Exploring the use of social network analysis to measure social integration among older adults in assisted living.

Published

Journal Article

Social integration is measured by a variety of social network indicators each with limitations in its ability to produce a complete picture of the variety and scope of interactions of older adults receiving long-term services and supports. The purpose of this study was to develop and evaluate the feasibility of collecting sociocentric (whole network) data among older adults in one assisted living neighborhood. The sociocentric approach is required to conduct social network analysis. Applying social network analysis is an innovative way to measure different facets of social integration among residents. Sociocentric data are presented for 12 residents. Network visualization or sociograms are used to illustrate the level of social integration among residents and between residents and staff. Measures of network centrality are reported to illustrate the number of personal connections and cohesion. The use of resident photographs helped residents with cognitive impairment to nominate individuals with whom they interacted. The sociocentric approach to data collection is feasible and allows researchers to measure levels and different aspects of social integration in assisted living environments. Residents with mild to moderate cognitive impairment were able to participate with the aid of resident and staff photographs. This approach is sensitive to capturing routine day-to-day interactions between residents and assisted living staff members that are often not reported in person-centered networks. This study contributes to the foundation for larger more representative studies of entire assisted living organizations that could in the future inform interventions aimed at improving social integration and cohesion among recipients of long-term services and supports.

Full Text

Duke Authors

Cited Authors

  • Abbott, KM; Bettger, JP; Hampton, K; Kohler, H-P

Published Date

  • October 2012

Published In

Volume / Issue

  • 35 / 4

Start / End Page

  • 322 - 333

PubMed ID

  • 22929378

Pubmed Central ID

  • 22929378

Electronic International Standard Serial Number (EISSN)

  • 1550-5057

Digital Object Identifier (DOI)

  • 10.1097/FCH.0b013e318266669f

Language

  • eng

Conference Location

  • United States