Evidence map›Paper›PMID 40821959›Full record

ArticleSociological inquiry2025

Anticipatory Race-Related Stress and Depressive Symptoms among U.S. Black Women Attending A Historically Black University: Are Psychosocial Resources Stress Buffers?

Christy L Erving, Tiffany R Williams, Alexander J Holt, Aigné Taylor

Abstract read
In one paragraph

Article in Sociological inquiry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Christy L ErvingDepartment of Sociology, Population Research Center, The University of Texas at Austin.
Tiffany R WilliamsDepartment of Psychological Sciences and Counseling, Tennessee State University.
Alexander J HoltDepartment of Sociology, The University of Texas at Austin.
Aigné TaylorDepartment of Political Science & History, Department of Social Work & Sociology, North Carolina Agricultural & Technical State University.

Funding

Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
NICHD NIH HHS P2C HD042849
6 · The paper itself

Abstract

In an era of police brutality and the Black Lives Matter movement, many Black Americans believe that racism is a mainstay of U.S. culture. Even if not experiencing racial threats or violence directly, racial tension can induce stress via anticipatory race-related stress (ARRS). Drawing from theories of social stress and the intersectionality framework, this study examined the association between ARRS and depressive symptoms among Black women attending a historically Black university (N = 207). Second, we investigated whether psychosocial resources (mastery, resilience, self-esteem, social support) moderated the association between ARRS and depressive symptoms. Study results revealed that anticipatory race-related stress was positively associated with depressive symptoms. Mastery and resilience moderated the association between anticipatory race-related stress and depressive symptoms; that is, the association between ARRS and depressive symptoms was weaker for those with elevated levels of mastery and resilience. In sum, building resilience and mastery among Black women may be effective coping strategies for combatting anticipatory race-related stress. However, dismantling structural racism is necessary to eliminate the anticipation of racism.

Indexed as

anticipatory stressBlack womendepressive symptomsmasteryresilience

Identifiers

PMID40821959
PMCPMC12356155

What OpenQuestion holds

Textmetadata
LicenceTDM
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.