Electric scooter–related traumatic brain injuries: a scoping review of injury patterns, risk factors, management, and clinical outcomes

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OBJECTIVE: Electric scooters (e-scooters) have rapidly gained popularity in urban environments worldwide. While promoted as sustainable and convenient, their widespread adoption has led to a rise in injury rates, particularly traumatic brain injuries (TBIs). Despite increasing recognition of e-scooter-related head trauma, the literature remains fragmented and lacks focused synthesis. METHODS: A comprehensive search of PubMed, Embase, Scopus, Web of Science, and Cochrane databases was conducted in March 2025. Studies were included if they reported on e-scooter-related TBIs in real-world settings. The review followed PRISMA-ScR and Arksey and O'Malley guidelines. Data on demographics, mechanisms of injury, TBI severity, associated injuries, interventions, and outcomes were extracted. RESULTS: Twenty-five studies (3088 patients) met inclusion criteria. E-scooter-related TBIs predominantly affected young adults (median age 26-40 years), with males accounting for 61.5% of cases. Falls were the leading mechanism of injury (83.0%), often occurring in urban areas during evenings and weekends. Alcohol intoxication was reported in 31.1% of patients and drug use in 12.9%. Helmet use was strikingly low (2.4%). Common diagnoses included concussions (17.8%), contusions (11.5%), subarachnoid hemorrhages (6.1%), and subdural hematomas (4.1%). Associated injuries included maxillofacial trauma (15.4%) and upper limb fractures (24.5%). Surgical intervention was required in 21.8% of cases. Hospitalization occurred in 31.1% and ICU admission in 4.4%, and mortality ranged from 1.6% to 21.1%. Functional outcomes were inconsistently reported, but available data indicated generally favorable discharge outcomes (modified Rankin Scale scores 0-2). CONCLUSIONS: E-scooter-related TBIs represent a growing public health concern, marked by low helmet compliance and significant clinical variability. Future research should prioritize prospective data collection, behavioral risk factors, and robust evaluation of preventive strategies to guide policy and improve rider safety.

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