映射人格特征:一种网络方法来揭示精神疾病诊断与统计手册的人格清单,第五版,简要形式的析因结构。

IF 4.2
Ludovica Oppici, Alessia Antelmi, Cristina Mazza, Merylin Monaro, Francesca Bosco, Paolo Roma
{"title":"映射人格特征:一种网络方法来揭示精神疾病诊断与统计手册的人格清单,第五版,简要形式的析因结构。","authors":"Ludovica Oppici, Alessia Antelmi, Cristina Mazza, Merylin Monaro, Francesca Bosco, Paolo Roma","doi":"10.1037/per0000745","DOIUrl":null,"url":null,"abstract":"<p><p>This study explores the structural properties of the Personality Inventory for the <i>Diagnostic and Statistical Manual of Mental Disorders</i>, fifth edition, Brief Form (PID-5-BF) by applying network analysis and community detection as a data-driven alternative to traditional factor models. Traditionally, the PID-5-BF assesses personality traits across five domains-Negative Affectivity, Detachment, Antagonism, Disinhibition, and Psychoticism-but has shown notable inconsistencies in item alignment and factorial coherence. To examine these issues, data were collected from 2,766 Italian participants (71.7% female, 28.3% male, <i>M</i><sub>age</sub> = 32.94 years, <i>SD</i> = 13.2). The estimated network revealed a stable structure, supported by robust centrality measures (closeness = 0.59, expected influence = 0.75, strength = 0.75). Community detection identified five empirically coherent clusters-Disinhibition, Demoralization, Detachment and Irritability, Psychosocial Alienation, and Pathological Egocentrism-suggesting an alternative organization of maladaptive traits in this population. To assess generalizability, a second analysis was conducted on a Hungarian sample (<i>N</i> = 355), yielding a five-structure solution with different item compositions. While the network approach emphasizes item-level associations, the specific configurations varied across samples in ways that reflect contextual influences. Nonetheless, this method offers complementary insights to traditional factorial models, highlighting how personality traits may organize differently across populations and supporting the use of network-based approaches in refining dimensional models of personality pathology. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":74420,"journal":{"name":"Personality disorders","volume":" ","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping personality traits: A network approach to uncovering Personality Inventory for Diagnostic and Statistical Manual of Mental Disorders, fifth edition, Brief Form's factorial structure.\",\"authors\":\"Ludovica Oppici, Alessia Antelmi, Cristina Mazza, Merylin Monaro, Francesca Bosco, Paolo Roma\",\"doi\":\"10.1037/per0000745\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study explores the structural properties of the Personality Inventory for the <i>Diagnostic and Statistical Manual of Mental Disorders</i>, fifth edition, Brief Form (PID-5-BF) by applying network analysis and community detection as a data-driven alternative to traditional factor models. Traditionally, the PID-5-BF assesses personality traits across five domains-Negative Affectivity, Detachment, Antagonism, Disinhibition, and Psychoticism-but has shown notable inconsistencies in item alignment and factorial coherence. To examine these issues, data were collected from 2,766 Italian participants (71.7% female, 28.3% male, <i>M</i><sub>age</sub> = 32.94 years, <i>SD</i> = 13.2). The estimated network revealed a stable structure, supported by robust centrality measures (closeness = 0.59, expected influence = 0.75, strength = 0.75). Community detection identified five empirically coherent clusters-Disinhibition, Demoralization, Detachment and Irritability, Psychosocial Alienation, and Pathological Egocentrism-suggesting an alternative organization of maladaptive traits in this population. To assess generalizability, a second analysis was conducted on a Hungarian sample (<i>N</i> = 355), yielding a five-structure solution with different item compositions. While the network approach emphasizes item-level associations, the specific configurations varied across samples in ways that reflect contextual influences. Nonetheless, this method offers complementary insights to traditional factorial models, highlighting how personality traits may organize differently across populations and supporting the use of network-based approaches in refining dimensional models of personality pathology. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>\",\"PeriodicalId\":74420,\"journal\":{\"name\":\"Personality disorders\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Personality disorders\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1037/per0000745\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Personality disorders","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1037/per0000745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究采用网络分析和社区检测作为传统因素模型的数据驱动替代方法,探讨了《精神障碍诊断与统计手册》第五版简要表(PID-5-BF)中人格量表的结构特征。传统上,PID-5-BF评估人格特质的五个领域——消极情感、超然、对抗、去抑制和精神病——但在项目对齐和因子一致性方面显示出显著的不一致性。为了研究这些问题,收集了2766名意大利参与者的数据(71.7%为女性,28.3%为男性,年龄32.94岁,SD = 13.2)。估计的网络显示了一个稳定的结构,由稳健的中心性度量(接近度= 0.59,预期影响= 0.75,强度= 0.75)支持。社区检测发现了五个经验上一致的集群——去抑制、士气低落、疏离和易怒、社会心理疏离和病理性自我中心——这表明该人群中存在另一种适应不良特征的组织。为了评估通用性,对匈牙利样本(N = 355)进行了第二次分析,得出了具有不同项目组成的五结构解决方案。虽然网络方法强调项目层面的关联,但不同样本的具体配置以反映上下文影响的方式有所不同。尽管如此,该方法为传统的因子模型提供了补充见解,突出了人格特征在不同人群中的组织方式不同,并支持使用基于网络的方法来完善人格病理学的维度模型。(PsycInfo Database Record (c) 2025 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping personality traits: A network approach to uncovering Personality Inventory for Diagnostic and Statistical Manual of Mental Disorders, fifth edition, Brief Form's factorial structure.

This study explores the structural properties of the Personality Inventory for the Diagnostic and Statistical Manual of Mental Disorders, fifth edition, Brief Form (PID-5-BF) by applying network analysis and community detection as a data-driven alternative to traditional factor models. Traditionally, the PID-5-BF assesses personality traits across five domains-Negative Affectivity, Detachment, Antagonism, Disinhibition, and Psychoticism-but has shown notable inconsistencies in item alignment and factorial coherence. To examine these issues, data were collected from 2,766 Italian participants (71.7% female, 28.3% male, Mage = 32.94 years, SD = 13.2). The estimated network revealed a stable structure, supported by robust centrality measures (closeness = 0.59, expected influence = 0.75, strength = 0.75). Community detection identified five empirically coherent clusters-Disinhibition, Demoralization, Detachment and Irritability, Psychosocial Alienation, and Pathological Egocentrism-suggesting an alternative organization of maladaptive traits in this population. To assess generalizability, a second analysis was conducted on a Hungarian sample (N = 355), yielding a five-structure solution with different item compositions. While the network approach emphasizes item-level associations, the specific configurations varied across samples in ways that reflect contextual influences. Nonetheless, this method offers complementary insights to traditional factorial models, highlighting how personality traits may organize differently across populations and supporting the use of network-based approaches in refining dimensional models of personality pathology. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信