Adapting the McMaster-Ottawa scale and developing behavioral anchors for assessing performance in an interprofessional Team Observed Structured Clinical Encounter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Current scales for interprofessional team performance do not provide adequate behavioral anchors for performance evaluation. The Team Observed Structured Clinical Encounter (TOSCE) provides an opportunity to adapt and develop an existing scale for this purpose. We aimed to test the feasibility of using a retooled scale to rate performance in a standardized patient encounter and to assess faculty ability to accurately rate both individual students and teams. METHODS: The 9-point McMaster-Ottawa Scale developed for a TOSCE was converted to a 3-point scale with behavioral anchors. Students from four professions were trained a priori to perform in teams of four at three different levels as individuals and teams. Blinded faculty raters were trained to use the scale to evaluate individual and team performances. G-theory was used to analyze ability of faculty to accurately rate individual students and teams using the retooled scale. RESULTS: Sixteen faculty, in groups of four, rated four student teams, each participating in the same TOSCE station. Faculty expressed comfort rating up to four students in a team within a 35-min timeframe. Accuracy of faculty raters varied (38-81% individuals, 50-100% teams), with errors in the direction of over-rating individual, but not team performance. There was no consistent pattern of error for raters. CONCLUSION: The TOSCE can be administered as an evaluation method for interprofessional teams. However, faculty demonstrate a 'leniency error' in rating students, even with prior training using behavioral anchors. To improve consistency, we recommend two trained faculty raters per station.
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.
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 | 0.003 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it