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Record W2947516333 · doi:10.1186/s12913-019-4112-3

Intensification to injectable therapy in type 2 diabetes: mixed methods study (protocol)

2019· article· en· W2947516333 on OpenAlexaboutno aff
Simon de Lusignan, William Hinton, Emmanouela Konstantara, Neil Munro, Martin Whyte, Julie Mount, Michael Feher

Bibliographic record

VenueBMC Health Services Research · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
FundersRoyal College of General PractitionersEli Lilly and Company
KeywordsMedicineFocus groupContext (archaeology)Protocol (science)Health informaticsNursing researchNursingFamily medicineMedical educationPublic healthAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In the UK, type 2 diabetes mellitus (T2D) is largely managed in primary care. Delay in the intensification to injectable therapy, a form of clinical inertia, is associated with worse glycaemic control. UK general practice is highly computerised, with care being recorded on computerised medical record systems; this allows for quantitative analysis of clinical care but not of the underpinning decision-making process. The aim of this study is to investigate perceptions of patients and clinicians in primary care on the initiation of injectable therapies in T2D, and the context within which those decisions are made. METHODS: This is a mixed methods study, taking a "realist evaluation" approach. The qualitative components comprise focus groups, interviews, and video recordings of simulated surgeries; the quantitative analysis: an overview of participating practices, elements of the video recording, and an online survey. We will recruit primary care clinicians (general practitioners and nurses) and patients from a representative sample of practices within the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network. Participants will be patients with T2D, and primary care clinicians. Focus groups and semi-structured interviews will be recorded, transcribed verbatim and analysed using Framework Analysis. The simulated surgeries will include cases that might be escalated to injectable therapy. The consultation will be reviewed using the Calgary-Cambridge model to assess communication and determination of adherence to national prescribing guidelines. We will conduct multi-channel video recording including screen capture, clinician and patient facial expressions, wide angle view of the consultation, and the computerised medical record screen. This allows annotation and qualitative analysis of the video recordings, and statistical analyses for the quantitative data. We will also conduct an online survey of primary care clinicians' attitudes to, and perceptions of, initiation of injectable therapies, which will be analysed using summary statistics. DISCUSSION: Results aim to provide a detailed insight into the dynamic two-way decision-making process underpinning use of injectable therapy for T2D. The study will provide insights into clinical practice and enable the development of training, interventions and guidelines that may facilitate, where appropriate, the intensification to injectable therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.053
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.037
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0360.005

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 head0.120
GPT teacher head0.535
Teacher spread0.415 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations6
Published2019
Admission routes1
Has abstractyes

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