Self-reports could be affected by 2 primary sources of distortion: content-related (CRD) and content-unrelated (CUD) distortions. CRD and CUD, however, might covary, and similar detection strategies have been used to capture both. Thus, we hypothesized that a scale developed to detect random responding—arguably, one of the most evident examples of CUD—would likely be sensitive to both CUD and, albeit to a lesser extent, CRD. Study 1 (N = 1,901) empirically tested this hypothesis by developing a random responding scale (RRS) for the recently introduced Inventory of Problems–29 (Viglione, Giromini, & Landis, 2017 Viglione, D. J., Giromini, L., & Landis, P. (2017). The development of the Inventory of Problems–29: A brief self-administered measure for discriminating bona fide from feigned psychiatric and cognitive complaints. Journal of Personality Assessment, 99(5), 534–544.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), and by testing it with both experimental feigners and honest controls. Results supported our hypothesis and offered some insight on how to pull apart CRD- from CUD-related variance. Study 2 (N = 700) then evaluated whether our RRS would perform similarly well with data from human participants instructed to respond at random versus computer-generated random data. Interestingly, the sensitivity of our RRS dropped dramatically when considering the data from human participants. Together with the results of additional analyses inspecting the patterns of responses provided by our human random responders, these findings thus posed a major question: Is humans’ random responding really random?
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Giromini et al. (2019) studied this question.
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