Language proficiency among respondents: implications for data quality in a longitudinal face-to-face survey

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.