A dynamic systems approach to psychotherapy: A meta-theoretical framework for explaining psychotherapy change processes.

Abstract

Notwithstanding the many methodological advances made in the field of psychotherapy research, at present a metatheoretical, school-independent framework to explain psychotherapy change processes taking into account their dynamic and complex nature is still lacking. Over the last years, several authors have suggested that a dynamic systems (DS) approach might provide such a framework. In the present paper, we review the main characteristics of a DS approach to psychotherapy. After an overview of the general principles of the DS approach, we describe the extent to which psychotherapy can be considered as a self-organizing open complex system, whose developmental change processes are described in terms of a dialectic dynamics between stability and change over time. Empirical evidence in support of this conceptualization is provided and discussed. Finally, we propose a research design strategy for the empirical investigation of psychotherapy from a DS approach, together with a research case example. We conclude that a DS approach may provide a metatheoretical, school-independent framework allowing us to constructively rethink and enhance the way we conceptualize and empirically investigate psychotherapy. (PsycINFO Database Record

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

“…During the past few decades, the conceptualization of psychotherapy as a nonlinear, dynamic, and complex process has been outlined in many publications and by different research groups (Schiepek et al, 1992a, 2014a,b; Orsucci, 2006, 2015; Hayes et al, 2007; Guastello et al, 2009; Pincus, 2009, 2015, 2016; Haken and Schiepek, 2010; Salvatore and Tschacher, 2012; Gelo and Salvatore, 2016). The interest in this approach is increasing, since it is capable of explaining important features of human change processes, including: discontinuous progress (sudden gains or sudden losses, Lutz et al, 2013; Stiles et al, 2003), missing proportionality and nonlinear relations between interventions and outcome (Muran et al, 1995; Hayes et al, 2007; Haken and Schiepek, 2010), unpredictability of long-term courses (Strunk et al, 2015), the dependency of human functioning on specific contexts and situative requirements (Kashdan and Rottenberg, 2010), the eigendynamics and individuality of evolutionary patterns (Barkham et al, 1993; Tschacher et al, 2000; Molenaar, 2004; Fisher, 2015; Fisher and Boswell, 2016), and the important role of client's contributions (e.g., motivation, ressources) to psychotherapeutic gains (Orlinsky et al, 2004; Bohart and Tallman, 2010).…”

“…Some authors discuss the nonlinear dynamics approach as a new paradigm or a meta-theoretical framework in psychology (Lichtwarck-Aschoff et al, 2008; Haken and Schiepek, 2010; Orsucci, 2015; Gelo and Salvatore, 2016). We are currently seeing an era where the life sciences, including psychology, become ever more sophisticated and computational in their modeling practices—with high-throughput technologies providing access to different layers of data, from biological to organizational scales, and with simulations becoming an integral part of the discovery process.…”

Intersession improvement and outcome in psychotherapy

“…Returning to the psychotherapy literature, Vittengl, Clark, Thase, and Jarrett () found that among 362 individuals treated with cognitive therapy for recurrent depression, fully half had symptom trajectories that were not easily modelled with polynomial functions and/or demonstrated large shifts over one or more treatment sessions. Gelo and Salvatore () have suggested that although symptomatic distress changes gradually during much of psychotherapy, periods of dynamic instability may occur that are followed by a new level of more stable functioning. Such dynamic instability might occur over several sessions, or it might occur within a single session, as Pascual‐Leone () has shown.…”

Under the Hood: Using Computational Psychiatry to Make Psychological Therapies More Mechanism-Focused

“…This is analogous to the use of biomarkers in clinical trials being used as secondary outcomesfor example, changes in amyloid-beta measures in clinical trials for Alzheimer dementia may suggest possible treatment efficacy even if no change is seen in cognitive scores (18). It has previously been proposed that outcomes in psychological therapy could be formally modeled, using dynamic systems theory, for example (19,20). As compared to these proposals, computational modeling parameters from reinforcement learning models would serves to model the underlying computational process driving change rather than the complex dynamics of psychotherapy.…”