The Atlas of Social Complexity. Chapter 18: Complex Social Psychology

As I stated in my previous posts, The Atlas of Social Complexity is comprised of several content themes.

 

The first major content theme in The Atlas of Social Complexity is Cognition, Emotion and Consciousness. This first theme includes six chapters, which I have so far blogged on. Chapter 6 addresses autopoiesis. Chapter 7 turns to the role of bacteria in human consciousness. Chapter 8 explores how the immune system, just like bacteria and cells, is cognitive – and the implications this has for our wider brain-based consciousness. Chapter 9 explores a complexity framing of brain-based cognition, emotion and consciousness. Chapter 10 explores the complex multilevel dynamics of the Self. Chapter 11 is about human-machine intelligence.

 

The second major content theme in The Atlas of Social Complexity is The Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders ; Chapter 15: Healing and the therapeutic process; and Chapter 16: Mindfulness, imagination, and creativity.

 

The third major theme is living in social systems (Chapter 17), which was the focus of my previous post. The focus of this post is the first chapter in this theme, Chapter 18:

 

 

OVERVIEW OF COMPLEX SOCIAL PSYCHOLOGY

Symbolic Interactionism. Herbert Blumer 1969. C.E.[1] Of the various fields of study we will tour for Theme 4, social psychology plays a crucial role as the theoretical and empirical link between the dynamics of human psychology and the macroscopic patterns of social systems. It is all about social interaction, socialisation, families, small groups, social networks, organisations, values and beliefs, deviance and stigma, the presentation of self and identity, social media – what is generally referred to as the microscopic and mesoscopic levels of daily social life and living in social systems. One can also think of these topics as the nuts and bolts of social systems.

The challenge, however, is that many of the topics in social psychology, particularly from a sociological perspective, are not central to the complexity sciences or the study of social complexity. This absence is beyond odd given that the entire project of generative social science[2] and the core concepts of self-organisation and emergence are grounded in the idea of interacting agents engaging one another at the microscopic level, giving rise to the macroscopic social systems in which the live.

 

Sometimes the obvious is staring us right in the face.  

 

Fortunately, there are two fields of study addressing this absence.  

 

But first an important point about how we approach social psychology.

 

Social psychology can be approached in two distinct ways:  

Sociological social psychology (Soc-SP) and psychological social psychology (Psych-SP). While both examine the relationship between individuals and their social worlds, their focus differs significantly. Psych-SP emphasizes how social systems influence individual psychology, such as personality, identity, and beliefs, often adopting a person-centred and individualistic perspective. In contrast, Soc-SP centres on social interactions and systems, exploring how complex, symbolic interactions create social reality.

 

We advocate for the sociological approach, as it aligns with our commitment to understanding social complexity. Soc-SP highlights how personal struggles are often shared functions of broader systemic patterns, providing a foundation for studying collective behaviour, intersectionality, and resilience in socio-ecological systems. This interaction-centred perspective, rooted in traditions like symbolic interactionism and social constructionism, is vital for advancing computational social science and modelling methodologies, even as it remains underrepresented in the broader social and computational sciences.

 

With that clarification in order, the two fields we explore are:

 

Dynamical social psychology:

This field is an extension of the dynamical systems theory approach to human psychology outlined in Theme 2. The two most prominent figures in dynamical social psychology are Andrzej Nowak and Robin Vallacher.

 

Computational social science (i.e., social simulation):

While dynamical social psychology is mostly about applying complexity science to its topics of interest, which gives the field its narrowness in interest; computational social science, at least in its current form, is very much grounded in the social science turn, and is really about using computational tools to assist the study of various social science topics. Also, given the nature of many of the techniques in the field, there is a tendency toward the microscopic and mesoscopic; that is, the social psychological. For those new to the field, suggest spending time exploring the Journal of Artificial Societies and SocialSimulation, founded by Nigel Gilbert, the British sociologist, complexity scientist and leading figure in complex policy evaluation, agent-based modelling and social simulation.

 

 

KEY WORDS: Complex social psychology, computational social science, social simulation, dynamical systems theory, sociological social psychology, agency and structure.

 

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[1] Blumer, Herbert. Symbolic interactionism: Perspective and method. Univ of California Press, 1969/1986.

[2] Joshua M. Epstein, ‘Agent-Based Computational Models and Generative Social Science’, Complexity 4, no. 5 (1999): 41–60.

COMPLEX-IT: Enabling Non-Experts to Leverage Advanced Computational Modelling for Policy Evaluation and Decision Making

Much thanks to Rachel Caswell, Mohammed Amin Mohammed and Jennifer Wood for the chance to present on COMPLEX-IT at the Midlands Analyst Network Huddle as part of the NHS Strategy Unit.

A QUICK OVERVIEW OF THE COMPLEX-IT WORKSHOP

COMPLEX-IT: Enabling Non-Experts to Leverage Advanced Computational Modelling for Policy Evaluation and Decision Making

 

ABSTRACT

While the complexity sciences offer a new approach to thinking about social and health data, making use of their computational methods can be considerably challenging for non-experts – particularly postgraduate students, applied researchers, policy evaluators and civil servants. There is a solution! This workshop will introduce COMPLEX-IT, a free online R-platform designed for non-experts to employ the latest developments in machine learning, data visualisation, participatory systems mapping, network analysis, simulation, data forecasting, and cluster analysis. For our workshop, we will explore a real-world data set to walk through the steps of using COMPLEX-IT and the concepts of complexity science to show how these tools can help attendees gain new insights into social and health data. The goal is for participants to leave with a new methods platform they can use in their own work.

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For those who attended or simply might be interested, here are some links to the material from the day.

CLICK HERE for a link to the PowerPoint from the Workshop.

CLICK HERE for a link to COMPLEX-IT.

CLICK HERE for a link to the dataset we explored. NOTE: The dataset is a CSV (comma separated) file, created in EXCEL. It is just a sample to function as an example. It contains several public health indicators (e.g., access to health services, fuel poverty, crime, teen pregnancies, etc) for 100 authority districts in England, UK. 

CLICK HERE for a link to PRSM, the participatory systems mapping tool.

 

 

The Atlas of Social Complexity. THEME 3: LIVING IN SOCIAL SYSTEMS (Chapter 17)

As I stated in my previous posts, the Atlas of Social Complexity is comprised of several content themes.

 

The first major content theme in The Atlas of Social Complexity is Cognition, Emotion and Consciousness. This first theme includes six chapters, which I have so far blogged on. Chapter 6 addresses autopoiesis. Chapter 7 turns to the role of bacteria in human consciousness. Chapter 8 explores how the immune system, just like bacteria and cells, is cognitive – and the implications this has for our wider brain-based consciousness. Chapter 9 explores a complexity framing of brain-based cognition, emotion and consciousness. Chapter 10 explores the complex multilevel dynamics of the Self. Chapter 11 is about human-machine intelligence.

 

The second major content theme in The Atlas of Social Complexity is The Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders ; Chapter 15: Healing and the therapeutic process; and Chapter 16: Mindfulness, imagination, and creativity.

 

The focus of this post is THEME 3: LIVING IN SOCIAL SYSTEMS

Chapter 17 introduces this theme

2020 C.E. The Social Science Turn. The complexity turn in social science has come to an end. It is being replaced by a new movement, the social science turn in complexity. This new turn is an advance insomuch as it provides a way out of the thirteen challenges, in particular.

 

So, what happened to the complexity turn?

 

If one goes back to the 2005 special issue of Theory, Culture and Society,[1] which John Urry guest edited, one it taken by several things. The first is how theoretically flowing and philosophically oriented the issue is, including Urry’s opening article. Still grounded in the 1990s criticisms and concerns of postmodernism, poststructuralism, and the sociology of science, the special issue looks to complexity science not only as a way forward but also as a deconstruction of current scientific practice. Second, the promise of not only applying the complexity sciences to social inquiry, but also the potential to make the boundaries of disciplines and sciences more fluid and permeable infuses the spirit of the entire issue. Third, is the list of highly acclaimed authors,[2] which included (in order) Helga Nowotny (social studies of science), Fritjof Capra (physicist and author of The Web of Life), Adrian Mackenzie (sociology and social studies of Science and technology), Brian Wynne (science studies), David Byrne (case-based complexity, sociology), Cristian Suteanu (environmental science and complexity), John Smith and Chris Jenks (socio-ecology of complexity), Nigel Clark (geography), Graeme Chesters and Ian Welsh (social movements, qualitative methods), Karin Knorr Cetina (globalisation, markets, science studies, post-social theory), and Paul Cilliers (philosopher, complexity scholar). It is a veritable list of who’s-who for social complexity studies over the last thirty years. Finally, is the definition used to articulate the complexity turn. Urry states,

 

This new Special Issue seeks to reflect upon, to develop and in part to evaluate yet another turn, the complexity turn. This turn derives from developments over the past two decades or so within physics, biology, mathematics, ecology, chemistry and economics, from the revival of neo-vitalism in social thought, and from the emergence of a more general ‘complex structure of feeling’ that challenges some everyday notions of social order.[3]

 

For Urry, the complexity turn of the 1990s not only draws on the complexity sciences writ large, but also the neo-vitalist concerns in social inquiry at the time,[4] which had to do with getting back to processes, dynamics and the animated, living and aspects of social life and social systems. The complexity turn is also about the increasing complexities of globalised life at the end of the 20^th century – all of which would become part of the sales pitch for the value of complexity and complex systems thinking as a post-postmodern approach to social inquiry. Despite this trifecta of concerns, for Urry the complexity turn is still ultimately about transporting the theories, concepts, mathematics, and methods of complexity science, as developed by physics and the natural and computational sciences, into social inquiry – even if only on a metaphorical level, as Urry did his book, The complexities of the global.[5]

 

Or at least that is what the complexity turn constitutes for most scholars. There is always the adjacent possible, or in this case what one might call the social science turn within the complexity turn. In Urry’s special issue, the adjacent possible is David Byrne. Urry states:

 

In his article here, [Byrne] argues that the way to make complexity work as part of critical realist social science is through the comparative method and especially through its shaping of the tools of social science. This project he examines through a distinction between ‘simplistic complexity’ (rather like the reductionism Wynne argues against) and ‘complex complexity’. The latter involves a dialogical engagement with involved social actors seeking to transform social systems. He is less concerned with importing ideas from the sciences but rather with developing ways of thinking and challenging the social world through complexity understood as a more general epistème.[6]

 

As this quote demonstrates, the social science turn has always been a possibility for the study of social complexity. It was right there from the start. Byrne was visionary insomuch as he engaged the complexity sciences, while simultaneously recognising (as with the French philosopher and sociologist, Edgar Morin[7]) that certain ways of practicing it are problematic for social inquiry and therefore to be avoided. For Byrne, such a restrictive approach is entirely avoidable.

 

The complexity turn in social science happened over thirty years ago. During this time a tremendous amount of innovative and creative work took place applying the tools of complexity science to social inquiry.[8]  Of late, this innovation and creativity seems to be one of diminishing returns. The complexity turn, as a form of disruptive science, appears to be over.

 

FORTUNATELY, THAT IS NOT WHERE THE STORY ENDS!!!!

 

 

The social science turn in complexity is not a promise. It is not a panacea. It is more an advance by those who see themselves largely outside the complexity sciences. They see value in the tools of complexity and also social science and the humanities, and are simply trying to find ways to keep social inquiry disruptive by getting past one or more of the thirteen conditions. As with the other two themes, not all of the work in this area is equal in its innovation. There is still a lot to do. Hence the purpose of this part of our tour. We seek to identify key topics, with an eye to work waiting to be done by those reading the book.

 

Here are the lines of research for this theme:

 

• Complex social psychology (Ch 18)
• Collective behaviour, mass psychology and social movements (Ch 19)
• Configurational social science (Ch 20)
• The complexities of place at the local and global level (Ch 21)
• Socio-technological life (Ch 22)
• Governance, politics and technocracy (Ch 23)
• The challenges of applying complexity (Ch 24)
• Economics in an unstable world (Ch 25)
• Resilience (Ch 26)

 

 

KEY WORDS: configurational social science, sociology of collective behaviour, complex social psychology, complexity in policy and practice, resilience, governance, politics and technocracy.

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[1] See, Volume 22 Issue 5, October 2005, Theory, Culture and Society. Special Issue on Complexity. Editor: John Urry. https://journals.sagepub.com/toc/tcsa/22/5

[2] For more on these authors, visit the website or paper version of the special edition, listed in Footnote 1.

[3] John Urry, ‘The Complexity Turn’, Theory, Culture & Society 22, no. 5 (October 2005): 1–14. p. 1. References were removed from the quoted text to improve readability.

[4] See, for example, Fraser, M., Kember, S., & Lury, C. Inventive life: Approaches to the new vitalism. Theory, Culture & Society. 2005: 22(1), 1-14.

[5] Urry, J. The complexities of the global. Theory, culture & society, 22(5). 2005: 235-254.

[6] Ibid, pp. 9-10.

[7] See Morin, E. Restricted complexity, general complexity. Science and us: Philosophy and Complexity. Singapore: World Scientific, 2007, pp. 1-25.

[8] See D. S. Byrne, Complexity Theory and the Social Sciences: An Introduction (London: Routledge, 1998); Byrne and Callaghan, Complexity Theory and the Social Sciences; Brian Castellani and Frederic William Hafferty, Sociology and Complexity Science, Understanding Complex Systems (Berlin, Heidelberg: Springer Berlin Heidelberg, 2009).

Best Practices for Community-Based Medical Research. RENKEI Health Workshop: Developing Japan-UK research

I would like to thank RENKEI, the British Council Japan and Keio University for the opportunity to present at the Researcher Workshop: Developing Japan-UK research collaboration in Health, December 2024.

My lecture topic was Best Practices for Community-Based Medical Research 

In my presentation I focus on how we can advance health research through inclusivity, interdisciplinary methods, and complexity thinking. I define community health as more than the absence of disease—it’s about physical, mental, and social well-being—and I emphasize the importance of working collaboratively with local stakeholders to address pressing health issues.

I highlight the role of participatory research, where co-creation, respect for local knowledge, and shared decision-making are at the forefront. Through transdisciplinary methods, I aim to break down silos, tackle multifaceted health challenges, and create sustainable solutions. I also explore the complexities of place, recognizing how interconnected systems, social determinants, and geographic disparities shape health outcomes.

Acknowledging barriers such as power imbalances and limited funding, I point to success levers like trust-building, training in complexity science, and the development of flexible, adaptive research frameworks. My goal is to inspire a shift toward participatory approaches and the use of complexity thinking to better address the dynamic challenges faced by communities today.

 

HERE IS A LINK to my PowerPoint

CLICK HERE to visit InSPIRE Consortium 

CLICK HERE for a link the THE ATLAS OF SOCIAL COMPLEXITY

CLICK HERE for a link to COMPLEX-IT.

CLICK HERE for a link to the dataset we explored. NOTE: The dataset is a CSV (comma separated) file, created in EXCEL. It is just a sample to function as an example. It contains several public health indicators (e.g., access to health services, fuel poverty, crime, teen pregnancies, etc) for 100 authority districts in England, UK. 

CLICK HERE to visit CECAN (Centre for the Evaluation of Complexity Across the Nexus)

CLICK HERE to visit the MAP OF COMPLEXITY SCIENCES

 

 

 

The Atlas of Social Complexity. Chapter 16: Mindfulness, Creativity

As I stated in my previous post, the second major content theme in The Atlas of Social Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders and then Chapter 15: Healing and the therapeutic process.

 

The focus of this post is CHAPTER 16: Mindfulness, imagination, and creativity

 

OVERVIEW OF CHAPTER:

 

The human brain is a portal between the physical world and mental life. With the brain (as its own form of structure and organisation) acting as a bridge, the two domains, the physical and the mental, are not separate but deeply intertwined, such that life and reality regularly relent to the powers of imagination and creativity, meanwhile the mind is entirely embodied, including the metaphors by which we live.

 

Humans dream of flying and traveling past the speed of light; they imagine superheroes and demons; they create gods and monsters; they envisage lives outside the laws of physics, where reality is bent to their goals and desires and their hopes and dreams. Some humans dream the sublime and beautiful, others dream disturbing nightmares. They are all still dreams to which reality and nature regularly relent.

 

As Oscar Wilde famously stated in The Decay of Lying (1891) “Paradox though it may seem – and paradoxes are always dangerous things – it is none the less true that Life imitates art far more than Art imitates life.”

 

It is at the nexus of mindfulness, imagination, and creativity that the arts and humanities collide with the complexity science study of cognition, emotion, and consciousness.

 

To explore this nexus, the focus of this chapter, we examine the five key issues that need to be addressed.

• The first is that we need to be clear what mindfulness, imagination, and creativity mean.
• The second is understanding the different levels or degrees of creativity.
• The third is the adverse impact that hyper-specialisation has on these topics.
• The fourth is the continued restriction of creativity to a mental act, which ignores emotions, as in the case of spontaneous creativity and flow.
• The fifth is how creativity draws on our embodied minds and social life.

 

We end the chapter exploring what we see as the most promising inquiry in these areas. This chapter can be read in tandem with Chapter 32 ‘The Unfinished Space’.

One examples is the work of Orion Maxted[1] . Maxted is a British theatre performance artist based presently in Amsterdam. He studied computing, music and performance art and holds an MA in theatre. His work explores hybrid forms of performance that explore the nexus between complex systems, cybernetics, computation, language, musicality, and theatre. He calls this nexus ‘algorithmic theatre’ as the computational modelling taking place is done entirely by people, mostly through the usage of language. Several examples of his algorithmic theatre, such as flocking or flow, theatre of mind and the brain, can be seen online.[2]  The Theatre of Mind is an experimental piece “to transform the theatre and the audience into a collective intelligence, aka, a mind – achieved by connecting the audience together via mobile phones in a distributed-intelligence network or swarm intelligence – and creating feedback loops between what the audience collectively write, and the ideas that come into existence live on stage”.[3] The purpose of the piece is to ask such questions as: “Do the mind and the world share a common structure? Is the world becoming an increasingly interconnected ‘global brain’? And if so, how do we get the best ideas to rise to the surface and think about the survival of the group?” [4] What makes Maxted’s work so valuable is that, as a way of expanding the focus of the science of mindfulness, imagination and creativity, which is driven to seek answers, he finds value in pushing us to also ask other or different types of critical questions – which is just as powerful.

 

 

KEY WORDS: mindfulness, creativity, imagination, complexity and art, complexity and music, humanities and complexity theory.

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[1] For more, visit https://www.artscienceforum.nl/community/orion-maxted

[2] For more on this work visit https://vimeo.com/orionmaxted/videos. See also https://ias.uva.nl/people/artists-in-residence/current-and-former-artists-in-residence/orion-maxted.html?origin=kYo1rHhER0SPcrDyBywiFg

[3] http://www.artscienceforum.nl/community/orion-maxted

[4] Ibid.

The Atlas of Social Complexity. Chapter 15: Healing and the therapeutic process

As I stated in my previous post, the second major content theme in The Atlas of Social Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders.

 

The focus of this post is Chapter 15: Healing and the therapeutic process.

OVERVIEW OF CHAPTER

Chapter 14 explores the question: What does complexity have to say about healing and therapeutic process?

While historical texts on healing can be found across all cultures, the emergence of therapy as a specific technique for healing has a distinct history. In terms of the complexity sciences, our story begins in the 1950s with family systems theory and with the application of dynamical systems theory to therapy.

 

While theories of the family are endemic to social science, a systems view is distinct, getting its start when Gregory Bateson applied systems thinking to family communication patterns, thereby developing a systems approach to family therapy. Other key figures of the time were Jay Haley and John Weakland – who also worked on the Bateson project – as well as such pioneering scholars as Virginia Satir, Milton Erickson and Mara Selvini Palazzoli. Palazzoli developed the Milan model of family systems therapy,[1] which she later applied to schools, hospitals, and corporations. Theodore Lidz and colleagues,[2] advocating for the role of environmental factors, examined how schizophrenia emerges out of dysfunctional or pathological environments and emphasized – rightly so, as it still remains the case – that while biological models and psychopharmacology are of value, therapy, particularly family systems, is incredibly successful. Other major schools of thought include the Palo Alto Mental Research Institute, structural family therapy, and the intergenerational therapies of Murray Bowen, Ivan Boszormenyi-Nagy, and James Framo, which explore how the pathology of family life is passed down across generations.[3]

 

Somewhat distinct from family systems theory – but certainly in concert with its ‘systems’ view of psychopathology, including the role of familial and contextual forces, as well as the importance of social interaction, particularly between a therapist and client – is the formal application of dynamical systems theory to therapy. This approach starts with the complexity turn in social science. Here the heavy emphasis is on the value of dynamical systems theory, as a set of methodological tools, for modelling and doing therapy. While this includes a variety of computational modelling approaches, including simulation, genetic algorithms and complex networks, it is primarily grounded in the mathematics of dynamical systems theory. As readers may recall, the Swiss psychologist, Wolfgang Tschacher was (and remains) a key figure in application of dynamical systems theory to therapy.[4] Starting in the 1990s with his work on time and self-organisation, and then continuing onward to the study of embodiment and synchrony in the therapeutic process, Tschacher has been pivotal to the field’s development. Later, in the early aughties, he began working with Hermann Haken on the application of synergetics (a theory of nonlinear complex systems) to the dynamics of cognition, psychology and therapy[5] – all points we will get to later. Another key figure is the American psychologist, Adele Hayes. In particular is her 1998 publication, “Dynamic systems theory as a paradigm for the study of change in psychotherapy: an application to cognitive therapy for depression”.[6] Her work is central to the development of a dynamical systems approach to change in therapy, with particular emphasis on cognitive-behavioural therapy, associative networks, system flexibility, destabilization of pathological patterns, and the development of new patterns or attractors. Other key scholars include John Mordechai Gottman,[7] Helmut Schöller,[8] Fred Hasselman,[9] Günter Schiepek[10] and David Pincus.[11]

Despite their significant differences, these scholars (be they family systems theory or otherwise) variously embrace the following assumptions about the healing and therapeutic process. For our review, we will constrain ourselves to the therapeutic process, as the variety of settings and situations in which mental health healing takes place would require a level of detail beyond what we can address here. The majority of the literature also tends to focus on therapy (be it in an office, clinic, or hospital) as it provides a somewhat controlled setting for exploring the healing and therapeutic process.

 

Here are the topics we review in the chapter:

• the role of time in healing
• how therapy takes place within complex social systems
• the dynamics, nonlinearities, initial conditions and feedback loops in the therapeutic process
• embodiment and synchrony in therapy
• therapeutic process as both stochastic and deterministic
• self-organisation and attractors
• the stability of mental disorders
• how therapy is both time varying and time-invariant; symptom targeting; and therapeutic synergetics.

 

 

 

KEY WORDS: Synergetics in therapy, dynamical systems theory, synchrony in therapy, family systems theory, family therapy, psychotherapy.

 

 

 

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[1] Boscolo, Luigi, Gianfranco Cecchin, Lynn Hoffman, and Peggy Penn. Milan systemic family therapy: Conversations in theory and practice. Basic Books, 1987.

[2] Lidz, Theodore. "Schizophrenia and the family." Psychiatry 21, no. 1 (1958): 21-27.

[3] See footnote 4. See also Sexton, T. L., & Lebow, J. (Eds.). Handbook of family therapy. Routledge 2016.

[4] Wolfgang Tschacher, ‘Time and Embodiment in the Process of Psychotherapy: A Dynamical Systems Perspective’, in Time and Body, ed. Christian Tewes and Giovanni Stanghellini, 1st ed. (Cambridge University Press, 2020), 104–16.

[5] Wolfgang Tschacher and Hermann Haken, ‘Causation and Chance: Detection of Deterministic and Stochastic Ingredients in Psychotherapy Processes’, Psychotherapy Research 30, no. 8 (16 November 2020): 1075–87.

[6] Adele M. Hayes and Jennifer L. Strauss, ‘Dynamic Systems Theory as a Paradigm for the Study of Change in Psychotherapy: An Application to Cognitive Therapy for Depression.’, Journal of Consulting and Clinical Psychology 66, no. 6 (1998): 939.

[7] Gottman, John M., et al. The mathematics of marriage: Dynamic nonlinear models. MIT Press, 2005.

[8] Schöller, Helmut, et al. "Personality development in psychotherapy: a synergetic model of state-trait dynamics." Cognitive Neurodynamics 12 (2018): 441-459.

[9] Hasselman, Fred, and Anna MT Bosman. "Studying complex adaptive systems with internal states: A recurrence network approach to the analysis of multivariate time-series data representing self-reports of human experience." Frontiers in Applied Mathematics and Statistics 6 (2020): 9.

[10] Schiepek, Günter K., et al. "Psychotherapy is chaotic—(not only) in a computational world." Frontiers in Psychology 8 (2017): 379.

[11] Pincus, David, and Annette Metten. "Nonlinear dynamics in biopsychosocial resilience." Nonlinear dynamics, psychology, and life sciences 14, no. 4 (2010): 353.