The research team, led by Jeremy J. Cottle of Nationwide Children’s Hospital together with colleagues at the University of Alabama at Birmingham, analyzed records from 458 children and adolescents who had been referred for an autism evaluation at a tertiary care clinic between 2013 and 2020. Crucially, the sample included every child referred for assessment, not only those who ultimately received a diagnosis. Of the participants, 118, or 25.8 percent, were female, and 61.6 percent were diagnosed with autism spectrum disorder. The average age was just under seven years. By including children who did not receive an autism diagnosis, the researchers deliberately avoided a common pitfall: studies restricted to diagnosed individuals can systematically exclude the very girls whose presentations current tools fail to capture.

The study focused on the two instruments widely regarded as the gold standard for autism assessment. The Autism Diagnostic Observation Schedule, Second Edition, or ADOS-2, is a semi-structured, play-based observation administered directly to the child by a trained clinician. The Autism Diagnostic Interview, Revised, or ADI-R, is a structured interview conducted with caregivers, drawing on their long-term knowledge of the child’s behavior across settings and years. Both produce scores across domains of social communication and restricted, repetitive behaviors, but they capture autism traits through very different lenses: one through a clinician’s real-time observation, the other through a caregiver’s retrospective report.

To detect bias at the level of individual test items, the team used a statistical technique called multiple indicator multiple cause modeling, or MIMIC. The approach works by first estimating latent variables, in this case underlying traits such as social affect and repetitive behaviors, from the pattern of item scores. It then asks a precise question: does a child’s sex predict how they score on a particular item even after holding their overall level of the underlying trait constant? If so, that item exhibits differential item functioning, meaning it behaves differently for boys and girls beyond what overall trait levels can explain. The researchers converted these effects into odds ratios, flagging differences as meaningful when the ratio exceeded 2.0 or fell below 0.5, and used delta transformations to compare the magnitude of bias across items, domains, and instruments.

The results split cleanly along the two measures. On the ADOS-2, girls did show lower overall levels of restricted and repetitive behaviors than boys, consistent with a large body of prior research. Yet when the researchers probed individual items, they found no differential item functioning at all. No single ADOS-2 item, whether measuring social affect or repetitive behavior, functioned differently for boys and girls once overall trait levels were accounted for. In other words, the observed domain-level sex difference on the ADOS-2 appears to reflect genuine differences in the traits children display during observation, not biased scoring of the instrument itself.

The ADI-R told a different story. Four items showed differential item functioning, spread across all three of the diagnostic content areas the researchers examined. In the social interaction domain, girls were scored higher on inappropriate facial expressions even at the same overall level of social interaction difficulties, an odds ratio of exactly 2.0. In the communication domain, girls were scored lower on spontaneous imitation of actions and imaginative play, with odds ratios of 0.225 and 0.256 respectively, indicating substantially higher endorsement of autistic traits for boys on these items. These two communication items also carried the largest delta values in the study, marking them as the sites of the greatest sex bias. In the repetitive behavior domain, girls were scored lower on circumscribed interests, though this effect narrowly missed the formal threshold for meaningfulness.

Each of these biased items can be interpreted through the leading theories of why autism is missed in girls. The circumscribed interests finding suggests that girls’ intense interests may take forms, such as art, animals, or celebrities, that clinicians do not immediately recognize as unusual, whereas interests in trains or schedules are more readily flagged. Intense interests in dolls or babies may even be mistaken for typical pretend play unless their intensity and peculiarity are explicitly probed. The imaginative play result aligns with the idea that play centered on dolls is more easily labeled as imaginative by caregivers than play with cars or trucks. The imitation finding fits camouflage theory: girls may more often observe and copy peers’ behavior, skills that caregivers notice and that can mask underlying difficulties. The inappropriate facial expressions result, meanwhile, may reflect the perception hypothesis, with caregivers judging girls’ expressions against stricter social expectations.

The contrast between the two instruments carries practical weight. On the ADI-R, males were significantly more likely to receive an autism classification than females, a pattern that did not appear on the ADOS-2. The authors caution that the ADI-R contains more diagnostic items than the subset of ADOS-2 items analyzed, which raises the statistical chance of detecting bias, and that the cross-module comparison excluded some ADOS-2 items that could not be validly compared across versions. Still, the finding that boys were more likely to clear the ADI-R’s diagnostic threshold, combined with item-level bias on that same instrument, suggests that caregiver-report measures may be a specific point where female presentations slip through. The authors note that if the ADI-R is used to determine eligibility for research studies, girls with characteristically female presentations may be disproportionately excluded, reinforcing the male skew of autism research samples.

Notably, the study found no overall sex difference in the likelihood of receiving a clinical autism diagnosis, a result that diverges from earlier research but may reflect growing clinician awareness of female presentations in recent years. The authors also acknowledge limitations: the retrospective clinical data could not examine gender as distinct from sex assigned at birth, could not account for cognitive ability, and spanned a wide age range from two to eighteen years. Some girls who are never referred for evaluation in the first place remain invisible to any clinic-based study.

The implications reach beyond statistics. The authors argue that the findings point toward concrete adaptations, such as guidance for ADI-R interviewers to use gender-balanced prompts and examples when probing interests, play, and imitation, and greater education about the female autism phenotype for everyone involved in referral and diagnosis, from pediatricians and educators to psychologists and caregivers. Even when boys and girls show similar overall levels of autistic traits, the specific ways those traits appear can differ, and diagnostic conversations need to be structured to notice that. As the authors conclude, a well-informed understanding of sex differences in how autism traits are presented and measured is critical for correcting the sex bias that persists in clinics and research alike, and for ensuring that children of both sexes receive accurate identification and the support that follows from it.

Subject of Research: Item-level sex differences in autism diagnostic measurement using ADOS-2 and ADI-R in a referred pediatric sample

Article Title: Item-Level Sex Differences in Autism Spectrum Disorder Measures: A MIMIC Model Analysis of ADOS-2 and ADI-R in a Referred Pediatric Sample

Article References: Cottle, J. J., Arnold, Z. E., Guest, K. C., Mrug, S., Brisendine, A. E., Khatri, S., & O’Kelley, S. E. (2026). Item-Level Sex Differences in Autism Spectrum Disorder Measures: A MIMIC Model Analysis of ADOS-2 and ADI-R in a Referred Pediatric Sample. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-026-07527-6

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07527-6

Keywords: autism spectrum disorder, sex differences, ADOS-2, ADI-R, differential item functioning, MIMIC model, female autism phenotype, diagnostic bias, restricted repetitive behaviors, camouflaging, pediatric assessment, underdiagnosis