Evidence map›Paper›PMID 39761171›Full record

ReviewAnnals of the New York Academy of Sciences2025

Researching gender and loneliness differently.

Manuela Barreto, David Matthew Doyle, Marlies Maes

Abstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Researching gender and loneliness differently.Annals of the New York Academy of Sciences · 2025
    Review
  9. 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

3 authors.

Manuela BarretoDepartment of Psychology, University of Exeter, Exeter, UK.ORCID 0000-0002-6973-7233
David Matthew DoyleVUmc, Amsterdam UMC, Amsterdam, The Netherlands.
Marlies MaesSocial and Behavioural Sciences, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-1710-5728

Funding

H2020 European Research Council ERC-H2020 European Research Council StG 101042028
6 · The paper itself

Abstract

The majority of research on loneliness considers gender by comparing the loneliness reported by men and women. Drawing on current conceptualizations of gender and its effects, we propose alternative ways in which gender should be examined in relation to loneliness. To do so, we consider multiple gender-related factors and the role of the social environment, particularly societal ideologies about what gender is and how it should be expressed. We provide examples of how this expanded conceptualization can contribute to an improved understanding of loneliness by focusing on the impact of gender nonconformity, gendered life experiences, and couple relationships. We highlight the need for more research and evidence to fill existing gaps in understanding. We conclude that the field can move forward by considering the role of biological sex, gender identity, gender expression, gender roles, gender relational experiences, and sexual orientation, as well as the social norms against which these are experienced. To truly examine the role of gender in loneliness, we need to consider the normative context where some, but not others, are minoritized and marginalized, as well as move beyond binary notions of gender to include those with nonbinary, transgender, and intersex identities.

Indexed as

Gender IdentityGender RoleLonelinessFemaleHumansInterpersonal RelationsMalegendergender stereotypesintersexlonelinessnonconformitysocial stigmatransgender

Identifiers

PMID39761171
PMCPMC11829320

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.