International Journal of Injury Control and Safety Promotion最新文献

Speeding increases the likelihood and severity of road traffic crashes, but many riders do not consider speeding as a serious safety issue. By using belief-based variables derived from the Theory of Planned Behaviour (i.e. behavioural beliefs, normative beliefs, and control beliefs), this study investigated the socio-cognitive determinants of speeding intentions among Vietnamese adolescents operating motorized/electrified two-wheelers. 189 adolescent powered two-wheeled riders in Ho Chi Minh City participated in a cross-sectional survey. The results lend clear support to the Expectancy-Value approach since belief-based product factors (e.g. outcome beliefs x outcome evaluations) significantly and independently contributed to the prediction of speeding intentions. Speeding intentions were mostly influenced by behavioural beliefs, followed by normative beliefs and control beliefs, respectively. This study not only proves the Expectancy-Value approach as an appropriate framework for the investigation of speeding intentions but also supports authorities in the formulation and execution of more effective interventions for reducing speeding among adolescent powered two-wheeled riders in Vietnam. Instead of motivation-oriented methods, there is a need for strategies that stimulate the translation of good intentions into the desirable behaviour, and encourage adolescents not to relapse in case they are exposed to risk facilitating circumstances. Yet, besides focussing on person-specific dispositions towards speeding, policy makers are advised to adopt a more broadly encompassing systemic approach with inclusion of safe roads, safe vehicles, improved post-crash care, and shared stakeholder responsibilities.

Drawing on the core idea of Propensity Score Matching, this study proposes a new concept named Historical Traffic Violation Propensity to describe the driver's historical traffic violations, and combines the new concept with an improved mutual information-based feature selection algorithm to construct a method for screening key traffic violations from the perspective of expressing driver's accident risk. The validation analysis based on the real data collected in Shenzhen demonstrated that drivers' state of Historical Traffic Violation Propensity on 19 key traffic violations screened have a stronger predictive ability of their subsequent accidents compared to the level in existing research. The positive state of Historical Traffic Violation Propensity on 'Drinking', 'Parking in dangerous areas', 'Wrong use of turn lights', 'Violating prohibited and restricted traffic regulations', and 'Disobeying prohibition sign' will increase the probability of a driver's subsequent accident by more than 1.7 times. The research provides directions to more efficiently and accurately capture the driver's accident risk through historical traffic violations, which is valuable for identifying high-risk drivers as well as the key psychological or physical risk factors that manifest in daily driving activities and lead to subsequent accidents.

China has experienced remarkable achievements in terms of reducing the number of extraordinarily severe traffic crashes (ESTCs) that cause more than 10 deaths each crash. However, ESTCs still occur occasionally and result in extremely adverse social impacts. This study aims at investigating the common characteristics, characteristic patterns, and changes of characteristics of ESTCs in China with the expectation to learn from the past and act for the future. A total of 373 ESTCs occurred in 2004-2019 were collected, and characteristics of driver factors, road factors, vehicle factors, environment factors, and other factors were analyzed through the multiple correspondence analysis (MCA). The results show that run off road crashes, not qualified drivers, improper driving, large bus, overload, class II highway, and straight road sections are the most common categories of characteristics. In addition, four underlying characteristic patterns are identified through the MCA. Significant changes in characteristics and characteristic patterns are also found, and these changes are the results of various law enforcement, safety policies, educational interventions, and engineering interventions. It is also inferred that the specific law enforcement targeting to certain category of characteristics is more effective than the corresponding safety campaigns or policies in terms of ESTC prevention.

Road accidents remain a serious problem and directly affect drivers. Therefore, the perspectives of drivers are important in improving road safety. The objectives of this study are to empirically examine damage due to road accidents using the willingness-to-pay (WTP) approach and to analyze the factors that influence WTP at the driver and district levels. This study obtained data on WTP derived from car drivers across Thailand, which covers 96 districts. The value of statistical life was 824,344 USD per fatality (2,296 million USD annually). The results of Multilevel Structural Equation Modeling revealed a statistically important insight. At the driver level, the Health Belief Model and sociodemographic exert influence on the intention to pay. The demographic factor that has the greatest influence on perceived risk and leads to a high intention to pay is the working age group (γ = 0.826). However, when considering the HBM, perceived susceptibility (γ = 0.901) emerges as the most valuable factor influencing drivers' concerns about road accidents. On the other hand, district-level factors have a negative influence on the intention to pay for road safety measures. Among these factors, the law enforcement (γ = -0.555) practices implemented by local authorities have the most significant impact on drivers' perspectives and intentions regarding WTP. This finding can be used as a guideline for budget allocation and policy recommendation for policymakers in improving road safety according to the area contexts.