Validity, Reliability and Acceptability of the Team Standardized Assessment of Clinical Encounter Report*
Bibliographic record
Abstract
BACKGROUND: The Team Standardized Assessment of a Clinical Encounter Report (StACER) was designed for use in Geriatric Medicine residency programs to evaluate Communicator and Collaborator competencies. METHODS: The Team StACER was completed by two geriatricians and interdisciplinary team members based on observations during a geriatric medicine team meeting. Postgraduate trainees were recruited from July 2010-November 2013. Inter-rater reliability between two geriatricians and between all team members was determined. Internal consistency of items for the constructs Communicator and Collaborator competencies was calculated. Raters completed a survey previously administered to Canadian geriatricians to assess face validity. Trainees completed a survey to determine the usefulness of this instrument as a feedback tool. RESULTS: Thirty postgraduate trainees participated. The prevalence-adjusted bias-adjusted kappa range inter-rater reliability for Communicator and Collaborator items were 0.87-1.00 and 0.86-1.00, respectively. The Cronbach's alpha coefficient for Communicator and Collaborator items was 0.997 (95% CI: 0.993-1.00) and 0.997 (95% CI: 0.997-1.00), respectively. The instrument lacked discriminatory power, as all trainees scored "meets requirements" in the overall assessment. Niney-three per cent and 86% of trainees found feedback useful for developing Communicator and Collaborator competencies, respectively. CONCLUSIONS: The Team StACER has adequate inter-rater reliability and internal consistency. Poor discriminatory power and face validity challenge the merit of using this evaluation tool. Trainees felt the tool provided useful feedback on Collaborator and Communicator competencies.
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 | 0.042 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".