Bereaved Parents as Communication Workshop Facilitators for Clinicians Caring for Seriously Ill Children
Bibliographic record
Abstract
Introduction: The Serious Illness Conversation Guide-Pediatrics (SICG-Peds) is a validated tool and training program that increases clinicians' confidence in leading complex conversations with seriously ill pediatric patients and their families. We initiated a pilot project incorporating bereaved parents as facilitators in SICG-Peds education. Objectives: To assess how incorporating bereaved parents in a facilitator role in the SICG-Peds education program impacted the experience for clinician trainees and clinical facilitators and the parents themselves. Methods: Four bereaved parents were onboarded and included as family facilitators. Workshop experience was measured through post-workshop surveys. Clinical facilitators and family facilitators provided feedback about the co-teaching experience. Results: Clinicians reported that having bereaved parents as teaching faculty enriched their learning. Clinical facilitators found that family facilitators offered additional perspectives and value. Parents recognized that they could hone their story and experience to support the clinician learners in unique ways. Conclusions: The addition of family facilitators in the delivery of SICG-Peds workshops enhanced clinicians' learning. Moreover, bereaved parents reported that functioning as workshop facilitators was a deeply meaningful experience.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".