A Systematic Review of Mental Health–Improving Interventions in Veterinary Students
Bibliographic record
Abstract
Literature over the past 5 years has demonstrated that veterinary students globally are experiencing poor mental health. This has detrimental consequences for their emotional well-being and physical health, as well as implications for their future careers. Considering this issue, a systematic review was devised to investigate what interventions were being used, and what effect they had, in veterinary students. The review process involved a search of five databases, from which 161 records were retrieved. Following this, the screening process revealed seven articles eligible for appraisal. These studies investigated seven different interventions, six being cohort-level workshops/courses and one being a collation of several individual strategies. All seven studies reported that the interventions were effective to some degree in improving the mental health of their participants. However, the lack of repeat interventions and control groups limited the external validity of each intervention. A comparison to the research in medical students is briefly discussed. Three of the appraised articles were recommended for further investigation.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".