Resident Evaluations: The Use of Daily Evaluation Forms in Rheumatology Ambulatory Care
Bibliographic record
Abstract
OBJECTIVE: The in-training evaluation report (ITER) is widely used to assess clinical skills, but has limited validity and reliability. The purpose of our study was to assess the feasibility, validity, reliability, and effect on feedback of using daily evaluation forms to evaluate residents in ambulatory rheumatology clinics. METHODS: An evaluation form was developed based on the Royal College of Physicians and Surgeons of Canada CanMEDS roles. There were 12 evaluation items including overall clinical competence. They were rated on a 5-point scale from unsatisfactory to outstanding. All internal medicine residents rotating on rheumatology were strongly encouraged to provide the form to their preceptor at the end of each clinic. A questionnaire was administered to residents and faculty. RESULTS: Seventy-three internal medicine residents completed a 1-month rotation at University of Ottawa (n=26) and McMaster University (n=47). Faculty members completed a total of 637 evaluation forms. The number of evaluation forms ranged from 2 to 16 (mean 8.73) per resident. At an average of 8.73 forms per resident the reliability was 0.71 for the composite score. Fourteen forms would be required for a reliability of 0.8. The correlation between the objective structured clinical examination scores and the forms was 0.48 (p=not significant). Faculty and residents reported increased feedback following implementation of the forms. CONCLUSION: The use of daily evaluation forms is feasible and provides very good reliability. Use of the evaluation forms increases feedback to residents on their performance. The forms were well received by faculty and residents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".