Primary Health Care Case Management Through the Lens of Complexity: an Exploratory Study of Naturopathic Practice Using Complexity Science Principles

BackgroundAdvances in systems science creates an opportunity to bring a complexity perspective to health care practices and research. While medical knowledge has greatly progressed using a reductionist and mechanistic philosophy, this approach may be limited in its capacity to manage chronic and complex illness. With its holistic foundation, naturopathy is a primary health profession with a purported alignment with a complexity perspective. As such this pilot study aimed to investigate the application of complexity science principles, strategies, and tools to primary health care using naturopathy as a case study.MethodsA network mapping and analysis of the naturopathic case management process was conducted. Mind maps were created by naturopathic practitioners to reflect their clinical conceptualisation of a common paper clinical case. These mind maps were inputed into Gephi, a network mapping, exploration, and analysis software. Various layouts of the data were produced, and these were analysed using exploratory data analysis and computational network analysis.ResultsSeven naturopathic practitioners participated in the study. In the combined network mapping, 133 unique elements and 399 links were identified. Obesity, the presenting issue in the case, was centrally located. Along with obesity, other keystone elements included: systemic inflammation, dysbiosis, diet, the liver, and mood. Each element was connected on average to 3.05 other elements, with a degree variation between one and 36. Six communities within the dataset were identified, comprising: the nervous system and mood, gastroinstetinal and dietary factors, systemic inflammation and obesity, the endocrine system and metabolism.ConclusionsThis pilot study demonstrates that it is feasible to apply a complexity science perspective to investigating primary health care case management. This supports a shift to viewing the human organism as a complex adaptive system within primary health care settings, with implications for health care practices that are more cognisant with the treatment of chronic and complex conditions and research opportunities to capture the complex clinical reasoning processes of practitioners.

The Concept of Complexity in Philosophical Contexts: Semantic and Pragmatic Specifics

The present research featured the content of complexity in philosophical contexts in the aspects of its validity, consistency, and compliance with the pragmatics of philosophical comprehension of reality. The article considers both explicit and implicit attempts to define complexity as a philosophical concept. The author addressed the validity of using the term complexity in a philosophical context by standardizing its meaning, i.e. building a pattern in accordance with the basic linguistic denotations of this concept. A review of its ontological and epistemological use made it possible to identify some cases of redundancy, unreasonableness, and semantic shift. The article introduces some possible ways of using the concept of complexity. The limited implementation of its epistemic function makes it possible to establish the boundaries of its applicability. The concept of complexity is important for metaphysics; however, such ideas as "metaphysics of complexity", "ontology of complexity", or "epistemology of complexity" have no ground. The article also provides a comparative analysis of the concept of complexity in specific scientific and philosophical contexts. Based on the revealed discrepancies in its interpretation, the author speculates whether the so-called philosophy of complexity can act as a context for understanding the philosophical problems of complexity science with its ambiguous nature.

Inferring the connectivity of coupled chaotic oscillators using Kalman filtering

Inferring the interactions between coupled oscillators is a significant open problem in complexity science, with multiple interdisciplinary applications. While the Kalman filter (KF) technique is a well-known tool, widely used for data assimilation and parameter estimation, to the best of our knowledge, it has not yet been used for inferring the connectivity of coupled chaotic oscillators. Here we demonstrate that KF allows reconstructing the interaction topology and the coupling strength of a network of mutually coupled Rössler-like chaotic oscillators. We show that the connectivity can be inferred by considering only the observed dynamics of a single variable of the three that define the phase space of each oscillator. We also show that both the coupling strength and the network architecture can be inferred even when the oscillators are close to synchronization. Simulation results are provided to show the effectiveness and applicability of the proposed method.

All the King’s Horses and all the King’s Men: International anti-corruption discourse, political economy analysis and assemblage theory

<p>Corruption emerged as a key issue area in international relations and development in the 1990s. However, efforts to control corruption have, to date, been relatively unsuccessful. This has prompted international organisations, like the World Bank, to acknowledge that corruption is a political issue as much as it is an economic one. This shift has led to an increasing use of political economy analysis to inform the anticorruption and governance reform operations of international organisations. This thesis examines political economy analysis as a feature of the expertise housed in the World Bank. It argues that because anti-corruption and governance expertise is essential to the legitimate authority of the organisation, there are risks to that authority if World Bank experts are unable to provide more than highly conventional recommendations for tackling corruption in developing countries. Commentators on development practice have suggested that integrating concepts from complexity science into political economy analysis and adopting an “upside-down” approach to development might be useful to help generate new ideas for controlling corruption. However, this thesis argues that in order to do so, it is necessary to address the philosophical implications of complexity science for mainstream anti-corruption discourse, which is dominated by the positivist assumptions of neo-classical economics. To this end, the thesis argues that Manuel DeLanda’s assemblage theory offers a social ontology in which the relevance of complexity science concepts for social analysis can be developed, and a way of thinking that emphasises how social entities emerge from “the bottom up” without reducing causal explanations to individual human beings and their interests. Social networks, institutional organisations, and cities are examples of social assemblages, real emergent entities with causal power in the world. Mapping social assemblages in political economy analysis, and understanding the relations between social entities and different spatial scales, may reveal new ways of addressing corruption and the intensification of elite domination it enables.</p>

All the King’s Horses and all the King’s Men: International anti-corruption discourse, political economy analysis and assemblage theory

<p>Corruption emerged as a key issue area in international relations and development in the 1990s. However, efforts to control corruption have, to date, been relatively unsuccessful. This has prompted international organisations, like the World Bank, to acknowledge that corruption is a political issue as much as it is an economic one. This shift has led to an increasing use of political economy analysis to inform the anticorruption and governance reform operations of international organisations. This thesis examines political economy analysis as a feature of the expertise housed in the World Bank. It argues that because anti-corruption and governance expertise is essential to the legitimate authority of the organisation, there are risks to that authority if World Bank experts are unable to provide more than highly conventional recommendations for tackling corruption in developing countries. Commentators on development practice have suggested that integrating concepts from complexity science into political economy analysis and adopting an “upside-down” approach to development might be useful to help generate new ideas for controlling corruption. However, this thesis argues that in order to do so, it is necessary to address the philosophical implications of complexity science for mainstream anti-corruption discourse, which is dominated by the positivist assumptions of neo-classical economics. To this end, the thesis argues that Manuel DeLanda’s assemblage theory offers a social ontology in which the relevance of complexity science concepts for social analysis can be developed, and a way of thinking that emphasises how social entities emerge from “the bottom up” without reducing causal explanations to individual human beings and their interests. Social networks, institutional organisations, and cities are examples of social assemblages, real emergent entities with causal power in the world. Mapping social assemblages in political economy analysis, and understanding the relations between social entities and different spatial scales, may reveal new ways of addressing corruption and the intensification of elite domination it enables.</p>

Dynamics in and dynamics of networks using DyNSimF

Advancements of formal theories, network science, and data collection technologies make network analysis and simulation an increasingly crucial tool in complexity science. We present DyNSimF; the first open-source package that allows for the modeling of com- plex interacting dynamics on a network a well as dynamics of (the structure of) a net- work. The package can deal with weighted as well as directional connections, is scalable and efficient, and includes a utility-based edge-altering framework. DyNSimF includes visualization methods and tools to help analyze models. It is designed to be easily ex- tendable and makes use of NetworkX graphs. It aims to be easy to learn and to work with, enabling non-experts to focus on the development of models, while at the same time being highly customizable and extensible to allow for complex custom models.

Comment in Reply to "On the complexity of extending the convergence region for Traub’s method"

This comment is in reply to the paper “On the complexity of extending the convergence region for Traub’s method” [1]. In complexity science, from the mathematical perspective, discussions of complexity often concern algorithmic complexity such as in the paper responded to here [2]. But this is only one of the kinds of complexity that exists even in the mathematical domain. There is also the complexity in the behavior of a system of equations; there is the complexity of the reasoning or algorithm required to understand a system of equations (“understand” interpreted here as defining the problem needing to be solved); and, as mentioned, there is the complexity of the reasoning or algorithm required to solve a system of equations.

Mapping the perception of “complex systems” across educational levels through cognitive network science

Despite recent efforts promoting complexity science across different educational contexts, there is little literature about how school students perceive complex systems. This research report aims to quantify the current perception of “complex systems” among 159 Italian high school students, providing a data-informed map of the general attitude and knowledge structure towards complexity through tools from cognitive network science. Adopting the framework of forma mentis networks, i.e. conceptual networks where words are related by memory recall patterns and labelled according to their positive/negative/neutral sentiment, the students’ mindset or forma mentis towards “complex systems” was reconstructed and compared to the mindset of 59 international postgraduate researchers working on complexity topics. Despite studying multiple scientific disciplines at the same time, students perceived complexity as an abstract and negative entity, strongly associated to “complicated” and “difficult” whereas researchers identified complexity as a positive concept, with a stronger STEM-oriented, multidisciplinary connotation towards mathematics, physics, biology and other scientific disciplines. This comparison was discussed in light of relevant literature about silo mentality in education. Mindset reconstruction through forma mentis networks opens novel ways for quantifying current perceptions of “complexity science” in mainstream educational curricula, suggesting key challenges for developing complexity education through the mindsets of complexity researchers.