{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T00:26:23Z","timestamp":1793319983549,"version":"4.5.0"},"reference-count":49,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T00:00:00Z","timestamp":1627603200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["647209"],"award-info":[{"award-number":["647209"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Objective<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Method<\/jats:title>\n<jats:p>To investigate this implication, we combined longitudinal data on the Borderline Personality Disorder Severity Index from four samples of borderline personality disorder patients (<jats:italic>N<\/jats:italic> = 683). We related parameters from baseline partial correlation networks of symptoms to relationships between change trajectories of these symptoms.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Across multiple levels of analysis, our results showed that parameters from baseline partial correlation networks are strongly predictive of relationships between change trajectories.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0254496","type":"journal-article","created":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T17:46:04Z","timestamp":1627667164000},"page":"e0254496","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":55,"title":["The exploratory value of cross-sectional partial correlation networks: Predicting relationships between change trajectories in borderline personality disorder"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5098-0372","authenticated-orcid":true,"given":"Lino","family":"von Klipstein","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denny","family":"Borsboom","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnoud","family":"Arntz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,7,30]]},"reference":[{"issue":"1","key":"pone.0254496.ref001","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1146\/annurev-clinpsy-050212-185608","article-title":"Network Analysis: An Integrative Approach to the Structure of Psychopathology.","volume":"9","author":"D Borsboom","year":"2013","journal-title":"Annu Rev Clin Psychol"},{"issue":"2\u20133","key":"pone.0254496.ref002","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1017\/S0140525X09991567","article-title":"Comorbidity: a network perspective","volume":"33","author":"AOJ Cramer","year":"2010","journal-title":"Behav Brain Sci"},{"issue":"4","key":"pone.0254496.ref003","doi-asserted-by":"crossref","first-page":"e60188","DOI":"10.1371\/journal.pone.0060188","article-title":"A network approach to psychopathology: new insights into clinical longitudinal data","volume":"8","author":"LF Bringmann","year":"2013","journal-title":"PLoS One"},{"issue":"54","key":"pone.0254496.ref004","first-page":"13","article-title":"State of the aRt personality research: A tutorial on network analysis of personality data in R","author":"G Costantini","year":"2014","journal-title":"J Res Pers"},{"key":"pone.0254496.ref005","doi-asserted-by":"crossref","first-page":"5918","DOI":"10.1038\/srep05918","article-title":"A new method for constructing networks from binary data.","volume":"4","author":"CD van Borkulo","year":"2014","journal-title":"Sci Rep"},{"key":"pone.0254496.ref006","volume-title":"The Wiley Handbook of Psychometric Testing: A Multidisciplinary Reference on Survey, Scale and Test Development","author":"S Epskamp","year":"2018"},{"issue":"4","key":"pone.0254496.ref007","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1037\/met0000167","article-title":"A tutorial on regularized partial correlation networks.","volume":"23","author":"S Epskamp","year":"2018","journal-title":"Psychol Methods"},{"key":"pone.0254496.ref008","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.jad.2015.09.005","article-title":"What are \u2019good\u2019 depression symptoms? 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