CARD (Comfort Ask Relax Distract) for school-based immunizations in Calgary, Canada: a pragmatic cluster trial
Bibliographic record
Abstract
ABSTRACT: School-based immunizations are fear-inducing events for many students and contribute to vaccine hesitancy. We developed an immunization delivery framework called the CARD (Comfort Ask Relax Distract) system that incorporates evidence-based interventions to improve the experience (eg, reduce fear, pain, dizziness). We evaluated CARD in grades 6 and 9 students in Calgary, Canada. In this pragmatic, hybrid, effectiveness-implementation, cluster trial, we randomized 8 Community Health Centres providing regional immunization services to CARD or control (usual care). In the CARD group, public health staff educated students about CARD and planned processes to reduce fear cues and support student coping choices during immunization. Students self-reported fear, pain, and dizziness during immunization using a 0-10 numerical rating scale; staff recorded procedure details, including vaccines administered, fainting episodes, and coping strategies used. Staff participated in focus groups afterward. Altogether, 8839 children from 105 schools in the 2019 to 2020 school calendar year were included. Fear was lower for CARD (mean = 3.6 [SD = 3.1] vs control 4.1 [3.2]; mean difference = -0.5; 95% confidence interval = -0.74 to -0.21; P < 0.001). Effectiveness persisted after stratification by student gender (male and female) and grade level (grade 6 and grade 9). Other symptoms did not differ. Compared with control, CARD students used peers, privacy, muscle tension, and topical anesthetics more; verbal distraction, deep breathing, and adult support were used less frequently ( P < 0.05, all analyses). Immunization rate did not differ. Staff reported positive to neutral attitudes about CARD. In summary, this pragmatic trial demonstrated that CARD improved the immunization experiences of students at school.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".