Understanding the role of emotion and expertise in psychotherapy: An application of dynamical systems mathematical modeling to an entire course of therapy.

Introduction: The therapeutic relationship continues to be one of the most important factors in therapeutic outcomes. Given the place of emotion in the definition of the therapeutic relationship, as well as the demonstrated positive impact that emotional expression has on therapeutic process and outcome, it stands to reason that studying the emotional exchange between the therapist and client further would be warranted. Methods: This study used a validated observational coding system--the Specific Affect Coding System (SPAFF) and a theoretical mathematical model to analyze behaviors which make up the therapeutic relationship. Specifically, the researchers used to codify relationship-building behaviors between an expert therapist and his client over the course of six sessions. Dynamical systems mathematical modeling was also employed to create "phase space portraits" depicting the relational dynamics between the master therapist and his client over six sessions. Results: Statistical analysis was used to compare SPAFF codes and model parameters between the expert therapist and his client. The expert therapist showed stability in affect codes over six sessions while the client's affect codes appeared to be more flexible over time, though model parameters remained stable across the six sessions. Finally, phase space portraits depicted the evolution of the affective dynamics between the master therapist and his client as the relationship matured. Discussion: The clinician's ability to stay emotionally positive and relatively stable across the six sessions (relative to the client) was noteworthy. It formed the basis for a stable base from which she could explore alternative methods to relate to others that she had allowed to dictate her actions, which is in keeping with previous research on the role of therapist facilitation of the therapeutic relationship, emotional expression within the therapeutic relationship, and influence of these on client outcomes. These results provide a valuable foundation for future research on emotional expression as a key component of the therapeutic relationship in psychotherapy.

Paradoxical interventions: A meta-analysis.

This article outlines the evidence base for the use of paradoxical interventions (PIs) in individual psychotherapy. Often misunderstood, PIs have shown long-term (distal) impacts on clinical outcomes, yet a review of the existing literature on these interventions illustrates a trending decline in consideration and use within both research and applied settings. Definitions of PIs and their constituent elements are presented along with clinical examples. We conducted one meta-analysis comparing PIs with a placebo or control and another comparing PIs to other therapeutic methods. PIs demonstrated a large effect (d = 1.1, k = 17 studies) compared to controls and a medium effect size (d = .49, k = 17 studies) compared to other therapeutic methods. We included a review of several case studies using PIs as well. Among the salient findings, there is a lack of assessment measure to track the implementation of PIs in session or a method to track their in-session effects. Further, there is a dearth of contemporary quantitative experimental research and development of PIs. We further advocate for the development and integration of PI training and supervision into clinical education and posteducation programs, given the current data demonstrating clinical utility. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Using dynamical systems mathematical modeling to examine the impact emotional expression on the therapeutic relationship: A demonstration across three psychotherapeutic theoretical approaches.

Objective: The purpose of this paper is to describe an approach to dynamical systems (DS) using a set of differential equations, and how an application of these equations can be used to address a critical element of the therapeutic relationship. Using APA's Three Approaches to Psychotherapy with a Female Client: The Next Generation and Three Approaches to Psychotherapy with a Male Client: The Next Generation videos, DS models were created for each of the six sessions with expert clinicians (Judith Beck, Leslie Greenberg, and Nancy McWilliams) from the three theoretical approaches. Method: A second-by-second observational coding system of the emotional exchanges of the therapists and clients was used as the data for the equations. Results: DS modeling allowed for a side-by-side comparison between the three approaches as well as between the two clients. Examining the graphs created by plotting the results of the DS equations (in particular, phase-space portraits) revealed that there were similarities among the three theoretical approaches, and there were notable differences between the two clients. Conclusions: DS modelling can provide researchers and clinicians with a powerful tool to investigate the complex phenomenon that is psychotherapy.

Therapist and client emotional expression and psychotherapy outcomes: A meta-analysis.

Although emotion has long been considered important to psychotherapeutic process, empirical assessment of its impact has emerged only recently. The present study applied two meta-analyses to explore the association between therapist expression of emotion and psychotherapy outcome, and client expression of emotion and psychotherapy outcome. Overall, 66 studies (13 for the therapist meta-analysis and 43 for the client meta-analysis) were included. A significant medium effect size was found between the therapist's emotional expression and outcomes (d = 0.56) and a significant medium-to-large effect size between the client's emotional expression and outcomes (d = 0.85). Third-party rating of emotional expression emerged as a significant moderator of outcomes. Limitations of the research, diversity considerations, and therapeutic practices that conclude the article are then presented. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A mathematical model of psychotherapy: an investigation using dynamic non-linear equations to model the therapeutic relationship.

Mathematical models, such as the one developed by Gottman et al. (1998, 2000, 2002) to understand the interaction between husbands and wives, can provide novel insights into the dynamics of the therapeutic relationship. A set of nonlinear equations were used to model the changing emotional state of a therapist and client. The results suggest: (1) The person that is most responsive to the other achieves the most positive state, (2) the emotional state of the client oscillates before reaching its final state, (3) therapy is least successful when the therapist starts from a negative state, and (4) there is an inverse relationship between models that change only the influence parameter and models that change only the inertia parameter, creating a series of four basic models to work with. These theoretical models require further, empirical investigation to test the derived parameters. If validated, or revised based on observations of therapist-client relationships in development, they could provide specific direction in creating successful therapeutic relationships for training clinicians and those already in practice.

Mathematical model of the dynamics of psychotherapy.

The success of psychotherapy depends on the nature of the therapeutic relationship between a therapist and a client. We use dynamical systems theory to model the dynamics of the emotional interaction between a therapist and client. We determine how the therapeutic endpoint and the dynamics of getting there depend on the parameters of the model. Previously Gottman et al. used a very similar approach (physical-sciences paradigm) for modeling and making predictions about husband-wife relationships. Given that this novel approach shed light on the dyadic interaction between couples, we have applied it to the study of the relationship between therapist and client. The results of our computations provide a new perspective on the therapeutic relationship and a number of useful insights. Our goal is to create a model that is capable of making solid predictions about the dynamics of psychotherapy with the ultimate intention of using it to better train therapists.