Construct validity of the quality of life in life-threatening illness-patient questionnaire (QOLLTI-P) in cancer patients
Bibliographic record
Abstract
Quality of life (QOL) optimization is an important issue during the process of care for patients suffering from a life-threatening illness such as cancer. The Quality of Life in Life-Threatening Illness-Patient questionnaire (QOLLTI-P) is a self-administered questionnaire based on the McGill Quality of Life questionnaire (MQOL) with domains added to enhance content validity. This study's main objective was to assess the construct validity of QOLLTI-P in cancer patients. Cancer outpatients were asked to complete a set of questionnaires including QOLLTI-P and the Functional Assessment of Chronic Illness Therapy- Spiritual well-being scale (FACIT-Sp). An 8-factor structure was suggested for QOLLTI-P. In general, QOLLTI-P Total and subscale scores are highly correlated with their corresponding FACIT-Sp scores. In conclusion, QOLLTI-P is a valid instrument to assess the QOL of cancer patients.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".