Mind Full or Mindful? A cohort student of Equine-Facilitated Therapy for Women Veterans
Bibliographic record
Abstract
Abstract Background: The purpose of the evaluation was to understand, through participant self-report, the assets and challenges of partnering with equines for female Veterans seeking to increase skills in their mindfulness practice. Methods: Surveys were administered to participants to gain insight into self-identified mindfulness pre- and post-equine intervention. All measures were anonymous with only the date included to indicate the cohort. The study included three measures post-consent: The Toronto Mindfulness Scale, the Mindfulness Scale, and the Program Evaluation. Results: The Mindfulness Survey responses were averaged for pre- intervention, then for post- intervention. The pre- intervention survey responses ranged from 2.3 to 6.5 with a response range of 0 to 10 (M=4.59, SD=1.29). The post- intervention survey responses ranged from 6.7 to 9.2 (M=8.2, SD=0.69). A paired sample t-test found a significant difference in the scores from pre- intervention to post- intervention conditions (t=-9.43, df=13, p<.001). In the evaluations, participants shared that their favorite moments were (Q3): grooming and Breathe With (an activity to match breathing to the horse’s breathing). In the question asking what the participants will take away from the program (Q9) one participant shared, “The horses have taught me a lot about myself”; a common theme across respondents. Conclusion: The current study demonstrates that Veterans’ interactions with equines impacts the participants’ mindfulness throughout their experiences at Fieldstone Farm. The Veterans established a significant increase in their mindfulness scores post-equine intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".