Patients’ perspectives on the extent of resident participation in the operating room for total hip or knee arthroplasty
Bibliographic record
Abstract
INTRODUCTION: Previous work suggests that patients do not understand the extent of resident involvement in their care and are also uncomfortable with resident involvement. METHODS: We recruited 202 English speaking patients with previous or planned total joint arthroplasty of the lower limb for a prospective survey trial. We assessed participant's knowledge of resident level of education and confidence of resident involvement in their surgery as a function of supervision. RESULTS: < 0.05). 11.1% of participants did not want residents involved in their treatment. 60.6% would like to know more about the education level of the trainee. Less than half of participants correctly identified the education level of residents and fellows. CONCLUSION: Patient confidence in residents performing part or all of their surgery increases with resident experience and supervision. Compared with attending surgeons, patients have significantly less confidence in residents performing their surgery, including while supervised. Most patients do not understand the educational progression of medical trainees and would like to know more about the education level of the resident involved in their care. Further work should explore how we can help patients better understand resident involvement in their surgical care.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".