Development and Usability Testing of the Mobile Childhood Asthma Management Program (mCHAMP) App: Sequential Mixed Methods Study
Bibliographic record
Abstract
Background More than 6 million children in the United States have asthma, and more than 20% are clinically obese. Youth with asthma and obesity are susceptible to poor health outcomes, including greater asthma symptom severity and hospitalizations, reduced physical activity, and poorer quality of life. Mobile health technologies can increase access to chronic disease self-management interventions, and family members can be powerful influencers given their substantial control over a child’s behavior and home environment. Objective The Mobile Childhood Asthma Management Program (mCHAMP) app is based on the in-person Childhood Asthma Management Program (CHAMP) behavioral family intervention pilot trial of school-aged children with asthma and obesity. In this study, we translated the CHAMP content into digital content and conducted summative testing to measure the usability, learnability, and efficiency of the mCHAMP app. Methods We applied a sequential mixed methods approach. The mCHAMP app targeted adult caregivers of children living with asthma and obesity aged 6 to 12 years. A consumer-centered approach was used to guide the identification of user requirements and conduct of summative usability testing. While the mCHAMP app is primarily caregiver facing, it is intended to connect caregivers with registered nurse (RN) interventionists. Therefore, we sought feedback from RNs as key stakeholders. Results Caregivers (n=10) were female (n=10, 100%) and mostly African American (n=8, 80%), and half (n=5, 50%) had an annual household income of Conclusions Caregivers expressed a desire for an intervention that was easy to use and could integrate into their busy family lives. We met this expectation based on the usability, learnability, and efficiency results of our study. The mCHAMP app has the potential to increase self-management for parents and pediatric patients with asthma with multimorbidity, which could improve patient and health system outcomes. The use of mCHAMP may also enable novel clinical outcome studies based on patient-reported data from the app. International Registered Report Identifier (IRRID) RR2-10.2196/13549
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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 | 0.046 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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 | 0.001 |
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".