158 Chapter 7 Complex systems theory Complex systems theory1, on the other hand, does provide a framework that can be empirically studied at the individual level. Table 1 contrasts the core assumptions of complex systems theory versus traditional component-dominant theories and how theoretical principles (explicitly or implicitly) guided the various chapters. In short, complex systems principles prioritize an understanding of the dynamics of interdependent components. This theoretical framework poses no overarching architecture of interconnected behavioral components, but instead suggests a set of nomothetic principles of change that leads to highly idiographic change patterns (Olthof et al., 2023). The framework is largely derived from other scientific disciplines, making it an interdisciplinary theory of how complex systems change over time. All living beings are complex systems, from bacteria to ant colonies to ecosystems. Yet also many non-living systems, like the weather, financial markets, or the internet, are all examples of complex systems. What all complex systems have in common is that they have numerous interdependent components that interact with each other over time, leading to the emergence of stable patterns and changes that can be described with the same ontology. Strange as it may sound, social scientists interested in behavioral change (of people with a mild intellectual disability), may learn from how ecologists understand the change of a population of fish in a pond or how meteorologists monitor and predict the weather. 1 In Chapter 5 we refer to the theorem as dynamic systems theories while in Chapter 6 we label it complex systems theory. Dynamic- and complex systems theory are two sides of the same coin.
RkJQdWJsaXNoZXIy MTk4NDMw