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), 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?.

An Inventory of Problems–29 Study on Random Responding Using Experimental Feigners, Honest Controls, and Computer-Generated Data

Giromini L.
First
;
Pignolo C.;Zennaro A.
Last
2020-01-01

Abstract

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), 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?.
2020
102
6
731
742
Giromini L.; Viglione D.J.; Pignolo C.; Zennaro A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1766436
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