常见精神障碍(CMDs)自我报告精神病理学维度的网络结构

IF 2.5 4区 医学 Q2 PSYCHIATRY
Manuel J. Cuesta , Juan I. Arrarás , Gustavo J. Gil-Berrozpe , Victor Peralta , Laura Barrado , Olga Correa , Rebeca Elorza , Lorea Fernández , Irma Garmendia , Lucía Janda , Patricia Macaya , Camino Núñez , Pablo Sabater , Aileen Torrejon
{"title":"常见精神障碍(CMDs)自我报告精神病理学维度的网络结构","authors":"Manuel J. Cuesta ,&nbsp;Juan I. Arrarás ,&nbsp;Gustavo J. Gil-Berrozpe ,&nbsp;Victor Peralta ,&nbsp;Laura Barrado ,&nbsp;Olga Correa ,&nbsp;Rebeca Elorza ,&nbsp;Lorea Fernández ,&nbsp;Irma Garmendia ,&nbsp;Lucía Janda ,&nbsp;Patricia Macaya ,&nbsp;Camino Núñez ,&nbsp;Pablo Sabater ,&nbsp;Aileen Torrejon","doi":"10.1016/j.ejpsy.2022.11.003","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and objectives</h3><p>Common mental disorders (CMDs) in mental health settings show high rates of comorbidities. While semi-structured interviews are the gold standard to establish a diagnosis, there are self-report instruments such as the Psychiatric Diagnostic Screening Questionnaire (PDSQ) that aids clinicians in improving the diagnostic process in a time-efficient manner.</p></div><div><h3>Methods</h3><p>Network analysis of the 13 domains of the PDSQ was applied to a sample of 374 first-contact outpatients to identify domains of psychopathology acting as hubs and bridges of interconnections within the CMDs.</p></div><div><h3>Results</h3><p>A global network densely connected with positive connections among PDSQ domains was found. The global network has four main clusters: depression-anxiety, somatoform, psychosis and substance-related domains. This network allowed for the identification of main ‘nodes’ acting as hubs favoring interconnections between dimensions and main ‘bridges’ easing the connections between clusters.</p></div><div><h3>Conclusion</h3><p>The network structure of the PDSQ domains might provide a complementary explanation to the high rates of comorbidity among CMDs. Moreover, our results support the relevance of the self-administered PDSQ inventory to account for a deeper understanding of comorbidities among CMDs.</p></div>","PeriodicalId":12045,"journal":{"name":"European Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The network structure of self-reported psychopathological dimensions in common mental disorders (CMDs)\",\"authors\":\"Manuel J. Cuesta ,&nbsp;Juan I. Arrarás ,&nbsp;Gustavo J. Gil-Berrozpe ,&nbsp;Victor Peralta ,&nbsp;Laura Barrado ,&nbsp;Olga Correa ,&nbsp;Rebeca Elorza ,&nbsp;Lorea Fernández ,&nbsp;Irma Garmendia ,&nbsp;Lucía Janda ,&nbsp;Patricia Macaya ,&nbsp;Camino Núñez ,&nbsp;Pablo Sabater ,&nbsp;Aileen Torrejon\",\"doi\":\"10.1016/j.ejpsy.2022.11.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background and objectives</h3><p>Common mental disorders (CMDs) in mental health settings show high rates of comorbidities. While semi-structured interviews are the gold standard to establish a diagnosis, there are self-report instruments such as the Psychiatric Diagnostic Screening Questionnaire (PDSQ) that aids clinicians in improving the diagnostic process in a time-efficient manner.</p></div><div><h3>Methods</h3><p>Network analysis of the 13 domains of the PDSQ was applied to a sample of 374 first-contact outpatients to identify domains of psychopathology acting as hubs and bridges of interconnections within the CMDs.</p></div><div><h3>Results</h3><p>A global network densely connected with positive connections among PDSQ domains was found. The global network has four main clusters: depression-anxiety, somatoform, psychosis and substance-related domains. This network allowed for the identification of main ‘nodes’ acting as hubs favoring interconnections between dimensions and main ‘bridges’ easing the connections between clusters.</p></div><div><h3>Conclusion</h3><p>The network structure of the PDSQ domains might provide a complementary explanation to the high rates of comorbidity among CMDs. Moreover, our results support the relevance of the self-administered PDSQ inventory to account for a deeper understanding of comorbidities among CMDs.</p></div>\",\"PeriodicalId\":12045,\"journal\":{\"name\":\"European Journal of Psychiatry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0213616322000957\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0213616322000957","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 1

摘要

背景与目的心理健康环境中常见的精神障碍(CMDs)合并症发生率较高。虽然半结构化访谈是确定诊断的金标准,但也有一些自我报告工具,如精神病诊断筛查问卷(PDSQ),可以帮助临床医生及时改进诊断过程。方法对374例首次接触门诊患者进行PDSQ 13个领域的网络分析,以确定精神病理学领域作为CMD内部互连的枢纽和桥梁。全球网络有四个主要集群:抑郁焦虑、体型、精神病和物质相关领域。该网络允许识别作为集线器的主要“节点”,有利于维度之间的互连,并允许识别缓解集群之间连接的主要“桥梁”。结论PDSQ结构域的网络结构可能为CMD合并症的高发病率提供补充解释。此外,我们的研究结果支持自我管理的PDSQ清单的相关性,以解释对CMD合并症的更深入理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The network structure of self-reported psychopathological dimensions in common mental disorders (CMDs)

Background and objectives

Common mental disorders (CMDs) in mental health settings show high rates of comorbidities. While semi-structured interviews are the gold standard to establish a diagnosis, there are self-report instruments such as the Psychiatric Diagnostic Screening Questionnaire (PDSQ) that aids clinicians in improving the diagnostic process in a time-efficient manner.

Methods

Network analysis of the 13 domains of the PDSQ was applied to a sample of 374 first-contact outpatients to identify domains of psychopathology acting as hubs and bridges of interconnections within the CMDs.

Results

A global network densely connected with positive connections among PDSQ domains was found. The global network has four main clusters: depression-anxiety, somatoform, psychosis and substance-related domains. This network allowed for the identification of main ‘nodes’ acting as hubs favoring interconnections between dimensions and main ‘bridges’ easing the connections between clusters.

Conclusion

The network structure of the PDSQ domains might provide a complementary explanation to the high rates of comorbidity among CMDs. Moreover, our results support the relevance of the self-administered PDSQ inventory to account for a deeper understanding of comorbidities among CMDs.

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
CiteScore
2.90
自引率
0.00%
发文量
40
审稿时长
43 days
期刊介绍: The European journal of psychiatry is a quarterly publication founded in 1986 and directed by Professor Seva until his death in 2004. It was originally intended to report “the scientific activity of European psychiatrists” and “to bring about a greater degree of communication” among them. However, “since scientific knowledge has no geographical or cultural boundaries, is open to contributions from all over the world”. These principles are maintained in the new stage of the journal, now expanded with the help of an American editor.
×
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:481959085
Book学术官方微信