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methods, data, analyses, Vol 13, No 1 (2019) published!

| Categories: GESIS-News

Social Desirability Bias in Surveys – Collecting and Analyzing Sensitive Data


Guest Editors: Ben Jann1, Ivar Krumpal2, Felix Wolter3

1 University of Bern, 2 University of Leipzig, 3 Johannes Gutenberg University Mainz

Studying social phenomena and social problems often involves measuring and analyzing behaviors or attitudes that are sensitive in several ways. Topics such as delinquency, substance abuse, sexual issues, xenophobia or homophobia may oblige survey respondents to self-report information about very private issues or to report that they have acted against social or legal norms. Hence, survey participants could fear negative consequences of violating social desirability (SD) norms or of a disclosure of their private information to third parties. As cumulative empirical research has shown, this prompts respondents to engage in self-protective behavior when answering sensitive survey questions, namely by providing untruthful and biased answers or by refusing to answer at all. This systematic misreporting or nonresponse leads to biased estimates and poor data quality. At the same time, research about sensitive topics and norm-violations is of particular interest for the social sciences and public discussions likewise. This special issue of methods, data, analyses with seven papers has the ambition to contribute to the contemporary debates this field. It provides various important contributions to both theoretical and practical challenges in the research on sensitive questions.

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Categories: GESIS-News