Evidence map›Paper›PMID 33468085›Full record

ArticleBMC public health2021

The target/perpetrator brief-implicit association test (B-IAT): an implicit instrument for efficiently measuring discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age.

Maddalena Marini, Pamela D Waterman, Emry Breedlove, Jarvis T Chen, Christian Testa, Sari L Reisner, Dana J Pardee, Kenneth H Mayer, Nancy Krieger

Registry-linked trialAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07283523 (The Use of Virtual Reality to Combat Weight-Based Implicit Bias Among Physicians in Training at Brigham and Women's Hospital), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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.

NCT07283523 naenrolling by invitationnot on this mapstarted 2024, after this paper: background citation

The Use of Virtual Reality to Combat Weight-Based Implicit Bias Among Physicians in Training at Brigham and Women's Hospital: A Pilot Study

TypeinterventionalSponsorBrigham and Women's HospitalRan2024 to 2026Enrolled52ConditionsImplicit Bias, Implicit Association TestArms360 Video on a Virtual Reality Headset, 360-Control Video
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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

9 authors.

Maddalena MariniIstituto Italiano di Tecnologia, Ferrara, FE, Italy. Maddalena.Marini@iit.it.
Pamela D WatermanHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Emry BreedloveHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Jarvis T ChenHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Christian TestaHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Sari L ReisnerHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Dana J PardeeThe Fenway Institute, Boston, MA, USA.
Kenneth H MayerThe Fenway Institute, Boston, MA, USA.
Nancy KriegerHarvard T.H. Chan School of Public Health, Boston, MA, USA.

Funding

The impact of HIV viral diversity and cellular immunity on HIV pathogenesisP30AI060354 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ARTHUR Y KIM · 2004 to 2026
$94.4M
Advancing novel methods to measure and analyze multiple types of discrimination for population health researchR01MD012793 · NIMHD · HARVARD SCHOOL OF PUBLIC HEALTH · PI KRIEGER, NANCY · 2019 to 2023
$3.3M
Foundation for the National Institutes of Health #1R01MD012793-01A1NIAID NIH HHS P30 AI060354NIMHD NIH HHS R01 MD012793
6 · The paper itself

Abstract

backgroundTo 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.

methodsBetween 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.

resultsAmong 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.

conclusionsThis 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.

Indexed as

Gender IdentityRacismAdultEthnicityFemaleHeterosexualityHumansMaleSexual BehaviorAgeBrief implicit association test (B-IAT)DiscriminationGender identityImplicit association test (IAT)Implicit measuresRace/ethnicitySexSexual orientationWeight

Identifiers

PMID33468085
PMCPMC7814653

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.