Sex-Related Measurement Bias in Autism Spectrum Disorder Symptoms in the Baby Siblings Research Consortium
Bibliographic record
Abstract
Importance: Disparities exist in age of diagnosis and prevalence of autism spectrum disorder (ASD) for female compared with male children. Correcting for sources of bias is critical for improving equitable ASD identification. Objective: To determine whether sex differences exist in measurement of ASD symptoms using the Autism Diagnostic Observation Schedule (ADOS) among young children at high familial likelihood (HFL) and low familial likelihood (LFL) of ASD. Design, Setting, and Participants: This cohort study collected longitudinal, prospective data from the Baby Siblings Research Consortium between January 1, 2003, and December 31, 2021. Participants included 3106 children who had an older sibling with ASD (HFL group) and 1444 without (LFL group). Data from as many as 3 visits when participants were aged 20 to 40 months were included. Analysis occurred between March 1, 2023, and May 29, 2025. Exposures: Child sex and age and ASD diagnosis. Main Outcomes and Measures: Measurement invariance by sex and age was examined across item-level ADOS data. Diagnostic group and sex differences were then examined using mixed-effect models on corrected scores. Results: Repeated visits (n = 7557) from 4550 participants (2548 [56.0%] male) were included, of whom 1444 (31.7%) were in the LFL and 3016 (68.3%) in the HFL groups. Confirmatory factor analysis indicated social communication and restricted and repetitive behaviors models fit the data well in the HFL group but poorly in the LFL group. In the HFL group, females were rated as less impaired in eye contact (differential item functioning estimate [SE] = 0.088 [0.033]; P = .01), and their response to joint attention (differential item functioning estimate [SE] = 0.290 [0.105]; P = .01) and quality of social overtures (differential item functioning estimate [SE] = 0.053 [0.019]; P = .005) was associated with less underlying social communication difficulties compared with males. Adjusting for differential item functioning by age and sex resulted in moderate levels of measurement differences. Females showed milder autistic traits than males, although this gap was smaller in the participants diagnosed with ASD. Conclusions and Relevance: Sex differences exist in the general population in many social communication traits, yet ASD diagnostic thresholds do not account for these sex differences. Future instrument development, as well as clinician training, should acknowledge milder presentation (fewer difficulties with eye contact or quality of social impairments) in many females. This may help identify developmental differences earlier and improve outcomes for autistic females (estimate [SE] = -0.160 [0.061]; P = .009).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".