Social Cognitive and Emotion Processing Abilities of Children With Fetal Alcohol Spectrum Disorders: A Comparison With Attention Deficit Hyperactivity Disorder
Bibliographic record
Abstract
BACKGROUND: Although children with Fetal Alcohol Spectrum Disorders (FASDs) are at high risk of attention deficit hyperactivity disorder (ADHD), direct comparisons show distinct cognitive phenotypes in the 2 diagnoses. However, these groups have not been directly compared for social problems or social cognition, nor has social cognition been directly examined in FASDs. OBJECTIVES: To compare FASDs and ADHD groups on social cognition tasks and determine whether deficient social cognition and emotion processing predict behavioral problems and social skills. METHODS: Studied were 33 children with FASDs, 30 with ADHD, and 34 normal controls (NC). All received tasks of social cognition and emotion processing. Parents and teachers rated children on measures of completed questionnaires assessing child's behavioral problems and social skills using the Child Behavior Checklist, Teacher Report Form, and Social Skills Rating Scale. Children received 3 subtests from the Saltzman-Benaiah and Lalonde (2007) Theory of Mind Task as a measure of social cognition and 4 subtests from the Minnesota Test of Affective Processing (Lai et al., 1991) to assess emotion processing. RESULTS: Parents and teachers reported more behavior problems and poorer social skills in children in FASD and ADHD than NC groups. FASDs demonstrated significantly weaker social cognition and facial emotion processing ability than ADHD and NC groups. Regression analyses identified social cognition as a significant predictor of behavior problems and emotion processing as a significant predictor of social skills. CONCLUSIONS: Children with FASDs show a distinct behavioral profile from children with ADHD. Difficulties in social cognition and emotion processing in children with FASDs may contribute to their high incidence of social behavioral 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".