The development and usability testing of digital knowledge translation tools for parents of children with bronchiolitis
Bibliographic record
Abstract
Abstract Bronchiolitis is an acute infection of the lower respiratory tract that predominantly affects children less than two years old. Although self-limiting, symptoms of bronchiolitis can be distressing for young children. Research has demonstrated that parents may not have the necessary information to be able to identify bronchiolitis symptoms, resulting in emergency department (ED) visits and hospitalizations. Parents have expressed that they feel unprepared, afraid, and that they lack information on their child’s condition. Digital knowledge translation (KT) tools have the potential to convey complex health information to parents to support their healthcare decision-making needs. We worked with parents of children with bronchiolitis to develop and evaluate three digital tools on bronchiolitis (whiteboard animation video, infographic, and e-Book). Following prototype completion, usability testing was conducted using iPads in two Alberta ED waiting rooms. Parents were randomized to one out of the three tools. Overall, the tools were highly rated, suggesting that arts-based digital tools are useful in delivering complex health information to 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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".