Abstract

Indirect questioning techniques such as the crosswise model aim to control for socially desirable responding in surveys on sensitive personal attributes. Recently, the extended crosswise model has been proposed as an improvement over the original crosswise model. It offers all of the advantages of the original crosswise model while also enabling the detection of systematic response biases. We applied the extended crosswise model to a new sensitive attribute, campus islamophobia, and present the first experimental investigation including an extended crosswise model, and a direct questioning control condition, respectively. In a paper-pencil questionnaire, we surveyed 1,361 German university students using either a direct question or the extended crosswise model. We found that the extended crosswise model provided a good model fit, indicating no systematic response bias and allowing for a pooling of the data of both groups of the extended crosswise model. Moreover, the extended crosswise model yielded significantly higher estimates of campus Islamophobia than a direct question. This result could either indicate that the extended crosswise model was successful in controlling for social desirability, or that response biases such as false positives or careless responding have inflated the estimate, which cannot be decided on the basis of the available data. Our findings highlight the importance of detecting response biases in surveys implementing indirect questioning techniques.

Highlights

  • Surveys of sensitive personal attributes often rely on self-reports

  • Twice as many respondents were assigned to the extended crosswise model (ECWM) condition (n = 911; 66.94%) as to the DQ condition (n = 450; 33.06%) to compensate for the lower efficiency of indirect questioning techniques [51]

  • The prevalence estimate of campus Islamophobia was significantly higher in the ECWM (21.19%; SE = 2.23%) than in the DQ (10.89%; SE = 1.47%) condition, ΔG2(1) = 14.69, p < .001, and both estimates were significantly higher than zero, DQ: ΔG2(1) = 1495.46, p < .001; ECWM: ΔG2(1) = 119.40, p

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Summary

Introduction

Socially desirable responding, that is, the tendency to answer in accordance with social norms rather than truthfully, may result in underestimates of the prevalence of socially undesirable attributes and overestimates of the prevalence of socially desirable attributes [1, 2]. To address this problem, indirect questioning techniques such as the randomized response technique (RRT [3]) have been proposed. Based on an experimental randomization procedure, the RRT provides prevalence estimates of sensitive attributes on the sample level while preserving the confidentiality of individual responses. A comprehensive meta-analysis [4] confirmed the usefulness of this

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