Establishing the Need for Anticipatory Symptom Guidance and Networked Models of Disease in Adaptive Family Management Among Children With Medical Complexity: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Caregivers of children with medical complexity navigate complex family management tasks for their child both in the hospital and home-based setting. The roles and relationships of members of their social network and the dynamic evolution of these family management tasks have been underexamined. OBJECTIVE: The purpose of this study was to explore the structures and processes of family management among caregivers of children with medical complexity, with a focus on the underlying dynamic nature of family management practices and the role of members of their social network. METHODS: This study used a qualitative approach to interview caregivers of children with medical complexity and members of their social network. Caregivers of children with medical complexity were recruited through an academic Children's Hospital Complex Care Clinic in the mid-Atlantic region and interviewed over a period of 1 to 3 days. Responses were analyzed using constructivist grounded theory and situational analysis to construct a new conceptual model. Only caregiver responses are reported here. RESULTS: In total, 20 caregivers were included in this analysis. Caregiver perspectives revealed the contextual processes that allowed for practices of family management within the setting of rapidly evolving symptoms and health concerns. The dynamic and adaptive nature of this process is a key underlying action supporting this novel conceptual model. The central themes underpinning the adaptive family management model include symptom cues, ongoing surveillance, information gathering, and acute on chronic health concerns. The model also highlights facilitators and threats to successful family management among children with medical complexity and the networked relationship among the structures and processes. CONCLUSIONS: The adaptive family management model provides a basis for further quantitative operationalization and study. Previously described self- or family management frameworks do not account for the underlying dynamic nature of the disease trajectory and the developmental stage progression of the child or adolescent, and our work extends existing work. For future work, there is a defined role for technology-enhanced personalized approaches to home-based monitoring. Due to the disparities caregivers and the children in this population already experience, technology-enhanced approaches must be built alongside key stakeholders with an equity orientation to technology co-development. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14810.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".