Evaluating Dog- and Cat-Owner Preferences for Calgary-Cambridge Communication Skills: Results of a Questionnaire
Bibliographic record
Abstract
Veterinary client retention by companion animal practices is influenced by whether the client feels connected to the healthcare provider. Effective communication between the veterinarian and the client facilitates that connection. To prepare new graduates for success in clinical practice, many colleges of veterinary medicine are now incorporating communication into the curriculum to emphasize its importance in establishing and maintaining the veterinarian-client relationship. A 2016 focus group study by Englar et al. evaluated dog and cat owner communication preferences for Calgary-Cambridge Guide (CCG) communication skills and concluded that dog and cat owners may have different communication needs. This study was conducted to confirm whether species-based communication preferences exist among veterinary clients. A questionnaire was distributed online and on-site, within veterinary teaching hospitals and private practices. Based upon 215 submissions from dog owners and 166 from cat owners, the communication preferences of dog and cat owners overlap. Both dog and cat owners prioritize reflective listening as the most important foundational CCG communication skill, and both prioritize asking permission as the most important core CCG skill. However, dog owners valued open-ended questions more than cat owners, and cat owners valued empathy more than dog owners. Survey limitations were largely demographic: participants were predominantly female and between the ages of 18-40 years. Survey data may therefore not be representative of the perspective of males and/or those >40 years of age.
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 | 0.009 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".