Toward an Emergent Paradigm for Neurodiversity and Health

Autism research has developed through multiple paradigms. Medical models locate difficulty within individual neurology, while social and neurodiversity models emphasize environmental barriers and the legitimacy of cognitive variation. Biopsychosocial and hybrid approaches integrate these perspectives, recognizing that biological, psychological, and social factors all matter. Yet these frameworks remain largely descriptive and offer limited accounts of how these domains dynamically interact across development to produce the wide heterogeneity observed in autistic experience and adult outcomes. This paper introduces the Evolutionary Stress Framework (ESF), a complexity-based model that reframes neurodevelopmental variation as the emergent outcome of stress–energy regulation and predictive processing over time. Drawing on stress physiology, adaptive calibration theory, predictive processing, and disability scholarship, we review traditional medical, social, biopsychosocial, and hybrid models; examine the contributions and limits of the neurodiversity paradigm; and articulate ESF’s core constructs: emergent neurotypes, stress incoherence, and emergent allostasis. Within ESF, autistic traits function as coherent, context-dependent stress–energy strategies rather than separable strengths and deficits. ESF conceptualizes pathology not as deviation from a normative baseline but as stress incoherence—states in which long-standing calibrations become unsustainable under current environmental conditions. This framework helps explain heterogeneity, developmental change, the clustering of physical and mental health conditions, and the disproportionate burden of burnout and health disparities observed in autistic adulthood. ESF shifts intervention targets from trait suppression to environmental design, co-regulation, and individualized support organized around bio-neurotype–specific regulatory needs. We outline implications for research, clinical practice, and policy and identify directions for empirically operationalizing ESF constructs.