Measuring quality of life in cancer survivors: a methodological review of existing scales
Bibliographic record
Abstract
BACKGROUND: Studies examining quality of life (QoL) in cancer survivors have relied on instruments specific to the cancer patient population. METHOD: MEDLINE and PsycINFO were systematically searched to identify instruments and papers reporting the psychometric qualities of relevant instruments. Two reviewers undertook data extraction with respect to reliability, validity, predictive validity, responsiveness, acceptability, readability, cross cultural acceptability and feasibility. RESULTS: Forty-two instruments were identified. Most were either measures of general health-related QoL or developed for individuals in active treatment. Nine were developed specifically for cancer survivors. None met the rigorous psychometric standards set by the review. All established acceptable levels of validity, however, only one instrument (Quality of Life-Cancer Survivors) demonstrated adequate test-retest reliability. Acceptability, feasibility and predictive validity remain unexamined. Readability was examined in only two (Cancer Survivors' Unmet needs and Quality of Life in Adult Cancer Survivors (QLACS)). Only two instruments (QLACS and Impact of Cancer) have been developed with a wide range of cancer survivors. Generally, shorter-term cancer survivors (1-5 years) are underrepresented. CONCLUSION: There is a need for a psychometrically credible QoL instrument for cancer survivors who are 1-5 years post diagnosis.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.062 | 0.159 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.019 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".