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On the Control of Psychological Networks

Published online by Cambridge University Press:  01 January 2025

Teague R. Henry Open the ORCID record for Teague R. Henry [Opens in a new window] ,
Donald J. Robinaugh  and
Eiko I. Fried
Teague R. Henry*
Affiliation:
University of Virginia University of Pittsburgh
Donald J. Robinaugh
Affiliation:
Harvard Medical School & Massachusetts General Hospital
Eiko I. Fried
Affiliation:
Leiden University
*
Correspondence should be made to Teague R. Henry, Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA. Email: trhenry@virginia.edu
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Abstract

The combination of network theory and network psychometric methods has opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, simply estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, nor is it sufficient for determining the potential efficacy of any given intervention. In this paper, we attempt to remedy this gap by introducing fundamental concepts of control theory to both psychometricians and applied psychologists. We introduce two controllability statistics to the psychometric literature, average and modal controllability, to facilitate selecting the best set of intervention targets. Following this introduction, we show how intervention scientists can probe the effects of both theoretical and empirical interventions on networks derived from real data and demonstrate how simulations can account for intervention cost and the desire to reduce specific symptoms. Every step is based on rich clinical EMA data from a sample of subjects undergoing treatment for complicated grief, with a focus on the outcome suicidal ideation. All methods are implemented in an open-source R package netcontrol, and complete code for replicating the analyses in this manuscript are available online.

Keywords

control theorynetwork psychometricscomplicated griefpersonalized medicineintervention sciencepsychopathology
Type
Application Reviews and Case Studies
Information
Psychometrika , Volume 87 , Issue 1: Special Issue on Network Psychometrics in Action , March 2022 , pp. 188 - 213
Copyright
Copyright © 2021 The Psychometric Society

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Footnotes

This project was supported by the American Foundation for Suicide Prevention, the Charles A. King Trust Postdoctoral Research Fellowship Program, Bank of America, N.A., Co-Trustees, and a National Institute of Mental Health Career Development Award (1K23MH113805-01A1) awarded to D. Robinaugh. The content is solely the responsibility of the authors and does not necessarily represent the views of these organizations. Correspondence should be directed to Teague R. Henry at trhenry@virginia.edu

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