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Facilitating Day-to-Day Decision Making in Palliative Care

2000· article· en· W2031754609 on OpenAlexaff
Joan L. Bottorff, Rose Steele, Betty Davies, Pat Porterfield, Candy Garossino, Mary Shaw

Bibliographic record

VenueCancer Nursing · 2000
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrounded theoryNursingPalliative careMedicinePsychological interventionEveryday lifeQualitative researchPsychology

Abstract

fetched live from OpenAlex

As part of a larger grounded theory study investigating the process by which palliative care patients make everyday choices, a secondary analysis of data was conducted to investigate the ways nurses support or restrict patients' participation in their care. Constant comparative methods were used to generate a detailed, contextually grounded description of nurses' strategies that influenced patients' participation in making everyday choices about their personal and nursing care. Data consisted of field notes derived from observations of patients and their caregivers in two hospital-based palliative care units and from 23 transcripts of interviews with participating nurses and patients. Nurses' efforts to support patients' participation in decision making were described as a four-phase process: getting to know the patient, enhancing opportunities for choice, being open to patient choice, and respecting choice. Factors influencing nurses' use of supportive behaviors and behaviors that restricted patients' participation in everyday choices were identified. Given the importance patients attributed to making choices, these findings provide a foundation for the design of nursing interventions that hold great potential for directly influencing quality of life.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.236
GPT teacher head0.522
Teacher spread0.287 · 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.

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

Citations33
Published2000
Admission routes1
Has abstractyes

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