Stress Management Interventions for Veterinary Students
Bibliographic record
Abstract
Two-hundred-and-eighty-nine veterinary students from all four years of the University of Tennessee, College of Veterinary Medicine (UTCVM) were invited to complete the Derogatis Stress Profile (DSP)1 and an original Demographic Data Profile (DDP). The DSP assessed the students' current experiences of perceived stress, and the DDP was designed to gather information about students' academic year, their living situations, their financial situations, their interest area within the veterinary medical profession, and their current methods of coping with stress. These data were gathered as a baseline measure of veterinary medical students' perceived level of stress and quality of life. In an earlier study, data were also collected from faculty and staff about the perceived quality of the climate and culture of the veterinary college. The results of the DSP and DDP suggest that, although veterinary students at UTCVM do not experience significant levels of stress overall, they do report higher levels of subjective stress, time pressure, and depression than the general population. The more companion animals that veterinary students cared for in their personal lives, the more likely they were to report higher levels of perceived stress. Lastly, there were significant differences between genders, with female veterinary students reporting higher levels of perceived stress than their male counterparts. The preliminary results of the climate and culture data suggest that faculty and staff of the veterinary college individually feel that they are cared for in the work environment and collectively believe that the college strives for excellence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".