IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i9p4831-d547325.html
   My bibliography  Save this article

The National ReferAll Database: An Open Dataset of Exercise Referral Schemes Across the UK

Author

Listed:
  • James Steele

    (Ukactive Research Institute, Ukactive, London WC1A 2SL, UK
    Faculty of Sport, Health, and Social Sciences, Solent University, Southampton SO14 0YN, UK)

  • Matthew Wade

    (Ukactive Research Institute, Ukactive, London WC1A 2SL, UK)

  • Robert J. Copeland

    (The Advanced Wellbeing Research Centre, Sheffield Hallam University, Sheffield S9 3TU, UK
    The National Centre for Sport and Exercise Medicine, Sheffield S9 3TY, UK)

  • Stuart Stokes

    (ReferAll Ltd., Worthing BN11 1LY, UK)

  • Rachel Stokes

    (ReferAll Ltd., Worthing BN11 1LY, UK)

  • Steven Mann

    (4Global Consulting Ltd., London W4 5YG, UK)

Abstract

In 2014, The National Institute for Health and Care Excellence (NICE) called for the development of a system to collate local data on exercise referral schemes (ERS). This database would be used to facilitate continued evaluation of ERS. The use of health databases can spur scientific investigation and the generation of evidence regarding healthcare practice. NICE’s recommendation has not yet been met by public health bodies. Through collaboration between ukactive, ReferAll, a specialist in software solutions for exercise referral, and the National Centre for Sport and Exercise Medicine, which has its research hub at the Advanced Wellbeing Research Centre, in Sheffield, data has been collated from multiple UK-based ERS to generate one of the largest databases of its kind. This database moves the research community towards meeting NICEs recommendation. This paper describes the formation and open sharing of The National ReferAll Database, data-cleaning processes, and its structure, including outcome measures. Collating data from 123 ERSs on 39,283 individuals, a database has been created containing both scheme and referral level characteristics in addition to outcome measures over time. The National ReferAll Database is openly available for researchers to interrogate. The National ReferAll Database represents a potentially valuable resource for the wider research community, as well as policy makers and practitioners in this area, which will facilitate a better understanding of ERS and other physical-activity-related social prescribing pathways to help inform public health policy and practice.

Suggested Citation

  • James Steele & Matthew Wade & Robert J. Copeland & Stuart Stokes & Rachel Stokes & Steven Mann, 2021. "The National ReferAll Database: An Open Dataset of Exercise Referral Schemes Across the UK," IJERPH, MDPI, vol. 18(9), pages 1-17, April.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4831-:d:547325
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/9/4831/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/9/4831/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luc Rocher & Julien M. Hendrickx & Yves-Alexandre de Montjoye, 2019. "Estimating the success of re-identifications in incomplete datasets using generative models," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    2. Jan Van den Broeck & Solveig Argeseanu Cunningham & Roger Eeckels & Kobus Herbst, 2005. "Data Cleaning: Detecting, Diagnosing, and Editing Data Abnormalities," PLOS Medicine, Public Library of Science, vol. 2(10), pages 1-1, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John R. J. Thompson & Longlong Feng & R. Mark Reesor & Chuck Grace, 2021. "Know Your Clients’ Behaviours: A Cluster Analysis of Financial Transactions," JRFM, MDPI, vol. 14(2), pages 1-29, January.
    2. Prabhsimran Singh & Yogesh K. Dwivedi & Karanjeet Singh Kahlon & Ravinder Singh Sawhney & Ali Abdallah Alalwan & Nripendra P. Rana, 0. "Smart Monitoring and Controlling of Government Policies Using Social Media and Cloud Computing," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    3. Ron S. Jarmin & John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Nathan Goldschlag & Michael B. Hawes & Sallie Ann Keller & Daniel Kifer & Philip Leclerc & Jerome P. Reiter & Rolando A. Rodrígue, 2023. "An in-depth examination of requirements for disclosure risk assessment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(43), pages 2220558120-, October.
    4. Ratul Das Chaudhury & Chongwoo Choe, 2023. "Digital Privacy: GDPR and Its Lessons for Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 56(2), pages 204-220, June.
    5. Rehse, Dominik & Tremöhlen, Felix, 2020. "Fostering participation in digital public health interventions: The case of digital contact tracing," ZEW Discussion Papers 20-076, ZEW - Leibniz Centre for European Economic Research.
    6. Tesary Lin & Sanjog Misra, 2022. "Frontiers: The Identity Fragmentation Bias," Marketing Science, INFORMS, vol. 41(3), pages 433-440, May.
    7. Atabey, Ayça & Pothong, Kruakae & Livingstone, Sonia, 2023. "Glossary of terms relating to children’s digital lives," LSE Research Online Documents on Economics 119728, London School of Economics and Political Science, LSE Library.
    8. German Data Forum RatSWD (ed.), 2020. "Data collection using new information technology," RatSWD Output Series, German Data Forum (RatSWD), volume 6, number 6-6en.
    9. Jeongwook Lee & Joon Jin Song & Yongku Kim & Jung In Seo, 2020. "Estimation and Prediction of Record Values Using Pivotal Quantities and Copulas," Mathematics, MDPI, vol. 8(10), pages 1-16, October.
    10. Miren Gutierrez & John Bryant, 2022. "The Fading Gloss of Data Science: Towards an Agenda that Faces the Challenges of Big Data for Development and Humanitarian Action," Development, Palgrave Macmillan;Society for International Deveopment, vol. 65(1), pages 80-93, March.
    11. Ziwen Sun & Ka Yan Lai & Simon Bell & Iain Scott & Xiaomeng Zhang, 2019. "Exploring the Associations of Walking Behavior with Neighborhood Environments by Different Life Stages: A Cross-Sectional Study in a Smaller Chinese City," IJERPH, MDPI, vol. 17(1), pages 1-16, December.
    12. Se-Ra Oh & Young-Duk Seo & Euijong Lee & Young-Gab Kim, 2021. "A Comprehensive Survey on Security and Privacy for Electronic Health Data," IJERPH, MDPI, vol. 18(18), pages 1-48, September.
    13. Frank C Mng'ong'o & Joseph J Sambali & Eustachkius Sabas & Justine Rubanga & Jaka Magoma & Alex J Ntamatungiro & Elizabeth L Turner & Daniel Nyogea & Jeroen H J Ensink & Sarah J Moore, 2011. "Repellent Plants Provide Affordable Natural Screening to Prevent Mosquito House Entry in Tropical Rural Settings—Results from a Pilot Efficacy Study," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-11, October.
    14. Lara Lusa & Marianne Huebner, 2021. "Organizing and Analyzing Data from the SHARE Study with an Application to Age and Sex Differences in Depressive Symptoms," IJERPH, MDPI, vol. 18(18), pages 1-20, September.
    15. Pasichnyi, Oleksii & Wallin, Jörgen & Levihn, Fabian & Shahrokni, Hossein & Kordas, Olga, 2019. "Energy performance certificates — New opportunities for data-enabled urban energy policy instruments?," Energy Policy, Elsevier, vol. 127(C), pages 486-499.
    16. Sevgi Arca & Rattikorn Hewett, 2021. "Analytics on Anonymity for Privacy Retention in Smart Health Data," Future Internet, MDPI, vol. 13(11), pages 1-20, October.
    17. Mariano Sana & Alexander A. Weinreb, 2008. "Insiders, Outsiders, and the Editing of Inconsistent Survey Data," Sociological Methods & Research, , vol. 36(4), pages 515-541, May.
    18. Carlo Giacomo Leo & Maria Rosaria Tumolo & Saverio Sabina & Riccardo Colella & Virginia Recchia & Giuseppe Ponzini & Dimitrios Ioannis Fotiadis & Antonella Bodini & Pierpaolo Mincarone, 2022. "Health Technology Assessment for In Silico Medicine: Social, Ethical and Legal Aspects," IJERPH, MDPI, vol. 19(3), pages 1-13, January.
    19. Margherita E. Ghiselli & Idongesit Nta Wilson & Brian Kaplan & Ndadilnasiya Endie Waziri & Adamu Sule & Halimatu Bolatito Ayanleke & Faruk Namalam & Shehu Ahmad Tambuwal & Nuruddeen Aliyu & Umar Kadi , 2019. "Comparison of Micro-Census Results for Magarya Ward, Wurno Local Government Area of Sokoto State, Nigeria, with Other Sources of Denominator Data," Data, MDPI, vol. 4(1), pages 1-19, January.
    20. Barry Dewitt & Baruch Fischhoff & Alexander L. Davis & Stephen B. Broomell & Mark S. Roberts & Janel Hanmer, 2019. "Exclusion Criteria as Measurements I: Identifying Invalid Responses," Medical Decision Making, , vol. 39(6), pages 693-703, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4831-:d:547325. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.