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Record W2159284822 · doi:10.2460/javma.228.5.714

Veterinarian-client-patient communication patterns used during clinical appointments in companion animal practice

2006· article· en· W2159284822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2006
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Guelph
FundersOVC Pet Trust
KeywordsCompanion animalMedicineDescriptive statisticsSocial communicationFamily medicineBehavioral patternPsychologyVeterinary medicineCommunicationComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify communication patterns used by veterinarians during clinical appointments in companion animal practice. DESIGN: Cross-sectional descriptive study. SAMPLE POPULATION: A random sample of 50 companion animal practitioners in southern Ontario and a convenience sample of 300 clients and their pets. PROCEDURE: For each practitioner, 6 clinical appointments (3 wellness appointments and 3 appointments related to a health problem) were videotaped. The Roter interaction analysis system was used to analyze the resulting 300 videotapes, and cluster analysis was used to identify veterinarian communication patterns. RESULTS: 175 (58%) appointments were classified as having a biomedical communication pattern, and 125 (42%) were classified as having a biolifestyle-social communication pattern. None were classified as having a consumerist communication pattern. Twentythree (46%) veterinarians were classified as using a predominantly biomedical communication pattern, 19 (38%) were classified as using a mixed communication pattern, and 8 (16%) were classified as using a predominantly biolifestyle-social communication pattern. Pattern use was related to the type of appointment. Overall, 103 (69%) wellness appointments were classified as biolifestyle-social and 127 (85%) problem appointments were classified as biomedical. Appointments with a biomedical communication pattern (mean, 11.98 minutes) were significantly longer than appointments with a biolifestyle-social communication pattern (10.43 minutes). Median relationship-centered care score (ie, the ratio of client-centered talk to veterinarian-centered talk) was significantly higher during appointments with a biolifestyle-social communication pattern (1.10) than during appointments with a biomedical communication pattern (0.40). CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that veterinarians in companion animal practice use 2 distinct patterns of communication. Communication pattern was associated with duration of visit, type of appointment, and relationship-centeredness. Recognition of these communication patterns has implications for veterinary training and client and patient outcomes.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.502
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it