scholarly journals Implicit social cognition through years: The Implicit Association Test at age 21

Author(s):  
Ottavia M. Epifania ◽  
Egidio Robusto ◽  
Pasquale Anselmi

<p>The advent of implicit measures opened the access to processes of which people might not be completely aware but that can still influence their attitudes, preferences, and behaviors towards different objects. Among the existing implicit measures, the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) is one of the most studied and used. The descriptive literature review presented in this work was aimed at providing an overview of how the IAT has been used from the year of its first introduction until current days. Specifically, the main fields of application of the IAT, the specific topics for which it has been used, and its concurrent use with other implicit measures have been highlighted and described. When possible, information on the samples on which the studies were carried out are reported. Results indicate an on-going growth of the IAT in a constantly wider range of topics. The ability of the IAT to overcome self-presentation biases and to access the implicit aspects of attitudes have been particularly exploited for investigating biases towards different out-groups, especially in sensitive contexts.<br></p>

2020 ◽  
Author(s):  
Ottavia M. Epifania ◽  
Egidio Robusto ◽  
Pasquale Anselmi

<p>The advent of implicit measures opened the access to processes of which people might not be completely aware but that can still influence their attitudes, preferences, and behaviors towards different objects. Among the existing implicit measures, the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) is one of the most studied and used. The descriptive literature review presented in this work was aimed at providing an overview of how the IAT has been used from the year of its first introduction until current days. Specifically, the main fields of application of the IAT, the specific topics for which it has been used, and its concurrent use with other implicit measures have been highlighted and described. When possible, information on the samples on which the studies were carried out are reported. Results indicate an on-going growth of the IAT in a constantly wider range of topics. The ability of the IAT to overcome self-presentation biases and to access the implicit aspects of attitudes have been particularly exploited for investigating biases towards different out-groups, especially in sensitive contexts.<br></p>


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250068
Author(s):  
Jimmy Calanchini ◽  
Franziska Meissner ◽  
Karl Christoph Klauer

The ReAL model is a multinomial processing tree model that quantifies the contribution of three qualitatively distinct processes–recoding, associations, and accuracy–to responses on the implicit association test (IAT), but has only been validated on a modified version of the IAT procedure. The initial goal of the present research was to validate an abbreviated version of the ReAL model (i.e., the Brief ReAL model) on the standard IAT procedure. Two experiments replicated previous validity evidence for the ReAL model on the modified IAT procedure, but did not produce valid parameter estimates for the Brief ReAL model on the standard IAT procedure. A third, pre-registered experiment systematically manipulated all of the task procedures that vary between the standard and modified IAT procedures–response deadline, number of trials, trial constraints–to determine the conditions under which the Brief ReAL model can be validly applied to the IAT. The Brief ReAL model estimated theoretically-interpretable parameters only under a narrow range of IAT conditions, but the ReAL model generally estimated theoretically-interpretable parameters under most IAT conditions. We discuss the application of these findings to implicit social cognition research, and their implications to social cognitive theory.


2016 ◽  
Author(s):  
Brian A. Nosek ◽  
Mahzarin R. Banaji

Overview=======The GNAT (pronounced like the bug) is a flexible technique designed to measure implicit social cognition. Conceptually similar to other implicit measures like the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, JPSP, 1998), the GNAT assesses automatic associations between concept (e.g., gender) and attribute (e.g., evaluation) categories. The GNAT has two features that distinguish it from other measures of implicit social cognition. First, the GNAT is designed to be use signal detection statistics in its calculation of automatic associations (d-prime), but can also be adapted to utilize response latency as its operational dependent variable. Second, the GNAT is flexible in the establishing of contextual characteristics for the evaluative situation. For example, the IAT requires an attitude toward one category (insects) be assessed relative to a second category (flowers). With the GNAT, experimenters can vary whether insects are evaluated in the context of a single category (flowers), a superordinate category (animals), a generic category (objects) or with no context at all.


2019 ◽  
Author(s):  
Michael McCarthy

After two decades of research on implicit social cognition, it has become clear many of the field's theories and practices need to be redressed. Addressed in the present paper are the assumptions and memetic ideas embedded in the language, theory, and measurement tools of so-called implicit social cognition, their historical and contemporary shortcomings, and solutions to avoid these shortcomings and improve scholarship in this field. Specifically, the present paper recommends researchers and theorists adopt more accurate and epistemically honest language in their work, and determine what measures of implicit social cognition measure through experimental research rather than through empirically unjustifiable assumptions. Contributing to this endeavour, the present paper includes an experiment testing whether performance on the Implicit Association Test (IAT) can be changed through the indirect activation of complex associations. Here it is demonstrated that performance on IAT appears to be unaffected by indirectly activated complex associations, ruling out a possible cognitive mechanism that could contribute to performance on the IAT.


2020 ◽  
Vol 35 (4) ◽  
pp. 23-44
Author(s):  
Axelle Faure-Ferlet ◽  
Sonia Capelli ◽  
William Sabadie

This research investigates whether a label on cooperative governance influences the perceived taste of a product through a sensation transfer process. The first study measures perceived taste of unbranded products implicitly (via an Implicit Association Test) and explicitly (via a survey). The label improves the implicitly and explicitly perceived taste. The second study, reproducing the same protocols with branded products, confirms this result for implicitly perceived taste, but the effect of the label on explicitly perceived taste disappears. Because implicit measures are more predictive of routine purchasing than are explicit measures, we recommend spotlighting cooperative governance on food products.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maddalena Marini ◽  
Pamela D. Waterman ◽  
Emry Breedlove ◽  
Jarvis T. Chen ◽  
Christian Testa ◽  
...  

Abstract Background To date, research assessing discrimination has employed primarily explicit measures (i.e., self-reports), which can be subject to intentional and social desirability processes. Only a few studies, focusing on sex and race/ethnicity discrimination, have relied on implicit measures (i.e., Implicit Association Test, IAT), which permit assessing mental representations that are outside of conscious control. This study aims to advance measurement of discrimination by extending the application of implicit measures to multiple types of discrimination and optimizing the time required for the administration of these instruments. Methods Between September 27th 2019 and February 9th 2020, we conducted six experiments (984 participants) to assess implicit and explicit discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age. Implicit discrimination was measured by using the Brief-Implicit Association Test (B-IAT), a new validated version of the IAT developed to shorten the time needed (from ≈15 to ≈2 min) to assess implicit mental representations, while explicit discrimination was assessed using self-reported items. Results Among participants (mean age = 37.8), 68.6% were White Non-Hispanic; 69% were females; 76.1% were heterosexual; 90.7% were gender conforming; 52.8% were medium weight; and 41.5% had an advanced level of education. Overall, we found implicit and explicit recognition of discrimination towards all the target groups (stronger for members of the target than dominant groups). Some exceptions emerged in experiments investigating race/ethnicity and weight discrimination. In the racism experiment, only people of Color showed an implicit recognition of discrimination towards the target group, while White people were neutral. In the fatphobia experiment, participants who were not heavy showed a slight implicit recognition of discrimination towards the dominant group, while heavy participants were neutral. Conclusions This study provides evidence that the B-IAT is a valuable tool for quickly assessing multiple types of implicit discrimination. It shows also that implicit and explicit measures can display diverging results, thus indicating that research would benefit from the use of both these instruments. These results have important implications for the assessment of discrimination in health research as well as in social and psychological science.


2020 ◽  
Author(s):  
Jessica Röhner ◽  
Calvin K. Lai

<p>Performance on implicit measures reflects construct-specific and non-construct-specific processes. This creates an interpretive issue for understanding interventions to change implicit measures: change in performance could reflect changes in the constructs-of-interest or changes in other mental processes. We re-analyzed data from six studies (<i>N</i> = 23,342) to examine the process-level effects of 17 interventions and one sham intervention to change race Implicit Association Test (IAT) performance. Diffusion models decompose overall IAT performance (<i>D</i>-scores) into construct-specific (ease of decision-making), and non-construct-specific processes (speed-accuracy tradeoffs, non-decision-related processes like motor execution). Interventions that effectively reduced <i>D-</i>scores changed ease of decision-making on compatible and incompatible trials. They also eliminated differences in speed-accuracy tradeoffs between compatible and incompatible trials. Non-decision-related processes were impacted by two interventions only. There was little evidence that interventions had any long-term effects. These findings highlight the value of diffusion modeling for understanding the mechanisms by which interventions affect implicit measure performance.</p>


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