Developing Assessments for Key Stakeholders in Pediatric Congenital Heart Disease: Qualitative Pilot Study to Inform Designing of a Medical Education Toy
Bibliographic record
Abstract
BACKGROUND: Congenital heart disease (CHD) is a birth defect of the heart that requires long-term care and often leads to additional health complications. Effective educational strategies are essential for improving health literacy and care outcomes. Despite affecting around 40,000 children annually in the United States, there is a gap in understanding children's health literacy, parental educational burdens, and the efficiency of health care providers in delivering education. OBJECTIVE: This qualitative pilot study aims to develop tailored assessment tools to evaluate educational needs and burdens among children with CHD, their parents, and health care providers. These assessments will inform the design of medical education toys to enhance health management and outcomes for pediatric patients with CHD and key stakeholders. METHODS: Through stakeholder feedback from pediatric patients with CHD, parents, and health care providers, we developed three tailored assessments in two phases: (1) iterative development of the assessment tools and (2) pilot testing. In the first phase, we defined key concepts, conducted a literature review, and created initial drafts of the assessments. During the pilot-testing phase, 12 participants were recruited at the M Health Fairview Pediatric Specialty Clinic for Cardiology-Explorer in Minneapolis, Minnesota, United States. We gathered feedback using qualitative methods, including cognitive interviews such as think-aloud techniques, verbal probing, and observations of nonverbal cues. The data were analyzed to identify the strengths and weaknesses of each assessment item and areas for improvement. RESULTS: The 12 participants included children with CHD (n=5), parents (n=4), and health care providers (n=3). The results showed the feasibility and effectiveness of the tailored assessments. Participants showed high levels of engagement and found the assessment items relevant to their education needs. Iterative revisions based on participant feedback improved the assessments' clarity, relevance, and engagement for all stakeholders, including children with CHD. CONCLUSIONS: This pilot study emphasizes the importance of iterative assessment development, focusing on multistakeholder engagement. The insights gained from the development process will guide the creation of tailored assessments and inform the development of child-led educational interventions for pediatric populations with CHD.
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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 | 0.059 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".