Modeling Psychopathology: From Data Models to Formal Theories

Translational Abstract Over the last decade, there has been a surge of empirical research investigating mental disorders as networks of interacting symptoms. This rapidly growing empirical literature has raised a critical question: How can we best make use of these empirical findings to achieve our aim of explaining, predicting, and controlling mental disorders? In this article, we argue that achieving these aims requires the construction of formal theories and we investigate how empirical research can best inform the construction of well-developed formal theories. We begin by reviewing the philosophy of science literature to clarify the nature of formal theories, data models, and the relationship between them. We identify three plausible ways in which empirical data models can be used to develop formal theories. In the first, data models are treated as formal theories. In the second, data models are used to make direct inferences about the real world and, thereby, inform the development of a formal theory. In the third, the empirical data model is compared to a theory-implied data model, and any differences between them is used to inform subsequent theory development. Using simulations from a computational model of panic disorder, we investigate which of these three routes best informs the development of formal theories of psychopathology and conclude that the third approach is most promising. We then build on this evaluation by proposing the abductive formal theory construction (AFTC) framework: a three-stage framework rooted in abductive inference and the comparison between theory-implied and empirical data models. We argue that this approach provides a challenging, yet promising way forward for using empirical research to construct formal theories. Over the past decade, there has been a surge of empirical research investigating mental disorders as complex systems. In this article, we investigate how to best make use of this growing body of empirical research and move the field toward its fundamental aims of explaining, predicting, and controlling psychopathology. We first review the contemporary philosophy of science literature on scientific theories and argue that fully achieving the aims of explanation, prediction, and control requires that we construct formal theories of mental disorders: theories expressed in the language of mathematics or a computational programming language. We then investigate three routes by which one can use empirical findings (i.e., data models) to construct formal theories: (a) using data models themselves as formal theories, (b) using data models to infer formal theories, and (c) comparing empirical data models to theory-implied data models in order to evaluate and refine an existing formal theory. We argue that the third approach is the most promising path forward. We conclude by introducing the abductive formal theory construction (AFTC) framework, informed by both our review of philosophy of science and our methodological investigation. We argue that this approach provides a clear and promising way forward for using empirical research to inform the generation, development, and testing of formal theories both in the domain of psychopathology and in the broader field of psychological science.

Automated summary

Over the last decade, empirical research has increasingly focused on mental disorders as complex systems. This article explores how to utilize this research to advance the field towards explaining, predicting, and controlling psychopathology. The authors propose that constructing formal theories of mental disorders is essential, and suggest using empirical data models to inform the development of these theories, with the comparison of empirical and theory-implied data models being the most promising approach. The introduction of the abductive formal theory construction (AFTC) framework provides a clear and promising pathway forward for using empirical research to inform the development and testing of formal theories in psychopathology and psychology more broadly.