Evidence map›Paper›PMID 31372349›Full record

ArticleInternet interventions2019

A digital self-management intervention for adults with type 2 diabetes: Combining theory, data and participatory design to develop HeLP-Diabetes.

Charlotte Dack, Jamie Ross, Fiona Stevenson, Kingshuk Pal, Elsa Gubert, Susan Michie, Lucy Yardley, Maria Barnard, Carl May, Andrew Farmer and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Internet interventions, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Observational
  6. Article
  7. Co-Designing a Palliative Dementia Care Framework to Support Holistic Assessment and Decision Making: The EMBED-Care Framework.Health expectations : an international journal of public participation in health care and health policy · 2024
    Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Charlotte DackDepartment of Psychology, University of Bath, Claverton Down, Bath BA2 7AY, UK.
Jamie RossResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.
Fiona StevensonResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.
Kingshuk PalResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.
Elsa GubertResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.
Susan MichieCentre for Behaviour Change, Research Department of Clinical, Educational and Health Psychology, University College London, 1-19 Torrington Place, London WC1E 7HB, UK.
Lucy YardleyDepartment of Experimental Psychology, University of Bristol, Priory Road, Clifton BS8 1TU, UK.
Maria BarnardWhittington Health, Magdala Avenue, London N19 5NF, UK.
Carl MayFaculty of Health Sciences, University of Southampton, SO17 1BJ, UK.
Andrew FarmerNuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Bindie WoodResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.
Elizabeth MurrayResearch Department of Primary Care and Population Health, University College London, London NW3 2PF, UK.

Funding

Department of Health RP-PG-0609-10135
6 · The paper itself

Abstract

backgroundDigital health interventions have potential to contribute to better health outcomes, better healthcare and lower costs. However, evidence for their effectiveness is variable. The development and content of digital health interventions are often not described in enough detail to enable others to replicate the research or improve on previous interventions. This has led to a call for transparent reporting of intervention content and development. PURPOSE: To describe the development process and content of a digital self-management intervention for people with type 2 diabetes (HeLP-Diabetes) that has been found to achieve its target clinical outcome, the reduction of HbA1c, a measure of glycaemic control.

methodWe synthesised theory, data from existing research evidence and international guidelines, and new qualitative data from target users to identify the determinants of self-management and the content to be included in HeLP-Diabetes. Using an ongoing iterative participatory design approach the content of the intervention was written, produced, reviewed and changed.

conclusionIt is possible to develop and transparently report self-management programmes for long-term conditions, which reflect current best evidence, theoretical underpinning and user involvement. We intend that reporting the development process and content will inform future digital intervention development.

Indexed as

CBT, Cognitive Behaviour TherapyDiabetes mellitus, type 2Digital intervention developmentHCPs, Health Care ProfessionalsHealthTalk Online, HTOHeLP Diabetes, Healthy Living for People with Type 2 DiabetesInternetLLTTF, Living Life to the FullMRC, Medical Research CouncilNICE, National Institute for Health Care ExcellenceNPT, Normalisation Process TheoryParticipatory designPatient education as topicRNIB, Royal National Institute of Blind PeopleSelf-managementT2DM, Type 2 diabetes mellitus

Identifiers

PMID31372349
PMCPMC6660456

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.