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Record W3012726802 · doi:10.1186/s12877-020-1459-6

Perspectives of older adults, caregivers, and healthcare providers on frailty screening: a qualitative study

2020· article· en· W3012726802 on OpenAlexafffund
Jill Van Damme, Elena Neiterman, Mark Oremus, Kassandra Lemmon, Paul Stolee

Bibliographic record

VenueBMC Geriatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of Waterloo
FundersCanadian Frailty NetworkGovernment of Canada
KeywordsMedicineThematic analysisFocus groupQualitative researchHealth careGerontologyCoding (social sciences)MEDLINENursing

Abstract

fetched live from OpenAlex

BACKGROUND: Screening is an important component of understanding and managing frailty. This study examined older adults', caregivers' and healthcare providers' perspectives on frailty and frailty screening. METHODS: Fourteen older adults and caregivers and 14 healthcare providers completed individual or focus group interviews. Interviews were audio recorded, transcribed verbatim, and analyzed using line-by-line emergent coding techniques and inductive thematic analysis. RESULTS: The interviews yielded several themes with associated subthemes: definitions and conceptualizations of frailty, perceptions of "frail", factors contributing to frailty (physical,, cognitive, social, pharmaceutical, nutritional), and frailty screening (current practices, tools in use, limitations, recommendations). CONCLUSION: Older adults, caregivers and healthcare providers have similar perspectives regarding frailty; both identified frailty as multi-dimensional and dynamic. Healthcare providers need clear "next steps" to provide meaning to frailty screening practices, which may improve use of frailty-screening tools.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.346
Teacher spread0.289 · 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 designQualitative
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

Citations44
Published2020
Admission routes2
Has abstractyes

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