A New Approach to Detecting Cheating in Sensitive Surveys: The Cheating Detection Triangular Model

Abstract

Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting instruction non-adherence, and similar to the Triangular Model, it uses simplified instructions to improve respondents’ understanding of the procedure. Based on a comparison with the known prevalence of a sensitive attribute serving as external criterion, we report the first individual-level validation of the Cheating Detection Model, the Triangular Model and the Cheating Detection Triangular Model. Moreover, the sensitivity and specificity of all models was assessed, as well as the respondents’ subjective evaluation of all questioning technique formats. Based on our results, the Cheating Detection Triangular Model appears to be the best choice among the investigated indirect questioning techniques.