Vocation, Belongingness, and Balance: A Qualitative Study of Veterinary Student Well-Being
Bibliographic record
Abstract
An elevated risk for suicide among veterinarians has stimulated research into the mental health of the veterinary profession, and more recently attention has turned to the veterinary student population. This qualitative study sought to explore UK veterinary students' perceptions and experiences of university life, and to consider how these may affect well-being. Semi-structured interviews were conducted with 18 students from a single UK school who were purposively selected to include perspectives from male, female, graduate-entry, standard-entry (straight from high school), and widening participation students across all 5 years of the program. Three main themes were identified: a deep-rooted vocation, navigating belongingness, and finding balance. Participants described a long-standing goal of becoming a veterinarian, with a determination reflected by often circuitous routes to veterinary school and little or no consideration of alternatives. Although some had been motivated by a love of animals, others were intrinsically interested in the scientific and problem-solving challenges of veterinary medicine. Most expressed strong feelings of empathy with animal owners. The issue of belongingness was central to participants' experiences, with accounts reflecting their efforts to negotiate a sense of belongingness both in student and professional communities. Participants also frequently expressed a degree of acceptance of poor balance between work and relaxation, with indications of a belief that this imbalance could be rectified later. This study helps highlight future avenues for research and supports initiatives aiming to nurture a sense of collegiality among veterinary students as they progress through training and into the profession.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".