Translation and validation of the German version of the Pet-Related Stress Scale
Bibliographic record
Abstract
Background Pet-related stress refers to the stress of living with a pet. The aim of this study was to translate and validate the German version of the Pet-Related Stress Scale (PRSS-G). Moreover, reference values were determined. Methods Data for validation were gathered from a quota-based online sample of Germany’s adult population aged 18 to 74 years, with n = 3,270 representing the demographic distribution of Germany in terms of sex, age, and federal states. The data collection took place online in January 2025. Reliability was assessed, and confirmatory factor analysis was performed to evaluate construct validity. Concurrent validity was examined through pairwise correlations of PRSS-G with depressive symptoms, anxiety symptoms, perceived stress, life satisfaction and loneliness. Additionally, reference values were provided for key sociodemographic groups. Results Strong to excellent reliability was found for the PRSS-G, with Cronbach’s alpha of 0.96 overall and coefficients from 0.88 to 0.96 for the subscales. The mean pet-related stress score equaled 1.9 (SD: 0.8), with the highest levels among younger individuals, individuals with low education and individuals with a migration background. The original three-factor model (economic, psychological and social stress subscales) was confirmed in the present study. Higher pet-related stress was associated with more depressive symptoms (r = 0.50, p < 0.001), more anxiety symptoms (r = 0.48, p < 0.001), more perceived stress (r = 0.35, p < 0.001), lower life satisfaction (r = −0.13, p < 0.001) and higher loneliness (r = 0.30, p < 0.001). Conclusion The PRSS-G is a reliable and valid tool to measure pet-related stress levels among individuals speaking German. To facilitate comparisons across different countries, additional translation and validation studies are required.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".