Sleep Terrors in Children: A Prospective Study of Twins
Bibliographic record
Abstract
OBJECTIVE: There is growing evidence that genetic factors are involved in the occurrence of sleep terrors. Twin studies provide invaluable information regarding genetic and environmental factors that can affect the manifestation of the disease; however, most previous twin studies on sleep terrors were performed retrospectively or with a sample that was too small to yield conclusive results. The aim of this large prospective study was to clarify the genetic and environmental contributions to sleep terrors in childhood. METHODS: In all, 390 pairs of monozygotic and dizygotic twins were recruited at birth for a longitudinal study. The prevalence and frequency of sleep terrors were assessed at 18 and 30 months of age with a questionnaire administered to the biological mother of the twins. Zygosity was determined by a questionnaire and genotyping. The prevalence and polychoric correlation for each type of twins were calculated. Structural-equation modeling was used to determine the proportion of variance attributable to additive genetic, shared, and nonshared environmental factors. RESULTS: The prevalence of sleep terrors was 36.9% at 18 months and 19.7% at 30 months; 49% of affected children were boys, and 51% were girls. At 18 months, the polychoric correlations were 0.63 for monozygotic and 0.36 for the dizygotic twins. These were 0.68 (monozygotic) and 0.24 (dizygotic) at 30 months. Our model-fitting analysis showed that sleep terrors were explained by a 2-component model at 18 months (43.7% additive genetic effects and 56.3% nonshared environment) and at 30 months (41.5% additive genetic effects and 58.5% nonshared environment). CONCLUSIONS: These results strongly support the heritability of sleep terrors. There also seems to be continuity in genetic effects with the persistence of sleep-terror symptoms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".