Dog and Guardian Relationships: Application of a Dual-Process Actor–“Partner” Interdependence Model to Predict Regular Walking
Bibliographic record
Abstract
Physical inactivity is a major global health risk, yet many fail to meet activity guidelines. Dog guardianship has been linked to increased physical activity, though the dog–guardian walking relationship remains understudied. This study applied the Actor–Partner Interdependence Model (APIM) to examine how guardians’ and dogs’ dual-process constructs influence walking behaviour. A sample of 127 Canadian dog guardians reported their walking habits, hedonic motivation, and expectations (Time 1) for themselves and their dogs, with follow-up walking behaviour assessed after three weeks (Time 2). Structural equation modelling revealed significant covariation in dog–guardian walking (r = 0.38, p = 0.03), supporting APIM. Guardians’ hedonic motivation (β = 0.37, p = 0.02) and expectations (β = 0.38, p = 0.02) predicted both human and dog walking. Findings confirm that guardians are the primary drivers of walking, suggesting interventions targeting guardian motivation and expectations may enhance physical activity in both humans and dogs, benefiting health.
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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 | 0.000 | 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 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".