Diadegma semiclausum is an important parasitoid wasp and biological control agent of diamondback moth, Plutella xylostella. Diadegma semiclausum is naturally infected with the endosymbiotic bacterium Wolbachia. In other hymenopterans, Wolbachia can influence host reproduction and fitness, but its effects in D. semiclausum are unknown. Preliminary experiments suggested Wolbachia could not be cured from D. semiclausum with antibiotics, and multi-generational exposure to antibiotics ultimately crashed lines. This led us to infer that Wolbachia is essential for reproduction. We then examined phenotypic effects following partial suppression of Wolbachia using six antibiotic concentrations (0, 0.06, 0.6, 6, and 60 mg mL⁻¹ tetracycline and rifampicin) and a non-injected control. In the exposed G0 generation, control wasps exhibited negative associations between longevity and Wolbachia density, suggesting that high Wolbachia densities reduced life span. Antibiotic-treated G0 wasps exhibited reduced Wolbachia densities but did not exhibit associations between Wolbachia density and longevity. In the next G1 generation, Wolbachia densities generally recovered across treated groups and converged on longevity patterns seen in the control group. We highlight the resilience of the Wolbachia infection in Diadegma semiclausum wasps but also its potential costs at a high density. Future work could explore whether artificial selection could produce strains that exhibit better performance under mass-rearing conditions.
On May 22, 2020, Pakistan International Airlines flight PK-8303 crashed in Karachi, resulting in 97 fatalities. Many victims' remains were burned, fragmented, or commingled, making visual or fingerprint identification impossible. A rapid and reliable Disaster Victim Identification (DVI) process was initiated, integrating advanced forensic genetic techniques with kinship analysis to meet urgent humanitarian, cultural, and legal needs. Biological samples, including bone fragments, teeth, and soft tissue, were collected under strict chain-of-custody procedures. DNA was extracted using optimized protocols for degraded material, quantified via real-time PCR, and profiled with a high-sensitivity autosomal STR multiplex kit (GlobalFiler™). Y-STR and mitochondrial DNA sequencing were employed for cases where nuclear DNA was insufficient. Reference samples from 92 families were analyzed, and kinship likelihood ratios were calculated using dedicated forensic software. Within 16 days, complete identifications were made for 96 victims, with partial matches supporting the remaining case. The combined application of sensitive STR systems, lineage markers, and probabilistic kinship analysis significantly improved recovery rates from compromised remains and reduced turnaround times compared to standard DVI workflows. This case demonstrates how technological advances in forensic genetics can meet the humanitarian imperative of victim identification in mass disasters while ensuring legally robust outcomes.
During the Covid19 pandemic restrictions, overall traffic volume decreased in Finland. Fatigue and sleepiness while driving are common risks factors for fatal motor vehicle accidents. We analyzed the effects of Covid19 pandemic restrictions on the number of Fatal sleepiness-related motor vehicle accidents (FSMVA) during and before the pandemic. All fatal motor vehicle accidents during the years 2016-2022 were studied using Finnish Road Accidents data. Of the 1226 accidents, 235 formed FSMVA group and the others the control group. FSMVA values before the pandemic restrictions were compared with the values during the pandemic period. Statistical analysis was performed with Stata 18.5. The FSMVA proportion of fatal crashes before the pandemic period was 22.7%, and during the pandemic 13.4%(p < 0.001). The COVID years were significantly associated with a lower mortality rate (fatal accidents per million vehicle-kilometers) from FSMVA(p = 0.012). According to logistic regression, the probability of FSMVA was lower in the youngest age group (OR 0.6) and higher in the early morning (OR 2.0) and mid-morning (OR 1.7). Furthermore, the incidence of FSMVA increased when the blood alcohol concentration (BAC) was ≥0.5‰ (OR 2.2). During the pandemic, predictions of FSMVA decreased in the summer months (from 27% to 13%), in the early morning (from 38% to 16%) and in the afternoon (from 21% to 9%) compared to the pre-pandemic era. Furthermore, the FSMVA was observed to be less prevalent during the pandemic, particularly among individuals under the age of 25 (8% versus 21%). Proportion of fatal crashes and mortality rate of FSMVA decreased during the pandemic period compared to the pre-pandemic era. A possible explanation for the results may be the increase in remote work, which effectively reduced drowsy driving during pandemic era.
Understanding spatial disparities in traffic accident severity is essential not only for improving transport safety but also for advancing sustainable and inclusive transportation systems. Road crashes represent a persistent public health and equity challenge, directly linked to the United Nations Sustainable Development Goals (SDG 3: Good Health and Well-Being and SDG 11: Sustainable Cities and Communities). This study proposes an explainable, spatially segmented machine learning framework to examine urban-rural heterogeneity in crash outcomes, using disaggregated accident data from Kent, UK (2022-2024). By treating urban and rural systems as separate analytical units, the study captures risk heterogeneity that conventional pooled approaches often obscure. Among five tested models, Random Forest achieved the best performance and was further interpreted using SHapley Additive exPlanations (SHAP) to uncover how key factors differ in influence across spatial contexts. The results reveal a behavioral risk profile dominating in urban areas and infrastructure-driven risks in rural environments. These findings highlight the need for context-sensitive, evidence-based interventions that ensure transport equity across regions. Additionally, the study contributes to sustainable governance frameworks, enabling spatially adaptive risk mitigation, inclusive policy design and the long-term resilience of transport infrastructures.
Motorcycles are a common mode of transport in major Cameroonian cities, contributing to a rising burden of injuries among both users and pedestrians. These groups differ in exposure, mechanisms, and vulnerability, yet both bear a disproportionately high injury burden. However, comparative data on their epidemiological patterns and outcomes remain scarce. To support targeted prevention policies, we analysed trauma registry data to describe demographic, crash, injury, clinical, and outcome characteristics across both populations. This was a retrospective analysis of the Cameroon Trauma Registry (CTR), which collects information on injured patients presenting to 10 hospitals across seven of the 10 regions of Cameroon. Patients presenting with motorcycle-related injuries between June 1st 2022 and May 31st 2023 were assessed for demographic, crash, injury, clinical patterns of care and outcomes variables and compared using χ² or Fisher's exact tests for categorical data. The analysis was done using R version 4.2.1. A total of 2,757 motorcycle-related injury patients were included from the CTR database, including 2,339 (84.8%) motorcycle users and 418 (15.2%) pedestrians. Motorcycle users were mostly aged 15-34 years (59.1%) and males (83.0%), while pedestrians were frequently aged ≥60 years (23.4%) and females (37.8%). Helmet use among motorcycle users was low (3.0%). Alcohol involvement was more frequent among users (14.2%) than pedestrians (7.4%, p = 0.001). Most injuries occurred during work for users (33.1%) and during leisure for pedestrians (77.5%, p < 0.001). Severe multi-region injuries (abbreviated injury severity ≥3) were more common in users (21.9%) than pedestrians (16.1%, p = 0.014). Hospital admissions were high in both motorcycle users (60.2%) and pedestrians (58.4%); 6.2% required intensive care, and 2.2% underwent immediate surgery. Functional outcomes were similar: 44.8% had minor and 19.9% had major disability at discharge; 3.6% died during hospitalization. Motorcycle-related injuries in Cameroon disproportionately affect young male motorcycle users, with low helmet use, higher rates of alcohol use and severe trauma, together with older female pedestrians. Despite differing profiles, both motorcycle users and pedestrians face high disability and hospitalization rates. Targeted safety strategies are urgently needed to address these overlapping and distinct risks.
Bus crashes remain a significant public safety concern due to their potential to cause both passenger injuries and substantial vehicle damage. These two severity outcomes are interrelated, as the physical forces in high-impact crashes contribute simultaneously to occupant harm and structural damage. However, most existing studies model these outcomes independently, overlooking their statistical dependence and shared risk factors. To address this gap, this study employs a copula-based modeling framework to jointly analyze passenger injury and vehicle damage severity using bus crash data from Maryland (2015-2022). The joint estimation results reveal distinct sets of significant predictors for passenger injury severity and vehicle damage severity. For injury outcomes, the most influential variables include driver fault, airbag deployment, and safety equipment usage, underscoring the critical role of both human error and protective systems in shaping injury levels. In contrast, vehicle damage severity is more strongly associated with vehicle type, movement status at the time of impact, and mechanical condition. The inclusion of the vehicle type variable shows that school buses, despite being structurally safer, are frequently involved in crashes due to high exposure, contributing to notable damage risks. Additionally, adverse vehicle conditions and airbag deployment exhibit a strong association with disabling or destroyed damage, highlighting the role of structural integrity and energy dissipation mechanisms in post-impact outcomes. These patterns, revealed through the Copula-MNL model, reflect not only the different underlying risk structures of the two severity measures but also their shared dependence on critical safety-related factors.
It is well established that an anti-intrusion beam is a passive safety system that serves an essential role for passengers during collisions. In this study, the influence of internal reinforcements on the bending failure of a cylindrical aluminum tube was systematically investigated through a series of composite beam tests. Polymeric materials, including cast polyamide (PA6) and polypropylene (PP), with varying wall thicknesses, were deemed suitable for use as the inner reinforcement of the Al 6063-T6 tube. The test setup, which simulates impact conditions experienced by structural components in full-scale crash tests, is a powerful tool for the bending impacts in the study. To describe the connection between bending impact and quasi-static loading of composite beams, each method is compared to clarify the composite's failure behavior. An explicit Finite Element Analysis (FEA) of impact scenarios has been performed to understand the deformation behavior of polymer-reinforced composites and to determine the absorbed impact energy, thereby clarifying which specimen is better able to absorb bending impact energy. Primarily, three polymer-reinforced specimens were accepted with a hollow Al tube. After initial tests and simulations, the expected parametric study could not be achieved except for one. Then, three more combinations were offered. For one of the three specimens, the thickness of the central reinforcement PP was increased until a fully developed shaft was produced, resulting in better-than-expected bending impact-absorbing performance. The results indicate that the energy level of the inner reinforcements with polymeric materials increased 8.8 times, to about 750 J, compared to the plain Al tube (85 J) under bending impact loads. The numerical simulations are relevant and reliable for the details of the specimens' impact process and show good agreement with the experimental results. Finally, depending on the content, this research, rather than focusing on the fundamental concept of polymer-reinforced aluminum crash tubes, focuses on the specific dynamic bending impact evaluation of the Al, PA6, and PP configuration and the design insight that hollow PP reinforcement can accelerate fracture. In contrast, a fully filled PP core inside a PA6 sleeve can suppress splitting and substantially improve impact energy absorption.
Motor vehicle crashes (MVCs) are a leading cause of injury and death in the United States. Community-level factors, such as social vulnerability and urbanicity, have been associated with risk of death; less is known about how these factors impact nonfatal, post-injury outcomes. This study examined the association between social vulnerability and urbanicity with hospital length of stay (LOS) and hospital discharge disposition among MVC patients. Patients aged 18 years and older who were admitted to a Montana regional trauma center with a non-fatal injury following an MVC from 2016 to 2024 were included in the study. The CDC Social Vulnerability Index (SVI) was used to quantify social vulnerability at the census tract level and scores were divided into tertiles representing low, medium, and high vulnerability. Urbanicity was defined using RUCA codes based on patient residence. Generalized estimating equations with a binomial distribution were used to estimate the joint association between SVI and urbanicity with discharge disposition (home vs. facility) and prolonged LOS (≥7 days), controlling for injury severity, patient demographics, and comorbidities. Of the 668 patients, 529 (79%) were discharged home and 179 (27%) had a prolonged LOS. Among metropolitan patients, higher SVI rankings were associated with increased odds of discharge home; patients with medium and high SVI had respectively 2.6 and over 3 times greater odds of being discharged home than low SVI (medium aOR: 2.64; 95% CI: 1.96, 3.57; high aOR: 3.26; 95% CI: 2.52, 4.23). This association was not observed for non-metropolitan patients; however, patients from non-metropolitan had 2 times the odds of a prolonged LOS than those from metropolitan areas regardless of SVI (aOR: 2.03; 95% CI: 1.38, 2.98). The association between social vulnerability and discharge disposition following a MVC differed by urbanicity, and urbanicity was also associated with prolonged LOS. Further research to better understand how sociodemographic factors impact nonfatal injury outcomes can help reduce disparities in care.
This study examines the effect of fund managers' crash experience on their risk-taking behaviors. Using China's 2007-2008 and 2014-2015 A-share market crashes, as well as the COVID-19 pandemic, as exogenous shocks, we find that managers with crash experiences significantly increased their overall risk-taking. We explain these findings using the lens of risk components, asset allocation, portfolio concentration, and incentive mechanisms. We also find that incentive mechanisms encourage these managers to take on greater risks and adopt more aggressive strategies, including increasing portfolio concentration and expanding securities holdings. These findings enrich behavioral finance theories on fund managers and provide insights for regulators to design more effective incentives and manage risk in the post-crisis periods.
The timing of Emergency Medical Services (EMS) notification, crash scene arrival, and hospital arrival may impact motor vehicle fatalities. We examined EMS response time intervals over the past three decades, considering the effects of weather, vehicles involved, time of day, and location. We used the Fatal Accident Reporting System to compute and describe annual (1987-2020) EMS response time intervals. This included total time (i.e., crash-to-hospital), as well as the intervals between four key timepoints: crash, crash notification, crash scene arrival, and hospital arrival. We examined the proportion of fatal crashes with total intervals under 60 min (i.e., the "golden hour"), and where the crash arrival-to-hospital interval was under 30 min (the "beneficial timeframe"). Additionally, analyses were stratified by crash factors including weather (poor/clear) number of vehicles involved (single/multiple), time of day (early morning/rest of the day), and location (urban/rural). A total of 310,001 fatal crashes were analyzed. Between 1987-1994 total median response times ranged between 40 and 42 min. By 1999, intervals had increased to 45 min; elevated intervals were evident through 2009. By 2020, observed intervals had returned to 41 min. Paralleling this pattern, crashes with "golden hour" intervals decreased from 77.0% in 1987 to 72.4% in 2009 and increased to 78.0% by 2020. Similarly, crashes with a "beneficial timeframe" decreased from 60% in 1987 to 52% in 2009 and increased to 56.0% by 2020. The largest discrepancies for crash strata were evident for location: rural crash total response time intervals were 15-23 min longer than urban. From 1987-2020, the total time response interval following a fatal crash remained relatively stable. However, steady increases in intervals between crash notification and both crash scene and hospital arrival are evident. Future research should focus on approaches to reduce response time intervals.
Road traffic crashes are sudden and traumatic events that extend beyond physical injuries, exerting profound adverse effects on individuals' cognitive, emotional, and social functioning. The literature demonstrates that survivors of road traffic crashes may develop a wide range of psychological responses, including Posttraumatic Stress Disorder (PTSD), Acute Stress Disorder, depression, anxiety, traumatic grief, dissociative disorders, sleep disturbances, and avoidance behaviors. The severity and course of these reactions vary depending on multiple factors, such as the nature and intensity of the crash, prior trauma history, personality traits, level of social support, and demographic characteristics. This narrative review examines the psychological and behavioral responses observed in traffic crash survivors, highlighting how these responses differ across developmental stages, the risk factors that contribute to their emergence, and the ways in which psychological intervention needs are shaped. Findings indicate that children and adolescents are particularly vulnerable to the psychological consequences of traffic crashes due to their developmental characteristics. Among psychosocial intervention methods, trauma-focused cognitive-behavioral therapy, Eye Movement Desensitization and Reprocessing (EMDR), group therapy, virtual reality-based exposure techniques, and psychoeducation programs have been found to be effective. Early psychological assessment, timely referral to appropriate intervention programs, and strengthening social support networks are crucial for preventing chronicity and promoting well-being. In conclusion, this review underscores that traffic crashes generate not only physical but also significant psychological and societal consequences. The assessment of multidimensional post-traumatic responses, the identification of risk and protective factors, and the implementation of evidence-based interventions address critical gaps in the literature and make substantial contributions to reducing the psychosocial burden associated with traffic accidents.
Current real-time crash prediction models (RTCPMs) for freeway diverging areas primarily rely on macroscopic traffic parameters, which inadequately capture how vehicle interactions escalate into crash risks. This study analyzed 12 interchange diverging areas from two multilane freeways in China, employing image recognition technology to extract 48 vehicle motion parameters and surrogate safety measures (SSMs). Extended Time-to-Collision (ETTC)-a validated two-dimensional metric for lateral conflicts-was innovatively applied to establish a refined database with longitudinal/lateral conflict labels at 30-second intervals. Following spatiotemporal conflict analysis, four RTCPM types-Random Forest, Neural Network, Support Vector Machine, and XGBoost-were developed, with SHAP interpretability framework analyzing key risk factor contributions. Results showed: 1) XGBoost achieved optimal performance; 2) lateral conflicts exhibited longer durations and higher crash risks than longitudinal conflicts, with severe conflicts concentrated within 200 meters upstream of exit ramps; 3) SSMs including Modified Time-to-Collision (MTTC)-which incorporates relative acceleration-alongside Stopping Headway Distance and Time-to-Collision, emerged as decisive factors for both crash types, ranking highest in predictive contribution. These findings provide scientific foundations for designing dangerous driving warning systems and implementing proactive traffic safety management at interchange diverging areas.
The current is a scoping review of the possible link between seasonal patterns in traffic accidents and chronobiological aspects. Although this relationship has been widely investigated in different contexts, the present study performs an in-depth analysis of the existing literature on the topic. The main objectives are to map and synthesize the scientific evidence and to identify knowledge gaps. To ensure methodological rigor and transparent reporting, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) update was employed as the framework the development of the present article. The review confirmed the seasonal pattern in the occurrence of traffic accidents and highlighted the deficit in melatonin production, which can lead to drowsiness and, consequently, impair driving performance. Seasonal sensitivity, common in winter, can affect psychological well-being, posing a risk to drivers' mental health. Daylight saving time (DST) increases driver fatigue and drowsiness, while adverse winter conditions increase the risk of collision. These biological disruptions follow a seasonal pattern and may contribute to the higher rates of crashes observed at certain times of the year.
Wrong-turn violations in safety-critical spaces such as road roundabouts are a type of traffic violation that can lead to traffic congestion and increase the risk of road crashes. Although many researchers have focused on detecting various traffic violations, wrong-turn violations have not received enough attention. This may be due to a lack of relevant datasets. This study aims to address this gap. We developed a deep learning-based approach to detect wrong-turn traffic violations at roundabouts. The proposed system captures video from strategically placed cameras at roundabouts, which is then fed into an artificial intelligence (AI) model capable of detecting vehicles committing wrong-turn violations in real time. For this purpose, we utilized the popular You Only Look Once (YOLO) algorithm. Due to the absence of an existing dataset for this specific type of violation, we created our own. Images were collected and annotated from local roundabouts in Peshawar, Pakistan. The YOLO model was trained on this dataset and evaluated using standard performance metrics, including accuracy and recall. The results suggest that the proposed approach has strong potential for refinement and real-world implementation.
Neighborhood socioeconomic context influences pediatric injury risk, yet few studies apply child-focused metrics to quantify disparities in pedestrian and bicyclist crashes. We hypothesized that lower childhood opportunity would be associated with higher crash incidence and more severe and hazardous crash characteristics. This retrospective study examined pedestrian and bicyclist crashes involving children aged 0 to 17 years using Florida Signal Four Analytics (2015-2023) and the National Fatality Analysis Reporting System (2012-2023). The primary exposure was the crash zip code's Child Opportunity Index quintile. Florida crashes were used to estimate incidence, with national fatality data analyzed for replication. Incidence was modeled using negative binomial regression to estimate incidence rate ratios (IRRs) and 95% CIs. Injury severity and crash-level characteristics were assessed using logistic regression. A total of 18 272 crashes (49.6% pedestrian, 50.4% bicyclist) were identified; more than 60% occurred in low- or very low-opportunity neighborhoods. Incidence increased stepwise as opportunity declined (very low vs very high IRR 1.35 [95% CI 1.21-1.51]). Nationally, 3612 pediatric fatalities showed a similar pattern (very low vs very high IRR 2.82 [95% CI 2.65-3.00]). Very low-opportunity neighborhoods had higher odds of incapacitating injury (adjusted odds ratio [aOR] 1.71, 95% CI 1.34-2.16) and of improper actions (aOR 1.48, 95% CI 1.31-1.67). Lower neighborhood opportunity is associated with higher pediatric pedestrian and bicyclist crash incidence, more severe injuries, and more hazardous crash contexts, supporting targeted prevention efforts in disadvantaged communities.
Background/Objectives: Damage Control Resuscitation (DCR) is a critical strategy in the management of severe trauma, focusing on the optimisation of the patient's physiological condition. This study reviews current DCR strategies, emphasizing the mitigation of the "diamond of death"-hypothermia, acidosis, coagulopathy, and hypocalcemia-while addressing complex disturbances like respiratory distress syndrome (ARDS) and (acute kidney injury) AKI in high-ISS (Injury Severity Score) patients. Methods: A systematic review of 59 contemporary sources was conducted, encompassing clinical trials (e.g., CRASH-2), military-to-civilian protocol translations, and guidelines from the C and European Resuscitation Council. The analysis focused on pre-hospital interventions, in-hospital transfusion protocols, and the impact of transport logistics on survival. Results: Evidence highlights that aggressive crystalloid resuscitation (over 5 L) significantly increases mortality, favoring balanced blood component therapy (1:1:1 ratio) or Whole Blood guided by viscoelastic testing like rotational thromboelastometry (ROTEM) or thromboelastography (TEG). Pre-hospital success is driven by rapid hemorrhage control via tourniquets, early administration of Tranexamic Acid (TXA), no aggressive crystalloids, permissive hypotension, proactive calcium supplementation is recommended in early care. Furthermore, the integration of Helicopter Emergency Medical Services (HEMS) is independently associated with improved survival in multi-organ trauma by reducing time to definitive care and facilitating "en-route" damage control. Conclusions: The evolution of rescue strategies focused on mitigating the effects of the diamond of death, combined with the implementation of permissive hypotension and optimized HEMS logistics, constitutes the foundation of a modern model aimed at minimizing mortality in multi-organ trauma.
Reducing disparities and achieving health equity are critical goals for the trauma community. Although significant advances have been made in short-term trauma outcomes, disparities persist across various dimensions including race, sex, gender, socioeconomic status, and geographic location. This manuscript represents a distillation of a panel discussion from the 2024 Western Trauma Association meeting that examined three under-recognized categories of trauma disparities beyond traditional demographic factors. First, sex-related disparities in motor vehicle crashes stem from crash test dummies designed primarily for male physiology. Second, financial toxicity and exploring the relationship between acute trauma, financial hardship, and long-term mental and physical quality of life. Third, geographic disparities create "trauma deserts" where disadvantaged populations experience prolonged transport times and reduced access to life-saving care. The panel explored opportunities within each to improve patient outcomes at the local, regional, and national levels. (J Trauma Acute Care Surg. 2026;00:000-000. Copyright© 2026 Wolters Kluwer Health, Inc. All rights reserved.).
The Commission on Accreditation of Medical Transport Systems has used patients being admitted for less than 24 hours at the receiving facility as a surrogate marker for improper helicopter emergency medical services (HEMS) utilization, therefore triggering a review to determine proper HEMS utilization. Recent guidelines modified this to use discharge directly from the emergency department (ED) after transfer as a marker for inappropriate HEMS utilization. This study aimed to evaluate which metric is associated with better adherence to Wisconsin (WI) HEMS utilization criteria in adult trauma patients transported to the ED. This was a retrospective chart review of 1,520 transports by a midwestern HEMS service to a level 1 adult trauma center between January 1, 2013, and December 31, 2022. Charts with a disposition of discharge home, admission of less than 24 hours, or death in the ED were evaluated for adherence to WI HEMS utilization guideline criteria. A total of 287 patients met the inclusion criteria. Most patients were transported directly from the scene; 53% of transports met utilization criteria. Interfacility transports were more likely to meet utilization criteria than scene transports. Patients admitted for less than 24 hours were more likely to meet utilization criteria than patients discharged directly from the ED. This significance occurred for both scene and interfacility transports. Patients transported after a motor vehicle crash were less likely to have met utilization criteria. Patients admitted for less than 24 hours were more likely to have met WI HEMS utilization guidelines than patients discharged from the ED. The relatively low adherence rate to the WI HEMS utilization guidelines suggests that stricter guidelines may be necessary to reduce overtriaging in HEMS transport.
Hazard perception plays a pivotal role in preventing road accidents. Despite control measures in developing countries, crash and injury rates remain high, indicating limitations in current strategies. Framed within Endsley's Situational Awareness Theory, this study examined associations between crash history, traffic penalties, and demographic factors (age and education) with hazard perception among Iranian professional drivers. This cross-sectional study included 220 Iranian professional car drivers (age range: 23-75 years; M = 48.3, SD = 10.4). Participants completed a demographic questionnaire and the standardized Hazard Perception Test (HPT) validated for the Iranian context. Data were analyzed using univariate tests and a General Linear Model (GLM). The mean hazard perception score was remarkably low at 35.60 ± 15.68 (out of 100), with an average error rate of 3.68 ± 1.91 missed hazards. Drivers with no crash history in the past three years scored 11.68 points higher on average than those with crash involvement (p < 0.001). Higher penalty frequency was associated with lower hazard perception scores (p < 0.001). In the GLM, crash history (β = 11.68, 95% CI: 8.14-15.21, p < 0.001) and penalty frequency (β = -3.62, p < 0.001) remained significant predictors, while age, education, gender, and driving experience showed no independent association (all p > 0.05). This performance level is substantially lower than scores typically reported in high-income countries with mandatory HPT in licensing (often >50-60% among experienced drivers). Crash and penalty history were strongly linked to poorer hazard perception, highlighting behavioral factors as key risk markers. The HPT effectively distinguished high- from low-risk drivers, supporting its use as a screening tool for targeted interventions in settings with limited systemic protections. These findings extend Situational Awareness theory to low- and middle-income contexts and emphasize the need for context-specific training.
Bastos and Krupenye (2026, Science, 391: 583-586) present an innovative series of studies in which they explore the capacity of a single enculturated bonobo, Kanzi, to represent pretend objects-in other words-"imagination." Their experiments involved pantomimed actions of pouring and emptying juice or placing and dumping out grapes from transparent cups or bowls and asking Kanzi to indicate where the juice or grape would remain, indicating that he was tracking an imagined object, but they failed to account for cuing or alternative explanations. (PsycInfo Database Record (c) 2026 APA, all rights reserved).