Evidence map›Paper›PMID 35400385›Full record

ArticleSocial science research2022

Everyday discrimination in later life: A social network approach.

Alyssa W Goldman

Abstract read
In one paragraph

Article in Social science research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Alyssa W GoldmanDepartment of Sociology, Boston College, 140 Commonwealth Avenue, 424 McGuinn Hall, Chestnut Hill, MA, 02467, USA. Electronic address: alyssa.goldman@bc.edu.

Funding

National Social Life, Health, and Aging Project: Round 5R01AG048511 · NIA · NATIONAL OPINION RESEARCH CENTER · PI LINDA J WAITE · 2014 to 2026
$49.5M
National Social Life, Health and Aging: Wave 4R01AG043538 · NIA · NATIONAL OPINION RESEARCH CENTER · PI LINDA J WAITE · 2013 to 2026
$42.7M
National Social Life, Health, and Aging Project: Anaylsis of Wave 1 and Wave 2R37AG030481 · NIA · NATIONAL OPINION RESEARCH CENTER · PI WAITE, LINDA J · 2008 to 2017
$15.4M
NSHAP Wave II Partner Data CollectionR01AG033903 · NIA · NATIONAL OPINION RESEARCH CENTER · PI WAITE, LINDA J · 2009 to 2013
$5.8M
NIA NIH HHS R01 AG033903NIA NIH HHS R01 AG043538NIA NIH HHS R01 AG048511NIA NIH HHS R37 AG030481
6 · The paper itself

Abstract

What factors shape everyday discrimination among older adults? Existing perspectives focus on individual identities and social group membership (e.g., race/ethnicity, age) as key determinants of perceived discrimination. This paper examines the idea that individuals' broader social contexts - including their personal social networks - also shape perceived discrimination, and in ways that may differ across racial groups. Using data from Round 3 of the National Social Life, Health, and Aging Project (N = 3312), I consider how properties of personal networks are associated with how frequently older adults report everyday discrimination. Results indicate that more kin-centric personal networks protect against more frequent everyday discrimination, but that this protective effect may be stronger among White older adults. I propose why more kin-centric networks may play a different role in the perceived discrimination of White and Black older adults, and close by suggesting that social network composition may be a source of heterogeneity in the link between everyday discrimination and inequality in later life outcomes such as health.

Indexed as

EthnicityRacismAgedHumansRacial GroupsSocial NetworkingAgeismAgingEveryday discriminationKinLife courseRace/ethnicityRacismSocial networks

Identifiers

PMID35400385
PMCPMC9001990

What OpenQuestion holds

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Registered trials

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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.