Handbook of Research Methods in Complexity Science
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Handbook of Research Methods in Complexity Science

Theory and Applications

Edited by Eve Mitleton-Kelly, Alexandros Paraskevas and Christopher Day

This comprehensive Handbook is aimed at both academic researchers and practitioners in the field of complexity science. The book’s 26 chapters, specially written by leading experts, provide in-depth coverage of research methods based on the sciences of complexity. The research methods presented are illustratively applied to practical cases and are readily accessible to researchers and decision makers alike.
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Chapter 26: Dynamical systems therapy (DST): complex adaptive systems in psychiatry and psychotherapy

Theory and Applications

Professor Yakov Shapiro and Associate Professor J. Rowan Scott

Abstract

The synthesis of complexity and nonlinear science with evolutionary theory informs both functional neuroscience and psychotherapeutic exploration of conscious and unconscious processes. The nonlinear dynamical systems approach allows psychiatric practitioners to shift from categorical diagnostic and treatment algorithms to integrative process models of individual and group dynamics. Dynamical systems therapy (DST) represents a complexity derived application that conceptualizes individuals as Complex Adaptive Systems with emergent properties of subjective and cultural experience. It puts self-organization and flexible adaptation to changing environmental demands at the cornerstone of psychological health. Within the DST model, recurrent patterns of feeling, thinking and relating can be analysed by using modified fitness diagrams (adaptive A-landscapes), which integrate objective, subjective and intersubjective clinical data. This approach allows to chart the patient’s unique life trajectory through attractor/repellor configurations and reveals a paradigm shift from reductionism towards systemic psychobiology conceptualized as an integrative scientific perspective that incorporates emergent levels of psychobiological complexity.

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