Evidence map›Paper›PMID 36540419›Full record

ArticleResearch in social stratification and mobility2021

COVID-19-associated discrimination in Germany.

Jörg Dollmann, Irena Kogan

Open access · hybridAbstract read
In one paragraph

Article in Research in social stratification and mobility, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
7.7field-weighted citation impact, top 3% 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

6 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. [COVID-19-related self-stigma: association with vulnerability and trust in institutions].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2023
    Article
  4. Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Jörg DollmannUniversity of Mannheim, Mannheim Centre for European Social Research MZES, Postfach, 68131, Mannheim, Germany.
Irena KoganUniversity of Mannheim, Mannheim Centre for European Social Research MZES, Postfach, 68131, Mannheim, Germany.
University of Mannheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines whether ethnic minorities in general and Asian minorities in particular have perceived an increase in discrimination during the COVID-19 pandemic, a phenomenon known as COVID-19-associated discrimination (CAD). Drawing on the CILS4COVID data, which were collected among 3,517 individuals in the initial phase of the pandemic (mainly between April and June 2020), we demonstrate that especially Asian minorities (n = 80) report instances of CAD. Furthermore, CAD is reported more by Asian respondents residing in administrative districts that have been particularly affected by the COVID-19 pandemic, i.e., that had high seven-day COVID-19 incidence rates. Higher levels of perceived CAD are also reported by respondents originating from the Americas (n = 61) and the former Soviet Union (n = 197), but only in administrative districts with high incidence rates. We conclude that CAD reported by these groups is likely due to these groups being perceived to pose a higher threat of infection transmission. CAD reported by Asian-origin respondents is not entirely due to the actual threat posed by COVID-19, but rather to a mix of perceived threat, overt discrimination and the attribution of various negative experiences suffered since the outbreak of the pandemic to CAD.

Indexed as

AsiansCOVID-19COVID-19–associated discriminationGermanyIntergroup threat theory (ITT)Perceived discrimination

Identifiers

PMID36540419
PMCPMC9756773
OpenAlexW3184473434

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.