Response to network analysis highlights need for improved methods in autism-anxiety research, suggesting new variables.
Zaidman-Zait et al. (Child and Adolescent Mental Health, 2025, 30, 327) present a rigorous network analysis of autism characteristics and anxiety symptoms in 623 autistic children across four countries, identifying preference for predictability and sensory hypersensitivity rather than social communication difficulties as the primary bridge nodes linking autistic features to anxiety. We offer three methodological and conceptual extensions. First, the unexpected weakness of the social communication-social anxiety connection may reflect the absence of theory of mind (ToM) and affective social cognition as network nodes: impaired affective ToM independently contributes to social anxiety in clinical adolescent samples and may mediate the social communication-anxiety pathway in ways that parent-reported social communication items cannot capture. Second, while preference for predictability and sensory hypersensitivity are identified as bridge nodes, their underlying mechanisms, intolerance of uncertainty and arousal dysregulation, are not explicitly modelled; including these as network variables would enable direct testing of their bridging function and identify specific intervention targets. Third, the exclusive reliance on parent-report data in a population in which anxiety masking is well documented introduces a systematic informant asymmetry that may distort the network structure. Multi-informant designs incorporating child self-report are essential for accurately mapping autism-anxiety co-occurrence.
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Berkan Şahin (2026) studied this question.
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