Changing the conversation: Empowering community pharmacists to address pneumococcal vaccine hesitancy
Bibliographic record
Abstract
BACKGROUND: Although pneumococcal vaccine is recommended for everyone 65 years of age and older, only 58% of Canadians in this age group have been vaccinated, well below the Public Health Agency of Canada's target of 80%. To improve uptake, a stepped-wedge cluster randomized trial testing the effectiveness of a community pharmacist intervention was developed. OBJECTIVE: This prespecified sub-study aimed to uncover and quantify factors contributing to vaccine hesitancy by exploring the nature of patient-pharmacist conversations about pneumococcal vaccine. METHODS: Beginning each month (April- August 2023), participating pharmacies were randomly selected to receive an education package designed to enhance pharmacists' knowledge, skills, and abilities in promoting pneumococcal vaccination. Pharmacists provided usual care (control stage) until they received the educational package and transitioned to the intervention stage. Weekly scorecards tracked patient-pharmacist conversations about pneumococcal vaccination. Chi-squared tests compared time taken for each conversation and patient-reported reason(s) for refusal between control and intervention stages. RESULTS: Thirteen pharmacies from across Alberta were included in the analysis, reporting 656 patient-pharmacist conversations (control stage n = 271, intervention stage n = 385). Time taken for pneumococcal vaccine conversations decreased after pharmacies received the education package (65% of conversations resulting in vaccination took <20 minutes in the control stage, compared to 88% in the intervention stage [P = 0.004]). The most common patient-reported reason for refusal, needing more time to think about the vaccine, remained similar between stages (P = 0.23). However, during the intervention stage, fewer patients refused vaccination due to lack of time to receive it today (P = 0.016) and perceived lack of benefit (P = 0.035), but more patients refused vaccination due to cost barriers (P = 0.026). CONCLUSION: The education provided in this study changed the reasons for refusing vaccines, suggesting the nature of patient-pharmacist conversations became more efficient and informed. Similar interventions could be adopted across Canada and the United States to help combat vaccine hesitancy.
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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 | 0.016 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.012 | 0.023 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".