Exploring the Link between Mindset and Psychological Well-Being among Veterinary Students
Bibliographic record
Abstract
This study set out to improve our understanding of potential pedagogical factors that may influence the mental health of veterinary students. Previous research has demonstrated that the type of feedback given to children by parents and teachers can strongly influence young people's beliefs in their ability to modify their intelligence-their "mindset." There is also evidence that we can change the mindset of students relating to their intelligence by changing the methods by which we teach and assess. We used a paper-based questionnaire to assess mindset and psychological well-being in veterinary students (n=148). We found an association linking students' mindset to their intelligence and their psychological well-being. Students who believed that their level of intelligence was fixed had significantly lower scores on five out of six areas of psychological well-being compared to students who believed that their intelligence was malleable. Giving process rather than person feedback and reducing assessment methods that encourage comparison with other students could increase the proportion of our students with a growth mindset and, if the association we identified is causal, improve their psychological well-being.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".