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The next of kin of older people undergoing haemodialysis: a discursive perspective on perceptions of participation

2011· article· en· W2150020359 on OpenAlexaff
Elin Margrethe Aasen, Marit Kvangarsnes, Bente Wold, Kåre Heggen

Bibliographic record

VenueJournal of Advanced Nursing · 2011
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsTyndale University
Fundersnot available
KeywordsNext of kinPaternalismPerceptionPerspective (graphical)IdeologyNursingQualitative researchHealth careSociologyPsychologyPublic relationsMedicineSocial psychologyGender studiesPolitical scienceLawPoliticsSocial science

Abstract

fetched live from OpenAlex

AIM: This paper is a report of a study conducted to explore how the family members of older people who will undergo haemodialysis treatment for the rest of their lives perceive participation. BACKGROUND: The rights of families to participate in treatment and health care are supported by international law, and by national law in Norway since 1999. METHOD: This study, which employed an explorative qualitative approach, was carried out in Norway in 2008. Data were derived from transcribed interviews with seven family members underwent critical discourse analysis. FINDINGS: Three discourse practices about the next of kin perception of participation were found: (1) to care and take control, (2) to struggle for involvement, and (3) to be forgotten and powerless. The next of kin said that they had no dialogue with the healthcare team, and some fought to be included in the decision-making process. CONCLUSION: The dominant part of the discourse as expressed by the next of kin seems to be a paternalistic ideology. Thus, finding ways to enable the next of kin to participate in the decision-making process seems to be a major challenge for the healthcare team in the dialysis units.

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)0.003
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 score0.142
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.097
GPT teacher head0.422
Teacher spread0.324 · 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

Citations29
Published2011
Admission routes1
Has abstractyes

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