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Record W3111389289 · doi:10.1080/13607863.2020.1857698

Admission to long-stay residential care and mortality among people with and without dementia living at home but on the boundary of residential care: a competing risks survival analysis

2020· article· en· W3111389289 on OpenAlexaff
Laura Carter, Stephen O’Neill, Peter C. Austin, Fiona Keogh, Maria Pierce, Eamon O’Shea

Bibliographic record

VenueAging & Mental Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsDementiaHazardMedicineHazard ratioAffect (linguistics)GerontologyActivities of daily livingPsychologyDiseasePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Health policy in many countries is underpinned by a commitment to support dependent older people to remain in their own home for as long as possible and practicable. This study explores factors affecting both admission to long-stay residential care (LSRC) and mortality among people with and without dementia who are currently living at home with intensive formal care support. METHODS: This is a cross-sectional study based on administrative data collected on 429 dependent older people in Ireland, 269 of whom were people with dementia. A cause-specific hazard model was used to investigate the hazard of admission to LSRC, while accounting for mortality as a competing risk and vice versa. RESULTS: Admission to LSRC was higher for people with dementia relative to people without and for those receiving lower amounts of informal care. The hazard of mortality was significantly higher for older people aged 85+, whereas it was lower for individuals with a medium level of dependency relative to those with high levels of dependency. The hazard of mortality was also influenced by the amount of informal care provision. CONCLUSION: People with dementia are more likely to be admitted to LSRC than people without. Care for people with dementia needs to be more specialised and personal, and intensity of provision should not be equated to the number of care hours on offer. Informal care provision may help to prevent admission to LSRC. Advanced age, physical dependency and informal care provision affect mortality, raising interesting issues in relation to resource allocation.

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 score0.054
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.037
GPT teacher head0.380
Teacher spread0.343 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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