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Record W2988394292 · doi:10.3138/jvme.1018-124r1

Implications of a Novel Method for Analyzing Communication in Routine Veterinary Patient Visits for Veterinary Research and Training

2019· article· en· W2988394292 on OpenAlexvenueno aff
Michael P. McDermott, Malcolm Cobb, Iain Robbé, Rachel Dean

Bibliographic record

VenueJournal of Veterinary Medical Education · 2019
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingMedicinePerspective (graphical)Simulated patientFamily medicineNursingVeterinary medicineMedical educationPsychologyComputer science

Abstract

fetched live from OpenAlex

The patient-centered clinical method (PCCM), a model developed to characterize communication during patient-physician visits in the 1980s, identifies elements of patient-orientated, physician-orientated, and shared dialogue during the encounter. The model also includes elements that reflect the emotional aspects of these interactions, recognizing expressions of feelings and exchanges related to both personal and medical interests. Fifty-five routine veterinary patient visits in the United Kingdom and United States were analyzed using the novel application of a PCCM adapted for veterinary patient visits. The patient visits were video recorded, transcribed, coded, and analyzed for frequency and proportion of PCCM elements observed. Elements representing the greatest proportion of patient visits were related to gathering information and shared decision making. Those representing the smallest proportion were related to signs of the presenting condition and effects of the condition on the clients' lives. Dialogue during the patient visits flowed iteratively and back and forth between the veterinarian and the client perspective. The findings suggest that patient visits are focused more on gathering information and planning rather than exploring effects of the health problem on the client's life, and that patient visits flow very iteratively and randomly between veterinarian and client perspectives. Both of these topics should be studied further and given emphasis in the way that communication models are developed and taught in order to enhance client-centeredness in veterinary patient visits.

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 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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.701
GPT teacher head0.655
Teacher spread0.047 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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