Pharmacists' perceptions of their practice: a comparison between Alberta and Northern Ireland
Bibliographic record
Abstract
OBJECTIVE: To explore how community pharmacists from Alberta, Canada, and Northern Ireland, UK, describe what a pharmacist does and to compare their responses. METHODS: Two hundred community pharmacists were interviewed using the telephone. The interviewer who introduced himself as a researcher asked two questions about the period over which the participants had been practising pharmacy and the way they describe what a pharmacist does. Responses were categorised into three categories: patient-centred, product-focused and ambiguous. Word-cloud analysis was used to assess the use of patient-care-related terms. KEY FINDINGS: Of the responses from community pharmacists in Alberta, 29% were categorised as patient-centred, 45% as product-focused and 26% as ambiguous. In Northern Ireland, 40% of the community pharmacists' responses were categorised as patient-centred, 39% as product-focused and 21% as ambiguous. Community pharmacists in Northern Ireland provided more patient-centred responses than community pharmacists in Alberta (P=0.013). The word-cloud analysis showed that 'medicine' and 'dispense' were the most frequently reported terms. It also highlighted a relative lack of patient-care-related terms. CONCLUSIONS: The findings of the present study are suggestive of some movement towards patient-centredness; however, product-focused practice still predominates within the pharmacy profession in Alberta and Northern Ireland. The relative lack of patient-care-related terms suggests that patient care is still not the first priority for pharmacists in both Alberta and Northern Ireland.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".