Derivation, Evaluation, and Validation of Illustrations of Key Counselling Points for a Pediatric Eczema Action Plan
Bibliographic record
Abstract
BACKGROUND: Current eczema action plans (EAP) are based on written instructions without illustrations. Incorporating validated illustrations into EAPs can significantly improve comprehension and usability. OBJECTIVE: To produce and validate a set of illustrations for key counselling points of a pediatric EAP. METHODS: Illustrations were developed using key graphic elements and refined by subject experts. Illustrations were evaluated during one-on-one structured interviews with parents/caregivers of children ages 9 and younger, as well as with children ages 10 to 17 years between September 2015 and June 2016. The concepts of transparency, translucency, and short-term recall were assessed for validation. RESULTS: Of 245 participants, 81.3% were parents and/or caregivers of children 0 to 9 years old, and 18.7% were children between 10 and 17 years old. A total of 15 illustrations and 2 storyboards were evaluated; 9 illustrations and 2 storyboards were redesigned to reach the preset validation targets. Overall, 13 illustrations and 2 storyboards were validated. CONCLUSION: A set of illustrations for use in an EAP was prospectively designed and validated, achieving acceptable transparency, translucency, and recall, with input from patients and a multidisciplinary medical team. The incorporation of validated illustrations into eczema action plans benefits patients with limited health literacy. Future studies should evaluate if illustrations improve understanding of eczema management and translate into improved clinical outcomes.
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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 | 0.022 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".