Incorporating video telehealth for improving at-home management of chronic health conditions in cats: a focus on chronic mobility problems
Bibliographic record
Abstract
Introduction Feline degenerative joint disease (DJD), commonly referred to as feline arthritis, is one of the most prevalent chronic health conditions in companion cats. DJD results in chronic mobility-related pain and difficulties that require long-term at-home management by the caregiver. Common mitigation strategies include pain control and client education about in-home modifications to make the living environment more comfortable. Cats with chronic mobility problems should receive regular veterinary appointments to monitor the cat’s condition; however, it is well recognized that many caregivers do not bring their cat to see a veterinarian on a routine basis. A possible solution to reducing accessibility barriers, improving compliance, and increasing access to pet education is veterinary video telehealth. Methods The current study used video visits to assess the impact of telehealth on caregiver education and home care of cats living with chronic mobility difficulties. US and Canadian caregivers of companion cats with chronic mobility difficulties or arthritis (N = 106) filled out a recruitment survey and then two study questionnaires approximately four months apart. The study questionnaires included questions regarding their cat’s mobility, their attitudes toward using video telehealth, and preference for video telehealth or in-person visits for various veterinary appointment types. Participants were randomly allocated to a treatment (n = 63; 6 video visits every 3 weeks over approximately 4 months) or a control (n = 43; no video visits) group. Results and discussion Overall, the results suggest caregivers were interested in and preferred video telehealth appointments to assist with managing their cat’s chronic mobility challenges. In addition, undergoing the synchronous video telehealth appointments increased participant knowledge of their cat’s mobility challenges and perceived helpfulness of their at-home management strategies. This suggests that from the caregiver’s perspective, the video telehealth appointments were beneficial for both themselves and their cat. There was also evidence that caregivers whose cats were more mobility impaired (higher Feline Musculoskeletal Pain Index – short form score) were associated with increased interest in using veterinary telehealth for at-home management of their cat. Further research should assess the impact of common environmental modifications implemented to improve cat comfort, on health and behavior outcomes for cats living with chronic mobility problems.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".