Bibliographic record
Abstract
PURPOSE: An exploration was completed of health professionals' experiences implementing evidence-based guidelines that promote intensive management (IM) for people with diabetes. METHODS: In-depth, semi-structured interviews were conducted with 50 health professionals from across Canada. These professionals are considered to be opinion leaders in diabetes care. Interviews were audiotaped, transcribed verbatim, and coded with the assistance of NVivo software. Transcripts were analyzed using Potter and Wetherell's approach to discourse analysis. RESULTS: Participants noted that recent clinical trials validated intensive approaches to diabetes management. While they viewed the evidence as sound, they did not feel that it justified IM approaches in all situations. Evidence-based practice therefore gave way to individual patient considerations. Implementing behavioural strategies, such as the stages of change model, allowed participants to modify their practices in ways that accommodated both evidence-based and patient-focused practice paradigms. CONCLUSIONS: While evidence-based medicine influenced practice, it was only one discourse that shaped the way health professionals approached diabetes care.
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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 | 0.085 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".