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A new integrative approach to psychotherapy and counseling, based on nonlinear dynamic systems
Existing schools of psychotherapy and counseling all have limitations and shortcomings and there is increasing empirical evidence that it is the factors they have in common which contribute most to their efficacy. This volume describes an innovative integrative, systemic approach to psychotherapy and counseling based around theories of nonlinear dynamic systems ( fuzzy logic ).
Table des matières
Table of Contents (preliminary): Integrative Psychotherapy A Feedback-Driven Dynamic Systems Approach Gunter Schiepek, Heiko Eckert, Benjamin Aas, Sebastian Wallot & Anna Wallot Foreword 1 Why Is It so Challenging to Define Systemic Psychotherapy? 2 The End of Therapeutic Schools 2.1 What Do Interventions and Therapeutic Techniques Really Contribute? 2.2 Laymen in Psychotherapy 2.3 The Dodo Bird Effect 2.4 Allegiance With One's Own Approach 2.5 Sudden Changes 2.6 The Heroic Client 2.7 Should We Follow Manuals? 2.8 The Therapist 2.9 The Therapeutic Relationship 2.10 Psychotherapy as a Complex System 3 Psychotherapy as Providing Conditions for Self-Organization 3.1 What Is Synergetics? 3.2 How Does Self-Organization Work? 3.3 Neuronal and Mental Self-Organization 4 Conditions for Support of Self-Organization: The Generic Principles 4.1 Stability Conditions 4.2 Identification of Relevant System Patterns 4.3 Sense of Significance 4.4 Control Parameters and Motivation for Change 4.5 Destabilization and Amplification of Fluctuations 4.6 Cairos, Resonance, and Synchronization 4.7 Purposeful Symmetry Breaking 4.8 Stabilization of New Patterns 5 Synergetic Process Management 6 The Synergetic Navigation System (SNS) 6.1 Ambulatory Assessment and Real-Time Monitoring in Psychotherapy 6.2 Functionalities of the SNS 7 Case Study 7.1 Problems and Resources 7.2 Therapeutic Progress With Order Transition 7.3 System Modeling 8 Entanglement of Monitoring and Therapy 8.1 Therapeutic Effects of Feedback Systems 8.2 SNS-Based Therapy Sessions 8.3 Reactive Measures 9 Conceptual Developments 9.1 Dynamic Pattern Recognition and Process Regulation as Components of Therapeutic Practice 9.2 Evidence-Based Practice and Relative Rational Justification of Treatments 9.3 The Relation Between Common Factors and Generic Principles 9.4 The Model of Self-Organization as a Synthesis of the Medical Model and the Common Factors Model 10 What Are Integrative SystemicTherapies? 10.1 SystemicNeurotherapies 10.1.1 Real-Time Neuro-Feedback With fMRI 10.1.2 Neuromodulation 10.2 Psychotherapy Integration
A propos de l'auteur
Günter Schiepek ist Professor für Psychologie an den Universitäten Krems und Bamberg und Leiter des Forschungsprojekts 'Synergetik der Psychotherapie' am Universitätsklinikum der RWTH Aachen sowie Direktor des Center for Complex Systems (Stuttgart). Seine Arbeitsschwerpunkte sind die Synergetik und Dynamik nichtlinearer Systeme in der Psychologie und in den Neurowissenschaften, Prozess-Outcome-Forschung in der Psychotherapie, Neurobiologie der Psychotherapie, Computerbasiertes Real-Time Monitoring in verschiedenen Anwendungsfeldern, Sozialpsychologie, Management und Kompetenzforschung. Schiepek ist Wissenschaftlicher Beirat zahlreicher Institute, Verbände und Fachzeitschriften und hat zahlreiche internationale und deutschsprachige Publikationen veröffentlicht.
Résumé
Integrative psychotherapy: using the principles of dynamic complex systems to guide everyday clinical work
This book introduces a new, integrative, systemic approach to psychotherapy and counseling and shows how the principles of dynamic complex systems can guide everyday clinical work.
Our mental, interpersonal, and biological (e.g., neuronal) systems are complex and nonlinear, and allow spontaneous pattern formation and chaotic dynamics. Their self-organizing nature sometimes maneuvers the systems into pathological states. However, the very same principles can be utilized therapeutically to encourage change for the better. The feedback-driven nonlinear dynamic systems approach described here basically attempts to facilitate positive self-organizing processes, such as order transitions, healthy patterns of behavior, and learning processes.
In addition to describing the theory and evidence supporting the feedback-driven nonlinear dynamic systems approach, the authors use an extensive case study to illustrate how the principles of dynamic complex systems can guide everyday clinical work. They show how modeling and monitoring of the client‘s systems and an empirical description of its patterns allows the therapist to individually fine-tune therapeutic techniques to support the client’s progress. Fine-meshed feedback based on real-time data and time-series analysis is at the core of the approach, and so an internet-based monitoring system – the Synergetic Navigation System (SNS) – that helps capture dynamic processes and guide practitioners’ therapeutic decisions is also described
