Techniques to Communicate Better With Parents During End-of-Life Scenarios in Neonatology
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Clinicians are urged to optimize communication with families, generally without empirical practical recommendations. The objective of this study was to identify core behaviors associated with good communication during and after an unsuccessful resuscitation, including parental perspectives. METHODS: Clinicians from different backgrounds participated in a standardized, videotaped, simulated neonatal resuscitation in the presence of parent actors. The infant remained pulseless; participants communicated with the parent actors before, during, and after discontinuing resuscitation. Twenty-one evaluators with varying expertise (including 6 bereaved parents) viewed the videos. They were asked to score clinician-parent communication and identify the top communicators. In open-ended questions, they were asked to describe 3 aspects that were well done and 3 that were not. Answers to open-ended questions were coded for easily reproducible behaviors. All the videos were then independently reviewed to evaluate whether these behaviors were present. RESULTS: Thirty-one participants' videos were examined by 21 evaluators (651 evaluations). Parents and actors agreed with clinicians 81% of the time about what constituted optimal communication. Good communicators were more likely to introduce themselves, use the infant's name, acknowledge parental presence, prepare the parents (for the resuscitation, then death), stop resuscitation without asking parents, clearly mention death, provide or enable proximity (clinician-parent, infant-parent, clinician-infant, mother-father), sit down, decrease guilt, permit silence, and have knowledge about procedures after death. Consistently, clinicians who displayed such behaviors had evaluations >9 out of 10 and were all ranked top 10 communicators. CONCLUSIONS: During a neonatal end-of-life scenario, many simple behaviors, identified by parents and providers, can optimize clinician-parent communication.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".