Bell IR, Koithan M, Pincus D. Research methodological implications of nonlinear dynamical systems models for whole systems of complementary and alternative medicine. Forsch Komplementarmed Klass Naturheilkd 2012, 19(Supplement 1):15–21.
This paper focuses on the worldview hypotheses and research design approaches from nonlineardynamical complex systems (NDS) science that can inform future studies of whole systems ofcomplementary and alternative medicine (WS-CAM), e.g., Ayurveda, traditional Chinese medicine,and homeopathy. The worldview hypotheses that underlie NDS and WS-CAM (contextual, organismic, interactive-integrative – Pepper, 1942) overlap with each other, but differ fundamentally from those of biomedicine (formistic, mechanistic). Differing views on the nature of causality itself lead to different types of study designs. Biomedical efficacy studies assume a simple direct mechanistic cause-effect relationship between a specific intervention and a specific bodily outcome, an assumption less relevant to WS-CAM outcomes. WS-CAM practitioners do not necessarily treat a symptom directly. Rather, they intervene to modulate an intrinsic central imbalance of the person as a system and to create a more favorable environmental context for the emergence of health, e.g., with dietary changes compatible with the constitutional type. The rebalancing of the system thereby fosters the emergence of indirect, diffuse, complex effects throughout the person and the person’s interactions with his/her environment. NDS theory-driven study designs thus have the potential for greater external and model validity than biomedically driven efficacy studies (e.g., clinical trials) for evaluating the indirect effects of WS-CAM practices. Potential applications of NDS analytic techniques to WS-CAM include characterizing different constitutional types and documenting the evolution and dynamics of whole-person healing and well-being over time. Furthermore, NDS provides models and methods for examining interactions across organizational scales, from genomic/proteomic/metabolomic networks to individuals and social groups.