Zavlis, Orestis;
Story, Giles;
Friedrich, Claire;
Fonagy, Peter;
Moutoussis, Michael;
(2025)
A systematic review of computational modeling of interpersonal dynamics in psychopathology.
Nature Mental Health
10.1038/s44220-025-00465-9.
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Abstract
Interpersonal dynamics have long been acknowledged as critical for the development and treatment of mental health problems. While recent computational approaches have been argued to be uniquely suited for investigating such dynamics, no systematic assessment has been made to scrutinize this claim. Here we conduct a systematic review to assess the utility of computational modeling in the field of interpersonal psychopathology. Candidate studies (k = 4,208), including preprints and conference manuscripts, were derived from five databases (MEDLINE, Embase, PsycINFO, Web of Science and Google Scholar) up to May 2025. A total of 58 studies met inclusion criteria and were assessed in terms of the validity, performance and transparency of their computational modeling. Bayesian modeling was the most common approach (k = 18), followed by machine learning (k = 17), dynamical systems modeling (k = 13) and reinforcement learning (k = 10). These approaches revealed several interpersonal disruptions across various mental health conditions, including rigid social learning in mood conditions, hypo- versus hyper-mentalizing in autism versus psychotic conditions and polarized relational dynamics in personality conditions. Despite these insights, critical challenges persist, with few studies reporting comprehensive performance metrics (16%) or adopting open science practices (20%). We discuss these challenges and conclude with more optimistic messages by suggesting that when rigorously and transparently conducted, computational approaches have the potential to advance our understanding of psychopathology by highlighting the social underpinnings of both mental health and disorder.
| Type: | Article |
|---|---|
| Title: | A systematic review of computational modeling of interpersonal dynamics in psychopathology |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s44220-025-00465-9 |
| Publisher version: | https://doi.org/10.1038/s44220-025-00465-9 |
| Language: | English |
| Additional information: | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Psychology, Public health |
| UCL classification: | UCL 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 > UCL Queen Square Institute of Neurology 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 UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211703 |
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