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Record W4406670764 · doi:10.1037/cdp0000731

Mindfulness as a moderator of associations between intergroup bias and psychological health: A scoping review.

2025· article· en· W4406670764 on OpenAlexaff
Marina M. Doucerain, Sarah Benkirane

Bibliographic record

VenueCultural Diversity & Ethnic Minority Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyMindfulnessModerationClinical psychologyMeta-analysisMental healthPsychotherapistSocial psychologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The health repercussions of intergroup bias on members of minoritized groups are massive. This scoping review examines the available peer-reviewed evidence on mindfulness as a moderator of associations between intergroup bias and psychological health indicators. METHOD: Peer-reviewed studies of mindfulness moderating associations between intergroup bias and psychological health indicators through May 2024 were surveyed, with no limitations in terms of intergroup bias variety, study context, participants' characteristics, or date of publication. Sixteen articles were eligible and reviewed. RESULTS: Trait mindfulness moderated negative associations between intergroup bias and psychological health indicators in most studies reviewed, such that the associations are reduced or disappear at high, compared to low, levels of trait mindfulness. CONCLUSIONS: Important caveats of this protective role of mindfulness are discussed, such as the lack of diversity in mindfulness research and interventions, and the potentially silencing effect of mindfulness as construed in mainstream Western contexts. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.261
GPT teacher head0.489
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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