Effectiveness of digital and remote provision of the Healthier You: NHS Diabetes Prevention Programme during the COVID‐19 pandemic
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Aims: To assess weight change in the Healthier You: NHS Diabetes Prevention Programme (NHS DPP) delivered via video conferencing (remote) sessions or delivered via specific digital interventions through apps or websites, during the COVID‐19 pandemic compared to group‐based face‐to‐face interventions, pre‐pandemic. Methods: Prospectively collected national service‐level data relating to individuals with non‐diabetic hyperglycaemia (HbA 1c 42–47 mmol/mol (6.0%–6.4%) or fasting plasma glucose 5.5–6.9 mmol/L) referred to the NHS DPP from June 2016 to March 2022. Results: Between March 2020 and March 2022, 335,961 people were referred to the programme and were offered a choice of remote or digital intervention. This was preceded by 556,793 people referred to the face‐to‐face programme between June 2016 and February 2022. Uptakes to intervention sessions were 47% for those offered a choice and 39% for face‐to‐face. Remote and digital participants were significantly younger (60 and 56 vs. 65 years) and heavier (86.1 kg and 91.0 kg vs. 84.1 kg) compared to face‐to‐face. Weight change was assessed for 42,407 remote, 7699 digital and 97,205 face‐to‐face participants with sufficient time to have finished the programme and no missing data. Mean weight losses for participants attending at least one intervention session were: 2.40 (2.36–2.44) kg, 2.59 (2.49–2.68) kg and 2.01 (1.98–2.04) kg for remote, digital and face‐to‐face participants respectively. Corresponding mean weight losses for those who completed the programme were: 3.24 (3.19–3.30) kg, 4.76 (4.60–4.92) kg and 3.04 (3.00–3.07) kg. There were no significant differences in weight change between interventions by ethnicity and deprivation. Conclusions: Weight losses achieved through remote and digital interventions were greater than those previously achieved through face‐to‐face interventions, without evidence of exacerbation of health inequalities.
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In a study of more than 330 000 participants of the national DPP, there were similar rates of greater than or equal to 5% weight loss with in-person and distance learning formats (34.3% vs 37.2%).
“Ina study of more than 330 000 participants of the national DPP, there were similar rates of greater than or equal to 5% weight loss with in-person and distance learning formats (34.3% vs 37.2%) and, in the UK National Health Service DPP, synchronous remote delivery produced slightly greater weight loss than prepandemic in-person sessions (2.40 kg vs 2.01 kg).46,47”
From An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial (2025) · cites this paper as [47]
In the UK National Health Service DPP, synchronous remote delivery produced slightly greater weight loss than prepandemic in-person sessions (2.40 kg vs 2.01 kg).
“Ina study of more than 330 000 participants of the national DPP, there were similar rates of greater than or equal to 5% weight loss with in-person and distance learning formats (34.3% vs 37.2%) and, in the UK National Health Service DPP, synchronous remote delivery produced slightly greater weight loss than prepandemic in-person sessions (2.40 kg vs 2.01 kg).46,47”
From An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial (2025) · cites this paper as [47]
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van Deursen, A. J., & van Dijk, J. A. (2019) · New Media & Society · doi:10.1177/1461444818797082 · Cited by 1,234 · see citing works
Estacio, E. V., Whittle, R., & Protheroe, J. (2017) · Journal of Health Psychology · doi:10.1177/1359105317695429 · Cited by 315 · see citing works
Validation of self-reported height and weight in a large, nationwide cohort of U.S. adults
Hodge, J. M., Shah, R. A., McCullough, M. L., Gapstur, S. M., & Patel, A. V. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231229 · Cited by 252 · see citing works
Kriaučionienė, V., Bagdonavičienė, L., Rodríguez‐Pérez, C., & Petkevičienė, J. (2020) · Nutrients · doi:10.3390/nu12103119 · Cited by 249 · see citing works
Joiner, K. L., Nam, S., & Whittemore, R. (2017) · Preventive Medicine · doi:10.1016/j.ypmed.2017.04.033 · Cited by 223 · see citing works
Early Outcomes From the English National Health Service Diabetes Prevention Programme
Valabhji, J., Barron, E., Bradley, D., Bakhai, C., Fagg, J., O’Neill, S., Young, B., Wareham, N., Khunti, K., Jebb, S., et al. (2020) · Diabetes Care · doi:10.2337/dc19-1425 · Cited by 211 · see citing works
Self-citationLongitudinal Weight Gain and Related Risk Behaviors during the COVID-19 Pandemic in Adults in the US
Bhutani, S., vanDellen, M. R., & Cooper, J. A. (2021) · Nutrients · doi:10.3390/nu13020671 · Cited by 208 · see citing works
Van Rhoon, L., Byrne, M., Morrissey, E., Murphy, J., & McSharry, J. (2020) · DIGITAL HEALTH · doi:10.1177/2055207620914427 · Cited by 182 · see citing works
Albury, C., Strain, W. D., Brocq, S. L., Logue, J., Lloyd, C., & Tahrani, A. (2020) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(20)30102-9 · Cited by 170 · see citing works
Chew, H. S. J., & Lopez, V. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18041876 · Cited by 114 · see citing works
Chatterton, H. T., Younger, T., Fischer, A., Khunti, K. K., & on behalf of the Programme Development Group (2012) · BMJ · doi:10.1136/bmj.e4624 · Cited by 107 · see citing works
Self-citationThe effect of technology-mediated diabetes prevention interventions on weight: a meta-analysis
Bian, R. R., Piatt, G. A., Sen, A., Plegue, M. A., De Michele, M. L., Hafez, D., Czuhajewski, C. M., Buis, L. R., Kaufman, N., & Richardson, C. R. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.4709 · Cited by 99 · see citing works
Mulugeta, W. M., Desalegn, H., & Solomon, S. (2021) · Clinical Obesity · doi:10.1111/cob.12453 · Cited by 91 · see citing works
Barron, E., Clark, R., Hewings, R., Smith, J. A. E., & Valabhji, J. (2017) · Diabetic Medicine · doi:10.1111/dme.13562 · Cited by 81 · see citing works
Self-citationRoss, J., Barron, E., McGough, B., Valabhji, J., Daff, K., Irwin, J., Henley, W., & Murray, E. (2022) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002736 · Cited by 60 · see citing works
Self-citationValabhji, J., Barron, E., Bradley, D., Bakhai, C., Khunti, K. K., & Jebb, S. A. (2021) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(21)00218-7 · Cited by 27 · see citing works
Self-citationPrevention of type 2 diabetes through remotely administered lifestyle programs: A systematic review
Villegas, V., Shah, A., Manson, J. E., & Tobias, D. K. (2022) · Contemporary Clinical Trials · doi:10.1016/j.cct.2022.106817 · Cited by 18 · see citing works
McGough, B., Murray, E., Brownlee, L., Barron, E., Smith, J. A. E., & Valabhji, J. (2019) · Diabetic Medicine · doi:10.1111/dme.14083 · Cited by 17 · see citing works
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Research works printed but not linked: 2
- [2]Parkinson B, MCManus E, Meacock R; M Sutton Health Organisation, Politics and Economics (HOPE) research group. The effectiveness of the NHS Diabetes Prevention Programme at reducing type 2 diabetes incidence amongst people with non‐diabetic hyperglycaemia. 10.1111/dme.14809 · DOI
- [6]National Institute for Health and Care Excellence. BMI: preventing ill health and premature death in black, Asian and other minority ethnic groups. Accessed May 8, 2022. https://www.nice.org.uk/guidance/ph46 31841286
Cited by
Sorted by citations
Anson, M., Henney, A. E., Broadwell, N., Zhao, S. S., Ibarburu, G. H., Lip, G. Y. H., Wilding, J. P. H., Cuthbertson, D. J., & Alam, U. (2024) · eClinicalMedicine · doi:10.1016/j.eclinm.2024.102777 · Cited by 44 · see citing works
Mathioudakis, N., Lalani, B., Abusamaan, M. S., Alderfer, M., Alver, D., Dobs, A., Kane, B., McGready, J., Riekert, K., Ringham, B., et al. (2025) · JAMA · doi:10.1001/jama.2025.19563 · Cited by 41 · see citing works
Abusamaan, M. S., Ballreich, J., Dobs, A., Kane, B., Maruthur, N., McGready, J., Riekert, K., Wanigatunga, A. A., Alderfer, M., Alver, D., et al. (2024) · Trials · doi:10.1186/s13063-024-08177-8 · Cited by 16 · see citing works
Lalani, B., Shim, J., Vadini, V., Valdez, Y., Zade, D., & Mathioudakis, N. (2025) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2025.1562108 · Cited by 7 · see citing works
- Authors
- Barron, E., Bradley, D., Safazadeh, S., McGough, B., Bakhai, C., Young, B., Khunti, K., Murray, E., Wareham, N., Jebb, S., & Valabhji, J.
- Affiliations
- NHS England (GB)
- Diabetes UK (GB)
- University of Leicester (GB)
- University College London (GB)
- MRC Epidemiology Unit Institute of Metabolic Science, University of Cambridge Cambridge UK
- University of Oxford (GB)
- Imperial College Healthcare NHS Trust (GB)
- Corresponding author
- Barron, Emma
- ORCID
- Venue
- Diabetic Medicine
- Publisher
- Wiley
- Published
- 2023-01-21
- Volume
- 40
- Issue
- 5
- Pages
- e15028-e15028
- ISSN
- 0742-3071 (ISSN-L)
- 1464-5491
- PMC
- PMC9878108
- OpenAlex
- W4311663549
- Cited by
- 32
- References
- 18
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 16 · 2023: 7
- FWCI
- 6.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetic Medicine (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- NHS Diabetes Prevention Programme, diabetes prevention, remote delivery, digital interventions, videoconferencing, weight loss, COVID-19 pandemic, face-to-face intervention, health disparities, ethnic differences, socioeconomic deprivation
- MeSH terms
- COVID-19, Diabetes Mellitus, Type 2, Humans, State Medicine, Weight Loss, Pandemics
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