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Social networking sites (SNSs) might be important tools to contrast social exclusion in old age. However, the so-called gray digital divide (GDD) may undermine the potentialities of SNSs. Despite its relevance, there is very little research, which documented the characteristics of the digital divide in SNS use among the old-age population in Europe. Drawing on the “ material access in resources and appropriation” theory developed by van Dijk, this work contributes to consolidate the body of research, documenting the nature of the GDD in SNS use in Europe and evaluating the role that older people’s categorical, personal, and positional characteristics together with ICT characteristics play in gaining access to digital technologies. We analyze data from the 2013–2016 Eurostat Community Statistics on Information Societies (CSIS) survey and perform bivariate and multilevel regression analysis. Key findings are (i) the persistence of the intergeneration digital divide in old age together with the marked cross-countries differences in SNS use across European countries and over time and (ii) the stability over old-age generations, countries, and time of the positional categories associated with SNS use in old age, providing further empirical support to van Dijk’s theory.

When surveying immigrant populations or ethnic minority groups, it is important for survey researchers to consider that respondents might vary in their level of language proficiency. While survey translations might be offered, they are usually available for a limited number of languages, and even then, non-native speakers may not utilize questionnaires translated into their native language. This article examines the impact of language proficiency among respondents interviewed in English on survey data quality. We use data from Understanding Society: The United Kingdom Household Longitudinal Study (UKHLS) to examine five indicators of data quality, including “don’t know” responding, primacy effects, straightlining in grids, nonresponse to a self-completion survey component, and change in response across survey waves. Respondents were asked whether they are native speakers of English; non-native speakers were subsequently asked to self-rate whether they have any difficulties speaking or reading English. Results suggest that non-native speakers provide lower data quality for four of the five quality indicators we examined. We find that non-native respondents have higher nonresponse rates to the self-completion section and are more likely to report change across waves, select the primary response option, and show straightlining response behavior in grids. Furthermore, primacy effects and nonresponse rates to the self-completion section vary by self-rated level of language proficiency. No significant effects were found with regard to “don’t know” responding between native and non-native speakers.