Exaggeration is Harder Than Understatement, but Practice Makes Perfect!

Abstract

Previous research on the fakeability of the Implicit Association Test (IAT) yielded inconsistent results. The present study simultaneously analyses several relevant factors: faking direction, type of instructions, and practice. Furthermore, it takes baseline individual differences into account. After a baseline assessment in a self-esteem IAT without faking instructions (t0), participants in the faking conditions then (t1) faked high or low scores without being provided with recommended strategies on how to do so (i.e., individual strategies). At t2 and t3, they were asked to fake the IAT after having received information on recommended faking strategies. At t4, faking direction was reversed. Without the recommended strategies, faking high scores was not possible, but faking low scores was. With the recommended strategies, participants needed additional practice to fake high scores. When faking directions were reversed, participants were successful without additional practice, suggesting a transfer in faking skills. In most of the faking attempts, faking success was moderated by individual differences in baseline implicit self-esteem. This suggests that the complex interplay of factors influencing faking success should be taken into account when considering the issue of fakeability of the IAT.

EZ: An Easy Way to Conduct a More Fine-Grained Analysis of Faked and Nonfaked Implicit Association Test (IAT) Data

“…The latter seems problematic as faking becomes easier and more likely when test takers have greater knowledge about the test procedure (see, e. g., Dalen, Stanton, & Roberts, 2001). It is thus no wonder that the fakeability of the IAT has been well-documented (e. g., Fiedler & Bluemke, 2005;Röhner et al, 2011Röhner et al, , 2013Steffens, 2004) especially for the situation in which participants are informed about how the IAT works (i.e., informed faking; see, e. g., Röhner et al, 2011). The IAT is often used to assess socially stigmatized associations that might motivate people to fake (e. g., Agerström & Rooth, 2011;Banse et al, 2010;Banse et al, 2001;Carlsson & Björklund, 2010;Gray et al, 2005;Greenwald & Banaji, 1995;Greenwald et al, 1998;Latu et al, 2011).…”

“…Research has shown that the traditional IAT effect (i.e., the D measure; Greenwald et al, 2003aGreenwald et al, , 2003b contains not only variance related to the construct but also methodspecific variance (e. g., Back, Schmukle, & Egloff, 2005;McFarland & Crouch, 2002;Mierke & Klauer, 2003) and fakingrelated variance (e. g., De Houwer, Beckers, & Moors, 2007;Fiedler & Bluemke, 2005;McDaniel, Beier, Perkins, Goggin, & Frankel, 2009;Röhner, Schröder-Abé, & Schütz, 2011Steffens, 2004). Here, the diffusion model comes into play.…”

“…Given that (a) the IAT represents a very popular measure (Bosson et al, 2000;Rudolph et al, 2008), (b) its fakeability has already been well-documented (e. g., Fiedler & Bluemke, 2005;Röhner et al, 2011Röhner et al, , 2013Steffens, 2004), (c) diffusion model analyses are advantageous for interpreting IAT results (Klauer et al, 2007;Röhner & Ewers, 2016b), and (d) most likely the main obstacle that prevents researchers from using diffusion model analyses is the complexity of such analyses (e. g., A. Voss, Rothermund, Gast, & Wentura, 2013;Wagenmakers et al, 2007;Wagenmakers et al, 2008), an important question is whether EZ might be a tool that combines the advantage of being an easy diffusion model analysis to apply with the advantage of offering a better interpretation of IAT results.…”

How to analyze (faked) Implicit Association Test data by applying diffusion model analyses with the fast-dm software: A companion to Röhner & Ewers (2016)

“…The latter might be of particular concern among researchers as not only has the fakeability of the IAT been well documented by many studies (Fiedler & Bluemke, 2005;Röhner et al, 2011Röhner et al, , 2013, but also, the IAT is often used to measure associations with socially stigmatized or sensitive topics (e.g., pedophilia, racism, stereotypes, and sexism; Greenwald et al, 1998;Agerström & Rooth, 2011;Banse, Schmidt, & Clarbour, 2010;Banse, Seise, & Zerbes, 2001;Carlsson & Björklund, 2010;Gray, Brown, MacCulloch, Smith, & Snowden, 2005;Greenwald & Banaji, 1995;Latu et al, 2011) which might increase the motivation to fake. Thus, a possible and welcome alternative to analyzing and interpreting the results of the IAT effect came from diffusion model analyses that can be applied to analyze the results of fast binary decision tasks, including the IAT (e.g., Klauer, Voss, Schmitz, & Teige-Mocigemba, 2007;Ratcliff, 1978Ratcliff, , 2014van Ravenzwaaij, van der Maas, & Wagenmakers, 2011;A.…”

“…This D measure, however, may sometimes be contaminated by construct-irrelevant sources of variance (e.g., method-specific variance; fakingrelated variance; Mierke & Klauer, 2003;Röhner, Schröder-Abé, & Schütz, 2011. The latter might be of particular concern among researchers as not only has the fakeability of the IAT been well documented by many studies (Fiedler & Bluemke, 2005;Röhner et al, 2011Röhner et al, , 2013, but also, the IAT is often used to measure associations with socially stigmatized or sensitive topics (e.g., pedophilia, racism, stereotypes, and sexism; Greenwald et al, 1998;Agerström & Rooth, 2011;Banse, Schmidt, & Clarbour, 2010;Banse, Seise, & Zerbes, 2001;Carlsson & Björklund, 2010;Gray, Brown, MacCulloch, Smith, & Snowden, 2005;Greenwald & Banaji, 1995;Latu et al, 2011) which might increase the motivation to fake.…”