Communication Skills Training at the Atlantic Veterinary College, University of Prince Edward Island
Bibliographic record
Abstract
Communication skills are considered a core clinical skill in human medicine. Recognizing the importance of communication skills and addressing them in veterinary curricula, however, is just beginning. In the fall of 2003, the Atlantic Veterinary College, University of Prince Edward Island, markedly changed the way in which it approaches communication teaching. An intensive one-week elective rotation on client communication was offered in the senior year. This rotation made extensive use of experiential techniques through the use of role plays and videotaped real client interactions. A group of faculty and hospital staff members were trained as coaches to support students as they practiced their communication in various client scenarios. The skills taught were based on the Calgary-Cambridge Observation Guide, which outlines observable behaviors that contribute to effective medical communication. Student response to and feedback on the rotation have been very positive. As a result, the number of rotations given per year has been increased. Long-term plans include expanding communication skills teaching into other years of the DVM program and incorporating simulated clients into the teaching program. Challenges that lie ahead include the development of a fully integrated communication teaching program that spans the whole curriculum, addressing the ongoing need for the professional development of coaches, improving methods of student assessment, and recruiting/training a sufficient number of coaches.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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".