Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems
AimIn many cases, the dynamics of psychotherapeutic change processes is characterized by sudden and critical transitions. In theoretical terms, these transitions may be “phase transitions” of self-organizing nonlinear systems. Meanwhile, a variety of methods is available to identify phase transition...
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Frontiers Media S.A.
2020-08-01
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Online Access: | https://www.frontiersin.org/article/10.3389/fpsyg.2020.01970/full |
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Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Günter Schiepek Günter Schiepek Helmut Schöller Giulio de Felice Giulio de Felice Sune Vork Steffensen Sune Vork Steffensen Marie Skaalum Bloch Clemens Fartacek Wolfgang Aichhorn Kathrin Viol |
spellingShingle |
Günter Schiepek Günter Schiepek Helmut Schöller Giulio de Felice Giulio de Felice Sune Vork Steffensen Sune Vork Steffensen Marie Skaalum Bloch Clemens Fartacek Wolfgang Aichhorn Kathrin Viol Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems Frontiers in Psychology self-organization phase transitions pattern identification nonlinear methods change points real-time monitoring |
author_facet |
Günter Schiepek Günter Schiepek Helmut Schöller Giulio de Felice Giulio de Felice Sune Vork Steffensen Sune Vork Steffensen Marie Skaalum Bloch Clemens Fartacek Wolfgang Aichhorn Kathrin Viol |
author_sort |
Günter Schiepek |
title |
Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems |
title_short |
Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems |
title_full |
Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems |
title_fullStr |
Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems |
title_full_unstemmed |
Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems |
title_sort |
convergent validation of methods for the identification of psychotherapeutic phase transitions in time series of empirical and model systems |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2020-08-01 |
description |
AimIn many cases, the dynamics of psychotherapeutic change processes is characterized by sudden and critical transitions. In theoretical terms, these transitions may be “phase transitions” of self-organizing nonlinear systems. Meanwhile, a variety of methods is available to identify phase transitions even in short time series. However, it is still an open question if different methods for timeseries analysis reveal convergent results indicating the moments of critical transitions and related precursors.Methods and ProceduresSeven concepts which are commonly used in nonlinear time series analysis were investigated in terms of their ability to identify changes in psychological time series: Recurrence Plots, Change Point Analysis, Dynamic Complexity, Permutation Entropy, Time Frequency Distributions, Instantaneous Frequency, and Synchronization Pattern Analysis, i.e., the dynamic inter-correlation of the system’s variables. Phase transitions were simulated by shifting control parameters in the Hénon map dynamics, in a simulation model of psychotherapy processes (one by an external shift of the control parameter and one created by a simulated control parameter shift), and three sets of empirical time series generated by daily self-ratings of patients during the treatment.ResultsThe applied methods showed converging results indicating the moments of dynamic transitions within an acceptable tolerance. The convergence of change points was confirmed statistically by a comparison to random surrogates. In the three simulated dynamics with known phase transitions, these could be identified, and in the empirical cases, the methods converged indicating one and the same transition (possibly the phase transitions of the cases). Moreover, changes that did not manifest in a shift of mean or variance could be detected.ConclusionChanges can occur in many different ways in the psychotherapeutic process. For instance, there can be very slow and small transitions or very high and sudden ones. The results show the validity and stability of different measures indicating pattern transitions and/or early warning signals of those transitions. This has profound implications for real-time monitoring in psychotherapy, especially in cases where a transition is not obvious to the eye. Reliably identifying points of change is mandatory also for research on precursors, which in turn can help improving treatment. |
topic |
self-organization phase transitions pattern identification nonlinear methods change points real-time monitoring |
url |
https://www.frontiersin.org/article/10.3389/fpsyg.2020.01970/full |
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AT gunterschiepek convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT gunterschiepek convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT helmutscholler convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT giuliodefelice convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT giuliodefelice convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT sunevorksteffensen convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT sunevorksteffensen convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT marieskaalumbloch convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT clemensfartacek convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT wolfgangaichhorn convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems AT kathrinviol convergentvalidationofmethodsfortheidentificationofpsychotherapeuticphasetransitionsintimeseriesofempiricalandmodelsystems |
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doaj-e73f129f335945b3b4175cd98582afbd2020-11-25T03:41:46ZengFrontiers Media S.A.Frontiers in Psychology1664-10782020-08-011110.3389/fpsyg.2020.01970528684Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model SystemsGünter Schiepek0Günter Schiepek1Helmut Schöller2Giulio de Felice3Giulio de Felice4Sune Vork Steffensen5Sune Vork Steffensen6Marie Skaalum Bloch7Clemens Fartacek8Wolfgang Aichhorn9Kathrin Viol10Institute of Synergetics and Psychotherapy Research, University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, AustriaDepartment of Psychology, Ludwig Maximilian University of Munich, Munich, GermanyInstitute of Synergetics and Psychotherapy Research, University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, AustriaDepartment of Dynamic and Clinical Psychology, Sapienza University of Rome, Rome, ItalyFaculty of Psychology, NCIUL University, London, United KingdomCentre for Human Interactivity, Department of Language and Communication, University of Southern Denmark, Odense, DenmarkCenter for Ecolinguistics, South China Agricultural University, Guangzhou, ChinaOutpatient Clinic of Anxiety Disorders and Personality Disorders, Brønderslev Psychiatric Hospital, Brønderslev, DenmarkInstitute of Synergetics and Psychotherapy Research, University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, AustriaInstitute of Synergetics and Psychotherapy Research, University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, AustriaInstitute of Synergetics and Psychotherapy Research, University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, AustriaAimIn many cases, the dynamics of psychotherapeutic change processes is characterized by sudden and critical transitions. In theoretical terms, these transitions may be “phase transitions” of self-organizing nonlinear systems. Meanwhile, a variety of methods is available to identify phase transitions even in short time series. However, it is still an open question if different methods for timeseries analysis reveal convergent results indicating the moments of critical transitions and related precursors.Methods and ProceduresSeven concepts which are commonly used in nonlinear time series analysis were investigated in terms of their ability to identify changes in psychological time series: Recurrence Plots, Change Point Analysis, Dynamic Complexity, Permutation Entropy, Time Frequency Distributions, Instantaneous Frequency, and Synchronization Pattern Analysis, i.e., the dynamic inter-correlation of the system’s variables. Phase transitions were simulated by shifting control parameters in the Hénon map dynamics, in a simulation model of psychotherapy processes (one by an external shift of the control parameter and one created by a simulated control parameter shift), and three sets of empirical time series generated by daily self-ratings of patients during the treatment.ResultsThe applied methods showed converging results indicating the moments of dynamic transitions within an acceptable tolerance. The convergence of change points was confirmed statistically by a comparison to random surrogates. In the three simulated dynamics with known phase transitions, these could be identified, and in the empirical cases, the methods converged indicating one and the same transition (possibly the phase transitions of the cases). Moreover, changes that did not manifest in a shift of mean or variance could be detected.ConclusionChanges can occur in many different ways in the psychotherapeutic process. For instance, there can be very slow and small transitions or very high and sudden ones. The results show the validity and stability of different measures indicating pattern transitions and/or early warning signals of those transitions. This has profound implications for real-time monitoring in psychotherapy, especially in cases where a transition is not obvious to the eye. Reliably identifying points of change is mandatory also for research on precursors, which in turn can help improving treatment.https://www.frontiersin.org/article/10.3389/fpsyg.2020.01970/fullself-organizationphase transitionspattern identificationnonlinear methodschange pointsreal-time monitoring |