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

心理治疗中的过程-症状-桥梁:一种个体化网络方法

阅读:1

Abstract

AIM: 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. Case-wise 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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。