Martin's Map: a conceptual framework for teaching and learning the medical interview using a patient‐centred approach
Bibliographic record
Abstract
OBJECTIVE: At the end of training, students seem to lack a basic understanding of how to take an organised, relevant medical and social history using a patient-centred approach. The aim of developing the map described in this paper was to provide a framework for such an approach. METHODS: Action research was used to continuously modify and refine an interview map that was used by medical clerks, family medicine residents, international medical graduates and practising doctors for teaching and learning purposes over a 10-year period. CONCLUSION: 'Martin's Map' provides a realistic framework for flexibly organising and integrating medical content with process that did not previously exist. The map provides medical educators with a standardised framework for talking about the medical interview, which helps learners understand how to use their medical knowledge with a patient-centred approach. Learners are able to visually see how they can take a focused medical and social history using a patient-centred approach, which subsequently seems to help them organise their thinking and approach during the medical encounter.
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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 | 0.002 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".