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Review
. 2021 Feb 27;21(1):119.
doi: 10.1186/s12888-021-03128-y.

Extended network analysis: from psychopathology to chronic illness

Adela-Maria Isvoranu  1 , Edimansyah Abdin  2 , Siow Ann Chong  2 , Janhavi Vaingankar  2 , Denny Borsboom  3 , Mythily Subramaniam  2
Affiliations
Review

Extended network analysis: from psychopathology to chronic illness

Adela-Maria Isvoranu et al. BMC Psychiatry. .

Abstract

Background: Understanding complex associations between psychopathology and chronic illness is instrumental in facilitating both research and treatment progress. The current study is the first and only network-based study to provide such an encompassing view of unique associations between a multitude of mental and physical health-related domains.

Methods: The current analyses were based on the Singapore Mental Health Study, a cross-sectional study of adult Singapore residents. The study sample consisted of 6616 respondents, of which 49.8% were male and 50.2% female. A network structure was constructed to examine associations between psychopathology, alcohol use, gambling, major chronic conditions, and functioning.

Results: The network structure identified what we have labeled a Cartesian graph: a network visibly split into a psychopathological domain and a physical health domain. The borders between these domains were fuzzy and bridged by various cross-domain associations, with functioning items playing an important role in bridging chronic conditions to psychopathology.

Conclusions: Current results deliver a comprehensive overview of the complex relation between psychopathology, functioning, and chronic illness, highlighting potential pathways to comorbidity.

Keywords: Chronic illness; Functioning; Mental health; Network analysis; Network psychometrics; Physical health; Psychopathology.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Network structure depicting the different domains of psychopathology, functioning, and chronic conditions, differentiated by colors. Blue edges indicate positive associations, red edges indicate negative associations, and the thickness of an edge represents the strength of the association
Fig. 2
Fig. 2
Centrality plot depicting the strength of each node in the network structure, ordered from the node with the highest strength to the node with the lowest strength in the network. Node strength quantifies how strongly a node is directly connected to other nodes in the network (i.e., by summing all absolute edge weights of edges connected to the given node). All values are standardized and higher values indicate greater centrality in the network
See this image and copyright information in PMC

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