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Record W4412681981 · doi:10.1177/07334648251360098

The Influence of Physical, Social, and Organizational Environments on Recreational Activities in Long-Term Care for Residents With Dementia: A Scoping Review

2025· review· en· W4412681981 on OpenAlexaff
Z. Zhang, Habib Chaudhury, Wenjin Wang

Bibliographic record

VenueJournal of Applied Gerontology · 2025
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCINAHLPsycINFORecreationLong-term careDementiaStaffingPsychologyMEDLINEGerontologyNursingMedicinePsychological interventionPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: This scoping review explores how physical, social, and organizational factors influence recreational activity engagement for residents with dementia in long-term care settings. METHODS: A literature search in AgeLine, PsycINFO, CINAHL, Medline, and Web of Science identified studies on environmental factors affecting recreational activities for long-term care residents with dementia. A narrative approach was used to collate and summarize the findings from peer-reviewed English studies available until June 30, 2024. RESULTS: A total of 28 studies were reviewed, examining how physical, social, and organizational factors-such as homelike ambiance, staffing levels, and medicalized care culture-affect residents' engagement in recreational activities. The review also highlights the interrelationship among these factors. DISCUSSION AND IMPLICATIONS: The findings emphasize the importance of creating care environments that support activity participation. These insights can inform future assessments and the development of long-term care settings to improve activity experiences and outcomes 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 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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.399
Threshold uncertainty score0.487

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 head0.043
GPT teacher head0.428
Teacher spread0.384 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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