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OBJECTIVE: Prospective patient survey comparing profiles of riders injured using hired versus privately owned e-scooters across four major Queensland hospitals. METHODS: Multicenter prospective cohort study of emergency department presentations (May 2024-June 2025) involving e-scooter riders aged ≥16 years. Univariate generalized linear regression used to screen predictors of ownership type (hire vs private), followed by multivariable binary logistic regression. RESULTS: Of 218 eligible cases, 190 (87.2%) had complete data and were included in multivariable analyses. Infrequent e-scooter use was strongly associated with hire use. Compared with frequent users (6+ days/week), participants who rode once per week had substantially higher odds of being injured while using a hire e-scooter rather than a private e-scooter (OR 19.8, 95% CI 4.6-84.8). Riding at >25 km/h was associated with lower odds of hire use compared with ≤12 km/h (OR 0.04, 95% CI 0.01-0.23). Bruising/abrasions (vs fracture) were strongly associated with hire use (OR 15.2, 95% CI 3.6-64.1). Hire use was also more likely among participants who would have otherwise walked if an e-scooter were unavailable (OR 4.9, 95% CI 1.9-12.9) and those who had consumed alcohol prior to the incident (OR 10.0, 95% CI 2.0-51.0). Finally, late night injuries were more prevalent in hire scooters. CONCLUSIONS: While database/chart audit studies provide insights into the patterns of e-scooter injuries, it is only through data collection directly with patients can a more nuanced understanding of ownership profiles be established. Findings support targeted prevention, infrastructure and policy measures tailored to ownership profiles.
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Vallmuur et al. (2026) studied this question.
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