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Record W2749486513 · doi:10.1177/0898264317725618

Long-Term Care Service Trajectories and Their Predictors for Persons Living With Dementia: Results From a Canadian Study

2017· article· en· W2749486513 on OpenAlexafffundabout
Denise Cloutier, Margaret J. Penning, Kim Nuernberger, Deanne Taylor, Stuart MacDonald

Bibliographic record

VenueJournal of Aging and Health · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsInterior HealthUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsDementiaGerontologyLong-term careService (business)Activities of daily livingMedicineIndependent livingSample (material)PsychologyPsychiatryBusinessDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: We used latent transition analysis to explore common long-term care (LTC) service trajectories and their predictors for older adults with dementia. METHOD: Using linked administrative data collected over a 4-year interval (2008-2011), the study sample included 3,541 older persons with dementia who were clients of publicly funded LTC in British Columbia, Canada. RESULTS: Our results revealed relatively equal reliance on home care (HC) and facility-based residential care (RC) as starting points. HC service users were further differentiated into "intermittent HC" and "continuous HC" groups. Mortality was highest for the RC group. Age, changes in cognitive performance, and activities of daily living were important predictors of transitions into HC or RC. DISCUSSION: Reliance on HC and RC by persons with dementia raises critical questions about ensuring that an adequate range of services is available in local communities to support aging in place and to ensure appropriate timing for entry into institutions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.047
GPT teacher head0.374
Teacher spread0.327 · 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.

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

Citations15
Published2017
Admission routes3
Has abstractyes

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