Gender differences in autism spectrum disorders: Divergence among specific core symptoms.
The ADI-R may under-score girls, so use extra tools or lower cutoffs when a girl shows subtle ASD signs.
01Research in Context
What this study did
Beggiato et al. (2017) looked at the ADI-R interview scores of the kids with ASD.
They asked: do boys and girls score the same on each item?
They used math called discriminant analysis to spot which items split the sexes.
What they found
Several ADI-R items gave boys higher scores than girls.
This means the same behavior in a girl could earn a lower score.
Lower scores can push girls below the ASD cutoff and out of services.
How this fits with other research
Souza et al. (2023) backs this up. Their big review shows boys have more repetitive behaviors while girls have more intellectual disability.
Wormald et al. (2019) seems to disagree. They used the SRS-2 and found no sex gap in high-functioning kids. The catch: SRS-2 asks teachers, not parents, and only looked at high-IQ kids.
Gotham et al. (2015) adds another layer. In preterm babies, boys still had more extra issues like seizures, while preterm girls were more often nonverbal. Sex differences stay even when birth risk is high.
Why it matters
If you rely only on the ADI-R, girls with milder or different ASD traits may be missed. Add a second tool like the SRS-2 or watch for signs more common in girls, such as social masking or intense interests in people.
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Join Free →When you score an ADI-R for a girl, flag any item where she scores just below the cutoff and double-check with classroom observation or the SRS-2.
02At a glance
03Original abstract
Community-based studies have consistently shown a sex ratio heavily skewed towards males in autism spectrum disorders (ASD). The factors underlying this predominance of males are largely unknown, but the way girls score on standardized categorical diagnostic tools might account for the underrecognition of ASD in girls. Despite the existence of different norms for boys and girls with ASD on several major screening tests, the algorithm of the Autism Diagnosis Interview-Revised (ADI-R) has not been reformulated. The aim of our study was to investigate which ADI-R items discriminate between males and females, and to evaluate their weighting in the final diagnosis of autism. We then conducted discriminant analysis (DA) on a sample of 594 probands including 129 females with ASD, recruited by the Paris Autism Research International Sibpair (PARIS) Study. A replication analysis was run on an independent sample of 1716 probands including 338 females with ASD, recruited through the Autism Genetics Resource Exchange (AGRE) program. Entering the raw scores for all ADI-R items as independent variables, the DA correctly classified 78.9% of males and 72.9% of females (P < 0.001) in the PARIS cohort, and 72.2% of males and 68.3% of females (P < 0.0001) in the AGRE cohort. Among the items extracted by the stepwise DA, four belonged to the ADI-R algorithm used for the final diagnosis of ASD. In conclusion, several items of the ADI-R that are taken into account in the diagnosis of autism significantly differentiates between males and females. The potential gender bias thus induced may participate in the underestimation of the prevalence of ASD in females. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 680-689. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
Autism research : official journal of the International Society for Autism Research, 2017 · doi:10.1002/aur.1715