Resident self-assessment of operative experience in primary total knee and total hip arthroplasty: Is it accurate?
Bibliographic record
Abstract
BACKGROUND: A prerequisite for a valuable surgical case log is the ability to perform an accurate self-assessment. Studies have shown mixed results when examining residents' ability to self-assess on varying tasks. We sought to examine the correlation between residents' self-assessment and staff surgeons' evaluation of surgical involvement and competence in performing primary total knee (TKA) and hip arthroplasty (THA). METHODS: We used the intraclass correlation coefficient (ICC) to evaluate interobserver agreement between residents' self-perception and staff surgeons' assessment of involvement. An assessment of competency was performed using a categorical global scale and evaluated with the κ statistic. We piloted a structured surgical skills assessment form as an additional objective appraisal of resident involvement. RESULTS: We analyzed assessment data from 65 primary TKA and THA cases involving 17 residents and 17 staff surgeons (93% response rate). The ICC for resident involvement between residents and staff surgeons was 0.80 (95% confidence interval [CI] 0.69-0.88), which represents substantial agreement. The agreement between residents and staff surgeons about residents' competency to perform the case had a κ value of 0.67 (95% CI 0.50-0.84). The ICC for resident, staff surgeon and third-party observer using the piloted skills assessment form was 0.82 (95% CI 0.75-0.88), which represents substantial agreement. CONCLUSION: This study supports the ability of orthopedic residents to perform self-assessments of their degree of involvement and competency in primary TKA and THA. Staff surgeons' assessment of resident involvement correlated highly with the surgical skills assessment form. Self-assessment is a valuable addition to the surgical case log.
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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 | 0.001 | 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 | 0.000 |
| 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".