Single‐item measure for assessing quality of life in children with drug‐resistant epilepsy
Bibliographic record
Abstract
Objective: The current study investigated the psychometric properties of a single-item quality of life (QOL) measure, the Global Quality of Life in Childhood Epilepsy question (G-QOLCE), in children with drug-resistant epilepsy. Method: Data came from the Impact of Pediatric Epilepsy Surgery on Health-Related Quality of Life Study (PESQOL), a multicenter prospective cohort study (n = 118) with observations collected at baseline and at 6 months of follow-up on children aged 4-18 years. QOL was measured with the QOLCE-76 and KIDSCREEN-27. The G-QOLCE was an overall QOL question derived from the QOLCE-76. Construct validity and reliability were assessed with Spearman's correlation and intraclass correlation coefficient (ICC). Responsiveness was examined through distribution-based and anchor-based methods. Results: The G-QOLCE showed moderate (r ≥ 0.30) to strong (r ≥ 0.50) correlations with composite scores, and most subscales of the QOLCE-76 and KIDSCREEN-27 at baseline and 6-month follow-up. The G-QOLCE had moderate test-retest reliability (ICC range: 0.49-0.72) and was able to detect clinically important change in patients' QOL (standardized response mean: 0.38; probability of change: 0.65; Guyatt's responsiveness statistics: 0.62 and 0.78). Caregiver anxiety and family functioning contributed most strongly to G-QOLCE scores over time. Significance: Results offer promising preliminary evidence regarding the validity, reliability, and responsiveness of the proposed single-item QOL measure. The G-QOLCE is a potentially useful tool that can be feasibly administered in a busy clinical setting to evaluate clinical status and impact of treatment outcomes in pediatric epilepsy.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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, 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".