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Psychotherapy Is Chaotic—(Not Only) in a Computational World

Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some comm...

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Autores principales: Schiepek, Günter K., Viol, Kathrin, Aichhorn, Wolfgang, Hütt, Marc-Thorsten, Sungler, Katharina, Pincus, David, Schöller, Helmut J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5402620/
https://www.ncbi.nlm.nih.gov/pubmed/28484401
http://dx.doi.org/10.3389/fpsyg.2017.00379
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author Schiepek, Günter K.
Viol, Kathrin
Aichhorn, Wolfgang
Hütt, Marc-Thorsten
Sungler, Katharina
Pincus, David
Schöller, Helmut J.
author_facet Schiepek, Günter K.
Viol, Kathrin
Aichhorn, Wolfgang
Hütt, Marc-Thorsten
Sungler, Katharina
Pincus, David
Schöller, Helmut J.
author_sort Schiepek, Günter K.
collection PubMed
description Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some common factors of psychotherapeutic change and psychological hypotheses on motivation, emotion regulation, and information processing of the client's functioning can be integrated into a comprehensive nonlinear model of human change processes. Methods: The model combines 5 variables (intensity of emotions, problem intensity, motivation to change, insight and new perspectives, therapeutic success) and 4 parameters into a set of 5 coupled nonlinear difference equations. The results of these simulations are presented as time series, as phase space embedding of these time series (i.e., attractors), and as bifurcation diagrams. Results: The model creates chaotic dynamics, phase transition-like phenomena, bi- or multi-stability, and sensibility of the dynamic patterns on parameter drift. These features are predicted by chaos theory and by Synergetics and correspond to empirical findings. The spectrum of these behaviors illustrates the complexity of psychotherapeutic processes. Conclusion: The model contributes to the development of an integrative conceptualization of psychotherapy. It is consistent with the state of scientific knowledge of common factors, as well as other psychological topics, such as: motivation, emotion regulation, and cognitive processing. The role of chaos theory is underpinned, not only in the world of computer simulations, but also in practice. In practice, chaos demands technologies capable of real-time monitoring and reporting on the nonlinear features of the ongoing process (e.g., its stability or instability). Based on this monitoring, a client-centered, continuous, and cooperative process of feedback and control becomes possible. By contrast, restricted predictability and spontaneous changes challenge the usefulness of prescriptive treatment manuals or other predefined programs of psychotherapy.
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spelling pubmed-54026202017-05-08 Psychotherapy Is Chaotic—(Not Only) in a Computational World Schiepek, Günter K. Viol, Kathrin Aichhorn, Wolfgang Hütt, Marc-Thorsten Sungler, Katharina Pincus, David Schöller, Helmut J. Front Psychol Psychology Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some common factors of psychotherapeutic change and psychological hypotheses on motivation, emotion regulation, and information processing of the client's functioning can be integrated into a comprehensive nonlinear model of human change processes. Methods: The model combines 5 variables (intensity of emotions, problem intensity, motivation to change, insight and new perspectives, therapeutic success) and 4 parameters into a set of 5 coupled nonlinear difference equations. The results of these simulations are presented as time series, as phase space embedding of these time series (i.e., attractors), and as bifurcation diagrams. Results: The model creates chaotic dynamics, phase transition-like phenomena, bi- or multi-stability, and sensibility of the dynamic patterns on parameter drift. These features are predicted by chaos theory and by Synergetics and correspond to empirical findings. The spectrum of these behaviors illustrates the complexity of psychotherapeutic processes. Conclusion: The model contributes to the development of an integrative conceptualization of psychotherapy. It is consistent with the state of scientific knowledge of common factors, as well as other psychological topics, such as: motivation, emotion regulation, and cognitive processing. The role of chaos theory is underpinned, not only in the world of computer simulations, but also in practice. In practice, chaos demands technologies capable of real-time monitoring and reporting on the nonlinear features of the ongoing process (e.g., its stability or instability). Based on this monitoring, a client-centered, continuous, and cooperative process of feedback and control becomes possible. By contrast, restricted predictability and spontaneous changes challenge the usefulness of prescriptive treatment manuals or other predefined programs of psychotherapy. Frontiers Media S.A. 2017-04-24 /pmc/articles/PMC5402620/ /pubmed/28484401 http://dx.doi.org/10.3389/fpsyg.2017.00379 Text en Copyright © 2017 Schiepek, Viol, Aichhorn, Hütt, Sungler, Pincus and Schöller. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Schiepek, Günter K.
Viol, Kathrin
Aichhorn, Wolfgang
Hütt, Marc-Thorsten
Sungler, Katharina
Pincus, David
Schöller, Helmut J.
Psychotherapy Is Chaotic—(Not Only) in a Computational World
title Psychotherapy Is Chaotic—(Not Only) in a Computational World
title_full Psychotherapy Is Chaotic—(Not Only) in a Computational World
title_fullStr Psychotherapy Is Chaotic—(Not Only) in a Computational World
title_full_unstemmed Psychotherapy Is Chaotic—(Not Only) in a Computational World
title_short Psychotherapy Is Chaotic—(Not Only) in a Computational World
title_sort psychotherapy is chaotic—(not only) in a computational world
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5402620/
https://www.ncbi.nlm.nih.gov/pubmed/28484401
http://dx.doi.org/10.3389/fpsyg.2017.00379
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