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Emma Aiken Thesis AN ECOLOGICAL MODEL FOR HEALTH, ILLNESS AND MEDICINE: Pathogenesis and healing as self-organising processes in semiotic biofields EMMA AIKEN Submitted for the Degree of Doctor of Philosophy – 2018 Department of Philosophy and Cultural Inquiry School of Arts, Social Sciences and Humanities Swinburne University of Technology, Hawthorn, Victoria, Australia i Abstract The dominant metaphysic in medicine, mechanistic reductionism, limits research to concepts of forceful causes acting on organisms. This entails the telos of biomedicine: to identify, isolate and control pathogens and pathological entities. Bio-psycho-social models developed in response to the need to grasp interrelated causes in multimorbid pathology have been limited by a lack of an adequate complexity-based ontology and epistemology for understanding pathogenesis and guiding treatment. A complex processes paradigm for understanding organisms and the causes of illness and healing is presented, focusing on the contribution of biofield theorists in understanding formal dynamics, and of biosemioticians in understanding telic causes according to the selective sensitivity and interpretative responses of need-feeling, anticipatory organisms. This semiotic biofield ontology forms the basis of the ecological model: in which symptoms are understood to be responses of the organism to its perceived needs, and healing is understood to involve processes that resolve or transform need states. The recognition and use of these causes in non-biomedical therapies is explored, and the common ontological grounds of these theories and therapies are reconciled in terms of semiotic biofields and their causal processes. The implications of this paradigm for transforming healthcare are discussed, including development of methodologies for assessment of pathogenesis based on the patient’s experience rather than multiple disease categories and causes, and non-forceful interventions to promote self-healing while avoiding the defensive responses generated by forceful interventions. ii Acknowledgements This work is the culmination of nearly thirty years of research in holistic medicine, psychotherapy and philosophy, and there are many to whom I owe a debt of gratitude. My lecturers in homeopathic philosophy and practice, John Wilmshurst and Elisha Norrie, for inspiring me to look further into the extraordinary claims of homeopathy. The interest and open-mindedness of psychology and philosophy academic staff and colleagues, who by their willingness to engage in creative discussions assisted me in making crucial reflections and connections between apparently diverse therapeutic practices. My supervisors, Michael Dix and Arran Gare, for invaluable support, feedback and inspiration, and the many other researchers in the fields of autopoiesis, biosemiosis and biofields for the extremely important work they are doing in changing our relationships with ourselves and the world for the better. My dear Jack and beloved Steven, for their patience and support. Colleagues within the biomedical community whose interest in this research has been very motivational. Last but not least, my clients and patients for teaching me so much about the processes of pathogenesis and healing in their stories and transformations. iii Declaration I declare that this thesis: i. contains no material which has been accepted for the award to the candidate of any other degree or diploma, except where reference is made in the text of the thesis; ii. to the best of my knowledge, contains no material previously published or written by another person, except where due reference is made in the text of the thesis; and iii. where the work is based on joint research or publications, discloses the relative contributions of the respective workers or authors. ……………………………………………………………… Date: 14/12/2018 Dr Emma Kate Aiken, D Psych iv Contents Abstract…………………………………………………………………….………ii Acknowledgments……………………………..…………………….……….……iii Declaration………………………………………………………………….……...iv Contents……………………………………………………………….……………v Introduction……………………………………………………….………………..1 Section One: The Metaphysics of Disease and Health 1. The Mechanistic Paradigm in Health……………………………………. 6 2. The Bio-Psycho-Social (BPS) Model………………….………………….20 3. Process Philosophy…………………………….………………………….35 4. Complexity-Oriented Biology…………………………………………… 53 Section Two: The Ecological Model 5. Adaptive Sequences: Normal Functioning and Need States……………91 6. Pathogenesis and Complex Pathology…………………………………. 119 7. Healing: Prompts and Processes ………………………………………..149 8. Evaluation of the Model: Comparison with Mind-Body Therapies…..177 9. Evaluation of the Model: Comparison with Homeopathy……………..202 10. Discussion and Conclusions……………………………………………...226 References…………………………………………………………………………239 v Introduction A quiet revolution has been occurring in science in diverse fields such as ecology, meteorology, economics, and evolutionary biology. In these sciences, the behaviour of whole complex systems over time is of central interest, and as technology has progressed to enable researchers to gather and process vast quantities of data over time, it has become both possible and necessary to make the complexity of whole systems accessible to study. This project is claimed to be more than just the application of new technologies to problems in science, rather it has been described as the construction of a new paradigm in science; one which attempts to grasp the behaviour of systems as wholes, rather than investigating the constituent elements of entities. Meteorologists can now make long term, accurate forecasts based on probabilities calculated from many data points recorded over time, to reveal underlying patterns or weather cycles that pertain to many spatio-temporal levels, from daily, local events to cycles that affect entire seasons globally, to models that assess probabilities for climate change over the next century. However, it should not be assumed that advances in technology can ever allow us to quantify every variable and predict the weather with certainty. Indeed, ubiquitous unpredictability in nature is an invisible "elephant in the room" of science. As the physiologist A. Szent-Gyorgyi observed: As soon as I revealed that in any living system there are more than two electrons, the physicists would not speak to me. With all their computers they could not say what the third electron might do. The remarkable thing is that it knows exactly what to do...1. For researchers and theorists in the fields of "general systems theory", it has become increasingly obvious since the conception of this project in the late 1920's that the behaviour of these systems is not reducible to natural laws describing matter in motion2. As such the analytical procedure that requires parts to be first isolated from each other and then related according to linear causal pathways is inadequate to understand the behaviour of dynamic systems3. Perhaps because nonlinearity and unpredictability are nowhere more apparent than in the most complex systems of all, living organisms, it is from the biological sciences that some of the most robust alternative ontological and epistemological stances to mechanistic reductionism have derived4. Yet, as this research will show, mainstream health practices have adapted poorly to this "new" paradigm, lacking the ontological and epistemological theory that is needed to grasp the dynamics of complex systems and take advantage of new approaches. In naming this a revolution, not just a common methodology for processing and interpreting large amounts of data, it is necessary to identify profound laws or core foci of theory and research that are novel and contrast with existing paradigms, and which lead to novel and important outcomes, finally maturing as a coherent structure for scientific 1 A Szent-Györgyi. Teaching and the Expanding Knowledge. Science 146 (1964): p. 1278-1279; cited in: L Bertalanffy General System Theory. (Penguin Press, London, 1971) p. 5. 2 L Bertalanffy, General System Theory, p.5-7 3 Non-linear mathematical modelling and the phenomenon of spontaneous order arising in complex systems is introduced in the context of evolutionary biology by Stuart Kauffman in The Origins of Order: Self-Organisation and Selection in Evolution. (Oxford University Press, New York, 1993) 4 The work of Terence Deacon, Jesper Hoffmeyer, Franscisco Varela, Brian Goodwin, Richard Levins and Richard Lewontin among others is discussed in Chapter 4 1 practices5. Across the diverse fields mentioned above, common, non-trivial parameters have emerged to guide research; that is, they have developed and matured in an empirical, data- driven manner, in response to the availability of the data and the need to organise and interpret this data in ways not available previously. Thus has evolved the ontology and epistemology of the science of wholes, of processes over time, and of unpredictability: the science of complex systems. When fully revealed, it stands in stark contrast to the science of analysis and control of parts; the mechanistic model that continues to dominate science today. Yet this is a quiet revolution, in the sense that in many ways, researchers in all fields of science are already grappling with the problems of complexity. In the most basic sense, these problems concern organisation and order in the management and comprehension of large quantities of data, a problem that even those who are largely concerned with the reduction of complexity to simpler, constituent elements cannot escape.
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