Scoping review of complexity theory in health services research

Abstract

BackgroundThere are calls for better application of theory in health services research. Research exploring knowledge translation and interprofessional collaboration are two examples, and in both areas, complexity theory has been identified as potentially useful. However, how best to conceptualize and operationalize complexity theory in health services research is uncertain. The purpose of this scoping review was to explore how complexity theory has been incorporated in health services research focused on allied health, medicine, and nursing in order to offer guidance for future application. Given the extensiveness of how complexity theory could be conceptualized and ultimately operationalized within health services research, a scoping review of complexity theory in health services research is warranted.MethodsA scoping review of published research in English was conducted using CINAHL, EMBASE, Medline, Cochrane, and Web of Science databases. We searched terms synonymous with complexity theory.ResultsWe included 44 studies in this review: 27 were qualitative, 14 were quantitative, and 3 were mixed methods. Case study was the most common method. Long-term care was the most studied setting. The majority of research was exploratory and focused on relationships between health care workers. Authors most commonly used complexity theory as a conceptual framework for their study. Authors described complexity theory in their research in a variety of ways. The most common attributes of complexity theory used in health services research included relationships, self-organization, and diversity. A common theme across descriptions of complexity theory is that authors incorporate aspects of the theory related to how diverse relationships and communication between individuals in a system can influence change.ConclusionComplexity theory is incorporated in many ways across a variety of research designs to explore a multitude of phenomena.. Although complexity theory shows promise in health services research, particularly related to relationships and interactions, conceptual confusion and inconsistent application hinders the operationalization of this potentially important perspective. Generalizability from studies that incorporate complexity theory is, therefore, difficult. Heterogeneous conceptualization and operationalization of complexity theory in health services research suggests there is no universally agreed upon approach of how to use this theory in health services research. Future research should include clear definitions and descriptions of complexity and how it was used in studies. Clear reporting will aid in determining how best to use complexity theory in health services research.

Systems thinking in public health: a bibliographic contribution to a meta-narrative review

“…While there has been much ontological adaptation and some competing metaphysical discussion, we note a paucity of empirical public health research validating, refining or refuting these mental constructs within the dataset. This finding is corroborated in similar recent reviews (Carey et al 2015;Sturmberg et al 2014;Thompson et al 2016) Certainly the study of complex systems to generate 'knowledgeabout-systems' is not a novel pursuit, with decades of empirical research and theoretical development improving our understanding based on specific underlying perspectives predominantly relating to network structures and dynamics at the social scale. More recently, scientists have proposed refinements to modelling methods and devised novel approaches conducive to studying complex social systems.…”

“…Its adoption by a multilateral global institution such as the WHO has enabled greater variation in research environments which have until recently been dominated by micro-meso scale study in Western health systems. As researchers explore combinations of borrowed systems approaches to study aspects such as agents, structure, signals, dynamics, boundaries, scale, time and degree of complexity from multiple perspectives, the framework will evolve further to its adapted context in public health and may contribute to a more generalizable mental model or theory of Systems Thinking (Cabrera et al 2008) Our broad yet superficial inductive approach to bibliographically visualize the development of Systems Thinking is one of the several recent reviews attempting to explore this literature (Carey et al 2015;Sturmberg et al 2014;Thompson et al 2016) While others have reviewed the application of 'complexity theory' or 'systems sciences' to particular fields such as Health Services Research or Primary Care, our 'Systems Thinking' review differed most significantly in its methodology and broad scope. However, we were unable to conduct a full interdisciplinary meta-narrative content review.…”

Complex systems, explanation and policy: implications of the crisis of replication for public health research

“…Despite this attention, it is not at all clear how studies should best report their definitions and use of complexity (Thompson, Fazio, Kustra, Patrick, & Stanley, 2016). Pre-specified analysis plans have been crucial in improving the conduct of clinical trials, but when applied to complex systems do not provide details of analytical simplifications, so there is considerable scope for overt and cryptic multiplicity.…”

“…Recent reviews of research using complexity theory have criticised the lack of mathematical models. We are wary of deterministic mathematical models reintroducing old statistical problems, but microsimulation, also called agent-based modelling, a technique from economics, offers a very flexible framework that could help with understanding and explaining patterns in complex systems (Greenwood-Lee et al, 2016;Thompson et al, 2016).…”

Research on the Application of Intelligent Calibration Device for Nuclear Power Plants Based on Wireless Sensor Technology

“…A wireless sensor network (WSN) has important applications, such as remote environmental monitoring and target tracking. Such applications have been enabled by the recent availability of sensors that are considerably small, inexpensive, and intelligent [2]. One of the fundamental issues in networks is coverage, thereby reflecting that a network is monitored or tracked by sensors.…”