The Healer's Art (HART): Veterinary Students Connecting with Self, Peers, and the Profession
Bibliographic record
Abstract
This case study sought to understand veterinary students' perceptions and experiences of the Healer's Art (HART) elective to support well-being and resilience. Students' "mindful attention" was assessed using the MAAS-State scale. Course evaluations and written materials for course exercises (artifacts) across the 2012-2015 cohorts of Colorado State University's HART veterinary students (n=99) were analyzed for themes using a grounded theory approach, followed by thematic comparison with analyses of HART medical student participants. HART veterinary students described identity/self-expression and spontaneity/freedom as being unwelcome in the veterinary curriculum, whereas HART medical students described spirituality as unwelcome. HART veterinary students identified issues of "competition" and "having no time," which were at odds with their descriptions of not competing and having the time to connect with self and peers within their HART small groups. HART veterinary students shared that the course practices of nonjudgment, generous listening, and presence (i.e., mindfulness practices) helped them build relationships with peers. Although not statistically significant, MAAS pre-/post-scores trended in the positive direction. HART provides opportunities for students to connect with self and foster bonds with peers and the profession, factors that are positively associated with resilience and wellness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".