Physicians' attitudes to the pharmacological treatment of patients with stable angina pectoris
Bibliographic record
Abstract
BACKGROUND: Little is known about how physicians' knowledge of and attitudes to practice guidelines for stable angina may influence their implementation. AIM: To explore the association between physicians' demographics, their knowledge, and opinions about stable angina and their self-reported adherence to guideline recommendations. DESIGN: Questionnaire-based survey. METHODS: We surveyed 1228 Quebec physicians using a questionnaire based on the 'awareness-to-adherence' conceptual framework to measure their adherence with recommendations for the pharmacological treatment of stable angina. Independent predictors of adherence with the targeted recommendations were determined by stepwise linear regression analysis. RESULTS: We received 877 (71.4%) responses from the 1228 eligible physicians. More than 90% of respondents were aware of and agreed with the targeted recommendations. However, the adoption rate varied, even among physicians who generally agreed with the guidelines. Factor analysis indicated that most physicians agreed with recommendations concerning ASA. More negative attitudes were expressed toward beta-blockers and hypolipaemic drugs. Respondents trusted the recommendations of a variety of scientific and professional organizations. Awareness, agreement, and adoption were the strongest predictors of adherence for the three recommendations. Physician demographics and practice characteristics did not predict adherence. DISCUSSION: Physicians were aware of and agreed with the recommendations, so additional large-scale dissemination of the guidelines would be unlikely to improve prescription patterns. However, negative attitudes about beta-blockers and hypolipaemic therapy affected adherence to recommendations for these drugs. Continuing medical education interventions involving local opinion leaders might address some of the obstacles identified.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".