Exploring the Experiences of Multiple Perspectives Within Equine-Assisted Programs Using Photovoice
Bibliographic record
Abstract
The purpose of this study was to explore the motivations and experiences of people who participated in various equine-assisted therapeutic programs. There is a need to broaden and explore the range of recreational services available to individuals with neurodevelopmental conditions and their families. The present study collaborated with TROtt, a therapeutic riding barn based in Ottawa, to collect data as a measure of their quality assurance. Participants of the current study included two instructors, one equine-assisted learning facilitator, two adult volunteers, one staff member, and one facilitator for an equine-assisted social group for young adults on the spectrum. The study used a qualitative method called Photovoice or photoelicitation, a non-invasive and participant forward way to capture participant perspectives. Participants took photos of various aspects of their equine-sessions including horses, barn equipment, and nature and then submitted those photos with a short accompanying narrative explaining the photo’s significance to their experience. Through a reflexive thematic coding analysis, results demonstrated that equine-based programs provided many benefits to participants including feelings of autonomy, opportunities to develop new skills, finding a sense of community, positive emotions, multisensory experiences, opportunities for non-verbal communication, and a calming environment. By moving towards a better understanding of motivations, preferences, and values that drive engagement in equine-based services, our work can allow for a more comprehensive knowledge of how to better structure and program recreational services to reach broader audiences.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".