Associations between the Psychological Characteristics of the Human–Dog Relationship and Oxytocin and Cortisol Levels
Bibliographic record
Abstract
The aim of the present study was to explore possible correlations between dog owners' relationships with their dogs, as measured with the Monash Dog Owner Relationship Scale (MDORS), and oxytocin and cortisol levels in both the owners and their dogs. Ten female owners of male Labrador Retrievers completed the MDORS. The scores obtained from the single items, subscales, and total score of the MDORS were calculated. Ten blood samples were collected from each dog owner and her dog during a 60-minute interaction. Blood samples were analyzed for oxytocin and cortisol by Enzyme Immuno Assay (EIA) and mean values of oxytocin and cortisol were calculated in both owners and dogs. The MDORS scores obtained were correlated with basal and mean oxytocin and cortisol levels. The correlation analysis revealed some relationships between the scores of items in the MDORS that reflect the character of the dog–owner-relationship and the owners' hormone levels. For example, higher oxytocin levels in the owners were associated with greater frequency in kissing their dogs (rs = 0.864, p = 0.001). Lower cortisol levels in the owners were associated with their perception that it will be more traumatic when their dog dies (rs = –0.730, p = 0.025). The correlation analysis also revealed some relationships between the scores of items in the MDORS and the dogs' hormone levels. For example, greater frequency in owners kissing their dogs was associated with higher oxytocin levels in the dogs (rs = 0.753, p = 0.029). Six items in the subscale Perceived Costs, as well as the subscale itself, correlated significantly with the dogs' oxytocin levels (rs = 0.820, p = 0.007), that is, the lower the perceived cost, the higher the dogs' oxytocin levels. In addition, significant correlations between the oxytocin levels of the owners and the dogs were demonstrated. Possible mechanisms behind these correlations are discussed. In conclusion, the scores of some items and the subscales of the MDORS correlated with oxytocin, and to a lesser extent cortisol, levels in both the owners and dogs.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".