Evidence map›Paper›PMID 37758761›Full record

ArticleScientific reports2023

Robust within-session modulations of IAT scores may reveal novel dynamics of rapid change.

Aaron Cochrane, William T L Cox, C Shawn Green

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Aaron CochraneDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI, USA. aaron_cochrane@brown.edu.
William T L CoxDepartment of Psychology, University of Wisconsin-Madison, Madison, WI, USA.
C Shawn GreenDepartment of Psychology, University of Wisconsin-Madison, Madison, WI, USA.
University of Wisconsin–Madison · USUniversity of Geneva · CH

Funding

Basic and Translational Research to Combat Stereotypes and Unintentional BiasesR35GM128888 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI COX, WILLIAM TAYLOR LAIMAKA · 2018 to 2022
$1.9M
NIGMS NIH HHS 1R35GM128888NIGMS NIH HHS R35 GM128888
6 · The paper itself

Abstract

The Implicit Association Test (IAT) is employed in the domain of social psychology as a measure of implicit evaluation. Participants in this task complete blocks of trials where they are asked to respond to categories and attributes (e.g., types of faces and types of words). Reaction times in different blocks sharing certain response combinations are averaged and then subtracted from blocks with other response combinations and then normalized, the result of which is taken as a measure indicating implicit evaluation toward or away from the given categories. One assumption of this approach is stationarity of response time distributions, or at a minimum, that temporal dynamics in response times are not theoretically relevant. Here we test these assumptions, examine the extent to which response times change within the IAT blocks and, if so, how trajectories of change are meaningful in relation to external measures. Using multiple data sets we demonstrate within-session changes in IAT scores. Further, we demonstrate that dissociable components in the trajectories of IAT performance may be linked to theoretically distinct processes of cognitive biases as well as behaviors. The present work presents evidence that IAT performance changes within the task, while future work is needed to fully assess the implications of these temporal dynamics.

Identifiers

PMID37758761
PMCPMC10533519
OpenAlexW4387078737

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.