Risk Of Vehicle Collision Research Articles

Resident Physicians Have an Increased Risk of Adverse Driving Events Following Extended-Duration Work Shifts: A Systematic Review.

Resident physicians often work extended-duration work shifts (EDWSs) exceeding 16 hours. EDWSs are associated with fatigue, workplace errors, mental health problems, and motor vehicle incidents. A 2019 systematic review reported that resident physicians had an increased risk of motor vehicle collisions (MVCs) and of falling asleep at the wheel after EDWSs. This systematic review updates those findings with recent literature. Embase, PubMed, Cochrane Database, and Ovid Medline were searched for original research articles studying resident physician driving safety following EDWS. Two authors independently reviewed articles for inclusion. Both reviewers performed data extraction and quality appraisal for each included article. Six articles met the inclusion criteria. Three articles found associations between EDWS and increased sleepiness in resident physicians. Self-reported sleepiness was increased by 46% following an EDWS compared to a normal-length shift. Objective measures of sleepiness were also increased following an EDWS. Similarly, there was a three-fold increase in adverse driving events following an EDWS compared to pre-EDWS. One study found 3.90 higher odds of an adverse driving incident following an EDWS compared to a day shift. EDWS are associated with an increased risk of adverse driving incidents, including collisions and falling asleep while driving, in resident physicians. Possible solutions including compensation for ride-share and taxi services, scheduled breaks, education on risks of driving while fatigued, and the use of caffeine may lower the risk of adverse driving incidents post-EDWSs. Further research is needed to assess the impact of possible solutions.

Discrete element method simulation of high-speed vehicle collisions with road barrier systems

AbstractThe behavior of road or perimeter protection barriers under vehicle impact are usually investigated based on crash tests and finite element (FE) numerical approaches, which are ether expensive or time-consuming. Several studies have proposed to reduce the computation time of the numerical analysis by substituting the complex FE models of vehicles using simplified mass–spring–damper system models. However, these models have drawbacks since consideration of different vehicle impact angles is difficult and they are unable to correctly simulate the risk of high-speed vehicle collision running over the barrier. In this paper, a new approach is proposed to simulate the collision of vehicles with barriers based on the discrete element method (DEM). Here, to save computation time only a handful of 3D non-spherical particles are used to represent the barrier and vehicle. These particles are generated based on the super-quadric function, which is capable of generating a variety of shapes needed for the model. The contact detection and evaluation are carried out based on discrete function representation of the particles with uniform sampling. The bond between two discrete elements is defined using a nonlinear cohesive beam model since the distance between the elements is relatively large. The simulation results obtained based on this approach are more accurate and complete than the simplified mass–spring models and computationally more efficient than the FE model.

Comparison of hunting site strategies of the common buzzard Buteo buteo in open landscapes and along expressways.

The expansion of human activities in their many forms increases the frequency, diversity, and scale of human-wildlife interactions. One such negative form is the expansion of road infrastructure, causing road kill and traffic-related noise as well as habitat loss and fragmentation. Even so, habitats around road infrastructure are attractive foraging areas that attract certain bird species. We assessed the impact of road infrastructure on the foraging strategies of the common buzzard Buteo buteo. Birds were observed during two winter seasons in two land-use types, along an expressway and an open agricultural landscape. Individual birds were tracked for a 10-min sequence as a separate sample was analysed. The material, covering 1,220 min along the expressway, and 1,100 min in the agricultural landscape, was collected. Time spent by buzzards on medium-height sites was higher along the expressway than in farmland. Buzzards changed their hunting sites following the mean wind speed. Also, they more often changed their sites along the expressway than in farmland. The land-use types, snow cover, and the mean wind speed mediated the number of attacks on prey. These results illustrate the high plasticity of the buzzards' behaviour, which can adapt their hunting strategies to both foraging locations (expressway and farmland) and weather conditions. Roadsides along expressways are attractive foraging areas for this diurnal raptor, so reducing the risk of vehicle collisions with this and other birds of prey may require targeted planning efforts.

Urbanisation has impacted the population genetic structure of the Eurasian red squirrel in Japan within a short period of 30 years

Human activities often induce maladaptive effects in urban wildlife, such as increased inbreeding and decreased gene flow, consequently leading to a loss of biodiversity. Although maladaptive effects are commonly reported in urban wildlife, some wildlife species are not affected. Understanding the conditions and factors that affect the genetic structure of wildlife is crucial for its conservation in urban environments. Eurasian red squirrels Sciurus vulgaris in Obihiro City, Hokkaido, Japan, have settled in large residential lots with a high risk of vehicle collisions for approximately 30 years, raising the possibility that the urban population would be genetically isolated from nearby rural populations and may experience a rapid decrease in genetic diversity. In this study, we analysed the population structure, genetic distance, and nucleotide diversity of squirrels in the Obihiro area using genome-wide single nucleotide polymorphisms (SNPs). Principal component analysis and ADMIXTURE showed that urban and rural squirrel populations formed distinct clusters with intermediate urban and rural boundary populations. Genetic distances between the urban populations were greater than that of other pairs. Nucleotide diversities were lower in urban populations than in other populations, suggesting limited gene flow between urban and other populations, possibly due to urbanisation. The change in the genetic characteristics of urban squirrel populations during this short period demonstrates the strong impact of urbanisation. Our findings suggest that a genome-wide approach to the genetic structure of wildlife contributes to its conservation in urban environments.

Numerical investigation of impact response of bridge pier subjected to off-center vehicle collision

The increased risk of vehicle collisions on bridge piers causes damage to bridge structures and traffic congestion. In extreme cases, severe collisions caused by trucks lead to bridge collapse and loss of lives. Many studies have been conducted to investigate the dynamic responses of bridge piers subjected to vehicle collisions. Most of them focused on head-on (center-to-center) collisions based on the assumption that they represented the worst scenarios. However, off-center collisions were most often observed in vehicle collision accidents. In this study, bridge piers with different cross-section geometries (i.e., circular, and square) subjected to off-center vehicle collisions are numerically investigated. The results show that off-center vehicle collisions result in more severe spalling damage to the circular piers than head-on collisions. However, the curved surface of the circular piers effectively avoids inducing torsional response under off-center collisions. On the other hand, off-center collisions on square piers induce torsional response, thus more significant deformation, and damage than head-on collisions. Further mechanism analyses are conducted to explain the influence of off-center collisions, focusing on truck type and rectangular cross-section. Furthermore, some meaningful suggestions are put forward to resist off-center vehicle collisions for bridge piers in design process or in service.

EEG-based driving intuition and collision anticipation using joint temporal-frequency multi-layer dynamic brain network.

Intuition plays a crucial role in human driving decision-making, and this rapid and unconscious cognitive process is essential for improving traffic safety. We used the first proposed multi-layer network analysis method, "Joint Temporal-Frequency Multi-layer Dynamic Brain Network" (JTF-MDBN), to study the EEG data from the initial and advanced phases of driving intuition training in the theta, alpha, and beta bands. Additionally, we conducted a comparative study between these two phases using multi-layer metrics as well as local and global metrics of single layers. The results show that brain region activity is more stable in the advanced phase of intuition training compared to the initial phase. Particularly in the alart state task, the JTF-MDBN demonstrated stronger connection strength. Multi-layer network analysis indicates that modularity is significantly higher for the non-alert state task than the alert state task in the alpha and beta bands. In the W4 time window (1 second before a collision), we identified significant features that can differentiate situations where a car collision is imminent from those where no collision occurs. Single-layer network analysis also revealed statistical differences in node strength and local efficiency for some EEG channels in the alpha and beta bands during the W4 and W5 time windows. Using these biomarkers to predict vehicle collision risk, the classification accuracy of a linear kernel SVM reached up to 87.5%, demonstrating the feasibility of predicting driving collisions through brain network biomarkers. These findings are important for the study of human intuition and the development of brain-computer interface-based intelligent driving hazard perception assistance systems.

Revisiting Older Drivers' Risks of At-fault Motor Vehicle Collisions in Japan.

In Japan, older drivers have been encouraged to surrender their driving licenses for traffic safety, despite the potential adverse social and health outcomes of driving cessation. We reconsidered such policies and social pressure by comparing the risk of at-fault motor vehicle collisions (MVCs) across the age groups of drivers. Using the national data of police-reported MVCs that occurred between 2016 and 2020, we examined the number of at-fault MVCs per licensed driver (MVC rate) and the number of fatally and non-fatally injured persons per at-fault MVC by the sex and age groups of at-fault drivers. The MVC rate of older drivers was higher than that of middle-aged drivers but lower than that of young drivers. The number of injured persons among the collided counterparts (collided car occupants, motorcyclists, bicyclists, and pedestrians) per MVC caused by older drivers was not greater than that by drivers in other age groups. In fatal MVCs caused by older drivers, drivers themselves or their passengers tend to be killed rather than their collided counterparts. Overall, the results were mostly consistent between male and female drivers. The risk of at-fault MVCs increased with the advancing age of drivers after middle age; however, this risk among older drivers did not exceed that among young drivers, without posing a high risk of injuries to their collided counterparts.

Movements and habitat selection of a marsupial carnivore in a modified landscape

AbstractLandscape modification is a major threat to carnivores worldwide, but modified landscapes can also provide important habitat for these species, as protected areas alone are insufficient. Understanding how carnivores use modified landscapes, such as production forests, can inform management strategies to improve the value of these landscapes to carnivores. Little is known about habitat selection by marsupial carnivores in production forests, where they occupy a similar ecological niche to their more well‐studied eutherian counterparts. We used GPS tracking, Hidden Markov Models, and Manly's selection ratios to identify the habitat selected in three behavioral states by the largest marsupial carnivore, the Tasmanian devil (Sarcophilus harrisii), in a timber plantation‐dominated landscape. Behavioral states were approximated as: state 1, resting or feeding at a carcass; state 2, foraging; and state 3, travel. Devils did not show preferences for any of native forest, native grassland, and plantation in any behavioral state. Within plantations, devils preferred a plantation age of 4–7 years (selection ratio [wi] = 1.52). Devils preferred roads (state 1: wi = 2.71, state 2: wi = 2.48, state 3: wi = 2.97) and plantation edges (state 1: wi = 2.38, state 2: wi = 2.24, state 3: wi = 2.78) in all behavioral states, and moved faster on roads and edges than away from them. Together, our results indicate devils use road and edges for foraging (scavenging and hunting) and travel. No measured habitat variables influenced devil home range size. To support devils in plantation landscapes, we recommend maintaining a heterogeneous landscape of different plantation ages and native remnants and reducing the risk of vehicle collisions by minimizing forestry traffic at night. Tasmanian devils share similar adaptable traits to generalist eutherian carnivore species in their use of modified landscapes. Plantations can provide valuable habitat for this and other threatened predator species.

Risk of motor vehicle collision associated with cannabis and alcohol use among patients presenting for emergency care

BackgroundThe objective of this study was to examine the relationship between cannabis and alcohol use and occurrence of motor vehicle collision (MVC) among patients in the emergency department (ED). MethodsThis was a cross-sectional study of visits to EDs in Denver, CO, Portland, OR, and Sacramento, CA by drivers who were involved in MVCs and presented with injuries (cases) and non-injured drivers (controls) who presented for medical care. We obtained blood samples and measured delta-9-THC and its metabolites. Alcohol levels were determined by breathalyzer or samples taken in the course of clinical care. Participants completed a research-assistant-administered interview consisting of questions about drug and alcohol use prior to their visit, context of use, and past-year drug and alcohol use. Multiple logistic regression was used to estimate the association between MVC and cannabis/alcohol use, adjusted for demographic characteristics. We then stratified participants based on levels of cannabis use and calculated the odds of MVC across these levels, first using self-report and then using blood levels for delta-9-THC in separate models. We conducted a case-crossover analysis, using 7-day look-back data to allow each participant to serve as their own control. Sensitivity analyses examined the influence of usual use patterns and driving in a closed (car, truck, van) versus open (motorcycle, motorbike, all-terrain vehicle) vehicle. ResultsCannabis alone was not associated with higher odds of MVC, while acute alcohol use alone, and combined use of alcohol and cannabis were both independently associated with higher odds of MVC. Stratifying by level of self-reported or measured cannabis use, higher levels were not associated with higher odds for MVC, with or without co-use of alcohol; in fact, high self-reported acute cannabis use was associated with lower odds of MVC (odds ratio [OR] 0.18, 95% confidence interval [CI] 0.05–0.65). In the case-crossover analysis, alcohol use alone or in combination with cannabis was associated with higher odds of MVC, while cannabis use alone was again associated with decreased odds of MVC. ConclusionsAlcohol use alone or in conjunction with cannabis was consistently associated with higer odds for MVC. However, the relationship between measured levels of cannabis and MVC was not as clear. Emphasis on actual driving behaviors and clinical signs of intoxication to determine driving under the influence has the strongest rationale.

Modeling collision risk for unsafe lane-changing behavior: A lane-changing risk index approach

The lane-changing maneuvers are challenging and contributes to traffic accidents and crashes. They are complicated task that often lead to an increased risk of vehicle collisions and deteriorates traffic flow. This paper proposes a vehicle collision risk model based on vehicle lane-changing movement for autonomous vehicles using the probability threat assessment approach and the lane-changing risk index (LCRI). Given two vehicles, A and B, we first estimate the movements of vehicle B using a GPS device, which accurately identifies the vehicle while changing lanes. We then evaluate the collision risks between vehicles using the probabilistic assessment approach to determine whether a collision event occurs at a later stage. Then, we propose the LCRI, which aims to identify the risk level associated with vehicle lane-changing movement and determine the severity of the crash level. In this study, the HighD vehicle trajectory dataset is used to obtain accurate traffic information and help us investigating collision risks among vehicles. The results show that the proposed model can identify the risks of collision ahead of time. Furthermore, the random parameter ordered logit (RPOL) with heterogeneity model achieves better performance and provides a good fit model and measures for improving traffic safety.

Dynamic Risk Assessment and Control Framework for Work Zone and Its First Implementation under Simulation Environment

The number of road maintenance operations in China is increasing. Work zones can interfere with everyday driving and bring significant safety hazards to the throughput vehicles and construction personnel. However, there is currently a lack of effective methods to conduct a dynamic risk assessment of work zones and provide control guidance when necessary. Therefore, this study proposes a dynamic risk assessment and control framework for the work zones. The framework adopts a closed-loop control and dynamic monitoring architecture. A massive amount of microscopic data on vehicles’ behavior is obtained based on advanced data collection technologies (including multicamera multiobject tracking, naturalistic driving, and microscopic traffic simulation). Traffic conflicts between single vehicle and two- or multivehicle are detected using vehicle behavior analyzing technology and the surrogate safety assessment model. A comprehensive assessment index, i.e., UTECN (unit total equivalent conflict number), is established that can consider the severity and possibility of accidents caused by conflicts based on the vehicle collision energy theory, probability theory, and risk management theory. A risk assessment standard is established based on the level of safety service. The framework is first implemented in a simulation environment, and its feasibility and effectiveness are verified by taking a work zone of Shanghai Waihuan Expressway S20 as a case study. The result shows that the framework has good practicality. Under a moderate traffic level, the risk of the work zone can be assessed within 20 minutes. It can be quickly and effectively controlled at an acceptable level after several iterations, which is of great significance for ensuring the safety of life and property of throughput vehicles and construction personnel within the work zone.

Risk of motor vehicle collisions and culpability among older drivers using cannabis: a meta‐analysis

AbstractBackgroundWhile the effects of cannabis use on driving have been established in younger populations, limited studies have investigated this association among older adults, who represent the fastest growing segment of drivers globally.MethodWe conducted a systematic review and meta‐analysis to evaluate the effect of THC exposure on (1) risk of motor vehicle collisions (MVC) and (2) risk of culpability (being responsible for the collision), among adults 50 years and older. Three reviewers screened 7,022 studies identified through MEDLINE, EMBASE, CENTRAL, and PsycINFO and published between inception and 2021. Odds Ratios (OR) were calculated with a random‐effects model using the Mantel‐Haenszel method in Review Manager 5.4.1. Heterogeneity was assessed using I2. An adapted version of the National Heart, Lung, and Blood Institute quality assessment tool was used to assess the quality of each study.Result7 cross‐sectional studies were included. Three studies were rated ‘Good’ quality, one rated ‘Fair’, and three rated ‘Poor’. Three of the included studies evaluated culpability (NTHC+ = 239 NTHC‐ = 4609) while four evaluated MVC risk (NTHC+ = 158, NTHC‐ = 6152). We found that the pooled risk of MVC was not significantly different between older drivers exposed to THC and those who were not (OR, 95% CI 1.15 [0.40, 3.31]; I2 = 72%). In the studies assessing driver culpability, THC exposure was not significantly associated with an increased risk of being culpable for MVC among adults over the age of 50 (OR, 95% CI 1.24 [0.95, 1.61]; I2 = 0%). A visual inspection of the funnel plots did not indicate any publication bias.ConclusionOur review found that THC exposure was not associated with MVC involvement nor with culpability. However, it would be an oversimplification to conclude that cannabis use does not pose a safety risk to older drivers. Rather, our results may reflect several methodological limitations of the studies included in this review. Due to the increasing prevalence of cannabis use worldwide, we are optimistic that future research will be able to address this research question using more objective methodologies.

Variables Affecting the Risk of Vehicle Collisions in Australian Road Tunnels

The characteristics of road tunnels as part of the road network differ from those of general open roads, resulting in different vehicle collision characteristics. Understanding the characteristics of these collisions and the variables that contribute to them is critical for developing mitigation strategies. The purpose of this paper is to identify the characteristics of vehicle collisions in Australian road tunnels, as well as to investigate the variables that influence the number of casualties and the types of collisions. The study utilised data from seven road tunnels in Queensland and New South Wales. Data cleaning and transformation were carried out, yielding 12 variables for further analysis with statistical descriptive analysis, cross-tabulation, and logistic regression. The findings reveal that rear-end collisions are the most common type of collision in Australian road tunnels. Furthermore, only one variable had a significant impact on the number of casualties, while three variables had a significant impact on the types of collisions. These findings provide valuable insights for tunnel stakeholders in developing preventive measures to improve road tunnel safety.

Interactive on-ramp merging decision-making with motion prediction considering merging motivation

On-ramp is one of the scenarios most likely to cause traffic accidents and congestion. In order to mitigate the conflict between mainline vehicles and ramp vehicles, and improve vehicle safety and travel efficiency, we propose an interactive on-ramp merging decision-making (IORMDM) method based on motion prediction. We first propose a motion prediction method for different actions of vehicles based on model predictive control. Meanwhile, the game theory is employed to construct the interaction behavior between the ramp vehicle and the mainline vehicle, and the merging motivation of the ramp vehicle is modeled to describe the collision risk between it with the end of the acceleration lane. Afterward, according to the predicted trajectories of vehicles, the comprehensive payoff of vehicle collision risk, efficiency, passenger comfort, and merging motivation of each action is solved. The Nash equilibrium solution is solved to determine the optimal action of each vehicle according to the payoff table. Simulation experiments demonstrate that our proposed method could reduce collision risk and improve traffic efficiency.

Taiwan study cautions against methadone for drivers; NIDA responds

A recent literature review from Taiwan, “Risk of motor vehicle collisions after methadone use: A systematic review and meta‐analysis” by T.Y. Tsai and colleagues, found that methadone use is associated with an almost doubled risk of motor vehicle collisions, and concluded that “clinicians should exercise caution in implementing methadone maintenance therapy for drivers.” The study, published in the current issue of Drug and Alcohol Dependence, flies in the face of what is known in this country about methadone maintenance: that it is safe for driving when taken in therapeutic doses. We asked the National Institute on Drug Abuse (NIDA) to comment on the study. Here is what they said.

NIDA comments on Taiwan methadone‐driving study

A recent literature review from Taiwan, “Risk of motor vehicle collisions after methadone use: A systematic review and meta‐analysis” by T.Y. Tsai and colleagues, found that methadone use is associated with an almost doubled risk of motor vehicle collisions, and concluded that “clinicians should exercise caution in implementing methadone maintenance therapy for drivers.” The study, published in the current issue of Drug and Alcohol Dependence, flies in the face of what is known in this country about methadone maintenance: That it is safe for driving when taken in therapeutic doses. ADAW asked the National Institute on Drug Abuse (NIDA) to comment on the study. Here is what they said.

Risk perceptions of driving under the influence of cannabis: Comparing medical and non-medical cannabis users

BackgroundReduced perception of potential harm resulting from cannabis use is associated with greater risk of driving under the influence of cannabis (DUIC). Understanding risk perceptions of DUIC among subgroups of users will positively inform targeting and content of anti-DUIC driver education and public awareness campaigns. The current study compared DUIC-related risk perceptions among individuals who use cannabis exclusively for non-medical purposes versus those who use cannabis for exclusively medical or for both medical and non-medical purposes (i.e., dual-purpose users). MethodData were drawn from a regionally stratified cross-sectional general population telephone survey of adults (18 + years) in Ontario, Canada conducted in 2017. Respondents who reported past-year use of cannabis and answered questions regarding DUIC risk perceptions were selected (weighted N = 343). Modified Poisson regression models with robust standard error estimation were conducted for three attitudes: disagree that DUIC increases motor vehicle collision risk, agree that DUIC is safer than driving under the influence of alcohol (DUIA), agree that chances of being caught by police for DUIA higher than DUIC. In addition to type of cannabis user (non-medical only versus medical or dual-purpose), covariates included demographic characteristics and past-year alcohol and cannabis use frequency. ResultsAdjusting for other covariates, regression analyses indicated that medical or dual-purpose cannabis users were 45 % more likely than non-medical users to agree that DUIC is safer than DUIA (Adjusted Prevalence Ratio = 1.45, 95 %CI = 1.10, 1.91, p = 0.007). No other differences in risk perception between medical or dual-purpose and non-medical cannabis users were found. DiscussionAlthough no difference between medical or dual-purpose and non-medical cannabis users was found in perceptions of collision risk associated with DUIC or risk of police enforcement, the perception that DUIC is safer than DUIA was stronger among medical or dual-purpose than non-medical users. Recognizing that the shift in public perception of DUIA as a high-risk behaviour contributed to reductions in incidence of DUIA, results of the current study support education and awareness campaigns that target medical or dual-purpose users and emphasize that, like DUIA, DUIC is also a high-risk behaviour.

Risk of motor vehicle collisions after methadone use: A systematic review and meta-analysis

IntroductionMethadone maintenance therapy is a leading treatment strategy for stabilizing and rehabilitating patients with opioid dependence; however, findings related to the risk of motor vehicle collisions after methadone use have been conflicting. In the present study, we compiled the available evidence on the risk of motor vehicle collisions after methadone use. MethodsWe completed a systematic review and meta-analysis of studies identified on six databases. Two reviewers independently screened the identified epidemiological studies, extracted data, and used the Newcastle–Ottawa Scale to assess the quality of the studies. Risk ratios were retrieved for analysis, conducted using random-effects model. Sensitivity analyses, subgroup analyses, and tests for publication bias were conducted. ResultsAmong 1446 identified relevant studies, a total of 7 epidemiological studies enrolling 33226142 participants met the inclusion criteria. Overall, study participants with methadone use had a higher risk of motor vehicle collisions than did those without methadone use (pooled relative risk 1.92, 95% CI 1.25–2.95; number needed to harm 11.3, 95% CI 5.3–41.6); the I2 statistic was 95.1%, indicating substantial heterogeneity. Subgroup analyses revealed that database type explained 95.36% of the between-study variance (p = 0.008). Egger’s (p = 0.376) and Begg’s (p = 0.293) tests revealed no evidence of publication bias. Sensitivity analyses indicated that the pooled results were robust. ConclusionThe present review revealed that methadone use is significantly associated with a nearly doubled risk of motor vehicle collisions. Therefore, clinicians should exercise caution in implementing methadone maintenance therapy for drivers.

Risk of Motor Vehicle Collisions and Culpability among Older Drivers Using Cannabis: A Meta-Analysis.

Limited studies have investigated the effects of cannabis use on driving among older adults, who represent the fastest growing segment of drivers globally. We conducted a systematic review and meta-analysis to evaluate the effects of delta-9-tetrahydrocannabinol (THC) exposure on risks of (1) motor vehicle collisions (MVC) and (2) culpability for MVCs among adults 50 years and older. Three reviewers screened 7022 studies identified through MEDLINE, EMBASE, CENTRAL, and PsycINFO. Odds Ratios (OR) were calculated using the Mantel-Haenszel method in Review Manager 5.4.1. Heterogeneity was assessed using I2. The National Heart, Lung, and Blood Institute tool was used to assess the quality of each study. Seven cross-sectional studies were included. Three studies evaluated culpability while four evaluated MVC. The pooled risk of MVC was not significantly different between THC-positive and THC-negative older drivers (OR, 95% CI 1.15 [0.40, 3.31]; I2 = 72%). In culpability studies, THC exposure was not significantly associated with an increased risk of being culpable for MVC among adults over the age of 50 (OR, 95% CI 1.24 [0.95, 1.61]; I2 = 0%). Inspection of funnel plots did not indicate publication bias. Our review found that THC exposure was not associated with MVC involvement nor with culpability for MVCs.

Association between mandatory cognitive testing for license renewal and motor vehicle collisions and road injuries.

We examined whether the policy amendment from March 2017 for a cognitive screening test for older drivers at driver's license renewal was associated with the decreased risk of motor vehicle collisions for drivers and the increased risk of injuries for pedestrians and cyclists among older people. This was a controlled interrupted time-series study. We used police-reported data on the number of collisions as drivers and injuries as pedestrians and cyclists among people aged 70 years or older in Japan from July 2012 to December 2019. As the outcome measures, we used the ratio of the monthly number of collisions per population among drivers of three groups aged 75 years or older (75-79, 80-84, and ≥85 years), who were targeted or exposed by the policy, to that among drivers aged 70 to 74 years, who were unaffected or unexposed by the policy and would serve as controls. The ratio of pedestrian and cyclist injuries was also calculated, as previous studies have shown a concomitant increase in these injuries after the introduction of cognitive screening for driver's licenses. During the study period, there were 602,885 collisions as drivers and 196,889 injuries as pedestrians and cyclists among people aged 70 years or older. After the policy amendment in March 2017, collisions decreased among male drivers, and injuries increased among some age subgroups in both sexes. Cumulative estimated changes in the numbers of collisions and injuries from March 2017 to December 2019 were -3670 (95% confidence interval: -5125, -2104) and 959 (95% confidence interval: 24, 1834), respectively. Following the policy amendment, there was a decrease in motor vehicle collisions as drivers and an increase in road injuries as pedestrians and cyclists among older people.