Evidence map›Paper›PMID 35907120›Full record

ArticleThe patient2022

Opportunities to Improve Long COVID Care: Implications from Semi-structured Interviews with Black Patients.

Rachel S Bergmans, Keiyana Chambers-Peeple, Deena Aboul-Hassan, Samantha Dell'Imperio, Allie Martin, Riley Wegryn-Jones, Lillian Z Xiao, Christine Yu, David A Williams, Daniel J Clauw and 1 more

Abstract read
In one paragraph

Article in The patient, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

11 authors.

Rachel S BergmansDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA. rbergs@med.umich.edu.ORCID 0000-0001-5740-6691
Keiyana Chambers-PeepleDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA.
Deena Aboul-HassanCollege of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA.
Samantha Dell'ImperioDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA.
Allie MartinDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA.
Riley Wegryn-JonesCollege of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA.
Lillian Z XiaoCollege of Pharmacy, University of Michigan, Ann Arbor, MI, USA.
Christine YuCollege of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, USA.
David A WilliamsDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA.
Daniel J ClauwDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Medical School, Ann Arbor, MI, USA.ORCID 0000-0002-8114-7818
Melissa DeJonckheereDepartment of Family Medicine, University of Michigan, Medical School, Ann Arbor, MI, USA.ORCID 0000-0002-2660-3358

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
TRAINING OF ARTHRITIS RESEARCH SCIENTISTST32AR007080 · NIAMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jason Knight · 1986 to 2026
$6.3M
NIAMS NIH HHS T32 AR007080NIEHS NIH HHS P30 ES017885
6 · The paper itself

Abstract

backgroundLong coronavirus disease (COVID) is an emerging condition that could considerably burden healthcare systems. Prior qualitative studies characterize the experience of having long COVID, which is valuable for informing care strategies. However, evidence comes from predominantly White samples. This is a concern because underrepresentation of Black patients in research and intervention development contribute to racial inequities.

objectiveTo facilitate racial equity in long COVID care, the purpose of this qualitative study was to inform the development of care strategies that are responsive to the experiences and perspectives of Black patients with long COVID in the United States of America.

methodsUsing convenience sampling, we conducted race-concordant, semi-structured, and open-ended interviews with Black adults (80% female, mean age = 39) who had long COVID. We transcribed and anonymized the recorded interviews. We analyzed the transcripts using inductive, thematic analysis. Theme development focused on who can help or hinder strategies for reducing health inequities, what should be done to change care policies or treatment strategies, and when are the critical timepoints for intervention.

resultsWe developed four main themes. Participants reported challenges before and after COVID testing. Many participants contacted primary care physicians as a first step for long COVID treatment. However, not all respondents had positive experiences and at times felt dismissed. Without a qualifying diagnosis, participants could not obtain disability benefits, which negatively influenced their employment and increased financial hardship.

conclusionsThere are possible targets for improving long COVID care, from COVID testing through to long-term treatment plans. There is a need to increase long COVID awareness among physicians. Diagnosis and a standardized treatment plan could help patients avoid unnecessary healthcare utilization and obtain comprehensive support.

Indexed as

COVID-19PhysiciansAdultBlack or African AmericanBlack PeopleCOVID-19 TestingFemaleHumansMalePost-Acute COVID-19 SyndromeQualitative ResearchUnited States

Identifiers

PMID35907120
PMCPMC9362503

What OpenQuestion holds

Textmetadata
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.