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Record W17574322 · doi:10.1177/082585970802400102

Lived Experiences of Canadian Women with Metastatic Breast Cancer in Preparation for Their Death: A Qualitative Study. Part I-Preparations and Consequences

2008· article· en· W17574322 on OpenAlexaffabout
Kanoknuch Chunlestskul, Linda E. Carlson, Janice P. Koopmans, Maureen Angen

Bibliographic record

VenueJournal of Palliative Care · 2008
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsAlberta Cancer FoundationUniversity of Calgary
Fundersnot available
KeywordsGriefThematic analysisPsychosocialQualitative researchFeelingBreast cancerLived experienceMedicinePsychologyPalliative careNursingPsychotherapistCancerSocial psychologySociology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aimed to detail the tasks of death preparation and the consequences of such preparation for women with metastatic breast cancer. METHODS: A phenomenological qualitative approach was used. Five women with metastatic breast cancer were interviewed on two occasions. Themes were analyzed, described, and validated, until saturation was met. Outcomes of thematic analysis related to the impetus, process, and consequences of preparing for one's own death. FINDINGS: The women prepared for their death by: acknowledging their grief; preparing mentally; seeking information and support; preparing the family; and preparing for the end of life. They also engaged in creating life projects that enhanced their connections with loved ones, and lived full and joyful lives. These activities helped increased their readiness to die in peace. CONCLUSIONS: Preparing for their own death can help women with incurable cancer live full, satisfying lives, and be prepared to face their own death with peace. Helping women express their feelings around their own death and their preparation for death should be a key interdisciplinary psychosocial nursing intervention.

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 score0.159
Threshold uncertainty score0.990

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 head0.142
GPT teacher head0.451
Teacher spread0.310 · 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

Citations20
Published2008
Admission routes2
Has abstractyes

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