Outreach Medicine as an Experiential Teaching Tool to Improve Veterinary Student and Client Education
Bibliographic record
Abstract
Outreach medicine is used to improve students' medical, technical, behavioral, and communication training among health professional schools; it is also used in veterinary schools, but little has been described on its educational impacts among pre-clinical veterinary students. Aiming to train practice-ready graduates, we established a monthly nonprofit vaccine clinic serving low-income clients to provide pre-clinical veterinary students with a realistic experiential learning environment. We developed surveys to assess the educational impacts of outreach medicine on pre-clinical veterinary student and client education. We received 101 student surveys, 26 educator (i.e., veterinarians and registered veterinary technicians) surveys, and 96 client surveys. Veterinarians, students, and technicians reported that students improved in important veterinary skills such as client communication, subcutaneous injection, patient handling, and physical examination. They also reported improved confidence in students' clinical decision making. Veterinarians valued the vaccine clinic as a favorable educational tool to teach behavior assessment and low-stress handling, and they highlighted that experiential learning via the vaccine clinic provided students with a clinical experience representative of most veterinarian practices (i.e., small animal general practitioner). Clients reported that the clinic's students and veterinarians greatly improved their knowledge of their pets' care and vaccines-notably, their knowledge of rabies and leptospirosis improved. Outreach medicine in the form of a vaccine clinic creates valuable experiential learning opportunities that increase veterinary student preparedness and complement didactic, laboratory, and case-based teaching.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".