Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heterogeneous neurodevelopmental disorder prevalent in childhood. Traditional symptom-oriented diagnosis and intervention models lack targeted efficacy due to insufficient coverage of individual differences in biological mechanisms, cognitive functions, environmental interactions, and developmental trajectories. Precision subtyping is key to addressing this dilemma, as it locks in core pathological dimensions and individual characteristics to inform personalized interventions. The Research Domain Criteria (RDoC) framework proposed by the National Institute of Mental Health (NIMH)-featuring six core domains (Arousal/Regulatory Systems, Positive Valence Systems, Sensorimotor Systems, Negative Valence Systems, Cognitive Systems, Social Processes), environmental interaction, and lifespan development-breaks the limitations of traditional diagnostic classifications and provides a standardized, cross-level scientific paradigm for ADHD precision assessment and subtyping. This review systematically summarizes the necessity of ADHD precision subtyping and its intrinsic link to efficient interventions, elaborates on RDoC’s core concepts and adaptability for ADHD assessment, and examines the rationality and application of existing objective assessment methods (neuroimaging, neurophysiology, behavioral-cognitive paradigms, biomarkers, etc.) based on RDoC’s six core domains. Furthermore, it outlines the construction path of a comprehensive ADHD assessment system under RDoC, including multimodal data integration, AI-driven dynamic subtyping, and environment-development interaction assessment. Finally, targeted intervention schemes addressing core domain deficits and adapting to environmental/developmental stages are proposed, and the practical value of the “assessment-subtyping-intervention-reassessment” closed-loop model in improving ADHD intervention efficacy is discussed. This review provides theoretical references for the precision prevention and treatment of childhood ADHD, brain health development, and related clinical/educational practices. • Integrates RDoC’s six core domains to address ADHD heterogeneity, bridging biological and behavioral assessments. • Systematically maps existing ADHD assessment methods to RDoC domains, facilitating method selection and integration. • Proposes a “core domain-environment-development” integrated assessment system with AI-driven subtyping. • Establishes a targeted closed-loop intervention model adapting to children’s developmental characteristics and environmental factors. • Provides actionable insights for translating RDoC-based research into clinical and educational practices for ADHD.
Li et al. (Wed,) studied this question.