Healthcare provider awareness, attitudes, beliefs, and behaviors regarding the role of pharmacists as immunizers
Bibliographic record
Abstract
We explored perceptions of healthcare providers in Nova Scotia and New Brunswick about pharmacists as immunizers. Pharmacists’ scopes of practice are increasingly broadening to include immunization, and providers and policymakers may find meaning in the lessons we learned. Invitations to participate in our online survey were circulated by professional associations, health authorities, and in social media posts. A total of 204 healthcare providers completed our survey, of whom 59.3% were pharmacists, 17.6% were nurses, and 23.0% were physicians. Nurses (30.6%) and physicians (34.0%) experienced fewer logistical barriers to immunizing compared to pharmacists, 71.1% of whom identified practice logistics as a determinant in offering vaccines to patients (p < .001). Pharmacists were most supportive of the expansion of their own scope of practice to include the provision of vaccines to adults (95.9%) and children as young as five years (92.6%) compared to nurses (72.2% and 69.4%) and physicians (61.7% and 40.4%) (p < .001). Diversity of opinion was evident even among pharmacists about whether they should be permitted to vaccinate children younger than five years. Nurse and physician respondents had lower odds of thinking pharmacists have enough training to vaccinate (p < .001), that vaccines should be given in a pharmacy (p < .001), and of supporting the expansion of pharmacists’ scope of practice (p < .001) than pharmacists did in the multivariable analyses. Pharmacists are well-positioned and willing to vaccinate and generally have support from their nurse and physician peers, but logistical challenges and interprofessional complexities persist as barriers to optimizing immunization by pharmacists.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".