Assessment of community pharmacists’ engagement in pharmacy-delivered influenza vaccination: a mixed-methods study
Bibliographic record
Abstract
OBJECTIVES: This study aimed to identify factors contributing to pharmacists' engagement in vaccination services during the first influenza vaccination campaign in 2019-2020 for the Canadian province of Quebec, led by community pharmacists. METHODS: A mixed-methods study was conducted using a sequential exploratory design. Semi-structured interviews were administered to pharmacists and key informants (n = 23) and data were analysed according to the Consolidated Framework for Implementation Research in community pharmacy. The findings were then used to construct a survey of community pharmacists' engagement in vaccination, which was tested in a Quebec urban community. The study participation rate was 34.6% (n = 29). KEY FINDINGS: Pharmacists expressed positive attitudes towards the implementation of vaccination services, following legislative reform. Factors such as previous involvement in vaccination campaigns and the number of pharmacists on duty were positively associated with engagement in influenza vaccination, whereas staff shortages and logistical problems were a barrier to engagement. Qualitative findings provided in-depth understanding of the value of interprofessional collaboration between pharmacists and nurses. CONCLUSIONS: Vaccination in pharmacies is currently more reflective of individual choice than an indication of collective change in the profession. Logistical factors are key to enhancing the uptake of vaccination in community pharmacies throughout Quebec. External support from professional associations and interprofessional collaboration should be enhanced to promote the implementation of vaccination services in pharmacies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".