Relationships among owner consideration of euthanasia, caregiver burden, and treatment satisfaction in canine osteoarthritis
Bibliographic record
Abstract
Although diagnosis of osteoarthritis (OA) has been recently linked to euthanasia in dogs, no prior work has examined the roles of caregiver burden or treatment satisfaction in this relationship. We expected that there would be an indirect effect of caregiver burden on the association between consideration of euthanasia and clinical signs of OA, but that this effect would be influenced by owner satisfaction. Cross-sectional online evaluations were completed by 277 owners of dogs with OA recruited through social media. Canine OA-related pain and functional impairment, owner consideration of euthanasia, caregiver burden, and satisfaction were examined. Relationships among OA-related pain and functional impairment, owner consideration of euthanasia, caregiver burden, and satisfaction were statistically significant (P 0.01 for all). Cross-sectional mediation analysis demonstrated a statistically significant indirect effect of caregiver burden on the relationship between consideration of euthanasia and OA-related clinical signs (bias-corrected 95% confidence interval [BC 95% CI], 0.001-0.009), which was significantly moderated by owner satisfaction (BC 95% CI, -0.003 to -0.0002). Findings align with prior work connecting canine OA to euthanasia. The current study extends past research to demonstrate that caregiver burden in the owner may be partially responsible for this relationship. The moderating role of owner satisfaction suggests that optimizing owner impressions of treatment and the veterinary team could attenuate these relationships, potentially decreasing the likelihood of premature euthanasia for dogs with OA.
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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 | 0.004 | 0.015 |
| 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 | 0.001 | 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".