Unconventional diets and nutritional supplements are more common in dogs with cancer compared to healthy dogs: An online global survey of 345 dog owners
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This survey aimed to investigate and compare diet type and supplement use between dogs (Canis lupus familiaris, L.) with cancer and a population of owner-reported healthy dogs and to assess the sources of information dog owners consult. Respondents were mainly from English-speaking countries. Dogs were considered healthy (N = 213) if owners reported them to be in good health. Dogs were included in the cancer group (N = 132) if the owner reported that their dog had been diagnosed with cancer. An online survey was distributed to clients presenting to a tertiary oncology service, clients presenting to a local primary care veterinary practice, and through social media. Owners of dogs with cancer spent more time researching pet health (P < .001), pet nutrition (P < .01) and nutritional supplements (P < .001) than owners of healthy dogs. While veterinarians were most commonly reported to be an information source for both groups, owners of healthy dogs more likely consulted pet stores and owners of dogs with cancer tended more to social media groups and blogs. Healthy dogs were more likely fed commercial dry food (P < .001), whereas homemade cooked (P < .001) and raw diets (P < .05) were more prevalent among dogs with cancer. Supplement use, especially cannabidiol products, mushroom extracts or turmeric/curcumin, was also more common for this group (P < .001). Alternative diets and supplements were more popular among owners of dogs with cancer compared to owners of healthy dogs. These findings highlight the need for nutritional counselling and education of pet owners regarding nutrition-related topics, especially when their dog is diagnosed with cancer.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it