Traffic Injury Prevention最新文献

{"title":"An analysis of drug recognition expert evaluations and comparisons with police issued citations in Maryland, 2017-2021.","authors":"Komal Bhagat, Kartik Kaushik, Joseph A Kufera, Kimberly M Auman, Roumen Vesselinov","doi":"10.1080/15389588.2025.2493754","DOIUrl":"https://doi.org/10.1080/15389588.2025.2493754","url":null,"abstract":"<p><strong>Objective: </strong>Drug Recognition Expert (DRE) officers utilize standardized evaluations to assess physiological and behavioral indicators of drug impairment. This study analyzed data from Maryland DRE officers (2017-2021), comparing their drug category/ies assessments with blood tests results. DRE evaluation records were linked to citations issued for alcohol/drug-impaired driving, to examine the agreement between charges, DRE evaluation, arrest outcomes, and repeat offenses.</p><p><strong>Methods: </strong>Data from 4,931 DRE evaluations were analyzed, involving 4,727 drivers linked to citation records for alcohol/drug-impaired driving offenses. Agreement between DRE opinions and blood test results was quantified by estimating binomial success probabilities with 95% confidence intervals. Citation outcomes and repeat offense rates for DRE and non-DRE cases were also presented.</p><p><strong>Results: </strong>Of 4,931 unique evaluations, blood specimens were collected in 2,118 (42.9%), yielding 1,599 positive drug test results (75.5%). Most evaluated drivers were white (67.6%), male (73.8%), and aged 21-34 years (43.2%). Comparison of DRE opinion with blood test results revealed an overall success probability of 84.2 ± 0.65%. DRE accuracy improved to 91.8 ± 0.85% when none or one drug was detected and decreased to 80.5 ± 0.87% when two or more drugs were involved. When linked to citation data, 3,237 drivers (68.5%) received 36,878 citations, with 88.1% having two or more drug-related offenses and 72.5% having at least one negligent driving offense. Matched DRE drivers were involved in 9,105 traffic stops, with approximately 48.4% receiving over five citations during their first stop. 97.3% were cited for drug impairment, with only 87 drivers avoiding such citations.</p><p><strong>Conclusions: </strong>This study highlights the effectiveness of the DRE program in identifying impaired drivers, providing insights into driver demographics and impairment patterns, while emphasizing need for improved polysubstance impairment data collection. A high degree of agreement between DRE opinions and blood test results for all tested drug categories were statistically established. Despite the program's success, significant gaps remain in testing methods and integrating alcohol and drug evaluations. Future research should enhance testing protocols, expanding data collection, and examining the link between substance use disorders and impaired driving to strengthen prevention, enforcement, and intervention efforts.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-8"},"PeriodicalIF":1.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on nighttime road visibility monitoring based on video images.","authors":"Yonggao Yue, Shang Zhang, Zhiyuan Wu, Jianpu Xi, Zonglin Shi, Lei Wang, Lijuan Deng","doi":"10.1080/15389588.2025.2495203","DOIUrl":"https://doi.org/10.1080/15389588.2025.2495203","url":null,"abstract":"<p><strong>Objective: </strong>Road traffic accidents have become a serious social problem, with a significant proportion of accidents caused by insufficient visibility on roads at night. Therefore, nighttime road visibility detection based on video images has become one of the difficulties and a key issue in domestic and international research.</p><p><strong>Methods: </strong>This study analyzes the importance of nighttime road visibility monitoring, introduces the structure, working principle, and monitoring method of a video image nighttime visibility monitoring system, and proposes a nighttime road visibility monitoring method based on video images. Based on the characteristics of nighttime images, an improved dark channel prior method was adopted to calculate the nighttime road visibility. This method mainly includes eight steps: video image acquisition, image grayscale processing, calculation of image average variance, image average gradient, drawing grayscale histograms, image enhancement based on the calculated values, calculation of transmittance, and calculation of visibility.</p><p><strong>Results: </strong>The experimental results show that the proposed night road visibility monitoring method based on video images can effectively realize real-time monitoring of night road visibility, effectively overcome the inherent defects of traditional methods, and the constructed night visibility monitoring framework can realize high-precision visibility calculation, and has broad application prospects.</p><p><strong>Conclusions: </strong>Through adaptive threshold and adaptive filtering technology, the improved dark channel algorithm has shown competitive advantages in both image quality index and practical application effect, especially in noise suppression and edge preservation. However, under extreme illumination conditions, the algorithm still has room for improvement in the processing of the strong light source region, and the dark channel prior may lead to bias in the transmission estimation.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of confidence level and hazard type on the visual search patterns and hazard response times of young drivers.","authors":"Wenjing Hu, Long Sun, Liang Cheng","doi":"10.1080/15389588.2025.2497521","DOIUrl":"https://doi.org/10.1080/15389588.2025.2497521","url":null,"abstract":"<p><strong>Objective: </strong>While numerous studies have reported that overconfidence affects young drivers' crash risk, direct comparisons of hazard perception differences among overconfident, underconfident young drivers and their peers with relatively accurate self-rated confidence remain limited. This study addressed this gap by exploring the effects of hazard type and confidence level on the hazard perception of young drivers.</p><p><strong>Methods: </strong>A total of 72 young drivers aged 18-25 years agreed to participate in this study. A 2 (hazard type: environmental prediction hazards/EP, behavioral prediction hazards/BP) × 4 (driver group: overconfident, very confident, moderately confident, underconfident) mixed experimental design was adopted. Twelve video clips with BP hazards and 12 with EP hazards were presented to the four groups of drivers. Response time and eye movement were recorded.</p><p><strong>Results: </strong>Underconfident drivers had longer response times than very confident and moderately confident drivers did, regardless of hazard types. Overconfident drivers took longer to fixate the AOIs that contained EP hazards and responded slower to EP hazards than moderately confident drivers did. Although overconfident drivers responded slower to BP hazards compared to very confident and moderately confident drivers did, all three groups took similar times to fixate the AOIs that contained BP hazards. Additionally, compared to very confident drivers, overconfident drivers had a higher no-response rate and fewer fixations on the hazards.</p><p><strong>Conclusions: </strong>These findings indicate that moderately confident drivers outperformed both overconfident and underconfident drivers in response times, highlighting how confidence level influences hazard perception and response efficiency depending on hazard type. The results provide valuable insights for hazard perception training programs tailored to young drivers, emphasizing the need to address both overconfidence and underconfidence in driver education.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-7"},"PeriodicalIF":1.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Waymo Rider-Only crash rates by crash type to human benchmarks at 56.7 million miles.","authors":"Kristofer D Kusano, John M Scanlon, Yin-Hsiu Chen, Timothy L McMurry, Tilia Gode, Trent Victor","doi":"10.1080/15389588.2025.2499887","DOIUrl":"https://doi.org/10.1080/15389588.2025.2499887","url":null,"abstract":"<p><strong>Objective: </strong>SAE Level 4 Automated Driving Systems (ADSs) are deployed on public roads, including Waymo's Rider-Only (RO) ride-hailing service (without a driver behind the steering wheel). The objective of this study was to perform a retrospective safety assessment of Waymo's RO crash rate compared to human benchmarks, including disaggregated by crash type.</p><p><strong>Methods: </strong>Eleven crash type groups were identified from commonly relied upon crash typologies that are derived from human crash databases. Human benchmarks were developed from state vehicle miles traveled (VMT) and police-reported crash data. Benchmarks were aligned to the same vehicle types, road types, and locations as where the Waymo Driver operated. Waymo crashes were extracted from the NHTSA Standing General Order (SGO). RO mileage was provided by the company <i>via</i> a public website. Any-injury-reported, Airbag Deployment, and Suspected Serious Injury + crash outcomes were examined because they represented previously established, safety-relevant benchmarks where statistical testing could be performed at the current mileage.</p><p><strong>Results: </strong>Data were examined over 56.7 million RO miles through the end of January 2025; resulting in a statistically significant lower crashed vehicle rate for all crashes compared to the benchmarks in Any-Injury-Reported and Airbag Deployment, and Suspected Serious Injury + crashes. Of the crash types, V2V Intersection crash events represented the largest total crash reduction, with a 96% reduction in Any-injury-reported (87-99% confidence interval) and a 91% reduction in Airbag Deployment (76-98% confidence interval) events. Cyclist, Motorcycle, Pedestrian, Secondary Crash, and Single Vehicle crashes were also statistically reduced for the Any-Injury-Reported outcome. There was no statistically significant disbenefit found in any of the 11 crash type groups.</p><p><strong>Conclusions: </strong>This study represents the first retrospective safety assessment of an RO ADS that made statistical conclusions about more serious crash outcomes (Airbag Deployment and Suspected Serious Injury+) and analyzed crash rates on a crash type basis. The crash type breakdown applied in the current analysis provides unique insight into the direction and magnitude of safety impact being achieved by a currently deployed ADS system. This work should be considered by stakeholders, regulators, and other ADS companies aiming to objectively evaluate the safety impact of ADS technology.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-13"},"PeriodicalIF":1.6,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescription pattern of driving-impairing psychotropic medications in Tabriz in 2022.","authors":"Mostafa Farahbakhsh, Ali Fakhari, Ehsan Aghajani, Amin Khameneh, Sepideh Harzand-Jadidi","doi":"10.1080/15389588.2025.2484224","DOIUrl":"https://doi.org/10.1080/15389588.2025.2484224","url":null,"abstract":"<p><strong>Objectives: </strong>Some psychotropic medications could impair drivers' cognitive skills, concentration and reaction by affecting the central nervous system (CNS), thereby increasing the risk of traffic accidents. However, there is limited evidence regarding the prescription pattern of these medications in Iran. The present study aims to investigate the prescription pattern of psychotropic medications impairing driving in Tabriz, Iran.</p><p><strong>Methods: </strong>In this descriptive-analytical cross-sectional study, psychotropic medications prescribed by physicians in Tabriz from March, 2021, to March, 2022, were reviewed. The data were obtained from Iranian Social Security Organization (SSO), which included 1,167,460 eligible prescriptions. Psychotropic medications were classified into six main categories based on reliable scientific sources, and their level of effect on driving was determined using driving-impairing medication classification system. The data were analyzed using Stata 17.0 and Chi-square test. The significance level was considered to be less than 0.05.</p><p><strong>Results: </strong>The results showed out of 1,167,460 prescribed psychotropic medications, 65.32% were for women, and the rest were for men. The most frequently prescribed medications were antidepressants (38.07%), followed by anxiolytics (18.60%) and antipsychotics (15.48%), respectively. More than half of the medications (57.10%) was categorized to have moderate effect, 23.73% was categorized to have mild effect and 18.87% was categorized to have severe effect on driving. Gabapentin, sertraline, nortriptyline, fluoxetine and trifluoperazine were the most frequently prescribed medications, respectively. A significant correlation was observed between the impairment category of prescribed medications and patients' gender and age (<i>P</i> <0.001). Additionally, general practitioners prescribed the highest number of medications with severe adverse effects, while neurosurgeons, general surgeons, neurologists and psychiatrists prescribed the highest number of medications with moderate adverse effects on driving.</p><p><strong>Conclusions: </strong>More than half of the prescribed psychotropic medications in Tabriz was categorized to have moderate effects on driving, and about one-fifth was categorized to have severe effects. Antidepressants, anxiolytics and antipsychotics are considered to have the most relevant impairing effects on driving according to the categorization system, with gabapentin, sertraline, nortriptyline, fluoxetine and trifluoperazine being the most frequently prescribed medications. The findings highlighted the importance of raising awareness among physicians and patients about the effects of psychotropic medications on driving.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-8"},"PeriodicalIF":1.6,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinematic analysis of volunteers in a highly reclined rigid seat in limited load frontal sled tests.","authors":"Qiang Wang, Yu Liu, Jing Fei, Peifeng Wang, Xiaofan Wu, Linwei Zhang, Yao Jin, Zhonghao Bai","doi":"10.1080/15389588.2025.2495201","DOIUrl":"https://doi.org/10.1080/15389588.2025.2495201","url":null,"abstract":"<p><strong>Objective: </strong>The goal of the study was to investigate the kinematic response patterns of human volunteers in highly reclined postures with a safe limited load.</p><p><strong>Methods: </strong>The sled testing environment consisted of an adjustable rigid seat and an integrated 3-point seat belt, using a pulse with a nominal peak deceleration of 3.5 g. Preliminary tests with anthropomorphic test devices and simulations with human body model were performed to verify the safety of the testing environment. Various sensors were set up to record static data and kinematic responses from three 50th percentile male volunteers. A total of 36 tests were carried out under 4 seat configurations, including standard posture, semi-reclined posture, reclined posture, and zero-gravity posture (a modern term for a highly reclined vehicle seat design mimicking a comfortable recliner with leg support). All procedures were approved by the relevant ethics committees.</p><p><strong>Results: </strong>The results indicated that as the reclining degree increased, the initial position of the hip moved backward and downward. The maximum displacement in the Z-axis of the head and neck increased, as well as the forward excursion of the upper torso and hip also significantly increased, while the shoulder and lap belts forces decreased.</p><p><strong>Conclusions: </strong>This illustrates that the integrated 3-point seat belt fails to effectively restrain the torso and hip of the occupants in highly reclined postures, particularly in the zero-gravity posture. These responses mirror those of a real human body in the early stage of a collision, providing insights into the potential injury risks for reclined occupants in crash.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-8"},"PeriodicalIF":1.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prior identification method of safety performance boundary for autonomous vehicles based on Safety Threat Field.","authors":"Deyu Kong, Konghui Guo","doi":"10.1080/15389588.2025.2472294","DOIUrl":"https://doi.org/10.1080/15389588.2025.2472294","url":null,"abstract":"<p><strong>Objective: </strong>Identifying the safety performance boundary (SPB) of autonomous vehicles (AVs) is crucial for verifying the coverage of scenario-based tests for AVs. Researchers proposed posteriori methods based on collected crash scenarios that demonstrated promising advancements in identifying the SPB. Nevertheless, the search for crash scenarios is often rendered complex and time-consuming due to the \"curse of dimensionality and rarity.\" To address this limitation, this paper introduces the Safety Threat Field-based Prior Identification Method (STF-PIM) to identify the SPB a priori.</p><p><strong>Method: </strong>Firstly, the STF model is constructed to quantify the safety risks posed by various scenario elements, where background vehicles and other obstacles are considered as sources of safety threats. By defining the Safety Threat Field Potential Energy (STFPE), we establish a state space that maps the ego vehicle's response to a crash in an actual physical scenario as its traversal through the state space to dissipate the STFPE. The maximum STFPE that the ego vehicle can dissipate is defined as its safety capacity. Next, we calibrate the safety capacity of the ego vehicle using critical crash scenarios. Through analysis, we find that in critical crash scenarios, the ego vehicle makes its utmost effort to avoid a crash, resulting in the dissipation of the STFPE from its initial value in the first frame to exactly zero in the last frame. Consequently, the threshold STFPE for all crash scenarios (the minimum STFPE that leads to a crash) can be equated to the safety capacity of the ego vehicle. By comparing the initial STFPE of a scenario with this threshold, crash scenarios can be identified without having to examine every possible scenario in the scenario space.</p><p><strong>Results: </strong>A cut-in scenario is performed in simulation to validate the proposed STF-Prior Identification Method (STF-PIM) for identifying the SPB a priori. Simulation results show that the proposed STF-PIM successfully describes the SPB of the ego vehicle without traversing the entire scenario space.</p><p><strong>Conclusions: </strong>The proposed STF-PIM enables the calibration of the safety capacity of the tested ego-vehicle through a small number of critical crash scenarios, thereby providing an a priori description of the SPB.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-11"},"PeriodicalIF":1.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Undercounts stemming from misclassification derived from fatal injuries in traffic crashes in Colombia, 2010 to 2021.","authors":"Jorge Martín Rodríguez Hernández, Pablo Enrique Chaparro Narváez, Arsenio Hidalgo Troya, Flor Stella Piñeros Garzón","doi":"10.1080/15389588.2025.2495863","DOIUrl":"https://doi.org/10.1080/15389588.2025.2495863","url":null,"abstract":"<p><strong>Objectives: </strong>To identify and address potential misclassification of traffic fatalities in Colombia from 2010 to 2021.</p><p><strong>Methods: </strong>For an ecological study, we employed national records and databases. A database was consolidated to include information on the fatality occurrence site, area, place of death, year of occurrence, marital status, age, and enrollment in social security. Generalized linear regression models were used to detect and adjust possible errors in records due to misclassification starting from existing data, allowing reclassification with a high probability of specific garbage codes being valid, potentially associated with mortality caused by traffic.</p><p><strong>Results: </strong>In 2010; there was a mortality rate of 13.3 deaths per 100,000 population, while in 2021; it was 15.1/per 100,000 population. In 2020; from the effects of pandemic-related confinement, the risk came down to 11.5/100.000 population. With the imputation, these records increased from 14.9 (2010) to 16.4 (2021); the most notable rise was among motorcyclists, who contributed 62%, with a marked increase in 2021:13/100.000 population, while pedestrians contributed 27.2%, cyclists: 4% and vehicle occupants: 6.5%.</p><p><strong>Conclusions: </strong>Over the past decade, Colombia has stood out as one of the few countries worldwide that have been unable to reduce traffic-related mortality. The potential underestimation of the problem likely exacerbates this challenge due to record misclassification or measurement errors, which may be as high as 10%. Motorcyclists are particularly vulnerable, facing a significantly increased risk of death. To address this critical issue, cross-sectoral and inter-institutional policies, and plans are urgently needed to mitigate the high incidence of motorcycle fatalities and break the cycles of poverty and orphanhood they can cause.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of male and female SUV-driver injury rates in similar crashes.","authors":"Charles M Farmer","doi":"10.1080/15389588.2025.2496939","DOIUrl":"https://doi.org/10.1080/15389588.2025.2496939","url":null,"abstract":"<p><strong>Objective: </strong>The current study sought to determine the extent of differences in serious injury risk by sex using crash data maintained by individual U.S. states. As with many earlier studies, crash and vehicle differences were controlled. The vehicles of interest were restricted to SUVs, the most popular vehicle type in the U.S.</p><p><strong>Methods: </strong>Records of SUV-driver crash involvements during 2017 to 2023 were obtained from motor-vehicle crash files maintained by 13 states. Logistic regressions were used to model the odds of a serious or fatal injury for each of the states (A or K on the KABCO scale). Common predictors were light condition (dark vs. daylight), road surface condition (dry vs. slippery), vehicle age (7-12 years old vs. younger), vehicle weight ratio (case vehicle to partner vehicle), driver age (< 25 years vs. 25-64 years vs. 65+ years), and driver sex (female vs. male). An overall female-to-male injury odds ratio was computed from the weighted average of the logarithms of individual state odds ratios.</p><p><strong>Results: </strong>The data were restricted to safety-belt-restrained SUV drivers in head-on crashes with another passenger vehicle. Serious and fatal injuries were coded for 3.8% of the female drivers and 3.4% of the male drivers. Crashes in darkness and crashes of older drivers were significantly more likely to result in serious/fatal injuries, while crashes of younger drivers were significantly less likely to result in serious/fatal injuries. Female drivers were 17% more likely than males to incur serious/fatal injuries (95% confidence limits 8% to 27%). When the opposing vehicle was another SUV, female drivers were only 11% more likely than males to incur serious/fatal injuries (95% confidence limits -4% to 28%). However, female drivers were 20% more likely than males to incur at least minor injuries (95% confidence limits 13% to 28%).</p><p><strong>Conclusions: </strong>Observed differences in serious injury rates for female and male drivers declined after accounting for other driver, vehicle, and crash characteristics. In similar crash circumstances, female drivers are more likely than males to be injured, but this difference is clear only for minor injuries.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-6"},"PeriodicalIF":1.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal assessment of post-concussion driving reaction time.","authors":"Julia D Drattell, Samuel D Fu, Eric J Shumski, Thomas A Prato, Robert C Lynall, Hannes Devos, Julianne D Schmidt","doi":"10.1080/15389588.2025.2497066","DOIUrl":"https://doi.org/10.1080/15389588.2025.2497066","url":null,"abstract":"<p><strong>Objectives: </strong>Concussed patients present multiple neurocognitive and motor impairments including slowed reaction time (RT), a function essential to driving. We compared driving RT between concussed and non-concussed individuals across their concussion recovery (aim 1) and explored whether clinical concussion outcomes were correlated with driving RT uniquely in the concussion group (aim 2).</p><p><strong>Methods: </strong>We recruited collegiate athletes (26 concussed and 23 age- and sex-matched controls) to complete the sport concussion assessment tool (SCAT5), a computerized neurocognitive test (CNS Vital Signs), and a driving simulation across 3 timepoints: ≤72 h, asymptomatic, and unrestricted medical clearance. RTs were recorded in response to 4 unanticipated driving events. CNSVS included 10 measures of cognitive function. General linear mixed models assessed interaction between group and time for aim 1 and group and concussion assessment outcome for aim 2 (α = 0.05). Pairwise comparisons with Cohen's d values were used following significant interactions and main effects.</p><p><strong>Results: </strong>There was a significant main effect for timepoint, such that pedestrian RT was slower at the ≤72-h timepoint relative to both the asymptomatic (p value = 0.023) and unrestricted medical clearance (p- value = 0.022). There were no other significant group-by-timepoint interaction or timepoint main effects for yellow stoplight RT (p-value range = 0.334-0.798), vehicle incursion RT (p-value range = 0.234-0.925) or vehicle cross RT (p-value range = 0.177-0.364). There was no significant group main effect (p-value range = 0.077-0.955), assessment outcome main effect (p-value range = 0.099-0.999) or interaction (p-value range = 0.103-0.998) for predicting any of the RTs, except for executive function (<i>p</i> = 0.046), motor speed (<i>p</i> = 0.006), and psychomotor speed (<i>p</i> = 0.027) predicting vehicle cross RT regardless of group.</p><p><strong>Conclusion: </strong>This study demonstrates that driving RT may not differ between acutely concussed and healthy individuals or may not be detected on a short, simulated drive. Current clinical concussion outcomes poorly relate to driving RT. More research is needed to determine when it is safe to return to driving post-concussion.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-8"},"PeriodicalIF":1.6,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}