Abstract
Background: Germ Defence (www.germdefence.org) is an evidence-based interactive website that promotes behaviour change for infection control within households. To maximise the potential of Germ Defence to effectively reduce the spread of COVID-19, the intervention needed to be implemented at scale rapidly. Methods: With NHS England approval, we conducted an efficient two-arm (1:1 ratio) cluster randomised controlled trial (RCT) to examine the effectiveness of randomising implementation of Germ Defence via general practitioner (GP) practices across England, UK, compared with usual care to disseminate Germ Defence to patients. GP practices randomised to the intervention arm (n = 3292) were emailed and asked to disseminate Germ Defence to all adult patients via mobile phone text, email or social media. Usual care arm GP practices (n = 3287) maintained standard management for the 4-month trial period and then asked to share Germ Defence with their adult patients. The primary outcome was the rate of GP presentations for respiratory tract infections (RTI) per patient. Secondary outcomes comprised rates of acute RTIs, confirmed COVID-19 diagnoses and suspected COVID-19 diagnoses, COVID-19 symptoms, gastrointestinal infection diagnoses, antibiotic usage and hospital admissions. The impact of the intervention on outcome rates was assessed using negative binomial regression modelling within the OpenSAFELY platform. The uptake of the intervention by GP practice and by patients was measured via website analytics. Results: Germ Defence was used 310,731 times. The average website satisfaction score was 7.52 (0–10 not at all to very satisfied, N = 9933). There was no evidence of a difference in the rate of RTIs between intervention and control practices (rate ratio (RR) 1.01, 95% CI 0.96, 1.06, p = 0.70). This was similar to all other eight health outcomes. Patient engagement within intervention arm practices ranged from 0 to 48% of a practice list. Conclusions: While the RCT did not demonstrate a difference in health outcomes, we demonstrated that rapid large-scale implementation of a digital behavioural intervention is possible and can be evaluated with a novel efficient prospective RCT methodology analysing routinely collected patient data entirely within a trusted research environment. Trial registration: This trial was registered in the ISRCTN registry (14602359) on 12 August 2020.
| Original language | English |
|---|---|
| Article number | 67 |
| Number of pages | 13 |
| Journal | Implementation science |
| Volume | 18 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 4 Dec 2023 |
Bibliographical note
Funding Information:B. G., H. J. C., S. B. and A. M. have received research funding from the Laura and John Arnold Foundation, the NHS National Institute for Health Research (NIHR), the NIHR School of Primary Care Research, NHS England, the NIHR Oxford Biomedical Research Centre, the Mohn-Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, the Wellcome Trust, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organisation, UKRI MRC, Asthma UK, the British Lung Foundation and the Longitudinal Health and Wellbeing strand of the National Core Studies programme. B. G. is a Nonexecutive Director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. C. B. is employed by TPP, UK. R. A. is an employee of the UK Health Security Agency. All other authors declare that they have no competing interests.
Funding Information:
This research is funded by UKRI Coronavirus Rapid Response Call (CV220-009) and National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) West at University Hospitals Bristol and Weston NHS Foundation Trust and NIHR Health Protection Research Unit (HPRU) in Behavioural Science and Evaluation at University of Bristol. UKRI did not play any part in the design of this study, collection, analysis and interpretation of data and in writing the manuscript. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. Research in OpenSAFELY uses data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). In addition, the OpenSAFELY platform is supported by grants from the Wellcome Trust (222097/Z/20/Z), MRC (MR/V015737/1, MC_PC-20059, MR/W016729/1), NIHR (NIHR135559, COV-LT2-0073) and Health Data Research UK (HDRUK2021.000, 2021.0157).
Funding Information:
We thank the participating primary care practices and all the clinicians and patients who took part in the study. In addition, we would like to thank Chris Voisey and Margie Berrow CRN West of England and Ed Park from the NIHR CRN Coordinating Centre for their help with management of the study and Chris Metcalfe (University of Bristol) for his assistance with the randomisation of practices. We also thank all who have supported and disseminated Germ Defence, including the University of Bath (Andy Dunne) and NIHR HPRU in Behavioural Science and Evaluation at University of Bristol (Helen Bolton and Clare Thomas), NIHR ARC West (Zoe Trinder-Widdess). We thank all who have assisted in the translation of Germ Defence into other languages (documented here: http://lang.germdefence.org/). We also thank the many citizen scientists and public contributors who assisted in the development of the Germ Defence intervention. We are very grateful for all the support received from the TPP Technical Operations team throughout this work and for generous assistance from the information governance and database teams at NHS England and the NHS Transformation Directorate. OpenSAFELY collective Alex J. Walker7, Brian MacKenna7, Peter Inglesby7, Caroline E. Morton7, Jessica Morley7, George Hickman7, Richard Croker7, David Evans7, Tom Ward7, Nicholas J. DeVito7, Louis Fisher7, Amelia C. A. Green7, Jon Massey7, Rebecca M. Smith7, William J. Hulme7, Simon Davy7, Colm D. Andrews7, Lisa E. M. Hopcroft7, Henry Drysdale7, Iain Dillingham7, Robin Y. Park7, Rose Higgins7, Christine Cunningham7, Milan Wiedemann7, Linda Nab7, Steven Maude7, Ben F. C. Butler-Cole7, Thomas O'Dwyer7, Catherine L. Stables7, Christopher Wood7, Andrew D. Brown7, Victoria Speed7, Lucy Bridges7, Andrea L. Schaffer7, Caroline E. Walters7, Christopher T. Rentsch14, Krishnan Bhaskaran14, Anna Schultze14, Elizabeth J. Williamson14, Helen I. McDonald14, Laurie A. Tomlinson14, Rosalind M. Eggo14, Kevin Wing14, Angel Y. S. Wong14, John Tazare14, Daniel J. Grint14, Sinead Langan14, Kathryn E. Mansfield14, Ian J. Douglas14, Stephen J. W. Evans14, Liam Smeeth14, Jemma L. Walker14, Viyaasan Mahalingasivam14, Thomas E. Cowling14, Emily L. Herrett14, Ruth E. Costello14, Bang Zheng14, Edward P. K. Parker14, Rohini Mathur15, Harriet Forbes6, Jonathan Cockburn8, John Parry8, Frank Hester8, Sam Harper814London School of Hygiene and Tropical Medicine, UK15Queen Mary, University of London
Publisher Copyright:
© 2023, The Author(s).
Keywords
- Behaviour change
- COVID-19
- Digital medicine
- Efficient trial design
- eHealth
- Infection control
- Primary care
- RCT
- Respiratory tract infections