Fuchshuber Jürgen, Zeldovich Marina, Aranyi Gabor, Winter Lisa, Kuska Martin, Dumont Dominique, Humer Elke, Unterrainer Human-Friedrich
Department of Psychoanalysis and Psychotherapy, Medical University Vienna, Vienna, Austria.
Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University Vienna, Vienna, Austria.
Clin Psychol Psychother. 2025 Mar-Apr;32(2):e70063. doi: 10.1002/cpp.70063.
The Clinical Outcomes in Routine Evaluation - Outcome Measures (CORE-OM) is a pantheoretical diagnostic instrument that has been widely used in mental health research. Nevertheless, the exploration of the factor structure of the CORE-OM yields diverse results.
This study aimed to explore the internal structure of the German CORE-OM using network analysis and compare several competing factorial structures of the CORE-OM with traditional confirmatory factor analysis (CFA) to gain a more comprehensive understanding of its structural validity.
A total sample comprised 4496 (63% female) participants from an outpatient population. In a first step, we used network analysis (n = 2248) to assess relationships between the items, followed by explorative graph analysis (EGA) to analyse community structure. Finally, we specified five competing models, including the one derived from the EGA, and used CFA in a second sample (n = 2248) to identify the best-fitting structure of the instrument.
The estimated cross-sectional network demonstrated high correlation stability. The average item predictability was R = 0.42. The EGA identified four distinct communities in the German CORE-OM (General Problems; Interpersonal Problems; Positive Resources; Self Harm Risk). Confirmatory factor analysis showed that the EGA-derived models had the most parsimonious fit.
These findings suggest a refined structure for the CORE-OM, highlighting key item relationships and offering potential improvements for scoring and clinical use.
常规评估中的临床结果 - 结果测量(CORE-OM)是一种泛理论诊断工具,已在心理健康研究中广泛使用。然而,对CORE-OM因子结构的探索产生了不同的结果。
本研究旨在使用网络分析探索德语版CORE-OM的内部结构,并将CORE-OM的几种竞争因子结构与传统验证性因子分析(CFA)进行比较,以更全面地了解其结构效度。
总样本包括来自门诊人群的4496名参与者(63%为女性)。第一步,我们使用网络分析(n = 2248)评估项目之间的关系,随后进行探索性图分析(EGA)以分析社区结构。最后,我们指定了五个竞争模型,包括从EGA得出的模型,并在第二个样本(n = 2248)中使用CFA来确定该工具的最佳拟合结构。
估计的横断面网络显示出高相关性稳定性。平均项目可预测性为R = 0.42。EGA在德语版CORE-OM中识别出四个不同的社区(一般问题;人际问题;积极资源;自伤风险)。验证性因子分析表明,源自EGA的模型具有最简约的拟合度。
这些发现表明CORE-OM有一个优化的结构,突出了关键项目关系,并为评分和临床应用提供了潜在的改进。