Evidence map›Paper›PMID 38125758›Full record

ArticleFrontiers in digital health2023

Gender in the disclosure of loneliness on Twitter during COVID-19 lockdowns.

Yelena Mejova, Anya Hommadova Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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 2 institutions in 2 countries.

Yelena MejovaISI Foundation, Turin, Italy.
Anya Hommadova LuCommunication Studies, Sam Houston State University, Huntsville, TX, United States.
Institute for Scientific Interchange · ITSam Houston State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Loneliness has been shown to affect both mental and physical health, and was a major concern even before the COVID-19 pandemic. During the COVID-19 distancing measures, millions of people took to social media to express their feelings and seek social support. Methods: In this mixed-methods study, we examine the self-disclosure of loneliness by users identifying as male or female (via self-disclosed naming conventions) on Twitter before and during the COVID-19 "lockdowns." Results: We show that in the first two months of COVID-19 restrictions, self-disclosure of loneliness on this platform rose dramatically, and also have changed qualitatively. We find that female accounts tend to post more loneliness self-disclosures compared to male ones, even before COVID. Female disclosures more often center around pregnancy, family, and close relationships, whereas those posted by the male ones are more related to leadership, video gaming and sex. During COVID lockdowns, female accounts turn to online messaging apps and hobbies, and male become increasingly vocal in seeking partners. Discussion: The insights of this study have important implications for the design of interventions for lessening the burden of loneliness in the current digitized world.

Indexed as

computer mediated communicationCOVID-19genderlockdownslonelinessself-disclosuresocial media

Identifiers

PMID38125758
PMCPMC10731375
OpenAlexW4389393169

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.