Knowledge translation of the HELPinKIDS clinical practice guideline for managing childhood vaccination pain: usability and knowledge uptake of educational materials directed to new parents
Bibliographic record
Abstract
BACKGROUND: Although numerous evidence-based and feasible interventions are available to treat pain from childhood vaccine injections, evidence indicates that children are not benefitting from this knowledge. Unrelieved vaccination pain puts children at risk for significant long-term harms including the development of needle fears and subsequent health care avoidance behaviours. Parents report that while they want to mitigate vaccination pain in their children, they lack knowledge about how to do so. An evidence-based clinical practice guideline for managing vaccination pain was recently developed in order to address this knowledge-to-care gap. Educational tools (pamphlet and video) for parents were included to facilitate knowledge transfer at the point of care. The objectives of this study were to evaluate usability and effectiveness in terms of knowledge acquisition from the pamphlet and video in parents of newly born infants. METHODS: Mixed methods design. Following heuristic usability evaluation of the pamphlet and video, parents of newborn infants reviewed revised versions of both tools and participated in individual and group interviews and individual knowledge testing. The knowledge test comprised of 10 true/false questions about the effectiveness of various pain management interventions, and was administered at three time points: at baseline, after review of the pamphlet, and after review of the video. RESULTS: Three overarching themes were identified from the interviews regarding usability of these educational tools: receptivity to learning, accessibility to information, and validity of information. Parents' performance on the knowledge test improved (p≤0.001) from the baseline phase to after review of the pamphlet, and again from the pamphlet review phase to after review of the video. CONCLUSIONS: Using a robust testing process, we demonstrated usability and conceptual knowledge acquisition from a parent-directed educational pamphlet and video about management of vaccination pain. Future studies are planned to determine the impact of these educational tools when introduced in clinical settings on parent behaviors during infant vaccinations.
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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 | 0.046 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".