Evaluation, Modification and Validation of a Set Of Asthma Illustrations in Children with Chronic Asthma in the Emergency Department
Bibliographic record
Abstract
OBJECTIVES: To test, modify and validate a set of illustrations depicting different levels of asthma control and common asthma triggers in pediatric patients (and⁄or their parents) with chronic asthma who presented to the emergency department at the Children's Hospital of Eastern Ontario, Ottawa, Ontario. METHODS: Semistructured interviews using guessability and translucency questionnaires tested the comprehensibility of 15 illustrations depicting different levels of asthma control and common asthma triggers in children 10 to 17 years of age, and parents of children one to nine years of age who presented to the emergency department. Illustrations with an overall guessability score <80% and⁄or translucency median score <6, were reviewed by the study team and modified by the study's graphic designer. Modifications were made based on key concepts identified by study participants. RESULTS: A total of 80 patients were interviewed. Seven of the original 15 illustrations (47%) required modifications to obtain the prespecified guessability and translucency goals. CONCLUSION: The authors successfully developed, modified and validated a set of 15 illustrations representing different levels of asthma control and common asthma triggers. PRACTICE IMPLICATIONS: These illustrations will be incorporated into a child-friendly asthma action plan that enables the child to be involved in his or her asthma self-management care.
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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 | 0.015 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".