Caregiver experiences with transitions from pediatric to adult healthcare for children with complex care needs
Bibliographic record
Abstract
BACKGROUND: Caring for a youth with complex care needs (CCN) who is transitioning from paediatric to adult healthcare can produce many challenges. For example, caregivers must often manage their youth's care at home, coordinate care and advocate for their youth. Experiences of fragmented and uncoordinated care often result in caregivers feeling ill-prepared and uncertain about the transition process. The current study explores caregiver experiences with the transition from paediatric to adult healthcare for youth with CCN in a semi-rural Canadian province. METHODS: This study used a cross-sectional qualitative descriptive design, involving semi-structured interviews with caregivers of youth with CCN who were preparing for, in the process of, or completed a transition from paediatric to adult healthcare within the province of New Brunswick, Canada. Thematic analysis focused on describing caregiver experiences with the transition from paediatric to adult healthcare. RESULTS: Seventeen caregivers completed interviews for this study. Four key themes emerged relating to caregiver experiences with the transition from paediatric to adult healthcare for these youth: (1) lack of caregiver support, (2) lack of continuity of care, (3) need for collaborative care and (4) difficulty navigating transition. CONCLUSION: There is a clear need to address the challenges experienced by youth with CCN and their caregivers throughout the transition from paediatric to adult healthcare. An effective transition strategy should involve early and coordinated planning between the paediatric and adult care team; continued communication across the care team throughout the transition process; and coordination among health, education and social services.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".