ArticlePsychological medicine2025
Integrating causal discovery and clinically-relevant insights to explore directional relationships between autistic features, sex at birth, and cognitive abilities.
Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Computerized Adaptive Tests for Rapid and Accurate Assessment of Autism.JAMA network open · 2026Article
- Causal Discovery in Observational Medical Research: Scoping Review.JMIR medical informatics · 2026Article
- Healthcare professionals' experiences of participating in withdrawing life-sustaining treatment decisions in a Chinese intensive care unit: a qualitative study.BMC medical ethics · 2025Article
- Integrating causal discovery and clinically-relevant insights to explore directional relationships between autistic features, sex at birth, and cognitive abilities - ERRATUM.Psychological medicine · 2025Article
Corrections and comments
- Erratum issued
- Update of
Authors and funding
8 authors.
Funding
Abstract
backgroundAccess to "big data" is a boon for researchers, fostering collaboration and resource-sharing to accelerate advancements across fields. Yet, disentangling complex datasets has been hindered by methodological limitations, calling for alternative, interdisciplinary approaches to parse manifold multi-directional pathways between clinical features, particularly for highly heterogeneous autism spectrum disorder (ASD). Despite a long history of male-bias in ASD prevalence, no consensus has been reached regarding mechanisms underlying sex-related discrepancies.
methodsApplying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a well-characterized sample (http://sfari.org/simons-simplex-collection) of autistic males (N = 2175, Age = 8.9 ± 3.5 years) and females (N = 334, Age = 9.2 ± 3.7 years). Expert clinical review of exploratory factor analysis (EFA) results yielded factors of interest in sensory, social, and restricted and repetitive behavior domains. To offset inherent confounds of sample imbalance, we identified a comparison subgroup of males (N = 331) matched to females (by age, IQ). We applied data-driven causal discovery analysis (CDA) using Greedy Fast Causal Inference (GFCI) on three groups (all females, all males, matched males). Structural equation modeling (SEM) extracted measures of model-fit and effect sizes for causal relationships between sex, age-at-enrollment, and IQ on EFA-determined factors.
resultsWe identified potential targets for intervention at nodes with mediating or indirect effects. For example, in the female and matched male groups, analyses suggest mitigating RRB domain behaviors may lead to downstream reductions in oppositional and self-injurious behaviors.
conclusionsOur investigation unveiled sex-specific directional relationships that inform our understanding of differing needs and outcomes associated with biological sex in autism and may serve to further development of targeted interventions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.