Understanding Incoming Canadian and US Veterinary Students’ Attitudes and Perceptions of Their Dietary Habits and Levels of Physical Activity
Bibliographic record
Abstract
As critical components of individual well-being, nutrition and physical activity have important physical and psychological implications. Veterinary students face demanding schedules and potentially high rates of psychological distress. Though veterinary students’ strategies for healthy eating have been explored, factors influencing their ability to achieve a healthy diet are less understood. This study assesses incoming veterinary students’ perceived attitudes to their dietary habits and physical activity levels. Incoming students ( n = 322) at five Canadian and five randomly selected US veterinary schools completed a questionnaire inquiring about demographic information, dietary attitudes and habits, and activity levels. More than half (58%) of students perceived their diet to be moderately healthy. A desire to feel better and have more energy was the most reported (79%) motivating factor to modifying personal eating habits and was significantly associated with improved odds of having a perceived healthy diet ( OR = 2.22, p < .024). A busy lifestyle was perceived as a barrier to changing current eating habits by 92% of respondents. Students reporting a desire to maintain their health ( OR = 3.42, p < .001) and moderate ( OR = 2.81, p < .003) or high ( OR = 2.30, p < .044) routine physical activity levels were also more likely to perceive their diet as healthy. Findings show that incoming veterinary students’ perceptions may influence their goals of achieving a healthy lifestyle. An understanding of incoming veterinary students’ barriers and motivators could be applied in future research to assist students in achieving personalized goals.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".