Risk for Childhood Internalizing and Externalizing Behavior Problems in the Context of Prenatal Alcohol Exposure: A Meta‐Analysis and Comprehensive Examination of Moderators
Bibliographic record
Abstract
Prenatal alcohol exposure (PAE) is associated with a constellation of physical, neurocognitive, and behavioral abnormalities in offspring. The presence of internalizing (e.g., anxiety, mood disorders) and externalizing (e.g., oppositional defiant and conduct disorders) behavior problems has devastating and often long-lasting impacts on children, adolescents, and their families. The present meta-analysis explored the strength of the association between PAE and behavior problems, as well as factors that increase or mitigate risk. The current meta-analysis included 65 studies comparing children and adolescents with PAE to non- or light-exposed controls and attention-deficit/hyperactivity disorder (ADHD) samples, on a variety of internalizing and externalizing behavior outcomes. Results indicated that individuals with PAE are at increased risk for internalizing (d = 0.71, medium effect) and externalizing (d = 0.90, large effect) problems compared to control samples. The occurrence of total behavior problems was similar to that seen in ADHD samples. The strength of the association between internalizing and externalizing behavior problems and PAE was significantly moderated by several distinct sample characteristics, such as sample age, socioeconomic status, severity of exposure, and type of behavior problem. These findings further our understanding of the behavior problems experienced by children and adolescents with PAE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.038 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".