Survey questions asking about taboo topics such as sexual activities, illegal behaviour such as social fraud, or unsocial attitudes such as racism, often generate inaccurate survey estimates which are distorted by social desirability bias. Due to self-presentation concerns, survey respondents underreport socially undesirable activities and overreport socially desirable ones. This article reviews theoretical explanations of socially motivated misreporting in sensitive surveys and provides an overview of the empirical evidence on the effectiveness of specific survey methods designed to encourage the respondents to answer more honestly. Besides psychological aspects, like a stable need for social approval and the preference for not getting involved into embarrassing social interactions, aspects of the survey design, the interviewer's characteristics and the survey situation determine the occurrence and the degree of social desirability bias. The review shows that survey designers could generate more valid data by selecting appropriate data collection strategies that reduce respondents' discomfort when answering to a sensitive question.

Yu, Tian, and Tang (2008) proposed two new techniques for asking questions on sensitive topics in population surveys: the triangular model (TM) and the crosswise model (CM). The two models can be used as alternatives to the well-known randomized response technique (RRT) and are meant to overcome some of the drawbacks of the RRT. Although Yu, Tian, and Tang provide a promising theoretical analysis of the proposed models, they did not test them. We therefore provide results from an experimental survey in which the crosswise model was implemented and compared to direct questioning. To our knowledge, this is the first empirical evaluation of the crosswise model. We focused on the crosswise model because it seems better suited than the triangular model to overcome the self-protective ''no'' bias observed for the RRT. This paper-and-pencil survey on plagiarism was administered to Swiss and German students in university classrooms. Results suggest that the CM is a promising data-collection instrument eliciting more socially undesirable answers than direct questioning.

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This article contributes to an ongoing debate about how to measure sensitive topics in population surveys. We propose a novel technique that can be applied to the measurement of quantitative sensitive variables: the item sum technique (IST). This method is closely related to the item count technique (ICT), which was developed for the measurement of dichotomous sensitive items. First, we provide a description of our new technique and discuss how data collected by the IST can be analyzed. Second, we present the results of a CATI survey on undeclared work in Germany, in which the IST has been applied. Using an experimental design, we compare the IST to direct questioning. Our empirical results indicate that the IST is a promising data collection technique for sensitive questions. We conclude the article by discussing the limitations of the new technique and outlining possible improvements for future studies.

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