Bibliographic record
Abstract
BACKGROUND: Cancer is the leading cause of death in Korean adults. A good quality of life for patients at end life can control pain and symptoms and help maintain well-being. OBJECTIVE: The aim of this study was to measure quality of life in end-stage cancer patients using the Korean version of the McMaster Quality of Life (K-MQOL). METHODS: The K-MQOL was administered to adult end-stage cancer patients from 4 Korean university hospitals. We hypothesized quality-of-life differences between participants by daily activity level, number of symptoms, and participant status (alive or not) at end of study. RESULTS: Participants' mean age was 49.2 years, and 74.5% were men. As hypothesized for discriminant validity, Pearson correlation coefficients among the K-MQOL were less than 0.4, with the exceptions of emotion (0.25-0.52) and cognition (0.33-0.51). A higher Eastern Cooperative Oncology Group Performance States Rating score was significantly associated with a lower quality of life (F = 2.840, P = 0.034). The mean score of those within 21 days of death was significantly lower than that of patients who were alive at the end of the study (t = -2.48, P = .04). Patients with a smaller number of symptoms other than pain had significantly higher quality-of-life scores than did those with more symptoms (F = 5.059, P = .004). CONCLUSIONS: The K-MQOL provided reliable and valid scores of quality of life in end-stage cancer patients. IMPLICATIONS FOR PRACTICE: Assessing end-stage cancer patients' quality of life helps to identify each patient's condition and aspects that could benefit from nursing care. We anticipate that the K-MQOL will be useful for patient assessment in clinical and community settings.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".