Ultimate journey of the terminally ill: Ways and pathways of hope.
Bibliographic record
Abstract
OBJECTIVE: To better understand the role of hope among terminally ill cancer patients. DESIGN: Qualitative analysis. SETTING: A tertiary specialized cancer centre in Canada. PARTICIPANTS: Cancer patients in palliative care with an estimated remaining life expectancy of 12 months or less (N = 12) and their loved ones (N = 12) and treating physicians (N = 12). METHODS: Each patient underwent up to 3 interviews and identified a loved one who participated in 1 interview. Treating physicians were also interviewed. All interviews were fully transcribed and analyzed by at least 2 investigators. Interviews were collected until saturation occurred. MAIN FINDINGS: Seven attributes describe the experiences of palliative cancer patients and their caregivers: hope as an irrational phenomenon that is a deeply rooted, affect-based response to adversity; initial hope for miraculous healing; hope as a phenomenon that changes over time, evolving in different ways depending on circumstances; hope for prolonged life when there is no further hope for cure; hope for a good quality of life when the possibility of prolonging life becomes limited; a lack of hope for some when treatments are no longer effective in curbing illness progression; and for others hope as enjoying the present moment and preparing for the end of life. CONCLUSION: Approaches aimed at sustaining hope need to reflect that patients' reactions might fluctuate between despair and a form of acceptance that leads to a certain serenity. Clinicians need to maintain some degree of hope while remaining as realistic as possible. The findings also raise questions about how hope influences patients' perceptions and acceptance of their treatments.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".