Child‐ and parent‐reported quality of life trajectories in children with epilepsy: A prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To describe the developmental trajectories of quality of life (QoL) in a large cohort of children with epilepsy, and to assess the relative contribution of clinical, psychosocial, and sociodemographic variables on QoL trajectories. METHODS: Five assessments during a 28-month prospective cohort study were used to model trajectories of QoL. Participants were recruited with their parents from six Canadian tertiary centers. A convenience sample of 506 children aged 8-14 years with epilepsy and without intellectual disability or autism spectrum disorder were enrolled. A total of 894 children were eligible and 330 refused participation. Participating children were, on average, 11.4 years of age, and 49% were female. Nearly one third (32%) had partial seizures. At baseline, 479 and 503 child- and parent-reported questionnaires were completed. In total, 354 children (74%) and 366 parents (73%) completed the 28-month follow-up. QoL was measured using the child- and parent-reported version of the Childhood Epilepsy QoL scale (CHEQOL-25). RESULTS: Child-reported QoL was fitted best by a six-class model and parent-reported QoL by a five-class model. In both models, trajectories remained either stable or improved over 28 months. Of these children, 62% rated their QoL as high or moderately high, defined as at least one standard deviation above the average CHEQOL-25 score. Greater family, classmate, and peer social support, fewer symptoms of child and parent depression, and higher receptive vocabulary were identified as the most robust predictors of better QoL (all p < 0.001). SIGNIFICANCE: Most children with epilepsy and their parents reported relatively good QoL in this first joint self- and proxy-reported trajectory study. Findings confirm the heterogeneous QoL outcomes for children with epilepsy and the primary importance of psychosocial factors rather than seizure and AED-specific factors in influencing QoL. These predictors that are potentially amenable to change should now be the focus of specific intervention studies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".