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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...

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Autores principales: Vassilev, Ivaylo, Rogers, Anne, Kennedy, Anne, Wensing, Michel, Koetsenruijter, Jan, Orlando, Rosanna, Portillo, Maria Carmen, Culliford, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
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.
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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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