Jog with your dog: Dog owner exercise routines predict dog exercise routines and perception of ideal body weight
Bibliographic record
Abstract
Canine obesity is becoming an increasingly prevalent concern among companion animal veterinarians and professionals alike. A number of sociodemographic, dietary, and exercise related variables have been shown to be predictive of a dog's bodyweight, however, all previous surveys designed to address these variables have been focussed on only one area of the world at a time. The objective of this survey was to investigate how an owner's exercise routine influences their dog's exercise routine and which of the owner's dietary and exercise habits influence their perception of their dog's body weight. The survey included respondents across France, Germany, the United Kingdom, Canada and the United States. The survey was distributed online via Qualtrics (Qualtrics XM, Utah, USA) and a total of 3,298 responses were collected, equally distributed across country and between sexes. Comparison of column proportions and multinomial logistic regression were performed in SPSS Statistics (Version 26, IBM Corp, North Castle, New York, USA). Respondents from Germany were more likely to exercise their dog for a longer amount of time, rank the importance of exercise as extremely important, report that their dog is an ideal body weight, and were less likely to report that someone (including a veterinarian) had told them their dog was overweight. Results from linear regression revealed that those who had been told their dog was overweight, those who restrict their dog's food intake to control weight, those who select a weight control diet and those who give their dog more other foods (treats, table scraps, fruits/vegetables) on a daily basis were all less likely to believe that their dog is an ideal body weight. In contrast, only those who reported doing more vigorous exercise themselves or those who reported that their dog performs vigorous exercise were more likely to believe that their dog is an ideal body weight. The results highlight owner's perceptions of healthy weight and the role of nutrition and exercise. Owner's intentions and attitudes towards the value of exercise and promoting an ideal body weight in their dog should be explored, but may require a One Health approach to ensure successful weight management among both dogs and their owners.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".