Process-Based psychotherapy personalization: considering causality with continuous-time dynamic modeling

Psychother Res. 2023 Nov;33(8):1076-1095. doi: 10.1080/10503307.2023.2222892. Epub 2023 Jun 12.

Abstract

Psychotherapy can be improved by integrating the study of mediators (how it works) and moderators (for whom it works). To demonstrate this integration, we studied the relationship between resource activation, problem-coping experiences and symptoms in cognitive-behavior therapy (CBT) for depression, to obtain preliminary insights on causal inference (which process leads to symptom improvement?) and prediction (which one for whom?).

A sample of 715 patients with depression who received CBT was analyzed. Hierarchical Bayesian continuous time dynamic modeling was used to study the temporal dynamics between the variables analyzed within the first ten sessions. Depression and self-efficacy at baseline were examined as predictors of these dynamics.

There were significant cross-effects between the processes studied. Under typical assumptions, resource activation had a significant effect on symptom improvement. Problem-coping experience had a significant effect on resource activation. Depression and self-efficacy moderated these effects. However, when system noise was considered, these effects may be affected by other processes.

Resource activation was strongly associated with symptom improvement. To the extent of inferring causality, for patients with mild-moderate depression and high self-efficacy, promoting resource activation can be recommended. For patients with severe depression and low self-efficacy, promoting problem-coping experiences can be recommended.

Keywords: complex dynamic systems; prediction; problem coping; process-outcome research; resource activation.

MeSH terms

  • Bayes Theorem
  • Cognitive Behavioral Therapy*
  • Depression / therapy
  • Depressive Disorder*
  • Humans
  • Psychotherapy
  • Self Efficacy
  • Treatment Outcome