Supporting the transition to adult care for youth with medical complexity: family experiences, adaptation, and recommendations
Bibliographic record
Abstract
Background: A growing population of youth with medical complexity (YMC) are surviving into adulthood and being forced to transition from pediatric to adult health care. YMC and their families face significant challenges during this transition, putting them at risk for service fragmentation, inadequate care, and negative health outcomes. Existing interventions to support transition continue to have limited benefits for this group, demonstrating a clear need for tailored supports, informed by the perspectives of YMC and their families. Currently, these families’ transition experiences are poorly understood in the Canadian context. Thus, the aim of this dissertation was to holistically examine the experiences of families of YMC with the transition to adult care in Ontario. Methods: This sandwich thesis consists of: 1) a meta-ethnography synthesizing qualitative literature about the experiences of YMC and their families during the transition to adulthood; and 2) a patient-oriented qualitative case study exploring: i) how families of YMC adapt to the transition to adult care; ii) the influence of contextual factors; and iii) family recommendations for support. Findings: Transition impacts nearly all aspects of the youth’s and family’s lives. Families encounter numerous challenges in their pursuit of a good future and they “survive” by advocating, making sacrifices, and persisting despite inequities. Furthermore, families’ experiences are shaped by the complex interplay of personal and environmental factors. Conclusion: Implications for nursing practice, health care provider education, and health policy focus on: supporting nurses to provide instrumental and psychological support to families; building capacity in primary care (e.g., through nurse-led models of care); training health professionals on complex care management; and advocating for system-wide strategies to improve health care transition. Future research should prioritize the co-design and evaluation of interventions to address families’ information and emotional needs and training initiatives to facilitate the implementation of recommendations into practice.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".