A simple guide to chaos and complexity

Identifying precondition configurations of mathematics anxiety among middle school students in China: using NCA and QCA approaches

Introduction

Addressing mathematics anxiety is important to ensure that students achieve good academic performance and maintain their mental health during the critical middle school period. However, previous studies have focused on the separate effects of the preconditions for mathematics anxiety, ignoring the interaction of factors. Therefore, this study aims to identify the determinants of mathematics anxiety from the perspective of complex systems via necessary condition analysis (NCA) and qualitative comparative analysis (QCA). To the best of our knowledge, this is the first study to identify configurations of preconditions of mathematics anxiety among middle school students.

Methods

A total of 183 middle school students aged 16 to 19 years (M age = 17.47, SD = 0.89) in China participated in this cross-sectional study. The outcome variable of the study is mathematics anxiety, and the condition variables include mathematics grade, parental support, learning motivation, learning planning, and learning interest.

Results

The necessity condition analysis shows that not all the condition variables constitute the necessity condition of mathematics anxiety alone. Four paths for the influence of multiple condition variables on mathematics anxiety are identified via the configuration analysis. Notably, even students with high mathematics scores and learning interest still experience mathematics anxiety due to a lack of practical parental support and learning motivation. High levels of parental support can exacerbate the mathematics anxiety of students under two conditions: 1) a lack of learning motivation and learning plans, and 2) interest in learning but low mathematics scores and unclear learning plans.

Discussion

This study highlights the need to consider the comprehensive impact of mathematics anxiety, and the findings will help educators and researchers identify the different characteristics of mathematics anxiety in student populations.

Reflective practice is a prerequisite for One Health development

One Health is being promoted as a transformative approach in health, conservation, and environmental sustainability. The polycrisis of climate change, pandemics, food insecurity, biodiversity loss, pollution and inequity is creating an urgency to evolve the epistemology and methods of One Health. However, the amount of effort placed into critical and systematic reflection on One Health is outweighed by advocacy for its use, or for expanding its scope of practice. This paper advocates for reflective One Health practice to foster new ways of knowing and doing that are helpful in the face of a rapidly narrowing window of opportunity to preserve the social and environmental factors that secure health and resilience for all species and generations. We propose six areas for reflection; (1) how to moderate conformity so that One Health does not become its own silo; (2) finding the moral purpose of One Health to align actions with desired outcomes; (3) coping with the problem of too many interacting problems; (4) the strategic trajectory of growth to accelerate action on root causes and ensure One Health is future-ready; (5) how to identify priorities across a vast array of problems, values, and needs and (6) how to know if we are making the world healthier and safer and for whom. Reflective practice requires investment in ongoing conversation to guard against over-confidence that we have captured the "one right way" to meet changing expectations and circumstances in a fair and effective way. Our intention is to stimulate thinking and discussion within the One Health community to ensure that "doing is shaped by knowing". We hope One Health will continue to be an emergent and highly variable set of ever more effective practices that constantly changes in response to the complex, interconnected and changing problems facing the health of people, animals, and the environment.

On the higher-order smallest ring-star network of Chialvo neurons under diffusive couplings

Network dynamical systems with higher-order interactions are a current trending topic, pervasive in many applied fields. However, our focus in this work is neurodynamics. We numerically study the dynamics of the smallest higher-order network of neurons arranged in a ring-star topology. The dynamics of each node in this network is governed by the Chialvo neuron map, and they interact via linear diffusive couplings. This model is perceived to imitate the nonlinear dynamical properties exhibited by a realistic nervous system where the neurons transfer information through multi-body interactions. We deploy the higher-order coupling strength as the primary bifurcation parameter. We start by analyzing our model using standard tools from dynamical systems theory: fixed point analysis, Jacobian matrix, and bifurcation patterns. We observe the coexistence of disparate chaotic attractors. We also observe an interesting route to chaos from a fixed point via period-doubling and the appearance of cyclic quasiperiodic closed invariant curves. Furthermore, we numerically observe the existence of codimension-1 bifurcation points: saddle-node, period-doubling, and Neimark-Sacker. We also qualitatively study the typical phase portraits of the system, and numerically quantify chaos and complexity using the 0-1 test and sample entropy measure, respectively. Finally, we study the synchronization behavior among the neurons using the cross correlation coefficient and the Kuramoto order parameter. We conjecture that unfolding these patterns and behaviors of the network model will help us identify different states of the nervous system, further aiding us in dealing with various neural diseases and nervous disorders.

A New Paradigm for Nurse Leader Decision-Making Within Complex Adaptive Systems

Health care is a complex and ever-changing environment for nurse leaders and other health care industry decision-makers. The prevailing leadership and decision-making models, rooted in Industrial Age principles, often struggle to adapt to the complexities of modern health care. This article explores the foundations of complexity science and its application to health care decision-making, highlighting the importance of understanding systems dynamics and embracing complexity. Drawing from systems knowledge, the Cynefin Sensemaking Framework, and understanding how to develop enabling constraints, nurse leaders can navigate the complexities of health care by identifying the nature of the problem and applying appropriate decision-making strategies, fostering agility and innovation. By embracing complexity and adopting adaptive leadership approaches, nurse leaders can pragmatically navigate the complexities of modern health care and drive transformative change. This manuscript provides methods for nurse leaders to enhance decision-making within the dynamic landscape of health care as a complex adaptive system.

The historical and philosophical roots of emergentism in the neurosciences

Understanding and characterizing the relationship between mental phenomena and the brain is a huge challenge for modern neuroscience. No doubt, the conservative orthodox view of this relationship can be described as physicalist. Physicalism is the idea that, no matter how enigmatic mental phenomena may seem, they are nevertheless completely describable in physical and material terms. Still, despite centuries of effort, aspects of mind, such as the qualitative nature of subjective experience, have defied physical characterization. In the early 1920s, emergentism was advanced to explain the relationship between physical reality and higher-order phenomena, including life and mind. According to emergentism, such higher-order phenomena are derivative of and, at the same time, autonomous to underlying physical reality. This article describes the historical and philosophical development of emergentist theses, particularly as they have been treated in the neurosciences.

Mapping communities as complex adaptive systems: A study of the response to violence against women by communities in Samoa

This paper explores the concept of communities as complex adaptive systems in the context of violence against women (VAW) prevention. Using thematic network analysis on data from 80 semi-structured interviews with community members in Samoa, we found that communities exhibit many properties of complex adaptive systems. Within nested systems, diverse and dynamic agents interact based on their knowledge and attitudes, which changes over time, leading to emergent and unpredictable outcomes. The functioning of communities and their response to VAW is a product of non-linear and emerging relationships and interactions between systems components at the community level. The approach we propose for conceptualising communities as complex adaptive systems provides a structured method for designing and evaluating community-based interventions that are grounded in the local context and existing resources. With in-depth knowledge of how a community works, interventions can be better equipped to address wicked problems such as VAW.

A Holistic Review of Cyber-Physical-Social Systems: New Directions and Opportunities

A Cyber-Physical-Social System (CPSS) is an evolving subset of Cyber-Physical Systems (CPS), which involve the interlinking of the cyber, physical, and social domains within a system-of-systems mindset. CPSS is in a growing state, which combines secure digital technologies with physical systems (e.g., sensors and actuators) and incorporates social aspects (e.g., human interactions and behaviors, and societal norms) to facilitate automated and secure services to end-users and organisations. This paper reviews the field of CPSS, especially in the scope of complexity theory and cyber security to determine its impact on CPS and social media's influence activities. The significance of CPSS lies in its potential to provide solutions to complex societal problems that are difficult to address through traditional approaches. With the integration of physical, social, and cyber components, CPSS can realize the full potential of IoT, big data analytics, and machine learning, leading to increased efficiency, improved sustainability and better decision making. CPSS presents exciting opportunities for innovation and advancement in multiple domains, improving the quality of life for people around the world. Research challenges to CPSS include the integration of hard and soft system components within all three domains, in addition to sociological metrics, data security, processing optimization and ethical implications. The findings of this paper note key research trends in the fields of CPSS, and recent novel contributions, followed by identified research gaps and future work.

Health Service Implementation and Antifragile Characteristics in Rural Communities: A Dirt Research Approach

The implementation of health and care services within rural communities requires necessary sensitivity to the unique facets of rural places. Often, rural service implementation is executed with inappropriate frameworks based on assumptions derived from urban centres. To understand the characteristics of rural communities that can facilitate successful program implementation better, ethnographic accounts of rural health and care services were compiled in rural communities within Canada, Australia, and Iceland. Ethnographic accounts are presented in the first and third person, with an accompanying reflexive analysis immediately following these accounts. Antifragility was the guiding concept of interest when investigating rural implementation environments, a concept that posits that a system can gain stability from uncertainty rather than lose integrity. These ethnographic accounts provide evidence of antifragile operators such as optionality, hybrid leadership, starting small, nonlinear evaluation, and avoiding suboptimisation. It is shown that the integration of these antifragile operators allows programs to function better in complex rural systems. Further, the presence of capable individuals with sufficient knowledge in several disciplines and with depth in a single discipline allows for innovative local thinking initiatives.

Guidance on the use of complex systems models for economic evaluations of public health interventions

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Toward a cohesive understanding of ecological complexity

Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.

Ethics Inside the Black Box: Integrating Science and Technology Studies into Engineering and Public Policy Curricula

There is growing need for hybrid curricula that integrate constructivist methods from Science and Technology Studies (STS) into both engineering and policy courses at the undergraduate and graduate levels. However, institutional and disciplinary barriers have made implementing such curricula difficult at many institutions. While several programs have recently been launched that mix technical training with consideration of "societal" or "ethical issues," these programs often lack a constructivist element, leaving newly-minted practitioners entering practical fields ill-equipped to unpack the politics of knowledge and technology or engage with skeptical publics. This paper presents a novel format for designing interdisciplinary coursework that combines conceptual content from STS with training in engineering and policy. Courses following this format would ideally be team taught by instructors with advanced training in diverse fields, and hence co-learning between instructors and disciplines is a key element of the format. Several instruments for facilitating both student and instructor collaborative learning are introduced. The format is also designed for versatility: in addition to being adaptable to both technical and policy training environments, topics are modularized around a conceptual core so that issues ranging from biotech to nuclear security can be incorporated to fit programmatic needs and resources.

Implementing a cirrhosis order set in a tertiary healthcare system: a theory-informed formative evaluation

BACKGROUND

Standardized order sets are a means of increasing adherence to clinical practice guidelines and improving the quality of patient care. Implementation of novel quality improvement initiatives like order sets can be challenging. Before the COVID-19 pandemic, we conducted a formative evaluation to understand healthcare providers' perspectives on implementing clinical changes and the individual, collective and organizational contextual factors that might impact implementation at eight hospital sites in Alberta, Canada.

METHODS

We utilized concepts from the Consolidated Framework for Implementation Research (CFIR) and Normalisation Process Theory (NPT) to understand the context, past implementation experiences, and perceptions of the cirrhosis order set. Eight focus groups were held with healthcare professionals caring for patients with cirrhosis. Data were coded deductively using relevant constructs of NPT and CFIR. A total of 54 healthcare professionals, including physicians, nurses, nurse practitioners, social workers and pharmacists and a physiotherapist, participated in the focus groups.

RESULTS

Key findings revealed that participants recognized the value of the cirrhosis order set and its potential to improve the quality of care. Participants highlighted potential implementation challenges, including multiple competing quality improvement initiatives, feelings of burnout, lack of communication between healthcare provider groups, and a lack of dedicated resources to support implementation.

CONCLUSIONS

Implementing a complex improvement initiative across clinician groups and acute care sites presents challenges. This work yielded insights into the significant influence of past implementation of similar interventions and highlighted the importance of communication between clinician groups and resources to support implementation. However, by using multiple theoretical lenses to illuminate what and how contextual and social processes will influence uptake, we can better anticipate challenges during the implementation process.

"Preparing them for the profession": An interpretative phenomenological analysis of anatomy educators coping with complexity in the United Kingdom curriculum

Efforts to integrate the basic sciences into the ever-changing curriculum are a trending area of research in health professions education. Low-stakes, high-frequency assessment methods such as the progress test are now widely implemented in the United Kingdom and Northern Ireland as a means of furthering curricular integration toward contemporary goals of competency and professional identity formation. The anatomy educator's experience vis-à-vis these curricular changes is not well understood. This study aimed to explore how anatomy educators make sense of the shifting demands of their role. The interviews were semi-structured, particularly concerned with the phenomenon of teachers adapting to the complexity of their learning environment. The study used interpretative phenomenological analysis (IPA) to focus on the lived experiences of participants coping with the phenomena in question: how do anatomy educators make sense of the learning environment in the United Kingdom? Interviews were transcribed verbatim and interpreted inductively, identifying four key themes: confidence through connectedness, variations in appraisals of curricular integration, managing expectations to perform in paradoxical situations, and the emergence of innovative teaching. Results point to the learning environment as a complex system and highlight the importance of feeling support from and connection to colleagues, enabling individual educators to develop confidence, meet the top-down demands of changing curricula, and experience personal identity development and uncertainty tolerance within their role. This IPA study offers insight into the lived experiences of anatomy educators whose experiential interpretations of a complex and changing curriculum can uniquely inform stakeholders in health professions education.

Evolution and expansion of the One Health approach to promote sustainable and resilient health and well-being: A call to action

One Health is a transdisciplinary approach used to address complex concerns related to human, animal, plant, and ecosystem health. One Health frameworks and operational tools are available to support countries and communities, particularly for the prevention and control of zoonotic diseases and antimicrobial resistance and the protection of food safety. However, One Health has yet to be implemented in a manner that fully considers the complexities and interconnectedness of the diverse influences that have impacts at a larger system level. This lack of consideration can undermine the sustainability of any positive outcomes. To ensure the One Health approach can function effectively within the new global context of converging and escalating health, social, economic, and ecological crises, it must evolve and expand in three overlapping dimensions: (1) Scope: the partners, knowledge, and knowledge systems included, (2) Approach: the techniques, methodologies, and scholarship considered, and (3) Worldview inclusivity: the interweaving of other worldviews together with the mainstream scientific worldview that currently predominates. Diverse partners and knowledge from outside the mainstream health and scientific sectors, including Indigenous peoples and representatives of local communities, and traditionally generated knowledge, must be included. These systems of knowledge can then be braided together with mainstream science to comprise a holistic framework for decision-making. Scholarship and methodologies being applied in other fields and contexts to solve complex challenges and manage uncertainty, such as collaborative governance, social-ecologic systems theory, and complexity science, must be recognized and incorporated. The spectrum of considered worldviews must also expand to authentically integrate the expanded scope and approach into action and sustainable impact. By increasing community and social engagement and by recognizing and entwining different worldviews, the plurality of disciplines, and traditional and scientific ways of knowing to address community concerns in the contexts in which they exist, we can ensure that One Health remains effective and true to its paradigm in our rapidly changing and complex world.

Sustainable adoption of noninvasive telemonitoring for chronic heart failure: A qualitative study in the Netherlands

Objective

Noninvasive telemonitoring aims to improve healthcare for patients with chronic heart failure (HF) by reducing hospitalizations and improving patient experiences. Yet, sustainable adoption seems to be limited. Therefore, the goal of our study is to gain insight in the processes that support sustainable adoption of telemonitoring for patients with HF.

Methods

We conducted semi-structured interviews with 25 stakeholders that were involved with the adoption of telemonitoring, such as healthcare professionals, policymakers and healthcare insurers. We analyzed the interviews by using a combination of open-coding and the themes of the Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability framework.

Results

We found that telemonitoring projects have moved beyond initial pilot phases despite a high level of complexity on multiple topics. The patient selection, the business case, the evidence, the aims of telemonitoring, integration of telemonitoring in the care pathway, reimbursement, and future centralization were items that yielded different and sometimes contradictory opinions.

Conclusions

This study showed that the sustainable adoption of telemonitoring for HF is a complex endeavor. Different aims and perspectives play an important role in the patient selection, design, evaluations and envisioned futures of telemonitoring. High conviction among participants of the added value that telemonitoring may support further adoption of telemonitoring. Structural evaluations will be needed to guide cyclical improvement and adapt programs to employ telemonitoring in such a manner that it contributes to collectively supported aims.

Ongoing Bidirectional Feedback between Planning and Assessment in Educational Contexts: A Narrative Review

Quality in education is one of the 17 goals in the United Nations' sustainable agenda for 2030, presupposing careful planning and assessment of learning. Traditional planning in sports education (either in training or school settings) largely adopts pre-determined learning sequences and temporal milestones that, in theory, enhance the learning process. However, learning is a context-dependent, non-linear process with considerable intra- and interindividual variability, whereby planning and assessment should also be non-linear. In this narrative review, the main findings suggest that the specific teaching or training contents and their relative (i.e., ordering or sequencing) and absolute timing (i.e., the specific time point where certain learning or adaptations are expected) should vary depending on the learners and the context. In a process-oriented perspective, this requires flexible planning and the establishment of ongoing bidirectional links between planning and assessment. In this framework, assessment should be a flexible, evolving, and daily pedagogical tool instead of a set of formal checkpoints. We further explored how planning and assessment could be linked to provide an ongoing feedback loop that respects the individuality of each learner and its context, and therefore hope this review helps bring about a change in current planning and assessment paradigms in sports education.

A novel lower extremity non-contact injury risk prediction model based on multimodal fusion and interpretable machine learning

The application of machine learning algorithms in studying injury assessment methods based on data analysis has recently provided a new research insight for sports injury prevention. However, the data used in these studies are primarily multi-source and multimodal (i.e., longitudinal repeated-measures data and cross-sectional data), resulting in the models not fully utilising the information in the data to reveal specific injury risk patterns. Therefore, this study proposed an injury risk prediction model based on a multi-modal strategy and machine learning algorithms to handle multi-source data better and predict injury risk. This study retrospectively analysed the routine monitoring data of sixteen young female basketball players. These data included training load, perceived well-being status, physiological response, physical performance and lower extremity non-contact injury registration. This study partitions the original dataset based on the frequency of data collection. Extreme gradient boosting (XGBoost) was used to construct unimodal submodels to obtain decision scores for each category of indicators. Ultimately, the decision scores from each submodel were fused using the random forest (RF) to generate a lower extremity non-contact injury risk prediction model at the decision-level. The 10-fold cross-validation results showed that the fusion model was effective in classifying non-injured (mean Precision: 0.9932, mean Recall: 0.9976, mean F2-score: 0.9967), minimal lower extremity non-contact injuries risk (mean Precision: 0.9317, mean Recall: 0.9167, mean F2-score: 0.9171), and mild lower extremity non-contact injuries risk (mean Precision: 0.9000, mean Recall: 0.9000, mean F2-score: 0.9000). The model performed significantly more optimal than the submodel. Comparing the fusion model proposed with a traditional data integration scheme, the average Precision and Recall improved by 8.2 and 20.3%, respectively. The decision curves analysis showed that the proposed fusion model provided a higher net benefit to athletes with potential lower extremity non-contact injury risk. The validity, feasibility and practicality of the proposed model have been confirmed. In addition, the shapley additive explanation (SHAP) and network visualisation revealed differences in lower extremity non-contact injury risk patterns across severity levels. The model proposed in this study provided a fresh perspective on injury prevention in future research.

Control of cell state transitions

Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology. Here we present cell state transition assessment and regulation (cSTAR), an approach for mapping cell states, modelling transitions between them and predicting targeted interventions to convert cell fate decisions. cSTAR uses omics data as input, classifies cell states, and develops a workflow that transforms the input data into mechanistic models that identify a core signalling network, which controls cell fate transitions by influencing whole-cell networks. By integrating signalling and phenotypic data, cSTAR models how cells manoeuvre in Waddington's landscape1 and make decisions about which cell fate to adopt. Notably, cSTAR devises interventions to control the movement of cells in Waddington's landscape. Testing cSTAR in a cellular model of differentiation and proliferation shows a high correlation between quantitative predictions and experimental data. Applying cSTAR to different types of perturbation and omics datasets, including single-cell data, demonstrates its flexibility and scalability and provides new biological insights. The ability of cSTAR to identify targeted perturbations that interconvert cell fates will enable designer approaches for manipulating cellular development pathways and mechanistically underpinned therapeutic interventions.

Optimising health system capacity: A case study of community care staff's role transition in response to the coronavirus pandemic

The coronavirus disease (COVID-19) increased the demand for critical care spaces and the task for individual countries was to optimise the capacity of their health systems. Correlating governance and health system capacity to respond to global crises has subsequently garnered the pace in reviewing normalised forms of identifying health priorities. Aligning global health security and universal health security enhances the capacity and resilience of a health system. However, weak methods of governance hinder the alignment necessary for controlling infection spread and coping with the increase in demand for hospital critical care. A range of qualitative studies has explored staff experiences of providing care in hospitals amidst the COVID-19 pandemic. Nonetheless, limited understanding of the influence of governance on health and social care staff experiences in response to the COVID-19 pandemic exists. This case study aimed to explore the influence of health system governance on community care staff experiences of role transition in response to the COVID-19 pandemic in England. We used criterion sampling to include community care staff initially recruited to deliver a community integrated model of dementia care at two facilities repurposed in March 2020 to optimise hospital critical care space. Six community care staff participated in the narrative correspondence inquiry. A lack of control over resources, limitations in collective action in decision making and lack of a voice underpinned staff experiences of role transition in contexts of current crisis preparedness, transition shock and moral dilemmas. Health system governance influenced the disposition of community care staff's role transition in response to the COVID-19 pandemic. Staff's mere coping clouds the glass of wider issues in health system governance and capacity. The normative dominance that the control over resources and centrally determined health system priorities ordain require reviewing to enable optimal health and social care cross systems' capacity and resilience.

Addressing alcohol-related harms in the local night-time economy: a qualitative process evaluation from a complex systems perspective

OBJECTIVES

English local authorities (LAs) are interested in reducing alcohol-related harms and may use discretionary powers such as the Late Night Levy (LNL) to do so. This study aims to describe how system stakeholders hypothesise the levy may generate changes and to explore how the system, its actors and the intervention adapt and co-evolve over time.

DESIGN

A process evaluation from a complex systems perspective, using qualitative methods.

SETTING

A London LA with high densities of residential and commercial properties, which implemented the LNL in 2014.

PARTICIPANTS

Data were generated through interviews with LNL implementers and alcohol consumers, observations in bars and during LNL patrols and documentary review.

INTERVENTION

The LNL allows LAs to charge late-night alcohol retailers an annual fee (£299-£4440) to manage and police the night-time economy (NTE).

RESULTS

When the LNL was being considered, stakeholders from different interest groups advanced diverse opinions about its likely impacts while rarely referencing supporting research evidence. Proponents of the levy argued it could reduce crime and anti-social behaviour by providing additional funds to police and manage the NTE. Critics of the levy hypothesised adverse consequences linked to claims that the intervention would force venues to vary their hours or close, cluster closing times, reduce NTE diversity and undermine public-private partnerships. In the first 2 years, levy-funded patrols developed relationships with the licensed trade and the public. The LNL did not undermine public-private partnerships and while some premises varied their hours, these changes did not undermine the intervention's viability, nor significantly cluster venue closing times, nor obviously damage the area's reputation for having a diverse NTE.

CONCLUSIONS

This study applies a framework for process evaluation from a complex systems perspective. The evaluation could be extended to measure alcohol-related outcomes and to consider the interplay between the national and local systems.

The missing bit in the middle: Implementation of the Nationals Health Services Standards for Papua New Guinea

OBJECTIVE

This case study examined implementation of the National Health Services Standards (NHSSs) as a continuous quality improvement (CQI) process at three church-based health facilities in Papua New Guinea. This process was designed to improve quality of care and accredit the level three health centers to level four as district hospitals to provide a higher level of care. The aims of the paper are to critically examine driving and restraining forces in CQI implementation and analyses how power influences agenda setting for change.

METHODS

Semi-structured interviews were conducted with nine managers and eight health workers as well as three focus group discussions with health workers from three rural church-based health facilities in Morobe and Madang provinces. They included senior, mid-level and frontline managers and medical doctors, health extension officers, nursing officers and community health workers. Thematic analysis was used as an inductive and deductive process in which applied force field analysis, leadership-member exchange (LMX) theory and agenda setting was applied.

RESULTS

Qualitative analysis showed how internal and external factors created urgency for change. The CQI process was designed as a collective process. Power relations operated at and between various levels: the facilities, which supported or undermined the change process; between management whereby the national management supported the quality improvement agenda, but the regional management exercised positional power in form of inaction. Theoretical analysis identified the 'missing bit in the middle' shaped by policy actors who exercise power over policy formulation and constrained financial and technical resources. Analysis revealed how to reduce restraining forces and build on driving forces to establish a new equilibrium.

CONCLUSION

Multiple theories contributed to the analysis showing how to resolve problematic power relations by building high-quality, effective communication of senior leadership with mid-level management and reactivated broad collaborative processes at the health facilities. Addressing the 'missing bit in the middle' by agenda setting can improve implementation of the NHSSs as a quality improvement process. The paper concludes with learning for policy makers, managers and health workers by highlighting to pay close attention to institutional power dynamics and practices.

Loss associated with subtractive health service change: The case of specialist cancer centralization in England

OBJECTIVE

Major system change can be stressful for staff involved and can result in 'subtractive change' - that is, when a part of the work environment is removed or ceases to exist. Little is known about the response to loss of activity resulting from such changes. Our aim was to understand perceptions of loss in response to centralization of cancer services in England, where 12 sites offering specialist surgery were reduced to four, and to understand the impact of leadership and management on enabling or hampering coping strategies associated with that loss.

METHODS

We analysed 115 interviews with clinical, nursing and managerial staff from oesophago-gastric, prostate/bladder and renal cancer services in London and West Essex. In addition, we used 134 hours of observational data and analysis from over 100 documents to contextualize and to interpret the interview data. We performed a thematic analysis drawing on stress-coping theory and organizational change.

RESULTS

Staff perceived that, during centralization, sites were devalued as the sites lost surgical activity, skills and experienced teams. Staff members believed that there were long-term implications for this loss, such as in retaining high-calibre staff, attracting trainees and maintaining autonomy. Emotional repercussions for staff included perceived loss of status and motivation. To mitigate these losses, leaders in the centralization process put in place some instrumental measures, such as joint contracting, surgical skill development opportunities and trainee rotation. However, these measures were undermined by patchy implementation and negative impacts on some individuals (e.g. increased workload or travel time). Relatively little emotional support was perceived to be offered. Leaders sometimes characterized adverse emotional reactions to the centralization as resistance, to be overcome through persuasion and appeals to the success of the new system.

CONCLUSIONS

Large-scale reorganizations are likely to provoke a high degree of emotion and perceptions of loss. Resources to foster coping and resilience should be made available to all organizations within the system as they go through major change.

A People-Focused Systems Approach to Sustainability

Creating organizations that promote human and ecological flourishing (i.e., sustainability) is a key challenge for contemporary societies. Here, we offer a people-focused systems approach to organizational sustainability based on an action research project conducted at Western Springs College/Ngā Puna O Waiōrea, a bicultural high school in Aotearoa New Zealand. The project ran from 2008 to 2018 and drew on the values and skills of community psychology and environmental education to build what we call a "sustainable social system" (SSS). In 2018/19, we conducted interviews with 23 key people involved in sustainability efforts at the school and analyzed the minutes of 46 meetings of the school's Sustainability Panel. We used a complex systems approach to produce a map of the core people, purpose, infrastructure, and activities components and sub-systems in the SSS, as well as its emergent properties of a sustainability culture and identities. We describe the historical trajectory of the SSS and discuss seven features that we consider of particular significance in contributing to its growth and resilience. We then offer steps toward a people-focused SSS led by insiders with sustainability values. These include establishing a democratic and inclusive sustainability network, and attempting to integrate sustainability with the organization's essential activities.

Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice

Complex systems are open systems consisting of many components that can interact among themselves and the environment. New forms of behaviours and patterns often emerge as a result. There is a growing recognition that most sporting environments are complex adaptive systems. This acknowledgement extends to sports injury and is reflected in the individual responses of athletes to both injury and rehabilitation protocols. Consequently, practitioners involved in return to sport decision making (RTS) are encouraged to view return to sport decisions through the complex systems lens to improve decision-making in rehabilitation. It is important to clarify the characteristics of this theoretical framework and provide concrete examples to which practitioners can easily relate. This review builds on previous literature by providing an overview of the hallmark features of complex systems and their relevance to RTS research and daily practice. An example of how characteristics of complex systems are exhibited is provided through a case of anterior cruciate ligament injury rehabilitation. Alternative forms of scientific inquiry, such as the use of computational and simulation-based techniques, are also discussed-to move the complex systems approach from the theoretical to the practical level.

Memory in Ion Channel Kinetics

Ion channels are transport proteins present in the lipid bilayers of biological membranes. They are involved in many physiological processes, such as the generation of nerve impulses, hormonal secretion, and heartbeat. Conformational changes in the ion channel-forming protein allow the opening or closing of pores to control the ionic flux through the cell membranes. The opening and closing of the ion channel have been classically treated as a random kinetic process, known as a Markov process. Here the time the channel remains in a given state is assumed to be independent of the condition it had in the previous state. More recently, however, several studies have shown that this process is not random but a deterministic one, where both the open and closed dwell-times and the ionic current flowing through the channel are history-dependent. This property is called long memory or long-range correlation. However, there is still much controversy regarding how this memory originates, which region of the channel is responsible for this property, and which models could best reproduce the memory effect. In this article, we provide a review of what is, where it is, its possible origin, and the mathematical methods used to analyze the long-term memory present in the kinetic process of ion channels.

Complex Adaptive Systems: A Framework for an Integrated Chronic Care Model

Chronic care management is a multidimensional phenomenon involving multilayered interaction, reaction, and adaptation responses to feedback within chronic care micro/macro- systems. Complex adaptive systems (CASs) consider interconnected dynamic relationships between discrete components of systems' internal and external environments. CAS is an applicable framework to examine components and networks within chronic care models. This article considers CAS as a framework for an alternate integrated patient-centered model that incorporates a holistic approach to chronic care. Recognizing relationships, behavioral patterns, and adaptive mechanisms informs health systems and health policy to influence service excellence improvements and quality of care and life within chronic disease populations.

Embracing complexity with systems thinking in general practitioners' clinical reasoning helps handling uncertainty

Clinical reasoning in general practice is increasingly challenging because of the rise in the number of patients with multimorbidity. This creates uncertainty because of unpredictable interactions between the symptoms from multiple medical problems and the patient's personality, psychosocial context and life history. Case analysis may then be more appropriately managed by systems thinking than by hypothetic-deductive reasoning, the predominant paradigm in the current teaching of clinical reasoning. Application of "systems thinking" tools such as causal loop diagrams allows the patient's problems to be viewed holistically and facilitates understanding of the complex interactions. We will show how complexity levels can be graded in clinical reasoning and demonstrate where and how systems thinking can have added value by means of a case history.

Nonclinical research areas of future importance for clinical therapies: Exploring the concepts of nonlinearity in dentistry

Linear system analysis has been dominating medical and dental research, and most of the research achievements in these fields have come from applying a reductionist view of nature. However, biologic systems are fundamentally nonlinear with highly composite dynamics made up of numerous interacting elements and feedback loops, therefore studying them as linear models may not result in an accurate representation of their true features. The authors reviewed and utilized some of the principles of chaos and nonlinearity and extended them to clinical dentistry, from cracked tooth and flare-up after root canal procedures to the outcome of clinical treatments. Utilization of the concepts of chaos and sensitive dependence on initial conditions, and the concepts of self-organization, stigmergy, and fractals may help us to understand some of the puzzles that have not been solved by conventional linear models. The goal of this paper is to present some areas within nonclinical research that we believe will have important roles in the development of future clinical examination methods and therapies.

Applying a complex systems perspective to alcohol consumption and the prevention of alcohol-related harms in the 21st century: a scoping review

BACKGROUND AND AIMS

A complex systems perspective has been advocated to explore multi-faceted factors influencing public health issues, including alcohol consumption and associated harms. This scoping review aimed to identify studies that applied a complex systems perspective to alcohol consumption and the prevention of alcohol-related harms in order to summarize their characteristics and identify evidence gaps.

METHODS

Studies published between January 2000 and September 2020 in English were located by searching for terms synonymous with 'complex systems' and 'alcohol' in the Scopus, MEDLINE, Web of Science and Embase databases, and through handsearching and reference screening of included studies. Data were extracted on each study's aim, country, population, alcohol topic, system levels, funding, theory, methods, data sources, time-frames, system modifications and type of findings produced.

RESULTS

Eighty-seven individual studies and three systematic reviews were identified, the majority of which were conducted in the United States or Australia in the general population, university students or adolescents. Studies explored types and patterns of consumption behaviour and the local environments in which alcohol is consumed. Most studies focused on individual and local interactions and influences, with fewer examples exploring the relationships between these and regional, national and international subsystems. The body of literature is methodologically diverse and includes theory-led approaches, dynamic simulation models and social network analyses. The systematic reviews focused on primary network studies.

CONCLUSIONS

The use of a complex systems perspective has provided a variety of ways of conceptualizing and analyzing alcohol use and harm prevention efforts, but its focus ultimately has remained on predominantly individual- and/or local-level systems. A complex systems perspective represents an opportunity to address this gap by also considering the vertical dimensions that constrain, shape and influence alcohol consumption and related harms, but the literature to date has not fully captured this potential.

A system dynamic perspective of stop-start prevention interventions in Australia

Time-limited prevention initiatives are frequently used to address complex and persisting public health issues, such as non-communicable diseases. This often creates issues in terms of achieving sustainable change. In this study, we use a system dynamic perspective to explore the effects of stop-start funding over system behaviour in two community-based initiatives designed to prevent chronic diseases and obesity. We conducted a qualitative exploratory study using complexity theory as an analytical lens of two Healthy Together Communities (HTCs) initiatives in Victoria, Australia. Data were generated from 20 semi-structured interviews with health promotion practitioners and managers, from community health and local government organizations. Template analysis based on properties of complex systems informed the inductive identification of system behaviour narratives across the stop-start life-course of HTCs. A central narrative of system behaviour emerged around relationships. Within it, we identified pre-existing contextual conditions and intervention design elements that influenced non-linearity of system self-organization and adaptation, and emergence of outcomes. Examples include cynicism, personal relationships and trust, and history of collaboration. Feedback loops operated between HTCs and these conditions, in a way that could influence long-term system behaviour. Taking a dynamic life-course view of system behaviour helps understand the pre-existing contextual factors, design and implementation influences, and feedback loops which shape the long-term legacy of short-lived interventions aimed at solving complex issues. In turn, greater awareness of such interactions can inform better design and implementation of community-based interventions.

The effects of polio eradication efforts on health systems: a cross-country analysis using the Develop-Distort Dilemma

Vertical disease control programmes have enormous potential to benefit or weaken health systems, and it is critical to understand how programmes' design and implementation impact the health systems and communities in which they operate. We use the Develop-Distort Dilemma (DDD) framework to understand how the Global Polio Eradication Initiative (GPEI) distorted or developed local health systems. We include document review and 176 interviews with respondents at the global level and across seven focus countries (Afghanistan, Bangladesh, Democratic Republic of Congo, Ethiopia, India, Indonesia and Nigeria). We use DDD domains, contextual factors and transition planning to analyse interactions between the broader context, local health systems and the GPEI to identify changes. Our analysis confirms earlier research including improved health worker, laboratory and surveillance capacity, monitoring and accountability, and efforts to reach vulnerable populations, whereas distortions include shifting attention from routine health services and distorting local payment and incentives structures. New findings highlight how global-level governance structures evolved and affected national actors; issues of country ownership, including for data systems, where the polio programme is not indigenously financed; how expectations of success have affected implementation at programme and community level; and unresolved tensions around transition planning. The decoupling of polio eradication from routine immunization, in particular, plays an outsize role in these issues as it removed attention from system strengthening. In addition to drawing lessons from the GPEI experience for other efforts, we also reflect on the use of the DDD framework for assessing programmes and their system-level impacts. Future eradication efforts should be approached carefully, and new initiatives of any kind should leverage the existing health system while considering equity, inclusion and transition from the start.

Emerging properties of malaria transmission and persistence in urban Accra, Ghana: evidence from a participatory system approach

Background

Several studies that aim to enhance the understanding of malaria transmission and persistence in urban settings failed to address its underlining complexity. This study aims at doing that by applying qualitative and participatory-based system analysis and mapping to elicit the system’s emergent properties.

Methods

In two experts’ workshops, the system was sketched and refined. This system was represented through a causal loop diagram, where the identification of leverage points was done using network analysis.

Results

45 determinants interplaying through 56 linkages, and three subsystems: urbanization-related transmission, infection-prone behaviour and healthcare efficiency, and Plasmodium resistance were identified. Apart from the number of breeding sites and malaria-positive cases, other determinants such as drug prescription and the awareness of householders were identified by the network analysis as leverage points and emergent properties of the system of transmission and persistence of malaria.

Conclusion

Based on the findings, the ongoing efforts to control malaria, such as the use of insecticide-treated bed nets and larvicide applications should continue, and new ones focusing on the public awareness and malaria literacy of city dwellers should be included. The participatory approach strengthened the legitimacy of the recommendations and the co-learning of participants.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03851-7.

Towards an Explanation of the Social Value of Health Systems: An Interpretive Synthesis

BACKGROUND

Health systems are complex social systems, and values constitute a central dimension of their complexity. Values are commonly understood as key drivers of health system change, operating across all health systems components and functions. Moreover, health systems are understood to influence and generate social values, presenting an opportunity to harness health systems to build stronger, more cohesive societies. However, there is little investigation (theoretical, conceptual, or empirical) on social values in health policy and systems research (HPSR), particularly regarding the capacity of health systems to influence and generate social values. This study develops an explanatory theory for the 'social value of health systems.'

METHODS

We present the results of an interpretive synthesis of HPSR literature on social values, drawing on a qualitative systematic review, focusing on claims about the relationship between 'health systems' and 'social values.' We combined relational claims extracted from the literature under a common framework in order to generate new explanatory theory.

RESULTS

We identify four mechanisms by which health systems are considered to contribute social value to society: Health systems can: (1) offer a unifying national ideal and build social cohesion, (2) influence and legitimise popular attitudes about rights and entitlements with regard to healthcare and inform citizen's understanding of state responsibilities, (3) strengthen trust in the state and legitimise state authority, and (4) communicate the extent to which the state values various population groups.

CONCLUSION

We conclude that, using a systems-thinking and complex adaptive systems perspective, the above mechanisms can be explained as emergent properties of the dynamic network of values-based connections operating within health systems. We also demonstrate that this theory accounts for how HPSR authors write about the relationship between health systems and social values. Finally, we offer lessons for researchers and policy-makers seeking to bring about values-based change in health systems.

Sustainable Development Goal Drivers in Food Systems

Interacting driving forces in food systems, resulting in cumulative driver effects and synergies, induce non-linear processes in multiple directions. This paper critically reviews the discourse on driving forces in food systems and argues that mindset is the primary predictor for food system outcomes. In the epoch of sustainable development goals (SDGs) and the Anthropocene, mindset matters more than ever. Transformative narratives are beginning to transcend the dominant social paradigm, which is still driving the food system's overall trajectory. The psychosocial portrayal of the systemic mindset found in organic food systems presented in this paper “flips the script” and hypothesizes that worldview and paradigm have the most causal linkages with unsustainable driver synergies and reversely the biggest leverage on the mitigation thereof. Borrowing from ecological economics discourses, the paper sharpens the driver definition by applying the DPSIR analytical tool as a modified diagnostic framework and modeling approach for food systems. This research sheds new light on the nature of drivers of change, which are often portrayed as almighty and inevitable trends shaping food systems. Instead, it is proposed that drivers emerge from the actors' mindset, affecting food system behavior in a non-linear way. Mindset drives reinforcing feedback loops, resulting in vicious and virtuous cycles. These driver motives manifest in subsystems and continue to drive their interaction across food system elements. Mindset acts as an encapsulated input of food systems, all the while responding to feedback and releasing new drivers. A transformation framework along leverage points of the food system is presented that features the concept of SDG drivers.

How many trials are needed in kinematic analysis of reach-to-grasp?-A study of the drinking task in persons with stroke and non-disabled controls

Background

Kinematic analysis of the 3D reach-to-grasp drinking task is recommended in stroke rehabilitation research. The number of trials required to reach performance stability, as an important aspect of reliability, has not been investigated for this task. Thus, the aims of this study were to determine the number of trials needed for the drinking task to reach within-session performance stability and to investigate trends in performance over a set of trials in non-disabled people and in a sample of individuals with chronic stroke. In addition, the between-sessions test–retest reliability in persons with stroke was established.

Methods

The drinking task was performed at least 10 times, following a standardized protocol, in 44 non-disabled and 8 post-stroke individuals. A marker-based motion capture system registered arm and trunk movements during 5 pre-defined phases of the drinking task. Intra class correlation statistics were used to determine the number of trials needed to reach performance stability as well as to establish test–retest reliability. Systematic within-session trends over multiple trials were analyzed with a paired t-test.

Results

For most of the kinematic variables 2 to 3 trials were needed to reach good performance stability in both investigated groups. More trials were needed for movement times in reaching and returning phase, movement smoothness, time to peak velocity and inter-joint-coordination. A small but significant trend of improvement in movement time over multiple trials was demonstrated in the non-disabled group, but not in the stroke group. A mean of 3 trials was sufficient to reach good to excellent test–retest reliability for most of the kinematic variables in the stroke sample.

Conclusions

This is the first study that determines the number of trials needed for good performance stability (non-disabled and stroke) and test–retest reliability (stroke) for temporal, endpoint and angular metrics of the drinking task. For most kinematic variables, 3–5 trials are sufficient to reach good reliability. This knowledge can be used to guide future kinematic studies.

Analysis of EEG Data Using Complex Geometric Structurization

Electroencephalogram (EEG) is a common tool used to understand brain activities. The data are typically obtained by placing electrodes at the surface of the scalp and recording the oscillations of currents passing through the electrodes. These oscillations can sometimes lead to various interpretations, depending on, for example, the subject's health condition, the experiment carried out, the sensitivity of the tools used, or human manipulations. The data obtained over time can be considered a time series. There is evidence in the literature that epilepsy EEG data may be chaotic. Either way, the Embedding Theory in dynamical systems suggests that time series from a complex system could be used to reconstruct its phase space under proper conditions. In this letter, we propose an analysis of epilepsy EEG time series data based on a novel approach dubbed complex geometric structurization. Complex geometric structurization stems from the construction of strange attractors using Embedding Theory from dynamical systems. The complex geometric structures are themselves obtained using a geometry tool, the α-shapes from shape analysis. Initial analyses show a proof of concept in that these complex structures capture the expected changes brain in lobes under consideration. Further, a deeper analysis suggests that these complex structures can be used as biomarkers for seizure changes.

Health technology assessment for digital technologies that manage chronic disease: a systematic review

OBJECTIVE

A growing number of evaluation frameworks have emerged over recent years addressing the unique benefits and risk profiles of new classes of digital health technologies (DHTs). This systematic review aims to identify relevant frameworks and synthesize their recommendations into DHT-specific content to be considered when performing Health Technology Assessments (HTAs) for DHTs that manage chronic noncommunicable disease at home.

METHODS

Searches were undertaken of Medline, Embase, Econlit, CINAHL, and The Cochrane Library (January 2015 to March 2020), and relevant gray literature (January 2015 to August 2020) using keywords related to HTA, evaluation frameworks, and DHTs. Included framework reference lists were searched from 2010 until 2015. The EUNetHTA HTA Core Model version 3.0 was selected as a scaffold for content evaluation.

RESULTS

Forty-four frameworks were identified, mainly covering clinical effectiveness (n = 30) and safety (n = 23) issues. DHT-specific content recommended by framework authors fell within 28 of the 145 HTA Core Model issues. A further twenty-two DHT-specific issues not currently in the HTA Core Model were recommended.

CONCLUSIONS

Current HTA frameworks are unlikely to be sufficient for assessing DHTs. The development of DHT-specific content for HTA frameworks is hampered by DHTs having varied benefit and risk profiles. By focusing on DHTs that actively monitor/treat chronic noncommunicable diseases at home, we have extended DHT-specific content to all nine HTA Core Model domains. We plan to develop a supplementary evaluation framework for designing research studies, undertaking HTAs, and appraising the completeness of HTAs for DHTs.

Frequent attendance at the emergency department shows typical features of complex systems: analysis of multicentre linked data

OBJECTIVE

Frequent attendance at the ED is a worldwide problem. We hypothesised that frequent attendance could be understood as a feature of a complex system comprising patients, healthcare and society. Complex systems have characteristic statistical properties, with stable patterns at the level of the system emerging from unstable patterns at the level of individuals who make up the system.

METHODS

Analysis of a linked dataset of routinely collected health records from all 13 hospital trusts providing ED care in the Yorkshire and Humber region of the UK (population 5.5 million). We analysed the distribution of attendances per person in each of 3 years and measured the transition of individual patients between frequent, infrequent and non-attendance. We fitted data to power law distributions typically seen in complex systems using maximum likelihood estimation.

RESULTS

The data included 3.6 million attendances at EDs in 13 hospital trusts. 29/39 (74.3%) analyses showed a statistical fit to a power law; 2 (5.1%) fitted an alternative distribution. All trusts' data fitted a power law in at least 1 year. Differences over time and between hospital trusts were small and partly explained by demographics. In contrast, individual patients' frequent attendance was unstable between years.

CONCLUSIONS

ED attendance patterns are stable at the level of the system, but unstable at the level of individual frequent attenders. Attendances follow a power law distribution typical of complex systems. Interventions to address ED frequent attendance need to consider the whole system and not just the individual frequent attenders.

Cancer Explant Models

Overcoming the challenges of understanding and treating cancer requires reliable patient-derived models of cancer (PDMCs). For decades, cancer research and therapeutic development relied primarily on cancer cell lines because of their prevalence, reproducibility, and simplicity to maintain. However, findings from research conducted in cell lines are rarely recapitulated in vivo and seldom directly translatable to patients. The tumor microenvironment (TME), tumor-stromal interactions, and associations with host immune cells produce profound changes in tumor phenotype and complexity not captured in traditional monolayer cell culture. In this chapter, we present various cancer explant models and discuss their applicability based on specific research aims. We discuss the appropriateness of these models for basic science questions, drug screening/development, and for personalized, precision medicine. We also consider logistical factors such as resource cost, technical difficulty, and accessibility. We finish this chapter with a practical guide intended to help the reader select the cancer explant model system(s) that best address their research aims.

Studying Behaviour Change Mechanisms under Complexity

Understanding the mechanisms underlying the effects of behaviour change interventions is vital for accumulating valid scientific evidence, and useful to informing practice and policy-making across multiple domains. Traditional approaches to such evaluations have applied study designs and statistical models, which implicitly assume that change is linear, constant and caused by independent influences on behaviour (such as behaviour change techniques). This article illustrates limitations of these standard tools, and considers the benefits of adopting a complex adaptive systems approach to behaviour change research. It (1) outlines the complexity of behaviours and behaviour change interventions; (2) introduces readers to some key features of complex systems and how these relate to human behaviour change; and (3) provides suggestions for how researchers can better account for implications of complexity in analysing change mechanisms. We focus on three common features of complex systems (i.e., interconnectedness, non-ergodicity and non-linearity), and introduce Recurrence Analysis, a method for non-linear time series analysis which is able to quantify complex dynamics. The supplemental website provides exemplifying code and data for practical analysis applications. The complex adaptive systems approach can complement traditional investigations by opening up novel avenues for understanding and theorising about the dynamics of behaviour change.

We Need to Talk About Complexity in Health Research: Findings From a Focused Ethnography

There is increasing focus on complexity-informed approaches across health disciplines. This attention takes several forms, but commonly involves framing research topics as "complex" to justify use of particular methods (e.g., qualitative). Little emphasis is placed on how divergent and convergent ways of knowing complexity become negotiated within academic communities. Drawing on findings from a focused ethnography of an international workshop, we illustrate how health researchers employ "boundary-ordering devices" to navigate different meanings ascribed to complexity while they attempt to sustain interdisciplinary communication and collaboration. These include (a) surfacing (but not resolving) tensions between philosophical grounding of knowledge claims and need for practical purchase, (b) employing techniques of representation and abstraction, and (c) drawing on the fluid, ongoing accomplishment of complexity for different audiences and purposes. Our findings have implications for progressing complexity-informed health research, particularly with respect to qualitative approaches.

Systems integration to promote the mental health of Aboriginal and Torres Strait Islander children: protocol for a community-driven continuous quality improvement approach

BACKGROUND

Systems integration to promote the mental health of Aboriginal and Torres Strait Islander children works towards developing a spectrum of effective, community-based services and supports. These services and supports are organised into a coordinated network, build meaningful partnerships with families and address their cultural and linguistic needs, to help children to function better at home, in school, in the community, and throughout life. This study is conducted in partnership with primary healthcare (PHC) and other services in three diverse Indigenous Australian communities. It entails conceptualising, co-designing, implementing, and evaluating the effectiveness of systems integration to promote the mental health and wellbeing of Indigenous school-aged children (4-17 years). This paper outlines a protocol for implementing such complex community-driven research.

METHODS/DESIGN

Using continuous quality improvement processes, community co-designed strategies for improved systems integration will be informed by narratives from yarning circles with Indigenous children and service providers, and quantitative data from surveys of service providers and audits of PHC client records and intersectoral systems. Agreed strategies to improve the integration of community-based services and supports will be modelled using microsimulation software, with a preferred model implemented in each community. The evaluation will investigate changes in the: 1) availability of services that are community-driven, youth-informed and culturally competent; 2) extent of collaborative service networks; 3) identification by PHC services of children's social and emotional wellbeing concerns; and 4) ratio of children receiving services to identified need. Costs and benefits of improvements to systems integration will also be calculated.

DISCUSSION

The study will provide evidence-informed, community-driven, and tested models that can be used for implementing systems integration to promote the mental health and wellbeing of Indigenous children. It will identify the situational enablers and barriers that impact systems integration and determine the extent to which systems integration improves service availability, systems and child outcomes. Evidence for the cost effectiveness of systems-level integration will contribute to national mental health policy reform.

Qualitative process evaluation from a complex systems perspective: A systematic review and framework for public health evaluators

BACKGROUND

Public health evaluation methods have been criticized for being overly reductionist and failing to generate suitable evidence for public health decision-making. A "complex systems approach" has been advocated to account for real world complexity. Qualitative methods may be well suited to understanding change in complex social environments, but guidance on applying a complex systems approach to inform qualitative research remains limited and underdeveloped. This systematic review aims to analyze published examples of process evaluations that utilize qualitative methods that involve a complex systems perspective and proposes a framework for qualitative complex system process evaluations.

METHODS AND FINDINGS

We conducted a systematic search to identify complex system process evaluations that involve qualitative methods by searching electronic databases from January 1, 2014-September 30, 2019 (Scopus, MEDLINE, Web of Science), citation searching, and expert consultations. Process evaluations were included if they self-identified as taking a systems- or complexity-oriented approach, integrated qualitative methods, reported empirical findings, and evaluated public health interventions. Two reviewers independently assessed each study to identify concepts associated with the systems thinking and complexity science traditions. Twenty-one unique studies were identified evaluating a wide range of public health interventions in, for example, urban planning, sexual health, violence prevention, substance use, and community transformation. Evaluations were conducted in settings such as schools, workplaces, and neighborhoods in 13 different countries (9 high-income and 4 middle-income). All reported some utilization of complex systems concepts in the analysis of qualitative data. In 14 evaluations, the consideration of complex systems influenced intervention design, evaluation planning, or fieldwork. The identified studies used systems concepts to depict and describe a system at one point in time. Only 4 evaluations explicitly utilized a range of complexity concepts to assess changes within the system resulting from, or co-occurring with, intervention implementation over time. Limitations to our approach are including only English-language papers, reliance on study authors reporting their utilization of complex systems concepts, and subjective judgment from the reviewers relating to which concepts featured in each study.

CONCLUSION

This study found no consensus on what bringing a complex systems perspective to public health process evaluations with qualitative methods looks like in practice and that many studies of this nature describe static systems at a single time point. We suggest future studies use a 2-phase framework for qualitative process evaluations that seek to assess changes over time from a complex systems perspective. The first phase involves producing a description of the system and identifying hypotheses about how the system may change in response to the intervention. The second phase involves following the pathway of emergent findings in an adaptive evaluation approach.

The value proposition of the Global Health Security Index

Infectious disease outbreaks pose major threats to human health and security. Countries with robust capacities for preventing, detecting and responding to outbreaks can avert many of the social, political, economic and health system costs of such crises. The Global Health Security Index (GHS Index)-the first comprehensive assessment and benchmarking of health security and related capabilities across 195 countries-recently found that no country is sufficiently prepared for epidemics or pandemics. The GHS Index can help health security stakeholders identify areas of weakness, as well as opportunities to collaborate across sectors, collectively strengthen health systems and achieve shared public health goals. Some scholars have recently offered constructive critiques of the GHS Index's approach to scoring and ranking countries; its weighting of select indicators; its emphasis on transparency; its focus on biosecurity and biosafety capacities; and divergence between select country scores and corresponding COVID-19-associated caseloads, morbidity, and mortality. Here, we (1) describe the practical value of the GHS Index; (2) present potential use cases to help policymakers and practitioners maximise the utility of the tool; (3) discuss the importance of scoring and ranking; (4) describe the robust methodology underpinning country scores and ranks; (5) highlight the GHS Index's emphasis on transparency and (6) articulate caveats for users wishing to use GHS Index data in health security research, policymaking and practice.

Learning dynamical systems in noise using convolutional neural networks

The problem of distinguishing deterministic chaos from non-chaotic dynamics has been an area of active research in time series analysis. Since noise contamination is unavoidable, it renders deterministic chaotic dynamics corrupted by noise to appear in close resemblance to stochastic dynamics. As a result, the problem of distinguishing noise-corrupted chaotic dynamics from randomness based on observations without access to the measurements of the state variables is difficult. We propose a new angle to tackle this problem by formulating it as a multi-class classification task. The task of classification involves allocating the observations/measurements to the unknown state variables in order to find the nature of these unobserved internal state variables. We employ signal and image processing based methods to characterize the different system dynamics. A deep learning technique using a state-of-the-art image classifier known as the Convolutional Neural Network (CNN) is designed to learn the dynamics. The time series are transformed into textured images of spectrogram and unthresholded recurrence plot (UTRP) for learning stochastic and deterministic chaotic dynamical systems in noise. We have designed a CNN that learns the dynamics of systems from the joint representation of the textured patterns from these images, thereby solving the problem as a pattern recognition task. The robustness and scalability of our approach is evaluated at different noise levels. Our approach demonstrates the advantage of applying the dynamical properties of chaotic systems in the form of joint representation of UTRP images along with spectrogram to improve learning dynamical systems in colored noise.

Health Care Organizations as Complex Adaptive Systems

Health care organizations that deliver health care to a population are a major constituent of health care systems in many countries. Although some of the components of a health care organization may function as a simple or complicated system where interventions would yield the expected results, many parts of it function as complex systems within the organization. As such, is not always possible to predict changes or the effects of interventions on these systems due to their complex nature. Appreciation of the complex nature of health care systems and characteristics of these complex systems and their networks are necessary to manage health care organizations and changes in health care. This article described different types of systems and discusses why health care organizations are considered complex adaptive systems.