Barriers and facilitators to the uptake of an antimicrobial stewardship program in primary care: A qualitative study
Bibliographic record
Abstract
The overuse of antimicrobials in primary care can be linked to an increased risk of antimicrobial-resistant bacteria for individual patients. Although there are promising signs of the benefits associated with Antimicrobial Stewardship Programs (ASPs) in hospitals and long-term care settings, there is limited knowledge in primary care settings and how to implement ASPs in these settings is unclear. In this context, a qualitative study was undertaken to explore the perceptions of primary care prescribers of the usefulness, feasibility, and experiences associated with the implementation of a pilot community-focused ASP intervention in three primary care clinics. Qualitative interviews were conducted with primary care clinicians, including local ASP champions, prescribers, and other primary health care team members, while they participated in an ASP initiative within one of three primary care clinics. An iterative conventional content analyses approach was used to analyze the transcribed interviews. Themes emerged around the key enablers and barriers associated with ASP implementation. Study findings point to key insights relevant to the scalability of community ASP activities with primary care providers.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".