Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder

The network theory of psychopathology posits that mental disorders are systems of mutually reinforcing symptoms. This framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. Cognitive behavioral theories of mental disorders provide considerable insight into how these systems may operate. However, the development of cognitive behavioral theories has itself been stagnant in recent years. In this article, we advance both theoretical frameworks by developing a network theory of panic disorder rooted in cognitive behavioral theory and formalized as a computational model. We use this computational model to evaluate the theory's ability to explain five fundamental panic disorder-related phenomena. Our results demonstrate that the network theory of panic disorder can explain core panic disorder phenomena. In addition, by formalizing this theory as a computational model and using the model to evaluate the theory's implications, we reveal gaps in the empirical literature and shortcomings in theories of panic disorder. We use these limitations to develop a novel, theory-driven agenda for panic disorder research. This agenda departs from current research practices and places its focus on (a) addressing areas in need of more rigorous descriptive research, (b) investigating novel phenomena predicted by the computational model, and (c) ongoing collaborative development of formal theories of panic disorder, with explanation as a central criterion for theory evaluation. We conclude with a discussion of the implications of this work for research investigating mental disorders as complex systems.