Loading…
Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis
•The interdependences of depressive symptoms, disability, social support, and mental and physical health-related quality of life after stroke are high but knowledge about multivariate associations is scarce.•Network analysis revealed depressive symptoms, social support and mental health-related qual...
Saved in:
Published in: | Journal of affective disorders reports 2025-01, Vol.19, p.100855, Article 100855 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | cdi_FETCH-LOGICAL-c1625-a39698441a327578bc616dfba5f985e94c26935414d6cc847ab554f57c325e393 |
container_end_page | |
container_issue | |
container_start_page | 100855 |
container_title | Journal of affective disorders reports |
container_volume | 19 |
creator | Ladwig, Simon Volz, Matthias Haupt, Julia Pedersen, Anya Werheid, Katja |
description | •The interdependences of depressive symptoms, disability, social support, and mental and physical health-related quality of life after stroke are high but knowledge about multivariate associations is scarce.•Network analysis revealed depressive symptoms, social support and mental health-related quality of life as the most central variables.•The results underline the relevance of mental aspects over physical stroke sequalae for quality of life.•Interventions targeting depressive symptoms and social support may efficiently mitigate the burden on quality of life after stroke.
Health-related quality of life (HRQOL), depressive symptoms, disability, and social support show complex interdependences after stroke, which cannot be sufficiently depicted by commonly used uni- or bivariate analyses. Applying a network analysis, we aim to disentangle these multivariate relationships and deduce meaningful starting points for interventions.
Stroke survivors (N = 202) were recruited from two inpatient rehabilitation clinics. Participants self-reported mental and physical HRQOL, depressive symptoms, disability, and social support. We computed a partial correlation network and included these five variables as separate nodes. We estimated edge weights, node centrality (expected influence), node predictability, and clusters. Bootstrap methods were applied to assess network stability.
Depressive symptoms and mental HRQOL were the most central and interconnected nodes in the network. Depressive symptoms built its own cluster. Social support showed a high association with depressive symptoms. Disability had no significant associations with other nodes in the network. Physical HRQOL was significantly connected only to its mental equivalent.
The cross-sectional design limits the findings to the setting of inpatient rehabilitation few weeks after stroke and allows no longitudinal inferences. The relatively small sample size and varying metrics of applied measures are counterbalanced by a high stability of estimations.
Depression and social support show stronger associations with HRQOL than physical aspects during stroke inpatient rehabilitation. This underscores the significance of mental aspects shortly after stroke. Development and implementation of early interventions targeting depressive symptoms and social support may sustainably mitigate the burden on HRQOL after stroke. |
doi_str_mv | 10.1016/j.jadr.2024.100855 |
format | article |
fullrecord | <record><control><sourceid>elsevier_doaj_</sourceid><recordid>TN_cdi_crossref_primary_10_1016_j_jadr_2024_100855</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2666915324001410</els_id><doaj_id>oai_doaj_org_article_b3c359c78113421b8eb4409dafe3754b</doaj_id><sourcerecordid>S2666915324001410</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1625-a39698441a327578bc616dfba5f985e94c26935414d6cc847ab554f57c325e393</originalsourceid><addsrcrecordid>eNp9kU1u1EAQhS0EElHIBVj1AfDg_rUbsYnCX6RIbGDdKneXZ9rxuE1XJ2gukvPimUEoK1ZVelXvU5VeVb3lzYY33LwfNyOEvBGNUKvQdFq_qC6EMaa2XMuXz_rX1RXR2DSN0FzyTl9UT58i4Vxg3k5x3rKyQ5ZxghLTTLu4EEsD2yFMZVefdAzs1wNMsRyOkykO-I4FXDISxUdkdNgvJe1pFSNBH0-LMAdGyUeYGD0sS8qFwVAwMyo53eMHds1mLL9Tvl9XYTpQpDfVqwEmwqu_9bL6-eXzj5tv9d33r7c313e150boGqQ1tlOKgxStbrveG27C0IMebKfRKi-MlVpxFYz3nWqh11oNuvVSaJRWXla3Z25IMLolxz3kg0sQ3UlIeesgl-gndL30UlvfdpxLJXjfYa9UYwMMKFut-pUlziyfE1HG4R-PN-4YlBvdMSh3DMqdg1pNH88mXL98jJgd-YizxxAz-rKeEf9n_wNwRJ5J</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis</title><source>ScienceDirect</source><creator>Ladwig, Simon ; Volz, Matthias ; Haupt, Julia ; Pedersen, Anya ; Werheid, Katja</creator><creatorcontrib>Ladwig, Simon ; Volz, Matthias ; Haupt, Julia ; Pedersen, Anya ; Werheid, Katja</creatorcontrib><description>•The interdependences of depressive symptoms, disability, social support, and mental and physical health-related quality of life after stroke are high but knowledge about multivariate associations is scarce.•Network analysis revealed depressive symptoms, social support and mental health-related quality of life as the most central variables.•The results underline the relevance of mental aspects over physical stroke sequalae for quality of life.•Interventions targeting depressive symptoms and social support may efficiently mitigate the burden on quality of life after stroke.
Health-related quality of life (HRQOL), depressive symptoms, disability, and social support show complex interdependences after stroke, which cannot be sufficiently depicted by commonly used uni- or bivariate analyses. Applying a network analysis, we aim to disentangle these multivariate relationships and deduce meaningful starting points for interventions.
Stroke survivors (N = 202) were recruited from two inpatient rehabilitation clinics. Participants self-reported mental and physical HRQOL, depressive symptoms, disability, and social support. We computed a partial correlation network and included these five variables as separate nodes. We estimated edge weights, node centrality (expected influence), node predictability, and clusters. Bootstrap methods were applied to assess network stability.
Depressive symptoms and mental HRQOL were the most central and interconnected nodes in the network. Depressive symptoms built its own cluster. Social support showed a high association with depressive symptoms. Disability had no significant associations with other nodes in the network. Physical HRQOL was significantly connected only to its mental equivalent.
The cross-sectional design limits the findings to the setting of inpatient rehabilitation few weeks after stroke and allows no longitudinal inferences. The relatively small sample size and varying metrics of applied measures are counterbalanced by a high stability of estimations.
Depression and social support show stronger associations with HRQOL than physical aspects during stroke inpatient rehabilitation. This underscores the significance of mental aspects shortly after stroke. Development and implementation of early interventions targeting depressive symptoms and social support may sustainably mitigate the burden on HRQOL after stroke.</description><identifier>ISSN: 2666-9153</identifier><identifier>EISSN: 2666-9153</identifier><identifier>DOI: 10.1016/j.jadr.2024.100855</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Depression ; Health-related quality of life ; Network analysis ; Psychological risk factors ; Stroke</subject><ispartof>Journal of affective disorders reports, 2025-01, Vol.19, p.100855, Article 100855</ispartof><rights>2024 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1625-a39698441a327578bc616dfba5f985e94c26935414d6cc847ab554f57c325e393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S2666915324001410$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3549,27924,27925,45780</link.rule.ids></links><search><creatorcontrib>Ladwig, Simon</creatorcontrib><creatorcontrib>Volz, Matthias</creatorcontrib><creatorcontrib>Haupt, Julia</creatorcontrib><creatorcontrib>Pedersen, Anya</creatorcontrib><creatorcontrib>Werheid, Katja</creatorcontrib><title>Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis</title><title>Journal of affective disorders reports</title><description>•The interdependences of depressive symptoms, disability, social support, and mental and physical health-related quality of life after stroke are high but knowledge about multivariate associations is scarce.•Network analysis revealed depressive symptoms, social support and mental health-related quality of life as the most central variables.•The results underline the relevance of mental aspects over physical stroke sequalae for quality of life.•Interventions targeting depressive symptoms and social support may efficiently mitigate the burden on quality of life after stroke.
Health-related quality of life (HRQOL), depressive symptoms, disability, and social support show complex interdependences after stroke, which cannot be sufficiently depicted by commonly used uni- or bivariate analyses. Applying a network analysis, we aim to disentangle these multivariate relationships and deduce meaningful starting points for interventions.
Stroke survivors (N = 202) were recruited from two inpatient rehabilitation clinics. Participants self-reported mental and physical HRQOL, depressive symptoms, disability, and social support. We computed a partial correlation network and included these five variables as separate nodes. We estimated edge weights, node centrality (expected influence), node predictability, and clusters. Bootstrap methods were applied to assess network stability.
Depressive symptoms and mental HRQOL were the most central and interconnected nodes in the network. Depressive symptoms built its own cluster. Social support showed a high association with depressive symptoms. Disability had no significant associations with other nodes in the network. Physical HRQOL was significantly connected only to its mental equivalent.
The cross-sectional design limits the findings to the setting of inpatient rehabilitation few weeks after stroke and allows no longitudinal inferences. The relatively small sample size and varying metrics of applied measures are counterbalanced by a high stability of estimations.
Depression and social support show stronger associations with HRQOL than physical aspects during stroke inpatient rehabilitation. This underscores the significance of mental aspects shortly after stroke. Development and implementation of early interventions targeting depressive symptoms and social support may sustainably mitigate the burden on HRQOL after stroke.</description><subject>Depression</subject><subject>Health-related quality of life</subject><subject>Network analysis</subject><subject>Psychological risk factors</subject><subject>Stroke</subject><issn>2666-9153</issn><issn>2666-9153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kU1u1EAQhS0EElHIBVj1AfDg_rUbsYnCX6RIbGDdKneXZ9rxuE1XJ2gukvPimUEoK1ZVelXvU5VeVb3lzYY33LwfNyOEvBGNUKvQdFq_qC6EMaa2XMuXz_rX1RXR2DSN0FzyTl9UT58i4Vxg3k5x3rKyQ5ZxghLTTLu4EEsD2yFMZVefdAzs1wNMsRyOkykO-I4FXDISxUdkdNgvJe1pFSNBH0-LMAdGyUeYGD0sS8qFwVAwMyo53eMHds1mLL9Tvl9XYTpQpDfVqwEmwqu_9bL6-eXzj5tv9d33r7c313e150boGqQ1tlOKgxStbrveG27C0IMebKfRKi-MlVpxFYz3nWqh11oNuvVSaJRWXla3Z25IMLolxz3kg0sQ3UlIeesgl-gndL30UlvfdpxLJXjfYa9UYwMMKFut-pUlziyfE1HG4R-PN-4YlBvdMSh3DMqdg1pNH88mXL98jJgd-YizxxAz-rKeEf9n_wNwRJ5J</recordid><startdate>202501</startdate><enddate>202501</enddate><creator>Ladwig, Simon</creator><creator>Volz, Matthias</creator><creator>Haupt, Julia</creator><creator>Pedersen, Anya</creator><creator>Werheid, Katja</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>202501</creationdate><title>Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis</title><author>Ladwig, Simon ; Volz, Matthias ; Haupt, Julia ; Pedersen, Anya ; Werheid, Katja</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1625-a39698441a327578bc616dfba5f985e94c26935414d6cc847ab554f57c325e393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Depression</topic><topic>Health-related quality of life</topic><topic>Network analysis</topic><topic>Psychological risk factors</topic><topic>Stroke</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ladwig, Simon</creatorcontrib><creatorcontrib>Volz, Matthias</creatorcontrib><creatorcontrib>Haupt, Julia</creatorcontrib><creatorcontrib>Pedersen, Anya</creatorcontrib><creatorcontrib>Werheid, Katja</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of affective disorders reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ladwig, Simon</au><au>Volz, Matthias</au><au>Haupt, Julia</au><au>Pedersen, Anya</au><au>Werheid, Katja</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis</atitle><jtitle>Journal of affective disorders reports</jtitle><date>2025-01</date><risdate>2025</risdate><volume>19</volume><spage>100855</spage><pages>100855-</pages><artnum>100855</artnum><issn>2666-9153</issn><eissn>2666-9153</eissn><abstract>•The interdependences of depressive symptoms, disability, social support, and mental and physical health-related quality of life after stroke are high but knowledge about multivariate associations is scarce.•Network analysis revealed depressive symptoms, social support and mental health-related quality of life as the most central variables.•The results underline the relevance of mental aspects over physical stroke sequalae for quality of life.•Interventions targeting depressive symptoms and social support may efficiently mitigate the burden on quality of life after stroke.
Health-related quality of life (HRQOL), depressive symptoms, disability, and social support show complex interdependences after stroke, which cannot be sufficiently depicted by commonly used uni- or bivariate analyses. Applying a network analysis, we aim to disentangle these multivariate relationships and deduce meaningful starting points for interventions.
Stroke survivors (N = 202) were recruited from two inpatient rehabilitation clinics. Participants self-reported mental and physical HRQOL, depressive symptoms, disability, and social support. We computed a partial correlation network and included these five variables as separate nodes. We estimated edge weights, node centrality (expected influence), node predictability, and clusters. Bootstrap methods were applied to assess network stability.
Depressive symptoms and mental HRQOL were the most central and interconnected nodes in the network. Depressive symptoms built its own cluster. Social support showed a high association with depressive symptoms. Disability had no significant associations with other nodes in the network. Physical HRQOL was significantly connected only to its mental equivalent.
The cross-sectional design limits the findings to the setting of inpatient rehabilitation few weeks after stroke and allows no longitudinal inferences. The relatively small sample size and varying metrics of applied measures are counterbalanced by a high stability of estimations.
Depression and social support show stronger associations with HRQOL than physical aspects during stroke inpatient rehabilitation. This underscores the significance of mental aspects shortly after stroke. Development and implementation of early interventions targeting depressive symptoms and social support may sustainably mitigate the burden on HRQOL after stroke.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jadr.2024.100855</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2666-9153 |
ispartof | Journal of affective disorders reports, 2025-01, Vol.19, p.100855, Article 100855 |
issn | 2666-9153 2666-9153 |
language | eng |
recordid | cdi_crossref_primary_10_1016_j_jadr_2024_100855 |
source | ScienceDirect |
subjects | Depression Health-related quality of life Network analysis Psychological risk factors Stroke |
title | Disentangling the relationships of health-related quality of life, depressive symptoms, disability and social support after stroke: A network analysis |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T01%3A23%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Disentangling%20the%20relationships%20of%20health-related%20quality%20of%20life,%20depressive%20symptoms,%20disability%20and%20social%20support%20after%20stroke:%20A%20network%20analysis&rft.jtitle=Journal%20of%20affective%20disorders%20reports&rft.au=Ladwig,%20Simon&rft.date=2025-01&rft.volume=19&rft.spage=100855&rft.pages=100855-&rft.artnum=100855&rft.issn=2666-9153&rft.eissn=2666-9153&rft_id=info:doi/10.1016/j.jadr.2024.100855&rft_dat=%3Celsevier_doaj_%3ES2666915324001410%3C/elsevier_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c1625-a39698441a327578bc616dfba5f985e94c26935414d6cc847ab554f57c325e393%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |