Visual function correlates of self-reported vision-related nighttime driving difficulties / La función visual se correlaciona con las dificultades de conducción nocturna relacionadas con la visión autoinformadas

Purpose: To investigate the visual function correlates of self-reported vision-related night driving difficulties among drivers. Methods: One hundred and seven drivers (age: 46.06 ± 8.24, visual acuity [VA] of 0.2logMAR or better) were included in the study. A standard vision and night driving questionnaire (VND-Q) was administered. VA and contrast sensitivity were measured under photopic and mesopic conditions. Mesopic VA was remeasured after introducing a peripheral glare source into the participants' field of view to enable computation of disability glare index. Regression analyses were used to assess the associations between VND-Q scores, and visual function measures. Results: The mean VND-Q score was -3.96±1.95 logit (interval scale score: 2.46±1.28). Simple linear regression models for photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index significantly predicted VND-Q score (P<0.05), with mesopic VA and disability glare index accounting for the greatest variation (21 %) in VND-Q scores followed by photopic contrast sensitivity (19 %), and mesopic contrast sensitivity (15 %). A multiple regression model to determine the association between the predictors (photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index) and VND-Q score yielded significant results, F (4, 102) = 8.58, P < 0.001, adj. R2 = 0.2224. Seeing dark-colored cars was the most challenging vision task. Conclusion: Changes in mesopic visual acuity, photopic and mesopic contrast sensitivity, as well as disability glare index are associated with and explain night driving-related visual difficulties. It is recommended to incorporate measurement of these visual functions into assessments related to driving performance.(AU)

Validated numerical unrestrained occupant-seat crash scenarios for high-speed trains integrating experimental, computational, and inverse methods.

OBJECTIVE: Occupant impact safety is critical for train development. This paper proposes a systematic procedure for developing validated numerical occupant crash scenarios for high-speed trains by integrating experimental, computational, and inverse methods. METHODS: As the train interior is the most potentially injury-causing factor, the material properties were acquired by mechanical tests, and constitutive models were calibrated using inverse methods. The validity of the seat material constitutive model was further verified via drop tower tests. Finite element (FE) and multibody (MB) models of train occupant-seat interactions in frontal impact were established in LS-DYNA and MADYMO software, respectively, using the experimentally acquired materials/mechanical characteristics. Three dummy sled crash tests with different folding table and backrest configurations were conducted to validate the numerical occupant-seat models and to further assess occupant injury in train collisions. The occupant impact responses between dummy tests and simulations were quantitatively compared using a correlation and analysis (CORA) objective rating method. RESULTS: Results indicated that the experimentally calibrated numerical seat-occupant models could effectively reproduce the occupant responses in bullet train collisions (CORA scores >80%). Compared with the train seat-occupant MB model, the FE model could simulate the head acceleration with slightly more acceptable fidelity, however, the FE model CORA scores were slightly less than for the MB models. The maximum head acceleration was 30 g but the maximum HIC score was 17.4. When opening the folding table, the occupant's chest injury was not obvious, but the neck-table contact and "chokehold" may potentially be severe and require further assessment. CONCLUSIONS: This study demonstrates the value of experimental data for occupant-seat model interactions in train collisions and provides practical help for train interior safety design and formulation of standards for rolling stock interior passive safety.

Employee Grievance Redressal and Corporate Ethics: Lessons from the Boeing 737-MAX Crashes.

Two Boeing 737-MAX passenger planes crashed in October 2018 and March 2019, suspending all 737-MAX aircraft. The crashes put Boeing's corporate practices and culture under the spotlight. The main objective of this paper is to use the case of Boeing to highlight the importance of efficient employee grievance redressal mechanisms and an independent external regulator. The methodology adopted is a qualitative analysis of statements of various whistleblowers and Boeing and the Federal Aviation Administration (FAA) stakeholders. It suggests that employee feedback flowing up the chain of command should be more flexible and dealt with more seriousness. It recommends that companies adopt a cooling-off period or a lifetime restriction for employees who have gone through the revolving door between regulators and the industry. The Boeing 737-MAX case, which emphasizes the ethical obligations of the job, can offer value to engineers, engineering educators, managers, ombudsmen, and human resource professionals.

Sex-related disparities in vehicle crash injury and hemodynamics.

Objective: Multiple studies evaluate relative risk of female vs. male crash injury; clinical data may offer a more direct injury-specific evaluation of sex disparity in vehicle safety. This study sought to evaluate trauma injury patterns in a large trauma database to identify sex-related differences in crash injury victims. Methods: Data on lap and shoulder belt wearing patients age 16 and up with abdominal and pelvic injuries from 2018 to 2021 were extracted from the National Trauma Data Bank for descriptive analysis using injuries, vital signs, International Classification of Disease (ICD) coding, age, and injury severity using AIS (Abbreviated Injury Scale) and ISS (Injury Severity Score). Multiple linear regression was used to assess the relationship of shock index (SI) and ISS, sex, age, and sex*age interaction. Regression analysis was performed on multiple injury regions to assess patient characteristics related to increased shock index. Results: Sex, age, and ISS are strongly related to shock index for most injury regions. Women had greater overall SI than men, even in less severe injuries; women had greater numbers of pelvis and liver injuries across severity categories; men had greater numbers of injury in other abdominal/pelvis injury regions. Conclusions: Female crash injury victims' tendency for higher (AIS) severity of pelvis and liver injuries may relate to how their bodies interact with safety equipment. Females are entering shock states (SI > 1.0) with lesser injury severity (ISS) than male crash injury victims, which may suggest that female crash patients are somehow more susceptible to compromised hemodynamics than males. These findings indicate an urgent need to conduct vehicle crash injury research within a sex-equity framework; evaluating sex-related clinical data may hold the key to reducing disparities in vehicle crash injury.

GIS-based intelligent planning approach of child-friendly pedestrian pathway to promote a child-friendly city.

Pedestrian safety, particularly for children, relies on well-designed pathways. Child-friendly pathways play a crucial role in safeguarding young pedestrians. Shared spaces accommodating both vehicles and walkers can bring benefits to pedestrians. However, active children playing near these pathways are prone to accidents. This research aims to develop an efficient method for planning child-friendly pedestrian pathways, taking into account community development and the specific needs of children. A mixed-methods approach was employed, utilizing the Datang community in Guangzhou, China, as a case study. This approach combined drawing techniques with GIS data analysis. Drawing methods were utilized to identify points of interest for children aged 2-6. The qualitative and quantitative fuzzy analytic hierarchy process assessed factors influencing pathway planning, assigning appropriate weights. The weighted superposition analysis method constructed a comprehensive cost grid, considering various community elements. To streamline the planning process, a GIS tool was developed based on the identified factors, resulting in a practical, child-friendly pedestrian pathway network. Results indicate that this method efficiently creates child-friendly pathways, ensuring optimal connectivity within the planned road network.

Hand telerehabilitation for polytrauma patients following road traffic accidents.

OBJECTIVE: Aim: This study aimed to examine the characteristics of upper limb and shoulder injuries combined with chest trauma in road accident victims and evaluate the effectiveness of telemedical monitoring and a newly developed telerehabilitation model in patient recovery. PATIENTS AND METHODS: Materials and Methods: Our study incorporated 136 medical records of inpatients who had sustained upper extremity and chest injuries, constituting a retrospective group. Additionally, in the main group, we included 73 patients with similar injuries of the upper extremity and chest. RESULTS: Results: We analyze the functional results between the retrospective group and the main group, providing valuable insights into the effectiveness of traditional rehabilitation versus telerehabilitation. Focusing first on the average time spent on rehabilitation exercises per day, we observe a noticeable difference: while the retrospective group dedicated an average of 29}8 minutes daily, the main group invested more time, averaging 42}4 minutes. The retrospective group reported an average of 12}2 visits, in stark contrast to the main group, which averaged only 4}2 visits. The rehabilitators spent considerably less time with each patient in the main group (92}14 minutes) compared to the retrospective group (263}15 minutes), with a significant difference (p<0.005). The discovery in our study that there was no notable statistical difference in the functional outcomes, as evaluated by QuickDASH scores, between patients undergoing telerehabilitation and those receiving traditional rehabilitation is of significant importance. CONCLUSION: Conclusions: The findings reveal that telerehabilitation can significantly increase patient engagement in rehabilitation exercises, primarily due to its convenience and accessibility.

Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique.

Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on highways. Comprehending the contributing factors to these occurrences is paramount in enhancing safety on road networks. Recent studies have demonstrated the utility of predictive modeling in gaining insights into the factors that precipitate accidents. However, there has been a dearth of focus on explaining the inner workings of complex machine learning and deep learning models and the manner in which various features influence accident prediction models. As a result, there is a risk that these models may be seen as black boxes, and their findings may not be fully trusted by stakeholders. The main objective of this study is to create predictive models using various transfer learning techniques and to provide insights into the most impactful factors using Shapley values. To predict the severity of injuries in accidents, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Residual Networks (ResNet), EfficientNetB4, InceptionV3, Extreme Inception (Xception), and MobileNet are employed. Among the models, the MobileNet showed the highest results with 98.17% accuracy. Additionally, by understanding how different features affect accident prediction models, researchers can gain a deeper understanding of the factors that contribute to accidents and develop more effective interventions to prevent them.

Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning.

Traffic accidents have emerged as one of the most public health safety matters, raising concerns from both the public and urban administrators. The ability to accurately predict traffic accident not only supports the governmental decision-making in advance but also enhances public confidence in safety measures. However, the efficacy of traditional spatio-temporal prediction models are compromised by the skewed distributions and sparse labeling of accident data. To this end, we propose a Sparse Spatio-Temporal Dynamic Hypergraph Learning (SST-DHL) framework that captures higher-order dependencies in sparse traffic accidents by combining hypergraph learning and self-supervised learning. The SST-DHL model incorporates a multi-view spatiotemporal convolution block to capture local correlations and semantics of traffic accidents, a cross-regional dynamic hypergraph learning model to identify global spatiotemporal dependencies, and a two-supervised self-learning paradigm to capture both local and global spatiotemporal patterns. Through experimentation on New York City and London accident datasets, we demonstrate that our proposed SST-DHL exhibits significant improvements compared to optimal baseline models at different sparsity levels. Additionally, it offers enhanced interpretability of results by elucidating complex spatio-temporal dependencies among various traffic accident instances. Our study demonstrates the effectiveness of the SST-DHL framework in accurately predicting traffic accidents, thereby enhancing public safety and trust.

Implementation of a realistic artificial data generator for crash data generation.

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. The crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

Does the priority of ambulance guarantee no delay? a MIPSSTW model of emergency vehicle routing optimization considering complex traffic conditions for highway incidents.

Globally, traffic accidents on the highway network contribute significantly to a high fatality rate, drawing considerable attention from health institutions. The efficiency of transportation plays a vital role in mitigating the severe consequences of these incidents. This study delves into the issues of emergency vehicles experiencing delays despite having priority. Therefore, we construct mixed-integer linear programming with semi-soft time windows (MIPSSTW) model for optimizing emergency vehicle routing in highway incidents. We analyze the time-varying and complex traffic situations and respectively propose corresponding estimation approaches for the travel time of road segments, intersections on the urban road network, and ramp-weave sections on the highway network. Furthermore, we developed a modified cuckoo search(MCS) algorithm to solve this combinatorial problem. Optimization strategies of Lévy flight and dynamic inertial weight strategy are introduced to strengthen the exploration capability and the diversity of solution space of the CS algorithm. Computational experiments based on the Chinese emergency medical system data are designed to validate the efficacy and effectiveness of the MIPSSTW model and MCS algorithm. The results show that our works succeed in searching for high-quality solutions for emergency vehicle routing problems and enhance the efficacy of strategic decision-making processes in the realm of incident management and emergency response systems.

Injury Patterns and Gender in Italy.

Introduction: Globally, injuries pose significant public health challenges, with road traffic accidents in particular being responsible for considerable morbidity, mortality, and economic distress. Italy has been significantly impacted due to its high population density and frequency of road traffic and domestic incidents. Method: This study set out to investigate the incidence of self-reported road traffic and home and leisure accidents in the Italian general population. A particular emphasis was placed on exploring possible gender differences across varying age groups. The data was obtained from the European Health Interview Survey and a representative sample of the Italian population was analyzed. Results: The analysis revealed that regardless of age, women experienced a reduced risk of road traffic accidents compared to men. However, gender disparities in home-leisure accidents were observed to be age-dependent. Women under the age of 25 exhibited a lower likelihood of home-leisure accidents and serious accidents necessitating hospital admission in comparison to their male counterparts. In contrast, women aged 65 and above had an increased likelihood of home-leisure accidents as opposed to men in the same age category. Conclusions: The findings of this study highlight the importance of considering age and gender as significant factors in the occurrence of different types of accidents, offering insight into how injury rates vary between these demographic groups within Italy.

Examination of factors associated with the temporal stability assessment of crash severity by using generalised linear model-A case study.

Road crashes are a major public safety concern in Pakistan. Prior studies in Pakistan investigated the impact of different factors on road crashes but did not consider the temporal stability of crash data. This means that the recommendations based on these studies are not fully effective, as the impact of certain factors may change over time. To address this gap in the literature, this study aims to identify the factors contributing to crash severity in road crashes and examine how their impact varies over time. In this comprehensive study, we utilized Generalised Linear Model (GLM) on the crash data between the years 2013 to 2017, encompassing a total sample of 802 road crashes occurred on the N-5 road section in Pakistan, a 429-kilometer stretch connecting two big cities of Pakistan, i.e., Peshawar and Lahore. The purpose of the GLM was to quantify the temporal stability of the factors contributing crash severity in each year from 2013 to 2017. Within this dataset, 60% (n = 471) were fatal crashes, while the remaining 40% (n = 321) were non-fatal. The results revealed that the factors including the day of the week, the location of the crashes, weather conditions, causes of the crashes, and the types of vehicles involved, exhibited the temporal instability over time. In summary, our study provides in-depth insights aimed at reducing crash severity and potentially aiding in the development of effective crash mitigation policies in Pakistan and other nations having similar road safety problems. This research holds great promise in exploring the dynamic safety implications of emerging transportation technologies, particularly in the context of the widespread adoption of connected and autonomous vehicles.

The impact of COVID-19 restrictions on motorcycle crashes in Taiwan.

Taiwan is one of the countries with the highest motorcycle per capita globally, and motorcycle crashes are predominant among traffic crashes. This study examines the impact of coronavirus disease 2019 restrictions on motorcycle crashes. We analyzed the trend of motorcycle crashes in Taipei City from 2019 to 2020 using the dataset provided by the Department of Transportation, Taipei City Government, Taiwan. We found 47,108 and 51,441 motorcycle crashes in 2019 and 2020, involving 61,141 and 67,093 motorcycles, respectively. Mopeds had the highest risk in 2020, followed by heavy motorcycles [≥550 cubic capacity (cc)] and scooters compared to 2019. Food delivery motorcycle crashes increased for scooters (0.93% in 2019 to 3.45% in 2020, P < .0001) and heavy motorcycles (250 < cc < 550) (0.90% in 2019 to 3.38% in 2020, P < .0001). While fatalities remained under 1%, 30% to 51% of motorcyclists sustained injuries. Food delivery with scooters or heavy motorcycles (250 < cc < 550) was significantly associated with motorcyclist injuries and deaths. Compared with 2019, the adjusted odds ratios of motorcyclist injuries and deaths in 2020 were 1.43 (95% confidence interval = 1.05-1.94) for heavy motorcycles (≥550 cc) and 1.07 (95% confidence interval = 1.04-1.09) for scooters. This study shows that coronavirus disease 2019 restrictions was associated with elevated risks of crashes, injuries, and deaths among motorcyclists, reflecting the general preference for private transport over public transport. The popularity of food delivery services also contributed to increased motorcycle crashes.

A method to enhance drivers' hazard perception at night based on "knowledge-attitude-practice" theory.

During nighttime driving, the inherent challenges of low-illuminance conditions often lead to an increased crash rate and higher fatalities by impairing drivers' ability to recognize imminent hazards. While the severity of this issue is widely recognized, a significant research void exists with regard to strategies to enhance hazard perception under such circumstances. To address this lacuna, our study examined the potential of an intervention grounded in the knowledge-attitude-practice (KAP) framework to bolster nighttime hazard detection among drivers. We engaged a cohort of sixty drivers split randomly into an intervention group (undergoing specialized training) and a control group and employed a holistic assessment that combined eye movement analytics, physiological response monitoring, and driving performance evaluations during simulated scenarios pre- and post-intervention. The data showed that the KAP-centric intervention honed drivers' visual search techniques during nighttime driving, allowing them to confront potential threats with reduced physiological tension and ensuring more adept vehicle handling. These compelling findings support the integration of this methodology in driver training curricula and present an innovative strategy to enhance road safety during nighttime journeys.

Tendencias en la mortalidad por accidentes de tránsito en motocicleta en Colombia, 2008-2021 / Trends in motorcycle road deaths in Colombia, 2008-2021 / Tendências de mortalidade por acidentes de motocicleta na Colômbia, 2008–2021

[RESUMEN]. Objetivo. Identificar las tendencias de mortalidad por accidentes de tránsito en motocicleta en Colombia entre los años 2008 y 2021. Métodos. Se realizó un estudio observacional y descriptivo de tendencias de la mortalidad por accidentes de tránsito en motocicleta a partir de los registros oficiales de defunciones entre 2008 y 2021. Se efectuó un análisis de regresión Jointpoint Poisson para detectar los puntos de inflexión en las tasas de mortalidad espe- cíficas por edad, sexo y área de residencia. Resultados. Se identificaron 28 200 muertes por accidentes de tránsito en motocicleta en todo el período; fallecieron 24 271 hombres y 3 929 mujeres. El 74,1% de las defunciones ocurrió en el área urbana y el 25,9% en el área rural. En esta área se observó una tendencia creciente en la mortalidad en adultos jóvenes de ambos sexos a lo largo de todo el período. Lo mismo ocurrió en hombres de más de 65 años. En el área urbana, se identificó una tendencia al aumento de la mortalidad en las edades entre 45 a 64 años para ambos sexos durante todo el período. Solo se detectó un punto de inflexión en el año 2015, que mostró una disminución en la tendencia, en mujeres adolescentes. Conclusión. La tendencia en la mortalidad por accidentes de tránsito en motocicleta en Colombia se mantuvo en aumento durante todo el período (2008-2021) tanto en áreas rurales para adultos jóvenes como en áreas urbanas para personas de mediana edad.

[ABSTRACT]. Objective. To identify trends in motorcycle road deaths in Colombia between 2008 and 2021. Methods. An observational and descriptive study of trends in motorcycle road deaths was conducted using official death records from 2008 to 2021. Jointpoint Poisson regression analysis was performed to detect inflection points in mortality rates specific to age, sex, and area of residence. Results. A total of 28 200 motorcycle road deaths were identified during the period; 24 271 men and 3 929 women died. Of the deaths, 74.1% occurred in urban areas and 25.9% in rural areas. In rural areas, there was an increasing trend in fatalities in young adults of both sexes during the period. The same occurred in men over 65 years of age. In urban areas, there was an upward trend in fatalities in the age group from 45-64 for both sexes during the period. Only one inflection point was detected, in 2015, showing a downward trend in adolescent females. Conclusion. The trend in motorcycle road deaths in Colombia continued to rise during the 2008-2021 period, both in rural areas for young adults and in urban areas for middle-aged adults.

[RESUMO]. Objetivo. Identificar tendências de mortalidade por acidentes de motocicleta na Colômbia entre 2008 e 2021. Métodos. Realizou-se um estudo observacional e descritivo das tendências de mortalidade por acidentes de motocicleta com base em registros oficiais de óbitos entre 2008 e 2021. Conduziu-se uma análise baseada na regressão de Poisson (Joinpoint) para detectar pontos de inflexão em taxas de mortalidade específicas por idade, sexo e área de residência. Resultados. Foram identificadas 28 200 mortes por acidentes de motocicleta durante todo o período, corres- pondendo a 24 271 homens e 3 929 mulheres. As mortes ocorreram tanto na área urbana (74,1%) quanto rural (25,9%). Na área rural, observou-se uma tendência crescente na mortalidade de adultos jovens de ambos os sexos ao longo de todo o período. O mesmo ocorreu em relação a homens com mais de 65 anos. Na área urbana, identificou-se uma tendência de aumento da mortalidade na faixa etária de 45 a 64 anos, em ambos os sexos, durante todo o período. Apenas um ponto de inflexão foi detectado em 2015, mostrando uma redução na tendência em adolescentes do sexo feminino. Conclusão. A tendência de mortalidade por acidentes de motocicleta na Colômbia continuou a aumentar durante todo o período (2008 a 2021), tanto na área rural, para jovens adultos, quanto na área urbana, para pessoas de meia-idade.

Epidemiology and Characteristics of Ankle and Foot Injuries in Electric Scooter-Related Accidents.

Background: The use of electric scooters (e-scooters) continues to increase as a simple, inexpensive means of transport, resulting in a sharp increase in the incidence of scooter-related accidents. No study to date has closely examined the injury extent to the lower leg, joints, and extremities from e-scooter-related accidents. Here, we investigated the epidemiology and injury patterns of such accidents, focusing on injuries to the ankle and foot. Methods: Based on data from a single tertiary hospital's database, the demographics of 563 patients with scooter-associated injuries were analyzed retrospectively. Among the patients, 229 patients who were injured by e-scooter riding were further investigated. Based on the data, the general demographics of whole scooter-associated injuries and the injury characteristics and fracture cases of the lower leg, ankle, and foot were analyzed. Results: During the 4-year study period, the number of patients injured by e-scooters increased every year. Lower extremities were the most common injury site (67.2%) among riders, whereas injuries to the head and neck (64.3%) were more common in riders of non-electric scooters. Among the lower leg, ankle, and foot injuries of riders (52 cases), the ankle joint (53.8%) was the most commonly injured site, followed by the foot (40.4%) and lower leg (21.2%). The fracture group scored significantly higher on the Abbreviated Injury Scale than the non-fracture group (p < 0.001). Among the fracture group (20 cases), ankle fractures (9 cases) were most common, including pronation external rotation type 4 injuries (4 cases) and pilon fractures (2 cases). Five patients (25%) had open fractures, and 12 patients (60%) underwent surgical treatment. Conclusions: The ankle and foot are the most common injury sites in e-scooter-related accidents. Given the high frequency and severity of e-scooter-related ankle and foot injuries, we suggest that more attention be paid to preventing these types of injuries with greater public awareness of the dangers of using e-scooters.

Treatment Gap in Mental Health Care for Victims of Road Traffic Accidents.

Road traffic accidents (RTAs) are among the most frequent negative life-events. About one in five RTA survivors is susceptible to posttraumatic stress disorder (PTSD). Knowledge about needs for, and usage of, mental health services (MHSs) may improve options for care for RTA victims. The current study aimed to assess rates of victims using different MHSs, including psychotherapy, pharmacotherapy and support groups, and to explore correlates of needs for and use of these MHSs. Further, we aimed to estimate the treatment gap in post-RTA care, defined as including people with probable PTSD who did not use MHSs and people wanting but not getting help from MHSs. Dutch victims of nonlethal RTAs (N = 259) completed self-report measures on needs for and use of MHSs and PTSD. Results showed that 26% of participants had utilized care from psychotherapy, pharmacotherapy or support groups. Among people with probable PTSD, this was 56%. Increased posttraumatic stress was the strongest correlate of MHS use. Forty-eight participants (17.8%) had an unmet care need and represented the treatment gap. Commonly reported reasons and barriers preventing MHS use were perceptions that problems were limited or would disappear without care and financial worries. Regarding possible future care, participants reported a preference for face-to-face (over online) help from a psychologist (over other professionals). The treatment gap for Dutch RTA victims may be limited. However, a significant number of RTA victims need care but do not obtain this care. Care options may be improved by reducing practical barriers to MHSs and increasing mental health literacy and acceptability of different forms of care (besides face-to-face care).

Risk field modeling of urban tunnel based on APF.

OBJECTIVE: The purpose of this paper is to explore the changing laws of driving safety in the complex and changing driving environment in urban tunnels, to analyze the evolution of driving risk fields caused by changes in adjacent vehicles, driving behavior characteristics and road environment, and to reveal the formation mechanism of tunnel driving danger zones. METHODS: The kinetic field, behavioral field and potential field models are constructed according to the APF theory. The driving safety risks arising from the surrounding vehicles, driving behavior characteristics and changes in the tunnel environment are analyzed in the process of driving from the open section to the exit of the tunnel. RESULTS: The magnitude of the risk field force is inversely proportional to the spacing of the vehicles and the distance between the tunnel sidewalls, and is proportional to the relative speed between the vehicles and the slope of the longitudinal slope. Under the same conditions, the vehicle at the entrance and exit of the tunnel is subjected to a greater force of travel risk than inside the tunnel, and the effect of speed on the force of the risk field is greater than the distance. CONCLUSIONS: The established model better describes the trend of driving risk during the driving of vehicles in urban tunnels, and the research findings can provide theoretical support for the design and traffic management of urban tunnels.

Risk factors associated with driving after marijuana use among West Virginia college students during the COVID-19 pandemic.

OBJECTIVES: The purpose of this study was to assess sociodemographic and behavioral risk factors associated with driving after marijuana use (DAMU) among West Virginia college students. METHODS: Participants were recruited from West Virginia University between September and November 2022. The study sample was restricted to students who were ≥18 years of age; reported recently driving; possessed a current, valid driver's license from any US state; and were enrolled for at least one credit hour in the Fall 2022 semester. RESULTS: Among respondents (N = 772), 28.9% reported DAMU. Students who had a GPA of B (adjusted odds ratio [AOR]: 2.17, 95% confidence interval [CI]: 1.06-4.42), smoked or ingested marijuana in the past year (AOR: 26.51, 95% CI: 10.27-68.39), drove after drinking (AOR: 2.38, 95% CI: 1.18-4.79), and used both marijuana and alcohol concurrently and then drove (AOR: 10.39, 95% CI: 2.32-46.54) associated with DAMU. Individuals who felt the behavior was somewhat dangerous or not dangerous or thought their peers approved of DAMU showed significant associations with DAMU. CONCLUSIONS: As DAMU was prevalent, future interventions that raise awareness of the danger and potential consequences of DAMU may be needed to reduce this risky behavior on college campuses.