Dog and cat owners’ use of online Facebook groups for pet health information
Bibliographic record
Abstract
BACKGROUND: Facebook is a frequently used social media platform and is often used for human health information, yet little research has been conducted on how pet owners use Facebook pet groups to obtain and share pet health information. METHOD: This study was designed to assess how pet owners use dog and cat Facebook groups to provide and receive pet health advice and their perception of these groups' trustworthiness. Two comparable questionnaires (dog and cat owners) were developed and distributed through an online survey platform. RESULTS: Results suggest that Facebook groups are a common source of pet health information, with 56.2% of dog owners and 51.8% of cat owners reporting receiving health information through Facebook groups. Similar numbers report giving health information through Facebook groups: 55.0% of dog owners and 57.9% of cat owners. Dog health information most commonly exchanged related to dermatology, gastroenterology and orthopaedics and the most common cat health information focused on gastroenterology, renal and urinary-related issues. While the majority of Facebook users report feeling that Facebook groups are not a trustworthy source of pet health information, a substantial minority of users do appear to be influenced by these groups. CONCLUSION: Approximately 50% of cat and dog owning respondents either give or receive pet health advice through Facebook groups. These results suggest that many owners deem Facebook groups as useful, but not entirely trustworthy, sources of information.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".