Evidence map›Paper›PMID 41804371›Full record

ArticleRace and social problems2026

The Critical Role of Race-Conscious Framework in Advancing Mental Health Workforce Diversity: A Case Study.

Eric Kyere, Zohra Asad, Sadaaki Fukui

Abstract read
In one paragraph

Article in Race and social problems, 2026. 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
–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.

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.

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.

Eric KyereIndiana University School of Social Work, Adjunct Associate Professor of Africana Studies, Indiana University, Indianapolis 902 West New York Street, Indianapolis, IN 46202-5156 USA.ORCID 0000-0003-3998-6324
Zohra AsadIndiana University School of Social Work, 902 West New York Street, Indianapolis, IN 46202-5156 USA.
Sadaaki FukuiIndiana University School of Social Work, 902 West New York Street, Indianapolis, IN 46202-5156 USA.

Funding

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth ProfessionalsR34MH119411 · NIMH · INDIANA UNIVERSITY INDIANAPOLIS · PI FUKUI, SADAAKI · 2020 to 2022
$845k
NIMH NIH HHS R34 MH119411
6 · The paper itself

Abstract

backgroundA racially diverse mental health workforce has been suggested to address persistent racial disparities in mental health among racially minoritized service recipients. However, in a racialized society such as the United States, structural racism is shown to constrain mental health organizations' efforts to address disparities through workforce diversity. Theoretical Framework and Method: We recruited Black mental health workers (

resultsFindings were organized around five themes: (1) workforce diversity matters, (2) whiteness of the leadership as the perceptions of organizational diversity, and (3) the impact of the whiteness of leadership. Two related subthemes were identified from the third theme: (3a) racial task burdens and (3b) racial outsourcing. Discussion/Implications: Workforce diversity among racialized workers without focusing on how structural racism shape organizational processes are more likely to burden and exploit racial minority workers instead of promoting equity. Anti-racist work must move beyond a focus on individuals, as racist or bad actors, to target organizational procedures, operations, and resource allocation, which may have far greater consequences.

Indexed as

Mental health disparitiesRacialized organizationRacial outsourcingRacial task burdenStructural racismWorkforce diversity

Identifiers

PMID41804371
PMCPMC12967603

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.