Developmental cascades to children's conduct problems: The role of prenatal substance use, socioeconomic adversity, maternal depression and sensitivity, and children's conscience
Bibliographic record
Abstract
This study investigated the longitudinal associations among prenatal substance use, socioeconomic adversity, parenting (maternal warmth, sensitivity, and harshness), children's self-regulation (internalization of rules and conscience), and conduct problems from infancy to middle childhood (Grade 2). Three competing conceptual models including cascade (indirect or mediated), additive (cumulative), and transactional (bidirectional) effects were tested and compared. The sample consisted of 216 low-income families (primary caretaker and children; 51% girls; 74% African American). Using a repeated-measures, multimethod, multi-informant design, a series of full panel models were specified. Findings primarily supported a developmental cascade model, and there was some support for additive effects. More specifically, maternal prenatal substance use and socioeconomic adversity in infancy were prospectively associated with lower levels of maternal sensitivity. Subsequently, lower maternal sensitivity was associated with decreases in children's conscience in early childhood, and in turn, lower conscience predicted increases in teacher-reported conduct problems in middle childhood. There was also a second pathway from sustained maternal depression (in infancy and toddlerhood) to early childhood conduct problems. These findings demonstrated how processes of risk and resilience collectively contributed to children's early onset conduct 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".