Faking strategies on the Implicit Association Test (IAT)

What is it about?

We investigated which faking strategies participants use when faking the IAT. Strategies depended on faking goals (faking high vs. low) and pre-existing knowledge.

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Photo by Paul Skorupskas on Unsplash

Photo by Paul Skorupskas on Unsplash

Why is it important?

Whereas self-report measures have long been suspected of being susceptible to faking, the fakeability of indirect measures such as the IAT has only recently been investigated. In fact, their alleged robustness against faking has been a selling point for indirect measures in the first place. However, research has shown that under certain conditions the Implicit Association Test (IAT) can be faked (e.g., Fiedler & Bluemke, 2005; McDaniel, Beier, Perkins, Goggin, & Frankel, 2009; Steffens, 2004) and that simply identifying fakers on the basis of expertise is not possible (Fiedler & Bluemke, 2005). Some indices have been developed to measure faking based on the slowing down of reaction times under faking (Agosta Ghirardi, Zogmaister, Castiello, & Sartori, 2010; Cvencek, Greenwald, Brown, Gray, & Snowden, 2010). Other possible faking strategies such as acceleration have not yet been considered. Furthermore, most research so far has examined only one of two possible faking directions (faking high vs. faking low scores). Lastly, previous research has not tested whether participants’ strategies differ depending on their a priori knowledge of faking the IAT. In addressing these issues, we investigated what fakers actually do when faking the IAT. Our results complement previous findings by showing that participants use different faking strategies depending on their specific faking goal (i.e., faking high vs. faking low) and on their a priori knowledge of faking strategies.