MétaCan
Menu
← Back to cohort
Record W2164741807 · doi:10.1016/j.jalz.2012.05.669

O2‐08‐04: Resident and facility determinants of long‐term care placement among older adults with dementia residing in assisted living facilities

2012· article· en· W2164741807 on OpenAlexaffabout
Monica Cepoiu‐Martin, Laurel A. Strain, Andrea Soo, David B. Hogan, Scott B. Patten, Andrea Gruneir, Ken LeClair, Kimberly Wilson, Joseph Emmanuel Amuah, Colleen J. Maxwell

Bibliographic record

VenueAlzheimer s & Dementia · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of WaterlooCanadian Institute for Health InformationProvidence Health CareWomen's College HospitalCanadian Mental Health AssociationUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineLong-term careStaffingGerontologyDementiaAging in placeCumulative incidenceIncidence (geometry)DiseaseNursing

Abstract

fetched live from OpenAlex

Background: Assisted Living is an increasingly important, yet poorly defined, setting for residential care of seniors with Alzheimer's disease and related disorders (ADRD). The AL philosophy implies that older adults receiving care will age in place, but admission and discharge criteria often make that impossible. The lower staffing rates and variability in services across facilities suggest the potential for poorer detection/management of emerging health issues and adverse health outcomes among ADRD residents. Our aim was to identify resident- and facility-level predictors of long-term care (LTC) placement and mortality over 1-year among older adults with ADRD across Designated Assisted Living (DAL) facilities in Alberta. Among 1,089 DAL residents aged 65+ (from 59 facilities) participating in the Alberta Continuing Care Epidemiologic Studies (ACCES), 58% (627) had a diagnosis of ADRD. Research nurses completed interRAI-AL resident assessments and interviewed family caregivers at baseline and 1-year (including discharge/decedent interviews). Standardized interviews with DAL administrators/managers provided facility-level data. Key predictors were examined using multivariate Cox proportional hazards regression models (with adjustment for clustering and competing risks). The cumulative incidence of LTC placement was 24.0% (95%CI 20.6-27.4) by 1 year, with an incidence rate of 29.9 per 100 person-years. Baseline resident characteristics significantly associated with placement included: greater health instability & cognitive impairment, mobility impairment, severe aggressive behaviours, urinary incontinence, previous hospitalizations, low activity levels and poor social engagement. Facility factors significantly associated with LTC placement were: <24 hrs/7 day LPN/RN coverage on-site (increased risk) and a higher number of DAL spaces within the facility (decreased risk). Other resident- (e.g., age, sex, ADL impairment, comorbidity, drug use) and facility-level characteristics (e.g., for-profit status, multi-level care, physician/specialist involvement) were not significant predictors in adjusted analyses. Conclusion(s): Assisted Living is rapidly expanding as a housing option for seniors with significant cognitive and functional needs. While often viewed as an alternative to traditional LTC care, one quarter of DAL residents with ADRD in Alberta required LTC admission over one year. Our findings on resident and facility predictors of institutionalization highlight various clinical and policy areas where targeted interventions may prevent or delay LTC admissions.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.330
Teacher spread0.294 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueAlzheimer s & Dementia→Same topicGeriatric Care and Nursing Homes→French-language works237,207→