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Record W4205258325 · doi:10.3928/00989134-20211206-05

Use of an Ambient Activity Technology for Long-Term Care Residents With Dementia

2022· article· en· W4205258325 on OpenAlexaff
Nicholas Lignos, Rose McCloskey, Cindy Donovan, Kate Ellis, Madison Herrington, Marc Kanik

Bibliographic record

VenueJournal of Gerontological Nursing · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLong-term careDementiaNursing homesAssisted livingGerontological nursingGerontologyFocus groupNursingPerceptionMedicinePsychologyBusiness

Abstract

fetched live from OpenAlex

The purpose of the current pilot study was to determine the impact of an ambient activity technology, ABBY ® , on responsive behavior and family visiting in a long-term care (LTC) home. We were also interested in family and staff perceptions of the technology. A mixed methods research study was conducted over a 6-month period and data were collected using standardized measures and focus groups. Although no significant differences were noted in responsive resident behaviors, focus group data showed the ABBY enriched the care environment and provided additional opportunities for families and staff to engage residents. Although the introduction of a new technology can create challenges for staff, with time, these challenges can be overcome. [ Journal of Gerontological Nursing, 48 (1), 35–41.]

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.537

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.419
Teacher spread0.330 · 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 designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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