International Journal of Injury Control and Safety Promotion最新文献

This study simultaneously modelled the injury severity of motorcycle riders and their pillion passengers and determine the associated risk factors. The analysis is based on motorcycle crashes data in Ashanti region of Ghana spanning from 2017 to 2019. The study implemented bivariate ordered probit model to identify the possible risk factors under the premise that the injury severity of pillion passenger is endogenously related to that of the rider in the event of crash. The model provides more efficient estimates by considered the common unobserved factors shared between rider and pillion passenger. The result shows a significant positive relationship between the two injury severities with a correlation coefficient of 0.63. Thus, the unobservable factors that increase the probability of the rider to sustain more severe injury in the event of crash also increase that of their corresponding pillion passenger. The rider and their pillion passenger injury severities have different propensity to some of the risk factors including passengers' gender, day of week, road width and light condition. In addition, the study found that time of day, weather condition, collision type, and number of vehicles involved in the crash jointly influence the injury severity of both rider and pillion passenger significantly.

Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted a comparative analysis of risk factors in crashes between traditional taxi drivers and ride-hailing taxi drivers in China, including their demographic characteristics, working conditions, and risky driving behaviors. The data was collected from 2,039 traditional taxi drivers and 2,182 ride-hailing taxi drivers via self-reported questionnaires. Four XGBoost models were established, taking into account different types of taxi drivers and crash types. All models showed acceptable performance, and SHAP explainer was used to analyze the model results. The results showed that for both taxi drivers, risk factors related to risky driving behaviors are more important in predicting property damage (PD) crashes, while risk factors related to working conditions are more important in predicting person injury (PI) crashes. However, the relative importance of each risk factor varied depending on the type of crashes and the type of taxi drivers involved. Furthermore, the results also validated certain interactions among the risk factors, indicating that the combination of certain factors generated a greater impact on crashes compared to individual factors alone. These findings can provide valuable insights for formulating appropriate measures to enhance road safety for taxi driver.

In-lane street hawking is the intermittent entry of signalized intersections by traders to sell groceries to drivers and passengers. Studies have shown that hawkers get exposed to traffic injuries but the lack of quantitative analysis of their lane entry and exit behaviors in signalized intersections makes it difficult to improve traffic safety. This study analyzes the significant predictors of in-lane street hawkers' (1) lane entry within 30 s after the red signal illumination, (2) lane exit within 30 s after the green signal illumination, and (3) probability of getting injuries during the green signal time. Drone-based trajectory data were collected from a selected signalized intersection in Accra, Ghana. A Weibull accelerated failure time duration model incorporating Gamma frailty was used to evaluate hawkers' behaviors. Overall, the majority of hawkers exhibited red-light running behaviors exposing them to traffic injuries. An increase in traffic speed, especially beyond 20 km/h, exposed hawkers to injury risks significantly. Notably, hawkers' lane entry decreased significantly as the traffic speed increased. Their lane exit duration was significantly predicted by the queue lengths and traffic volumes. Accordingly, safety practitioners can enhance traffic regulation and control methods in addition to pro-poor social interventions to demotivate hawking at signalized intersections.

Traffic violation is one of the leading causes of traffic crashes. In the context of global aging, it is important to study traffic violations by elderly drivers for improving traffic safety in preparation for a worldwide aging population. In this study, a hybrid approach of Latent Class Analysis (LCA) and XGBoost based SHAP is proposed to identify hidden clusters and to understand the key contributing factors on the severity of traffic violations by elderly drivers, based on the police-reported traffic violation dataset of Beijing (China). First, LCA is applied to segment the dataset into several latent homogeneous clusters, then XGBoost based SHAP is established on each cluster to identify feature contributions and the interaction effects of the key contributing factors on the severity of traffic violations by elderly drivers. Two comparison groups were set up to analyze factors, which are responsible for the different severities of traffic violations. The results show that elderly drivers can be classified into four groups by age, urban or not, license, and season; factors such as less annual number of traffic violations, national & provincial highway, night and winter are key contributing factors for higher severity of traffic violations, which are consistent with common cognition; key contributing factors for all clusters are similar but not identical, for example, more annual number of traffic violations contribute to more severe violation for all clusters except for Cluster 2; some factors which are not key contributing factors may affect the severity of traffic violations when they are combined with other factors, for example, the combination of lower annual number of traffic violations and county & township highway contributes to more severe violation for Cluster 1. These findings can help government to formulate targeted countermeasures to decrease the severity of traffic violations by specific elderly groups and improve road service for the driving population.

Road traffic crashes (RTCs) are significantly high in Nigeria with serious social and health consequences. While existing studies on RTCs have mainly focused on the effect of socio-economic, environmental, human and mechanical factors to address the high rates, the relationship between road transport fares and RTCs has been glossed over in literature. Thus, this study examines the influence of road transport fares and other covariates on RTCs. Data on RTCs and the predictors between 2017 and 2022 were obtained from the records of the National Bureau of Statistics and the Federal Road Safety Corps. Spatial statistical techniques were used for the data analysis. RTCs vary across the country, and Northern Nigeria is the hot spot. Results from the spatial analysis show that road transport fares, population density, and illiteracy rate are significant predictors of RTCs. The study recommends striking a balance between fare affordability, the quality of service provided, and the implementation of effective transportation strategies.

Pivotal crash factors are investigated, and crash-severity model for the safety assessment at roundabouts and its vicinity in non-lane based heterogenous traffic is developed. An ordered-probit model was developed using crash-data collected between 2015-2019 for 20 roundabouts in India. The analysis revealed critical influencing parameters for determining the severity-level of crash outcomes at roundabouts, namely, inscribed-circle diameter, height of central island, number of circulatory lanes, presence of splitter island and median, posted-speed limit, type of collision, type of violation behaviour, collision partner, the pattern of collision, presence of road lane-marking, presence of street-light and age of victims. To precisely quantify the impact of each significant factor, marginal effects analysis was also carried out. The results show that the probability of fatal-injuries increased by 14.28% due to angle-collision, 15% for hit-pedestrians, 20.6% due to the pattern of collision and 15.60% due to the collision-partner, Whereas the probability of occurrence of grievous injury was the highest for rear-end with 17%, followed by sideswipe collision with 16% respectively. This study's findings can aid in developing effective remedies to reduce the crash severity for roundabouts road-users and updating the roundabout design standards, considering the safety perceptive.

This paper investigates the factors influencing the severity of driver injuries in single-vehicle speeding-related crashes, by comparing different driver age groups. This study employed a random threshold random parameter hierarchical ordered probit model and analysed crash data from Thailand between 2012 and 2017. The findings showed that young drivers face a heightened fatality risk when speeding in passenger cars or pickup trucks, hinting at the role of inexperience and risk-taking behaviours. Old drivers exhibit an increased fatality risk when speeding, especially in rainy conditions, on flush median roads, and during evening peak hours, attributed to reduced reaction times and vulnerability to adverse weather. Both young and elderly drivers face escalated fatality risks when speeding on road segments lacking guardrails during adverse weather, with older drivers being particularly vulnerable in rainy conditions. All age groups show an elevated fatality risk when speeding on barrier median roads, underscoring the significant role of speeding, which increases crash impact and limits margins of error and manoeuvrability, thereby highlighting the need for safety measures focusing on driver behaviour. These findings underscore the critical imperative for interventions addressing not only driver conduct but also road infrastructure, collectively striving to curtail the severity of speeding-related crashes.

Cell phone use while walking escalates pedestrian safety risks, particularly among students, given their heavy reliance on these devices. Psychological factors wield significant influence on individual behavior, particularly among adolescents who navigate a blend of rational and social-reactive pathways in decision-making. Therefore, this paper employs the Prototype Willingness Model (PWM) to scrutinize psychological determinants of students' cell phone use while walking, drawing on data from 368 valid samples. Structural equation modeling (SEM) dissects the impact of psychological constructs on this behavior, highlighting the significance of both the social response and reasoning pathways within PWM. The study comprehensively analyzes direct, indirect, and overall effects of exogenous variables on behavioral intention and behavior.

Delivery riders are more vulnerable than other traffic participants, especially in vehicle-involved delivery crashes. This study aims at identifying the unobserved heterogeneities in different factors, based on 4251 vehicle-scooter-style electric bicycle (SSEB) crashes. First, some potential factors are selected from seven perspectives, and the spatiotemporal characteristics are analysed. Second, a latent class clustering method is proposed to clarify the optimal number of clusters by maximizing the heterogeneities across clusters. Third, partial proportional odds (PPO) models for the whole dataset and sub-datasets are developed to explore the heterogeneities across various clusters. Besides, marginal effects are implemented to quantify the heterogeneities. The results evidence that there are remarkable heterogeneities across different clusters, especially in riding behaviours and road conditions. Several factors only significantly affect particular clusters but not the whole dataset. The PPO models for the sub-datasets perform better in identifying the underlying heterogeneities. The results also highlight the greater roles of riding behaviours and road conditions in delivery SSEB-vehicle crashes. The top five influencing factors are running red light, using cell phones, vehicle type, reverse riding and bike lane (their maximum marginal effects exceeding +35%). The findings could support to mitigate the related crash losses.

Road traffic injuries (RTIs) are a significant cause of death and disability among young people worldwide. Programs that use injury prevention strategies have been shown to effectively reduce the number of injuries. This systematic review aims to present the available evidence on the effectiveness of intervention programs in preventing RTIs among adolescents and young adults. Articles were identified and retrieved from databases including PubMed, Embase, Web of Science, Scopus, Science Direct, Magiran, SID, and Iran Medex. Two reviewers independently screened the articles. Articles published from the first year of publication until January 2018 that met the eligibility criteria were included in the review. These articles covered randomized controlled trials, pretest/post-test interventions, and controlled pretest/post-test interventions aimed at reducing RTIs among adolescents and young people aged 12-26 years. The framework, provided by Murphy and Haddon, were used to categorize the interventions. According to this framework, the interventions were categorized into five groups including education/behavior change, incentive, engineering/technology, legislation/enforcement, and multifaceted programs. The methodological quality of the studies was assessed using the Effective Public Health Practice Project. Of the initial 3165 findings, 13 studies met the inclusion criteria. Eleven of these studies used educational/behavioral approaches, while two employed multifaceted programs. In the educational/behavioral approach, participants' behaviors were considered as outcome variables. Only one of these studies was not successful. Multifaceted interventions were successful in changing behaviors. No studies were found on the effectiveness of other interventions. Eight studies were assessed as having moderate quality. The systematic review shows that educational/behavioral strategies and multifaceted programs are effective in reducing RTIs among young adults and adolescents. However, there is a lack of studies on other potential interventions. The quality of the included studies was moderate, suggesting a need for more rigorous research.