Learning from usability testing of an arts‐based knowledge translation tool for parents of a child with asthma
Bibliographic record
Abstract
AIM: Digital, art- and story-based resources can be viable and engaging knowledge translation strategies in health care. Understanding the usability of these approaches can help maximize their impact. The aim of this work is to understand what aspects of 'My Asthma Diary', an art-based digital knowledge translation tool for parents of children with asthma, has an impact on usability. DESIGN: Sequential explanatory mixed methods pilot study. METHODS: Eighteen parents of children with asthma reviewed 'My Asthma Diary' in a paediatric emergency department and completed a usability questionnaire. Follow-up interviews were conducted with five parents and analysed with qualitative description. RESULTS: We identified four themes which complemented the quantitative results: (a) the eBooks are relatable and mirror personal experience; (b) the digital format is convenient and easy to navigate; (c) the narrative structure aids learning; and (d) the narrative and illustrations are synergistic. We summarize core usability considerations for subsequent research and creative knowledge translation tool development in other contexts.
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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 | 0.033 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".