An exploration of information exchange and decision-making within veterinarian-client-patient interactions during companion animal visits
Bibliographic record
Abstract
Information exchange and decision-making support positive healthcare outcomes. Focus group, questionnaire-based and observational research methodologies were used to investigate these important aspects of communication for companion animal veterinary practice. Pet owner expectations and veterinarians’ perceptions of pet owner expectations regarding information exchange and decision-making, along with communication challenges veterinarians face, were explored using 5 focus groups of pet owners (n=27) and 3 of veterinarians (n=24). Inductive thematic analysis of focus groups identified two themes: information exchange and decision-making. Subthemes of information exchange included understanding the client and providing information suitable for the client. Decision-making was seen by pet owners as an opportunity to be involved in their pets’ veterinary care decisions. Veterinarian-specific barriers were time constraints, involvement of multiple clients and language barriers. Audio-video recorded veterinary appointments (n=714) involving 60 veterinarians were assessed using the OPTION5 instrument to quantify client involvement in veterinary care decisions. Veterinarians’ mean score was 22.6 out of 100, indicating low use of client-involving behaviours. Veterinarians with fewer years in practice and increased appointment length were associated with higher levels of shared decision-making when controlling for a significant interaction between client household income and appointment type. Questionnaires were used to assess veterinarians’ (n=416) and veterinary clients’ (n=529) perceptions of information exchanged about pets’ blood tests. Significant differences were found between the perceptions of participating veterinarians and clients regarding the frequency with which veterinarians educated clients about characteristics of their pets’ blood tests. A mixed methods study was conducted to explore and identify characteristics associated with companion animal veterinarians’ communication of health parameter trends. Focus groups explored pet owners and veterinarians’ perceptions of veterinarians’ communication of health parameter trends and codes were identified. Audio-video recorded veterinary appointments (n=911) were analyzed using the focus group codes to assess the prevalence and nature of these conversations in practice. Fewer than 10% (76/911) of appointments included any mention of a health parameter trend; of those that did, the majority discussed body weight. This thesis contributed to the understanding of veterinarian-client-patient interactions regarding decision-making and identifies opportunities to improve client engagement in veterinary care by enhancing understanding of information exchange.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".