Protocol for the Development of a Behavioral Family Lifestyle Intervention Supported by Mobile Health to Improve Weight Self-Management in Children With Asthma and Obesity
Bibliographic record
Abstract
BACKGROUND: Asthma is the most common chronic childhood illness and is a leading cause of emergency department visits in the United States. Obesity increases the risk of poor health outcomes, reduced quality of life, and increased health care expenditures among youth with asthma. Weight loss is crucial for improving asthma outcomes in children with obesity. Our study team developed the Childhood Health and Asthma Management Program (CHAMP), a 16-session behavioral family lifestyle intervention (BFI) for school-age children with asthma and obesity and evaluated CHAMP in a randomized controlled trial compared with attention control. There were medium effect sizes favoring CHAMP for changes in body mass index z-scores, asthma control, and lung function among completers (ie, those who attended ≥9 of 16 sessions). Despite high rates of satisfaction reported by families, attendance and trial attrition were suboptimal, which raised concerns regarding the feasibility of CHAMP. Qualitative feedback from participants indicated 3 areas for refinement: (1) a less burdensome intervention modality, (2) a more individually tailored intervention experience, and (3) that interventionists can better answer health-related questions. OBJECTIVE: We propose to improve upon our pilot intervention by developing the Mobile Childhood Health and Asthma Management Program (mCHAMP), a nurse-delivered BFI, delivered to individual families, and supported by a mobile health (mHealth) app. This study aims to (1) identify structural components of mCHAMP and (2) develop and test the usability of our mCHAMP app. METHODS: Participants will be recruited from an outpatient pediatric pulmonary clinic. We will identify the structural components of mCHAMP by conducting a needs assessment with parents of children with asthma and obesity. Subsequently, we will develop and test our mCHAMP app using an iterative process that includes usability testing with target users and pediatric nurses. RESULTS: This study was funded in 2018; 13 parents of children with asthma and obesity participated in the needs assessment. Preliminary themes from focus groups and individual meetings included barriers to engaging in health-promoting behaviors, perceived relationships between asthma and obesity, facilitators to behavior change, and intervention preferences. Participatory design sessions and usability testing are expected to conclude in late 2019. CONCLUSIONS: Outcomes from this study are expected to include an mHealth app designed with direct participation from the target audience and usability data from stakeholders as well as potential end users. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13549.
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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 | 0.027 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.147 | 0.026 |
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".