Prevalence and trajectories of depressive symptoms in mothers of children with newly diagnosed epilepsy
Bibliographic record
Abstract
PURPOSE: To examine the prevalence, trajectories, and predictors of depressive symptoms (DS) in mothers of children with new-onset epilepsy. METHODS: A sample of 339 mothers was analyzed from the health-related quality of life in children with epilepsy study assessed four times during the first 24 months after diagnosis. Mothers' DS were measured using the Center for Epidemiological Studies Depression Scale. Trajectories of DS were investigated using group-based trajectory modeling, and maternal, child, and family factors were compared across groups using analysis of variance (ANOVA) and chi square tests. Multinomial logistic regression identified predictors of DS trajectories. KEY FINDINGS: A total of 258 mothers completed the study. Prevalence of depression ranged from 30-38% across four times within the first 24 months after their child's diagnosis. Four trajectories of DS were observed: low stable (59%), borderline (25%), moderate increasing (9%), and high decreasing (7%). Using the low stable group as the reference group, the borderline group was younger, had worse family functioning, and fewer family resources; the moderate increasing group was younger, had children with cognitive problems, worse family functioning, and more family demands; and the high decreasing group had less education and children with lower quality of life. SIGNIFICANCE: Risk for clinical depression is common among mothers of children with new-onset epilepsy. These mothers are not homogenous, but consist of groups with different trajectories and predictors of DS. Child's cognitive problems was the strongest predictor identified; epilepsy severity did not predict DS trajectory. Health care professionals should consider routinely assessing maternal depression during clinic visits for pediatric epilepsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".