Prevalence and Correlates of Dog Walking Among Japanese 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
BACKGROUND: Exploring the detailed pattern and correlates of dog walking is crucial to designing effective interventions to increase the proportion of dog walkers. The current study examined the prevalence and pattern of dog walking, the association between dog walking and health-related physical activity, and the correlates of dog walking among dog owners in Japan. METHODS: Japanese dog owners' (n=930) responses to an Internet-based cross-sectional survey were analyzed. A self-reported measure of physical activity, dog walking characteristics, and sociodemographic and dog-specific variables were obtained. Analyses of covariance and multivariate logistic regressions were used. RESULTS: Overall, 64.4% of the surveyed dog owners walked their dogs. On an average, they walked their dogs 214.1±189.5 minutes per week. The dog walkers were 3.47 times more likely to meet physical activity recommendations, were significantly less likely to be unmarried (OR=0.61), and had higher levels of attachment with their dogs (OR=2.32) than the nondog walkers. CONCLUSION: The findings confirmed that dog walking significantly helps dog owners meet physical activity recommendations for health and revealed that dog-specific factors such as dog attachment might be stronger correlates of dog walking than sociodemographic factors.
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) | 0.000 | 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 | 0.000 |
| 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