Evidence map›Paper›PMID 36586184›Full record

ArticleSocial science & medicine (1982)2023

Educational gradient in social network changes at disease diagnosis.

Won-Tak Joo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Social science & medicine (1982), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Won-Tak JooDepartment of Demography, University of California, Berkeley, 328 Social Sciences Building, Berkeley, CA, 94720, USA. Electronic address: wontak.joo@berkeley.edu.

Funding

Program Development (Pilot)P30AG012839 · NIA · UNIVERSITY OF CALIFORNIA BERKELEY · PI Magali Barbieri · 1999 to 2026
$18.6M
Statistical Data Enclave CoreP30AG017266 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1999 to 2026
$17.0M
Center for Demography and EcologyR24HD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI RAYMO, JAMES M · 2004 to 2013
$7.2M
Scientific and Technical CoreP2CHD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Katherine J. Curtis · 2014 to 2026
$5.1M
Dev-Core-001P2CHD073964 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI JOSHUA R. GOLDSTEIN · 2019 to 2026
$2.9M
CenSoc: A New, Public, Individual-level Dataset for Studying Mortality InequalityR01AG058940 · NIA · UNIVERSITY OF CALIFORNIA BERKELEY · PI GOLDSTEIN, JOSHUA R. · 2019 to 2023
$2.9M
Berkeley Population CenterR24HD073964 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI HOUT, MICHAEL · 2014 to 2017
$466k
NIA NIH HHS P30 AG012839NIA NIH HHS P30 AG017266NIA NIH HHS R01 AG058940NICHD NIH HHS P2C HD047873NICHD NIH HHS P2C HD073964NICHD NIH HHS R24 HD047873NICHD NIH HHS R24 HD073964
6 · The paper itself

Abstract

This study examines the educational gradient in social network changes following the diagnosis of new chronic diseases. Using a representative sample of the US older population, the author shows that the network size and amount of health-related discussion with social network members increased only for older adults with a bachelor's degree. Tie-level analyses reveal that such increase is from the activation of health discussion with the existing social network members, but not from the changes in discussion partners. These results suggest that heterogeneous temporal dynamics in social networks may be one mechanism that shapes diverging health trajectories in later life.

Indexed as

AgingSocial ChangeAgedEducational StatusHumansSocial NetworkingSocial SupportAgingChronic diseasesDiscussion networksHealth disparitiesNetwork activation

Identifiers

PMID36586184
PMCPMC10039803

What OpenQuestion holds

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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.