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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".