UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The network structure of paranoia in the general population

Bell, V; O'Driscoll, C; (2018) The network structure of paranoia in the general population. Social Psychiatry and Psychiatric Epidemiology , 53 (7) pp. 737-744. 10.1007/s00127-018-1487-0. Green open access

[img]
Preview
Text
Bell VoR Bell-ODriscoll2018_Article_TheNetworkStructureOfParanoiaI.pdf - Published version

Download (1MB) | Preview
[img]
Preview
Text (Supplementary data)
Bell_Network_structure_paranoia_Suppl.pdf

Download (428kB) | Preview

Abstract

PURPOSE: Bebbington and colleagues' influential study on 'the structure of paranoia in the general population' used data from the British National Psychiatric Morbidity Survey and latent variable analysis methods. Network analysis is a relatively new approach in psychopathology research that considers mental disorders to be emergent phenomena from causal interactions among symptoms. This study re-analysed the British National Psychiatric Morbidity Survey data using network analysis to examine the network structure of paranoia in the general population. METHODS: We used a Graphical Least Absolute Shrinkage and Selection Operator (glasso) method that estimated an optimal network structure based on the Extended Bayesian Information Criterion. Network sub-communities were identified by spinglass and EGA algorithms and centrality metrics were calculated per item and per sub-community. RESULTS: We replicated Bebbington's four component structure of paranoia, identifying 'interpersonal sensitivities', 'mistrust', 'ideas of reference' and 'ideas of persecution' as sub-communities in the network. In line with previous experimental findings, worry was the most central item in the network. However, 'mistrust' and 'ideas of reference' were the most central sub-communities. CONCLUSIONS: Rather than a strict hierarchy, we argue that the structure of paranoia is best thought of as a heterarchy, where the activation of high-centrality nodes and communities is most likely to lead to steady state paranoia. We also highlight the novel methodological approach used by this study: namely, using network analysis to re-examine a population structure of psychopathology previously identified by latent variable approaches.

Type: Article
Title: The network structure of paranoia in the general population
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s00127-018-1487-0
Publisher version: https://doi.org/10.1007/s00127-018-1487-0
Language: English
Additional information: Copyright © The Author(s) 2018. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Delusion, Epidemiology, Network, Psychosis, Schizophrenia
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10044034
Downloads since deposit
108Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item