系统理论指导下的安全研究?

IF 2.3 4区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Injury Control and Safety Promotion Pub Date : 2023-06-01 DOI:10.1080/17457300.2023.2210424
Geetam Tiwari
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The study presents the development of crash prediction models by assessing the roles of vehicles, both as impacting vehicle and victim, using historical crash data. The study compares the binary logistic regression model and the artificial neural network (ANN) method to understand the role of vehicle type in crashes. The authors have discussed the strengths and limitations of both methods, which is useful for other researchers. It has been observed that heavy vehicles and two-wheelers are prone to contribute to a large number of road accidents. While the involvement of heavy vehicles as impacting vehicles has been listed in many earlier studies, the role of two wheelers as an impacting vehicle is an important new insight, and an area where new research is required for preventive interventions. The assessment of actual traffic crash risk and the perceived traffic crash risk by different road users and their behaviours on the road has been studied by many researchers. Understanding of both risks is important since our behaviour is influenced by our perception; however, there could be many other contributory factors for actual traffic crash risk, such as road geometry, traffic mix and other factors. Sinao Sahebi et al studied the driving risk perception of drivers, whereas Ramachandra et al have analysed the actual risk to pedestrians near bus stops. Sinao Sahebi et al from Iran, studied the driving risk perception of road accidents of truck and car drivers, and their views on the possible association with resulting in fatality or severe injury. The authors developed a bivariate ordered probit model to better examine the distinction between perceived risk and objective risk. The study shows that several factors, like vehicle type and age, driving experience, and education levels, have important effects on the drivers’ risk perception, while (say) the road geometry would be an important factor in the measurement of the objective risk. K. Ramachandra Rao, et al, studied the risk assessment for pedestrians posed by the built environemnt in the vicinity of bus-stops. The present case study of Delhi city, is supported by video-graphic material and the relevant manual field survey conducted during the day-time and the night-time. 177 bus stop sites were chosen for study within high-crash clusters, following the hotspot analysis that the authors conducted. The study suggests implementation of important strategies in the built environments around bus stops that could minimise pedestrian injuries and fatalities in other cities with similar road infrastructures. Maria Rella Riccardi, et al, from Italy, have sent in an analysis of the contributory factors to fatal pedestrian crashes, making them the most vulnerable road users. This is in part because the road system is designed with vehicular traffic in mind. The study analysed around 100,000 pedestrian crashes in Italy over a five year period. The study used both, the econometric and the mixed logit models, a machine learning algorithm, and the association rule discovery in conjunction with each other, to arrive at more effective safety counter-measures. M. Ashifur Rahman, et al, from USA and China, have analysed the characteristics of crashes related to animals on the roadways, which is an area little studied, if not ignored. The unexpected appearance of an animal on the road may result in an animal-vehicle crash or in the vehicle making an unplanned manoeuvre that causes a roadway departure. The suggested counter-measures include, among others, speed management and retro-reflective warning signs on unlit, rural roads. Mesafint Molla Adane, et al, from Ethiopia, studied cooking-related burn injuries of children less than five years of age. Fire related burn injuries are estimated to annually cause ten million disability-adjusted life years lost worldwide. 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It has been observed that heavy vehicles and two-wheelers are prone to contribute to a large number of road accidents. While the involvement of heavy vehicles as impacting vehicles has been listed in many earlier studies, the role of two wheelers as an impacting vehicle is an important new insight, and an area where new research is required for preventive interventions. The assessment of actual traffic crash risk and the perceived traffic crash risk by different road users and their behaviours on the road has been studied by many researchers. Understanding of both risks is important since our behaviour is influenced by our perception; however, there could be many other contributory factors for actual traffic crash risk, such as road geometry, traffic mix and other factors. Sinao Sahebi et al studied the driving risk perception of drivers, whereas Ramachandra et al have analysed the actual risk to pedestrians near bus stops. Sinao Sahebi et al from Iran, studied the driving risk perception of road accidents of truck and car drivers, and their views on the possible association with resulting in fatality or severe injury. The authors developed a bivariate ordered probit model to better examine the distinction between perceived risk and objective risk. The study shows that several factors, like vehicle type and age, driving experience, and education levels, have important effects on the drivers’ risk perception, while (say) the road geometry would be an important factor in the measurement of the objective risk. K. Ramachandra Rao, et al, studied the risk assessment for pedestrians posed by the built environemnt in the vicinity of bus-stops. 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Safety research guided by systems theory?
This volume brings a mix of studies ranging from pedestrian crashes, risk perceptions, black spot analyses, and motorcycle crashes from the area of motor vehicle injuries, to children drowning, cooking related burn injuries, and emergency response by rescue agencies. The study of pedestrian and motorcycle crashes both continue to be important in all countries in general, and specifically for low and middle income countries, where nearly 50-60% of fatalities involve pedestrians and motorcycles (World Health Organization (WHO),) 2018). The importance of robust data and methods producing strong evidence for effective interventions must be recognized by all researchers and other stakeholders. Malaya Mohanty, et al, from India, have studied road traffic crashes in a medium size city in India. The study presents the development of crash prediction models by assessing the roles of vehicles, both as impacting vehicle and victim, using historical crash data. The study compares the binary logistic regression model and the artificial neural network (ANN) method to understand the role of vehicle type in crashes. The authors have discussed the strengths and limitations of both methods, which is useful for other researchers. It has been observed that heavy vehicles and two-wheelers are prone to contribute to a large number of road accidents. While the involvement of heavy vehicles as impacting vehicles has been listed in many earlier studies, the role of two wheelers as an impacting vehicle is an important new insight, and an area where new research is required for preventive interventions. The assessment of actual traffic crash risk and the perceived traffic crash risk by different road users and their behaviours on the road has been studied by many researchers. Understanding of both risks is important since our behaviour is influenced by our perception; however, there could be many other contributory factors for actual traffic crash risk, such as road geometry, traffic mix and other factors. Sinao Sahebi et al studied the driving risk perception of drivers, whereas Ramachandra et al have analysed the actual risk to pedestrians near bus stops. Sinao Sahebi et al from Iran, studied the driving risk perception of road accidents of truck and car drivers, and their views on the possible association with resulting in fatality or severe injury. The authors developed a bivariate ordered probit model to better examine the distinction between perceived risk and objective risk. The study shows that several factors, like vehicle type and age, driving experience, and education levels, have important effects on the drivers’ risk perception, while (say) the road geometry would be an important factor in the measurement of the objective risk. K. Ramachandra Rao, et al, studied the risk assessment for pedestrians posed by the built environemnt in the vicinity of bus-stops. The present case study of Delhi city, is supported by video-graphic material and the relevant manual field survey conducted during the day-time and the night-time. 177 bus stop sites were chosen for study within high-crash clusters, following the hotspot analysis that the authors conducted. The study suggests implementation of important strategies in the built environments around bus stops that could minimise pedestrian injuries and fatalities in other cities with similar road infrastructures. Maria Rella Riccardi, et al, from Italy, have sent in an analysis of the contributory factors to fatal pedestrian crashes, making them the most vulnerable road users. This is in part because the road system is designed with vehicular traffic in mind. The study analysed around 100,000 pedestrian crashes in Italy over a five year period. The study used both, the econometric and the mixed logit models, a machine learning algorithm, and the association rule discovery in conjunction with each other, to arrive at more effective safety counter-measures. M. Ashifur Rahman, et al, from USA and China, have analysed the characteristics of crashes related to animals on the roadways, which is an area little studied, if not ignored. The unexpected appearance of an animal on the road may result in an animal-vehicle crash or in the vehicle making an unplanned manoeuvre that causes a roadway departure. The suggested counter-measures include, among others, speed management and retro-reflective warning signs on unlit, rural roads. Mesafint Molla Adane, et al, from Ethiopia, studied cooking-related burn injuries of children less than five years of age. Fire related burn injuries are estimated to annually cause ten million disability-adjusted life years lost worldwide. This exploratory research of 5830 under-five year-olds in low and middle income countries shows that children, rather than adults, bear the burden of cooking related injuries due to low literacy, poor supervision and other such factors. Samed Bulbulia, et al, from South Africa have made a presentation on the mortality of children aged up to fourteen years of age as pedestrians, by drowning, and by burn injuries. Over a ten-year period in Johannesburg, the research recorded 756 pedestrian, 439 drowning and 399 burn injury deaths. The study examined the extent, demographics, risks and temporal circumstances of these fatalities. The authors suggest that targeted safety measures should become a part of the development agenda of all urban centres.
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来源期刊
International Journal of Injury Control and Safety Promotion
International Journal of Injury Control and Safety Promotion PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
4.40
自引率
13.00%
发文量
48
期刊介绍: International Journal of Injury Control and Safety Promotion (formerly Injury Control and Safety Promotion) publishes articles concerning all phases of injury control, including prevention, acute care and rehabilitation. Specifically, this journal will publish articles that for each type of injury: •describe the problem •analyse the causes and risk factors •discuss the design and evaluation of solutions •describe the implementation of effective programs and policies The journal encompasses all causes of fatal and non-fatal injury, including injuries related to: •transport •school and work •home and leisure activities •sport •violence and assault
期刊最新文献
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