Companion Animal Fostering as Health Promotion: A Literature Review
Bibliographic record
Abstract
There is growing interest in the health-promoting potential of human-companion animal relationships from a broad public health perspective while acknowledging barriers to ownership, particularly for older adults. Companion animal fostering is an alternative to pet ownership that aligns with the Ottawa Charter health promotion principle that caring for others in everyday settings promotes health. This narrative review of the literature on companion animal fostering draws on Te Whare Tapa Whā (the four-sided house), an indigenous model of health that is influential in Aotearoa/New Zealand, and the Ottawa Charter. We found that companion animal fostering can be considered health-promoting for human and non-human animals, using a broad and multidimensional understanding of health. As well as improving the long-term outcomes for homeless animals, companion animal fostering has the potential to promote the health of the individuals, families, and communities who provide foster homes. Our review highlights the importance of health promoters considering the reciprocal relationship between human and animal health. Future research should explore different aspects of human and non-human health, perspectives of different types of fosterers in different settings and communities, barriers to fostering, and methods that explore the role of caring for a wider range of companion animals in creating and sustaining wellbeing.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".