This article explores the potential of complex adaptive systems (CAS) theory to inform behaviour change research. A CAS describes a collection of heterogeneous agents interacting within a particular context, adapting to each other’s actions. In practical terms, this implies that behaviour change is (1) socially and culturally situated; (2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and (3) determined by multiple components interacting ‘chaotically’. Two approaches to studying CAS are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate ‘what if’ questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods – for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of CAS offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.

本文探讨了复杂自适应系统（CAS）理论为行为改变研究提供信息的潜力。CAS描述了在特定上下文中交互并适应彼此的动作的异构代理的集合。实际上，这意味着行为改变是（1）在社会和文化上所处的位置；（2）对个体，群体和干预成分的细微基线差异高度敏感；（3）由“混沌”相互作用的多个成分决定。简要回顾了两种研究CAS的方法。基于代理的建模是一种计算机仿真技术，可让研究人员研究虚拟环境中的“假设”问题。另一方面，应用的定性研究技术提供了一种方法，可以检查实时采取干预措施时会发生什么情况，并确定支配社会行为的各种规则和假设。尽管这些方法代表了非常不同的复杂性方法，但是可能存在混合使用这些方法的余地-例如，通过在定性野外工作得出的见解中建立模型基础。最后，我将认为CAS的概念提供了一个机会，可以加深对健康相关行为的理解，并研究产生促进健康或破坏健康行为的社会心理过程。