Evaluation of a Communication Skills Training Program for Companion-Animal Veterinarians: A Pilot Study Using RIAS Coding
Bibliographic record
Abstract
Effective veterinarian communication skills training and the related key outcomes provided the impetus for this study. We implemented a pre-experimental pre-test/post-test single-group design with a sample of 13 veterinarians and their 71 clients to evaluate the effects of a 6.5-hour communication skills intervention for veterinarians. Consultations were audiotaped and analyzed with the Roter Interaction Analysis System (RIAS). Clients completed the Consultation and Relational Care Measure, a global satisfaction scale, a Parent Medical Interview Satisfaction Scale, and the Adherence Intent measure. Veterinarians completed a communication confidence measure and a workshop satisfaction scale. Contrary to expectation, neither veterinarian communication skills nor their confidence improved post-training. Despite client satisfaction and perceptions of veterinarians' relational communication skills not increasing, clients nevertheless reported an increased intent to adhere to veterinarian recommendations. This result is important because client adherence is critical to managing and enhancing the health and well-being of animals. The results of the study suggest that while the workshop was highly regarded, either the duration of the training or practice opportunities were insufficient or a booster session was required to increase veterinarian confidence and integration of new skills. Future research should utilize a randomized control study design to investigate the appropriate intervention with which to achieve change in veterinarian communication skills. Such change could translate to more effective interactions in veterinarians' daily lives.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".