Effectiveness of Bi-lingual Multidisciplinary Simulation-based Training in Improving Communication and Breaking Bad-News Skills
Bibliographic record
Abstract
Background: Healthcare worker (HCW)-patient communication is an essential element of every patient’s journey, and evidence links good communication with favourable patient experiences and outcomes. Simulation-based training (SBT) is a promising and effective tool to improve such communication. Aim: To develop a bilingual SBT programme in communication skills for all HCWs in an academic tertiary hospital, to improve patient care, experiences and outcomes. Methods: This was a quasi-experimental design, conducted in 2018 at King Abdulaziz University (KAU). We designed and delivered a bilingual, simulation-based, full-day course for HCWs (both clinical and administrative), and measured its impact by comparing pre- and post-course test scores, participant feedback, and instructor performance satisfaction indices. Results: We trained 318 HCWs over 15 days, using 10 instructors. Post-test scores showed individual and overall improvement. The average scores were 26.6% (14-40%) for the pre-test and 55.8% (37-70%) for the post-test, with an average improvement of 29% (P<0.005). Participant feedback was 77% positive and in favour of more training. The average instructor performance satisfaction score was 96.2% (92-99%). Conclusion: We demonstrated the positive impact of SBT on communication skills for both clinical and administrative HCWs. We also demonstrated the sustainability and scalability of this course.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".