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Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries
BACKGROUND: Network types and characteristics have been linked to the capacity of inter-personal environments to mobilise and share resources. The aim of this paper is to examine personal network types in relation to long-term condition management in order to identify the properties of network types...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990169/ https://www.ncbi.nlm.nih.gov/pubmed/27536988 http://dx.doi.org/10.1371/journal.pone.0161027 |
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author | Vassilev, Ivaylo Rogers, Anne Kennedy, Anne Wensing, Michel Koetsenruijter, Jan Orlando, Rosanna Portillo, Maria Carmen Culliford, David |
author_facet | Vassilev, Ivaylo Rogers, Anne Kennedy, Anne Wensing, Michel Koetsenruijter, Jan Orlando, Rosanna Portillo, Maria Carmen Culliford, David |
author_sort | Vassilev, Ivaylo |
collection | PubMed |
description | BACKGROUND: Network types and characteristics have been linked to the capacity of inter-personal environments to mobilise and share resources. The aim of this paper is to examine personal network types in relation to long-term condition management in order to identify the properties of network types most likely to provide support for those with a long-term condition. METHOD: A cross-sectional observational survey of people with type 2 diabetes using interviews and questionnaires was conducted between April and October 2013 in six European countries: Greece, Spain, Bulgaria, Norway, United Kingdom, and Netherlands. 1862 people with predominantly lower socio-economic status were recruited from each country. We used k-means clustering analysis to derive the network types, and one-way analysis of variance and multivariate logistic regression analysis to explore the relationship between network type socio-economic characteristics, self-management monitoring and skills, well-being, and network member work. RESULTS: Five network types of people with long-term conditions were identified: restricted, minimal family, family, weak ties, and diverse. Restricted network types represented those with the poorest self-management skills and were associated with limited support from social network members. Restricted networks were associated with poor indicators across self-management capacity, network support, and well-being. Diverse networks were associated with more enhanced self-management skills amongst those with a long-term condition and high level of emotional support. It was the three network types which had a large number of network members (diverse, weak ties, and family) where healthcare utilisation was most likely to correspond to existing health needs. DISCUSSION: Our findings suggest that type of increased social involvement is linked to greater self-management capacity and potentially lower formal health care costs indicating that diverse networks constitute the optimal network type as a policy in terms of the design of LTCM interventions and building support for people with LTCs. |
format | Online Article Text |
id | pubmed-4990169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49901692016-08-29 Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries Vassilev, Ivaylo Rogers, Anne Kennedy, Anne Wensing, Michel Koetsenruijter, Jan Orlando, Rosanna Portillo, Maria Carmen Culliford, David PLoS One Research Article BACKGROUND: Network types and characteristics have been linked to the capacity of inter-personal environments to mobilise and share resources. The aim of this paper is to examine personal network types in relation to long-term condition management in order to identify the properties of network types most likely to provide support for those with a long-term condition. METHOD: A cross-sectional observational survey of people with type 2 diabetes using interviews and questionnaires was conducted between April and October 2013 in six European countries: Greece, Spain, Bulgaria, Norway, United Kingdom, and Netherlands. 1862 people with predominantly lower socio-economic status were recruited from each country. We used k-means clustering analysis to derive the network types, and one-way analysis of variance and multivariate logistic regression analysis to explore the relationship between network type socio-economic characteristics, self-management monitoring and skills, well-being, and network member work. RESULTS: Five network types of people with long-term conditions were identified: restricted, minimal family, family, weak ties, and diverse. Restricted network types represented those with the poorest self-management skills and were associated with limited support from social network members. Restricted networks were associated with poor indicators across self-management capacity, network support, and well-being. Diverse networks were associated with more enhanced self-management skills amongst those with a long-term condition and high level of emotional support. It was the three network types which had a large number of network members (diverse, weak ties, and family) where healthcare utilisation was most likely to correspond to existing health needs. DISCUSSION: Our findings suggest that type of increased social involvement is linked to greater self-management capacity and potentially lower formal health care costs indicating that diverse networks constitute the optimal network type as a policy in terms of the design of LTCM interventions and building support for people with LTCs. Public Library of Science 2016-08-18 /pmc/articles/PMC4990169/ /pubmed/27536988 http://dx.doi.org/10.1371/journal.pone.0161027 Text en © 2016 Vassilev et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Vassilev, Ivaylo Rogers, Anne Kennedy, Anne Wensing, Michel Koetsenruijter, Jan Orlando, Rosanna Portillo, Maria Carmen Culliford, David Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title | Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title_full | Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title_fullStr | Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title_full_unstemmed | Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title_short | Social Network Type and Long-Term Condition Management Support: A Cross-Sectional Study in Six European Countries |
title_sort | social network type and long-term condition management support: a cross-sectional study in six european countries |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990169/ https://www.ncbi.nlm.nih.gov/pubmed/27536988 http://dx.doi.org/10.1371/journal.pone.0161027 |
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