Refinement of a Parent–Child Shared Asthma Management Mobile Health App: Human-Centered Design Study
Bibliographic record
Abstract
BACKGROUND: The school-age years, approximately ages 7 through 11, represent a natural transition when children begin assuming some responsibility for their asthma management. Previously, we designed a theoretically derived, tailored parent-child shared asthma management mobile health app prototype, Improving Asthma Care Together (IMPACT). OBJECTIVE: The purpose of this study was to use human-centered design (HCD) to iteratively refine IMPACT to optimize user experience and incorporate evidence-based longitudinal engagement strategies. METHODS: This study used a mixed methods design from December 2019 to April 2021. Our app refinement used the HCD process of research, ideation, design, evaluation, and implementation, including 6 cycles of design and evaluation. The design and evaluation cycles focused on core app functionality, child engagement, and overall refinement. Evaluation with parent-child dyads entailed in-person and remote concept testing and usability testing sessions, after which rapid cycle thematic analyses identified key insights that informed future design refinement. RESULTS: Twelve parent-child dyads enrolled in at least one round of this study. Eight of the 12 child participants were male with a mean age of 9.9 (SD 1.6) years and all parent participants were female. Throughout evaluation cycles, dyads selected preferred app layouts, gamification concepts, and overall features with a final design prototype emerging for full-scale development and implementation. CONCLUSIONS: A theoretically derived, evidence-based shared asthma management app was co-designed with end users to address real-world pain points and priorities. An 8-week pilot study testing app feasibility, acceptability, and preliminary efficacy is forthcoming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".