Toward an Energetic Capacity Index in Autism: A Hypothesis-Generating Measurement Framework for Adaptive Reserve, Dynamic Therapeutic Availability, and Intervention Readiness

<jats:p>Autistic individuals often demonstrate substantial within-person variability in regulation, participation, recovery, learning readiness, and responsiveness to intervention across time and contexts. Although sleep disruption, fatigue, autonomic regulation, physiological stress, sensory demands, and recovery processes may contribute to this variability, no validated multidimensional instrument currently measures the dynamic biological and functional resources potentially available for adaptive developmental work. This Hypothesis and Theory article proposes a hypothesis-generating measurement framework for the future development of an Energetic Capacity Index (ECI) in autism. It distinguishes three scientifically separate levels: Energetic Capacity, the underlying translational construct; Estimated Energetic Capacity, a provisional research estimate derived from repeated multimodal observations; and the Energetic Capacity Index, a candidate measurement instrument requiring independent development and validation. A provisional measurement architecture is outlined across candidate domains of physiological regulation, restorative recovery, functional endurance, adaptive availability, and contextual demand. The proposed framework integrates repeated multimodal observations, including caregiver-reported, clinician-observed, behavioral, contextual, and, where feasible, physiological indicators while explicitly rejecting reliance on any single biomarker or isolated observation. The manuscript presents a staged development pathway encompassing conceptual operationalization, feasibility, reliability, construct discrimination, responsiveness, longitudinal sensitivity, fairness, external validation, and responsible digital implementation. The ECI is not presented as a validated scale, biomarker, diagnostic instrument, severity score, predictive algorithm, or clinical decision-support tool. Its scientific contribution will ultimately depend on whether future empirical studies demonstrate operational feasibility, coherent measurement properties, meaningful within-person variability, incremental explanatory value, fairness, and reproducibility across independent populations and settings. Rather than introducing a validated measurement instrument, this work establishes a transparent scientific roadmap for the responsible development of a future multidimensional measure of Energetic Capacity in autism.</jats:p>