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ABCD 研究中的精神病理学的以患者为中心的方法:表型和神经认知相关性。

Person-centred Approaches to Psychopathology in the ABCD Study: Phenotypes and Neurocognitive Correlates.

机构信息

Department of Psychology, School of Human and Health Sciences, University of Huddersfield, Huddersfield, UK.

Department of Health Sciences, University of Leicester, Leicester, UK.

出版信息

Res Child Adolesc Psychopathol. 2023 Aug;51(8):1195-1212. doi: 10.1007/s10802-023-01065-w. Epub 2023 Apr 29.

Abstract

Issues with classifying psychopathology using narrow diagnostic categories have prompted calls for the use of dimensional approaches. Yet questions remain about how closely dimensional approaches reflect the way symptoms cluster in individuals, whether known risk factors (e.g. preterm birth) produce distinct symptom phenotypes, and whether profiles reflecting symptom clusters are associated with neurocognitive factors. To identify distinct profiles of psychopathology, latent class analysis was applied to the syndrome scales of the parent-reported Child Behaviour Checklist for 11,381 9- and 10- year-olds from the Adolescent Brain Cognitive Development study. Four classes were identified, reflecting different profiles, to which children were assigned probabilistically; Class 1 (88.6%) reflected optimal functioning; Class 2 (7.1%), predominantly internalising; Class 3 (2.4%), predominantly externalising; and Class 4 (1.9%), universal difficulties. To investigate the presence of a possible preterm behavioural phenotype, the proportion of participants allocated to each class was cross-tabulated with gestational age category. No profile was specific to preterm birth. Finally, to assess the neurocognitive factors associated with class membership, elastic net regressions were conducted revealing a relatively distinct set of neurocognitive factors associated with each class. Findings support the use of large datasets to identify psychopathological profiles, explore phenotypes, and identify associated neurocognitive factors.

摘要

使用狭义诊断类别对精神病理学进行分类存在问题,这促使人们呼吁使用维度方法。然而,关于维度方法如何紧密反映症状在个体中的聚类方式、已知风险因素(如早产)是否产生独特的症状表型,以及反映症状聚类的特征是否与神经认知因素相关,仍存在疑问。为了确定精神病理学的不同特征,对来自青少年大脑认知发展研究的 11381 名 9 至 10 岁儿童的父母报告的儿童行为检查表的综合征量表进行了潜在类别分析。确定了四个反映不同特征的类别,这些类别是根据概率分配给儿童的;类别 1(88.6%)反映了最佳功能;类别 2(7.1%),主要是内化;类别 3(2.4%),主要是外化;类别 4(1.9%),普遍存在困难。为了研究是否存在早产行为表型的可能性,将每个类别的参与者比例与胎龄类别进行交叉制表。没有任何特征与早产有关。最后,为了评估与类别成员资格相关的神经认知因素,进行了弹性网络回归,揭示了与每个类别相关的相对独特的神经认知因素集。研究结果支持使用大型数据集来确定精神病理学特征、探索表型和识别相关的神经认知因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c273/10368562/be096a246314/10802_2023_1065_Fig1_HTML.jpg

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