Network analysis: An overview for mental health research

被引：18

作者：

Briganti, Giovanni ^{[1
]}

Scutari, Marco ^{[2
]}

Epskamp, Sacha ^{[3
]}

Borsboom, Denny ^{[4
]}

Hoekstra, Ria H. A. ^{[4
]}

Golino, Hudson Fernandes ^{[5
]}

Christensen, Alexander P. ^{[6
]}

Morvan, Yannick ^{[7
]}

Ebrahimi, Omid V. ^{[8
]}

Costantini, Giulio ^{[9
]}

Heeren, Alexandre ^{[10
]}

Ron, Jill de ^{[4
]}

Bringmann, Laura F. ^{[11
]}

Huth, Karoline ^{[4
]}

Haslbeck, Jonas M. B. ^{[12
]}

Isvoranu, Adela-Maria ^{[3
]}

Marsman, Maarten ^{[4
]}

Blanken, Tessa ^{[4
]}

Gilbert, Allison ^{[1
]}

Henry, Teague Rhine ^{[5
]}

Fried, Eiko I. ^{[13
]}

Mcnally, Richard J. ^{[14
]}

机构：

[1] Univ Mons, Mons, Belgium

[2] Ist Dalle Molle SullIntelligenza Artificiale, Lugano, Switzerland

[3] Natl Univ Singapore, Singapore, Singapore

[4] Univ Amsterdam, Amsterdam, Netherlands

[5] Univ Virginia, Charlottesville, VA USA

[6] Vanderbilt Univ, Nashville, TN USA

[7] Univ Paris Nanterre, Nanterre, France

[8] Univ Oxford, Oxford, England

[9] Univ Milano Bicocca, Milan, Italy

[10] Catholic Univ Louvain, Louvain La Neuve, Belgium

[11] Univ Groningen, Groningen, Netherlands

[12] Univ Maastricht, Maastricht, Netherlands

[13] Leiden Univ, Leiden, Netherlands

[14] Harvard Univ, Cambridge, MA USA

来源：

INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH | 2024年 / 33卷 / 04期

基金：

荷兰研究理事会;

关键词：

network analysis; network modeling; network psychometrics; network psychopathology; CRITICAL SLOWING-DOWN; EMOTION DYNAMICS; MODELS; PERSONALITY; DEPRESSION; CAUSALITY; FUTURE;

D O I：

10.1002/mpr.2034

中图分类号：

R749 [精神病学];

学科分类号：

100205 ;

摘要：

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 networks, 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.

引用

页数：24

共 174 条

[41] State of the aRt personality research: A tutorial on network analysis of personality data in R [J].