Psychophysiological effects of equine-facilitated psychotherapy on Veterans with PTSD and their horse partners
Bibliographic record
Abstract
Introduction: Animal-assisted therapies (AATs) are used to promote the mental and physical health of humans. Research using subjective assessments of psychotherapy incorporating horses (known as equine-facilitated psychotherapy, or EFP) for Veterans with posttraumatic stress disorder (PTSD) demonstrated positive effects on PTSD and comorbidities. Although EFP appears to positively influence human mental health, published physiological data are lacking, and little is known about the horses' responses. Methods: To determine the efficacy of EFP with Veterans with PTSD and the effect on horses through measurements of human-horse dyads, a prospective cohort design was used consisting of four eight-week EFP interventions for Veterans with PTSD. Changes in stress hormones and heart rate variability (HRV) in humans and horses, along with PTSD symptoms in humans and behavioural responses in horses, were recorded. Results: In humans, average daily measures of cortisol decreased and average daily oxytocin concentrations increased after each session. Additionally, daily self-reports of mood, anxiety, and well-being improved after each session. The Sympathetic Nervous System Index increased and Parasympathetic Nervous System Index decreased after daily sessions. Horses showed no significant difference in HRV, oxytocin, or observed stress behaviors. However, a significant decrease was observed in cortisol from pre- to post-session. Discussion: These findings indicate that EFP had psychological and physiological benefits for individuals with PTSD with no concomitant negative physiological effect on the welfare of horses. Biological metrics combined with human psychological and equine behavioural measures enhance understanding of the effect of EFP on the dyad participants.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".