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Record W4417497253 · doi:10.3390/healthcare14010002

What Do Older Adults with Frailty and Their Caregivers Want from Advance Care Planning Discussions? A Descriptive Qualitative Study

2025· article· en· W4417497253 on OpenAlexafffundabout
Robin Urquhart, Cynthia Kendell, Jessica Vickery, Elias Hirsch

Bibliographic record

VenueHealthcare · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersCanadian Frailty Network
KeywordsAdvance care planningQualitative researchDescriptive researchAutonomyHealth careDescriptive statisticsTelephone interviewGerontological nursingQualitative property

Abstract

fetched live from OpenAlex

Introduction: Advance care planning (ACP) may facilitate person-centered, goal-concordant care for this population. However, we know little about what older adults expect from ACP discussions (that is, the outcomes they expect or desire). We sought to explore patient and family views on the outcomes they consider most pertinent to ACP discussions for older adults living with frailty. Methods: This qualitative descriptive study used semi-structured telephone/video-conferencing interviews with older persons with frailty (65+ years) and their family/friend caregivers from across Canada. All interviews took place in person or via telephone or Zoom with healthcare professionals, depending on the participant’s preference, and were conducted by a researcher with experience in qualitative methods. Data analysis involved coding, grouping, detailing, and comparing the data, using techniques commonly employed in descriptive qualitative research. Results: Nine participants took part in this study: two were individuals living with frailty, and seven were caregivers of persons with frailty. They described three desired outcomes of ACP: (1) maximizing comfort and quality-of-life; (2) enhancing confidence in decision-making, which would heighten families’ level of reassurance as their loved one’s function and health status declines; and (3) maintaining autonomy so that people can live and die on their own terms. Conclusions: Ultimately, research and clinical care should tailor their ACP initiatives and evaluation metrics to align with what patients and families deem most important. The outcomes described by participants of this study should be further investigated and refined in future research.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.106
GPT teacher head0.455
Teacher spread0.349 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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