The development and usability testing of two arts-based knowledge translation tools for pediatric anaphylaxis
Bibliographic record
Abstract
Abstract Anaphylaxis, or anaphylactic reactions, are a severe allergic reaction with a rapid onset and can be fatal. Children are disproportionately at risk for hospitalization and emergency department visits due to anaphylaxis. A previously conducted mixed studies systematic review and qualitative descriptive study found that parents lacked confidence in recognizing and treating an anaphylactic reaction in their child, and were unsure of when to bring their child to the emergency department. This demonstrates that more effective knowledge translation (KT) tools are needed to satisfy parent information needs. The purpose of this research was to work with parents to develop and test the usability of an animated video and an interactive infographic about anaphylactic reactions in children. These tools merge the best available research evidence with narratives of parent experiences to respond to their information needs. Prototypes were evaluated by parents (video n=31; infographic n=30) through usability testing in an urban emergency department waiting room in Alberta. Parents viewed the tools on an iPad and answered questions via an electronic survey. The usability survey consisted of 9, 5-point Likert items, which assessed: 1) usefulness, 2) aesthetics, 3) length, 4) relevance, and 5) future use. Parents were also asked to provide their positive and negative opinions of the tool via two free text boxes. Overall, results were positive and the tools were highly rated across most usability items. Mean scores across usability items were 4.26 to 4.71 for the video and 3.83 to 4.43 for the infographic. The scores from the usability testing suggest arts-based digital tools are useful in sharing complex health information with parents about managing an anaphylactic reaction in their child and provide meaningful guidance on how to improve KT tools to better reflect the needs of parents.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".