A national survey of antimicrobial stewardship content in Canadian entry-to-practice pharmacy programs
Bibliographic record
Abstract
Objective: To describe the current landscape of antimicrobial stewardship (AMS) instruction in Canadian entry-to-practice pharmacy programs and the perceived barriers and facilitators to optimizing teaching and learning. Design: Electronic survey. Participants: Faculty representatives from the 10 Canadian entry-to-practice pharmacy programs, including content experts and faculty leadership. Methods: A review of international literature pertaining to AMS in pharmacy curricula informed a 24-item survey, which was open for completion from March to May of 2021. Curriculum content questions were developed using AMS topics recommended by pharmacy educators in the United States, and professional roles described by the Association of Faculties of Pharmacy of Canada. Results: All 10 Canadian faculties returned a completed survey. All programs reported teaching AMS principles in their core curricula. Content coverage varied, with programs teaching, on average, 68% of the recommended AMS topics from the United States. Potential gaps were identified within the professional roles of "communicator" and "collaborator." Didactic methods of content delivery and student assessment, such as lectures and multiple-choice questions, were most frequently used. Three programs offered additional AMS content in their elective curricula. Experiential rotations in AMS were commonly offered, though teaching AMS in formalized interprofessional settings was rare. Curricular time constraints were identified by all programs as a barrier to enhancing AMS instruction. A course to teach AMS, a curriculum framework, and prioritization by the faculty's curriculum committee were perceived as facilitators. Conclusions: Our findings highlight potential gaps and areas of opportunity within Canadian pharmacy AMS instruction.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".