Comorbidity: A network perspective

By A. Cramer, Lourens J. Waldorp, H.L.J. van der Maas, Denny Borsboom. Behavioral and Brain Sciences, 2010

1,321 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/b3cd789c812dcac582d337f7cda2b8d27afd7ce6

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

In Psychiatry and Mental health

Citations in the corpus

A Tutorial on Regularized Partial Correlation Networks (2016, background): “Psychological networks thus offer a different view of item clusters: syndromes such as depression or anxiety disorder in the realm of mental disorders (Cramer et al., 2010; Borsboom, 2017; Fried et al., 2017b), personality facets or domains such as extraversion or neuroticism in personality research”
Can network analysis transform psychopathology? (2016, background): “Indeed, as Cramer et al. (2010a) have persuasively argued, nonspecific symptoms (e.g., concentration impairment) that appear in many diagnostic criteria sets may be especially important.”
State of the aRt personality research: A tutorial on network analysis of personality data in R (2015, neutral): “The issue is important in terms of modeling idiosyncrasies in behavior, but may also be key in terms of relating normal personality to psychopathology (Cramer et al., 2010).”
Computational psychiatry as a bridge from neuroscience to clinical applications (2016, methodology): “The algorithm extracts 74 features from the EEG of each patient to predict the most likely successful medication for depression.”
Mental disorders as networks of problems: a review of recent insights (2016, neutral): “[2] found that the empirical network structure of MDD and GAD symptoms in a general population sample was entangled.”
Generalized Network Psychometrics: Combining Network and Latent Variable Models (2016, neutral): “causal effects, semantic overlap, or reciprocal interactions between putative indicators of a latent variable (Borsboom, 2008; Cramer et al., 2010; Borsboom et al., 2011; Cramer et al., 2012; Schmittmann et al., 2013).”
Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential (2015, background): “Network models estimate the relationships among symptoms within or across time [106,109,110], and offer a new perspective on why symptoms cluster.”
How well do network models predict observations? On the importance of predictability in network models (2016, background): “For instance, Cramer and colleagues [10] suggested an alternative view on the concept of comorbidity by analyzing how symptoms of diﬀerent psychological disorders are connected to each other.”
Estimating psychological networks and their accuracy: A tutorial paper (2016, background): “In the last ﬁve years, network research has gained substantial attention in psychological sciences (Borsboom and Cramer, 2013; Cramer et al., 2010).”
The Gaussian Graphical Model in Cross-Sectional and Time-Series Data (2016, methodology): “When the data are continuous and assumed normally distributed, the GGM can be estimated.”
Critical slowing down as early warning for the onset and termination of depression (2013, background): “Consequently, new models of the etiology of depression involve a network of interactions between components, such as emotions, cognitions, and behaviors (8, 9).”
Stevens’ forgotten crossroads: the divergent measurement traditions in the physical and psychological sciences from the mid-twentieth century (2015, background): “…researchers have begun to heed this message by adapting complex network models from biological and ecological sciences to investigate psychological phenomena without any necessary assumption of underlying psychological quantities or measurement (Cramer et al., 2010; Borsboom and Cramer, 2013).”