Investigating Factors Associated With Stress in Guardians of Dogs Under 12 Months of Age
Bibliographic record
Abstract
Similar to parenting, raising a puppy can be stressful for guardians; however, this aspect of the guardian experience has received limited research attention. This study sought to fill the gap in understanding the stress experienced by puppy guardians and shed light on the factors influencing stress levels. An online survey was developed for guardians of dogs under 12 months of age and made available worldwide. A validated instrument (Parental Stress Scale) was modified to suit “parenting” of dogs and used to measure guardian stress levels. Data from 783 valid responses were received. For the statistical model, we fitted a linear regression with a modified Parental Stress Scale as the single outcome variable. A full linear model was fitted with predictors with a p-value of 0.2 or less, and a backwards stepwise selection process was used to find the ideal model, using AIC as the heuristic. Guardians who were satisfied with their puppy’s behavior, lived in Australia (compared with those living in the USA and Canada), scored higher in self-esteem, were happy with the division of puppy responsibilities in their household, and were raising puppies scoring higher in trainability were all associated with lower Parental Stress Scale scores. In contrast, first-time puppy guardians, guardians who worked from home some or all of the time, guardians raising puppies scoring higher in extraversion or neuroticism, and guardians who agreed that managing more than one dog in the household took up a lot of their time and energy, were all associated with higher Parental Stress Scale Scores. Although not initially developed for puppy guardians, the modified Parental Stress Scale shows potential as a useful measure for future use in this population.
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 | 0.001 | 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) | 0.001 | 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".