Suppr超能文献

使用网络分析来表征认知加工疗法期间的临床改善情况。

Using network analysis to characterize clinical improvement during cognitive processing therapy.

作者信息

Schlesselmann Ante J, McNally Richard J, Held Philip

机构信息

Department of Clinical Psychology and Experimental Psychopathology, University of Groningen, Groningen, the Netherlands.

Department of Psychology, Harvard University, Cambridge, MA, USA.

出版信息

Behav Res Ther. 2025 Feb;185:104678. doi: 10.1016/j.brat.2024.104678. Epub 2024 Dec 24.

Abstract

OBJECTIVE

Cross-sectional network studies find mixed results regarding changes in network structure as a response to treatment across disorders. This study characterized improvement in mental health following Cognitive Processing Therapy (CPT) for PTSD in veterans from the perspective of network psychometrics and explored how cross-sectional networks inform our understanding of PTSD recovery.

METHODS

Veterans with PTSD participated in CPT-based intensive treatment programs (ITPs), offered in two-week (N = 635) or three-week (N = 457) formats. PTSD symptoms were self-reported on the PTSD Checklist for DSM-5 (PCL-5) at pre-, mid-, and post-treatment. Cross-sectional networks for each time point were compared using network comparison tests. Linear regression tested if the relationship of initial treatment gains from admission to mid-treatment with overall outcomes was associated with the expected influence centrality of a node.

RESULTS

Substantial improvement in PTSD symptoms were found, but network structure remained largely unaffected, with global edge strength increasing from pre-to post-treatment. Initial treatment gains in nodes with high expected influence were associated with overall treatment outcomes. A post-hoc simulation based on a common-cause model produced similar regression results, indicating that while our findings align with spreading activation, they are not exclusive to this mechanism.

CONCLUSION

The indiscernibility of cross-sectional networks between pre- and post-treatment raises questions about whether cross-sectional networks can illuminate PTSD recovery beyond traditional measures of treatment response.

摘要

目的

横断面网络研究发现,关于网络结构作为对跨疾病治疗的反应的变化,结果不一。本研究从网络心理测量学的角度描述了退伍军人创伤后应激障碍(PTSD)认知加工疗法(CPT)后心理健康的改善情况,并探讨了横断面网络如何增进我们对PTSD恢复的理解。

方法

患有PTSD的退伍军人参加了基于CPT的强化治疗项目(ITP),以两周(N = 635)或三周(N = 457)的形式提供。在治疗前、治疗中和治疗后,通过《精神疾病诊断与统计手册》第5版创伤后应激障碍检查表(PCL-5)自我报告PTSD症状。使用网络比较测试比较每个时间点的横断面网络。线性回归测试从入院到治疗中期的初始治疗获益与总体结果之间是否与节点的预期影响中心性相关。

结果

发现PTSD症状有显著改善,但网络结构在很大程度上未受影响,从治疗前到治疗后全局边强度增加。具有高预期影响的节点的初始治疗获益与总体治疗结果相关。基于共同原因模型的事后模拟产生了类似的回归结果,表明虽然我们的发现与扩散激活一致,但它们并不局限于这一机制。

结论

治疗前后横断面网络的不可区分性引发了关于横断面网络是否能够在传统治疗反应测量之外阐明PTSD恢复情况的疑问。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验