Effect of Human Attachment Style on Horse Behaviour and Physiology during Equine-Assisted Activities–A Pilot Study
Bibliographic record
Abstract
Equine-assisted activities (EAA) for human well-being and health rely on human-horse interactions for therapeutic effect. At-risk participants with mental and emotional difficulties can show poor social skills and functioning relationships, potentially leading to unsuccessful human-horse interaction in EAA. This study addresses the effect of the attachment style (AS) of at-risk adolescents on horse physiology and behaviour during an equine-facilitated learning (EFL) program. Thirty-three adolescents participated in a 10-week EFL program with nine therapy horses (the same therapy horse per adolescent throughout the program). Adolescent AS was categorized into secure (n = 7), preoccupied (n = 11), dismissing (n = 1), or fearful (n = 12) using an Experiences in Close Relationships - Relationship Structure questionnaire. Horse heart rate (HR) and behaviour (affiliative and avoidance behaviours) in response to adolescents were recorded during grooming and riding. Over time, horses with fearful AS adolescents showed consistently more affiliative behaviours compared to those with preoccupied AS adolescents during grooming, and more constant HR and avoidance behaviours compared to those with secure AS adolescents during riding. These results suggest that a more predictable and less stressful physiological and behavioural response of therapy horses toward participants in EAA with emotional and behavioural difficulties can be mediated by a human insecure attachment style.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".