67: Is Simulation an Effective Way to Teach Communication in Neonatal-Perinatal Medicine?
Bibliographic record
Abstract
Effective communication between neonatologists and families is essential to family-centered care. Neonatal-Perinatal Medicine (NPM) training, however, focuses on knowledge acquisition, rather than communication skill development. Presently, there is no standardised approach to communication skills training in Canada. The purpose of this project was to develop, implement and evaluate a simulation based communication skills workshop for Neonatal-Perinatal Medicine trainees. A questionnaire to assess current communication teaching methodology and trainee confidence was sent to NPM program directors and trainees across Canada. A workshop that included both didactic teaching and simulated parent encounters was then developed based on deficits identified in the needs assessment. Trainee communication skills were assessed in pre and post workshop scenarios using qualitative (Calgary-Cambridge – CC) and quantitative (Global Rating Scale – GRS) assessment tools. One month later, trainees participated in another simulated encounter to evaluate retention. Trainees completed questionnaires pre and post workshop, as well as one month post workshop to assess perceived confidence, communication skills and workshop satisfaction. Two thirds of training programs do not offer formal communication skills training. Eight trainees completed the workshop; four of these completed the retention assessment. Five trainees improved on both the GRS and CC with mean scores (sd) increasing from 29.6 (±1.8) to 33 (±2.4) out of 45 and 83.1 (±2.6) to 89.9 (±3.0) out of 100, respectively. At the one month post assessment, three trainees were equivalent to, or improved from, their post workshop assessment with scores of 35.3 (± 1) and 95.2 (±1.7). In pre vs. post workshop surveys, there were trends towards increasing confidence in discussing palliative care (33.3% vs. 77.8%), conflicts of opinion (44.4% vs. 66.7%) and religious or spiritual beliefs (33.3% vs. 66.7%). Seven of eight trainees “agreed” or “strongly agreed' that the workshop met their expectations and all “agreed” or “strongly agreed” that the workshop improved their communication skills. The implementation of a simulation based communication skills workshop resulted in improved confidence amongst trainees and improved qualitative and quantitative assessments in almost two-thirds of cases. Similar workshops should be implemented to enhance communication skills teaching across Canadian NPM programs.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".