Human Enjoyment in Tactile Interaction With Horses and Dogs: A Comparative Study
Bibliographic record
Abstract
Animal-assisted interventions (AAIs) are increasingly integrated into human healthcare due to their positive effects on mental and physical health. This study examined the impact of touch interactions on human physiological and emotional responses in two experiments with 10 horses and 18 dogs involved in AAI. Human heart rate (HR), heart rate variability (HRV), and positive emotional responses (assessed by the Positive Affect Scale (PAS) survey with three categories: activated, relaxed, and safe) were measured. The horse experiment also assessed how human experience with horses influenced these responses. Forty-nine participants interacted individually with horses, and 44 interacted individually with dogs under two conditions: forced touch (animals were restricted and required to interact) and consensual touch (animals were free to choose interaction). Human HR and HRV were recorded via heart rate monitors, and participants completed PAS surveys immediately after each interaction. Statistical analysis used a GLIMMIX model with repeated measures, and Pearson correlations examined human–horse HR relationships. During forced touch with horses, human HR was higher (p = 0.0001) and HRV lower (p = 0.0065) than during consensual touch. Experience with horses did not affect human HR (p = 0.3043) or HRV (p = 0.1366) but influenced PAS scores: the more experienced participants felt less "activated" (p = 0.0058) and the more "relaxed" (p = 0.0275) and "safe" (p = 0.0343). No significant correlation was found between human and horse HR (r = 0.09). In the dog study, touch treatment did not affect human HR (p = 0.2513), HRV (p = 0.1691), or PAS scores (all p > 0.0953). Descriptive results indicated that participants perceived dog interactions more positively than horse interactions. These findings suggest that allowing animals, especially horses, a choice to interact may reduce human physiological arousal during AAIs, with species-specific effects warranting further study.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".