Surviving transition: A qualitative case study on how families adapt as their youth with medical complexity transitions from child to adult systems of care
Bibliographic record
Abstract
Background: A growing population of youth with medical complexity (YMC) are entering adult health care, education, and social systems in which their needs have been largely neglected. To better support YMC and their families, an understanding of how they manage the challenges of transitioning to adult services is needed. The aim of this study was to examine how families of YMC adapt to challenges and opportunities posed by the youth's transition to adulthood and transfer to adult services. Methods: In partnership with two parent co-researchers and underpinned by complex adaptive systems and the Life Course Health Development framework, a qualitative explanatory case study was conducted. Seventeen participants from 11 families of YMC (aged 16-30) living in Ontario were recruited. Data from 21 semi-structured interviews were analyzed using reflexive thematic analysis and further refined through theory-driven analysis. Supplementary documents shared by participants were analyzed using directed content analysis. Findings: Three overarching themes were generated. "Imagining, pursuing, and building a good future" describes families' priorities and visions for the youth's life as an adult. "Perils and obstacles of an imposed transition" examines challenges that families face in their pursuit of a good future. Lastly, "surviving the transition" describes how families are forced to advocate, make sacrifices, and persist in their efforts to adapt to transition. Conclusions: Pediatric providers should offer anticipatory guidance, partner with families in advocacy, and provide psychological support during transition. Education for adult and primary care providers should focus on developing professional competencies in the safe care of YMC, building capacity through clinical exposure, and creating culturally safe environments. Most importantly, YMC and their families need a model of care that can provide integrated, holistic, multidisciplinary care management across the lifespan.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| 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".