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Does stereotype threat affect test performance of minorities and women? A meta-analysis of experimental evidence.
Abstract
A meta-analysis of stereotype threat effects was conducted and an overall mean effect size of |.26| was found, but true moderator effects existed. A series of hierarchical moderator analyses evidenced differential effects of race- versus gender-based stereotypes. Women experienced smaller performance decrements than did minorities when tests were difficult: mean ds = |.36| and |.43|, respectively. For women, subtle threat-activating cues produced the largest effect, followed by blatant and moderately explicit cues: ds = |.24|, |.18|, and |.17|, respectively; explicit threat-removal strategies were more effective in reducing stereotype threat effects than subtle ones: ds = |.14| and |.33|, respectively. For minorities, moderately explicit stereotype threat-activating cues produced the largest effect, followed by blatant and subtle cues: ds = |.64|, |.41|, and |.22|, respectively; explicit removal strategies enhanced stereotype threat effects compared with subtle strategies: ds = |.80| and |.34|, respectively. In addition, stereotype threat affected moderately math-identified women more severely than highly math-identified women: ds = |.52| and |.29|, respectively; low math-identified women suffered the least from stereotype threat: d= |.11|. Theoretical and practical implications of these findings are discussed.
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“even though the initial studies on stereotype threat found statistically significant effects (Nguyen and Ryan [2008]), subsequent re-analyses (Zigerell [2017]), and other studies failed to replicate them (Finnigan and Corker [2016]; Flore et al. [2019]).”
From Science Communication and the Problematic Impact of Descriptive Norms (2023) · cites this paper as Nguyen and Ryan [2008]
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Cited work 10.1037/0022-3514.91.2.243 · retracted 2013-01-01 · notice 10.1037/a0031270 · this paper published 2008
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Cited work 10.1002/ejsp.310 · retracted 2012-10-05 · notice 10.1002/ejsp.1919 · this paper published 2008
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Metadata
- Authors
- Nguyen, H.-H. D., & Ryan, A. M.
- Affiliations
- California State University, Long Beach (US)
- Michigan State University (US)
- ORCID
- Ryan, Ann Marie
- Venue
- Journal of Applied Psychology
- Published
- 2008
- Volume
- 93
- Issue
- 6
- Pages
- 1314-1334
- ISSN
- 0021-9010 (ISSN-L)
- 1939-1854
- OpenAlex
- W2170594921
- Cited by
- 913
- References
- 124
- Citations by year
- 2026: 27 · 2025: 38 · 2024: 50 · 2023: 38 · 2022: 73 · 2021: 74 · 2020: 72 · 2019: 81 · 2018: 68 · 2017: 82 · 2016: 55 · 2015: 56 · 2014: 54 · 2013: 44 · 2012: 41
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Applied Psychology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Michigan State University
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Developmental and Educational Psychology › Education, Achievement, and Giftedness
- Social Sciences › Psychology › Applied Psychology › Career Development and Diversity
- Keywords
- stereotype threat, test performance, women, racial minorities, gender stereotypes, racial stereotypes
- MeSH terms
- Affect, Employee Performance Appraisal, Female, Humans, Male, Minority Groups, Psychological Tests, Stereotyping
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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