Effects of a Veterinary Student Leadership Program on Measures of Stress and Academic Performance
Bibliographic record
Abstract
Assuming leadership roles in veterinary student governance or club activities could be considered an added stressor for students because of the impact on time available for personal and academic activities. The study reported here evaluated the effects of participation in a leadership program and leadership activity across two classes of veterinary students on measures of stress, using the Derogatis Stress Profile (DSP), and on veterinary school academic performance, measured as annual grade-point average (GPA) over a three-year period. Program participants and their classmates completed the DSP three times across the first three years of veterinary school. On average, participating students reported self-declared stress levels that were higher and measured DSP stress levels that were lower than those of the general population. Students were more likely to assume elected or appointed leadership roles while in their first three years of the veterinary degree program if they participated in the optional leadership program and demonstrated lower stress in several dimensions. Some increased stress, as measured in some of the DSP stress dimensions, had a small but statistically significant influence on professional school GPA. The study determined that the most important predictors of students' cumulative GPA across the three-year period were the GPA from the last 45 credits of pre-veterinary coursework and their quantitative GRE scores. The results of the study indicate that neither participation in the leadership program nor taking on leadership roles within veterinary school appeared to influence veterinary school academic performance or to increase stress.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".