ArticleBMJ open2021
Protocol for a cluster randomised controlled trial of the DAFNE
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- From language matters to stigma-free communication in diabetes: Evolution, challenges, and next steps.Diabetic medicine : a journal of the British Diabetic Association · 2026Review
- Impaired awareness of hypoglycemia: can structured education address this persistent challenge?Frontiers in endocrinology · 2026Review
- Training DAFNEplus facilitators in novel behaviour change approaches: A template for training design and delivery.Diabetic medicine : a journal of the British Diabetic Association · 2025Article
- Accelerating diabetes innovation for real-world community impact through interdisciplinary research: Who is at the table?Diabetic medicine : a journal of the British Diabetic Association · 2025Article
- The collaborative working group method for pre-trial knowledge mobilisation: a qualitative evaluation of a structured process for iteratively refining a complex intervention (DAFNEplus).Pilot and feasibility studies · 2024Article
- Perceptions of adults with type 1 diabetes toward diabetes-specific quality of life measures: a survey-based qualitative exploration.Health and quality of life outcomes · 2024Article
- Prevalence and risk factors for diabetic foot complications among people living with diabetes in Harare, Zimbabwe: a cross-sectional study.BMC public health · 2024Article
- Analysis of real-world capillary blood glucose data to help reduce HbADiabetic medicine : a journal of the British Diabetic Association · 2023Article
- Automatic inference of hypoglycemia causes in type 1 diabetes: a feasibility study.Frontiers in clinical diabetes and healthcare · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
35 authors at 8 institutions in 4 countries.
Funding
Abstract
introductionThe successful treatment of type 1 diabetes (T1D) requires those affected to employ insulin therapy to maintain their blood glucose levels as close to normal to avoid complications in the long-term. The Dose Adjustment For Normal Eating (DAFNE) intervention is a group education course designed to help adults with T1D develop and sustain the complex self-management skills needed to adjust insulin in everyday life. It leads to improved glucose levels in the short term (manifest by falls in glycated haemoglobin, HbA1c), reduced rates of hypoglycaemia and sustained improvements in quality of life but overall glucose levels remain well above national targets. The DAFNE METHODS AND ANALYSIS: A pragmatic cluster randomised controlled trial in adults with T1D, delivered in diabetes centres in National Health Service secondary care hospitals in the UK. Centres will be randomised on a 1:1 basis to standard DAFNE or DAFNE ETHICS AND DISSEMINATION: Ethics approval was granted by South West-Exeter Research Ethics Committee (REC ref: 18/SW/0100) on 14 May 2018. The results of the trial will be published in a National Institute for Health Research monograph and relevant high-impact journals. TRIAL REGISTRATION NUMBER: ISRCTN42908016.
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Registered trials
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.