Consensus statement on the content of clinical reasoning curricula in undergraduate medical education
Bibliographic record
Abstract
INTRODUCTION: Effective clinical reasoning is required for safe patient care. Students and postgraduate trainees largely learn the knowledge, skills and behaviours required for effective clinical reasoning implicitly, through experience and apprenticeship. There is a growing consensus that medical schools should teach clinical reasoning in a way that is explicitly integrated into courses throughout each year, adopting a systematic approach consistent with current evidence. However, the clinical reasoning literature is 'fragmented' and can be difficult for medical educators to access. The purpose of this paper is to provide practical recommendations that will be of use to all medical schools. METHODS: to teach). A consensus statement was then produced based on the agreed ideas and the literature review, discussed by members of the consensus statement group, then edited and agreed by the authors. RESULTS: The group identified 30 consensus ideas that were grouped into five domains: (1) clinical reasoning concepts, (2) history and physical examination, (3) choosing and interpreting diagnostic tests, (4) problem identification and management, and (5) shared decision making. The literature review demonstrated a lack of effectiveness for teaching the general thinking processes involved in clinical reasoning, whereas specific teaching strategies aimed at building knowledge and understanding led to improvements. These strategies are synthesised and described. CONCLUSION: What is taught, how it is taught, and when it is taught can facilitate clinical reasoning development more effectively through purposeful curriculum design and medical schools should consider implementing a formal clinical reasoning curriculum that is horizontally and vertically integrated throughout the programme.
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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 | 0.007 | 0.480 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".