Améliorer la prise en charge de l’enfant atteint de diabète de type 1 et celle de sa famille : quel rôle pour l’infirmière de pratique avancée, coordinatrice de parcours complexe de soins ? Une étude qualitative et exploratoire
Bibliographic record
Abstract
BACKGROUND: Type 1 diabetes in children in Switzerland is becoming increasingly prevalent. The coordination of care seems to be a determining element and is essential for effective and efficient care. OBJECTIVE: Identify the difficulties and the levers of coordination faced by healthcare workers and families during the discovery of type 1 diabetes in children aged from birth to fifteen. METHOD: Qualitative analysis using semi-directed interviews. RESULTS: Three families and five healthcare workers participated in the study. Confirmation of the diagnosis was received badly and was a shock for the families. Nurses specializing in pediatric diabetes are recognized for being experts in diabetes care and education. Non-specialist nurses consider diabetes care to be stressful and complex. Collaboration between units is described as compartmentalized. ICT tools are not shared between units. Psychological support is considered to be unsatisfactory by the families. DISCUSSION: Interdisciplinary nurses need to work together and with a structured coordination of care.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".