Department of Psychological Sciences, University of Missouri, United States.
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, United States.
Addict Behav. 2022 Aug;131:107333. doi: 10.1016/j.addbeh.2022.107333. Epub 2022 Apr 9.
Modern theoretical models of Alcohol Use Disorder (AUD) highlight the different functional roles played by various mechanisms associated with different symptoms. Symptom network models (SNMs) offer one approach to modeling AUD symptomatology in a way that could reflect these processes and provide important information on the progression and persistence of disorder. However, much of the research conducted using SNMs relies on cross-sectional data, which has raised questions regarding the extent they reflect dynamic processes. The current study aimed to (a) examine symptom networks of AUD and (b) compare the extent to which cross-sectional network models had similar structures and interpretations as longitudinal network models. 17,360 participants from Wave 1 (2001-2002) and Wave 2 (2003-2004) of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC) were used to model cross-sectional and longitudinal AUD symptom networks. The cross-sectional analyses demonstrate high replicability across waves and central symptoms consistent with other cross-sectional studies on addiction networks. The longitudinal network shared much less similarity than the cross-sectional networks and had a substantially different structure. Given the increasing attention given to the network perspective in psychopathology research, the results of this study raise concerns about interpreting cross-sectional symptom networks as representative of temporal changes occurring within a psychological disorder. We conclude that the psychological symptom network literature should be bolstered with additional research on longitudinal network models.
现代酒精使用障碍(AUD)理论模型强调了与不同症状相关的各种机制的不同功能作用。症状网络模型(SNM)提供了一种建模 AUD 症状的方法,可以反映这些过程,并提供有关疾病进展和持续的重要信息。然而,使用 SNM 进行的大部分研究都依赖于横断面数据,这引发了关于它们在多大程度上反映动态过程的问题。本研究旨在:(a)检查 AUD 的症状网络;(b)比较横断面网络模型和纵向网络模型在结构和解释上的相似程度。使用来自国家酒精和相关条件流行病学调查(NESARC)第 1 波(2001-2002 年)和第 2 波(2003-2004 年)的 17360 名参与者来构建横断面和纵向 AUD 症状网络。横断面分析表明,各波之间的高可重复性和与其他成瘾网络横断面研究一致的核心症状。纵向网络的相似性远低于横断面网络,结构也大不相同。鉴于网络视角在精神病理学研究中受到越来越多的关注,本研究的结果引发了对将横断面症状网络解释为代表心理障碍内发生的时间变化的担忧。我们得出结论,应该用更多关于纵向网络模型的研究来加强心理症状网络文献。