Feasibility of implementation of CARD™ for school-based immunizations in Calgary, Alberta: a cluster trial
Bibliographic record
Abstract
BACKGROUND: Negative experiences with school-based immunizations can contribute to vaccine hesitancy in youth and adulthood. We developed an evidence-based, multifaceted and customizable intervention to improve the immunization experience at school called the CARD™ (C-Comfort, A-Ask, R-Relax, D-Distract) system. We evaluated the feasibility of CARD™ implementation for school-based immunizations in Calgary, Canada. METHODS: In a mixed methods study, two Community Health Centres providing immunization services, including 5 schools each with grade 9 students (aged approximately 14 years), were randomized to CARD™ or control (usual care). In the CARD™ group, public health staff and students were educated about coping strategies prior to immunization clinics. Clinics were organized to reduce fear and to support student's choices for coping strategies. Public health staff in the CARD™ group participated in a focus group discussion afterwards. We sought a recruitment rate of 80% for eligible schools, an external stakeholder focus group (e.g., school staff) with 6 or more individuals, 85% of individual injection-related data acquisition (student and immunizer surveys), and 80% absolute agreement between raters for a subset of data that were double-coded. Across focus groups, we examined perceptions of acceptability, appropriateness, feasibility and fidelity of CARD™. RESULTS: Nine (90%) of eligible schools participated. Of 219 students immunized, injection-related student and immunizer data forms were acquired for 195 (89.0%) and 196 (89.5%), respectively. Reliability of data collection was high. Fifteen public health and 5 school staff participated in separate focus groups. Overall, attitudes towards CARD™ were positive and compliance with individual components of CARD™ was high. Public health staff expressed skepticism regarding the value of student participation in the CARD™ system. Suggestions were made regarding processes to refine implementation. CONCLUSION: While most outcome criteria were satisfied and overall perceptions of implementation outcomes were positive, some important challenges and opportunities were identified. Feedback is being used to inform a large cluster trial that will evaluate the impact of CARD™ during school-based immunizations. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov ( NCT03948633 ); Submitted April 24, 2019.
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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 | 0.007 | 0.006 |
| 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".