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Purpose Health resilience has become a critical concern for socio-technical systems facing demographic aging, social vulnerability and public health shocks. However, existing studies often treat resilience as a localized or static outcome, overlooking its hierarchical structure and regulatory logic across governance levels. From a cybernetics perspective, resilience is better understood as an adaptive system shaped by cross-level control and feedback mechanisms. This study aims to conceptualize health resilience as a hierarchical cybernetic system and to examine how upper-level governance capacity conditions local adaptive performance. Design/methodology/approach A multilevel analytical framework grounded in cybernetics and systems theory is developed to capture hierarchical control and variance transmission within health systems. Using data from 368 townships nested within 22 counties, a multi-level mixed-effects structural equation model is employed to integrate healthcare capacity, social vulnerability and demographic indicators into a unified latent resilience system. The framework decomposes total variance into within- and between-level components and estimates cross-level transmission strength to identify the stabilizing role of upper-level governance structures. Findings The empirical results reveal a pronounced hierarchical control effect, indicating that approximately two-thirds of township-level health resilience is structurally conditioned by county-level characteristics. Healthcare infrastructure functions as the dominant stabilizing component of the system, while social vulnerability and demographic aging increase system sensitivity and local volatility. Interpreted through a cybernetic lens, the findings demonstrate that health resilience operates as a regulated adaptive system in which higher-level governance dampens local fluctuations and contributes to systemic stability. Originality/value This study advances cybernetics and systems research by operationalizing health resilience as a hierarchical adaptive system rather than a purely local or statistical construct. By empirically identifying cross-level control strength and variance propagation within a socio-technical health system, the proposed framework provides a novel application of cybernetic principles to resilience analysis and offers a transferable approach for studying hierarchical regulation in other complex social systems.
Chich‐Ping Hu (Mon,) studied this question.