Lived Experiences of Canadian Women with Metastatic Breast Cancer in Preparation for Their Death: A Qualitative Study. Part I-Preparations and Consequences
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".