Comorbidity: A network perspective
Comorbidity: A network perspective
复制标题
DOI：
10.1017/s0140525x09991567
复制
发表时间：
2010-04-01
影响因子：
29.3
通讯作者：
Borsboom, Denny
中科院分区：
文献类型：
--
作者：
Cramer, Angelique O. J.;Waldorp, Lourens J.;Borsboom, Denny
共病研究的关键问题在于它所依赖的心理测量学基础，即潜变量理论，在该理论中，精神障碍被视为导致一系列症状的潜变量。从这个角度来看，协方差是多个潜在变量之间的（双向）关系。我们认为，这样一个潜在的变量的角度遇到了严重的问题，在研究的comorrhoea，并提供了一个根本不同的概念化的网络方法，comorrhoea是假设产生的多种疾病的症状之间的直接关系。我们提出了一种方法来可视化共病网络，并基于一个经验网络的抑郁症和广泛性焦虑症，我们认为，这种方法产生了现实的假设，途径共病，重叠的症状，和诊断边界，这是不自然容纳的潜变量模型：一些途径共病通过症状空间比其他人更有可能;这些路径通常具有相同的方向（即，从一种疾病的症状到另一种疾病的症状）;重叠的症状在合并症中起重要作用;诊断类别之间的界限必然是模糊的。
The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory, in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a radically different conceptualization in terms of a network approach, where comorbidity is hypothesized to arise from direct relations between symptoms of multiple disorders. We proposed method to visualize comorbidity networks and, based on an empirical network for major depression and generalized anxiety, we argue that this approach generates realistic hypotheses about pathways to comorbidity, overlapping symptoms, and diagnostic boundaries, that are not naturally accommodated by latent variable models: Some pathways to comorbidity through the symptom space are more likely than others; those pathways generally have the same direction (i.e., from symptoms of one disorder to symptoms of the other); overlapping symptoms play an important role in comorbidity; and boundaries between diagnostic categories are necessarily fuzzy.