The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.

<h4>Objective</h4>Within the network approach to psychopathology, cross-sectional partial correlation networks have frequently been used to estimate relationships between symptoms. The resulting relationships have been used to generate hypotheses about causal links between symptoms. In o...

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Autores principales:	Lino von Klipstein, Denny Borsboom, Arnoud Arntz
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/39211d2d043f42bba1613697736f7e66
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spelling	oai:doaj.org-article:39211d2d043f42bba1613697736f7e662021-12-02T20:08:51ZThe exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.1932-620310.1371/journal.pone.0254496https://doaj.org/article/39211d2d043f42bba1613697736f7e662021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254496https://doaj.org/toc/1932-6203<h4>Objective</h4>Within the network approach to psychopathology, cross-sectional partial correlation networks have frequently been used to estimate relationships between symptoms. The resulting relationships have been used to generate hypotheses about causal links between symptoms. In order to justify such exploratory use of partial correlation networks, one needs to assume that the between-subjects relationships in the network approximate systematic within-subjects relationships, which are in turn the results of some within-subjects causal mechanism. If this assumption holds, relationships in the network should be mirrored by relationships between symptom changes; if links in networks approximate systematic within-subject relationships, change in a symptom should relate to change in connected symptoms.<h4>Method</h4>To investigate this implication, we combined longitudinal data on the Borderline Personality Disorder Severity Index from four samples of borderline personality disorder patients (N = 683). We related parameters from baseline partial correlation networks of symptoms to relationships between change trajectories of these symptoms.<h4>Results</h4>Across multiple levels of analysis, our results showed that parameters from baseline partial correlation networks are strongly predictive of relationships between change trajectories.<h4>Conclusions</h4>By confirming its implication, our results support the idea that cross-sectional partial correlation networks hold a relevant amount of information about systematic within-subjects relationships and thereby have exploratory value to generate hypotheses about the causal dynamics between symptoms.Lino von KlipsteinDenny BorsboomArnoud ArntzPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254496 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lino von Klipstein Denny Borsboom Arnoud Arntz The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
description	<h4>Objective</h4>Within the network approach to psychopathology, cross-sectional partial correlation networks have frequently been used to estimate relationships between symptoms. The resulting relationships have been used to generate hypotheses about causal links between symptoms. In order to justify such exploratory use of partial correlation networks, one needs to assume that the between-subjects relationships in the network approximate systematic within-subjects relationships, which are in turn the results of some within-subjects causal mechanism. If this assumption holds, relationships in the network should be mirrored by relationships between symptom changes; if links in networks approximate systematic within-subject relationships, change in a symptom should relate to change in connected symptoms.<h4>Method</h4>To investigate this implication, we combined longitudinal data on the Borderline Personality Disorder Severity Index from four samples of borderline personality disorder patients (N = 683). We related parameters from baseline partial correlation networks of symptoms to relationships between change trajectories of these symptoms.<h4>Results</h4>Across multiple levels of analysis, our results showed that parameters from baseline partial correlation networks are strongly predictive of relationships between change trajectories.<h4>Conclusions</h4>By confirming its implication, our results support the idea that cross-sectional partial correlation networks hold a relevant amount of information about systematic within-subjects relationships and thereby have exploratory value to generate hypotheses about the causal dynamics between symptoms.
format	article
author	Lino von Klipstein Denny Borsboom Arnoud Arntz
author_facet	Lino von Klipstein Denny Borsboom Arnoud Arntz
author_sort	Lino von Klipstein
title	The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
title_short	The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
title_full	The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
title_fullStr	The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
title_full_unstemmed	The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.
title_sort	exploratory value of cross-sectional partial correlation networks: predicting relationships between change trajectories in borderline personality disorder.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/39211d2d043f42bba1613697736f7e66
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The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder.

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