P-41: What Mothers Think of Communication About Their Child with Tracheoesophageal Fistula (TEF)
Bibliographic record
Abstract
Tracheoesophageal Fistula (TEF) is a congenital anomaly that requires complex initial treatment. Children with TEF face multiple challenges including: surgeries, hospital stays, and complications. These children require numerous health care services to manage their complicated condition. This is a challenging time for the parents of a child with TEF. A multidisciplinary clinic was started in 2006 to coordinate the complex care of these children and their families. To gain an understanding of parental perceptions of the communication provided through this multidisciplinary clinic. Interviews were conducted with three primary caregivers of children with TEF born between 2010 and 2011. Qualitative data obtained from these interviews was analyzed to identify whether the TEF clinic has contributed to improvement of care. Parent interviews include positive feedback for these themes: appropriate information, coordination of care, positive relationships, and anticipatory guidance. Improvements could be made to coordination of care between disciplines especially during pre-surgical communications. A multidisciplinary approach to complex care of children with TEF is beneficial. There was positive feedback from parents with children enrolled in this clinic, indicating successful aspects of the clinic care and communication. Some aspects of care remains fragmented, and further aims to improve the TEF Clinic are required.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".