Disturbing Dreams and Psychosocial Maladjustment in Children: A Prospective Study of the Moderating Role of Early Negative Emotionality
Bibliographic record
Abstract
Although frequent disturbing dreams, including bad dreams and nightmares, have been repeatedly associated with poor psychological well-being in adults, considerably less information exists on their psychosocial correlates in children. Recent empirical and theoretical contributions suggest that the association between disturbing dream frequency and psychosocial adaptation in children may differ as a function of children's negative emotionality. The current study assessed the moderating effect of very early negative emotionality (17 months of age) in the relation between disturbing dream frequency and psychosocial maladjustment (i.e., externalizing + internalizing behaviors) in a sample of 173 11-year-old children. Mixed-model analyses revealed that disturbing dream frequency was associated with some internalizing behaviors but that the association between disturbing dream frequency and most externalizing behaviors was moderated by early negative emotionality. The latter result indicates that the relation between disturbing dream frequency and externalizing behaviors was significant in 11-year-old children showing moderate negative emotionality early in life, but particularly strong in those children with high early negative emotionality. Whereas, a moderating effect of early negative emotionality was not found between disturbing dream frequency and internalizing behaviors, the findings highlight the more specific role of early emotional negativity as a developmental moderator for the link between disturbing dreams and externalizing behaviors in children. The results are discussed in light of recent models of disturbed dreaming production.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".