Evidence map›Paper›PMID 35355276›Full record

ArticleJournal of community psychology2022

Intersectional social identities and loneliness: Evidence from a municipality in Switzerland.

Yang Li, Dario Spini

Abstract read
In one paragraph

Article in Journal of community psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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.

Yang LiNational Centre of Competence in Life Course Research LIVES, Institute of Social Sciences, University of Lausanne, Lausanne, Switzerland.
Dario SpiniNational Centre of Competence in Life Course Research LIVES, Institute of Social Sciences, University of Lausanne, Lausanne, Switzerland.

Funding

Swiss National Science Foundation 51NF40-185901
6 · The paper itself

Abstract

We examined the extent to which intersectional social identities combine to shape risks of loneliness and identified the specific social clusters that are most at risk of loneliness for more precise and targeted interventions to reduce loneliness in a Swiss municipality. Based on data collected using participatory action research, we used the novel multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to estimate the predictive power of intersectional social attributes on risk of loneliness. We found that 56% of the between-strata variance was captured by intersectional interaction but was not explained by the additive effect of social identities. We also found that nationality and education had the strongest predictive power for loneliness. Interventions to reduce loneliness may benefit from understanding the resident population's intersectional identities given that individuals with the same combinations of social identities face a common set of social exposures relating to loneliness.

Indexed as

LonelinessSocial IdentificationEducational StatusHumansMultilevel AnalysisSwitzerlandcommunity interventionintersectionalitymultilevel modelingparticipatory action researchsocial and emotional isolationsocial identitystratification

Identifiers

PMID35355276
PMCPMC9544721

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.