Network analysis: An overview for mental health research
(2024) International Journal of Methods in Psychiatric Research — Vol. 33, n° 4, p. e2034 (2024)
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- Abstract
- Network approaches to psychopathology have become increasingly common in mental health research, with many theoretical and methodological developments quickly gaining traction. This article illustrates contemporary practices in applying network analytical tools, bridging the gap between network concepts and their empirical applications. We explain how we can use graphs to construct networks representing complex associations among observable psychological variables. We then discuss key network models, including dynamic networks, time‐varying net- works, network models derived from panel data, network intervention analysis, latent networks, and moderated models. In addition, we discuss Bayesian networks and their role in causal inference with a focus on cross‐sectional data. After presenting the different methods, we discuss how network models and psychopathology theories can meaningfully inform each other. We conclude with a discussion that summarizes the insights each technique can provide in mental health research.
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Giovanni Briganti, Marco Scutari, Sacha Epskamp, Denny Borsboom, Ria H. A. Hoekstra, Hudson Fernandes Golino, Alexander P. Christensen, Yannick Morvan, Omid V. Ebrahimi, Giulio Costantini, Heeren, A., Jill de Ron, Laura F. Bringmann, Karoline Huth, Jonas M. B. Haslbeck, Adela‐Maria Isvoranu, Maarten Marsman, Tessa Blanken, Allison Gilbert, et al. (2024). Network analysis: An overview for mental health research. International Journal of Methods in Psychiatric Research, 33(4), e2034. https://doi.org/10.1002/mpr.2034 (Original work published 2024)