Social network type and long-term condition management support

• Verfasst von: Vassilev, Ivaylo [VerfasserIn]
• Verfasst von: Wensing, Michel [VerfasserIn]
• Titel: Social network type and long-term condition management support
• Titelzusatz: a cross-sectional study in six European countries
• Verf.angabe: Ivaylo Vassilev, Anne Rogers, Anne Kennedy, Michel Wensing, Jan Koetsenruijter, Rosanna Orlando, Maria Carmen Portillo, David Culliford
• Fussnoten: Gesehen am 21.03.2018
• Titel Quelle: Enthalten in: PLOS ONE
• Jahr Quelle: 2016
• Band/Heft Quelle: 11(2016,8) Artikel-Nummer e0161027, 15 Seiten
• ISSN Quelle: 1932-6203
• DOI: doi:10.1371/journal.pone.0161027
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1571281487

Abstract

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 theoptimal network type as a policy in terms of the design of LTCM interventions and building support for people with LTCs.