Effectiveness of Clinical Presentation (CP) Curriculum in teaching clinical medicine to undergraduate medical students: A cross-sectional study.
Bibliographic record
Abstract
Introduction: The Clinical Presentation (CP) curriculum was first formulated in 1990 at the University of Calgary, Canada. Since then, it has been adopted at various medical schools, including Patan Academy of Health Sciences (PAHS), a state-funded medical school in a low-income country (LIC), Nepal. This study aims to evaluate the perceived effectiveness of the CP curriculum by students and faculty at PAHS, and test knowledge retention through a surprise non-routine exam administered to students. Method: This is a cross-sectional study to evaluate the efficacy of the CP curriculum in teaching clinical medicine to the first batch of MBBS students of PAHS School of Medicine. Ethical approval was obtained from the Institutional Review Committee (IRC)-PAHS (Ref no std1505911069). Perceived effectiveness was evaluated using a set of questionnaires for faculty and students. A total of 33 students and 34 faculty filled the perception questionnaires. Subsequently, a questionnaire consisting of 50 Multiple Choice Questions (MCQs) from different clinical medicine disciplines was administered to test students’ knowledge retention. Out of 49 students, 38 participated in the surprise non-routine exam. Result: A significantly higher number of faculty preferred the CP curriculum compared to the traditional system of teaching clinical medicine (16 vs 11, Kruskal Wallis: 0.023, ie. P-value < 0.05). A significantly higher number of the students liked and recommended CP curriculum in the clinical year of medical education (20 vs. 13 with p-value < 0.05). In the non-routine surprise exam, two thirds of the students scored 60% or above. Conclusion: Both faculty and students perceive that the CP curriculum system is an effective teaching and learning method in medical education, irrespective of their different demographic and positional characteristics. The students’ overall performance was good in surprise, non-routine exams taken without scheduling or reminders.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".