Concerns, Beliefs and Attitudes of Pharmacists About Medical Cannabis Use in Poland
Bibliographic record
Abstract
INTRODUCTION: The global use of medical cannabis is steadily increasing. In Poland, medical cannabis was legalised in 2017; however, its use remains limited and not widely integrated into clinical practice. This study aimed to explore the attitudes, concerns, and beliefs of pharmacists and pharmacy students regarding the medical use of cannabis. METHODS: A study was conducted in 2021 among 422 pharmacists and pharmacy students in Poland, primarily working in community pharmacies. Data were collected using a custom-designed questionnaire addressing beliefs, concerns, and professional experiences related to medical cannabis. RESULTS: Nearly half of the respondents (48.9%) believe that cannabis should be used exclusively for medical purposes, while 47.6% support its use for both medical and recreational purposes following legalisation. A substantial majority (over 90%) consider cannabis effective for treating adults, with nearly 70% acknowledging its potential for treating children. Over 66% of respondents feel comfortable discussing medical cannabis with patients; however, fewer are confident in providing detailed advice about its use. The findings also highlight concerns about the long-term effects and potential legal implications of dispensing medical cannabis. CONCLUSIONS: Pharmacists and pharmacy students in Poland demonstrate openness to the medical use of cannabis and recognise its therapeutic potential. However, to enhance their ability to advise patients effectively, targeted educational initiatives are needed. These should focus on the clinical applications, safety, and long-term effects of cannabis, alongside strategies for addressing patient concerns and ensuring responsible usage.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".