Meta-Analysis of Sex Differences in Social and Communication Function in Children With Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
Background: Sex differences in the prevalence of neurodevelopmental disorders such as autism (ASD), attention-deficit hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have been well documented; still studies examining sex differences in social and communication in these disorders remain limited and inconclusive. Methods: Using PRISMA guidelines, a search was performed on studies (2000-2017) examining sex differences in social and communication abilities in ASD, ADHD and OCD compared to controls. Results: Eleven studies met criteria for ASD, 6 studies for ADHD and none met criteria for OCD. No significant sex differences were found between ASD and controls in social (p=0.5), or communication abilities (p=0.5) and between ADHD and controls in social abilities (p=0.7). No studies were identified to evaluate sex differences in communication in ADHD. Significant heterogeneity was noted in all analyses. Type of measure may have partially accounted for some variability between studies. Conclusions: A limited number of studies did not detect sex differences in social and communication abilities in children with ASD and ADHD; however significant heterogeneity was noted. Future larger studies, controlling for type of measure and including adequate numbers of female participants are required to further understand sex differences in these domains.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.024 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".