Quality-of-Life Assessment in Pediatric Advanced Cancer: Development of the Patient-Reported Outcome Measure Advance QoL
Bibliographic record
Abstract
A recent measure was developed to assess the Quality of Life (QoL) of young people with advanced cancer and is available for parents and professionals (Advance QoL). The present study aimed to elaborate self-reported versions for children and adolescents with advanced cancer. We adopted a four-phase research plan: (1) to elaborate the Advance QoL questionnaire for youth (8–12 and 13–18 years old) with a team of young research partners; (2) to evaluate the understandability of these versions in a sample of 12 young patients from the target population using cognitive interviews; (3) to assess social validity in the same group using a questionnaire and the content validity index (CVI); and (4) to refine the questionnaires according to these results. Four major themes were identified: (1) issues affecting the understanding of the tool; (2) issues that did not affect the understanding of the tool; (3) modifications to improve the tool; and (4) positive features of the tool. Advance QoL was well received, and feedback was positive. Adjustments were made according to young people’s comments and two self-reported versions are now available. It is essential to measure the key domains of QoL in advanced cancer. Advance QoL self-report versions will help target the specific needs of young people with this condition and their families.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".