Hybrid Modeling of Anxiety Propagation in Response to Threat Stimuli Flow
Abstract
:1. Introduction
2. Background: Cognitive Model of Anxiety
2.1. Anxiety Reactions
2.2. The Cycle of Anxiety in the Cognitive Model
3. Materials and Methods
3.1. The Sentiment Analysis for Measuring Triggering Stimuli Flow
3.2. Multi-Method Modeling Approach
3.3. Anxiety Scales and Datasets Used
4. Results
4.1. Multi-Agent Modeling of the Anxiety Propagation
4.1.1. Model Formulation
4.1.2. Model Refinement
4.2. Compartmental Modeling
4.2.1. Mathematical Model of Anxiety Propagation
4.2.2. Applied System Dynamics Model
5. Discussion and Conclusions
Practical Implications
6. Limitations and Future Directions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Sakalauskas, L.; Denisov, V.; Dirzyte, A. Hybrid Modeling of Anxiety Propagation in Response to Threat Stimuli Flow. Mathematics 2023, 11, 4121. https://doi.org/10.3390/math11194121
Sakalauskas L, Denisov V, Dirzyte A. Hybrid Modeling of Anxiety Propagation in Response to Threat Stimuli Flow. Mathematics. 2023; 11(19):4121. https://doi.org/10.3390/math11194121
Chicago/Turabian StyleSakalauskas, Leonidas, Vitalij Denisov, and Aiste Dirzyte. 2023. "Hybrid Modeling of Anxiety Propagation in Response to Threat Stimuli Flow" Mathematics 11, no. 19: 4121. https://doi.org/10.3390/math11194121