Assessing the impact of a cannabis course on pharmacy students’ understanding, beliefs and preparedness regarding medical and recreational cannabis
Bibliographic record
Abstract
Background: With the legalization of cannabis in Canada in 2018, pharmacists are increasingly likely to encounter patients using this substance. The primary objective of this pre-post questionnaire study was to evaluate the impact of an accredited cannabis course on the understanding, beliefs, perceptions and knowledge of undergraduate PharmD students. Methods: A 38-question, web-based survey generated in REDCap was administered to third-year PharmD students at the University of Waterloo, prior to and right after taking an accredited cannabis course. The pre- and postsurvey data were analyzed using SPSS version 25. Pearson chi-square tests were performed on questions in which answers consisted of qualitative categorical data. Two-sided t tests were performed to test the significance of mean differences of questions measuring continuous variables. Results: In a class of 120 students, 110 completed the presurvey and 79 students completed the postsurvey. After the course, students were more likely to report being knowledgeable and prepared for patient encounters dealing with medical and recreational cannabis, understanding that medical cannabis should be prescribed for select (vs all) medical conditions, rating the quality of evidence as poor to moderate for medical use of cannabis, understanding that medical documents should be more prescriptive and understanding that cannabis should not be sold in pharmacies ( p < 0.05). Interpretation: With cannabis education a part of their curriculum, pharmacy students felt more prepared to engage patients using cannabis both medically and recreationally. Furthermore, students were more cautious regarding the potential use of cannabis therapeutically and indicated that more oversight should be in place. Can Pharm J (Ott) 2021;154:xx-xx.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".