framework is proposed for systematically identifying and analyzing the evolution of accident causes. First, accident causal factors are identified and coded based on grounded theory (GT). Then, decision making trial and evaluation laboratory (DEMATEL) is integrated with interpretative structural modeling (ISM) to establish accident evolution hierarchy. Finally, complex networks (CN) are developed to analyze the evolution process of accidents. Compared to reported works, the contribution is threefold: (1) the demand for expert knowledge and personnel subjective influence are reduced through the data induction of accident cases; (2) the method of establishing influence matrix and interaction matrix is improved according to the accident frequency analysis; (3) a hybrid algorithm that can calculate multiple shortest paths of accident evolution under the same node pair is proposed. This method provides a new idea for step-by-step assessment of the accident evolution process, which weakens the subjectivity of traditional methods and achieves quantitative assessment of the importance of accident evolution nodes. The proposed method is demonstrated and validated by a case study of major offshore oil and gas industry accidents caused by storm disasters. Results show that there are five key nodes and five critical paths in the process of accident evolution. Through targeted prevention and control of these nodes and paths, the average shortest path length of the accident evolution network is increased by 35.19%, and the maximum global efficiency decreases by 20.12%. This indicates that the proposed method has broad applicability and can effectively reduce operational risk, so that it can guide actual offshore oil and gas operations during storm disasters.
Topics: Accidents; Accidents, Occupational; Disasters; Industry; Oil and Gas Industry; Risk Assessment
PubMed: 35742465
DOI: 10.3390/ijerph19127216 -
International Journal of Environmental... Jul 2022The frequent occurrence of ammonia-related refrigeration accidents (ArRAs) restricts the safety and sustainable development of cold storage. As an essential tool for...
The frequent occurrence of ammonia-related refrigeration accidents (ArRAs) restricts the safety and sustainable development of cold storage. As an essential tool for safety management, accident statistical analysis can provide a crucial decision-making basis for accident prevention and control. The present study combined descriptive statistics and comparative analysis methods to explore the characteristics and regularities of 82 ArRAs in China from 2010 to 2020. The results showed that the annual evolution of ArRAs presents a bimodal "M" mode in which 2013 and 2016 were the peaking years of accidents. The monthly distribution has an agglomeration effect, and the period from June to September had a high incidence period of accidents. The ArRAs mainly occurred in East China and Central China in the spatial dimension. Zhejiang, Shandong, Hubei, and Sichuan are the pivotal provinces for preventing and controlling ArRAs. Human factors and equipment failure are the leading causes of ArRAs. Accident numbers and casualties have inconsistent trends due to the uncertainty and variability of ArRAs' consequences. The safety situation of ammonia-related refrigeration enterprises has improved but still needs to strive to prevent and control major accidents. This study draws valuable references for safety decision-making by ammonia-related refrigeration enterprises and safety regulators.
Topics: Accidents; Ammonia; China; Humans; Refrigeration; Safety Management
PubMed: 35886081
DOI: 10.3390/ijerph19148230 -
Environment International Jan 2021Experience suggests that current nuclear accident response planning in European countries mostly has a technical focus, with less attention paid to social, psychological... (Review)
Review
The SHAMISEN Project: Challenging historical recommendations for preparedness, response and surveillance of health and well-being in case of nuclear accidents: Lessons learnt from Chernobyl and Fukushima.
Experience suggests that current nuclear accident response planning in European countries mostly has a technical focus, with less attention paid to social, psychological and ethical issues. Information provided tends to be directed towards decisions made by experts, rather than for the support of affected populations. The SHAMISEN (Nuclear Emergency Situations - Improvement of Medical And Health Surveillance) consortium, composed of close to 50 experts from 10 countries, performed a critical review of current recommendations and experiences regarding dose assessment and reconstruction, evacuation decisions, long-term health surveillance programmes and epidemiological studies. The review included case studies and lessons drawn from the living conditions and health status of populations affected by the Chernobyl and Fukushima accidents, taking an integrative approach to health and well-being. Based on this work, SHAMISEN developed a series of comprehensive recommendations aimed at improving the preparedness, response, long-term surveillance and living conditions of populations affected by past or future radiation accidents, in a manner responding to their needs, while minimising unnecessary anxiety.
Topics: Chernobyl Nuclear Accident; Europe; Fukushima Nuclear Accident; Japan; Learning
PubMed: 33197788
DOI: 10.1016/j.envint.2020.106200 -
International Journal of Environmental... Feb 2020Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident...
Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic accidents. This paper aims to improve our understanding of this relationship by analysing accidents at 120 intersections in Adelaide, Australia. Data comprised of 1629 motor vehicle accidents with traffic volumes from a dataset of more than five million hourly measurements. The effect of rainfall was also examined. Results showed an approximately linear relationship between traffic volume and accident frequency at lower traffic volumes. In the highest traffic volumes, poisson and negative binomial models showed a significant quadratic explanatory term as accident frequency increases at a higher rate. This implies that focusing management efforts on avoiding these conditions would be most effective in reducing accident frequency. The relative risk of rainfall on accident frequency decreases with increasing congestion index. Accident risk is five times greater during rain at low congestion levels, successively decreasing to no elevated risk at the highest congestion level. No significant effect of congestion index on accident severity was detected.
Topics: Accidents, Traffic; Australia; Models, Statistical; Rain
PubMed: 32098180
DOI: 10.3390/ijerph17041393 -
Sensors (Basel, Switzerland) Dec 2022Anomalous driving behavior detection is becoming more popular since it is vital in ensuring the safety of drivers and passengers in vehicles. Road accidents happen for...
Anomalous driving behavior detection is becoming more popular since it is vital in ensuring the safety of drivers and passengers in vehicles. Road accidents happen for various reasons, including health, mental stress, and fatigue. It is critical to monitor abnormal driving behaviors in real time to improve driving safety, raise driver awareness of their driving patterns, and minimize future road accidents. Many symptoms appear to show this condition in the driver, such as facial expressions or abnormal actions. The abnormal activity was among the most common causes of road accidents, accounting for nearly 20% of all accidents, according to international data on accident causes. To avoid serious consequences, abnormal driving behaviors must be identified and avoided. As it is difficult to monitor anyone continuously, automated detection of this condition is more effective and quicker. To increase drivers' recognition of their driving behaviors and prevent potential accidents, a precise monitoring approach that detects abnormal driving behaviors and identifies abnormal driving behaviors is required. The most common activities performed by the driver while driving is drinking, eating, smoking, and calling. These types of driver activities are considered in this work, along with normal driving. This study proposed deep learning-based detection models for recognizing abnormal driver actions. This system is trained and tested using a newly created dataset, including five classes. The main classes include Driver-smoking, Driver-eating, Driver-drinking, Driver-calling, and Driver-normal. For the analysis of results, pre-trained and fine-tuned CNN models are considered. The proposed CNN-based model and pre-trained models ResNet101, VGG-16, VGG-19, and Inception-v3 are used. The results are compared by using the performance measures. The results are obtained 89%, 93%, 93%, 94% for pre-trained models and 95% by using the proposed CNN-based model. Our analysis and results revealed that our proposed CNN base model performed well and could effectively classify the driver's abnormal behavior.
Topics: Accidents, Traffic; Deep Learning; Automobile Driving; Problem Behavior; Safety
PubMed: 36616911
DOI: 10.3390/s23010311 -
International Journal of Environmental... Oct 2022Mountain biking (MTB) is a cycling modality performed on a variety of unpaved terrain. Although the cross-country Olympic race is the most popular cross-country (XC)... (Review)
Review
Mountain biking (MTB) is a cycling modality performed on a variety of unpaved terrain. Although the cross-country Olympic race is the most popular cross-country (XC) format, other XC events have gained increased attention. XC-MTB has repeatedly modified its rules and race format. Moreover, bikes have been modified throughout the years in order to improve riding performance. Therefore, the aim of this review was to present the most relevant studies and discuss the main results on the XC-MTB. Limited evidence on the topic suggests that the XC-MTB events present a variation in exercise intensity, demanding cardiovascular fitness and high power output. Nonetheless, these responses and demands seem to change according to each event. The characteristics of the cyclists differ according to the performance level, suggesting that these parameters may be important to achieve superior performance in XC-MTB. Moreover, factors such as pacing and ability to perform technical sections of the circuit might influence general performance. Bicycles equipped with front and rear suspension (i.e., full suspension) and 29″ wheels have been shown to be effective on the XC circuit. Lastly, strategies such as protective equipment, bike fit, resistance training and accident prevention measures can reduce the severity and the number of injuries.
Topics: Accident Prevention; Accidents; Bicycling; Exercise; Sports
PubMed: 36231848
DOI: 10.3390/ijerph191912552