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HiTOP 谱图对预测大型非西方样本多维和分类躯体化的构建和标准效度。

Construct and criterion validity of the HiTOP spectra to predict dimensional and categorical somatization in a large non-western sample.

机构信息

Neurosciences Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.

Department of Neuroscience and Psychopathology Research, Mind GPS Institute, Kermanshah, Iran.

出版信息

Sci Rep. 2023 Aug 14;13(1):13197. doi: 10.1038/s41598-023-40545-3.

Abstract

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a phenotypic data-driven framework for the classification of psychopathology. We tested the construct and criterion validity of the HiTOP spectra measured by the Personality Inventory for DSM-5 (PID-5) using exploratory structural equation modeling (ESEM) and hierarchical regressions both to predict somatic symptom and related disorders (SSRD) and a somatization factor. The case-control study used hierarchical logistic regressions to distinguish 257 cases with SSRD from 1007 healthy controls by both the maladaptive and the temperament factors. The extracted factors were also used in hierarchical linear regressions to predict the dimensional somatization factor. The seven temperament factors explained more variance above and beyond the five maladaptive factors when predicting SSRD (pseudo R = 0.169 to 0.266 versus 0.125 to 0.196; change in pseudo R = 0.055 to 0.087 versus 0.011 to 0.017). The temperament factors also explained more variance above and beyond the maladaptive factors when predicting the somatization factor (R = 0.392 versus 0.269; change in R = 0.146 versus 0.023). Although the HiTOP spectra measured by PID-5 are significant structures related to the categorical and dimensional measurements of somatoform, our findings highlight potential problems with both the construct and criterion validity of the HiTOP spectra.

摘要

精神病理学的层次分类(HiTOP)是一种基于表型数据的精神病理学分类框架。我们使用探索性结构方程建模(ESEM)和层次回归来测试人格障碍诊断与统计手册第五版人格量表(PID-5)测量的 HiTOP 谱的构念和效标效度,以预测躯体症状及相关障碍(SSRD)和躯体化因子。病例对照研究使用分层逻辑回归来区分 257 例 SSRD 病例和 1007 例健康对照,同时区分适应不良和气质因素。提取的因子也用于分层线性回归来预测维度躯体化因子。在预测 SSRD 时,七个气质因素比五个适应不良因素解释了更多的方差(伪 R=0.169 至 0.266 与 0.125 至 0.196;伪 R 的变化=0.055 至 0.087 与 0.011 至 0.017)。在预测躯体化因子时,气质因素也比适应不良因素解释了更多的方差(R=0.392 与 0.269;R 的变化=0.146 与 0.023)。虽然 PID-5 测量的 HiTOP 谱是与躯体形式的分类和维度测量相关的显著结构,但我们的研究结果强调了 HiTOP 谱的构念和效标效度存在潜在问题。

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