Enhancing pharmacy student injection training with the CARD™ system
Bibliographic record
Abstract
Abstract Background Immunization stress-related responses (ISRR) such as fear, pain and fainting contribute to negative immunization experiences and non-compliance in about 20% of un-immunized people. We introduced the CARD™ (Comfort, Ask, Relax, Distract) system - the first vaccine delivery framework demonstrated to reduce ISRR - to 240 second year pharmacy students undergoing mandatory immunization injection training and subsequent elective practical experience delivering immunizations in 2022 at the University of Toronto, Canada. Objectives The objective was to explore pharmacy students’ perceptions and behaviours following CARD™ education within the injections training course and then after participating as immunizers at influenza pop-up clinics. Results Eighteen pharmacy students participated after the injections training course and 19 participated after the pop-up clinics. Students reported CARD™ was aligned with client needs and preferences and national professional standards. They believed it was important to address ISRR and had higher confidence in their ability to support clients during immunization. Students reported deeper understanding of CARD™ after practical experience, including inviting client participation rather than imposing coping strategies. Conclusions We are the first group to incorporate evidence-based education about reducing ISRR to training curricula of pharmacy students. We demonstrated that students value education about CARD™ and that including a practical component is important to implementation fidelity. This information is relevant for injection training programs across disciplines and countries. Key messages • Incorporating CARD™ in injections training and experiences is acceptable to pharmacy students. • Reducing ISRR promotes more positive experiences for clients and immunizers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".