Child behavior and maternal depressive mood during toddlerhood predict child adjustment after school entry
Bibliographic record
Abstract
The aim of this 5-wave, multimethod, multi-informant study was to examine the longitudinal associations between child disruptive behavior and maternal depressive mood in toddlerhood. Adopting a transactional perspective on developmental psychopathology, the predictive value of these risk factors for child internalizing and externalizing problem behavior after school entry was investigated using multivariate latent growth curve modeling. The sample consisted of 162 toddlers (mean age 30 months), their mothers and teachers. Observed child disruptive behavior and self report of maternal depressive mood showed interrelated change. Level and growth in child disruptive behavior during toddlerhood predicted teacher’s report of both externalizing and internalizing problem behavior at school entry. Maternal depressive mood during toddlerhood showed a unique effect on child externalizing problems. The importance of targeting maternal depressive mood as well as toddlerhood disruptive behavior in preventive interventions in early childhood is emphasized.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".