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A reliable and valid diagnostic classification system is pivotal for guiding clinical decision-making, facilitating rigorous and reproducible research findings, informing population-level health planning and resource allocation, and promoting well-being. However, the current categorical approaches, while foundational, have inherent limitations, including symptom overlap between diagnostic categories, heterogeneity, instability, unreliability, and a limited capacity to quantify individual variations. We outline several challenges regarding the diagnostic conceptualization of autism and propose how transdiagnostic dimensional alternatives might facilitate a more comprehensive understanding, assessment, and clinical care for this complex clinical condition. Research Domain Criteria and Hierarchical Taxonomy of Psychopathology are two distinct yet complementary dimensional approaches that have garnered the most empirical attention. In this review, we outline the central tenets of each approach in turn and explore their potential applications in enhancing understanding and addressing challenges associated with autism in both research and clinical practice.
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Chetcuti et al. (2025) studied this question.
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