An exploratory network analysis to investigate schizotypy's structure using the 'Multidimensional Schizotypy Scale' and 'Oxford-Liverpool Inventory' in a healthy cohort.

IF 3 Q2 PSYCHIATRY
Pierfrancesco Sarti, Werner Surbeck, Giacomo Cecere, Noemi Dannecker, Rahel Horisberger, Nils Kallen, Wolfgang Omlor, Anna Steiner, Dario Palpella, Marius Brandenberg, Victoria Edkins, Nicolas Langer, Johanna M C Blom, Philipp Homan
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Abstract

Schizophrenia spectrum disorders and schizotypy share traits across positive, negative, and disorganised domains. Instruments like the Multidimensional Schizotypy Scale (MSS) and the Oxford-Liverpool Inventory (O-LIFE) offer nuanced perspectives on schizotypy, including its expression as a personality trait and its potential clinical outcomes. This study investigates the structure of schizotypy using exploratory graph analysis (EGA) to analyse how the MSS and O-LIFE operationalise the construct in the same sample of German speakers. This approach allows comparison of their factorial structures from both statistical and clinical perspectives, while also assessing cross-cultural validity. 1059 German-speaking, healthy participants completed the MSS and O-LIFE questionnaires. EGA was conducted to identify dimensional structures within each scale, utilising the graphical lasso algorithm for network estimation and the Walktrap community detection method for clustering. Confirmatory factor analysis was used to assess model fit and reliability, using indices such as the comparative fit index and root mean square error of approximation. EGA of the MSS revealed three primary dimensions and an additional 'dissociated' domain. This four-dimensional model showed improved fit and reliability compared to the original model. For the O-LIFE, EGA identified a refined four-factor structure comprising: 'cognitive and behavioural disorganisation,' 'introversion', 'unusual experiences', and 'environmental valence', all validated by confirmatory analyses. This study supports the multidimensional view of schizotypy, introducing new factor structures in the MSS and O-LIFE that emphasise the previously unexplored domains 'dissociated' and 'environmental valence.' These findings highlight the value of culturally adaptive tools in enhancing schizotypy assessment and intervention strategies.

利用 "多维精神分裂症量表 "和 "牛津-利物浦量表 "对健康人群的精神分裂症结构进行探索性网络分析。
精神分裂症谱系障碍和分裂型在积极、消极和无组织域上具有共同的特征。多维分裂型量表(MSS)和牛津-利物浦量表(O-LIFE)等工具为分裂型提供了细致入微的视角,包括其作为一种人格特征的表达及其潜在的临床结果。本研究使用探索性图分析(EGA)来研究分裂型的结构,以分析MSS和O-LIFE如何在相同的德语使用者样本中运作该结构。这种方法允许从统计和临床角度比较它们的析因结构,同时也评估跨文化有效性。1059名讲德语的健康参与者完成了MSS和O-LIFE问卷调查。EGA用于识别每个尺度内的维度结构,使用图形lasso算法进行网络估计,使用Walktrap社区检测方法进行聚类。验证性因子分析采用比较拟合指数和近似均方根误差等指标来评估模型的拟合和可靠性。MSS的EGA显示了三个主要维度和一个额外的“解离”域。与原始模型相比,该四维模型显示出更好的拟合和可靠性。对于O-LIFE, EGA确定了一个精致的四因素结构,包括:“认知和行为紊乱”、“内向”、“不寻常的经历”和“环境效价”,所有这些都通过验证性分析得到验证。这项研究支持了分裂型的多维观点,在MSS和O-LIFE中引入了新的因子结构,强调了以前未探索的“解离”和“环境价”域。这些发现强调了文化适应性工具在加强精神分裂型评估和干预策略方面的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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