Mental disorders as networks of problems: a review of recent insights

By Eiko I. Fried, Claudia D van Borkulo, A. Cramer, L. Boschloo, Robert A. Schoevers, Denny Borsboom. Social Psychiatry and Psychiatric Epidemiology, 2016

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PurposeThe network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years.MethodsThis paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention.ResultsPertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality—a metric that measures how connected and clinically relevant a symptom is in a network—is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies.ConclusionsWe sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients.

Subfields: Clinical Psychology, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/679f5b67fb707b714b4b15d049bea22e87056bbe

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Citations in the corpus

Investigating the performance of Exploratory Graph analysis and traditional techniques to identify the number of latent factors: a simulation and tutorial (2018, methodology): “Network models have been used not only in the field of psychopathology (Fried et al., 2017), but also in clinical psychology (Bork, Borkulo, Waldorp, Cramer, & Borsboom, 2018), cognitive psychology and individual differences (Golino & Demetriou, 2017; Van Der Maas, Kan, Marsman, & Stevenson, 2017), ”
What do centrality measures measure in psychological networks? (2019, background): “Such psychological 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, & Olde”
Extending psychometric network analysis: Empirical evidence against g in favor of mutualism? (2019, background): “, 2012) that rapidly gained popularity in the fields of psychopathology (Fried et al., 2017) and entered recently the field of cognition and intelligence (Golino & Demetriou, 2017; van der Maas et al.”
Social Anxiety Disorder as a Densely Interconnected Network of Fear and Avoidance for Social Situations (2017, background): “The network approach has ignited an explosion of research on a wide range of mental disorders (for reviews, see Fried and Cramer 2017; Fried et al. 2017; McNally 2016).”
A Tutorial on Regularized Partial Correlation Networks (2016, background): “Recent work has put the importance of replicability in network modeling of psychological data in the spotlight (Epskamp et al. 2017a; Fried et al. 2017b; Fried and Cramer 2017; Fried et al. 2017a; Forbes et al. in press, but see also Borsboom et al. in press).”