The effect of undergraduate education in communication skills: a randomised controlled clinical trial
Bibliographic record
Abstract
PURPOSE: To determine whether students improve their communication skills as a result of supervised patient care and whether a newly implemented communication course could further improve these skills. METHOD: We conducted a randomised, controlled trial including all participants of the first clinical treatment course (n = 26) between October 2006 and February 2007. Randomisation was balanced by gender and basic communication skills. The test group practised dentist-patient communication skills in small groups with role-plays and videotaped real patient interviews, whereas the control group learned in problem-based workshops both on a weekly basis. Before and after the interventions (two group pre- and post-design) all students conducted two interviews with simulated patients. The encounters were rated using a 10-item checklist derived from the Calgary-Cambridge Observation Guide I. RESULTS: Repeated measures ANOVA (alpha = 0.05) showed a significant difference of the sum scores of the ratings between test and control group (P = 0.004). The participants educated in communication skills improved significantly (Delta = +14.9; P = 0.004), whereas in the control group no accretion of practical communication competence was observed (Delta = -3.9; P = 0.23). CONCLUSION: It could be demonstrated that solely interacting with patients during a clinical treatment course did not inevitably improve professional communication skills. In contrast, implementation of a course in communication skills improved the practical competence in dentist-patient interaction.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".