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Record W4411021932 · doi:10.5770/cgj.28.817

Perceptions of Frailty in Long-Term Care

2025· article· en· W4411021932 on OpenAlexafffundvenue
Kayla Atchison, Pauline Wu, Ann M. Toohey, Daniel Gaetano, Jacqueline M. McMillan, Jenna Naylor, Sharon Kaasalainen, Michelle Grinman, Vivian Ewa, Jessica Simon, James Silvius, Aynharan Sinnarajah, Beth Gorchynski, David B. Hogan, Jayna Holroyd‐Leduc, Zahra Goodarzi

Bibliographic record

VenueCanadian Geriatrics Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsQueen's UniversityBP (Canada)McMaster UniversityUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicinePalliative careAdvance care planningLong-term careNursingGerontologyMEDLINEFamily medicine

Abstract

fetched live from OpenAlex

Background: An early palliative approach to care may best suit the care needs of older persons with frailty living in long-term care (LTC). The study objective was to evaluate the barriers and facilitators to care for frailty in the LTC setting. Methods: Semi-structured interviews were completed with physicians, nurse practitioners, registered nurses, allied health-care providers, care partners, and residents with care experience in LTC. Framework analysis methods that leveraged behaviour change theories were used to analyze the interview data and produce practice-oriented findings. Results: Twenty-eight interviews were completed. Seven themes were identified: resident characteristics related to frailty; frailty detection and diagnosis; frailty treatment and care planning; frailty and prognosis conversations; palliative and end-of-life care; communication amongst LTC collaborators; and the LTC environment. All codes were labelled as barriers or facilitators and assigned to a primary domain within the Theoretical Domains Framework. Conclusions: The lack of clinical recognition of frailty in the LTC setting was a key barrier to clinical pathway implementation. There is a need for frailty to be linked to prognosis and care decisions, for frailty to be directly addressed through individualized treatments, and for an early palliative approach to care to be accessible to residents. Identifying barriers to care for frailty is a critical step toward clinical care pathway implementation which may improve care and outcomes for residents of LTC.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.287
Teacher spread0.273 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

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