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Record W2888244241 · doi:10.1111/jan.13830

Living with dying: A narrative inquiry of people with chronic kidney disease and their family members

2018· article· en· W2888244241 on OpenAlexafffund
Anita Molzahn, Laurene Sheilds, Anne Bruce, Kara Schick‐Makaroff, Marcy Antonio, Lacie White

Bibliographic record

VenueJournal of Advanced Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of OttawaUniversity of VictoriaUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsActive listeningNarrativeDyadKidney diseaseMedicinePsychologySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

AIMS: To describe how people diagnosed with chronic kidney disease and their family members describe uncertainty related to impending death. BACKGROUND: There has been little research about the experiences of people with chronic kidney disease and their family members as they near the end-of-life. We need to understand these experiences to give holistic person-centred care. DESIGN: A narrative enquiry was undertaken using a social constructionist perspective. METHODS: Data were collected in two in-depth interviews, approximately 3-4 months apart, followed by a telephone follow-up 2-3 months later. RESULTS: Eleven people with advanced chronic kidney disease and nine family members/significant others participated. For both participants in the dyad, a number of key themes/storylines were identified. These included recognition that: @life has a boundary, living on the edge, I'm not afraid to die but… and remembering loss and death experiences@. CONCLUSIONS: This enquiry illuminated four key storylines of about death and dying with advanced chronic kidney disease for people with the illness and their family members. Discussion about past experiences with illness, loss, death, and dying can give an entry for discussion about end-of-life. The person with illness and family members often held very similar perceptions and desires, but healthcare professionals' contributions to understanding of the experience were not mentioned. Implications for clinicians include attending to peoples' awareness of death as a distinct opportunity, listening attentively and posing questions that genuinely invite concerns and wishes about end-of-life and living well.

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 score0.137
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.046
GPT teacher head0.372
Teacher spread0.325 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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