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Record W3116129517 · doi:10.7748/ns.2020.e11625

Benefits and challenges of animal-assisted therapy in older adults: a literature review

2020· review· en· W3116129517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Standard · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsSt. Lawrence College
Fundersnot available
KeywordsAnimal-assisted therapyMedicinePsychological interventionMoodHealth careMEDLINEAnimal welfarePet therapyNursingPsychiatry

Abstract

fetched live from OpenAlex

Animal-assisted therapy involves the use of highly trained animals, such as dogs and cats, in conjunction with conventional treatments to address the physical and emotional needs of patients. This article presents a literature review of the health benefits and challenges associated with the use of animal-assisted therapy in the care of older patients in hospitals and long-term care facilities. Eleven original research articles were included and three themes were identified: physiological outcomes, psychological outcomes, and challenges associated with using animal-assisted therapy in patient care. The literature review aims to enhance nurses' knowledge of the health benefits of animal-assisted therapy as an adjunct to traditional treatments. It found that animal-assisted therapy can improve sleep, reduce depression and enhance mood in older patients. Challenges were identified in relation to ensuring infection prevention and control and in sustaining the implementation and benefits of interventions. Further research is necessary to explore the sustainability and long-term benefits of animal-assisted therapy in healthcare settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.392
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it