Speaker: Timur Guralnik.

Title: Theoretical and empirical applications of Dynamical Systems Theory in psychotherapy.

Abstract: 

Empirical research on psychotherapy generally supports the efficacy of most evidence-based treatment protocols. However, this field increasingly produces conclusions that can be generally described as such: “psychotherapy of a certain type works better for a certain type of disorder, under condition X but not condition Y, but also actually sometimes for condition Y under the condition of Z…” and so forth without end. We argue that this stems from a portrayal of therapy as a deterministic and linear process, both in theory and in statistical modeling practices. Such a portrayal enerally assumes that if enough information is entered into a statistical model, more certainty about the success of psychotherapy can be attained, and ‘unexplained variance’ can be eventually gotten rid of. 

Dynamical Systems Theory (DST) puts forward the idea that such determinism is unlikely to exist in biological systems, and shifts focus to the complex ebb and flow of states in time. In this talk, we will discuss the theoretical and practical applications of DST for psychotherapy research,and present a project where attractor reconstruction techniques were used to estimate Lyapunov Exponents in psychotherapy data. These estimates were then used as predictors of patient symptom change over the course of therapy.