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This is a protocol for a scoping review that seeks to identify, quantify and summarize the existing evidence-base on preventative strategies and interventions in neurotrauma, particularly for Road Traffic collisions

This paper applies the Kuznets (1955) curve approach to road traffic crashes in Algeria based on active population, motorization rate, income per capita, and land artificialization. It aims to establish a link between economic development and road safety by estimating the terms of quadratic equations related to the occurrence of traffic collisions. The results reveal that a link between economic development and road safety can be validated by two econometric specifications for the Kuznets curve (KC). Indeed, because economic conditions remained favorable, the Algerian economy reached its inflection point in 2011 and then entered the second phase of the KC. The increase in the level of economic development then in turn led to an improved road-safety situation in terms of lower mortality rates on the roads.

With the progressive ageing of the population, the study of the relations between road safety and elderly users is becoming increasingly relevant. Although the decline of pedestrian skills in the elderly has been widely studied in the literature, few studies have been devoted to the contributing built environmental factors of the elderly pedestrian collisions, such as the sidewalk density, the presence of traffic lights, or even some indicator related to land use or the socioeconomic features of the urban fabric. This paper contributes to the limited literature on elderly pedestrian safety by applying a negative binomial regression to a set of built environmental variables to study the occurrence of accidents involving elderly and younger (non-elderly) pedestrians in Madrid (Spain) between 2006 and 2018. The model considers a selection of built environmental factors per city district, linked to land use, infrastructure, and socioeconomic indicators. Results have highlighted that the elderly pedestrian collisions could be avoided with the existence of a wider sidewalk in the district and a greater traffic lights density. Unlike younger pedestrian accidents, these accidents are much more favored in ageing districts with higher traffic flows. Daniel Gálvez-Pérez is developing his doctoral thesis while he enjoys a grant from to the Universidad Politécnica de Madrid through the “Programa Propio de I + D + I 2020: Ayudas para Contratos Predoctorales”.

Background Road traffic accidents are a major global concern that affects all people regardless of their age, sex, wealth, and ethnicity. Injuries and deaths due to motorcycles are increasing, especially in developing countries. Wearing helmet is effective in reducing deaths and injuries caused by motorcycle accidents. Objectives To assess the magnitude of helmet wearing behavior and its determinants among motorcycle riders in Sawula and Bulky towns, Gofa zone, Southern Ethiopia. Methods A community-based cross-sectional study was conducted from April, 15 to May 25, 2020, among 422 motorcycle drivers in Sawula and Bulky towns, where people often drive motorcycles. A stratified sampling technique was used to recruit sampled drivers in a face-to-face interview. Data were entered into EPI-data version 3.1 software and exported to SPSS version 23 software to manage analysis. Descriptive analyses such as frequency, percentage, mean and standard deviation were performed as necessary. Logistic regression models were fitted to identify the predictors of helmet wearing behavior. Adjusted odds ratios (AOR) with 95% confidence interval (CI) were used to determine the magnitude and strength of the association. Results A total of 403 motorcycle drivers participated in the study which gave a 95.5% response rate. Among 403 motorcycle riders, only 12.4% (95% CI, 9.2 to 15.6%) wore helmets while driving motorcycles. Having license [AOR 3.51(95% C.I 1.56–7.89)], driving distance >10Km [AOR 2.53(95% C.I 1.08–5.91)], History of exposure to accident [AOR 2.71(95% C.I 1.32–5.55)], driving experience of ≥10 years [AOR 2.98 (95% C.I 1.25–7.09)] and high perceived susceptibility to accident [AOR 3.10(95% C.I 1.29–7.46)] had statistically significant association with helmet wearing compared to their counterparts. Conclusions This study found that helmet-wearing behavior was very low. Having a license, driving distance, exposure to accidents, driving experience, and accident risk perception were determinants of helmet wearing behavior. These determinants imply the need for interventions that focus on behavioral change communications such as awareness creation campaigns and mandatory helmet wearing laws.

To undertake a reliable analysis of injury severity in road traffic accidents, a complete understanding of important attributes is essential. As a result of the shift from traditional statistical parametric procedures to computer-aided methods, machine learning approaches have become an important aspect in predicting the severity of road traffic injuries. The paper presents a hybrid feature selection-based machine learning classification approach for detecting significant attributes and predicting injury severity in single and multiple-vehicle accidents. To begin, we employed a Random Forests (RF) classifier in conjunction with an intrinsic wrapper-based feature selection approach called the Boruta Algorithm (BA) to find the relevant important attributes that determine injury severity. The influential attributes were then fed into a set of four classifiers to accurately predict injury severity (Naive Bayes (NB), K-Nearest Neighbor (K-NN), Binary Logistic Regression (BLR), and Extreme Gradient Boosting (XGBoost)). According to BA’s experimental investigation, the vehicle type was the most influential factor, followed by the month of the year, the driver’s age, and the alignment of the road segment. The driver’s gender, the presence of a median, and the presence of a shoulder were all found to be unimportant. According to classifier performance measures, XGBoost surpasses the other classifiers in terms of prediction performance. Using the specified attributes, the accuracy, Cohen’s Kappa, F1-Measure, and AUC-ROC values of the XGBoost were 82.10%, 0.607, 0.776, and 0.880 for single vehicle accidents and 79.52%, 0.569, 0.752, and 0.86 for multiple-vehicle accidents, respectively.

Distracted driving behavior is one of the main factors of road accidents. Accurately predicting the risk of driving behavior is of great significance to the active safety of road transportation. The large amount of information collected by the sensors installed on the vehicle can be identified by the algorithm to obtain the distracted driving behavior data, which can be used to predict the driving behavior risk of the vehicle and the area. In this paper, a new neural network named Driving Behavior Risk Prediction Neural Network (DBRPNN) is developed for prediction based on the distracted driving behavior data. The network consists of three modules: the Feature Processing Module, the Memory Module, and the Prediction Module. In this process, attribute data (time in a day, daily driving time, and daily driving mileage) that can reflect external factors and driver statuses, are added to the network to increase the accuracy of the model. We predicted the driving behavior risk of different objects (Vehicle and Area). For the applicability improvement of the model, we further classify the distracted driving behavior categories, and DBRPNN can provide more accurate risk prediction. The results show that compared with traditional models (Classification and Regression Tree, Support Vector Machines, Recurrent Neural Network, and Long Short-Term Memory), DBRPNN has better prediction performance. The method proposed in this paper has been fully verified and may be transplanted into active safety early warning system for more accurate and flexible application.

ObjectiveSurge capacity refers to preparedness of health systems to face sudden patient inflows, such as mass-casualty incidents (MCI). To strengthen surge capacity, it is essential to understand MCI epidemiology, which is poorly studied in low- and middle-income countries lacking trauma databases. We propose a novel approach, the "systematic media review", to analyze mass-trauma epidemiology; here piloted in Rwanda.MethodsA systematic media review of non-academic publications of MCIs in Rwanda between January 1st, 2010, and September 1st, 2020 was conducted using NexisUni, an academic database for news, business, and legal sources previously used in sociolegal research. All articles identified by the search strategy were screened using eligibility criteria. Data were extracted in a RedCap form and analyzed using descriptive statistics.FindingsOf 3187 articles identified, 247 met inclusion criteria. In total, 117 MCIs were described, of which 73 (62.4%) were road-traffic accidents, 23 (19.7%) natural hazards, 20 (17.1%) acts of violence/terrorism, and 1 (0.09%) boat collision. Of Rwanda's 30 Districts, 29 were affected by mass-trauma, with the rural Western province most frequently affected. Road-traffic accidents was the leading MCI until 2017 when natural hazards became most common. The median number of injured persons per event was 11 (IQR 5-18), and median on-site deaths was 2 (IQR 1-6); with natural hazards having the highest median deaths (6 [IQR 2-18]).ConclusionIn Rwanda, MCIs have decreased, although landslides/floods are increasing, preventing a decrease in trauma-related mortality. By training journalists in "mass-casualty reporting", the potential of the "systematic media review" could be further enhanced, as a way to collect MCI data in settings without databases.

Background: Unlike some neighboring countries like Nigeria, few studies on actual causes, impact and the prevention of road traffic collisions have been carried out in Ghana. There is the need for further research and this study sought to link injuries that caused the death of drivers involved in vehicular collisions to the latent possible contributing diseases and medical conditions in these drivers and how these conditions predispose them to the collisions. Methods: This is a retrospective study that used the forensic autopsy records of driver fatalities and various injuries and medical conditions of drivers involved in road traffic collisions. Information on all drivers was retrieved from archives at the Komfo Anokye Teaching Hospital’ Pathology Unit. Demographics and cause of death were used in selecting the cases, including all driver-related road traffic collisions from 2009 to 2014. Results: A total of 1842 road traffic collisions were recorded with 127 of them being driver related. There were 31 cases (24.4%) in 2014; the highest cases recorded for this study, with the least recorded in 2009 with only 12 cases (9.4%). There were 121 (95.3%) male drivers and 6 female drivers (4.7%). Most of the male drivers were between the ages of 30 and 39 with 39 cases, while that of females was between 40 and 49 years with 6 cases. There was no significant statistical correlation between age and sex ( P = .124). No statistical correlation also existed between sex and year ( P = .331). Pathologies of all body systems were established. Cardiovascular diseases were the most prevalent systemic medical condition seen in the drivers with 44.1%. Conclusion: The study established that the drivers had various latent medical conditions and all these could lead to possible incapacitation, affecting driver judgment, leading to collisions on the road. The National Road Safety Commission (NRSC) should request medical screening before issuing driver licenses.

Background Pedestrian and cyclist injuries are a major concern globally, but especially in low-income countries. Locally conducted research is needed to measure the size of the problem and advise policy on road safety interventions. We wanted to investigate the precise circumstances of these injuries in Lilongwe, Malawi and to identify risk factors for severe injuries. Methods Cross-sectional study of all adult pedestrian and cyclist injuries presenting to a large central hospital. This was a sub-study of a larger study with all types of road users included. All patients provided detailed information about the incidents leading to injury and were tested for alcohol. Results There were 222 pedestrians, 183 bicycle riders and 42 bicycle passengers among the 1259 adult road traffic injury victims that were treated at Kamuzu Central Hospital during a 90-day period in 2019. Of these injuries, 60.2% occurred while the victim was walking/cycling along the road and 22.3% when the victim was trying to cross the road. The majority of the victims were men (89.1%). Helmet use for bicyclists was almost non-existent. Only 1 patient had used reflective devices when injured in the dark, despite 44.7% of these injuries occurring in reduced light conditions. There was an increased risk for serious and fatal injuries for pedestrians compared with bicyclists, and also compared with all types of road users. Patients injured in rural areas and those hit by lorries were more severely injured. Consuming alcohol before being injured was associated with more severe injuries in bicyclists. Being injured while crossing the road at painted zebra crossings was associated with an increased risk of serious and potentially fatal injuries. Conclusion This study identified important risk factors for severe injuries in pedestrians and cyclists. Implications for preventive measures are presented in a Haddon Matrix.

This study analyzed factors influencing clinical symptoms and treatment of patients with traffic accident injuries. It used a retrospective chart review and questionnaire survey obtained from 560 patients (266 men and 294 women). It also conducted follow-up observations of progress after car insurance settlements and investigated the usefulness of and patient satisfaction with integrative Korean medicine treatment for traffic accident injuries. Retrospective data of patients admitted for traffic accident injury were obtained. A questionnaire survey was conducted to collect data regarding the degree of traffic accident damage, severity of pain at settlement, any treatment after settlement and duration and cost of such treatment, and patient satisfaction with car insurance services and Korean medicine treatment for traffic accident injury. The results showed no significant association between pain and the degree of damage to the car at the time of traffic accident (P = 0.662), although the degree of damage to the car was more significantly associated with time to reach a car insurance settlement than severity of pain in the patient (P = 0.003). There was no significant association between the degree of damage to the car in a traffic accident and pain after a traffic accident. Greater severity of pain at the time of the car insurance settlement was associated with greater cost and longer time spent in treatment after the car insurance settlement.

The purpose of this study was to develop a driving behavior scale for professional drivers of heavy semi-trailer trucks in China, and study the causes of such driving behavior and its impact on traffic safety operation. Data was processed by IBM SPSS 25. In addition to principal component analysis, Promax rotation, Bartlett’s test, Cronbach’s alpha, correlation analysis and binary logistic regression were examined. A DBQ with 4 dimensions and 20 items, and a PDBQ with 1 dimension and 6 items were developed for professional drivers of heavy semi-trailer trucks in China. The KMO coefficients of PDBQ and DBQ were 0.822 and 0.852, respectively, and the significant level of Bartlett’s popularity test was p < 0.0001. The accident prediction model showed that the variables related to traffic accidents were negligence/lapses and driving time of heavy semi-trailer truck drivers. 1–5 a.m. was found to be the most dangerous period for drivers of medium and heavy semi-trailer trucks, during which accidents were most likely to happen. As negligence/lapses increased by one unit, the probability of traffic accidents increased by 2.293 times.

Although most fatalities in tsunami-related disasters are conjectured to be a result of drowning, injury risk owing to collision with other floating debris or fixed buildings has not been studied sufficiently. In this study, the impact force corresponding to the collision of a concrete block and drifting test body in a tsunami wave was experimentally investigated, and the injury risk was evaluated in terms of different biomechanical indexes; specifically, maximum acceleration, head injury criterion, and impact force. The injury risk indicated by the considered indexes was reasonably low. It was noted that if a healthy adult collided with a concrete wall under a velocity of 2.5 m s-1 and wave height of 0.59 m, the adult would likely not be critically injured. However, a similar collision impact poses considerable risk to infants and children, as well as the more sensitive regions of the adult body. Moreover, in the case of large tsunamis, such as that in the 2011 Great East Japan Earthquake, a drifting person may be at considerable risk for injuries. The collision impact occurring on the tip of a surge flow is notably significantly larger than that on a bore flow. This is because a surge flow, which arrives at the concrete block earlier than a bore flow, forms a certain water layer along the concrete wall and that layer acts as a cushion for any body drifting on the bore flow, indicating the importance of such a buffering effect. These findings can provide practical guidance regarding the formulation of effective tsunami-protection measures.

Empirical study of road traffic collision (RTCs) rates is challenging at small geographies due to the relative rarity of collisions and the need to account for secular and seasonal trends. In this paper, we demonstrate the successful application of Hidden Markov Models (HMMs) and Generalised Additive Models (GAMs) to describe RTCs time series using monthly data from the city of Edinburgh (STATS19) as a case study. While both models have comparable level of complexity, they bring different advantages. HMMs provide a better interpretation of the data-generating process, whereas GAMs can be superior in terms of forecasting. In our study, both models successfully capture the declining trend and the seasonal pattern with a peak in the autumn and a dip in the spring months. Our best fitting HMM indicates a change in a fast-declining-trend state after the introduction of the 20 mph speed limit in July 2016. Our preferred GAM explicitly models this intervention and provides evidence for a significant further decline in the RTCs. In a comparison between the two modelling approaches, the GAM outperforms the HMM in out-of-sample forecasting of the RTCs for 2018. The application of HMMs and GAMs to routinely collected data such as the road traffic data may be beneficial to evaluations of interventions and policies, especially natural experiments, that seek to impact traffic collision rates. Publisher PDF

IntroductionNeurotrauma is an important but preventable cause of death and disability worldwide, with the majority being associated with road traffic collisions (RTCs). The greatest burden is seen in low -and middle- income countries (LMICs) where variations in the environment, infrastructure, population and habits can challenge the success of conventional preventative approaches. It is therefore necessary to understand local perspectives to allow for the development and implementation of context-specific strategies which are effective and sustainable.MethodsThis study took place in Colombia where qualitative data collection was carried out with ten key informants between October and November 2019. Semi-structured interviews were conducted and explored perceptions on RTCs and neurotrauma, preventative strategies and interventions, and the role of research in prevention. Interview transcripts were analysed by thematic analysis using a framework approach.ResultsParticipants’ confirmed that RTCs are a significant problem in Colombia with neurotrauma as an important outcome. Human and organisational factors were identified as key causes of the high rates of RTCs. Participants described the current local preventative strategies, but were quick to discuss limitations and challenges to their success. Key barriers reported were poor attitudes and knowledge, particularly in the community. Suggestions were provided on ways to improve prevention through better education and awareness, stricter enforcement and new policies on prevention, proper budgeting and resource allocation, as well as through collaboration and changes in attitudes and leadership. Participants identified four key research areas they felt would influence prevention of RTCs and associated neurotrauma: causes of RTCs; consequences and impact of RTCs; public involvement in research; improving prevention.ConclusionRTCs are a major problem in Colombia despite the current preventative strategies and interventions. Findings from this study have a potential to influence policy, practice and research by illustrating different solutions to the challenges surrounding prevention and by highlighting areas for further research.

Background Globally, road traffic accidents are the leading causes of death among young people in general, and the main cause of death among young people aged 15–29 years. Recently, in Ethiopia, the number of road traffic accidents has been increasing. The study aimed to identify the potential factors associated with the number of human deaths by road traffic accidents in the Oromia Regional State, Ethiopia. Methods We used data obtained from the Oromia region traffic police office recorded on daily basis road traffic accidents from July 2016 up to July 2017. Count regression models were was used to analyses the factors associated with the number of human deaths from road traffic accidents. Results Age of the driver’s 31–50 years (AOR = 0.289, 95%CI: 0.175, 0.479) and higher than 50 years old (AOR = 0.311, 95%CI: 0.129, 0.751), driver’s years of experience 5–10 years (AOR = 0.014, 95%CI: 0.007, 0.027), and more than 10 years (AOR = 0.101, 95%CI: 0.057, 0.176), automobile vehicle type (AOR = 8.642, 95%CI: 2.7644, 27.023), vehicle years of service 5–10 years (AOR = 2.484, 95%CI: 1.194, 5.169), and more than 10 years (AOR = 2.639, 95%CI: 1.268, 5.497), vehicle upside down accidents (AOR = 5.560, 95%CI: 2.506, 12.336), turning illegal position (AOR = 0.454, 95%CI: 0.226, 0.913), residential areas (AOR = 108.506, 95%CI: 13.725, 857.798), and working areas (AOR = 129.606, 95%CI: 16.448, 1021.263) were significant associated number of human deaths per road traffic accident factors in the study area. Conclusion Human deaths per road traffic accidents occurred due to the younger age of the driver, driver’s lack of sufficient experience, vehicle serviced for long years, driving on a wet road, driving in the afternoon, driving near/around residential places and vehicle to driver’s relation. Thus, the regional traffic police should give special attention to younger drivers, less experienced drivers, old vehicles, driving near residential areas, driving automobiles, and driving in the afternoon to control traffic system to reduce the number of human deaths pear road traffic accident.

When meteorological conditions deviate from the optimal range for human well-being, the risks of illness, injury, and death increase, and such impacts are feared in particular with more frequent and intense extreme weather conditions resulting from climate change. Thermal indices, such as the universal thermal climate index (UTCI), can better assess human weather-related stresses by integrating multiple weather components. This paper quantifies and compares the seasonal and spatial association of UTCI with mortality, morbidity, and road accidents in the federal state of Bavaria, Germany. Linear regression was applied to seasonally associate daily 56 million hospital admissions and 2.5 million death counts (1995-2015) as well as approximately 930,000 road accidents and 1.7 million people injured (2002-2015) with spatially interpolated same day- and lagged- (up to 14 days) average UTCI values. Additional linear regressions were performed stratifying by age, gender, region, and district. UTCI effects were clear in all three health outcomes studied: Increased UTCI resulted in immediate (1-2 days) rises in morbidity and even more strongly in mortality in summer, and lagged (up to 14 days) decreases in fall, winter, and spring. The strongest UTCI effects were found for road accidents where increasing UTCI led to immediate decreases in daily road accidents in winter but pronounced increases in all other seasons. Differences in UTCI effects were observed e.g. between in warmer north-western regions (Franconia, more districts with heat stress-related mortality, but hospital admissions for lung, heart and external reasons decreasing with summer heat stress), the touristic alpine regions in the south (immediate effect of increasing UTCI on road accidents in summer), and the colder south-eastern regions (increasing hospital admissions for lung, heart and external reasons in winter with UTCI). Districts with high percentages of elderly suffered from higher morbidity and mortality, particularly in winter. The influences of UTCI as well as the spatial and temporal patterns of this influence call for improved infrastructure planning and resource allocation in the health sector.

Objectives Traffic speed is important to public health as it is a major contributory factor to collision risk and casualty severity. 20mph (32km/h) speed limit interventions are an increasingly common approach to address this transport and health challenge, but a more developed evidence base is needed to understand their effects. This study describes the changes in traffic speed and traffic volume in the City of Edinburgh, pre- and 12 months post-implementation of phased city-wide 20mph speed limits from 2016–2018. Methods The City of Edinburgh Council collected speed and volume data across one full week (24 hours a day) pre- and post-20mph speed limits for 66 streets. The pre- and post-speed limit intervention data were compared using measures of central tendency, dispersion, and basic t-tests. The changes were assessed at different aggregations and evaluated for statistical significance (alpha = 0.05). A mixed effects model was used to model speed reduction, in the presence of key variables such as baseline traffic speed and time of day. Results City-wide, a statistically significant reduction in mean speed of 1.34mph (95% CI 0.95 to 1.72) was observed at 12 months post-implementation, representing a 5.7% reduction. Reductions in speed were observed throughout the day and across the week, and larger reductions in speed were observed on roads with higher initial speeds. Mean 7-day volume of traffic was found to be lower by 86 vehicles (95% CI: -112 to 286) representing a reduction of 2.4% across the city of Edinburgh (p = 0.39) but with the direction of effect uncertain. Conclusions The implementation of the city-wide 20mph speed limit intervention was associated with meaningful reductions in traffic speeds but not volume. The reduction observed in road traffic speed may act as a mechanism to lessen the frequency and severity of collisions and casualties, increase road safety, and improve liveability.

Background While motorcycles are essential for moving people and goods, they are also, a significant contributor to Road Traffic Accidents (RTAs), making it a public health issue of concern globally. The Hohoe Municipal Hospital records increasing RTAs due to commercial motorcycles. Determining motorcycle riders’ compliance with road safety regulations is critical in helping to curb this menace. Method A cross-sectional study was employed involving a multistage sample of 238 motorcycle riders. Data were collected using a pretested structured questionnaire and entered into Epi Data version 3.2 software and exported to STATA software version 12 for analysis. Descriptive and inferential analyses were done while statistical significance was determined at 95% reliability interval and p-value of 0.05. Findings The level of compliance with road safety regulations among respondents was 59.2%. The mean age of respondents was 29.9 ± 7.9 years, and all respondents were males. Respondents who did not own their motorbikes were 0.39 times less likely to comply with road safety regulations compared to their counterparts who owned one, while those without alternate occupations were 0.51times less likely to comply with road safety regulations compared to those with an additional occupation. Those aged between 30–39 years and 40–49 years were 2.37 and 4.1 times more likely to comply with road safety regulations, respectively, compared to those aged ≤29 years, and those who did not smoke were 3.15 times more likely to comply with road safety regulations than those who smoked. Conclusion Compliance to safety regulations are fairly low and although motorcycle usage on a commercial basis is yet to be legalised in Ghana, routine education targeting riders who smoke, do not have alternate occupations, do not own motorbikes and younger riders will improve their compliance. Also, riders should be encouraged to obtain their license from the appropriate authorities.

Purpose Poor sleep quality is closed related with driving accidents. However, due to the lack of a valid instrument for assessing drivers’ sleep quality, few studies have examined drivers’ sleep quality and its associations with driving behaviours and traffic accidents in China. The aim of this paper is to revise the Sleep Quality Scale (SQS) and assess its reliability and validity in Chinese drivers. Methods 522 Chinese drivers aged from 18 to 56 years old agreed to complete the SQS, Daytime Sleepiness Perception Scale version 4 (DSPS-4), Self-report of Risky Driving Behavior (RD-SR) and Self-assessment of the Likelihood of Being Involved in a Risky Driving Situation (RD-SA). Results The final Chinese version of the SQS contained 23 items across four factors: difficulty in getting up, difficulty in falling asleep, sleep recovery and daytime dysfunction. Second, man scored lower on the difficulty in falling asleep factor but higher on the sleep recovery factor than women. Third, low to moderate correlations were found between the SQS factors and the DSPS-4, RD-SA and RD-SR, indicating that the validity of the revised scale was satisfactory. More importantly, daytime dysfunction factor is an effective predictor of violation involvement and accident involvement. Conclusion The revised SQS has acceptable reliability and validity and can be used as a tool to measure the sleep quality of Chinese drivers.

Introduction There are individuals who still refuse to wear seat belts, despite its effectiveness in reducing morbidity and mortality in road traffic accidents. We aimed to determine the prevalence and risk factors according to the use of seat belts among public transport drivers in Tacna, Peru. Methodology This analytical transversal study was carried out among public transport drivers (buses and taxis) in a Peruvian city. Questionnaires were used to evaluate the general and occupational characteristics and the use of seat belts (observed). Descriptive statistics and risk factors were obtained, these latter through generalized linear models. Results Of the 460 drivers, 77% used their seat belts, with a difference in use depending on the type of public transport (p 5 hours that day (p = 0.002). However, male drivers and those who had their belt with 3 anchorage points had greater use (both p Conclusions One in five drivers did not use a seat belt, and important characteristics of those who did not comply with this traffic law were evaluated to generate control and intervention measures.

Accurate calculation of the water-filled rut depth is critical for assessing hydroplaning potential. Nevertheless, due to the difficulty in collecting and calculating the water-filled rut depth, most transportation agencies do not use i, especially in the case of lateral slopes, although water-filled rut depth is a key parameter that impacts driving safety. Contributions of this paper are development of a methodology to reliably compute the water-filled rut depth and quantitatively evaluate the influence of lateral slope on the water-filled rut depth. The proposed method include: 1) acquisition of the high-resolution 3D point cloud data of rut, 2) smooth processing of rut profile through moving average method with Matlab programming, 3) water-filled rut depth computation at different lateral slopes with the assistance of key points based on rut sections. With the variation of water-filled rut depth (ΔWD), its change rate (δWD), and the calculation error between the rut depth and the water-filled rut depth (Δn) as evaluation indexes, the variation law of water-filled rut depth under different lateral slopes is analyzed when considering the severity level and rut shape of the rut profile. Results show that: 1) the increase in lateral slope leads to the reduction of water-filled rut depth; 2) the water-filled rut depth is affected by the rut shape, including rut side wall’s slope and the key points’ elevation. The accurate calculation of the water-filled rut depth can provide reliable suggestions for safe driving.

The present study aimed to adapt the Attitudes Toward Accompanied Driving Scale (ATADS) to a Chinese drivers sample and to examine its reliability and validity. Five hundred and seventy-two drivers aged 18 to 25 years old were asked to complete the ATADS and a validated Chinese version of the Multidimensional Driving Style Inventory. The factorial structure of the ATADS was examined using exploratory factor analysis (N = 259) and confirmatory factor analysis (N = 313). The validity of the scale was evaluated by examining the associations between the ATADS factors, demographic variables and driving styles. The results showed that both the findings of the EFA and CFA showed a five-factor structure of the ATADS, including tension, relatedness, avoidance, disapproval and anxiety. Second, significant gender differences were found in tension, relatedness, avoidance and anxiety. Third, tension, avoidance, disapproval and anxiety were moderately or weakly correlated with risky, anxious, angry and careful driving styles. Moreover, the number of traffic accidents after the accompanying phase was positively correlated with disapproval and avoidance. The findings supported the psychometric properties of the Chinese version of the ATADS and highlighted the adverse effects of young drivers’ negative attitudes toward accompanied driving on their driving styles.

Objective To estimate the prevalence and analyze the association between sociodemographic and behavioral variables with the use of prehospital care, hospitalization and sequelae and/or disability in victims of road traffic accidents victims in Brazil. Methods Data from the National Health Survey conducted in 2013 in Brazil were used. Data were collected through a direct household survey. The research sample consisted of 1,840 individuals who reported road traffic accidents in the previous 12 months. Poisson regression analysis was used to evaluate the factors associated with the use of prehospital care services, hospitalization, and the presence of sequelae and/or disability. Results The prevalence of road traffic accidents victims who received prehospital care was 13.0% (95% Confidence Interval [95% CI]: 10.3–16.3) and the factors associated with this outcome were: residing in the Northeast or North region of Brazil; residing in rural areas; and being a motorcycle occupant at the moment of the road traffic accident. The frequency of hospitalization was 7.7% (95% CI: 6.0–10.0) and the associated factors were: age between 40 and 59 years; being a motorcycle occupant or pedestrian and having received on-site care at the moment of the road traffic accident. The prevalence of sequelae and/or disability was 15.1% (95% CI: 12.5–18.2) and the associated factors were: age range between 30 and 39 years or 40 and 59 years; being a motorcycle occupant, being a pedestrian or belonging to other category of modes of transport and having received on-site care at the moment of the road traffic accident. Conclusion The study allowed to evaluate the factors associated with prehospital care, hospitalization and presence of sequelae and/or disability in the victims of road traffic accident and the results can guide the implementation of interventions that prioritize the population exposed to the highest risk of road traffic accident injuries and with less access to prehospital and hospital care services in Brazil.

Background Hazard perception ability, which develops with driving experience, has been proven to be associated with drivers' traffic involvement. Although classic reaction time-based hazard perception tests have been developed in many developed counties, experience-related differences may not be found in drivers from developing countries due to their increased opportunities to experience hazards on roads. Therefore, the present study aims to develop a hazard prediction test for Chinese drivers based on a predictive paradigm called “What happens next?” and assess its reliability and validity. Method Thirty-six video clips filmed from drivers’ perspectives of Chinese driving settings were presented to 54 novice drivers and 47 experienced drivers. Participants were asked to answer three questions after each video clip was blacked out and to then quickly press the mouse button on a reaction time-based hazard perception test. Both the differences in the test scores between novice and experienced drivers and the differences in scores between drivers with and without traffic violations were compared. Results The final hazard prediction test consisted of 20 video clips. A high internal consistency coefficient of the test, i.e., Cronbach's alpha = 0.862, was obtained. The total scores of the test were positively and significantly correlated with reaction times as measured on the video-based hazard perception test, thus providing evidence regarding the discriminant validity of the test. More importantly, drivers with traffic violations obtained significantly lower total scores on the test than did drivers without traffic violations. Conclusion The newly developed hazard prediction test exhibited adequate psychometric properties and provided a practical alternative for assessing drivers’ hazard perception ability in China.

The traditional full-scan method is commonly used for identifying critical links in road networks. This method simulates each link to be closed iteratively and measures its impact on the efficiency of the whole network. It can accurately identify critical links. However, in this method, traffic assignments are conducted under all scenarios of link disruption, making this process prohibitively time-consuming for large-scale road networks. This paper proposes an approach considering the traffic flow betweenness index (TFBI) to identify critical links, which can significantly reduce the computational burden compared with the traditional full-scan method. The TFBI consists of two parts: traffic flow betweenness and endpoint origin-destination (OD) demand (rerouted travel demand). There is a weight coefficient between these two parts. Traffic flow betweenness is established by considering the shortest travel-time path betweenness, link traffic flow and total OD demand. The proposed approach consists of the following main steps. First, a sample road network is selected to calibrate the weight coefficient between traffic flow betweenness and endpoint OD demand in the TFBI using the network robustness index. This index calculates changes in the whole-system travel time due to each link's closure under the traditional full-scan method. Then, candidate critical links are pre-selected according to the TFBI value of each link. Finally, a given number of real critical links are identified from the candidate critical links using the traditional full-scan method. The applicability and computational efficiency of the TFBI-based approach are demonstrated for the road network in Changchun, China. Published version

International audience; Achievement goals have been a major topic of research for more than 30 years. Achievement goals represent what and why individuals want to achieve. This literature has provided a large body of research in many domains (e.g., education, sports, work), but no study has hitherto been conducted in the driving domain. Moreover, no scale was available to assess achievement goals in driving even though driving is an achievement context. Indeed, driv-ers' personal competence is engaged and continuously evaluated both by others and the drivers themselves. The present study seeks to fill these gaps. The aims of the study were to emphasize the interest of investigating achievement goals in car driving, to develop and validate a scale named Achievement Goal Questionnaire in Driving (AGQ-D), to compare this baseline model with five alternative models, to assess the gender invariance of the scale, and to study its concurrent validity using interest and self-efficacy in driving, accidents , at-fault accidents, emergency maneuvers, and fines. The results of the Confirmatory Factor Analysis showed the good psychometric properties of the scale completed by 420 French car drivers, in comparison with five alternative models. The scale was also invariant across gender. Finally, the results of the hierarchical regression analyses showed its concurrent validity. The most significant results highlighted that mastery-avoidance goals (i.e., to avoid being a bad driver and avoiding failing in driving task demands) negatively predicted self-reported accidents and at-fault accidents. Performance-approach goals (i.e., to outper-form other drivers) also positively predicted self-reported emergency maneuvers. The AGQ-D is now a tool available to develop research in the driving domain and to extend the numerous advances already found in other domains.