The impact of the COVID-19 pandemic on a cohort of Labrador retrievers in England
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic is likely to have affected the welfare and health of dogs due to surges in adoptions and purchases, changes in the physical and mental health and financial status of dog owners, changes in dogs' lifestyle and routines and limited access to veterinary care. The aims of this study were to investigate whether COVID-19 restrictions were associated with differences in Labrador retrievers' lifestyle, routine care, insurance status, illness incidence or veterinary attendance with an illness, who were living in England and enrolled in Dogslife, an owner-based cohort study. Longitudinal questionnaire data from Dogslife that was relevant to the dates between the 23rd of March and the 4th of July 2020, during COVID-19 restrictions in England, were compared to data between the same dates in previous years from 2011 to 2019 using mixed regression models and adjusted chi-squared tests. RESULTS: Compared with previous years (March 23rd to July 4th, 2010 to 2019), the COVID-19 restrictions study period (March 23rd to July 4th 2020) was associated with owners reporting increases in their dogs' exercise and worming and decreases in insurance, titbit-feeding and vaccination. Odds of owners reporting that their dogs had an episode of coughing (0.20, 95% CI: 0.04-0.92) and that they took their dogs to a veterinarian with an episode of any illness (0.58, 95% CI: 0.45-0.76) were lower during the COVID-19 restrictions compared to before. During the restrictions period, owners were less likely to report that they took their dogs to a veterinarian with certain other illnesses, compared to before this period. CONCLUSIONS: Dogslife provided a unique opportunity to study prospective questionnaire data from owners already enrolled on a longitudinal cohort study. This approach minimised bias associated with recalling events prior to the pandemic and allowed a wider population of dogs to be studied than is available from primary care data. Distinctive insights into owners' decision making about their dogs' healthcare were offered. There are clear implications of the COVID-19 pandemic and associated restrictions for the lifestyle, care and health of dogs.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 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".