Social networks are the collection of personal ties that individuals variously maintain and from which they gain a range of benefits, supports and services. Given the significance of the social network construct for both science and policy, the Survey of Health, Ageing and Retirement in Europe (SHARE) is developing a unique module for the measurement of social networks that can serve as a model for other surveys. The SHARE Social Network Module (SN) is based principally on the approach that was employed in the National Social life, Health and Aging Project, in the United States, in 2005-2006 (Cornwell et al., 2009) applying a name generating mechanism in which respondents identify the people who are important to them and then add information on each person named (via “name interpreter questions”). It also allows the tracing of changes in respondents’ social networks over time and is programmed to avoid respondents having to duplicate information provided.
The first two documents provided below describe the basic structure of the name generator and its mode of operation and showcase the production of the name generator tool in a wide range of languages that are spoken in Europe. The SHARE country teams have translated the SN module into the different national languages of the participating countries. Surveycodings.org provide a generic questionnaire in English and the available translations from Austria, Belgium (French and Dutch), Switzerland (German, French and Italian), the Czech-Republic, Germany, Denmark, Spain, Spain \Girona, France, Croatia, Italy, Luxembourg (German, French and Portuguese), Poland, Sweden and Slovenia that can be used by other survey project collecting social network data.
The third document available below describes additional work that was executed under the current grant. The first aim of the work was to validate a previously derived network typology among adults aged 65 and over, using subsequently collected social network data. In addition, changes in the network types across the respective waves of data collection were traced and their socio-economic and health correlates were identified. Finally, in accordance with the second aim of the work, the document also presents a network change typology that was derived.