A Quantitative Study of Occupational Stress in Animal Shelter Workers
Bibliographic record
Abstract
Animal shelter workers are a unique cohort of care workers who have been shown to have high levels of burnout, compassion fatigue, and occupational stress. The full extent of the burden of this type of work is still being discovered. We deployed an online survey (n = 113) which included a novel occupational stress questionnaire and established mental health measures to evaluate levels of compassion fatigue, potential for moral injury, anxiety, and depression in animal shelter workers. Specific variables of interest were type of worker (full/part- time/volunteer), reason for euthanasia (medical vs. non-medical), and level of training. Results reveal only a small percentage of shelters did not practice any form of euthanasia (9%). Overall, respondents exceeded normative levels of burnout, compassion fatigue/secondary trauma, depression, and anxiety. Shelter work was shown to place respondents at a higher-than-average risk of moral injury, which was found to be significantly correlated with depression, anxiety, and compassion fatigue, and inversely related to optimism. Moral injury was higher for shelter workers whose work included euthanasia for non-medical reasons. Euthanasia for non-medical reasons and having formal animal care training, however, were not associated with significant increases in depression, compassion fatigue, or optimism. Full-time workers were found to have significantly higher levels of anxiety, depression, and risk of moral injury than part-time workers and volunteers. A factor analysis of the 43 workplace stressors included in the novel occupational stressor questionnaire revealed four distinct dimensions: 1) involvement in policy and decision-making, 2) public perceptions and stigma, 3) staff and the environment, and 4) job rigidity and social support. Of these scales, job rigidity and social support were found to have the greatest impact on burnout, depression, anxiety, optimism, and compassion fatigue/secondary trauma. Involvement in policy and decision-making had the greatest impact on moral injury. It is clear from our findings that the mental health burden of caring for shelter animals is great. Our findings add four distinct areas of focus that policy and decision-makers may consider to improve the wellbeing of animal shelter workers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".