Θεραπευτική επαφή με τα ζώα σε άτομα με καρκίνο (Animal-assisted Therapy – AAT)
Bibliographic record
Abstract
Introduction: Animal Assisted Therapy (AAT) is the planned inclusion of an animal in a patient's treatment program. It is an additional or alternative method and can be a group visit or an individual one. Initially it was used only for people with neurobiological disorders, but in recent years research has been carried out on its effects on various other conditions, as well as in people with cancer. So far, it has been shown that animal-assisted treatment can have quite beneficial effects on these individuals (with cancer). It can reduce stress, improve their emotional health and reduce the fatigue they feel. \nPurpose: The purpose of this bibliographic review is to review and provide scientific data on the effects that Animal-Assisted Therapy can have on people with cancer. \nMaterial and Method: A systematic review of the literature was carried out to investigate the effects that animal-assisted therapy (AAT) can have on people with cancer. In this systematic review, the relevant Greek and international literature was searched in the PubMed, Scopus and Science Direct databases. \nResults: The study of the international literature showed 10 articles that referred to the effects that animal-assisted therapy (AAT) can have on people with cancer, based on scientific data. These studies were published from 2007 to 2019. As regards the country of publication of these studies, they come from the United States of America (4), Japan (1), Canada (1), Germany (1), Italy (2) and the Czech Republic (1). \nConclusions: The frequency of use of AAT in various sectors over the last 10 years has been increasing rapidly. Animal-supported approaches from different countries and disciplines showed positive results in sensory, emotional and cognitive functions, especially in the physical structure and functions of individuals at different ages and diagnoses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 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 teacher head, 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".