Quality of life measure for children with Epilepsy: A psychometric evaluation of the Italian version
Bibliographic record
Abstract
Objective To report on the Italian validation of the Child Epilepsy Quality of Life Questionnaire (CHEQOL-25), including both the child self-report and parent-proxy versions. Methods The validation procedure was conducted at a single Italian centre between July 2024 and July 2025, involving 252 children with epilepsy and their parents. A forward–backward translation process was carried out in line with established best-practice guidelines. Data collection included family interviews and medical chart reviews. Psychometric evaluation covered reliability and validity. Results All items exceeded the accepted thresholds (≥ 0.78) for both content validity and comprehensibility. The factor structure closely replicated the original five-factor model, with certain items showing stronger loadings than the original study within the Interpersonal/Social and Intrapersonal/Emotional domains in both related versions. The Secrecy factor showed greater variability (h 2 = 0.06–.83), possibly reflecting differences in parental interpretation or their sensitivity to the epilepsy concealment. Children who engaged in playful activities scored higher across most subscales, particularly in the Interpersonal/Social and the Quest for Normality domains of the self-report version. Importantly, children not receiving school support reported higher scores across several subscales, suggesting fewer perceived psychosocial challenges. Agreement between child self-reports and parent proxy-reports ranged from moderate to strong (ICC = 0.53–.71). Conclusions The Italian version of the CHEQOL-25 measure demonstrates strong psychometric properties (consistent with the original version) and reinforces the value of assessing quality of life in children with epilepsy across diverse cultural contexts.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".