Achieving Influenza Vaccine Uptake Target in Canada via a Pharmacy-Led Telephone Discussion during the 2019–2020 Season
Bibliographic record
Abstract
Older adults (≥65 years) are at elevated risk of influenza-related morbidity and mortality. Many developed countries do not achieve the World Health Organization influenza immunization target of 75% in people ≥65 years. We aimed to determine whether a brief pharmacy phone call could increase vaccine uptake of standard and enhanced influenza. Twenty-eight community pharmacists across Canada performed a telephone consultation with 643 older adults whose primary care records indicated that they had not received their influenza vaccination from their usual practitioner. Of these 643 adults, 169 (26.3%) had been vaccinated in another setting. Of the remaining 474, 313 (66%) agreed to receive the vaccine. Of those who refused vaccination, 69 provided a rationale for not wanting it, including that the flu shot “causes the flu” (n = 25), “doesn’t work” (n = 25), “is too painful” (n = 10), and other (n = 10). Overall, of the 643 individuals who had not received their vaccination from their usual health care provider in the first wave of vaccinations, 75.4% (n = 485) ultimately received their vaccination in the 2019–2020 season. This highlights the important role of the community pharmacist in achieving the World Health Organization (WHO) targets for vaccination.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".