Complexity Theory

“ . . . beyond methods and tools, the articles in this special issue are proof that complexity science has provided IE an overarching knowledge paradigm that matches the continuously evolving resource, production, and consumption systems that are the object of study in the field.” co-authorship networks, and offer application of complex systems models and analyses. The articles demonstrate the links, relevance, and implications of many (often emerging) fields of study to IE, including network analysis, participatory modeling, nonequilibrium thermodynamics, and agent-based modeling. Together, these articles show that IE itself is a complex adaptive system, where knowledge, frameworks, methods, and tools evolve with and by their applications and use in small and large case studies— multidisciplinary knowledge ecology. In the special issue “Complexity and Industrial Ecology” (Volume 13, Number 2, 2009), Dijkema and Basson (2009, 157) propose that “ . . . complexity theory and its tools has potential to shift the frontier of Industrial Ecology, by enhancing the quality of systems analysis and by underpinning recommendations for redirecting industrial development towards sustainability.” Indeed, in action-oriented IE (Nikolic et al. 2009), we arguably study “complex, layered and dynamic systems that interact with their environment and thereby perpetually affect one another” (Dijkema and Basson 2009, 157). Indeed, we study sociotechnical systems, where the social evolves the technical and vice versa (de Bruijn and Herder 2009). Both their evolution and impact occur at multiple spatial, temporal, and systems scales. Where it has been argued that “sustainability” is an anthropocentric, normative concept (Allenby 2009; Ehrenfeld 2007), from complexity science we may learn that sustainability is an emerging characteristic of the complex adaptive system of our planet earth and any subsystem or part thereof (Nikolic et al. 2009). Taking a complex systems approach and applying complex systems methods can thus deepen and broaden our understanding of resource, production, and consumption systems. In fact,

IntroductionThe human body's response to pain is indicative of a complex adaptive system. Therapeutic yoga potentially represents a similar complex adaptive system that could interact with the pain response system with unique benefits.ObjectivesTo determine the viability of yoga as a therapy for pain and whether pain responses and/or yoga practice should be considered complex adaptive systems.MethodsExamination through 3 different approaches, including a narrative overview of the evidence on pain responses, yoga, and complex system, followed by a network analysis of associated keywords, followed by a mapping of the functional components of complex systems, pain response, and yoga.ResultsThe narrative overview provided extensive evidence of the unique efficacy of yoga as a pain therapy, as well as articulating the relevance of applying complex systems perspectives to pain and yoga interventions. The network analysis demonstrated patterns connecting pain and yoga, while complex systems topics were the most extensively connected to the studies as a whole.ConclusionAll three approaches support considering yoga a complex adaptive system that exhibits unique benefits as a pain management system. These findings have implications for treating chronic, pervasive pain with behavioral medicine as a systemic intervention. Approaching yoga as complex system suggests the need for research of mind-body topics that focuses on long-term systemic changes rather than short-term isolated effects.


 
 
 To say something is complex can often be conclusive. It can mean that an issue or an idea is too difficult to explain or understand, or has too many aspects to examine clearly. In many ways the designation “complex” can be an abdication, an end to an argument or discussion. An epochal change in thinking about complexity dates from post structuralist challenges to the idea that the world was known by arguing that everything was indeed much more complex than master narratives would suggest. In the last decade a social scientific engagement with complexity theory has meant that social and cultural meanings of “complex” and “complexity” are being explored. “Complex” has also made a renaissance within the popular and everyday imagination. Reference to “complex” and “complexity” can be found in advertising campaigns for Sydney City Rail (Figure 1), as well as advertising for a telecommunication company (Figure 2). Figure 1 Figure 2 In our feature article Bob Hodge provides a detailed analysis of Sydney City Rail’s “Rail Clearways” advertising campaign. In a comparable campaign, a telecommunications company claims “Simplicity trumps Complexity”. It seems that advertisers will call any networking system “complex” because its binary is “simple”, from the Latin simplex. Simple versus Complex creates a nice image of a telecommunication company possessing a SIMPLE solution for any COMPLEX networking system. “Simplicity trumps Complexity” denotes a competition between the two meanings and a “simple” solution for “complex” networking needs can be found within this company’s product portfolio. Rather than position “complex” in competition with “simple”, we wanted to explore the possibilities of “complex”. The idea of “complex” as a beginning, not a conclusion, has been the driving concept behind this journal edition. This M/C Journal edition assembles seemingly disparate interpretations of “complex”. We did not want to reduce a journal edition on “complex” into “simple” neat links. Instead, we have grouped the articles together under four titles: “‘Complex’ and Affect: Complexities in the Concept of Love”, “Situating ‘Complex’ within Fixed Social and Cultural Systems”, “Positioning ‘Complex’ in Cultural Theories” and “Locating ‘Complex’ in Design”. This thematic arrangement demonstrates how each interpretation of “complex” forms assemblages and from this other assemblages can be formed. Such an approach reveals the way in which “complex” entities emerge from “complex” processes. Our feature article, “The Complexity Revolution”, outlines and categorises complex(ity) in its varying forms. Bob Hodge positions complex(ity) in popular culture, science and humanities. Complex(ity)’s popular meaning reduces the concept to something that is intricate, involved, complicated or multi-dimensional. In a more negative sense complex(ity) is often stripped to simplicity. This article decodes Sydney City Rail’s “Rail Clearways” publicity campaign “untangling our complex rail network” to illustrate how complex(ity) is not reducible to simplicity, it is not strictly a positive or a negative but encompasses many meanings located with popular culture, science and humanities. “Complex” and Affect: Complexities in the Concept of Love “The Heart of the Matter” positions romantic love as productive force and explores the complexity that lies within the notions of love and desire. Richard Carpenter examines why romantic love is so complex by exploring its development from a romantic ideal to encorporating notions of desire. Carpenter explores the move from love as fusion, encapsulated by the movie Jerry Maguire (“you complete me”), to Anthony Gidden’s “plastic sexuality” where desire is detached from reproductive imperatives. It is not that we have moved past romantic love, Carpenter argues, but that we should explore the complex range of possibilities created by its productive force. Adding to this exploration of love’s complexities, Glen Fuller uses the film Punch Drunk Love to illustrate the contingent nature of contemporary romance. Inspired by a conversation with a woman who claims “everyone does rsvp” this paper probes the very notion of love by relating the experiences of the film’s lead characters, Barry and Lisa, to theories by Badio and Deleuze. The continual striving for an elusive harmony is presented as the materiality of love; reconciling love’s contradictions by suggesting it is the problematic nature of romance that elicits the “wonder at the heart of love”. Situating “Complex” within Fixed Social and Cultural Processes Mario Lopez’s article explores contemporary Japanese-Philippine relations through an ethnographic study in Japan on marriages between Japanese men and Filipino women. In this article, he focuses on one aspect of his research: Filipino women attending a ‘care-giver’ course and the outcomes. Japan’s aging society and a shortage of labour in Health Care Facilities has sparked an effort by the Japanese State to source and educate Filipino women to fill the labour void. “Bride to Care Worker” outlines how Filipino women are located within a complex system of nation-state relations. It has become common to claim that we live within a culture of fear and a by-product of this is increased surveillance technologies. “Commodifying Terrorism” explores London’s Metropolitan Police use of Closed Circuit Television (CCTV) cameras to monitor and control public spaces. Yasmin Ibrahim examines how surveillance systems like CCTV locate the body and its everyday actions as stored data in an effort to “combat” terrorism and make public spaces “safer”. The ramifications are that it constructs and supports new power relationships and new risk hierarchies; raising questions of how surveillance technologies are making us safer. In “Decisions on Fire” Valerie Ingham asserts one thought process or model cannot encompass the complex decisions made on the fire-ground. Ingham argues incident commanders use “Multimodal Decision Making” a term that she developed from her ethnographic research with fire-fighters. “Multimodal Decision Making” illustrates how sensorial awareness and experiential knowledge is used when assessing and recommending a course of action to fight fires. Positioning “Complex” in Cultural Theories Sarah James examines one mural, from one street in San Francisco’s, predominantly Mexican, Mission District. She assesses how it is symbolic of complex assemblages denoting a diasporic community, post colonial histories and cultural hybridity. “Culture and Complexity: Graffiti on a San Francisco Streetscape” argues complexity theories can extend and contribute to established concepts in humanities such as post colonialism and cultural hybridity. Karen Cham and Jeffrey Johnson argue that complex systems are cultural systems. They trace the developments within interactive digital media and industry design practice to illustrate the relationship between art and complex systems. This relationship is epitomised by the possibilities inherent within interactive media for experimentation and innovation. Drawing on post-structural, science and art theory, Cham and Johnson suggest that digital mediums serve as a model that highlights the nature of complex adaptive systems. Locating “Complex” in Design A labyrinth epitomises complexity in design with its numerous choices of pathways and directions. In “A Vision of Complex Symmetry”, Ilana Shiloh applies a complexity perspective to the Coen Brothers’ neo-noir film The Man Who Wasn’t There (2001) by arguing its symbolic relationship to a labyrinth. Shiloh uses the labyrinth as a metaphor to highlight the difference between rationalistic genre in detective fiction in which complexity is simplified by the work of the detective to film noir in which the audience is taken deeper into the labyrinthine maze of a story where little makes sense and nothing is what it seems. Vince Dziekan’s curatorial project during his recent “Remote” exhibition inspired his interactive piece for our journal edition. In his paper Dziekan’s explores the creative process behind curatorship, presenting it as a design process which adds levels of complexity to the experience of the gallery space. By creating an interactive element to his work, Dziekan’s draws the reader into the experience of curatorial design, using layers of black, magenta, cyan and yellow. Each colour represents an aspect of design: the ‘black’ layer is a synopsis of curatorial design and complexity, the article is situated within the four magenta layers, the cyan layer provides a visual experience of the exhibition and the yellow layer embodies Marcel Duchamp’s “Mile of String”. Dziekan’s work is symbolic of “complex” representing layers of concepts each interacting, reflecting and affecting the other. Through these papers this journal edition presents an exploration of the idea of “complex”. A complex “revolution” (in a quiet way) infuses the vast range of topics by adding depth to challenge all types of research. This journal, in keeping with the idea of complex, illustrates the possibilities from which to start/continue in an effort to expand rather than limit the possibilities of further explorations of “complex”. 
 
 Citation reference for this article
 
 MLA Style
 Cahir, Jayde, and Sarah James. "Complex." M/C Journal 10.3 (2007). echo date('d M. Y'); ?> <http://journal.media-culture.org.au/0706/00-editorial.php>. APA Style
 Cahir, J., and S. James. (Jun. 2007) "Complex," M/C Journal, 10(3). Retrieved echo date('d M. Y'); ?> from <http://journal.media-culture.org.au/0706/00-editorial.php>. 

A complex biosphere: Fragile Dominion: Complexity and the Commons, by Simon Levin

To discuss multiple organ dysfunction syndrome (MODS) from a complex systems' theory perspective and to delineate a conceptual framework for the development and care of MODS. MODS is an intricate and devastating manifestation of critical illness characterized by widespread aberrant molecular, cellular and systemic responses. Narrative literature review (MEDLINE, CINAHL databases) and knowledge synthesis with the theoretical assertions of chaos and complex systems' theory. Cellular and systemic response paradoxes in MODS (including cellular hypoxia, cell death and signalling) are reviewed. The diseased person is depicted as a complex adaptive system. The relevancy of some of the principles of complex chaotic systems' theory to the proposed model is illustrated, including sensitive dependence on initial conditions, emergence, attractors, self-organization, self-organized criticality and emerging order. The transition from life-supporting to death-related organismic responses is illustrated as a critical event in MODS and care implications are drawn. Patient responses in MODS appear to conform to the principles of chaotic systems. Death is illustrated not as a consequence of homeostatic failure but as a 'deliberate' self-organized phenomenon entailing multiple dynamically evolving mechanisms. Some of the principles of chaotic complex systems may need to be taken into account to advance care in MODS. An alternative theoretical perspective may support nurses to conceptualize both MODS and their role in a way that will help them to cope better with this devastating syndrome and develop practice.

Machinic Heterogenesis and Evolution

<i>Introduction to the Modeling and Analysis of Complex Systems.</i> H. Sayama (Ed.). (2015, Open SUNY Textbooks). Free open access PDF, 498 pp. ISBN 978-1-942341-06-2 (deluxe color edition). ISBN 978-1-942341-08-6 (print edition). ISBN 978-1-942341-09-3 (ebook).

The Complexity of the Homeopathic Healing Response Part 2: The Role of the Homeopathic Simillimum as a Complex System in Initiating Recovery from Disease.

Cormac McCarthy: A Complexity Theory of Literature

The emergence and use of complex adaptive systems remedied the need for a new alternative by resorting to existing paradigms. Both the health care system and nursing can be regarded as complex adaptive systems by applying a visual model that should be explored to empower the complexity of the science of nursing and health care. Viewed from this perspective, a nurse is a complex adaptive system, one that is dynamic and interacts, but is also an agent of a complex adaptive system in a nursing unit, which in turn is a complex adaptive system in a health organization. Today, nursing professionals seek to be current in terms of training and skilled in a variety of special fields, ranging from neonatal nursing to geriatric care, in order to do their job and to envision a working environment from the perspective of a complex system. Consequently, through complex systems based on shared knowledge among various professional and teamwork, organization of the health-care system is able to enjoy the support of the client-user-professional chain.

The paper examines the evolution in international commercial marriage migration from Southeast Asia to South Korea from a Complexity Theory (CT) framework, originally from natural sciences but vastly entering the field of social sciences. CT stresses the non-linear nature of complex systems that are composed of a large number of individual components operating within a conditioned boundary whose interactions lead emergent properties in an unpredictable way. The study is based on the author’s fieldwork interviews and participatory observations of marriage migrants, government officers, and social workers in South Korea in 2010-2013, which establishes five phases of brokered marriages, namely, (1) Outsourcing Brides (mid 1980s-), (2) Emerging Anti-Trafficking Norms (early 2000s-), (3) Institutionalizing Multiculturalism (2006- ), (4) Regulating Brokers (2008-), and 5) Sham Marriages and Emerging Nationalism (2010-). She explains the key elements of marriage migration as a complex adaptive system such as feedback loops, adaptation, emergence, self-organisation and agency, and suggests persistent observation and CT as an alternative methodology to study migration.

Concepts from complexity science are familiar experiences for those working in primary health care. We work with people, each one different from every other. We have the privilege of knowing our patients over long periods of time, and this helps us understand them better. We are not surprised by how differently patients respond to a particular treatment. We witness the influence of family and community on our patient’s experience of health and illness and the opportunities and constraints of health care provision within our organizational and policy context.1 As clinicians, we may work within organizations comprised of many individuals and experience the effect of the quality of communication on the organization.2 When we visit a different primary care practice, even though they may have similar objectives and resources and work in a similar way to our own, the difference in the character of the practice is often striking.3 Complexity sciences seek to understand complex systems. People and primary care organizations are examples of complex systems. They have emergent properties that are not explainable using linear models of interaction or causality. Seemingly similar complex systems such as people or organizations become diverse as small differences become amplified through interaction and feedback. The history of a complex system influences its current properties and these constantly evolve. The system is engaged within its context, changing it and being changed.4 Despite the apparent fit between complexity sciences and primary health care, what complexity sciences have to offer primary care research is still an open question. As a novel approach to research, complexity science challenges us to think clearly about the nature of reality and how we come to understand it, questions of ontology and epistemology, and challenges our understanding of causation and how we detect it. Where we are stuck on a particular problem, complexity sciences may offer an innovative way of thinking about it without necessarily needing new research methods. Studying interaction and its dynamics, and studying emergence may be of particular importance for primary care research and require learning or developing new research methods. Arguably the most robust current research in complexity sciences looks inside complex inanimate or cellular systems. Examples include energy networks, computer networks, moving fluids, and cellular enzyme systems. Large volume longitudinal data is collected and analyzed using data mining techniques. Computer simulation of the system can be compared with real life. Mathematics succinctly describes the structure and dynamics of the system. These research approaches require data that capture interaction. We have data about information exchange within our primary care organizations that can be analyzed in terms of network structure and dynamics. Similarly, patient interaction with health care may be explored through case by case longitudinal analysis of our patient data. However, our patients interact with their social and environmental context, and this influences their health.5 This dynamic interaction is poorly documented within available health care data. Linkage of large data sets from social surveys, census, and health care may provide future opportunities for analysis of this dynamic interaction; however, smaller scale mixed-method longitudinal research is likely to be more productive in the short term. Although medical science can claim many successes, there are health problems, for example low back pain and depression, where it can be argued traditional research approaches seem to be stuck. A complexity sciences approach may consider such health problems emergent phenomenon arising from the interaction of many different factors, biological, psychological, technological, social, and environmental. Emergence cannot be tracked back to a particular cause. Similarly, interactions between patients and physicians have emergent properties that are not determined by the patient or the doctor, but develop through their interchange. The function of a primary care practice emerges from the interaction of those who work there, the patients and context. Understanding emergence is a challenge for complexity science, not just for primary care, and is receiving attention from many research disciplines. NAPCRG will continue to serve as a forum for complexity science researchers to learn from one another and to create new, practical insights that will improve the design and delivery of primary health care.

Complex adaptive systems (CAS) have been identified as being hard to comprehend, composed of multiple interacting components acting interdependently with overlapping functions aimed at adapting to external/environmental forces. The current theoretical model utilized the natural functions of teams, viewing teams as a complex adaptive system, to develop the structure of the theory of complex adaptive team systems (CATS). The CATS model was formulated around the components of complexity theory (interactions, nonlinearity, interdependency, heterogeneity, complex systems, emergence, self-organizing, and adaptability) to show its utility across multiple domains (the role of leadership, organizational learning, organizational change, collective cognitive structures, innovation, cross-business-unit collaborations). In theorizing the CATS model, a new level of analysis was implemented, the interactions between agents as a move toward emergence in complex systems. The CATS model ultimately provides a model for organizations/institutions to drive knowledge creation and innovation while operating in today's complexity.

‘If it is complex it means we don’t really understand it,and the way forward is to break the problem down into its partsto make sense of it’. This thought reflects the way we havebeen taught, and the way we largely practise in clinical care everyday.But are we really functioning on this basis? Or is it the only waywe know how to live? We all experience situations every daywhere the evidence does not really fit our understanding of aproblem – the familiar reductionist approach limits our ability tofully explore new problems and to gain new insight. An increas-ingly persistent question has emerged in relation to what consti-tutes the knowledge we need for effective and efficient clinicalcare, an issue taken up by this new

Complex adaptive systems (CAS), to reiterate, are systems composed of many individual parts or agents in which patterns can emerges as a result of agents deploying "simple rules" from the "bottom-up" without external control—CAS are "self-organizing" systems. "Simple rules" in health care would include seeking to optimize both patient well-being and the functioning of professionals. If elements of a CAS system are altered, the system adapts or reacts. The behaviour of a complex adaptive system can be inherently unpredictable and non-linear as elements of the system, the internal (eg, professionals and managers) and external agents (eg, patients, families, and society), have multiple perturbations, changes, and interdependencies. Despite the flurry of interest in complex systems and non-linear dynamics in recent decades, application of knowledge and innovation about complexity and adaptation in systems for health care has been slow. Critics typically state that there is no "evidence" that applying CAS and complexity science is needed or "works" in the real world of health care systems.1 It is almost a decade since the issues of practicability were first raised in this Forum in 2009.2 Has progress been made? A PubMed scan (Figure 1) provides some comfort in the growth of applications of CAS thinking in health research. In this Forum, Wietmarschen, Wortelboer, and van der Greef3 provide a highly accessible vision for the future of complex adaptive systems and why they are needed. They re-articulate why a shift is needed from static silos of diagnoses and linear structures toward a more integrated biopsychosocial way of thinking about health, using systems thinking approaches. Moreover, in their far-sighted appraisal of Western lifestyle problems of obesity and sedentary behaviours, they demonstrate practical modelling techniques integrating molecular with cognitive and psychological metrics, and variables from different layers of human functioning. A systems dynamics software tool called Method to Analyse Relations between Variables using Enriched Loops was used to create the model during the group sessions. The resulting model contained various positive and negative feedback loops connecting multiple health domains, indicating non-linear mechanisms affecting processes that cross multiple health domains. These techniques have been applied to the analyses of individual trajectories in a clinical approach to obesity in Vogellanden-Centre for Rehabilitation, Zwolle, the Netherlands. System dynamics modelling (SD), is an interdisciplinary modelling method used for representing and understanding the behaviour of complex systems. An SD model consists of a series of stocks, which represent the total people receiving a type of service at a given time, interconnected through flows, which represent the movement of people from one stock to another over time. Participatory approaches align stakeholder understanding of the underlying causes of a problem and can achieve consensus for action. Advances in software are allowing the participatory model building approach to be extended to more sophisticated multimethod modelling that provides policy makers with more powerful tools to support the design of targeted, effective, and equitable policy responses for complex health problems.4 Cepoiu-Martin and Bischak5 utilized a system dynamics model of the Alberta Continuing Care System (ACCS), Canada, using stylized data to assist service planning. They explored policies of introducing staff/resident benchmarks in both supportive living and long-term care (LTC) in the background of predicted increases in the population of people with dementia and the provision of staffing benchmarks, The ACCS model developed, by going beyond linear cause-effect considerations, and allowed the exploration of the entire network of causal relationships between various components of the system. It provided evidence of applicability of SD simulation to analysis of the impact of adopting benchmarks related to the staff/resident ratios in the continuing care system in Alberta. The model provides a basis for future evaluations of interventions in the workforce development area, capturing all feedbacks that modify balance between staff supply and demand in the age care sector. The following three papers highlight practical applications at the clinical coal-face, albeit all are early stage studies. Bandini et al6 have successfully piloted a clinical tool for episode complexity in inpatient care on internal medical wards. Episode complexity represents the need for greater time and effort (compared with other patients and episodes) with respect to clinical assessment and treatment; relationships with the patients, caregivers, other specialists, and actors in the health care network; and information gathering and processing. A very interesting emergent finding from their study is that multimorbidity as measured by the Charlson comorbidity index was not a good predictor of episode complexity, as patients with multiple comorbidities often had simple hospital episodes while those without little comorbidity (low Charlson comorbidity score) had much more complex episodes with much less certain outcomes. The dynamics of those individual illness trajectories were not predicted by standard static disease based metrics nor supported by guidelines. Individual trajectories or journeys is a recurring theme in the developing CAS approaches in health care, representing the opportunity for responding to health status dynamics in a timely manner.7 This notion of intellectual work and time as markers of clinical complexity was also raised by Katerndahl et al in a previous analysis of medical work across clinical specialities.8 In complex systems, as the information in the input increases linearly, the complexity of the system increases exponentially. Thus, a simple rule is suggested, that clinical work complexity reflects the amount of care provided weighted by its diversity and variability. Primary care, because of its diversity and variability, scores highly on the amount of work demanded of its practitioners. In this theme, Fink et al9 describe the application of a clinical tool—Diagnostic Protocols (DP)—in a single handed practice over a 14-year period. Based on several decades of work by Braun and colleagues, DP represents a series of simple rules to reduce uncertainty in primary care presentations of serious conditions that may seem at first contact to be routine and non-serious. Here, we have the common theme of simple rules to identify courses of action related to simple and complex dynamics in patient trajectories over time in clinical care. At an organizational level, leadership is a crucial element of success, and its role is recognized as an important factor for achieving better performance and optimizing health improvements for patients. Horvat and Filipovic,10 using complexity leadership theory, identified three types of leadership and matched them to indicators of organizational maturity. Administrative leadership is grounded in traditional, bureaucratic notions of hierarchy, alignment, and control. Enabling leadership structures and enables conditions in which CAS can optimally address creative problem solving, adaptability, and learning. Adaptive leadership exemplifies a generative dynamic that underlies emergent change activities. Organizational maturity promotes organizational learning, enables effective and efficient management performance, reduces errors, and adapts to internal and external dynamics. Sustained success can be achieved by the effective management of the organization, through awareness of the organization's environment, by learning, and by the appropriate application of either improvements, or innovations, or both.11 Their survey of Serbian managers supported the hypothesis that administrative leadership had little influence on any maturity category of health care organizations. Adaptive and enabling leadership had greater association with managerial maturity. However, both adaptive and enabling leadership were also correlated with administrative leadership reflecting the entanglement of traditional structures and cultures of health care organizations with bottom-up informal emergent forces. A question that might be asked is: whether administrative leadership maintain the status quo by constraining emergence and self-organization to the detriment of organizational adaptability and learning? On an optimistic note, de Bock et al12 provide a case study of such bottom-up informal complex adaptive forces that successfully shifted clinical decision-making from professional silos into transdisciplinary inter-professional working. These shifts were driven by the internal and external tensions about caring for a longitudinal patient journey beyond technical rescue. The personal power of the nurses who were by the bedside, and their "bottom-up" understanding of the patient's needs, catalysed interdependent interactions and self-organization within the different professional groups. Care was thus adapted to patient-centred approaches beyond reductionist repair modes of thinking. This Forum highlights this emerging implementation of practical, but early stage CAS approaches to improving the outcomes of clinical care and health care more generally. To progress, a vision and practical goals for the shift needed from a conservative medical hierarchical disease focus, toward a more integrated biopsychosocial dynamic interactive ways of thinking about health.3 Tools to enable such implementation are needed, and four different practical approaches to deploy CAS theory in clinical care are highlighted that demonstrate innovation and adaptive thinking. They demonstrate a transition into enabling and adaptive leadership roles from the bottom-up. Yet the paper by Horvat and Filipovic provides some explanation about the slowness of the such transitions related to the challenges to complexity based leadership, with the ever-present dominant conservative health organizations. Administrative leadership models and cultures seeks to maintain the status quo and, for all intense and purposes, stand in the way of innovation and the emergence of "adapting and innovative" processes of care, system organization, and leadership. The International Organization for Standardization, a worldwide federation of national standards bodies (ISO member bodies), states that achievement of sustained success for any organization in a complex, demanding, and ever-changing environment requires enabling and adaptive leadership in health organizations.11 Health care will have to go through a huge cultural change to improve its organizational maturity with enabling and adaptive leadership. There is a need to successfully shape new ways of working and organizing in the evolution of health care. The role of adaptive leadership, as Ron Heifetz pointed out so eloquently, is not to solve problems, but rather to facilitate the necessary adaptive work of the people directly confronting the problems, often in the front-line in health care.13