The Procedure of IATs

Implicit Association Tests are designed to compare speed of response between two different pairings of a double discrimination task. One discrimination task asks for the categorization of a binary target concept, for example, ‘flower’ versus ‘insect’ The other discrimination task asks for the categorization of a binary attribute concept, for example,

‘positive’ versus ‘negative’. An IAT pairs both categorizations within a double discrimination task, and implements the two possible pairings. One pairing requires one response for one target and one attribute category, and another response for the alternative target and the alternative attribute category. The other pairing leaves responses for the attribute categories the same but exchanges the responses for the target categories.

An IAT starts by introducing participants to the target, and, subsequently, to the attribute concept. For instance, an IAT that assesses attitudes toward flowers and insects first trains participants to press the left response key when a flower name is presented on the screen and the right response key when an insect name is presented on the screen (see Table 1). In the second sequence, participants are trained to press the left key for positive words and the right key for negative words. The third sequence combines the target and the attribute discrimination, and asks participants to respond left to flower names or positive words, and right to insect names or negative words. The fourth sequence reverses the target discrimination, and assigns the left response to insect names and the right response to flower names. Finally, the fifth sequence combines the attribute and the previously reversed target discrimination, and asks participants to respond left to insect names or positive words, and right to flower names or negative words.

Table 1

Task Sequence and Stimuli of an Implicit Association Test to Measure Attitudes toward Flowers and Insects

Response key assignment

Sequence Task Left key Right key

1 Target discrimination Flower Insect

2 Attribute discrimination Positive Negative

3 Initial combined task Flower, positive Insect, negative 4 Reversed target discrimination Insect Flower

5 Reversed combined task Insect, positive Flower, negative Target concept Attribute concept

Categories Flower Insect Positive Negative

Sample stimuli aster fly caress abuse

hyacinth cockroach freedom crash

crocus mosquito health filth

iris wasp love murder

rose termite peace sickness

Note. Sample stimuli correspond to Greenwald et al. (1998).

For the calculation of IAT scores, or IAT effects, only response latencies within the combined tasks are relevant. Various variants of IAT scores are based upon the difference in mean response latencies in sequence 5 minus sequence 3. Thus, if participants are quicker in combining flower names + positive words and insect names + negative words relatively to the reverse pairing, they attain low latencies in sequence 3 and high latencies in sequence 5. This would result in a positive IAT score. Normally, participants evaluate flowers more positively than insects on direct attitude measures (Greenwald et al. 1998).

This was equally indicated in the indirect measure by a positive IAT effect. Greenwald and colleagues (1998) concluded that quicker responses plausibly reflect stronger associations for flower + positive and insect + negative relatively to flower + negative and insect + positive. The combined task that reveals quicker responses in most respondents is often referred to as the ‘compatible’ task. Thus, in the flower-insect attitude IAT, the flower + positive and insect + negative pairing would represent the ‘compatible’ task.

The conventional IAT scoring algorithm was presented in the initial publication of IAT data (Greenwald et al., 1998). This procedure discarded training trials from the combined blocks, and was based on log-transformed latencies. Recently, Greenwald, Nosek, and Banaji (2003) proposed an improved algorithm for IAT scores that are referred to as D measures. D measures (a) employ untransformed response latencies from all trials of the combined blocks, (b) include a latency penalty for error trials, and (c) are individually calibrated by each respondent’s standard deviation of latencies. D measures outperformed the conventional IAT scores with regard to several criteria. In contrast to conventional scores, D measures were more resistant to contamination by response speed differences, and less affected by prior experiences with the IAT procedure. D measures are also yielded in larger effect sizes and higher correlations with direct self-report measures.

One limitation that results from the procedure of IATs is that it is confined to relative association strength: An IAT effect reflects the association strength of one pairing of target and attribute categories relatively to the reverse pairing. For instance, a positive flower-insect IAT score in the above example merely reflects that one evaluates flowers more positively, or less negatively, than insects. This does not illuminate whether one endorses either positive or negative attitudes toward either flowers or insects. Thus, IATs assess associations between an attribute concept and a target category only in relation to an opposing target category.

Therefore, alternatives to the IAT were developed to allow for single target categories, that is, the EASTs (“Extrinsic Affective Simon Tasks”, De Houwer, 2003a), the EMAs (“Evaluative Movement Assessments”, Brendl, Markmann, & Messner, 2003), the GNATs (“Go/No-Go Association Tasks”, Nosek & Banaji, 2001), and the STIATs (“Single Target IATs”, Wigboldus, 2003). A variant of the EMA, the Indirect Association Procedure (IAP) was developed in Study 1 to assess the implicit self-concept of shyness.

This procedure is described in the pilot studies of Study 1. The other procedures are not discussed in more detail because they are not directly related to this research. The common goal of all of these measures is to assess associations between concepts by contrasting opposing pairings of the concepts.

A second limitation of the IAT is that it may not be unquestionably qualified as an indirect or an unobtrusive measure. Indirectness usually refers to (a) unawareness, and therefore (b) uncontrollability of what is measured by a certain procedure (Greenwald &

Banaji, 1995). However, the first aspect, unawareness, is not true for IATs as they

explicitly introduce the target and the attribute concept. Concerning the second aspect, uncontrollability, empirical evidence shows that IATs can be both robust against (Banse, Seise, & Zerbes, 2001; Egloff & Schmukle, 2002; Kim, 2003) and susceptible to (Fiedler

& Blümke, 2003) volitional influences. Nevertheless, IATs were fakable only when participants were informed beforehand how the calculation of the IAT score works (Fiedler

& Blümke, 2003). In addition, IAT results can be influenced by mind sets of the participants that they more or less deliberately acquire before the test (see the special issue of the Journal of Personality and Social Psychology, 71, 2001). Among the new tests only the EAST (De Houwer, 2003a) does not explicitly introduce the target concept. In this work, IATs are labeled as indirect measures because they aim to assess implicit representations. However, this does not imply that the procedure and the outcome of IATs are necessarily unaware and uncontrollable.

The third limitation of IATs is that they do not allow for the simultaneous assessment of multiple target or attribute concepts. Particularly in research on personality differences, one is often interested in simultaneously assessing numerous personality-describing attributes with the IAT, as it is possible in direct questionnaire measures.

Among the new tests, the EMA (Brendl et al, 2003) and the EAST (De Houwer, 2003a) allow for multiple concepts although right now empirical evidence is lacking that these procedures assess multiple implicit concepts without major confounds between them.