Traffic Injury Prevention最新文献

{"title":"Meta-analysis of crashes on two-lane rural highways using Bayesian Networks and Random Forest.","authors":"Randa Oqab Mujalli, Laura Garach, Alejandro Ruiz-Padillo","doi":"10.1080/15389588.2025.2472271","DOIUrl":"https://doi.org/10.1080/15389588.2025.2472271","url":null,"abstract":"<p><strong>Objective: </strong>The study used data for crashes that occurred on two-lane rural highways in Granada, Spain, over a four-year period (2016-2019). The obtained dataset consisted of 1,291 crashes. The data was used to identify the variables that influence crash injury severity.</p><p><strong>Methods: </strong>In this study, a hybrid meta-learning methodology based on Bayesian Networks (BNs) and Random Forest (RF) was used. To the authors' knowledge, these methods have never been combined in a single analysis. BNs identified the main factors influencing crash injury severity and the categories of these factors that are most important for each injury severity. These factors were ranked in importance from highest to lowest using RF.</p><p><strong>Results: </strong>It was found that the following variables significantly increase the risk of a fatality in a traffic crash: driver age, crash type, time of day, main crash cause according to police assessment, and lane width. In addition, it was found that the following categories of these factors were associated with a higher risk of fatality: driver age over 45, rollover crash type, nighttime lighting conditions, police reported driver distractions, and lane width of less than 3.25 meters.</p><p><strong>Conclusion: </strong>It became evident that using a hybrid meta-learning methodology based on BNs and RF was helpful in identifying the most significant factors, which influence the negative outcome of crashes. Local criteria that may evaluate the traffic safety of present and future highways should be developed and put into use in order to improve the level of traffic safety in two-lane rural highways, reducing the severity of injuries caused by traffic crashes and improving traffic safety.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143784447","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":"In-depth investigation into the hierarchical causal chain of fatal crashes between vulnerable road users and single motor vehicle.","authors":"Lan Huang, Xianghai Meng, Zhibin Ren","doi":"10.1080/15389588.2025.2471557","DOIUrl":"https://doi.org/10.1080/15389588.2025.2471557","url":null,"abstract":"<p><strong>Objectives: </strong>Crash pattern recognition and characterization are essential for reducing the damage vulnerable road users (VRUs) suffer in motor vehicle crashes. However, traditional methods provide an incomprehensive understanding of crash causality and the impacts of VRU-vehicle interactions. Therefore, this study aims to provide a reasonable causality for various types of crashes.</p><p><strong>Methods: </strong>To achieve this goal, a three-layer causal analysis framework was developed. The layers consist of physical states (mainly environmental and human factors), interactions (pre-crash behaviors of drivers and VRUs), and crashes. First, latent class cluster analysis and sequence analysis were used to identify the interactive behavior patterns and crash patterns of VRU-vehicle pairs, respectively. Besides, an oversampling algorithm was proposed to assist the Granger causality test in uncovering the latent causal relationships between pre-crash behavior patterns and crash patterns. Finally, Sankey diagrams were utilized to compare and analyze the crash path.</p><p><strong>Results: </strong>The results show that single and consecutive crashes have nine and eleven typical scenarios, respectively, excluding considering the potential causal chains. These potential causal chains provide nine new scenarios. It was found that personal subjective factors primarily influence pre-crash behavior of drivers, while for VRUs, the traffic environment plays a crucial role. Noteworthily, the highest crash risk was only associated with the causal chain where vehicles are unable to brake in time.</p><p><strong>Conclusions: </strong>Clarifying the causal relationships between VRU-vehicle interaction and crash is essential, which can help finding the critical causes of fatal crashes. The analysis identified VRU violations and the inability of vehicles to brake in time as critical determinants of crash severity in both single and consecutive crash scenarios. Accordingly, targeted safety interventions were proposed, including enhancements to pedestrian crossing infrastructure and improvements in vehicle braking systems to mitigate crash risk.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143784515","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":"Managing the road safety risks of last mile deliveries: Do telematics have a role to play?","authors":"Nicola Christie ,&nbsp;Sarah O’Toole ,&nbsp;Alice Holcombe ,&nbsp;Niamh Bull ,&nbsp;Shaun Helman","doi":"10.1080/15389588.2024.2413143","DOIUrl":"10.1080/15389588.2024.2413143","url":null,"abstract":"<div><h3>Objective</h3><div>The research aimed to understand the impact of telematics in reducing traffic violations and crashes among drivers working in parcel delivery and the perceived utility, effectiveness, and acceptability of telematics among drivers using them. The objective was to carry out an online survey among drivers who have telematics versus drivers who do not and compare their behaviors in terms of risks and violations controlling for key demographics an exposure.</div></div><div><h3>Methods</h3><div>An online anonymous survey was conducted of 780 home delivery drivers of which 430 used telematics in 2022. The survey was conducted by a fieldwork company and participants were compensated for their time. Univariate and multivariate analysis was conducted on the data.</div></div><div><h3>Results</h3><div>Telematics users did not report less crashes than drivers who did not use telematics. Most drivers, irrespective of telematics use agreed that the time pressure of delivery work increased speed limit violations and unsafe or hazardous parking. Multivariate analysis indicated that damage collisions for all drivers were associated with factors such as, driving medium to large vans, hazardous behavior related to parking, and having penalties for violations, especially related to speed. Delivery drivers, while generally facing pressure to speed and take risks to meet delivery schedules, did perceive telematics as a tool for safety enhancement and information dissemination, as well as for the management of performance. Non-telematics users viewed it with skepticism.</div></div><div><h3>Conclusions</h3><div>Telematics alone may not ensure the safety of last-mile deliveries and could potentially increase the pressure of deliveries. This research underscores the need for a holistic approach to road safety in the home delivery sector, combining telematics technology with a proactive safety culture.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 300-306"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142569989","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":"Crash data availability and best practices across the United States.","authors":"Hannah Younes, Robert B Noland","doi":"10.1080/15389588.2025.2466201","DOIUrl":"https://doi.org/10.1080/15389588.2025.2466201","url":null,"abstract":"<p><strong>Objective: </strong>Though data on fatal crashes are available through the Fatality Analysis Reporting System (FARS) and are readily available to the public, many states do not make their crash data (including injuries) easily accessible for the public and the research community. The public has an interest in knowing when and where crashes occur, partly so they can demand that authorities improve safety. Researchers have an interest in being able to download data and conduct analyses to better understand mechanisms that lead to crashes and assist decision makers in designing effective policies. The objective of our study is to document the state of crash data availability throughout the country and to determine the best practices for crash data management and procedures for making data open and easily accessible.</p><p><strong>Methods: </strong>We reviewed 2 main dimensions of crash data, raw crash data and dashboards, by scouring the internet and reaching out to relevant stakeholders. We also conducted structured in-depth interviews of those responsible for crash data in selected states and various users of the data.</p><p><strong>Results: </strong>We compiled a comprehensive nationwide database of open crash data characteristics for states and cities that provide such data. The database is available online in an effort to increase data transparency. Our interviews with stakeholders uncovered multiple issues beyond transparency, including quality control, usability, data linkages, data analysis, collaborations between stakeholders, and other political and financial constraints.</p><p><strong>Conclusions: </strong>Conclusions from our analysis include (1) the importance of linking crash data with other data sets (e.g., injury surveillance data); (2) the need for partnerships and collaborations between universities, advocates, and agencies; and (3) challenges with management of quality control. We present the results of our quantitative and qualitative work to offer best practices and Vision Zero guidance for state policymakers and traffic crash data experts.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782011","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":"Investigating the eye-catching effect in the entrance zone of highway tunnels through heart rate variability analysis","authors":"Lei Han ,&nbsp;Zhigang Du ,&nbsp;Shoushuo Wang","doi":"10.1080/15389588.2024.2405034","DOIUrl":"10.1080/15389588.2024.2405034","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to investigate the influence of visual attraction conditions on drivers’ cognitive workload and physiological responses, assessed through heart rate variability (HRV) indicators. The study examined four experimental scenarios, including a baseline condition and three visual attractions (landscape-style architecture, tip slogan, and billboard) at tunnel entrances.</div></div><div><h3>Methods</h3><div>HRV indicators, including RMSSD, SDNN, LF, and LF/HF ratio, were analyzed to assess cognitive workload and physiological states. The study collected data from a sample of drivers under each experimental scenario and compared the HRV measures across conditions.</div></div><div><h3>Results</h3><div>The presence of visual attractions at tunnel entrances significantly impacted drivers’ HRV. The introduction of visual attractions resulted in decreased RMSSD and SDNN values, indicating increased cognitive workload and reduced adaptability of the autonomic nervous system. Moreover, visual attractions led to increased LF values and LF/HF ratio, suggesting heightened sympathetic activation and potential cognitive engagement.</div></div><div><h3>Conclusions</h3><div>Visual attractions have a significant impact on drivers’ cognitive workload and physiological responses. Designing tunnel entrances with a balance between visual attractiveness and cognitive demands is essential to optimize drivers’ cognitive performance and overall driving experience. These findings provide valuable insights for transportation authorities and designers to create safer and more user-friendly tunnel environments.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 316-324"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367361","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":"Estimation and modeling of pedestrian dilemma zone at uncontrolled intersections under mixed traffic conditions","authors":"Govinda Lalam ,&nbsp;Ravishankar K.V.R","doi":"10.1080/15389588.2024.2409382","DOIUrl":"10.1080/15389588.2024.2409382","url":null,"abstract":"<div><h3>Objectives</h3><div>Pedestrian gap acceptance (PGA) theory is the basic concept for pedestrian dilemma zone (PDZ) analysis and modeling and their gap acceptance behavior depends on dilemma behavior also. Uncontrolled intersections are one of the major locations where pedestrians have more dilemma and there is a possibility of an interaction between the pedestrian and vehicle due to the incorrect decision taken by the pedestrian when the vehicle lies within the limits of PDZ. Elimination and modeling of spatial boundaries of pedestrian dilemma stage improve the PGA.</div></div><div><h3>Methods</h3><div>The present study is intended to quantify and model the pedestrian dilemma zone (PDZ) boundaries at uncontrolled X-intersections under mixed traffic conditions. Video data were collected from four four-legged uncontrolled intersections in India. Pedestrian and vehicle information was extracted using DataFromSky software and manually from video. The Cumulative Gap Distribution (GCD) and Support Vector Machine (SVM) methods were used to estimate the boundaries of PDZ and developed a binary logistic regression model to estimate the PDZ boundary limits.</div></div><div><h3>Results</h3><div>The lower boundary limits of PDZ using GCD and SVM methods are 9.0 m and 6.0, respectively, and the upper boundary limits of PDZ using GCD and SVM methods are 16.5 and 18.5 m, respectively. The GCD method overestimated the lower limit and underestimated the upper limit compared with the SVM method. The binary logistic regression model results confirmed that pedestrian age, gender and crossing speed have a negative correlation and location of pedestrian crossing, vehicle type, and approaching speed have a positive correlation with the boundary limits of PDZ.</div></div><div><h3>Conclusions</h3><div>From the present study, it is concluded that SVM better estimated the PDZ boundary limits with the largest margin compared to the GCD method. It is concluded that the boundary limits shift away from the intersection in the case of female and old-age pedestrians compared to male and young-age pedestrians, respectively. The size benefit in the case of 2Ws is the reason for shifting the PDZ boundary limits close to the crosswalk. The lower approaching speeds of the vehicles at uncontrolled intersections are the reason for pedestrians accept the gap at shorter distances.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 360-368"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481010","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":"Five-year trend analysis of drug use among individuals 16 years of age and older injured in non-fatal motor vehicle crashes in the US","authors":"Nae Y. Won ,&nbsp;Kelly K. Gurka ,&nbsp;Linda B. Cottler","doi":"10.1080/15389588.2024.2405038","DOIUrl":"10.1080/15389588.2024.2405038","url":null,"abstract":"<div><h3>Objective</h3><div>To examine the prevalence of drug use among individuals (age 16+) injured in non-fatal motor vehicle crashes (MVCs) from 2019 to 2023 and assess regional differences based on US Census regions (i.e., West, Midwest, Northeast, and South), and thereby contribute to a comprehensive understanding of drug-related MVCs.</div></div><div><h3>Methods</h3><div>We examined emergency medical services data from 19 US states (January 2019 to December 2023) to determine the annual mean drug use prevalence among individuals (age 16+) injured in non-fatal MVCs. Differences in drug use prevalence were assessed using ANOVA with the Tukey-Kramer test for year-to-year comparisons. Adjusted Poisson regression models with random effect for states were used to compare trends to the baseline (i.e., 2019) and to assess regional differences.</div></div><div><h3>Results</h3><div>Among individuals (age 16+) injured in non-fatal MVCs, 62,310 had reported drug use. ANOVA results showed significant year-to-year differences in the prevalence of drug use among individuals injured in non-fatal MVCs, with an increase from 2019 to 2020 and a subsequent decrease from 2020 to 2023 (<em>p</em> &lt; 0.05). Compared to the baseline year of 2019, the prevalence in 2020 was 1.34 times (95% confidence interval [CI]: 1.12, 1.61) the prevalence in 2019. The prevalence in 2022 and 2023 were similar to the 2019 prevalence. Although no significant associations were found between US regions and the overall mean prevalence from 2019 to 2023; there was a difference in the average annual rate of change in prevalence by region, with a 4.0% lower rate in the Midwest compared to the Northeast (<em>p</em> &lt; 0.001). This signifies a need to monitor future trends for potential regional differences.</div></div><div><h3>Conclusions</h3><div>Drug use prevalence among individuals (age 16+) injured in non-fatal MVCs increased from 2019 to 2020; then decreased to levels reflecting baseline prevalence in 2019; with no significant regional differences in the overall mean crash-related drug use prevalence. These findings highlight the need for continuous surveillance across the US over an extended period. They also underscore the potential impact of environmental risk factors, such as the COVID-19 pandemic, and the necessity to monitor how drug use prevalence related to non-fatal MVCs changes in the coming years.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 273-280"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481011","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":"Development of hazard prediction test and interventions for two-wheeled electric vehicle riders in China","authors":"Yanqun Yang ,&nbsp;Xinli Wu ,&nbsp;Yang Feng ,&nbsp;Said M. Easa ,&nbsp;Xinyi Zheng","doi":"10.1080/15389588.2024.2410417","DOIUrl":"10.1080/15389588.2024.2410417","url":null,"abstract":"<div><h3>Objective</h3><div>This paper aimed to develop a hazard prediction test and enhance two-wheeled electric vehicle (TWEV) riders’ hazard perception and prediction capabilities <em>via</em> interventions by executing two distinct studies. Study 1 aimed to develop and validate a hazard prediction test. Study 2 evaluated the efficacy of two interventions, self-commentary and what happens next (WHN), integrating expert commentary.</div></div><div><h3>Method</h3><div>For Study 1, a video-based hazard prediction test was developed through video recording and clipping, with participants categorized into high and low prediction ability groups for experimentation. Data analysis employed the receiver operating characteristic (ROC) curve. Study 2 categorized participants into four groups: self-commentary with licenses (SCL), self-commentary without licenses (SCNL), WHN with licenses (WHNL), and WHN without licenses (WHNNL), for conducting a one-week intervention experiment. Data collected from participants’ pre-intervention, post-intervention, and aftereffect tests were subjected to repeated measures analysis of variance (ANOVA).</div></div><div><h3>Results</h3><div>Analysis of the ROC curve indicated the test can distinguish the riders with different hazard prediction levels. ANOVA results demonstrated that the measurement time had a significant positive effect on scores (<em>p</em> &lt; 0.001). Both interventions significantly improved hazard prediction ability (<em>p</em> &lt; 0.05), and the effect persisted one week after administration. The effect of the WHN intervention was significantly greater than the self-commentary method across all time points.</div></div><div><h3>Conclusion</h3><div>The hazard prediction test developed in this study could assess riders’ hazard prediction ability, with the identified interventions demonstrating effectiveness in enhancing this ability. These findings suggested potential application in future qualification tests for TWEV riders, contributing to enhanced traffic safety awareness among TWEV riders in China, thus advancing overall traffic safety.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 325-334"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481009","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 dual-message tactile sliding takeover requests on takeover performance in an automated driving system","authors":"Zihao Qiu ,&nbsp;Huiyan Lai ,&nbsp;Hangyan Wu ,&nbsp;Meina Wang ,&nbsp;Xinkui Hu ,&nbsp;Hongyan Liu ,&nbsp;Shu Ma ,&nbsp;Zhiguo Hu","doi":"10.1080/15389588.2024.2409980","DOIUrl":"10.1080/15389588.2024.2409980","url":null,"abstract":"<div><h3>Objective</h3><div>The present study aimed to explore the effects of various tactile takeover requests (TORs) (i.e., tactile sliding TOR and traditional vibration TOR) on the takeover performance in an automated driving system.</div></div><div><h3>Methods</h3><div>A tactile sliding motor device was developed to signal the sliding TOR on the seatback of a driving simulator. Twenty-five young drivers were recruited as participants. Four types of TOR patterns were adopted in the study: ipsilateral motor rotation (IR), contralateral motor rotation (CR), ipsilateral and contralateral motor rotation (ICR), and ipsilateral motor vibration (IV). The participants were required to sit on the seat and underwent the automated driving in a low- or high-complexity scenario, then one of the four types of TORs was triggered randomly. The participants were asked to make a lane change using the steering wheel as soon as possible. Objective measures and subjective evaluations were used to assess the takeover performance.</div></div><div><h3>Results</h3><div>Results showed that the participants exhibited a shorter steering response time and lane change time under the three tactile sliding TORs (compared to the traditional vibration TOR). In the high-complexity scenarios and low-complexity scenarios conditions, different result patterns appeared regarding the maximum lateral acceleration and situational awareness.</div></div><div><h3>Conclusion</h3><div>Our findings suggested that the tactile sliding motor is a promising way to signal a TOR in an automated driving system.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 307-315"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142669773","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":"Evaluating risks, monitoring cannabis use, and planning to get home safely: Exploring self-regulation processes associated with cannabis use and driving","authors":"Paweena Sukhawathanakul ,&nbsp;Jie Li ,&nbsp;Alejandra Contreras ,&nbsp;Otis Geddes ,&nbsp;Myles Maillet","doi":"10.1080/15389588.2024.2413442","DOIUrl":"10.1080/15389588.2024.2413442","url":null,"abstract":"<div><h3>Objective</h3><div>Preventing Cannabis-impaired driving involves understanding how users assess risk, monitor their use, and plan to get home safely. While extant research has shown substantial heterogeneity in patterns of cannabis use among different user groups, far less research has examined self-regulation among users. The current study aims to identify sub-groups of individuals who used or have used cannabis based on how they perceive risks, monitor their impairment, and plan to avoid driving under the influence of cannabis (DUIC) to examine how the different profiles relate to DUIC outcomes.</div></div><div><h3>Methods</h3><div>Participants were a Canadian sub-sample in the province of British Columbia who participated in the 2022 International Cannabis Policy study and reported ever using or currently using cannabis (<em>N</em> = 886, M_age = 43.58, SD_age = 13.67; 63% female). Risk perception, impairment monitoring, planning ability, DUIC-related behaviors, Cannabis use and related problems were assessed through an online self-reported survey.</div></div><div><h3>Results</h3><div>Latent profile analysis identified three groups of self-regulators based on their level of risk perception, monitoring, and plan to avoid DUI. The majority (51%) of participants showed moderate self-regulation with average levels of risk perception, monitoring, and planning. A “highly self-regulated” group (20%) had the highest risk perception, monitoring, and planning. A “low self-regulated” group (29%) had the lowest risk perception, less confidence in monitoring, and lower DUI planning. There were significant differences between the profiles and DUIC outcomes. Cannabis users (including both historical and current users) with high self-regulation were less likely to be passengers of drivers under the influence and more likely to intervene to stop friends from driving while impaired, compared to those with low or moderate self-regulation. However, there were no profile differences in reports of having ever driven under the influence of cannabis.</div></div><div><h3>Conclusions</h3><div>Differences in risk perception, monitoring, and planning are associated with self-regulatory abilities. Understanding diverse self-regulation patterns among people who have used cannabis can help identify and mitigate risky behaviors, including DUI.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"26 3","pages":"Pages 263-272"},"PeriodicalIF":1.6,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142669775","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}