Exploring climate-conscious pharmacy: considerations for community pharmacists
Bibliographic record
Abstract
BACKGROUND: Climate change threatens health and the safe and effective operation of health services, including pharmacy care. Given the critical and increasing role of community pharmacy in providing accessible and community-based care, their role in addressing climate risks and pollution impacts warrants investigation. OBJECTIVE: To catalogue actionable resources available to support community pharmacists and learn about opportunities for incorporation into climate-conscious pharmacy practice. METHODS: We used a multi-method sequential design, with an environmental scan of resources for climate-conscious pharmacy practice across selected international jurisdictions, followed by qualitative interviews with key informants in Canada, UK, Ireland, and Norway. Resources identified through the environmental scan were categorized based on frequency of appearance and similarity of considerations seen across sources. Semi-structured interviews generated feedback on the resources identified, their categorization, and identified opportunities for implementing climate-conscious pharmacy practice. RESULTS: 115 sources were included from the environmental scan and 12 key informants were interviewed. Resources were initially classified into clinical and operational considerations they implied for practice and further sub-classified into mitigation and/or adaptation strategies. Key informants supported or did not disagree with the considerations that were identified. They shared resource constraints as a challenge in implementing climate-conscious practice and highlighted the importance of a patient-centred approach to support the implementation. CONCLUSION: Overall, actionable considerations for climate-conscious community pharmacy have been identified internationally. Pharmacists are continuing to contribute to planetary health as they are already engaged in many of the suggested considerations. Raising awareness of potential co-benefits may help further equip pharmacists to incorporate climate-conscious pharmacy practices.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| 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".