Simulated patient and role play methodologies for communication skills training in an undergraduate medical program: Randomized, crossover trial
Bibliographic record
Abstract
Background: Educators utilize real patients, simulated patients (SP), and student role play (RP) in communication skills training (CST) in medical curricula. The chosen modality may depend more on resource availability than educational stage and student needs. In this study, we set out to determine whether an inexpensive volunteer SP program offered an educational advantage compared to RP for CST in preclinical medical students. Methods: Students and volunteer SPs participated in interactions across two courses. Students allocated to SP interactions in one course participated in RP in the other course and vice versa. Audio recordings of interactions were made, and these were rated against criterion descriptors in a modified Calgary-Cambridge Referenced Observation Guide. Results: Independent t-test scores comparing ratings of RP and SP groups revealed no significant differences between methodologies. Discussion: This study demonstrates that volunteer SPs are not superior to RP, when used in CST targeted at preclinical students. This finding is consistent with existing literature, yet we suggest that it is imperative to consider the broader purpose of CST and the needs of stakeholders. Consequently, it may be beneficial to use mixed methods of CST in medical 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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".