SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Moffa G, Catone G, Kuipers J, Kuipers E, Freeman D, Marwaha S, Lennox BR, Broome MR, Bebbington P. Schizophr. Bull. 2017; 43(6): 1273-1279.

Affiliation

Division of Psychiatry, University College London, London, UK.

Copyright

(Copyright © 2017, Maryland Psychiatric Research Center, Publisher Oxford University Press)

DOI

10.1093/schbul/sbx013

PMID

28521005

Abstract

Modern psychiatric epidemiology researches complex interactions between multiple variables in large datasets. This creates difficulties for causal inference. We argue for the use of probabilistic models represented by directed acyclic graphs (DAGs). These capture the dependence structure of multiple variables and, used appropriately, allow more robust conclusions about the direction of causation. We analyzed British national survey data to assess putative mediators of the association between bullying victimization and persecutory ideation. We compared results using DAGs and the Karlson-Holm-Breen (KHB) logistic regression commands in STATA. We analyzed data from the 2007 English National Survey of Psychiatric Morbidity, using the equivalent 2000 survey in an instant replication. Additional details of methods and results are provided in the supplementary material. DAG analysis revealed a richer structure of relationships than could be inferred using the KHB logistic regression commands. Thus, bullying had direct effects on worry, persecutory ideation, mood instability, and drug use. Depression, sleep and anxiety lay downstream, and therefore did not mediate the link between bullying and persecutory ideation. Mediation by worry and mood instability could not be definitively ascertained. Bullying led to hallucinations indirectly, via persecutory ideation and depression. DAG analysis of the 2000 dataset suggested the technique generates stable results. While causality cannot be fully determined from cross-sectional data, DAGs indicate the relationships providing the best fit. They thereby advance investigation of the complex interactions seen in psychiatry, including the mechanisms underpinning psychiatric symptoms. It may consequently be used to optimize the choice of intervention targets.

© The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.


Language: en

Keywords

anxiety; bullying; depression; directed acyclic graphs; mediation; persecutory ideation; probabilistic graphical models; psychosis; worry

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print