Changes in Affective and Cognitive Empathy among Veterinary Practitioners
Bibliographic record
Abstract
Clinical empathy is a multi-dimensional concept characterized by four dimensions: (1) affective-the ability to experience patients' or clients' emotions and perspectives, (2) moral-the internal motivation to empathize, (3) cognitive-the intellectual ability to identify and comprehend others' perspective and emotions, and (4) behavioral-the ability to convey understanding of those emotions and perspectives back to the patient or client. The Davis Interpersonal Reactivity Index (IRI) was used to examine the affective and cognitive facets of empathy in veterinary practitioners. The IRI consists of four subscales that measure cognitive (perspective taking and fantasy) and affective (emphatic concern and personal distress) components of empathy. Data from a cross-sectional sample of practicing veterinarians (n=434) were collected. Veterinarians' fantasy scores were lowest for those with the most clinical experience. Personal distress scores were highest among new veterinarians and lowest for those with 26 or more years in practice. High levels of personal distress in the early years of practice are concerning for the professional wellness of veterinarians. To combat this trend, the implementation of resilience-building interventions should be considered to support veterinary practitioners.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".