Implementation of asthma clinical practice guidelines in primary care: A cross-sectional study based on the Knowledge-to-Action Cycle
Bibliographic record
Abstract
OBJECTIVE: Based on the Knowledge-to-Action Cycle, we assessed the self-reported implementation and perception of asthma clinical practice guideline (CPG) recommendations in primary care physicians (PCPs), along with the barriers and facilitators to CPG use in primary care. METHODS: , PCPs self-reported the following: their knowledge of 15 key asthma CPG recommendations, the perceived usefulness of each of these recommendations, their motivation to apply these recommendations, and their agreement with the content of these recommendations. Participants also reported the barriers and facilitators to CPG use in primary care. RESULTS: Out of the 46 potential participants, 43 physicians completed the questionnaire (response rate: 93%). Results underlined care gaps regarding the provision of asthma education and written action plans, inhaler technique demonstrations, and assessment of patients' concerns. Results showed that the majority of physicians knew the key asthma CPG recommendations, but their motivation to implement them and the perceived usefulness of these recommendations varied from one proposal to another. Main barriers to the implementation of these recommendations were related to time and resources. PCPs stressed the importance of teamwork for enhancing the use of asthma CPGs in primary care. CONCLUSIONS: Our results suggest that the implementation of asthma CPGs remains suboptimal in primary care. Interventions addressing the identified barriers and providing facilitators to asthma CPG implementation, such as continuing education, could be implemented and evaluated to sustain asthma CPG use in primary care settings.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".