Effectiveness of a Clinically Relevant Educational Program for Improving Medical Communication and Clinical Skills of International Medical Graduates
Bibliographic record
Abstract
Background: To assess the efficacy of a 16 week, intensive, full-time medical communication and clinical skills educational program – Medical Communication Assessment Project (M-CAP) – at the Universities of Calgary and Alberta for improving medical communication, clinical skills and professionalism of international medical graduates (IMGs). There is an 8 week didactic course (language instructors, standardized clinical case scenarios) and an 8 week supervised clinical placement.Method: In Study 1, 39 IMGs (mean age = 35.6) participated in the M-CAP program and were assessed in English language proficiency in a pre- post-test design and on an in training evaluation report (ITER) by practicum physicians. In Study 2, there were 235 IMGs (mean age = 39.2). In addition to the pre- post-test design, there was a comparison group analysis on OSCE data employing multivariate analysis of variance (MANOVA). Pre- post-test data were also collected on ITERs during the practicum as was IMG reported program efficacy data.Results: The findings show that the participants in the M-CAP program have 1) very large gains in language proficiency (listening and speaking, reading and writing; p < .001), and 2) high ratings on scales from the practicum physicians. The between group analyses showed that M-CAP participants outperformed the non M-CAP participants on clinical skills and professionalism (p < .05). The IMGs gave very positive ratings to the M-CAP program.Conclusions: IMGs who participated in a clinically relevant educational program improved their English language proficiency, clinical skills and professionalism for medical practice in a host country.
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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 | 0.230 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".