Assessing the impact of pediatric epilepsy and concomitant behavioral, cognitive, and physical/neurologic disability: Impact of Childhood Neurologic Disability Scale
Bibliographic record
Abstract
Epilepsy has a significant impact on a child's life, the extent to which is based on four factors: epilepsy, cognition, behavioral, and physical/neurologic function. This study evaluates the ability of the 44‐item Impact of Childhood Neurologic Disability Scale (ICND) to assess each of these four realms. Parents of children (aged 2 to 18 years) with epilepsy rated their child's overall quality of life and completed the ICND. External validation compared the ICND with (1) neurologists’reports of children's behavior, cognitive abilities, physical/neurologic disability, and epilepsy; and (2) parents, teachers, and children's ratings on six‘criterion standard’questionnaires. Families of 68 children with epilepsy only and 29 children with‘epilepsy‐plus’(additional cognitive, behavioral, or physical/neurologic disability; 39 males, 58 females; mean age at testing 10 years 3 months [SD 4.5] age range 2 to 17 years) participated. Internal consistency was excellent (Cronbach's α=0.92) as was test‐retest reliability (intraclass correlation=0.89). Caregivers distinguished the impact of each of the four realms. Scores were negatively related to quality of life (Pearson's r=‐0.59). Children with high ICND scores had more difficulties at home and school. Their parents saw them as less rewarding and adaptable and the children saw themselves as less intelligent and less popular with more emotional problems. In addition, children with‘epilepsy‐plus’had significantly higher total ICND scores as well as markedly elevated scores within each of the four realms when compared with the epilepsy‐only group. It is concluded that the ICND is an accurate, quick measurement tool reflecting the impact of behavior, cognitive learning ability, physical/neurologic disability, and epilepsy on children 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".