Evidence map›Paper›PMID 34019478›Full record

ArticleJMIR public health and surveillance2021

A Rapid Assessment of the Impact of COVID-19 on Asian Americans: Cross-sectional Survey Study.

Thu Quach, Lan N Ðoàn, Julia Liou, Ninez A Ponce

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
7.4field-weighted citation impact, top 2% of its field
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Pooled it
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  17. Trauma and US Minority Children and Youth.Current psychiatry reports · 2022
    Review
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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 at 3 institutions in 1 country.

Thu Quach *Asian Health Services, Oakland, CA, United States.ORCID 0000-0001-8155-4336
Lan N ÐoànDepartment of Population Health Section for Health Equity, New York University Grossman School of Medicine, New York, NY, United States.ORCID 0000-0003-1826-4728
Julia LiouAsian Health Services, Oakland, CA, United States.ORCID 0000-0002-0482-9639
Ninez A PonceDepartment of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.ORCID 0000-0001-5151-6718
Asian Health Services · USNew York University · USUniversity of California, Los Angeles · US

Funding

Scaling Community-Clinical Linkage Models to Address Diabetes and Hypertension Disparities in the Southeastern U.S.U54MD000538 · NIMHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI TRINH-SHEVRIN, CHAU · 2017 to 2022
$11.3M
NIMHD NIH HHS U54 MD000538
6 · The paper itself

Abstract

backgroundThe diverse Asian American population has been impacted by the COVID-19 pandemic, but due to limited data and other factors, disparities experienced by this population are hidden.

objectiveThis study aims to describe the Asian American community's experiences during the COVID-19 pandemic, focusing on the Greater San Francisco Bay Area, California, and to better inform a Federally Qualified Health Center's (FQHC) health care services and response to challenges faced by the community.

methodsWe conducted a cross-sectional survey between May 20 and June 23, 2020, using a multipronged recruitment approach, including word-of-mouth, FQHC patient appointments, and social media posts. The survey was self-administered online or administered over the phone by FQHC staff in English, Cantonese, Mandarin, and Vietnamese. Survey question topics included COVID-19 testing and preventative behaviors, economic impacts of COVID-19, experience with perceived mistreatment due to their race/ethnicity, and mental health challenges.

resultsAmong 1297 Asian American respondents, only 3.1% (39/1273) had previously been tested for COVID-19, and 46.6% (392/841) stated that they could not find a place to get tested. In addition, about two-thirds of respondents (477/707) reported feeling stressed, and 22.6% (160/707) reported feeling depressed. Furthermore, 5.6% (72/1275) of respondents reported being treated unfairly because of their race/ethnicity. Among respondents who experienced economic impacts from COVID-19, 32.2% (246/763) had lost their regular jobs and 22.5% (172/763) had reduced hours or reduced income. Additionally, 70.1% (890/1269) of respondents shared that they avoid leaving their home to go to public places (eg, grocery stores, church, and school).

conclusionsWe found that Asian Americans had lower levels of COVID-19 testing and limited access to testing, a high prevalence of mental health issues and economic impacts, and a high prevalence of risk-avoidant behaviors (eg, not leaving the house) in the early months of the COVID-19 pandemic. These findings provide preliminary insights into the impact of the COVID-19 pandemic on Asian American communities served by an FQHC and underscore the longstanding need for culturally and linguistically appropriate approaches to providing mental health, outreach, and education services. These findings led to the establishment of the first Asian multilingual and multicultural COVID-19 testing sites in the local area where the study was conducted, and laid the groundwork for subsequent COVID-19 programs, specifically contact tracing and vaccination programs.

Indexed as

PandemicsRisk Reduction BehaviorAdolescentAdultAgedAsianChildCOVID-19COVID-19 TestingCross-Sectional StudiesFemaleHealthcare DisparitiesHumansMaleMental DisordersMiddle Agedanti-Asian violenceAsian AmericanbarrierbehaviorCOVIDCOVID-19culturediscriminationdisparityexperienceimpactinequalitymental healthstresstestingviolence

Identifiers

PMID34019478
PMCPMC8202653
OpenAlexW3163465017

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.