Assessing Communications Competencies through Reviews of Client Interactions and Comprehensive Rotation Assessment: A Comparison of Methods
Bibliographic record
Abstract
The primary purpose of this study was to compare two methods for assessing student communication skills: a labor-intensive review of video-recorded interactions and global communications assessment using a comprehensive rotation-assessment tool. Secondary goals of the study were to evaluate student strengths and weaknesses to inform the pre-clinical communications curriculum and to evaluate for consistency between types of reviewers. Video recordings of 43 student encounters with clients presenting their animals for wellness or diagnostic appointments to the primary care service at a veterinary teaching hospital were reviewed by one of three primary care clinicians, a social worker, and a clinical communications instructor, using a common rubric. Scores using the rubric were compared with overall scores for verbal communications on a comprehensive rotation-assessment tool, both for the primary care rotation and for other small-animal rotations. Duration did not vary significantly between wellness and diagnostic appointments, or between dog and cat appointments. Scores achieved by students on video review varied by evaluator, with the clinical communications instructor scoring students the lowest and the social worker scoring students the highest. Strengths identified included greeting the client appropriately, gathering initial information about the reason for the visit, and using lay terminology appropriately. Weaknesses included summarizing information for the client, talking to clients about money, and making strong recommendations.
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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 | 0.058 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 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".