Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology

By Eiko I. Fried, A. Cramer. Perspectives on Psychological Science, 2017

829 citations recorded by the source corpus.

Subfields: Biological Psychiatry, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/d0af922042d52115d0837a438155c6ec320b1f5c

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Citations in the corpus

Mental Health and Social Contact During the COVID-19 Pandemic: An Ecological Momentary Assessment Study (2020, methodology): “Hardly, because there are many unknowns (cf. Fried, 2021; Fried & Cramer, 2017).”
All for one and one for all: Mental disorders in one dimension (2018, background): “in which disorders influence each other (straight arrows) and themselves (looped arrows) over time (131).”
What do centrality measures measure in psychological networks? (2019, background): “…networks are different from social networks, as the nodes in the network are not people but psychological variables, such as affect states or symptoms (Cramer et al., 2012; Fried & Cramer, 2017; Fried et al., 2017; Klippel et al., 2017; van Roekel, Heininga, Vrijen, Snippe, & Oldehinkel, 2018).”
Emotion Regulation Difficulties Related to Depression and Anxiety: A Network Approach to Model Relations Among Symptoms, Positive Reappraisal, and Repetitive Negative Thinking (2019, methodology): “This approach complies with the Research Domain Criteria (Insel et al., 2010) and may help us to better understand the heterogeneous nature of conventional diagnostic categories (Fried & Cramer, 2017).”
How well do network models predict observations? On the importance of predictability in network models (2016, background): “similar the variables are and do not re ect mutual causal in uence. Consequently, we would not interpret the predictability of these variables as the degree of determination by neighboring nodes. See [14] for a discussion of this problem. Solutions could be to determine the topological overlap [38] ”
Stability and variability of personality networks. A tutorial on recent developments in network psychometrics (2017, methodology): “Although correlation networks can be used (e.g., Cramer et al., 2012), the most common method for cross-sectional data has been to elaborate partial correlation networks (Costantini, Epskamp, et al., 2015; Epskamp, Borsboom,& Fried, 2017), which are equivalent to standardized Gaussian Graphical Mode”
Network analysis: a brief overview and tutorial (2018, methodology): “As noted by Fried and Cramer (2017) the literature in general requires more conceptual and methodological developments for estimating both the accuracy and stability of networks.”
A Tutorial on Regularized Partial Correlation Networks (2016, methodology): “Even when one expects a network model to largely explain the data, it may be implausible to assume that no latent variables cause any covariation in the network model (Fried and Cramer, 2017; Epskamp et al., 2017c; Chandrasekaran et al., 2012).”
Bridge Centrality: A Network Approach to Understanding Comorbidity (2019, background): “More recently, an emphasis has been placed on estimating networks at the level of the individual (Epskamp, Borsboom, & Fried, 2018; Fried & Cramer, 2017).”