Evaluating Medical Students' Confidence in Musculoskeletal Examination: Implications for Improving Musculoskeletal Medicine Education
Bibliographic record
Abstract
Introduction: Musculoskeletal (MSK) conditions are common in clinical settings, with approximately 20% of primary care and emergency department visits related to MSK issues. However, medical students in the United States and Canada often show a relative lack of confidence in conducting MSK examinations, especially when compared to their perceived examination skills of other organ systems. Objective: This study surveyed medical students at a local institution regarding their confidence with MSK examination skills, MSK examination education experience, and collected their suggestions about improving the curriculum. Methods: An anonymous, online survey was conducted among preclinical medical students at a state-funded allopathic medical school (John A Burns School of Medicine, University of Hawaii at Manoa). The survey, adapted from previous studies, included Likert scale and open-ended questions. Students reported their confidence in various physical exams, perceived preparedness for clerkships, usefulness of existing MSK clinical activities, and suggestions for improvement. Results: 64 out of 77 students from the Class of 2025 completed the survey. When compared with their perceived examination skills of other organ systems, students expressed less confidence in their ability to perform the musculoskeletal physical exam. Existing MSK teaching activities (Orthopedics, Rheumatology, and Transition to Clerkship Training), were deemed valuable by over 90% of students. It should be noted that 98.4% of students agreed that adding clinical MSK skills to their MD3 anatomy unit would be beneficial. Students also provided constructive comments and suggestions on how to integrate MSK exam curriculum with relevant anatomy units and increase small-group learning sessions for MSK exam practice. Discussion: The survey results indicated that third-year medical students lacked confidence in performing MSK examinations compared to other organ systems, aligning with findings in the existing literature. Traditionally, the Office of Medical Education (OME) incorporates MSK cases into pre-clerkship problem-based learning (PBL) sessions in the second year. The students expressed a desire for early exposure to MSK clinical skills. In response, the OME is implementing changes such as introducing MSK clinical exam skills in the first year with the collaboration of a physiatrist and the anatomy department. The same survey will be administered to future cohorts to assess the impact of these modifications, and objective outcomes such as anatomy examination results and standardized patient examination results will be collected. This initiative reflects a commitment to enhancing MSK education in medical school, with plans for further research and objective assessment.
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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 | 0.012 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".