Evidence map›Paper›PMID 40975649›Full record

ArticleSleep health2025

Ethnic and racial discrimination and sleep health among Asian American college students.

Jinjin Yan, Natasha C Johnson, Zhenqiang Zhao, Kyle Lorenzo, Heining Cham, Nidia Ruedas-Gracia, Mona El Sheikh, David H Chae, Tiffany Yip

Abstract read
In one paragraph

Article in Sleep health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jinjin YanDepartment of Psychology, Fordham University, Bronx, NY USA.
Natasha C JohnsonSchool of Social Work, Columbia University, New York, NY USA.
Zhenqiang ZhaoDepartment of Psychology, Fordham University, Bronx, NY USA.
Kyle LorenzoDepartment of Psychology, Fordham University, Bronx, NY USA.
Heining ChamDepartment of Psychology, Fordham University, Bronx, NY USA.
Nidia Ruedas-GraciaEducational Psychology, University of Illinois, Urbana-Champaign, IL USA.
Mona El SheikhDepartment of Human Development and Family Sciences, Auburn University, Auburn, AL USA.
David H ChaeCelia Scott Weatherhead School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA USA.
Tiffany YipDepartment of Psychology, Fordham University, Bronx, NY USA. Electronic address: tyip@fordham.edu.

Funding

Social-Environmental Predictors of Sleep Disparities During the Transition toCollegeR01MD015715 · NIMHD · FORDHAM UNIVERSITY · PI YIP, TIFFANY · 2021 to 2025
$3.2M
NIMHD NIH HHS R01 MD015715
6 · The paper itself

Abstract

objectivesSleep health is increasingly recognized as a key factor influencing college students' well-being. However, research remains limited on the ethnic and racial discrimination experiences (both indirect and direct discrimination) that shape sleep health in Asian American college students. This study investigated daily associations between discrimination and sleep among Asian American students.

methodsParticipants were 168 Asian American first-year college students (Mage = 18.38 years, SD = 0.41; 65.5% female) in the northeastern United States. Over a 14-day period, self-reported direct ethnic and racial discrimination, indirect discrimination (i.e., vicarious racism), and actigraphy-measured sleep outcomes were assessed.

resultsAt the within-person level, on days when Asian American students reported higher-than-usual levels of ethnic and racial discrimination, they woke up earlier (b = -0.487, p = .050) and got out of bed earlier (b = -0.543, p = .006). However, at the between-person level, students with higher levels of direct discrimination woke up later (b = 1.571, p = .045) and got out of bed later (b = 1.769, p = .024). Students with higher levels of indirect discrimination had lower sleep efficiency (b = -16.809, p = .031), more WASO (b = 39.011, p = .021) and shorter sleep duration (b = -157.211, p = .024).

conclusionsBoth direct and indirect discrimination are critical social determinants of sleep health among Asian American college students. This study offers insights to guide culturally tailored institution-level policies that promote sleep health among Asian American college students during this crucial transicition.

Indexed as

AsianRacismSleepStudentsActigraphyAdolescentFemaleHumansMaleUniversitiesYoung AdultAsian AmericanDiscriminationOut of bed timeWake time

Identifiers

PMID40975649
PMCPMC12453594

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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.