认知去抑制机制解释了成人注意力缺陷多动障碍特征的个体差异。

IF 3.2 2区 心理学 Q1 BEHAVIORAL SCIENCES
Jeggan Tiego, Antonio Verdejo-Garcia, Alexandra Anderson, Julia Koutoulogenis, Mark A. Bellgrove
{"title":"认知去抑制机制解释了成人注意力缺陷多动障碍特征的个体差异。","authors":"Jeggan Tiego,&nbsp;Antonio Verdejo-Garcia,&nbsp;Alexandra Anderson,&nbsp;Julia Koutoulogenis,&nbsp;Mark A. Bellgrove","doi":"10.1016/j.cortex.2023.06.013","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control – the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering – adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies.</p></div><div><h3>Methods</h3><p>This cross-sectional and correlational study recruited 650 adults (330 males) aged 18–69 years (<em>M</em> = 33.06; <em>MD</em> = 31.00; <em>SD</em> = 10.50), with previously diagnosed ADHD (<em>n</em> = 329) and those from the general community without a history of ADHD (<em>n</em> = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online.</p></div><div><h3>Results</h3><p>Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor.</p></div><div><h3>Conclusions</h3><p>Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.</p></div>","PeriodicalId":10758,"journal":{"name":"Cortex","volume":"167 ","pages":"Pages 178-196"},"PeriodicalIF":3.2000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits\",\"authors\":\"Jeggan Tiego,&nbsp;Antonio Verdejo-Garcia,&nbsp;Alexandra Anderson,&nbsp;Julia Koutoulogenis,&nbsp;Mark A. Bellgrove\",\"doi\":\"10.1016/j.cortex.2023.06.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control – the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering – adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies.</p></div><div><h3>Methods</h3><p>This cross-sectional and correlational study recruited 650 adults (330 males) aged 18–69 years (<em>M</em> = 33.06; <em>MD</em> = 31.00; <em>SD</em> = 10.50), with previously diagnosed ADHD (<em>n</em> = 329) and those from the general community without a history of ADHD (<em>n</em> = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online.</p></div><div><h3>Results</h3><p>Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor.</p></div><div><h3>Conclusions</h3><p>Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.</p></div>\",\"PeriodicalId\":10758,\"journal\":{\"name\":\"Cortex\",\"volume\":\"167 \",\"pages\":\"Pages 178-196\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cortex\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010945223001739\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BEHAVIORAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cortex","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010945223001739","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

背景:成人注意力缺陷多动障碍(ADHD)与精神共病和功能损害密切相关。在这里,我们的目标是使用一种新开发的具有强大心理测量特性的在线认知电池来测量三种认知机制的个体差异,这些认知机制被认为是成人多动症特征的基础:1)注意力控制——动员认知资源来阻止优势运动反应的能力;2) 信息采样/收集——在做出决定之前,对刺激检测任务中的信息进行充分采样;以及3)转变——适应积极和消极突发事件的能力。方法:这项横断面和相关性研究招募了650名18-69岁的成年人(330名男性)(M=33.06;MD=31.00;SD=10.50),他们之前诊断为多动症(n=329),以及来自普通社区的没有多动症病史的人(n=321)。ADHD特征(即注意力不集中/无组织、冲动、多动)和认知电池的自我报告测量是在网上完成的。结果:潜在类别分析、探索性结构方程模型和因子混合模型显示,自我报告的ADHD特征形成了一维且近似正态分布的表型。贝叶斯结构方程模型表明,通过认知电池测量的所有三种机制都解释了多动症特征的独特增量变化,总共15.9%的多动症特征因子解释了这一变化。结论:注意力控制和转移,以及较少研究的信息收集认知过程,解释了自我报告的多动症特征的个体差异差异,有可能对成人多动症产生遗传和神经生物学见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits

Background

Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control – the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering – adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies.

Methods

This cross-sectional and correlational study recruited 650 adults (330 males) aged 18–69 years (M = 33.06; MD = 31.00; SD = 10.50), with previously diagnosed ADHD (n = 329) and those from the general community without a history of ADHD (n = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online.

Results

Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor.

Conclusions

Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.

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
Cortex
Cortex 医学-行为科学
CiteScore
7.00
自引率
5.60%
发文量
250
审稿时长
74 days
期刊介绍: CORTEX is an international journal devoted to the study of cognition and of the relationship between the nervous system and mental processes, particularly as these are reflected in the behaviour of patients with acquired brain lesions, normal volunteers, children with typical and atypical development, and in the activation of brain regions and systems as recorded by functional neuroimaging techniques. It was founded in 1964 by Ennio De Renzi.
×
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