Life, complexity, and psychotherapy: A systemic perspective on the elusive construct of extra-therapeutic factors

STUDY AIMS

Despite being mentioned in well-known models of psychotherapeutic change, the concept of extra-therapeutic factors seems to have left the scene across time, eaten away by the progressive refinement of the construct of common factors. Aim of the present study is to better understanding the historical evolution of the concept of extra-therapeutic factors and its importance for psychotherapy today.

METHODS

This is a position paper based on a literature review on extra-therapeutic factors and psychotherapy outcome and process.

DISCUSSION

There is growing evidence of the decisive role of clients' and therapists' characteristics, as well as of the importance of therapeutic alliances and relationships in promoting change. Within this context, the concept of extra-therapeutic factors still deserves proper attention, rather than being relegated to a residual and vanishing category.

CONCLUSION

A renewed interest on extra-therapeutic factors could reinvigorate the debate over the relationship between psychotherapy and life contexts and conditions. In terms of complexity and systems thinking nothing, a priori, really falls outside the realm of psychotherapy and, in turn, psychotherapy is not a practice that could be abstracted from the context in which it is practiced or from clients' and therapists' lives.

Nature heals: An informational entropy account of self-organization and change in field psychotherapy

This paper reviews biophysical models of psychotherapeutic change based on synergetics and the free energy principle. These models suggest that introducing sensory surprise into the patient-therapist system can lead to self-organization and the formation of new attractor states, disrupting entrenched patterns of thoughts, emotions, and behaviours. We propose that the therapist can facilitate this process by cultivating epistemic trust and modulating embodied attention to allow surprising affective states to enter shared awareness. Transient increases in free energy enable the update of generative models, expanding the range of experiences available within the patient-therapist phenomenal field. We hypothesize that patterns of disorganization at behavioural and physiological levels, indexed by increased entropy, complexity, and lower determinism, are key markers and predictors of psychotherapeutic gains. Future research should investigate how the therapist's openness to novelty shapes therapeutic outcomes.

A consulting room with a view: Psychotherapy and the ecological context

BACKGROUND

The field of psychotherapy is witnessing a lively debate today. The literature on the efficacy of psychological interventions has grown exponentially, but the assumptions of the prevailing research paradigms have been criticised from many points of view. One of the main concerns is that of a too often simplistic conception of psychotherapy, viewed as a set of specific methods for the treatment of point-like problems or symptoms.

LITERATURE REVIEW ON MENTAL HEALTH AND THE ECOLOGICAL CONTEXT

Instead, emerging perspectives are trying to promote a more complex view on psychotherapy, as a process based on the therapeutic potential of relationships, which takes place in relevant social and cultural contexts. Even the ecological context is taken in greater consideration, as growing evidence exists about the detrimental effects of ecological threats-such as climate change and other environmental challenges-on mental health.

CONCLUSIONS

Psychotherapists and psychotherapy associations are now paying due attention to such issues, as well as to social justice and other dimensions that no longer can be thought of as mere elements of the scenario in which psychotherapy is practiced. Rather they are dimensions that exert a strong influence on psychological well-being, and thus must be properly acknowledged and assessed to connect clinical work with the communities and ecological contexts in which people live.

Initial validation of the Turkish version of the defense mechanisms rating scales-self-report-30

The Defense Mechanisms Rating Scales-Self Report-30 (DMRS-SR-30) was recently developed to add a self-report alternative to the assessment of defenses, reflecting their generally accepted hierarchical organization. In this study, we aimed to examine psychometric properties and factor structure of the Turkish language version of the DMRS-SR-30. The sample consisted of 1.002 participants who filled out a survey comprising the DMRS-SR-30, the Brief Symptom Inventory, and the Inventory of Personality Organization through Qualtrics. Confirmatory Factor Analysis indicated a three-factor structure (CFI = 0.89, RMSEA = 0.05) that confirms the DMRS theoretical frame with a relatively acceptable fit. Defensive categories and total scale scores showed good to excellent reliability (α values ranging from 0.64 to 0.89). Correlations between defenses, symptoms, and personality functioning demonstrated good convergent and discriminant validity. The individuals with clinically significant BSI scores (T-score ≥ 63) differed on the DMRS-SR-30 scores from the individuals in the non-clinical range. The Turkish version of the DMRS-SR-30 is a reliable and valid instrument to self-assess the hierarchy of defense mechanisms and overall defensive functioning. Moreover, the current study supports the validity of the tripartite model of defenses in a language and culture different from the origins of the DMRS and DMRS-SR-30.

Features of Self-Organization during the Process of Mindfulness-Based Stress Reduction: A Single Case Study

Compared to the extensive evidence of the effectiveness of mindfulness-based interventions, there is only a limited understanding of their mechanisms of change. The three aims of this study are (1) to identify features of self-organization during the process (e.g., pattern transitions), (2) to obtain an impression of the effects of continuous self-assessments and feedback sessions on mindfulness-related stress reduction, and (3) to test the feasibility of high-frequency process monitoring and process feedback. Concerning aim (1), the specific hypothesis is that change will occur as a cascade of discontinuous pattern transitions emerging spontaneously in the sense of not being a reaction to external input. This single case study describes changing patterns of multiple time series that were produced by app-based daily self-assessments during and after an 8-week mindfulness-based stress reduction program. After this MBSR program, the participant (a female nurse) continued the self-assessment and the mindfulness practice for a further 10 months. The results confirm findings on the positive effects of mindfulness programs for healthcare professionals, especially on coping with work-related stress. The analysis of the time series data supports the hypothesis of self-organization as a possible mechanism of change manifesting as a cascade of phase transitions in the dynamics of a biopsychosocial system. At the end of the year, the participant reported a beneficial impact of daily monitoring and systematic feedback on the change process. The results underline the feasibility and usefulness of continuous high-frequency monitoring during and after mindfulness interventions.

Stability and flexibility in psychotherapy process predict outcome

Ten good outcome and ten poor outcome psychotherapy cases were compared to investigate whether or not the temporal stability and flexibility of their process variables can predict their outcomes. Each participant was monitored daily using the Therapy Process Questionnaire (TPQ), which has 43 items and seven sub-scales, and responses over time were analyzed in terms of correlation robustness and correlation variability across the TPQ sub-scales. "Correlation robustness" and "correlation variability" are two basic characteristics of any correlation matrix: the first is calculated as the sum of the absolute values of Pearson correlation coefficients, the second as the standard deviation of Pearson correlation coefficients. The results demonstrated that the patients within the poor outcome group had lower values on both variables, suggesting lower stability and flexibility. Furthermore, a higher number of cycles of increase and decrease in correlation robustness and variability of the TPQ sub-scales was observed within good outcome psychotherapies, suggesting that, these cycles can be considered as process-markers of good-outcomes. These results provide support for the validity of these quantitative process-parameters, correlation robustness and variability, in predicting psychotherapeutic outcomes. Moreover, the results lend support to the common clinical experience of alternating periods of flexibility and integration being beneficial to good psychotherapeutic processes.

Detecting pattern transitions in psychological time series - A validation study on the Pattern Transition Detection Algorithm (PTDA)

With the increasing use of real-time monitoring procedures in clinical practice, psychological time series become available to researchers and practitioners. An important interest concerns the identification of pattern transitions which are characteristic features of psychotherapeutic change. Change Point Analysis (CPA) is an established method to identify the point where the mean and/or variance of a time series change, but changes of other and more complex features cannot be detected by this method. In this study, an extension of the CPA, the Pattern Transition Detection Algorithm (PTDA), is optimized and validated for psychological time series with complex pattern transitions. The algorithm uses the convergent information of the CPA and other methods like Recurrence Plots, Time Frequency Distributions, and Dynamic Complexity. These second level approaches capture different aspects of the primary time series. The data set for testing the PTDA (300 time series) is created by an instantaneous control parameter shift of a simulation model of psychotherapeutic change during the simulation runs. By comparing the dispersion of random change points with the real change points, the PTDA determines if the transition point is significant. The PTDA reduces the rate of false negative and false positive results of the CPA below 5% and generalizes its application to different types of pattern transitions. RQA quantifiers also can be used for the identification of nonstationary transitions in time series which was illustrated by using Determinism and Entropy. The PTDA can be easily used with Matlab and is freely available at Matlab File Exchange (https://www.mathworks.com/matlabcentral/fileexchange/80380-pattern-transition-detection-algorithm-ptda).

Mechanisms of Change in Trauma-Focused Treatment for PTSD: The Role of Rumination

OBJECTIVE

Cognitive behavioral therapy (CBT) has been well established in the treatment of posttraumatic stress disorder (PTSD). In recent years, researchers have begun to investigate its underlying mechanisms of change. Dysfunctional cognitive content, i.e. excessively negative appraisals of the trauma or its consequences, has been shown to predict changes in PTSD symptoms over the course of treatment. However, the role of change in cognitive processes, such as trauma-related rumination, needs to be addressed. The present study investigates whether changes in rumination intensity precede and predict changes in symptom severity. We also explored the extent to which symptom severity predicts rumination.

METHOD

As part of a naturalistic effectiveness study evaluating CBT for PTSD in routine clinical care, eighty-eight patients with PTSD completed weekly measures of rumination and symptom severity. Lagged associations between rumination and symptoms in the following week were examined using linear mixed models.

RESULTS

Over the course of therapy, both ruminative thinking and PTSD symptoms decreased. Rumination was a significant predictor of PTSD symptoms in the following week, although this effect was at least partly explained by the time factor (e.g., natural recovery or inseparable treatment effects). Symptom severity predicted ruminative thinking in the following week even with time as an additional predictor.

CONCLUSIONS

The present study provides preliminary evidence that rumination in PTSD is reduced by CBT for PTSD but does not give conclusive evidence that rumination is a mechanism of change in trauma-focused treatment for PTSD.

Integration of Cognitive and Emotional Processing Predicts Poor and Good Outcomes of Psychotherapy

Abstract

With the aim of investigating analogies and differences between psychotherapeutic processes, ten good-outcome and ten poor-outcome cases were selected from a sample of patients treated at the University Hospital of Psychiatry, Salzburg, Austria, and the Department of Psycho-Traumatology of the Clinic St. Irmingard, Prien am Chiemsee, Germany. They were monitored daily using the Therapy Process Questionnaire (TPQ), and their evolution over time was analyzed by means of Principal Components Analysis and Linear Discriminant Analysis. The results highlight that poor-outcome patients show a separation between cognitive processes (Principal Component 1) and relational-emotional processes (Principal Component 2) (r = − 0.25; p = n.s.), while in the good-outcome patients these aspects are well integrated (r = 0.70; p = 0.02). These results corroborate the validity of the daily monitoring procedure and also indicate the need for greater attention to the relational and emotional aspects of the patients rather than merely to their cognitive functioning and well-being.

Key Message

In poor-outcome cases, burdensome emotions and interpersonal experiences on the one hand and cognitive/well-being aspects of the mental processing on the other, stay unrelated. Successful therapeutic processing, as in good-outcome cases, requires an integration of cognitive and affective components.

Complexity in psychological self-ratings: implications for research and practice

BACKGROUND

Psychopathology research is changing focus from group-based "disease models" to a personalized approach inspired by complex systems theories. This approach, which has already produced novel and valuable insights into the complex nature of psychopathology, often relies on repeated self-ratings of individual patients. So far, it has been unknown whether such self-ratings, the presumed observables of the individual patient as a complex system, actually display complex dynamics. We examine this basic assumption of a complex systems approach to psychopathology by testing repeated self-ratings for three markers of complexity: memory, the presence of (time-varying) short- and long-range temporal correlations; regime shifts, transitions between different dynamic regimes; and sensitive dependence on initial conditions, also known as the "butterfly effect," the divergence of initially similar trajectories.

METHODS

We analyzed repeated self-ratings (1476 time points) from a single patient for the three markers of complexity using Bartels rank test, (partial) autocorrelation functions, time-varying autoregression, a non-stationarity test, change point analysis, and the Sugihara-May algorithm.

RESULTS

Self-ratings concerning psychological states (e.g., the item "I feel down") exhibited all complexity markers: time-varying short- and long-term memory, multiple regime shifts, and sensitive dependence on initial conditions. Unexpectedly, self-ratings concerning physical sensations (e.g., the item "I am hungry") exhibited less complex dynamics and their behavior was more similar to random variables.

CONCLUSIONS

Psychological self-ratings display complex dynamics. The presence of complexity in repeated self-ratings means that we have to acknowledge that (1) repeated self-ratings yield a complex pattern of data and not a set of (nearly) independent data points, (2) humans are "moving targets" whose self-ratings display non-stationary change processes including regime shifts, and (3) long-term prediction of individual trajectories may be fundamentally impossible. These findings point to a limitation of popular statistical time series models whose assumptions are violated by the presence of these complexity markers. We conclude that a complex systems approach to mental health should appreciate complexity as a fundamental aspect of psychopathology research by adopting the models and methods of complexity science. Promising first steps in this direction, such as research on real-time process monitoring, short-term prediction, and just-in-time interventions, are discussed.

Convergent Validation of Methods for the Identification of Psychotherapeutic Phase Transitions in Time Series of Empirical and Model Systems

Aim

In 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 Procedures

Seven 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.

Results

The 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.

Conclusion

Changes 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.