Stress Levels and Stressors of Veterinary Students in Indonesia
Bibliographic record
Abstract
Despite the growing collection of scientific publications on student stress levels, stress experienced by veterinary students in Indonesia has been less investigated. This study assessed the stress levels of veterinary students and investigated the stressors faced by veterinary students in Indonesia, both in undergraduate and professional programs. The study participants were 165 veterinary students from all universities offering veterinary medicine in Indonesia. The Perceived Stress Scale was used to evaluate stress levels, and the modified Veterinary Medical Stressor Inventory was used to indicate several stressors in this study, including academic performance, clinical graduation, negative evaluation, and online classes experienced by veterinary students. The findings show that most veterinary students in Indonesia experienced moderate stress levels. Results also found that female students experienced higher levels of stress than their male counterparts. The multiple regression result shows that stressors belonging to the academic group were the most significant, primarily in undergraduate students. Aside from academics, the rigorous veterinary medicine curriculum, loneliness, and peer competition are the major potential stressors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".