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A Network Analysis of the Association Between Depressive Symptoms and Patient Activation Among Those With Elevated Cardiovascular Risk

Background Network analysis provides a new method for conceptualizing interconnections among psychological and behavioral constructs. Objective We used network analysis to investigate the complex associations between depressive symptoms and patient activation dimensions among patients at elevated ri...

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Published in:Global advances in health and medicine 2022, Vol.11, p.2164957X221086257
Main Authors: Lee, Chiyoung, Wolever, Ruth Q., Yang, Qing, Vorderstrasse, Allison, Min, Se Hee, Hu, Xiao
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Wolever, Ruth Q.
Yang, Qing
Vorderstrasse, Allison
Min, Se Hee
Hu, Xiao
description Background Network analysis provides a new method for conceptualizing interconnections among psychological and behavioral constructs. Objective We used network analysis to investigate the complex associations between depressive symptoms and patient activation dimensions among patients at elevated risk of cardiovascular disease. Methods This secondary analysis included 200 patients seen in primary care clinics. Depressive symptoms were assessed using the 21-item Beck Depression Inventory. Patient activation was measured using the 13-item Patient Activation Measure. Glasso networks were constructed to identify symptoms/traits that bridge depressive symptoms and patient activation and those that are central within the network. Results “Self-dislike” and “confidence to maintain lifestyle changes during times of stress” were identified as important bridge pathways. In addition, depressive symptoms such as “punishment feelings,” “loss of satisfaction,” “self-dislike,” and “loss of interest in people” were central in the depressive symptom–patient activation network, meaning that they were most strongly connected to all other symptoms. Conclusions Bridge pathways identified in the network may be reasonable targets for clinical intervention aimed at disrupting the association between depressive symptoms and patient activation. Further research is warranted to assess whether targeting interventions to these central symptoms may help resolve other symptoms within the network.
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Objective We used network analysis to investigate the complex associations between depressive symptoms and patient activation dimensions among patients at elevated risk of cardiovascular disease. Methods This secondary analysis included 200 patients seen in primary care clinics. Depressive symptoms were assessed using the 21-item Beck Depression Inventory. Patient activation was measured using the 13-item Patient Activation Measure. Glasso networks were constructed to identify symptoms/traits that bridge depressive symptoms and patient activation and those that are central within the network. Results “Self-dislike” and “confidence to maintain lifestyle changes during times of stress” were identified as important bridge pathways. In addition, depressive symptoms such as “punishment feelings,” “loss of satisfaction,” “self-dislike,” and “loss of interest in people” were central in the depressive symptom–patient activation network, meaning that they were most strongly connected to all other symptoms. Conclusions Bridge pathways identified in the network may be reasonable targets for clinical intervention aimed at disrupting the association between depressive symptoms and patient activation. Further research is warranted to assess whether targeting interventions to these central symptoms may help resolve other symptoms within the network.</description><identifier>ISSN: 2164-957X</identifier><identifier>EISSN: 2164-9561</identifier><identifier>DOI: 10.1177/2164957X221086257</identifier><identifier>PMID: 35399615</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Cardiovascular disease ; Health risks ; Mental depression ; Original ; Primary care</subject><ispartof>Global advances in health and medicine, 2022, Vol.11, p.2164957X221086257</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022.</rights><rights>The Author(s) 2022. This work is licensed under the Creative Commons Attribution – Non-Commercial License https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2022 2022 Academic Consortium for Integrative Medicine &amp; Health, unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3997-6f4f0f9eff2c3a68f8936c11465b33943d795113ac70da7ece2688ac28703f0d3</cites><orcidid>0000-0003-2899-218X ; 0000-0001-6860-452X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988674/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2758570965?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4024,21966,25753,27853,27923,27924,27925,37012,37013,44590,44945,45333,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35399615$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Chiyoung</creatorcontrib><creatorcontrib>Wolever, Ruth Q.</creatorcontrib><creatorcontrib>Yang, Qing</creatorcontrib><creatorcontrib>Vorderstrasse, Allison</creatorcontrib><creatorcontrib>Min, Se Hee</creatorcontrib><creatorcontrib>Hu, Xiao</creatorcontrib><title>A Network Analysis of the Association Between Depressive Symptoms and Patient Activation Among Those With Elevated Cardiovascular Risk</title><title>Global advances in health and medicine</title><addtitle>Glob Adv Health Med</addtitle><description>Background Network analysis provides a new method for conceptualizing interconnections among psychological and behavioral constructs. Objective We used network analysis to investigate the complex associations between depressive symptoms and patient activation dimensions among patients at elevated risk of cardiovascular disease. Methods This secondary analysis included 200 patients seen in primary care clinics. Depressive symptoms were assessed using the 21-item Beck Depression Inventory. Patient activation was measured using the 13-item Patient Activation Measure. Glasso networks were constructed to identify symptoms/traits that bridge depressive symptoms and patient activation and those that are central within the network. Results “Self-dislike” and “confidence to maintain lifestyle changes during times of stress” were identified as important bridge pathways. In addition, depressive symptoms such as “punishment feelings,” “loss of satisfaction,” “self-dislike,” and “loss of interest in people” were central in the depressive symptom–patient activation network, meaning that they were most strongly connected to all other symptoms. Conclusions Bridge pathways identified in the network may be reasonable targets for clinical intervention aimed at disrupting the association between depressive symptoms and patient activation. 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subjects Cardiovascular disease
Health risks
Mental depression
Original
Primary care
title A Network Analysis of the Association Between Depressive Symptoms and Patient Activation Among Those With Elevated Cardiovascular Risk
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