Psychology, Interamerican
Overview of the Network Approach and Contributions to Clinical Research and Practice
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network approach
psychological disorders
latente variables
process-based therapy

How to Cite

Talask, G., Lemos, V. do C. O. de ., da Costa, R. T., Nardi, A. E., & de Carvalho, M. R. (2022). Overview of the Network Approach and Contributions to Clinical Research and Practice. Revista Interamericana De Psicología/Interamerican Journal of Psychology, 56(3), e1662.


A network approach has been offering an alternative to the conception of psychological disorders as underlying disease. The network assumption views psychological disorders as networks of symptoms of causal interaction. Network analysis offers a unique view of an individual’s system, obtained from data rather than categorization. It allows moving toward specific interventions for specific symptom relationships rather than a protocol approach. In order to provide a current overview of the network approach studies and to present the possible implications for clinical practice, a narrative review of the literature was conducted using the Scopus and PubMed databases. Studies sought to build symptom networks through cross-sectional and time-series data collection methods, allowing analysis of the symptom’s centrality in the inter/intra-individual network, enabling a specific intervention for each patient. Research suggests that changing the connectivity of symptoms and delaying the re-stabilization of an individual's network after a disturbance leads to changing from a healthy to a pathological-stable-state. Monitoring the network dynamics could predict relapse, permitting early intervention in the central symptoms. In conclusion, networks can provide information about the specific psychological mechanisms underlying the development of psychological disorders. However, research is in its infancy, and a consensus on the analysis model is necessary. It is also necessary to consider what types of variables should be included in psychopathological networks.
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Anderson, T., Lunnen, K. M., & Ogles, B. M. (2010). Putting models and techniques in context. In B. L. Duncan, S. D. Miller, B. E. Wampold, & M. A. Hubble (Eds.), The heart and soul of change: Delivering what works in therapy (pp. 143–166). American Psychological Association.

Alvarenga, M. A. S., Flores-Mendoza, C. E., & Gontijo, D. F. (2009). Evolução do DSM quanto ao critério categorial de diagnóstico para o distúrbio da personalidade antissocial. Jornal Brasileiro de Psiquiatria, 58(4).

American Psychiatric Association. (2014). DSM-5: Manual diagnóstico e estatístico de transtornos mentais. Artmed Editora.

American Psychiatric Association. (1980). Diagnostic and Statistical Manual of Mental Disorders [3rd ed.]. American Psychiatric Association.

Barlow, D. H., Farchione, T. J., Bullis, J. R., Gallagher, M. W., Murray-Latin, H., Sauer-Zavala, S., ... & Ametaj, A. (2017). The unified protocol for transdiagnostic treatment of emotional disorders compared with diagnosis-specific protocols for anxiety disorders: A randomized clinical trial. JAMA psychiatry, 74(9), 875-884.

Borsboom, D., & Cramer, A. O. (2013). Network analysis: an integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91-121.

Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5-13.

Campbell, D. G., Felker, B. L., Liu, C. F., Yano, E. M., Kirchner, J. E., Chan, D., Rubenstein, L. V., & Chaney, E. F. (2007). Prevalence of depression-PTSD comorbidity: implications for clinical practice guidelines and primary care-based interventions. Journal of general internal medicine, 22(6), 711–718.

Chorpita, B. F., Daleiden, E. L., & Weisz, J. R. (2005). Identifying and selecting the common elements of evidence based interventions: A distillation and matching model. Mental health services research, 7(1), 5-20.

Easden, M. H., & Kazantzis, N. (2018). Case conceptualization research in cognitive behavior therapy: A state of the science review. Journal of clinical psychology, 74(3), 356-384.

Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2018). The Gaussian graphical model in cross-sectional and time-series data. Multivariate behavioral research, 53(4), 453-480.

Epskamp, S., van Borkulo, C. D., van der Veen, D. C., Servaas, M. N., Isvoranu, A. M., Riese, H., & Cramer, A. O. (2018). Personalized network modeling in psychopathology: The importance of contemporaneous and temporal connections. Clinical Psychological Science, 6(3), 416-427.

Flory, J. D., & Yehuda, R. (2015). Comorbidity between post-traumatic stress disorder and major depressive disorder: alternative explanations and treatment considerations. Dialogues in clinical neuroscience, 17(2), 141–150.

Fried, E. I., van Borkulo, C. D., Cramer, A. O., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2017). Mental disorders as networks of problems: a review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52(1), 1-10.

Fried, E. I., Eidhof, M. B., Palic, S., Costantini, G., Huisman-van Dijk, H. M., Bockting, C. L., ... & Karstoft, K. I. (2018). Replicability and generalizability of posttraumatic stress disorder (PTSD) networks: a cross-cultural multisite study of PTSD symptoms in four trauma patient samples. Clinical Psychological Science, 6(3), 335-351.

Guloksuz, S., Pries, L. K., & van Os, J. (2017). Application of network methods for understanding mental disorders: pitfalls and promise. Psychological Medicine, 47(16), 2743-2752.

Hayes, S. C., Hofmann, S. G., Stanton, C. E., Carpenter, J. K., Sanford, B. T., Curtiss, J. E., & Ciarrochi, J. (2019). The role of the individual in the coming era of process-based therapy. Behaviour Research and Therapy, 117, 40-53.

Hayes, S. C., & Hofmann, S. G. (Eds.). (2018). Process-based CBT: The science and core clinical competencies of cognitive behavioral therapy. New Harbinger Publications.

Hektner, J. M., Schmidt, J. A., & Csikszentmihalyi, M. (2007). Experience sampling method: Measuring the quality of everyday life. Sage Publications, Inc.

Hofmann, S. G., & Curtiss, J. (2018). A complex network approach to clinical science. European Journal of Clinical Investigation, 48(8), e12986.

Hofmann, S. G., Curtiss, J., & McNally, R. J. (2016). A complex network perspective on clinical science. Perspectives on Psychological Science, 11(5), 597-605.

Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., ... & Wang, P. (2010). Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. The American Journal of Psychiatric, 167(7), 748-751.

Kuyken, W. (2006). Evidence-based case formulation: Is the emperor clothed? In N. Tarrier (Ed.), Case formulation in cognitive behavior therapy: The treatment of challenging and complex clinical cases (pp. 12–35). Brunner-Routledge.

Kuyken, W., Padesky, C. A., & Dudley, R. (2008). The science and practice of case conceptualization. Behavioural and Cognitive Psychotherapy, 36(6), 757-768.

Langer, J. K., Tonge, N. A., Piccirillo, M., Rodebaugh, T. L., Thompson, R. J., & Gotlib, I. H. (2019). Symptoms of social anxiety disorder and major depressive disorder: A network perspective. Journal of Affective Disorders, 243, 531-538.

Larson, R., & Csikszentmihalyi, M. (2014). The experience sampling method. In Flow and the foundations of positive psychology (pp. 21-34). Springer, Dordrecht.

Lutz, W., Schwartz, B., Hofmann, S. G., Fisher, A. J., Husen, K., & Rubel, J. A. (2018). Using network analysis for the prediction of treatment dropout in patients with mood and anxiety disorders: A methodological proof-of-concept study. Scientific Reports, 8(1), 7819.

Lyon, A. R., Lau, A. S., McCauley, E., Vander Stoep, A., & Chorpita, B. F. (2014). A case for modular design: Implications for implementing evidence-based interventions with culturally diverse youth. Professional Psychology: Research and Practice, 45(1), 57–66.

Martín-Brufau, R., Suso-Ribera, C., & Corbalán, J. (2020) Emotion Network Analysis During COVID-19 Quarantine ‐ A Longitudinal Study. Front. Psychol. 11, 559572.

McNally, R. J. (2016). Can network analysis transform psychopathology? Behaviour Research and Therapy, 86, 95-104.

Myin-Germeys, I., Kasanova, Z., Vaessen, T., Vachon, H., Kirtley, O., Viechtbauer, W., & Reininghaus, U. (2018). Experience sampling methodology in mental health research: new insights and technical developments. World Psychiatry, 17(2), 123-132.

Nuijten, M. B., Deserno, M. K., Cramer, A. O. J., & Borsboom, D. (2016). Mental disorders as complex networks: An introduction and overview of a network approach to psychopathology. Clinical Neuropsychiatry: Journal of Treatment Evaluation, 13(4-5), 68–76.

Organização Mundial da Saúde. (1994). CID-10: Classificação Estatística Internacional de Doenças com disquete Vol. 1. Edusp.

Richetin, J., Preti, E., Costantini, G., & De Panfilis, C. (2017). The centrality of affective instability and identity in Borderline Personality Disorder: Evidence from network analysis. PloS one, 12(10), e0186695.

Wampold, B. E., & Imel, Z. E. (2015). The great psychotherapy debate: The evidence for what makes psychotherapy work. Routledge.

Wichers, M., Wigman, J. T., Bringmann, L. F., & de Jonge, P. (2017). Mental disorders as networks: some cautionary reflections on a promising approach. Social Psychiatry and Psychiatric Epidemiology, 52(2), 143-145.

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Copyright (c) 2022 Gabriel Talask, Vinicius Lemos, Rafael da Costa, Antonio Egidio Nardi, Marcele de Carvalho