Validity and Reliability of the Standardized Orthopedic Assessment Tool (SOAT): A Variation of the Traditional Objective Structured Clinical Examination
Bibliographic record
Abstract
CONTEXT: Health care professions have replaced traditional multiple choice tests or essays with structured and practical, performance-based examinations with the hope of eliminating rater bias and measuring clinical competence. OBJECTIVE: To establish the validity and reliability of the Standardized Orthopedic Assessment Tool (SOAT) as a measure of clinical competence of orthopaedic injury evaluation. DESIGN: Descriptive laboratory study. SETTING: University. PATIENTS OR OTHER PARTICIPANTS: A total of 60 undergraduate students and 11 raters from 3 Canadian universities and 1 standardized patient. INTERVENTION(S): Students were required to complete a 30-minute musculoskeletal evaluation in 1 of 2 randomly assigned mock scenarios involving the knee (second-degree medial collateral ligament sprain) or the shoulder (third-degree supraspinatus muscle strain). MAIN OUTCOME MEASURE(S): We measured interreliability with an intraclass correlation coefficient (ICC) (2,k) and stability of the tool with standard error of measurement and confidence intervals. Agreement was measured using Bland-Altman plots. Concurrent validity was measured using a Pearson product moment correlation coefficient whereby the raters' global rating of a student was matched to the cumulative mean grade score. RESULTS: The ICCs were 0.75 and 0.82 for the shoulder and knee cases, respectively. Bland-Altman plots indicated no systematic bias between raters. In addition, Pearson product moment correlation analysis demonstrated a strong relationship between the overall cumulative mean grade score and the global rating score of the examinees' performances. CONCLUSIONS: This study demonstrated good interrater reliability of the SOAT with a standard error of measurement that indicated very modest stability, strong agreement between raters, and correlation indicative of concurrent validity.
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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 | 0.027 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".