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Record W2047058332 · doi:10.1177/0733464815574094

The Effect of Dining Room Physical Environmental Renovations on Person-Centered Care Practice and Residents’ Dining Experiences in Long-Term Care Facilities

2015· article· en· W2047058332 on OpenAlexaffabout
Lillian Hung, Habib Chaudhury, Tiana Rust

Bibliographic record

VenueJournal of Applied Gerontology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of AlbertaSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsAutonomyFocus groupLong-term carePsychologyNursingPerson-centered careUnit (ring theory)Qualitative researchApplied psychologyMedical educationMedicineBusinessHealth careSociologyMarketingPolitical science

Abstract

fetched live from OpenAlex

This qualitative study evaluated the effect of dining room physical environmental changes on staff practices and residents' mealtime experiences in two units of a long-term care facility in Edmonton, Canada. Focus groups with staff (n = 12) and individual interviews with unit managers (n = 2) were conducted. We also developed and used the Dining Environment Assessment Protocol (DEAP) to conduct a systematic physical environmental evaluation of the dining rooms. Four themes emerged on the key influences of the renovations: (a) supporting independence and autonomy, (b) creating familiarity and enjoyment, (c) providing a place for social experience, and (d) challenges in supporting change. Feedback from the staff and managers provided evidence on the importance of physical environmental features, as well as the integral nature of the role of the physical environment and organizational support to provide person-centered care for residents.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0070.007
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations67
Published2015
Admission routes2
Has abstractyes

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