An Examination of the Relations between Social Support, Anthropomorphism and Stress Among Dog Owners
Bibliographic record
Abstract
Although it is well documented that pet ownership has a number of benefits, the psychological characteristics of the pet–owner relationship that may affect human subjective well-being are not well understood. The purpose of the present study was to examine the relations between owners' perceived social support from their dog, anthropomorphism, and stress. Although studies have found that owning a pet is linked to stress reduction, this research has not examined whether engaging in anthropomorphism of dogs influences pet owners' stress levels. We hypothesized that, if dog owners are receiving social support through anthropomorphism of their pets, it is likely to lead to a reduction in stress. One hundred and seven dog owners completed a questionnaire package which included an Anthropomorphism Scale, the Perceived Stress Scale and the Multidimensional Scale of Perceived Social Support. Correlations revealed that pet owners who perceived themselves as having low levels of social support were more likely to engage in high levels of anthropomorphic behavior (r = −0.21, df = 91, p < 0.05, one-tailed). However, our results also revealed an unexpected, small positive relation between anthropomorphic behavior and stress (r = 0.17, df = 92, p < 0.05, one-tailed). Explanations for the potential role of anthropomorphism as a coping mechanism to enhance social support are provided.
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.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".