PHE 505 Module 10 Final Project Example

Bareheaded on Two Small Wheels: A Proposal to Study Helmet Use and Head Injury Among Injured Shared Scooter Riders

[Student Name]

Southern New Hampshire University

PHE 505: Research Methods in Public Health

Final Project

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Bareheaded on Two Small Wheels: A Proposal to Study Helmet Use and Head Injury Among Injured Shared Scooter Riders

Abstract

Background: Shared electric scooters have spread rapidly, injured riders often have head injuries and few wear helmets, but the protective effect of helmets for scooter riders has not been estimated with adjustment for other factors. Objective: To estimate how riding without a helmet relates to head trauma in adults seen after shared scooter crashes in a Midwestern university city. Methods: A retrospective review of records from two emergency departments and a university urgent care clinic over four years, analyzed as a case-control comparison of riders with and without head injury, using multivariable logistic regression adjusted for age, sex, alcohol, nighttime arrival and vehicle collision. Around 850 riders would give about 80% power for a halving of odds. Expected significance: Results will inform a pending city decision on helmet requirements and company helmet programs.

Significance

Head injuries cause most of the lasting harm from scooter crashes. In the city studied, emergency visits by injured shared scooter riders rose from 112 in the first year of service to 201 in the third, and about four in ten involved the head. The city council is debating a helmet rule for riders under 21 and asking operators to supply helmets, but it has no local evidence on how much helmets would help. A credible local estimate would inform that decision and widen a body of research that so far leans on big coastal metros.

Background

Studies of injured riders in Los Angeles and a California hospital network found head injuries in a large share of patients and documented helmet use of only 3% to 4% (Trivedi et al., 2019; Bloom et al., 2021). National emergency data showed scooter injuries and admissions rising steeply between 2014 and 2018 (Namiri et al., 2020). Compared with injured cyclists in Washington, DC, injured scooter riders rarely wore helmets and more often lost consciousness from concussion (Cicchino et al., 2021). For cyclists, a meta-analysis found that helmets roughly halved the odds of head injury (Olivier & Creighton, 2017). No scooter study has estimated a helmet effect adjusted for alcohol, time of day, age and vehicle involvement, and most scooter studies did not report how helmet status was determined.

Research Question and Hypotheses

Among adult riders treated after shared scooter crashes in the city, do riders not wearing a helmet have higher adjusted odds of head injury than helmeted riders? The primary hypothesis is that they do. Secondary hypotheses are that riding bareheaded also predicts brain injury specifically and, as an exploratory aim, that the association is stronger for late-night crashes Each has a corresponding null hypothesis of no association or no difference.

Methods

Design. The study reviews existing records retrospectively and compares riders with head injuries, the cases, against riders hurt only elsewhere, the controls, assuming helmets influence head injury but not other injuries.

Participants and setting. Adults aged 18 or older treated after a shared scooter crash at the city's two emergency departments or the university's urgent care clinic over four years are eligible; pedestrians struck by scooters, riders of private scooters and transfers are excluded.

Data collection. Records will be found by diagnosis codes and a keyword search of triage notes, then abstracted by two trained reviewers using written rules, with double abstraction of 10% and a kappa target of 0.7 or higher. Fifty records reviewed first will shake out the form and show how often helmet status is blank.

Sample size. Power was calculated with G*Power (Faul et al., 2007). Assuming 6% helmet use and 39% head injury among unhelmeted riders, about 850 riders provide close to 80% power to detect a halving of the odds, two-tailed at 0.05; three years at two hospitals alone would give only about half that power, which is why the urgent care clinic and a fourth year were added.

Analysis Plan

Riders will be described by helmet status and injury type. The main model will be a multivariable logistic regression of head injury on helmet use with the five covariates, reported as adjusted odds ratios and 95% confidence intervals. The traumatic brain injury model will mirror it, and a helmet by nighttime term will test the exploratory aim. Sensitivity analyses will reassign missing helmet status to each group in turn, exclude vehicle collisions and drop the urgent care records. Reporting will follow the STROBE checklist (von Elm et al., 2007).

Ethics

The study will seek approval from the hospitals' review board with a waiver of individual consent and of privacy authorization, justified by minimal risk and the impracticability of contacting former patients. Identifiers will be removed by the hospital analyst before abstraction, dates will be offset, small groups will not be reported and data will be destroyed under the hospital's retention schedule.

Limitations

Riders who were hurt but sought no care are missing, so results apply to riders whose injuries brought them to a clinic or hospital. Helmet status depends on documentation, which may be incomplete or recorded more often after head injuries. Speed, experience and road surface cannot be measured. The case-control assumption may not hold fully if helmets also change how riders fall. Findings from one city may not generalize.

Dissemination

Results will go to the city council and both scooter operators in a two-page brief, to hospital staff in a short presentation and to the county health board. A manuscript will be submitted to an injury prevention journal. If helmet status proves poorly documented, the study will also recommend a standard triage question for all micromobility injuries.

Timeline and Budget

The study would take nine months at modest cost.

Table 1. Timeline and budget

Note. Costs cover reviewer and statistician time; software is free.

Conclusion

The proposed study asks a narrow question that a city needs answered, uses data that already exist and plans honestly for its weaknesses, from limited power to missing helmet records. If funded, it would give local decision makers their first adjusted estimate of what helmets mean for injured scooter riders.

References

Bloom, M. B., Noorzad, A., Lin, C., Little, M., Lee, E. Y., Margulies, D. R., & Torbati, S. S. (2021). Standing electric scooter injuries: Impact on a community. American Journal of Surgery, 221(1), 227-232. https://doi.org/10.1016/j.amjsurg.2020.07.020

Cicchino, J. B., Kulie, P. E., & McCarthy, M. L. (2021). Injuries related to electric scooter and bicycle use in a Washington, DC, emergency department. Traffic Injury Prevention, 22(5), 401-406. https://doi.org/10.1080/15389588.2021.1913280

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://doi.org/10.3758/BF03193146

Namiri, N. K., Lui, H., Tangney, T., Allen, I. E., Cohen, A. J., & Breyer, B. N. (2020). Electric scooter injuries and hospital admissions in the United States, 2014-2018. JAMA Surgery, 155(4), 357-359. https://doi.org/10.1001/jamasurg.2019.5423

Olivier, J., & Creighton, P. (2017). Bicycle injuries and helmet use: A systematic review and meta-analysis. International Journal of Epidemiology, 46(1), 278-292. https://doi.org/10.1093/ije/dyw153

Trivedi, T. K., Liu, C., Antonio, A. L. M., Wheaton, N., Kreger, V., Yap, A., Schriger, D., & Elmore, J. G. (2019). Injuries associated with standing electric scooter use. JAMA Network Open, 2(1), Article e187381. https://doi.org/10.1001/jamanetworkopen.2018.7381

von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. The Lancet, 370(9596), 1453-1457. https://doi.org/10.1016/S0140-6736(07)61602-X