A singing choir: Understanding the dynamics of hope, hopelessness, and despair in palliative care patients. A longitudinal qualitative study
Bibliographic record
Abstract
OBJECTIVE: Hope, despair, and hopelessness are dynamic in nature; however, they have not been explored over time. The objective of the present study was to describe hope, hopelessness, and despair over time, as experienced by palliative care patients. METHOD: We employed a qualitative longitudinal method based on narrative theories. Semistructured interviews with palliative care patients were prospectively conducted, recorded, and transcribed. Data on hope, hopelessness and despair were thematically analyzed, which led to similarities and differences between these concepts. The concepts were then analyzed over time in each case. During all stages, the researchers took a reflexive stance, wrote memos, and did member checking with participants. RESULTS: A total of 29 palliative care patients (mean age, 65.9 years; standard deviation, 14.7; 14 females) were included, 11 of whom suffered from incurable cancer, 10 from severe chronic obstructive pulmonary disease, and 8 from severe heart failure. They were interviewed a maximum of three times. Participants associated hope with gains in the past or future, such as physical improvement or spending time with significant others. They associated hopelessness with past losses, like loss of health, income, or significant others, and despair with future losses, which included the possibility of losing the future itself. Over time, the nature of their hope, hopelessness, and despair changed when their condition changed. These dynamics could be understood as voices in a singing choir that can sing together, alternate with each other, or sing their own melody. SIGNIFICANCE OF RESULTS: Our findings offer insight into hope, hopelessness, and despair over time, and the metaphor of a choir helps to understand the coexistence of these concepts. The findings also help healthcare professionals to address hope, hopelessness, and despair during encounters with patients, which is particularly important when the patients' physical condition has changed.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 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".