Barriers to Care in Veterinary Services: Lessons Learned From Low-Income Pet Guardians' Experiences at Private Clinics and Hospitals During COVID-19
Bibliographic record
Abstract
This qualitative study aimed to explore the experiences of low-income pet guardians in accessing veterinary care during COVID-19. Participants were recruited through a purposive sampling method: 12 individuals who applied to and met the low-income threshold to access support for veterinary fees from the Vancouver Humane Society (VHS) were invited for semi-structured in-depth telephone interviews. Participants indicated that they experienced pandemic-related barriers related to and compounded by their low-income status. Their experiences fit into three categories: the barriers to accessing veterinary care pre-and peri-COVID-19, the emotional impact of compounding barriers related to accessing veterinary care during COVID-19, and the human-animal bond and resilience in the context of COVID-19. Drawing on the One Health, One Welfare approach, we argue that veterinary and animal services should evaluate and improve their support services, particularly programs developed for low-income pet guardians. Based on the participants' recommendations, we propose that veterinary and animal services prepare for future disaster situations by increasing their financial capacity to support people needing assistance, undergoing training to better work with people experiencing financial and emotional stress, and providing easily accessible resources to better distribute knowledge about animal needs and available financial assistance programming. The suggestions are intended to benefit animals, their guardians, and both veterinary and animal service sector workers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".