Longitudinal trajectories of depression symptoms in children with epilepsy
Bibliographic record
Abstract
AIM: To examine self- and proxy-reported symptoms of depression in children with epilepsy. METHOD: This was a prospective longitudinal cohort study of children with epilepsy. Participants were treated at six Canadian tertiary-care centers and followed over 28 months with repeated assessments of child self-reported symptoms of depression using the Children's Depression Inventory Short-Form (CDI-S). Trajectories of symptoms of depression were estimated using linear mixed effects (LME) modeling. RESULTS: At baseline, 477 children had complete data (mean age [SD] 11y 5mo [2y 1mo], range 7y 7mo-15y 1mo; 234 females, 243 males). Mean CDI-S T score at baseline was 45.7 (SD=7.5) and at 28 months was 44.9 (SD=8.2), both were within the 'average' range. Results from LME modeling revealed mean raw CDI-S score of 1.897, corrected for age 10 years (corresponding to T scores slightly below the normed mean of 50), with no significant change over three measurements (slope=-0.113, p=0.135), indicating that CDI-S scores were stable over 28 months. Children with high initial CDI-S scores had lower subsequent scores, as demonstrated by the correlation of -0.827 between intercept and slope (p<0.001). Parents reported comparable findings. INTERPRETATION: Self- and proxy-reported symptoms of depression were generally low and stable over an extended follow-up period. Normalization of scores was seen upon repeated assessment, even in children with higher scores of symptoms of depression at one point. These findings speak to the value and importance of repeated assessment over time. WHAT THIS PAPER ADDS: In children with epilepsy, self- and proxy-reported symptoms of depression were generally low and stable over 28 months. The trajectory of symptoms of depression was not associated with seizure severity, whether considering the frequency or type of seizures. Parents' reports of symptoms of depression were comparable to the children's self-evaluations.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".