A Review of Social Skills Deficits in Individuals with Fetal Alcohol Spectrum Disorders and Prenatal Alcohol Exposure: Profiles, Mechanisms, and Interventions
Bibliographic record
Abstract
BACKGROUND: Individuals gestationally exposed to alcohol experience a multitude of sociobehavioral impairments, including deficits in adaptive behaviors such as social skills. METHODS: The goal of this report is to critically review research on social skills deficits in individuals with prenatal alcohol exposure, including individuals with and without fetal alcohol spectrum disorders (FASD). RESULTS: Social deficits are found in alcohol-exposed children, adults, and adolescents with and without a clinical presentation. These deficits tend to persist across the lifespan and may even worsen with age. Social deficits in this population appear to be independent of facial dysmorphology and IQ and are worse than can be predicted based on atypical behaviors alone. Abnormalities in neurobiology, executive function, sensory processing, and communication likely interact with contextual influences to produce the range of social deficits observed in FASD. CONCLUSIONS: Future investigations should strive to reconcile the relationship between social skills deficits in FASD and variables such as gender, age, cognitive profile, and structural and functional brain impairments to enable better characterization of the deficits observed in this population, which will enhance diagnosis and improve remediation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".