How Animal-Assisted Therapy Is Understood and Perceived by Health Care Providers and the General Public in Canada
Bibliographic record
Abstract
The incorporation of dogs to assist humans with various activities has been documented for centuries. When a dog is included in treatment to meet an individual’s therapeutic goal it is known as Animal-Assisted Therapy (AAT). Little is known about how AAT is understood and perceived among healthcare professional and public populations in Canada. Although AAT has increased in popularly, limited research exists regarding its efficacy. Further, variation exists in the understanding and perceptions of AAT among the general pubic and healthcare professionals, possibly due to a lack of awareness of existing operational definitions and distinctions between classifications of “assistance animals.” According to the diffusion of innovation theory an innovation, defined as a new idea or practice, must be properly communicated to all appropriate channels before it may be adopted into practice. Thus, misunderstandings about AAT pose a barrier for future research and adoption of an intervention. This may further inhibit the success of AAT as an intervention, as both administrator and recipient’s attitudes and knowledge of a treatment may impact the treatment’s success. In the present study, health care professionals and the general public in Canada were surveyed regarding their knowledge of AAT, their attitude toward AAT, and their interest in learning more about AAT. Further, attitude toward dogs, openness to experience, agreeableness, and subjective distress were investigated for their influence on attitude toward AAT. Results suggest that both professional and public populations have limited knowledge of AAT and are interested in learning more about the intervention, yet are hesitant to recommend, administer, or receive the intervention without further information. Although attitude toward dogs appears to be positively associated with attitude toward AAT, the impact of openness to experience, agreeableness, and subjective distress is limited. Limitations and future directions are discussed.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".