What Determines the Quality of Life of Terminally Ill Cancer Patients from Their Own Perspective?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Although several instruments have been developed to measure the quality of life (QOL) of palliative care patients, a rigorous research study has not specifically asked patients themselves what is important to their QOL. It is, therefore, not clear whether these instruments measure what is most important to these patients' QOL. PURPOSE: To understand the primary determinants of the QOL of palliative care patients with cancer. METHOD: The study used a qualitative paradigm. Participants were interviewed concerning what was important to their QOL. A systematic content analysis of the transcripts was carried out by all the investigators. RESULTS: Five broad domains were found to be importnat determinants of patient QOL: (1) the patient's own state, including physical and cognitive functioning, psychological state, and physical condition; (2) quality of palliative care; (3) physical environment; (4) relationships; and (5) outlook. CONCLUSIONS: Existing instruments cover many of these domains, but no single instrument includes all of the relevant content. The McGill Quality of Life Questionnaire, which we developed previously, has been revised based on these data.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it