Latent State Trait Modelling of Executive Functions

执行功能的潜在状态特征建模

• 批准号: 451546386
• 负责人: Professor Dr. Ulrich Ettinger
• 金额: --
• 依托单位: Abteilung Allgemeine Psychologie I
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/451546386?language=en
• 关键词: Latent; State; Trait; Modelling; Executive

Executive functions are of great importance in the control of cognitive, perceptual and motor processes and allow goal-oriented, flexible behaviour. The measurement of performance in executive function paradigms and their individual differences plays an important role in cognitive psychological, neuropsychological and neuropsychiatric research. A fundamental assumption of these studies is the reliability of the dependent variables and the existence of large trait components; however, relevant findings in the literature are heterogeneous. Moreover, an estimation of the trait and state components of variance by means of latent state trait theory (LST) is missing so far. The proposed project wishes to fill this gap in the literature and additionally aims to provide data that allow conclusions on the required number of trials in each experimental task. To do so, 250 healthy, young men and women will be examined using a comprehensive executive functions battery. The executive functions under investigation are inhibition, working memory (updating) and cognitive flexibility (shifting). The sample will be examined with the test battery on three occasions at weekly intervals. Classic measures of test-retest reliability and internal consistency and, using structural equation modelling, LST parameters will be obtained.

执行功能在控制认知、知觉和运动过程中非常重要，并允许目标导向的灵活行为。执行功能范式的表现测量及其个体差异在认知心理学、神经心理学和神经精神病学研究中起着重要作用。这些研究的一个基本假设是因变量的可靠性和大性状成分的存在；然而，文献中的相关发现是异质的。此外，利用潜态特征理论（LST）对方差的特征和状态分量进行估计，目前尚缺乏。拟议的项目希望填补文献中的这一空白，并旨在提供数据，以便在每个实验任务中得出所需试验数量的结论。为此，将对250名健康的年轻男女进行综合执行功能检查。被研究的执行功能是抑制、工作记忆（更新）和认知灵活性（转移）。样品每星期用测试电池检测三次。测试-重测信度和内部一致性的经典度量，并使用结构方程建模，将获得LST参数。