Prenatal tobacco exposure and self-regulation in early childhood: Implications for developmental psychopathology
Bibliographic record
Abstract
Prenatal tobacco exposure (PTE) has a well-documented association with disruptive behavior in childhood, but the neurocognitive effects of exposure that underlie this link are not sufficiently understood. The present study was designed to address this gap, through longitudinal follow-up in early childhood of a prospectively enrolled cohort with well-characterized prenatal exposure. Three-year-old children (n = 151) were assessed using a developmentally sensitive battery capturing both cognitive and motivational aspects of self-regulation. PTE was related to motivational self-regulation, where children had to delay approach to attractive rewards, but not cognitive self-regulation, where children had to hold information in mind and inhibit prepotent motor responses. Furthermore, PTE predicted motivational self-regulation more strongly in boys than in girls, and when propensity scores were covaried to control for confounding risk factors, the effect of PTE on motivational self-regulation was significant only in boys. These findings suggest that PTE's impact on neurodevelopment may be greater in boys than in girls, perhaps reflecting vulnerability in neural circuits that subserve reward sensitivity and emotion regulation, and may also help to explain why PTE is more consistently related to disruptive behavior disorders than attention problems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".