Abstract
Network analysis has been recently adopted by the field of psychology to explore networks of symptoms in psychopathology, and wider interactive networks of biological, behavioral, and psychological factors influencing mental health. The network theory of psychopathology conceptualizes symptoms of mental disorder as causally connected, rather than being caused by disease or an underlying latent variable. The most common type of network analysis is based on partial correlations which estimate unique relationships between two variables while controlling for the effect of all other variables in the network on that relationship. Network analysis has the advantage over more traditional analytical methods in that it can examine multiple relationships between several variables at one time, without the need to arbitrarily assign a dependent or independent variable. It allows investigation of relationships between variables as causes of psychopathology, rather than as symptoms that share a single causal factor. Network analysis can be applied to mindfulness research, examining the structure of multifaceted mindfulness models, investigating how specific mindfulness factors relate to dimensions and symptoms of mental health, and exploring how relationships in a network change after mindfulness-based interventions. This chapter provides an introduction to the theoretical framework of network analysis and its practical applications for psychological research relevant to mindfulness.
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Chalmers, R.A., Cervin, M., Medvedev, O.N. (2022). Network Analysis. In: Medvedev, O.N., Krägeloh, C.U., Siegert, R.J., Singh, N.N. (eds) Handbook of Assessment in Mindfulness Research. Springer, Cham. https://doi.org/10.1007/978-3-030-77644-2_70-1
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