Extending the Implicit Association Test (IAT): Assessing Consumer Attitudes Based on Multi-Dimensional Implicit Associations

Background: The authors present a procedural extension of the popular Implicit Association Test (IAT; [1]) that allows for indirect measurement of attitudes on multiple dimensions (e.g., safe–unsafe; young–old; innovative–conventional, etc.) rather than on a single evaluative dimension only (e.g., good–bad). Methodology/Principal Findings: In two within-subjects studies, attitudes toward three automobile brands were measured on six attribute dimensions. Emphasis was placed on evaluating the methodological appropriateness of the new procedure, providing strong evidence for its reliability, validity, and sensitivity. Conclusions/Significance: This new procedure yields detailed information on the multifaceted nature of brand associations that can add up to a more abstract overall attitude. Just as the IAT, its multi-dimensional extension/application (dubbed md-IAT) is suited for reliably measuring attitudes consumers may not be consciously aware of, able to express, or willing to share with the researcher [2,3].Product Innovation ManagementIndustrial Design Engineerin

Structuring effect of tools conceptualized through initial goal fixedness for work activity

Analysis of work activities in nuclear industry has highlighted a new psycho-cognitive phenomenon: the structuring effect of tools (SET) sometimes leading to unexpected operating deviations; the subject is unable to perform a task concerning object A using or adapting a tool designed and presented to perform the same task concerning object B when object A is expected by the subject. Conditions to isolate and identify the SET were determined and reproduced in experiments for further analysis. Students and seven professional categories of adults (N = 77) were involved in three experimental conditions (control group, group with prior warning, group with final control) while individually performing a task with similar characteristics compared to real operating conditions and under moderate time-pressure. The results were: (1) highest performance with prior warning and (2) demonstration that academic and professional training favor the SET. After discussing different cognitive processes potentially related to the SET, we described (3) the psycho-cognitive process underlying the SET: Initial Goal Fixedness (IGF), a combination of the anchoring of the initial goal of the activity with a focus on the features of the initial goal favored by an Einstellung effect. This suggested coping with the negative effect of the SET by impeding the IGF rather than trying to increase the subjects’ awareness at the expense of their health. Extensions to other high-risk industries were discussed

Modeling working memory: An interference model of complex span

This article introduces a new computational model for the complex-span task, the most popular task for studying working memory. SOB-CS is a two-layer neural network that associates distributed item representations with distributed, overlapping position markers. Memory capacity limits are explained by interference from a superposition of associations. Concurrent processing interferes with memory through involuntary encoding of distractors. Free time in-between distractors is used to remove irrelevant representations, thereby reducing interference. The model accounts for benchmark findings in four areas: (1) effects of processing pace, processing difficulty, and number of processing steps; (2) effects of serial position and error patterns; (3) effects of different kinds of item-distractor similarity; and (4) correlations between span tasks. The model makes several new predictions in these areas, which were confirmed experimentally

Can the Implicit Association Test Measure Automatic Judgment? The Validation Continues

In this commentary, we welcome Schimmack\u2019s reanalysis of Bar-Anan and Vianello\u2019s multitrait multimethod (MTMM) data set, and we highlight some limitations of both the original and the secondary analyses. We note that when testing the fit of a confirmatory model to a data set, theoretical justifications for the choices of the measures to include in the model and how to construct the model improve the informational value of the results. We show that making different, theory-driven specification choices leads to different results and conclusions than those reported by Schimmack (this issue, p. 396). Therefore, Schimmack\u2019s reanalyses of our data are insufficient to cast doubt on the Implicit Association Test (IAT) as a measure of automatic judgment. We note other reasons why the validation of the IAT is still incomplete but conclude that, currently, the IAT is the best available candidate for measuring automatic judgment at the person level

The Relation Between Evaluation and Racial Categorization of Emotional Faces

Prior research has found that indirectly measured preference for White people over Black people is positively related to categorizing angry racially ambiguous faces as Black. This past work found no evidence that directly measured racial preferences predict this racial categorization bias (RCB), suggesting that the RCB could be a unique and easily administered tool for investigating automatic evaluation and validating automatic evaluation measures. In two studies (total N > 7,000), using structural equation models that account for error variance, multiple indirect evaluation measures were uniquely related to the RCB, thus bolstering their predictive validity. However, the RCB also correlated with self-reported evaluation, leaving psychologists without a robust, replicable outcome uniquely related to automatic evaluation. The lack of such an outcome hinders theoretical and practical progress in research on implicit social cognition