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Record W4286225587 · doi:10.1097/xce.0000000000000268

Enhancing type 2 diabetes treatment through digital plans of care. First results from the East Cheshire Study of an App to support people in the management of type 2 diabetes

2022· article· en· W4286225587 on OpenAlexaff
Adrian Heald, Lucia Albeda Gimeno, Erin Gilingham, Lynne M. Hudson, L. L. Price, Anuj Saboo, Laura Beresford, Sally Seviour, Alison White, Sarah Roberts, Jonathan Abraham

Bibliographic record

VenueCardiovascular Endocrinology & Metabolism · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsType 2 diabetesMedicineTreatment and control groupsDigital healthIntervention (counseling)Sample (material)GerontologyHealth careDiabetes mellitusFamily medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

Introduction The use of personalised care planning has been effective at improving health outcomes for people with long-term health conditions. Methods We analysed data in relation to changes in BMI/HbA1c. The sample was made up of ( n = 36) participants randomised to either the active intervention group (App+usual care) or the control group (usual care). Results: The average HbA1c percentage change for the treatment group was 9.5%, but just −2% for the control (usual care) group ( P = 0.015 for the difference). The average percentage change in BMI for the treatment group was −0.4%, but 0.1% for the control group ( P = 0.03 for the difference). Conclusion These preliminary findings point to how the provision of personalised plans of care, support and education linked to a mobile app, can result in HbA1c and BMI reduction over a 6-month period. While the results are preliminary, they portend the potential for digital plans of care to enhance T2DM management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.332
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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