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Record W4399669054 · doi:10.3390/robotics13060092

Robotic Animal Use among Older Adults Enrolled in Palliative or Hospice Care: A Scoping Review and Framework for Future Research

2024· review· en· W4399669054 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

VenueRobotics · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPalliative careMedicineHospice careNursingGerontologyPopulationPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

As the population of older adults increases, there is an anticipated rise in the utilization of hospice and palliative care. Many significant advancements in technology have been used to address the unique needs of this demographic; however, an unexplored area of research is the use of robotic animals as part of end-of-life care. The purpose of this scoping review was to examine the state of the literature on robotic animal use among older adults enrolled in palliative or hospice care and to offer a framework for future research. Following a guide for scoping reviews, we identified relevant studies and then charted, collated, summarized, and reported the data. Two articles were selected for final review. The results found that decreased medication use, behavior change, and emotional benefits were potential outcomes of robotic animal use in hospice and palliative care. Perceptions of the robot and ethical considerations were also discussed. Overall, the study findings point toward the potential uses of robotic animals as part of end-of-life care, however, more empirical research is critically needed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.111
GPT teacher head0.492
Teacher spread0.381 · 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