I teach a course in health behaviour change and one in systems thinking perspectives on public health. Both courses complement each other and both deal with change. However, most of the major theories of behaviour change deal with the subject in a straightforward, linear manner. Models and theories like the Health Belief Model, Theory of Reasoned Action, and Social Cognitive Theory all have elements explicit or implicit to them that suggest change occurs in a largely linear manner from problem state to desired state.
One of the more popular models of change is the Transtheoretical Model, which included the concept of Stages of Change. Developed by James Prochaska and colleagues at the University of Rhode Island (and others), the model has become widely popular and used all over the world to guide change efforts. The problem is that the evidence for its effectiveness, despite the logic it brings with it, is weak.
Robert West, the editor of the journal Addiction, and others, issued a rather stinging set of criticisms against the Transtheoretical Model’s Stages of Change concept, pointing to the evidence that suggests that as many (if not more) people quit smoking or behaviors like that with no apparent plan in place. “It just happened” .
Indeed, the data suggests that Stages of Change is not that strong as a predictor of eventual change, yet its popularity suggests something that goes beyond evidence. At its root is the idea of “ready, set, go” and taps into our deep-seated interests in making plans and moving ahead in a straightforward manner. In short, it fits linear thinking to a tee.
Over time, proponents of the Stages of Change theory and related models and theories have asserted that people do move forwards and backwards through the stages and that it is not simply a one-way view of change, but in both cases the end is still some form of linear trajectory.
What makes behaviour change theories like the TTM and others problematic from the perspective of complexity is that they are linear. Yet, linearity is the way we define the problems in the first place. These theories are all based on some form of cognitive-rational foundation that take at its core the idea that information is the starting point for change and that the way information is perceived and worked through will serve as a touchpoint for further motivational activities.
What is embedded within this assumption is the idea that, once configured, information is organized in a relatively stable, consistent manner. What it does not do is account for the ways in which our memories, circumstance, situation, and the addition of new information can only only change what we know, but also the way in which we know it. Thus, recombination of information leads to new insights and activities, not all of which are necessarily in support of the trajectory that was initiated.
Richard Resincow and Scott Page start to probe some of this terrain in their article published a couple of years ago looking at quantum change. The article, which was widely discussed, challenges the very notion that the approach we take to behaviour change is misaligned with much of what we know about complex adaptive systems. And to this end, the human mind and body is indeed a complex adaptive system in many respects. Certainly our social worlds fit this description.
If this is the case, and we take this idea that recombination of information can and does occur, it has profound implications for how we develop social institutions and the way in which we support individuals looking to make changes. It means not expecting that changes will stay in place, but rather always anticipating the possibility that something might shift and dramatic transformations could occur.
Flexible strategies, adaptive strategies and those that attend to context and the constant, dynamic flow of information are those that will provide more useful models for change in this worldview. It might now repudiate the models we use now, but it certainly casts new light on the directionality of change that they invoke. And in simply shifting those arrows around, we open possibility for understanding change in a wider way that might eventually lead us to one that takes complexity into account more fully, and learning.