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Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider.

Purpose - The purpose of this paper is to investigate the association of social networks with being in work, contrasting those under age 50 with those over 50 years. Design/methodology/approach - A case study is undertaken of a local labour market in Scotland. Data were collected by interview using a semi-structured questionnaire from 194 people divided into four groups. Data include information on individuals' socio-economic characteristics and on their networks. A four-way comparison is made by age and employment status. Findings - Those in work have denser social networks populated with members with higher social and human capital. For those over 50 years, the more contacts one has with higher prestige employment positions (a proxy for social capital), and the stronger the ties with these contacts, the more likely that one is to be in employment. For those under 50 years, their own qualifications and the number of contacts are important. Research limitations/implications - This work adds to both research on employability and social networks. Social implications - The over 50s tend to be the age group that is most likely to be not in employment and as populations age there is a need to ensure that barriers to employment against those over 50 are reduced. Finding routes to reduce unemployment will also help combat social exclusion. Originality/value - This is in the combination of a social network approach with age cohort analysis to give insight into how social capital is associated with being in employment