Neonatal Ethics Teaching Program - Scenario-Oriented Learning in Ethics: Announcing the Diagnosis of Trisomy 21
Bibliographic record
Abstract
INTRODUCTION: Delivering unexpected news to families can lead to emotionally charged conversations that cause discomfort and feelings of ineffectiveness in pediatric postgraduate trainees. Although prenatal screening exists, over 80% of trisomy 21 diagnoses continue to be made postnatally to unsuspecting parents who report a desire for better communication from health care professionals when they first receive the news of their child's diagnosis. Recognizing this area for improvement as reported in the literature, as well as the expressed desire from fellows in the University of Ottawa neonatal-perinatal medicine program for additional protected time to preemptively practice such disclosures, this trisomy 21 Scenario-Oriented Learning in Ethics workshop was developed. METHODS: During the workshop, trainees are introduced to an evidence-based communication framework that provides them with strategies to facilitate clear knowledge translation and promote rapport with families for this specific clinical scenario. Participants are divided into small groups and practice disclosing a trisomy 21 diagnosis to a standardized patient in the role of a new mother. Each small group is supported by two trained facilitators who are experts in delivering life-altering news. RESULTS: The pilot workshop was completed by 21 postgraduate trainees from the University of Ottawa. Qualitative evaluations were overwhelmingly positive, with feedback indicating high levels of perceived usefulness for the workshop. DISCUSSION: By preemptively practicing evidence-based communication, we hope to increase trainee confidence and preparation for trisomy 21 disclosures and improve parents' feelings regarding the quality of communication and support provided while receiving real-life trisomy 21 diagnoses.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".