A pilot study of transformation, attributed meanings to the illness, and spiritual well-being for terminally ill cancer patients
Bibliographic record
Abstract
OBJECTIVE: The present study investigated what types of transformation terminally ill cancer patients experienced from diagnosis until the terminal stage, what meanings terminally ill cancer patients attributed to their illness, and whether or not those who attributed positive meaning to their illness achieved high levels of spiritual well-being as a preliminary study. METHOD: Ten terminally ill cancer patients in the hospice wards of two general hospitals participated. A clinical psychologist conducted a semistructured interview with the patients individually for about 60 min. Patients completed the FACIT-Sp and HADS before the interview and talked about the meanings of cancer experience. The contents of the interviews were analyzed qualitatively. Patients were separated into high and low levels of spiritual-well being by the median of FACIT-Sp scores. RESULTS: Three types of transformation were extracted: "group with peaceful mind," "group with both positive attitude and uneasy feeling," and "groups with uneasy feeling." As attributed meanings to the illness, five categories were extracted: "positive meaning," "natural acceptance," "negative acceptance," "search for meaning," and "regret and sorrow." Patients in the high level spiritual well-being group attributed the meaning of illness to "positive meaning" and "natural acceptance," and those in the low level spiritual well-being group attributed it to "regret and sorrow" and "search for meaning." SIGNIFICANCE OF RESULTS: Some Japanese terminally ill cancer patients experienced positive transformation, and patients who attributed "positive meaning" and "natural acceptance" to their illness experience achieved high levels of spiritual well-being.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".