“He's opening everybody's heart up”: Co-creating pet therapy activities with inpatients at a large urban mental health and addictions hospital
Bibliographic record
Abstract
Background Animal-Assisted Activities (AAA) is now ubiquitous in many health care settings around the world. There is growing evidence about AAA's benefits but there is no literature about the inclusion of patients, the end-user, in the design and improvement of these programs. The aim of this study was to co-create AAA activities with inpatients to make their hospital experience in the psychiatric milieu more humanizing. Methods Informed by the principles of Participatory Action Research, we conducted seven focus group discussions with 38 participants in seven different inpatient units at a large urban mental health and additions hospital. In these discussions we asked participants what made pet therapy meaningful for them, the activities they enjoyed, what kind of activities they would like to see more of, and if they had experienced any barriers to their participation in this voluntary, recreational program. Results Our results show that AAA has four entangled elements: the bidirectional relationship between participant and therapy dog; the capacity of therapy dogs to generate social interactions, a tension between structured and unstructured activities with animals; and therapy dogs as a vector for a deeper relationship with nature. Conclusion Intentional patient-derived changes to AAA programs would amplify their impact for inpatients in psychiatric care. Providing both human (e.g., clinical support) and non-human (e.g., dog treats) would support patients in their desire to develop deeper relationships with their animal companions. Further, while most research to date emphasizes the therapeutic benefits of AAA, our results demonstrate that animal-led activities that result in positive social interactions with others (including non-human animals) were the most meaningful to participants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".