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Construal Level Theory Supported Method for Sensitive Topics: Applications in Three Different Populations

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Statistical Methods for Global Health and Epidemiology

Part of the book series: ICSA Book Series in Statistics ((ICSABSS))

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Abstract

Social desirability bias is a major threat to data quality for survey studies, particularly studies involving sensitive questions, such as age, income, sexual behaviors, and drug use. In this chapter, we introduced a construal level theory (CLT)-based method we devised to reduce social desirability bias. Construals are our mental constructions of the universe organized in hierarchies along with spatiotemporal and psychosocial distances, with self, here, and now as the reference. Answering sensitive question regarding self is often executed at low construal levels subjected to contextual factors. In this case, the respondent tend to edit the answer to make it socially desirable either to avoid penalty or to enhance reward. In contrast, answering sensitive questions for others is often executed at high construal levels, less likely to subject to contextual factors but more dependent on one’s own knowledge, attitudes and beliefs. CLT-based method is a technique based on this theory by asking participants to answer the same questions for 2–3 socially distant others. In this study, we reported our work on building the method through three studies, one with data collected from college students in the US, two with data collected in China, including one sample of urban residents and another sample of rural residents. Four questions (reading newspaper, engaging in physical activity, frequent of sexual intercourse and attitudes toward homosexuality) were used in the college student study conducted in the US; the Brief Sexual Openness Scale (BSOS) was used in the two studies conducted in China. The use of the method and future research are also recommended.

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Correspondence to Xinguang Chen .

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Wang, Y., Chen, X. (2020). Construal Level Theory Supported Method for Sensitive Topics: Applications in Three Different Populations. In: Chen, X., Chen, (.DG. (eds) Statistical Methods for Global Health and Epidemiology. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-35260-8_4

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