Trajectory of maternal depression and parasomnias
Bibliographic record
Abstract
Maternal depressive symptoms are associated with poorer sleep quality in their children. Although parasomnias can occur at any age, this group of sleep disorders is more common in children. The aim of this study was to assess whether maternal depression trajectories predict parasomnias at the age of 11 years. Data were from a Birth Cohort of 4231 individuals followed in the city of Pelotas, Brazil. Maternal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) at 12, 24, and 48 months, and 6 and 11 years postpartum. Maternal depression trajectories were calculated using a group-based modelling approach. Information on any parasomnias (confused arousals, sleepwalking, night terrors, and nightmares) was provided by the mother. Five trajectories of maternal depressive symptoms were identified: chronic-low (34.9%), chronic-moderate (41.4%), increasing (10.3%), decreasing (8.9%), and chronic-high (4.4%). The prevalence of any parasomnia at the age of 11 years was 16.8% (95% confidence interval [CI] 15.6%-18.1%). Confusional arousal was the most prevalent type of parasomnia (14.5%) and varied from 8.7% to 14.7%, 22.9%, 20.3%, and 27.5% among children of mothers at chronic-low, moderate-low, increasing, decreasing, and chronic-high trajectories, respectively (p < 0.001). Compared to children from mothers in the chronic-low trajectory, the adjusted prevalence ratio for any parasomnia was 1.58 (95% CI 1.29-1.94), 2.34 (95% CI 1.83-2.98), 2.15 (95% CI 1.65-2.81), and 3.07 (95% CI 2.31-4.07) among those from mothers in the moderate-low, increasing, decreasing, and chronic-high trajectory groups, respectively (p < 0.001). In conclusion, parasomnias were more prevalent among children of mothers with chronic symptoms of depression.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".