Complexity science education for clinical nurse researchers

Nurse researchers-in-training learn that traditional research methods aligning with the positivist paradigm are suitable for evaluating the effects of clinical interventions. Preferred research methods (such as the randomized controlled trial) are based on assumptions that linear cause-and-effect relationships are discoverable through careful manipulation of variables under controlled conditions. Yet clinical intervention trials in practice are much more often done in environments which are in constant states of flux, with dynamic and unpredictable variables rather than settings where uniformity and control are routine. Graduate nursing programs should expose students with interests in clinical research to methods that will enable them to make sense of how to evaluate clinical interventions in real world conditions. In this paper, we discuss the relevance of concepts from the field of Complexity Science-with a focus on Complex Adaptive Systems-to clinical research and examine their potential value to guide nursing research that informs evidence-based nursing interventions. We argue that the introduction of these concepts into graduate nursing curricula is fundamental to the preparation of future nurse scientists who will address the complex healthcare problems of this century.