CARD (Comfort Ask Relax Distract) and community pharmacy vaccinations: Evaluation of effectiveness outcomes from a cluster randomized trial
Bibliographic record
Abstract
While community pharmacies are an efficient setting for vaccinating large numbers of individuals, they can be stressful for vaccine recipients and providers, creating challenges for vaccine delivery. The CARD system (Comfort Ask Relax Distract) is an evidence-based protocol for vaccination delivery designed to improve the vaccination experience. A hybrid effectiveness-implementation cluster randomized trial was conducted between November 2023 and January 2024 whereby 25 pharmacies in Ontario (Canada) were randomly allocated to CARD training and resources (n = 12) or control (n = 13). This paper reports on the effectiveness outcomes of the trial. Vaccine recipients rated their vaccination experience compared to their last vaccination (primary outcome) and symptoms (fear, pain, dizziness). Sub-group analyses were performed according to age (0–19, 20–39, 40–59, ≥60 years) and sex (male, female). Pharmacy professionals recorded coping strategies utilized. Altogether, 2206 individuals received vaccinations. More vaccine recipients in the CARD group (vs. control) reported a better experience: 48.8% vs. 28.0%, p = .003 (intracluster correlation = 0.21). Mean pain score was lower in the CARD group in vaccine recipients aged 20–39, 40–59 and ≥60 years, and females (p < .03, all analyses). Mean fear and dizziness scores were lower in the CARD group in individuals aged 20–39 years (p = .03 and p = .007, respectively). More coping strategies were used in the CARD group (p < .05, all analyses). CARD is recommended as the standard of care for community pharmacy-based vaccinations to improve vaccine recipient experiences and symptoms.Trial Registration: NCT06098703
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".