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Record W2107397298 · doi:10.5539/gjhs.v6n5p301

Futile Care; Concept Analysis Based on a Hybrid Model

2014· article· en· W2107397298 on OpenAlexvenueno aff
Fatemeh Bahramnezhad, Mohammad Ali Cheraghi, Mahvash Salsali, Parvaneh Asgari, Fatemeh Khoshnavay Fomani, Mahnaz Sanjari, Pouya Farokhnezhad Afshar

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsnot available
FundersTehran University of Medical Sciences and Health Services
KeywordsPalliative careBachelorNursingInclusion (mineral)Unit (ring theory)Presentation (obstetrics)PsychologyData collectionMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Making decision about what kind of caring is entitled as futile care requires the presentation of a clear definition of such caretaking. OBJECTIVE: To report an analysis of the concept of futile care. DESIGN: The analysis in this research was carried out through hybrid model in three stages. At the theoretical stage: a review of the available literature. At the work-in-field stage: semi-structured interviews. SETTING: Data collection was on cancer unit and palliative care unit. PARTICIPANTS: A total of 7 participants were recruited in the study. The inclusion criteria were: having at least a bachelor's degree in nursing, having at least 5 years of experience in critical care or cancer units, and being willing to participate in the study. RESULTS: Three themes emerged: "low quality of life", "lack physiologic return to life" and "performing non-professional duties". CONCLUSION: Futile care consists giving clinical cares irrelevant to a nurse's job and giving cares through which the return of patient would be impossible both physiologically and qualitatively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.004
Scholarly communication0.0050.005
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.393
Teacher spread0.356 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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