Stressors Predicting Depression, Anxiety, and Stress in Korean Veterinary Students
Bibliographic record
Abstract
Psychological distress has a negative impact on professional development in health care professions. In this article, we measured the prevalence of students' depression, anxiety, and stress using the DASS-21 questionnaire in 10 veterinary colleges in Korea to investigate the stressors that contribute to these forms of psychological distress. The prevalence of academic and relationship types of stressors were higher than others. The proportion of students above a severe level of depression, anxiety, and stress on the DASS-21 scales was 30.9, 35.8, and 43.2%, respectively. The DASS-21 scores mediated the relationship between the perceived frequency of stressors and the respondents' satisfaction with their education and career. Statistical analysis revealed that female and pre-clinical students are more vulnerable to depression, anxiety, and stress. The findings of the article indicate the gravity of Korean veterinary students' mental and psychological state, emphasizing the importance of comprehensive management of students' mental health.
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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 | 0.000 | 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".