Diabetes Care Provision in UK Primary Care Practices
Bibliographic record
Abstract
BACKGROUND: Although most people with Type 2 diabetes receive their diabetes care in primary care, only a limited amount is known about the quality of diabetes care in this setting. We investigated the provision and receipt of diabetes care delivered in UK primary care. METHODS: Postal surveys with all healthcare professionals and a random sample of 100 patients with Type 2 diabetes from 99 UK primary care practices. RESULTS: 326/361 (90.3%) doctors, 163/186 (87.6%) nurses and 3591 patients (41.8%) returned a questionnaire. Clinicians reported giving advice about lifestyle behaviours (e.g. 88% would routinely advise about calorie restriction; 99.6% about increasing exercise) more often than patients reported having received it (43% and 42%) and correlations between clinician and patient report were low. Patients' reported levels of confidence about managing their diabetes were moderately high; a median (range) of 21% (3% to 39%) of patients reporting being not confident about various areas of diabetes self-management. CONCLUSIONS: Primary care practices have organisational structures in place and are, as judged by routine quality indicators, delivering high quality care. There remain evidence-practice gaps in the care provided and in the self confidence that patients have for key aspects of self management and further research is needed to address these issues. Future research should use robust designs and appropriately designed studies to investigate how best to improve this situation.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".