Process-symptom-bridges in psychotherapy: An idiographic network approach


  • Tim Kaiser University of Salzburg
  • Anton-Rupert Laireiter University of Salzburg



depression, anxiety, intersession processes, ecological momentary assessment, network analysis


Real-time monitoring of psychotherapeutic processes was recently described as a promising, new way of tracking periods of change in ongoing treatments. This approach generates complex, multivariate datasets that have to be presented in an intuitive way for clinicians to aid their clinical decision-making. Using network modeling and new approaches in centrality analyses, we examine “bridge nodes” between symptom stress and aspects of the psychotherapeutic process between therapy session (intersession processes, ISP).
Method: We recorded intersession processes as well as depressive and anxiety symptoms using daily questionnaires in ten cases. Regularized, thresholded intraindividual dynamic networks were estimated. We applied bridge centrality analysis to identify individual bridges between psychotherapeutic processes and symptoms in the resulting models. Casewise interpretations of bridge centrality values are offered.
Results: Bridge centrality analysis revealed individual bridge nodes between intersession processes and symptom severity. Strength and direction of bridges varied substantially across individuals.
Conclusion: Given current methodological challenges, idiographic network studies are feasible and offer important insights for psychotherapy process research. In this case, we demonstrated how patients deal with periods of increased symptom stress. In this case we have described how patients deal with their therapy under increased symptom load. Bridges between psychotherapeutic processes and symptom stress are a promising target for monitoring systems based on ISP. Future studies should examine the clinical utility of network-based monitoring and feedback in ongoing therapies. In the near future, process feedback systems based on idiographic models could serve clinicians to improve treatments.