SCOPING REVIEW PROTOCOL: STRATEGIES UTILIZED BY PHARMACISTS AND PHARMACY STUDENTS IN PRESCRIBING RELATED DECISION-MAKING
Bibliographic record
Abstract
Pharmacists have long been vital members of the healthcare care team (Gysel & Tsuyuki, 2024), but their role has significantly transformed over the past two decades with the introduction of independent pharmacist prescribing. In Canada, pharmacists can independently prescribe in all 12 provinces and the Yukon. However, this increased responsibility brings with it challenges in the clinical decision-making process. While recent studies have sought to better understand the decision-making process in the context of pharmacy practice, most of the research remains focused on other health practitioners (Edwards et al., 2022; Graham-Clarke et al., 2018). The challenges faced by pharmacists are also not well delineated. It also remains unknown how pharmacists address these challenges within the clinical decision-making process (Mertens et al., 2022; Wright et al., 2019). Gaining a better understanding of how pharmacists address these challenges is imperative in ensuring they are equipped with the skills required to confidently incorporate prescribing into their practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.018 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.022 | 0.017 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.002 |
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; both teacher heads agree on what is shown here.
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".