Asleep at the Wheel: Pharmacy Practice Research Advocacy and Knowledge Translation by Canadian Pharmacy Organizations
Bibliographic record
Abstract
Background: The Blueprint for Pharmacy clearly articulates the need and imperative for pharmacy practice to move toward patient-centred care. Pharmacy professional organizations have a crucial role to play in this change, through leadership, communication and advocacy. This survey aimed to determine what knowledge translation (KT) activities were performed by Canadian pharmacy professional organizations in relation to a major pharmacy practice study. Methods: We sent a letter summarizing the findings and implications of the recently published hypertension trial, SCRIP- HTN, to the leaders of each pharmacy regulatory and advocacy body in Canada. Six months later, we followed up with these groups to inquire about KT activities that had been performed around the study findings. Results: Of the 22 organizations, 3 performed some type of KT activity. The major barrier to KT cited by the regulatory bodies was that it was not their job. The most common reason given by the advocacy bodies was that the study or its implications were not a priority. Other barriers included lack of time, lack of resources and political issues. Conclusion: KT and advocacy by our pharmacy professional organizations was practically nonexistent. This must change if we are to put into effect the vision of the Blueprint for Pharmacy for pharmacy practice change and optimal patient care.
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 | 0.082 | 0.184 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| 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".