Traffic Injury Prevention

Objectives Seatbelts decrease injuries and fatalities in motor vehicle collisions. Most seatbelt use studies are performed at a national or international scale, yet many lack data granularity to evaluate trends in population subgroups that might have differing belt use behaviors, such as pregnant females. Using data from the Center of Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS), this study aims to evaluate geographic differences in habitual seatbelt use and trends over time across respondent factors, focusing on pregnant females. Methods Weighted responses of “always wearing seatbelt” in the 2011–2024 BRFSS were aggregated by state, year, age group, sex, and pregnancy status and analyzed using a Bayesian zero-one-inflated beta regression. State seatbelt enforcement was coded as primary or secondary and added into the model. Results There were 1,149,325 total responses: 585,543 nonpregnant females (33.3% aged 18–29); 23,356 pregnant female (49.4% aged 18–29); and 540,426 males (39.5% aged 18–29). On average, primary enforcement states exhibit increased habitual seatbelt use adjusted for other factors (aOR = 1.63 (95% CrI 1.36–1.97)). In a secondary enforcement state, pregnant females had higher odds vs. nonpregnant females of habitual seatbelt use (aOR = 1.20 (95% CrI 1.02–1.44) for ages 18–29; aOR = 1.20 (0.99–1.42) for ages 30–44). Pregnancy effects were smaller in primary enforcement states. The probability of habitual seatbelt use among pregnant females increased since 2020 (primary enforcement: 0.86–0.88; secondary: 0.80–0.83), but decreased for nonpregnant females during the same period (primary enforcement: 0.85–0.82; secondary: 0.78–0.75). Regional variations in seatbelt use patterns and trends were identified. Conclusions Seat belt primary enforcement laws could increase habitual usage, regardless of age group and pregnancy status. Pregnant females continued to have higher habitual seatbelt use, with stronger effects among younger survey respondents. Additionally, we have identified a cluster of states in the Southeast with declining seatbelt use among both pregnant females and males. Better understanding of local enforcement policies and occupant attitudes toward seat belts can help develop interventions aimed at improving seat belt compliance and in-turn occupant safety.

Objectives The core aim of this study was to assess secondary task engagement among Australian cyclists, considering demographic, behavioral, and psychosocial factors as potential contributors. Methods This study used the information provided by a sample of 1,240 Australian cyclists (24% females; 74% males; 2% non-binary) aged M = 53.6 (SD 12.9) years. They responded to an online survey on cycling-related affairs, including demographic, psychosocial (Risk Perception and Regulation Scale, RPRS), behavioral (Cycling Behavior Questionnaire, CBQ), and technology-related (Affinity for Technology Questionnaire, TAEG) factors. Results After analyzing the TAEG properties and outcomes in this Australian sample, it was found that engagement in secondary tasks while riding varies significantly according to demographic and cycling behavioral profiles. For instance, older cyclists were less likely to report engaging in secondary tasks while riding. In terms of cycling behavior, respondents who reported higher rates of violations were more likely to report high engagement with technology while riding. Moreover, the results from a multilinear regression model predicting secondary task engagement indicated associations between self-reported cycling behavior and engagement in secondary tasks, as well as a strong relationship between traffic violations and the latter. Additionally, knowledge of traffic rules and self-reported positive behaviors showed a significant negative relationship with secondary task engagement, suggesting that these respondents were less inclined to use mobile devices while riding. Conclusion Overall, the findings of this study support the hypothesis that secondary task engagement can be statistically explained by demographic factors (such as age and gender), attitudinal factors, and cycling behavior. These findings highlight several challenges and implications for cycling safety practices, particularly considering the increasing normalization of technology-related secondary tasks in transport activities such as cycling.

Objective 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. Methods 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 via 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. Results 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. Conclusions 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.

Objectives: 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. Methods: 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. Results: 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 (P <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. Conclusions: 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.

Objective: 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. Methods: 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. Results: 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%). Conclusions: 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.