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Record W4411159877 · doi:10.1089/pmr.2025.0022

Bereaved Parents as Communication Workshop Facilitators for Clinicians Caring for Seriously Ill Children

2025· article· en· W4411159877 on OpenAlexaff
Camara van Breemen, Nadine Lusney, Anne‐Mette Hermansen, L. Vang

Bibliographic record

VenuePalliative Medicine Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsVancouver Native Health SocietyBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsPsychologyNursingPsychotherapistMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.367
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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