BACKGROUND: Challenging behaviors like aggression and self-injury are dangerous for clients and staff in residential care. These behaviors are not well understood and therefore often labeled as \"complex\". Yet it remains vague what this supposed complexity entails at the individual level. This case-study used a three-step mixed-methods analytical strategy, inspired by complex systems theory. First, we construed a holistic summary of relevant factors in her daily life. Second, we described her challenging behavioral trajectory by identifying stable phases. Third, instability and extraordinary events in her environment were evaluated as potential change-inducing mechanisms between different phases.
METHODS: A woman, living at a residential facility, diagnosed with mild intellectual disability and borderline personality disorder, who shows a chronic pattern of aggressive and self-injurious incidents. She used ecological momentary assessments to self-rate challenging behaviors daily for 560 days.
CONCLUSIONS: A qualitative summary of caretaker records revealed many internal and environmental factors relevant to her daily life. Her clinician narrowed these down to 11 staff hypothesized risk- and protective factors, such as reliving trauma, experiencing pain, receiving medical care or compliments. Coercive measures increased the chance of challenging behavior the day after and psychological therapy sessions decreased the chance of self-injury the day after. The majority of contemporaneous and lagged associations between these 11 factors and self-reported challenging behaviors were non-significant, indicating that challenging behaviors are not governed by mono-causal if-then relations, speaking to its complex nature. Despite this complexity there were patterns in the temporal ordering of incidents. Aggression and self-injury occurred on respectively 13% and 50% of the 560 days. On this timeline 11 distinct stable phases were identified that alternated between four unique states: high levels of aggression and self-injury, average aggression and self-injury, low aggression and self-injury, and low aggression with high self-injury. Eight out of ten transitions between phases were triggered by extraordinary events in her environment, or preceded by increased fluctuations in her self-ratings, or a combination of these two. Desirable patterns emerged more often and were less easily malleable, indicating that when she experiences bad times, keeping in mind that better times lie ahead is hopeful and realistic.

BACKGROUND: Complex interactions between political economy factors and corporate power are increasingly recognized to prevent transformative policy action on non-communicable disease (NCD) prevention. System science offers promising methods for analysing such causal complexity. This study uses qualitative system dynamics methods to map the political economy of diet-related NCD (DR-NCD) prevention policy-making aiming to better understand the policy inertia observed in this area globally.
METHODS: We interviewed 25 key policy actors. We analysed the interviews using purposive text analysis (PTA). We developed individual then combined casual loop diagrams to generate a shared model representing the DR-NCD prevention policy-making system. Key variables/linkages identified from the literature were also included in the model. We validated the model in several steps including through stakeholder validation interviews.
RESULTS: We identified several inter-linked feedback processes related to political economy factors that may entrench different forms of corporate power (instrumental, structural, and discursive) in DR-NCD prevention policy-making in South Africa over time. We also identified a number of feedback processes that have the potential to limit corporate power in this setting.
CONCLUSIONS: Using complex system methods can be useful for more deeply understanding DR-NCD policy inertia. It is also useful for identifying potential leverage points within the system which may shift the existing power dynamics to facilitate greater political commitment for healthy, equitable, and sustainable food system transformation.

Due to the rapidly aging population in Japan, the government has been attempting to link the healthcare delivery system with the long-term care delivery system. However, there are complex challenges that must be overcome to link the two systems. A new methodology should be used to organize complex community challenges and propose solutions. This study aimed to visualize the unique challenges and worldviews of interested parties in each community, using the soft systems methodology (SSM). We aimed to visualize issues and clarify challenges associated with linking the healthcare and long-term care delivery systems; in turn, clarifying the thought process behind solution proposals. We gathered information regarding those who are actively linking these systems in communities in a Japanese municipality (community care coordinators) and organized the information according to the SSM procedure. By organizing information using the SSM, we were able to summarize the present situations of the community healthcare and long-term care delivery systems, visualize issues, clarify challenges associated with linking these two systems, and propose solutions. The SSM may be useful in organizing complex community information and deriving solutions.

The complexity of systems now under consideration (be they biological, physical, chemical, social, etc), together with the technicalities of experimentation in the real-world and the non-linear nature of system dynamics, means that computational modelling is indispensible in the pursuit of furthering our understanding of complex systems. Agent-based modelling and simulation is rapidly increasing in its popularity, in part due to the increased appreciation of the paradigm by the non-computer science community, but also due to the increase in the usability, sophistication and number of modelling frameworks that use the approach. The Flexible Large-scale Agent-based Modelling Environment (FLAME) is a relatively recent addition to the list. FLAME was designed and developed from the outset to deal with massive simulations, and to ensure that the simulation code is portable across different scales of computing and across different operating systems. In this study, we report our experiences when using FLAME to model the development and propagation of conflict within large multi-partner enterprise system implementations, which acts as an example of a complex dynamical social system. We believe FLAME is an excellent choice for experienced modellers, who will be able to fully harness the capabilities that it has to offer, and also be competent in diagnosing and solving any limitations that are encountered. Conversely, because FLAME requires considerable development of instrumentation tools, along with development of statistical analysis scripts, we believe that it is not suitable for the novice modeller, who may be better suited to using a graphical user interface driven framework until their experience with modelling and competence in programming increases.

Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.

BACKGROUND: Updating, improving and spreading the evidence base for healthcare practices has proven to be a challenge of considerable magnitude - a wicked, multi-dimensional problem. There are many interlinked factors which determine how, why and whether any particular implementation effort or intervention succeeds. Soft Systems Methodology (SSM), strongly grounded in systems ideas and complexity science, offers a structured, yet flexible process for dealing with situations that are perceived as problematical and in need of improvement. The aim of this paper is to propose the use of SSM for managing change in healthcare by way of addressing some of the complexities. The aim is further to illustrate examples of how SSM has been used in healthcare and discuss the features of the methodology that we believe can be harnessed to improve healthcare.
CONCLUSIONS: SSM is particularly suited for tackling real world problems that are difficult to define and where stakeholders may have divergent views on the situation and the objectives of change. SSM engages stakeholders in a learning cycle including: finding out about the problematical situation, i.e. the context in which the problem exists, by developing a rich picture of the situation; defining it by developing conceptual models and comparing these with the real world; taking action to improve it by deciding on desirable and feasible improvements; and implementing these in an iterative manner. Although SSM has been widely used in other sectors, it has not been extensively used in healthcare. We make the case for applying SSM to implementation and improvement endeavours in healthcare using the example of getting clinicians at the hospital level to use evidence-based guidelines.
CONCLUSIONS: Applying SSM means taking account of the multi-dimensional nature of care settings, and dealing with entrenched and unique contexts, cultures and socio-political ecosystems - precisely those that manifest in healthcare. There are gains to be made in appreciating complexity and facilitating contextualization of interventions, and by approaching improvements in an iterative learning cycle.

In a socio-technical work domain, humans, device interfaces and artefacts all affect transformations of information flow. Such transformations, which may involve a change of auditory to visual information & vice versa or alter semantic approximations into spatial proximities from instruments readings, are generally not restricted to solely human cognition. This paper applies a joint cognitive system approach to explore a socio-technical system. A systems ergonomics perspective is achieved by applying a multi-layered division to transformations of information between, and within, human and technical agents. The approach uses the Functional Resonance Analysis Method (FRAM), but abandons the traditional boundary between medium and agent in favour of accepting aircraft systems and artefacts as agents, with their own functional properties and relationships. The joint cognitive system perspective in developing the FRAM model allows an understanding of the effects of task and information propagation, and eventual distributed criticalities, taking advantage of the functional properties of the system, as described in a case study related to the cockpit environment of a DC-9 aircraft. Practitioner Summary: This research presents the application of one systemic method to understand work systems and performance variability in relation to the transformation of information within a flight deck for a specific phase of flight. By using a joint cognitive systems approach both retrospective and prospective investigation of cockpit challenges will be better understood. Abbreviations: ATC: air traffic control; ATCO: air traffic controller; ATM: air traffic management; CSE: cognitive systems engineering; DSA: distributed situation awareness; FMS: flight management system; FMV: FRAM model visualize; FRAM: functional resonance analysis method; GF: generalised function; GW: gross weight; HFACS: human factors analysis and classification system; JCS: joint cognitive systems; PF: pilot flying; PNF: pilot not flying; SA: situation awareness; SME: subject matter expert; STAMP: systems theoretic accident model and processes; VBA: visual basic for applications; WAD: work-as-done; WAI: work-as-imagined; ZFW: zero fuel weight.

In complexity science, the many models thinking philosophy argues for a multi-method approach to complex problems. This article investigates whether the use of multiple systems ergonomics methods to examine the same problem is useful, or whether using different approaches creates incompatible analyses. Five systems ergonomics analyses of road trauma are examined and their key insights extracted. The extent to which these insights are compatible with one another and can be integrated when attempting to reduce road trauma is assessed. The findings indicate that applying several systems ergonomics methods to the same problem is useful, as multiple insights are developed and deficiencies in one approach are countered by the others. Importantly, the case study demonstrates that the insights gained are compatible and support the development of holistic systems thinking-based interventions. In conclusion it is recommended that a many systems ergonomics model thinking approach be adopted by ergonomists working in complex problem spaces. Practitioner Summary: Many model thinking uses multiple methods to understand complex problems. We explore whether this is beneficial in systems ergonomics. Five models of road trauma, developed using five systems ergonomics methods, are examined. The findings demonstrate that a many model systems ergonomics approach produces a diverse but complimentary set of insights.

Plague remains a public health problem in specific areas located in Bolivia, Brazil, Ecuador and Peru. Its prevention and control encompasses adequate clinical management and timely laboratory diagnosis. However, understanding communities\' interaction with its surrounding ecosystem as well as the differences between community members and institutional stakeholders regarding the root causes of plague might contribute to understand its endemicity. We aim at bridging the traditionally separate biological and social sciences by elucidating communities\' risk perception and identifying knowledge gaps between communities and stakeholders. This approach has been used in other areas but never in understanding plague endemicity, nor applied in the Latin American plague context. The objectives were to identify (i) plague risk perception at community level, (ii) perceived social and environmental determinants of plague endemicity, and (iii) institutions that need to be involved and actions needed to be taken as proposed by stakeholders and community members. The study was performed in 2015 and took place in Ascope rural province, La Libertad Region, in Peru, where the study areas are surrounded by intensive private sugarcane production.
We propose using a multi-level discourse analysis. Community households were randomly selected (n = 68). Structured and semi-structured questionnaires were applied. A stakeholder analysis was used to identify policy makers (n = 34). In-depth interviews were performed, recorded and transcribed. Descriptive variables were analyzed with SPSS®. Answers were coded following variables adapted from the Commission on Social Determinants of Health and analyzed with the assistance of ATLAS.ti®.
Results showed that risk perception was low within the community. Policy-makers identified agriculture and sugarcane production as the root cause while community answers ranked the hygiene situation as the main cause. Stakeholders first ranked governmental sectors (education, housing, agriculture and transport) and the community prioritized the health sector. Social surveillance and improving prevention and control were first cited by policy-makers and community members, respectively.
The determinants of plague endemicity identified by the two groups differed. Similarly, actions and sectors needed to be involved in solving the problem varied. The gaps in understanding plague root causes between these two groups might hinder the efficiency of current plague prevention and control strategies.

An integrative approach across disciplines is needed for sustainable lagoon and estuary management as identified by integrated coastal zone management. The ARCH research project (Architecture and roadmap to manage multiple pressures on lagoons) has taken initial steps to overcome the boundaries between disciplines and focus on cross-disciplinary integration by addressing the driving forces, challenges, and problems at various case study sites. A model was developed as a boundary-spanning activity to produce joint knowledge and understanding. The backbone of the model is formed by the interaction between the natural and human systems, including economy and governance-based subsystems. The model was used to create state-of-the-lagoon reports for 10 case study sites (lagoons and estuarine coastal areas), with a geographical distribution covering all major seas surrounding Europe. The reports functioned as boundary objects to build joint knowledge. The experiences related to the framing of the model and its subsequent implementation at the case study sites have resulted in key recommendations on how to address the challenges of cross-disciplinary work required for the proper management of complex social-ecological systems such as lagoons, estuarine areas, and other land-sea regions. Cross-disciplinary integration is initially resource intensive and time consuming; one should set aside the required resources and invest efforts at the forefront. It is crucial to create engagement among the group of researchers by focusing on a joint, appealing overall concept that will stimulate cross-sectoral thinking and focusing on the identified problems as a link between collected evidence and future management needs. Different methods for collecting evidence should be applied including both quantitative (jointly agreed indicators) and qualitative (narratives) information. Cross-disciplinary integration is facilitated by functional boundary objects. Integration offers important rewards in terms of developing a better understanding and subsequently improved management of complex social-ecological systems. Integr Environ Assess Manag 2016;12:690-700. © 2016 SETAC.