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Record W3168352504 · doi:10.3138/jvme-2020-0133

A Scalable and Effective Course Design for Teaching Competency-Based Euthanasia Communication Skills in Veterinary Curricula

2021· article· en· W3168352504 on OpenAlexvenueno aff
Mei A. Schultz, James K. Morrisey, Leni K. Kaplan, J Colon, Dani G. McVety-Leinen, Ariana L. Hinckley-Boltax

Bibliographic record

VenueJournal of Veterinary Medical Education · 2021
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumCommunication skillsMedical educationPsychological interventionVeterinary medicineMedicineSkills managementVeterinary educationPsychologyNursingPedagogy

Abstract

fetched live from OpenAlex

Veterinary staff must be able to navigate end-of-life care with sensitivity and skill to create the best possible outcome for the patient, client, and veterinary team collectively. Despite the clear importance of euthanasia communication and procedural skills in veterinary practice, recent graduates of veterinary programs identified gaps between skills deemed important in clinical practice and skills emphasized in the curriculum. Little time is allocated to euthanasia procedural or communication training across the board in US veterinary programs. Thus, it is of paramount importance to establish intentional and well-designed instruction and assessment of euthanasia communication skills for veterinary trainees. A course on veterinary euthanasia communication skills was designed to emphasize themes and topics essential for a competent veterinarian. Through course evaluations, students expressed the sentiments that this course improved their euthanasia communication skills, that euthanasia communication skills are essential for their careers, and that the course content should be integrated into the core curriculum. This article presents a scaffold for the instruction and assessment of veterinary euthanasia communication skills in alignment with a competency-based veterinary education (CBVE) framework and outlines specific learning interventions used in the course that are scalable and may be extracted and incorporated into existing courses.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.203
GPT teacher head0.530
Teacher spread0.327 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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