Helmet (Health impact of e-bikes and e-scooters) study: Data collection methods and information gathered for the evaluation of the introduction of share hire schemes

Miranda EG Armstrong, James Garbutt, Tim Jones, Ben Spencer, Ian Philips, Sabina Sanghera, Lesley Welch, Rayne Roberts, Frank de Vocht, Russell Jago, Ruth Salway

Research output: Contribution to journalArticlepeer-review

Abstract

Background: This study aimed to collect information on e-bike and e-scooter use in areas with and without e-bike (EB) and e-bike plus e-scooter (EB+ES) combined share-hire schemes.

Methods: This study employed a repeated cross-sectional design. An online survey asking questions about demographics, travel, and health was completed by people in August and September 2023 before the schemes were launched in Bristol (EB+ES) and Leeds (EB), with Bradford and Sheffield as control sites. A resurvey was conducted at the same sites one year later, but also in Bath (EB+ES) and Plymouth (EB). We also interviewed eight e-bike and e-scooter users and non-users in Bristol (n=4) and Leeds (n=4).

Results: Following data cleaning, 3771 remained in the baseline sample and 5370 remained in the resurvey sample. The majority of participants reported having never used an e-bike (baseline: 61%; resurvey: 69%) or e-scooter (baseline: 77%; resurvey: 84%). At baseline, the most common e-bike access route was the use of their own e-bike (45%), with access via a share-hire scheme lower at 25%. In the resurvey sample, access levels were similar via a share-hire scheme (38%) and personal e-bikes (36%). The most common e-scooter access route was a share-hire scheme (baseline: 60%; resurvey: 74%). The most common weekly e-bike and e-scooter destinations were leisure/leisure venues, followed by work/education and shopping/errands.

Half said they would not use an e-bike scheme and 63% indicated they would not use an e-scooter scheme. Potential users were willing to walk ~500 m to access an e-bike/e-scooter.

Interviewees generally supported share-hire schemes, seeing them as a good addition to the wider transport offer, but with more support for e-bikes and reservations around e-scooters.

Conclusions: These data will be important for a later evaluation of EB and EB+ES share-hire schemes on public health, social, economic, and environmental factors.
Original languageEnglish
Article number44
JournalNIHR Open Research
Volume5
Early online date7 May 2025
DOIs
Publication statusPublished - 7 May 2025

Bibliographical note

Publisher Copyright:
Copyright: © 2025 Armstrong ME et al.

Data Availability Statement

This dataset was collected for use in a full, ongoing evaluation study running from January 2025 – December 2026 (NIHR163726, https://www.fundingawards.nihr.ac.uk/award/NIHR163726), and is therefore not publicly available at this time. Following the completion of the full evaluation study, fully anonymised datasets will be made available for public reuse in 2027 via the University of Bristol online data repository (Data.bris). Please email Dr Miranda Armstrong for further information regarding data access: [email protected].

Before sharing on Data.bris, all interview transcripts will have any possible identifying data redacted. Furthermore, all fields that could identify participants will not be shared in the dataset archived on Data.bris. Reuse is permissible under a Creative Commons Attribution 4.0 licence. The full study protocol for baseline and resurvey data collection, including the full questionnaire, can be found in the Open Science Framework online repository (https://osf.io/gq9s8/, DOI 10.17605/OSF.IO/GQ9S8).

Extended data
Extended data tables referenced within this manuscript are accessible at: https://osf.io/sbg2j via the Open Science Framework (OSF): HEaLth iMpact of E-bikes and e-scooTers (HELMET): Baseline data collection for the evaluation of e-bike and e-scooter hire schemes. Doi: https://doi.org/10.17605/OSF.IO/GQ9S849. These extended data tables are:

1. Extended Data Table 1. Respondent characteristics at baseline

2. Extended Data Table 2. Respondent characteristics at resurvey

3. Extended Data Table 3. Respondent characteristics at baseline and resurvey compared with Census 2021 data

4. Extended Data Table 4. Respondent transport use in a typical week at resurvey

Data are available under the terms of the Creative Commons Attribution 4.0 International license.

Acknowledgements

The authors would like to thank the Bradford Metropolitan District Council, Bristol City Council, Leeds City Council, Sheffield City Council, Bath and North East Somerset Council, Plymouth City Council and CNET Bradford for their contributions to the project. They would also like to thank the members of the Study Steering Committee ((Dr Paul Kelly (Chair - University of Edinburgh), Dr Anthony Laverty (Imperial College London), Mr Ian Achurch (North Northamptonshire Council), Mx Ben Foley (PPI Member), Miss Josephine Gyasi (PPI Member) and Mr Tim Burns (Sustrans)).

Funding

This study was funded by the National Institute for Health and Care Research (NIHR) PHR Rapid Funding Scheme (NIHR159622). This study has been delivered through the NIHR Bristol Biomedical Research Centre (BRC) and National Institute for Health and Care Research (NIHR) Applied Research Collaboration West (ARC West). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

FundersFunder number
National Institute for Health and Care Research
NIHR159622
NIHR Bristol Biomedical Research Centre
NIHR Imperial Biomedical Research Centre

    Keywords

    • e-bike
    • e-bike share hire
    • e-scooter
    • e-scooter share hire
    • natural experiment
    • physical activity

    ASJC Scopus subject areas

    • Epidemiology
    • Medicine (miscellaneous)
    • Health Policy
    • Public Health, Environmental and Occupational Health

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