Evaluation of communication skills training programs at North American veterinary medical training institutions
Bibliographic record
Abstract
OBJECTIVE: To describe how North American veterinary medical teaching institutions (VMTIs) provide communication skills training to students. SAMPLE: Faculty coordinators of communication skills training programs (CSTPs) at 30 North American VMTIs. PROCEDURES: An online survey instrument was designed and administered to each respondent followed by a telephone (n = 28) or in-person (2) interview. The survey and interview process were designed to evaluate all aspects of CSTPs, such as communication framework used, program format, number of student-contact hours, staffing models, outcome assessment, faculty background, program priorities, and challenges. Descriptive results were generated, and guidelines for future development of CSTPs were recommended. RESULTS: 27 US and 3 Canadian VMTIs were represented, and communication skills training was required at all. Twenty-five CSTPs used the Calgary-Cambridge Guide framework. Respondents provided a mean of 33 student-contact hours of training, primarily in the first 3 years of the veterinary curriculum in lecture (mean, 12 hours), communication laboratory (13 hours), and self-study (8 hours) formats with formative feedback. Communication skills training was integrated with other disciplines at 27 VMTIs. Most CSTPs were coordinated and taught by 1 faculty member with a < 0.50 full-time equivalent commitment and no administrative support. Stated priorities included acquisition of resources for CSTP faculty, administrative support, and video-equipped facilities; increasing integration of CSTPs into curricula; and assessment of educational outcomes. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that support for CSTPs and recognition of their value continue to grow, but a lack of resources, faculty expertise, validated methods for outcomes assessment, and leadership remain challenges.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".