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Record W4281659465 · doi:10.3233/shti220126

Use of Robots to Support Those Living with Dementia and Their Caregivers

2022· article· en· W4281659465 on OpenAlexafffund
Evangeline Wagner, Elizabeth M. Borycki, André Kushniruk

Bibliographic record

VenueStudies in health technology and informatics · 2022
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsMichael Smith Health Research BCUniversity of Victoria
FundersMichael Smith Health Research BC
KeywordsDementiaRobotHealth careAssisted livingRoboticsIntersection (aeronautics)Assisted Living FacilityIndependent livingCognitive impairmentPsychologyCognitionMedicineGerontologyComputer scienceArtificial intelligencePsychiatryEngineeringPathologyPolitical science

Abstract

fetched live from OpenAlex

Dementia and other related diseases causing symptoms of mild cognitive impairment are being increasingly diagnosed. These diseases are placing a significant strain on the healthcare system. Robotic technology research has also been increasing, specifically in the field of healthcare and assisted living. This scoping review explores the research at the intersection of dementia and robotic devices. More specifically, this paper looks at how robots can be used in dementia care to gain a deeper understanding of the potential benefits this technology may have on patient and caregiver lives. This research was conducted using PRISMA guidelines. Data were extracted from 13 articles. The researchers found that there is a lack of evidence regarding how robotics can assist patients living with dementia; however, robotic devices can be used by patients to perform some daily tasks in the home.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.041
GPT teacher head0.293
Teacher spread0.252 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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