Implicit measures can be defined as outcomes of measurement procedures that are caused in an automatic manner by psychological attributes. To establish that a measurement outcome is an implicit measure, one should examine (a) whether the outcome is causally produced by the psychological attribute it was designed to measure, (b) the nature of the processes by which the attribute causes the outcome, and (c) whether these processes operate automatically. This normative analysis provides a heuristic framework for organizing past and future research on implicit measures. The authors illustrate the heuristic function of their framework by using it to review past research on the 2 implicit measures that are currently most popular: effects in implicit association tests and affective priming tasks.Keywords: implicit measures, automaticity, IAT, affective priming Most psychologists would argue that a full understanding of the behavior of an individual requires knowledge not only of the external situation in which the individual is present but also of the internal psychological attributes of the individual. Throughout the history of psychology, researchers have therefore attempted to measure interindividual differences in the psychological attributes of people (e.g., Anastasi, 1958;Eysenck & Eysenck, 1985;Mischel & Shoda, 1995). During the past decade, a major development in this research has been the introduction of so-called implicit measures. These measures were originally put forward mainly within the social psychology literature (e.g., Fazio, Jackson, Dunton, & Williams, 1995;Greenwald, McGhee, & Schwartz, 1998) but have since then spread to various other subdisciplines of psychology, including differential psychology (e.g., Asendorpf, Banse, & Mücke, 2002), clinical psychology (e.g., Gemar, Segal, Sagrati, & Kennedy, 2001, consumer psychology (e.g., Maison, Greenwald, & Bruin, 2004), and health psychology (e.g., Wiers, van Woerden, Smulders, & de Jong, 2002).Despite the widespread use of implicit measures, the actual meaning of the term implicit measure is rarely defined. On the basis of the work of Borsboom (Borsboom, 2006;Borsboom, Mellenbergh, & van Heerden, 2004) and De Houwer (De Houwer, 2006;, we first provide a normative analysis of the concept "implicit measure." The analysis is normative in the sense that it stipulates the properties that an ideal implicit measure should have. As such, the analysis provides a heuristic framework for reviewing and evaluating existing research on implicit measures. By examining the extent to which a particular implicit measure exhibits these normative properties, one can clarify the way in which the measure is an implicit measure and highlight those issues on which further research is required. In the second part of this article, we perform this exercise with regard to the two types of implicit measures that are currently most popular: effects in implicit association tests (IATs;Greenwald et al., 1998) and affective priming tasks (Fazio et al., 1995). Before we present and ap...

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In the affective-priming paradigm, target stimuli are preceded by evaluatively polarized prime stimuli and then are to be classified as either good or bad as fast as possible. The typical and robust finding is assimilation: Primes facilitate the processing of evaluatively consistent targets relative to evaluatively inconsistent targets. Nevertheless, contrast effects have repeatedly been observed. The authors propose a new psychophysical account of normal (assimilative) and reversed (contrastive) priming effects and test new predictions derived from it in 5 studies: In Studies 1 and 2, the authors' account is shown to provide a better explanation of contrastive effects in a priming paradigm with two primes than the traditional attentional account does. Furthermore, as predicted by the new account, contrast effects emerge at an intermediate stimulus-onset asynchrony (SOA, Study 3) and even with short SOAs when target onset takes participants by surprise (Study 4). Finally, the use of extremely valenced primes triggers corrective efforts (Study 5) as predicted. Implications for priming measures of evaluative associations are discussed.

Recent studies have shown that robust affective priming effects can be obtained when participants are required to categorize the targets on the basis of their valence, but not when participants are asked to categorize the targets on the basis of nonaffective features. On the basis of this pattern of results, it has been argued that affective priming is due to processes that operate at a response selection stage rather than to processes that operate at an encoding stage. We demonstrate (a) that affective priming of nonaffective semantic categorization responses can be obtained when participants assign attention to the affective stimulus dimension, and (b) that affective priming in the standard evaluative categorization task is strongly reduced when participants assign attention to nonaffective stimulus features. On the basis of these findings, we argue (a) that processes operating at an encoding stage do contribute to the affective priming effect, and (b) that automatic affective stimulus processing is reduced when participants selectively attend to nonaffective stimulus features.

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