Let's put a person back into Cyber-Physical-Social research: Public Mental Models Framework

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Abstract

In the current paper our focus is on linking Public Mental Models with behavior, Situation Awareness and stress management, with predicting and intervening in public behavior in critical situations. Understanding and influencing behavior within complex Cyber-Physical-Social Systems (CPSS) requires an explicit link between mental models, behavior, situation awareness, and stress management. This paper introduces the Public Mental Models Framework (PMMF) as a systematic approach for analyzing and predicting public behavior in critical situations, thereby improving adaptive decision-making and person—AI collaboration. The PMMF explains how internal and external indicators such as cognitive, social, cultural, political, economic, and technological, that shape perception and behavioral responses across multiple levels: individual, team, organizational, community, and societal. By identifying these triggers and markers, the framework supports why behaviors deviate or stabilize under stress, providing an analytical basis for targeted interventions and resilience-oriented design. In contrast to traditional Situation Awareness models that emphasize what is perceived and how it is processed, PMMF focuses on the interpretive mechanisms through which actors construct meaning and make decisions. Integrating PMMF with the Motivation-Opportunity-Ability (MOA) theory enables systematic assessment of behavioral potential and performance within CPSS. This integration strengthens the neuroergonomic foundation for evaluating human and AI entities and enhances the capacity to design interventions that foster informed, adaptive, and ethically aligned behavior in complex sociotechnical environments.

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APA

Teichmann, M., Kaugerand, J., Meriste, M., & Rannat, K. (2025). Let’s put a person back into Cyber-Physical-Social research: Public Mental Models Framework. Frontiers in Neuroergonomics. Frontiers Media SA. https://doi.org/10.3389/fnrgo.2025.1520434

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