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Alyssa Joachim, MD
John Schomberg, PhD
Marizen Ramirez, MPH, PhD
Nikolas Mendoza
Natalia Solange Ramirez-Mendoza
Bryant Mendoza
Melanie Tacher Otero, MD
April A. Carlson, MD
Spencer Wilhelm, MD
Romeo Ignacio, MD
Amy Lawrence, MD
Yigit Guner, MD, MS
Laura Goodman, MD, MPH

As electric bike (e-bike) popularity continues to rise, the number of injuries resulting from e-bike accidents are also increasing. E-bike crashes can result in a wide spectrum of injuries, and even death, and are often more severe than injuries with traditional bicycles due to the higher associated speeds. E-bikes are generally classified based on speed and throttle presence: class 1 reaches speeds up to 20 miles per hour (mph) with pedal-assist, class 2 includes throttle assistance up to 20 mph, class 3 includes pedal-assist with a top assisted speed of 28 mph, and class 4 exceeds 28 mph using electric assistance. Although many municipalities have introduced legislation restricting pediatric access to higher speed e-bike classes, limited data exists regarding how e-bike class impacts collisions and injuries.

We performed a retrospective analysis of police-reported e-bike collisions involving riders ?18 years recorded in the Statewide Integrated Traffic Records System (SWITRS) between 2021-2025. Demographic characteristics, roadway conditions, injury severity, and collision factors were analyzed and compared by e-bike class.

A total of 384 collisions involving class 1-3 e-bikes and 267 collisions involving class 4 e-bikes were identified. The median rider age was 14 years in both groups; however, class 4 riders were more frequently ages 11-14 (61.7% vs 49.2%) and less likely to be aged 15-18 (35.5% vs 47.9%) compared with riders of class 1-3 e-bikes (p=0.009). Class 4 riders were more frequently male than class 1-3 riders (80.5% vs. 76.3%, p=0.02). Serious injuries occurred more often among class 4 riders compared to class 1-3 e-bike riders (10.8% vs. 5.98%, p=0.05). Riders of class 4 e-bikes were also more likely to be identified as at fault for the collision (65.1% vs 60.9%, p <0.0001), although rates of unsafe riding behaviors did not significantly differ between groups (12.3% vs 10.1%, p=0.37).

Class 4 e-bikes are capable of speeds exceeding 28 mph, often traveling at speeds similar to cars. Despite these risks, a substantial proportion of riders involved in collisions with class 4 e-bikes were children under the age of 15. Pediatric riders of class 4 e-bikes were also more likely to be deemed at fault and to sustain serious injuries following collisions. These findings support ongoing enforcement efforts for age restrictions on high-speed e-bikes and highlight the need for parent and rider education regarding e-bike classification and the associated risks, both physical and legal.

1. Risks associated with higher class (high speed) e-bikes
2. Understanding who is more at risk for e-bike collisions
3. Specific data-driven targets for e-bike education and legislative interventions

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Katia C. Genadry, MD
Amir A. Kimia, MD
James M. Chamberlain, MD
Alek Jorge, BA
Jennifer E. Welcher, MBA
Assaf Landschaft, MS
Kavya A. John, BS
Nina D. Kosciuszek, DO, MS
Fahd A. Ahmad, MD, MSCI
Lois K. Lee, MD, MPH

Micromobility device injuries, including e-bikes and e-scooters, are increasing. Injury surveillance commonly relies on administrative data (e.g. ICD-10 codes). However, their accuracy for identifying micromobility injuries is unknown, and relevant clinical details are often lacking. The objectives of this study were to: (1) analyze micromobility injury case identification when ICD-10 codes are augmented with natural language processing (NLP) of emergency department (ED) clinical narratives, and (2) examine detailed characteristics of these injuries and trends over time.

We conducted a multicenter cross-sectional study of patients 0-18 years old presenting with e-bike and e-scooter injuries to four tertiary-care pediatric EDs. Two centers contributed data from January 2022–December 2025, while the other two contributed data from January–December 2025. ED narratives were annotated using the NLP platform, Document Review Tools (DrT), which uses regular expressions to highlight relevant specific text. Two mutually exclusive approaches were used to identify micromobility-related injuries: (1) NLP analysis of ED electronic health record (EHR) narratives, and (2) ICD-10 codes. We a priori established a sensitivity ?95% for the models. The final NLP models were applied across all 4 site EHR narratives and aggregated results were analyzed. Data from all 4 centers was used to analyze characteristics of the injuries. Data from 2 centers covering 4 years were used to evaluate trends. We performed linear regression to analyze temporal trends in injury rates over time.

There were a total of 719 micromobility-related injuries identified using DrT from the study sample including all 4 sites: 303 (42.1%) e-bikes and 416 (57.8%) e-scooters. The performance metrics for the NLP models were: sensitivity 97.1% (95% CI 92-100%), specificity 84% (95% CI 79-89%), accuracy 91%, and F1-score 0.86. ICD-10 codes identified only 198 cases (27%) of all confirmed micromobility injuries. The median age of patients was 13 years [IQR 10.5-15.0 years]. Overall 29% of injures were in females, with differences by device: 18% females for e-bikes and 36% females for e-scooter. For e-bikes the leading mechanisms of injuries were: falls (32%), motor vehicle collisions (MVCs) (20%), and collisions with stationary object (13%). For e-scooters the leading mechanisms of injuries were: falls (48%), MVCs (20%), and due to road bump/pothole (9%). Helmet use was only documented as being used for 22% of e-bike injuries and 10% of e-scooter injuries. Time trends demonstrated statistically significant increases in micromobility injuries from 2022-2025 (p<0.01) (Figure 1A), as well as the proportion of micromobility injuries from MVCs (p<0.01) (Figure 1B).

Micromobility injuries from e-bikes and e-scooters are increasing, including from collisions with motor vehicles. Reliance on ICD-10 codes alone underestimates the incidence and limits surveillance. NLP of ED narratives improves injury identification and captures granular clinical details unavailable in administrative coding, supporting more effective surveillance and injury prevention research.

1- Describe the increasing burden of micromobility injuries (e-bikes, e-scooters) including injuries from motor vehicle collisions.
2- Recognize the limitations of relying solely on ICD-10 coding for identifying and surveilling micromobility-related injuries.
3-Explain how natural language processing of emergency department narratives can improve injury identification and provide detailed clinical information to support surveillance and injury prevention research.

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Julie Mansfield, PhD
Gretchen Baker, PhD
Cassandra Herring, BS
Morag MacKay, MSc

Motor vehicle crashes are consistently a leading cause of death and injury for children in the United States. Seat belts and booster seats are effective at reducing the risk of death and injury for pediatric occupants of motor vehicles. The objective of this study was to conduct an online survey of booster seat-aged children to define appropriate vs. inappropriate restraint use, identify high-risk behaviors, explore reasons for transitioning to new methods of restraint, and determine whether seat checks or riding with other drivers affects restraint behaviors.

A total of 3,026 parents and primary caregivers of children ages 4-10 years in the United States completed an online survey about their child’s passenger restraint type, knowledge and usage habits, reasons for using the restraint, and family demographics. Restraint type was categorized as appropriate or inappropriate based on reported child height and weight. Descriptive statistics, multivariable regressions, and chi-square tests were used to identify trends associated with various populations.

Restraint types were reported as rear-facing or forward-facing harness restraint (21.0%), booster seat (49.1%), seat belt alone (26.0%), and unrestrained (3.9%). Younger children were significantly more likely to be appropriately restrained and always seated in the rear seat compared to older children. Most “seat belt only” users (81.7%) had not yet reached the recommended height of 57 inches. Non-parent primary caregivers, those of lower socioeconomic levels, and Black Non-Hispanic families were significantly more likely to have children in an inappropriate restraint type. Allowing children to sit in the front row was significantly more likely among parents, especially highly educated males. Attendance at car seat checks was associated with appropriate restraint use, although gaps in booster seat-related knowledge persisted.

Despite continuing efforts in child passenger safety, fatality rates remain high for unrestrained and inappropriately restrained children. Many children in the current study transitioned restraint types before meeting the recommended height or weight milestones, especially for the transition from booster to seat belt alone. This work provides practical applications such as identifying populations who might benefit from targeted messaging campaigns or educational interventions to address specific types of high-risk behaviors and attitudes. Innovative intervention strategies should be explored using these population-based data as a guide.

1) Identify age ranges and populations of children most at risk of riding inappropriately restrained in vehicles.
2) Explore factors that influence caregivers’ decision-making processes for vehicle travel with their children.
3) Discuss opportunities to tailor messages for specific populations’ needs.

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Julie Mansfield, PhD
Gretchen Baker, PhD
Janelle Ozmun

Seat belts, booster seats, and child restraint systems (CRS) are among the most effective tools for reducing pediatric death and injuries in motor vehicle crashes (MVCs). Despite their proven effectiveness, large proportions of children continue to ride unrestrained or improperly restrained, especially elementary school-aged children.

Safety culture within families and communities plays a central role in child restraint practices. Children riding with unrestrained adult drivers have higher rates of being unrestrained or inappropriately restrained. These data highlight the intergenerational transmission of safety behaviors and the importance of addressing restraint use with a broader family and community context. Our state faces particular challenges related to occupant restraint. The state ranks 40th nationally for seat belt usage, with only 84.8% of the population buckling up.

These data form the basis of the objective of this program: to fill the need for innovative, effective solutions tailored to families with school-aged children, particularly in communities where safety culture is weak or underdeveloped.

A new program was developed in 2024 through a collaboration between the state Traffic Safety Office and a major university. The "Buckle Up" program is a classroom-based curriculum designed for elementary school children. It includes a facilitator’s guide enabling community representatives to lead a one-hour classroom session. The program is designed for law enforcement, school resource officers, nurses, or other community representatives to present the session in their local school classrooms. This builds a sense of community support and positive exposure for students to their local safety advocates.

The curriculum demonstrates how seat belts work using toy cars with egg occupants, emphasizes correct booster seat use, and encourages children to advocate for their own safety in vehicles. Instruction is reinforced through guided discussion, hands-on activities, and a high-energy song-and-dance video (the "Seat Belt Boogie") featuring the state university's beloved mascot. Supplemental materials, including word puzzles, drawing exercises, and parent handouts, reinforce key safety messages.

The program is funded by our state government. The entirety of the educational content can be downloaded for free from the state's Traffic Safety Office website. Presenters of the program can submit a request form for free items to hand out to students (tape measures and flashing reflectors). Presenters also receive monetary reimbursement for their agency to compensate for their time spent in the classroom.

Since its launch in Fall 2024, the Buckle Up program has been delivered to more than 17,000 elementary school students across 39 counties. Program adoption continues to grow as positive feedback spreads through participating communities. To ensure continued growth, our team will conduct focus groups with program users over Summer 2026 and incorporate improvements into the program for future classrooms. We will also launch a systematic evaluation of the program with students and parents beginning in Fall 2026.

By embedding safety education within the school environment, the Buckle Up program reinforces consistent safety messaging across the adults and peers in a child’s life.

1) Learn how one state government has worked together with safety experts and community advocates to build a robust car safety program for elementary school students.
2) Identify the key aspects of the program which can be replicated in other states or communities.
3) Discuss how similar programs can be evaluated to understand both the short-term and long-term effects of raising children in a safety-focused community.