Musculoskeletal examination teaching by patients versus physicians: How are they different? Neither better nor worse, but complementary
Bibliographic record
Abstract
BACKGROUND: Musculoskeletal (MSK) complaints comprise 12-20% of primary healthcare; however, practicing physicians' MSK physical examination (PE) skills are weak. Further, there is a shortage of specialists able to effectively teach this subject. Previous evaluations of patient educators have yielded mixed results. AIMS: The aim of this study is to document how teaching by patient educators and physician tutors in MSK PE skills differs. METHODS: A qualitative researcher observed, video-recorded, and took notes during preclerkship MSK PE teaching sessions given by patient educators or physician tutors. The researcher identified themes which were evaluated by collective case study methods. RESULTS: Two patient educator and four physician groups were evaluated. The patient educators were more consistent regarding content and style than the physicians. There appeared to be a continuum in teaching organization from patient educator to novice physician tutors to experienced physician tutors. The patient educators consistently covered all major joints (physicians did not); physicians were more likely to request verbalization of actions, relate findings to history, receive questions, and use opportunistic teaching moments. CONCLUSIONS: Understanding preclerkship MSK teaching by patient educators compared to physician tutors is necessary for appropriate targeting of the existing Patient Partners® in Arthritis patient educator program and to guide the development of future MSK teaching initiatives.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".