The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Identifying highly influential nodes in the complicated grief network.
Open accessAbstract
The network approach to psychopathology conceptualizes mental disorders as networks of mutually reinforcing nodes (i.e., symptoms). Researchers adopting this approach have suggested that network topology can be used to identify influential nodes, with nodes central to the network having the greatest influence on the development and maintenance of the disorder. However, because commonly used centrality indices do not distinguish between positive and negative edges, they may not adequately assess the nature and strength of a node's influence within the network. To address this limitation, we developed 2 indices of a node's expected influence (EI) that account for the presence of negative edges. To evaluate centrality and EI indices, we simulated single-node interventions on randomly generated networks. In networks with exclusively positive edges, centrality and EI were both strongly associated with observed node influence. In networks with negative edges, EI was more strongly associated with observed influence than was centrality. We then used data from a longitudinal study of bereavement to examine the association between (a) a node's centrality and EI in the complicated grief (CG) network and (b) the strength of association between change in that node and change in the remainder of the CG network from 6- to 18-months postloss. Centrality and EI were both correlated with the strength of the association between node change and network change. Together, these findings suggest high-EI nodes, such as emotional pain and feelings of emptiness, may be especially important to the etiology and treatment of CG. (PsycINFO Database Record
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Cites
Centrality in social networks conceptual clarification
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“Notably, the relevance of a centrality metric can vary as a function of the substantive phenomenon represented by the network (Freeman, 1978).”
Network analysis: An integrative approach to the structure of psychopathology
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THE DUAL PROCESS MODEL OF COPING WITH BEREAVEMENT: RATIONALE AND DESCRIPTION
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“In regard to the latter, this strong association is consistent with the emphasis placed on restoration of meaning in theories of natural grief resolution (Stroebe & Schut, 1999) and in prominent psychotherapies for CG (e.g., Neimeyer, 2000; Shear et al., 2005).”
Prolonged grief disorder: psychometric validation of criteria proposed for DSM-V and ICD-11
Prigerson, H. G., Horowitz, M. J., Jacobs, S. C., Parkes, C. M., Aslan, M., Goodkin, K., Raphael, B., Marwit, S. J., Wortman, C., Neimeyer, R. A., et al. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000121 · Cited by 1,863
Comorbidity: a network perspective
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Treatment of Complicated Grief: A Randomized Controlled Trial
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Mental Disorders as Causal Systems: A Network Approach to Posttraumatic Stress Disorder
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Self-citationSearching for the meaning of meaning: Grief therapy and the process of reconstruction
Neimeyer, R. A. (2000) · Death Studies · doi:10.1080/07481180050121480 · Cited by 591 · cited 1×
“In regard to the latter, this strong association is consistent with the emphasis placed on restoration of meaning in theories of natural grief resolution (Stroebe & Schut, 1999) and in prominent psychotherapies for CG (e.g., Neimeyer, 2000; Shear et al., 2005).”
An attachment-based model of complicated grief including the role of avoidance
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Treating Prolonged Grief Disorder: A Randomized Clinical Trial
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Cited by
Bridge Centrality: A Network Approach to Understanding Comorbidity
Jones, P. J., Ma, R., & McNally, R. J. (2021) · Multivariate Behavioral Research · doi:10.1080/00273171.2019.1614898 · Cited by 1,741
Self-citationNetwork analysis of multivariate data in psychological science
Borsboom, D., Deserno, M. K., Rhemtulla, M., Epskamp, S., Fried, E. I., McNally, R. J., Robinaugh, D. J., Perugini, M., Dalege, J., Costantini, G., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00055-w · Cited by 1,371
Self-citationCan network analysis transform psychopathology?
McNally, R. J. (2016) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.06.006 · Cited by 1,072
Network analysis of depression and anxiety symptom relationships in a psychiatric sample
Beard, C., Millner, A. J., Forgeard, M. J. C., Fried, E. I., Hsu, K. J., Treadway, M. T., Leonard, C. V., Kertz, S. J., & Björgvinsson, T. (2016) · Psychological Medicine · doi:10.1017/s0033291716002300 · Cited by 929
Self-citationRobinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2020) · Psychological Medicine · doi:10.1017/s0033291719003404 · Cited by 861
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Metadata
- Authors
- Robinaugh, D. J., Millner, A. J., & McNally, R. J.
- Venue
- Journal of Abnormal Psychology
- Published
- 2016-08
- Volume
- 125
- Issue
- 6
- Pages
- 747-757
- ISSN
- 0021-843X (ISSN-L)
- 1939-1846
- OpenAlex
- W2429047191
- Cited by
- 1,787
- References
- 12
- FWCI
- 39.86
- Type
- journal article
- Language
- en
- Open access
- green
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