Evidence map›Paper›PMID 35976184›Full record

ArticleJMIR research protocols2022

Digital Interventions Supporting Self-care in People With Type 2 Diabetes Across Greater Manchester (Greater Manchester Diabetes My Way): Protocol for a Mixed Methods Evaluation.

Joanna Goldthorpe, Thomas Allen, Joanna Brooks, Evangelos Kontopantelis, Fiona Holland, Charlie Moss, Deborah J Wake, Doogie Brodie, Scott G Cunningham, Naresh Kanumilli and 10 more

Abstract read
In one paragraph

Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

20 authors.

Joanna Goldthorpe *Manchester Centre for Health Psychology, School of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-7839-7544
Thomas AllenManchester Centre for Health Economics, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-2972-7911
Joanna BrooksManchester Centre for Health Psychology, School of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-0220-9847
Evangelos KontopantelisDivision of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-6450-5815
Fiona HollandDivision of Population Health, Health Services Research and Primary Care, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-2702-307X
Charlie MossDivision of Population Health, Health Services Research and Primary Care, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-4694-378X
Deborah J WakeMy Way Digital Health, Dundee, United Kingdom.ORCID https://orcid.org/0000-0003-4376-6973
Doogie BrodieMy Way Digital Health, Dundee, United Kingdom.ORCID https://orcid.org/0000-0002-3504-4519
Scott G CunninghamMy Way Digital Health, Dundee, United Kingdom.ORCID https://orcid.org/0000-0003-0861-8676
Naresh KanumilliNorthenden Group Practice, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-3080-7713
Hannah BishopGreater Manchester & Eastern Cheshire Strategic Clinical Networks, Greater Manchester Health & Social Care Partnership, Manchester, United Kingdom.ORCID https://orcid.org/0000-0003-4673-7000
Ewan JonesGreater Manchester & Eastern Cheshire Strategic Clinical Networks, Greater Manchester Health & Social Care Partnership, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-5164-6192
Nicola MilneDiabetes, Endocrinology & Metabolism Centre, Manchester Royal Infirmary, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-2290-4698
Steve BallDiabetes, Endocrinology & Metabolism Centre, Manchester Royal Infirmary, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-5134-2006
Mark JenkinsOviva Health, London, United Kingdom.ORCID https://orcid.org/0000-0002-3234-273X
Bogna NicinskaOviva Health, London, United Kingdom.ORCID https://orcid.org/0000-0002-2314-0132
Martina RattoBeingwell Group, English Institute of Sport, Sheffield, United Kingdom.ORCID https://orcid.org/0000-0002-2470-1990
Michael Morgan-CurranMyCognition Ltd, London, United Kingdom.ORCID https://orcid.org/0000-0002-5598-804X
Gemma JohnsonChanging Health Limited, Newcastle upon Tyne, United Kingdom.ORCID https://orcid.org/0000-0002-2826-7925
Martin K RutterDiabetes, Endocrinology & Metabolism Centre, Manchester Royal Infirmary, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-6380-539X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 2 Diabetes (T2D) is common, with a prevalence of approximately 7% of the population in the United Kingdom. The quality of T2D care is inconsistent across the United Kingdom, and Greater Manchester (GM) does not currently achieve the National Institute for Health and Care Excellence treatment targets. Barriers to delivery of care include low attendance and poor engagement with local T2D interventions, which tend to consist of programs of education delivered in traditional, face-to-face clinical settings. Thus, a flexible approach to T2D management that is accessible to people from different backgrounds and communities is needed. Diabetes My Way (DMW) is a digital platform that offers a comprehensive self-management and educational program that should be accessible to a wide range of people through mobile apps and websites. Building on evidence generated by a Scotland-wide pilot study, DMW is being rolled out and tested across GM.

objectiveThe overarching objectives are to assess whether DMW improves outcomes for patients with T2D in the GM area, to explore the acceptability of the DMW intervention to stakeholders, and to assess the cost-effectiveness of the intervention.

methodsA mixed methods approach will be used. We will take a census approach to recruitment in that all eligible participants in GM will be invited to participate. The primary outcomes will be intervention-related changes compared with changes observed in a matched group of controls, and the secondary outcomes will be within-person intervention-related changes. The cost-effectiveness analysis will focus on obtaining reliable estimates of how each intervention affects risk factors such as HbA1c and costs across population groups. Qualitative data will be collected via semistructured interviews and focus groups and organized using template analysis.

resultsAs of May 10, 2021, a total of 316 participants have been recruited for the quantitative study and have successfully enrolled. A total of 278 participants attempted to register but did not have appropriate permissions set by the general practitioners to gain access to their data. In total, 10 participants have been recruited for the qualitative study (7 practitioners and 3 patients). An extension to recruitment has been granted for the quantitative element of the research, and analysis should be complete by December 2022. Recruitment and analysis for the qualitative study should be complete by December 2021.

conclusionsThe findings from this study can be used both to develop the DMW system and improve accessibility and usability in more deprived populations generally, thus improving equity in access to support for T2D self-management. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/26237.

Indexed as

complex interventiondiabeteselectronic healthself-management

Identifiers

PMID35976184
PMCPMC9434385

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.