Knowledge, attitudes, and practices of pharmacists in caring for patients with substance use disorders
Bibliographic record
Abstract
Abstract Background While pharmacists are optimally positioned to help provide support for those with substance use disorders (SUD), little is known about their knowledge, attitudes, and practices in this area. Objectives The primary objective of this study is to assess the knowledge, attitudes, and practices of hospital pharmacists in caring for patients with SUD. The secondary objectives are to identify barriers and facilitators that exist in the current work environment and evaluate how these factors play a role in pharmacists' practice. Methods An anonymous, cross‐sectional, online survey of 770 pharmacists employed by Lower Mainland Pharmacy Services in British Columbia was conducted. The survey was comprised of 27 questions, including a mix of qualitative and quantitative questions. The domains of questions explored pharmacists' knowledge of SUD, attitudes toward provincial harm reduction policies, and care provided for different SUD. Results A total of 127 pharmacists (16.5%) responded to the survey. Seventy‐two percent of pharmacists received less than 5 hours of schooling on SUD and less than 7% of pharmacists reported feeling adequately prepared by their formal education to care for patients with SUD. Less than a quarter of pharmacists report regularly monitoring and recommending treatment options for patients with SUD. Most pharmacists expressed interest in some form of SUD courses that could help to improve patient care. Conclusion In this study of pharmacists, the majority of hospital pharmacists felt unprepared to care for patients with SUD, but expressed interest in education that could help to improve their knowledge and skills.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".