Evidence map›Paper›PMID 36650826›Full record

ArticleSAGE open

Linguistic Analysis of Online Domestic Violence Testimonies in the Context of COVID-19.

Valentin L Buchner, Sharina Hamm, Barbara Medenica, Marc L Molendijk

Open access · goldAbstract read
In one paragraph

Article in SAGE open. 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
0.8field-weighted citation impact, top 30% 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, 3 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

4 authors at 1 institution in 1 country.

Valentin L BuchnerLeiden University, The Netherlands.ORCID https://orcid.org/0000-0002-1262-3016
Sharina HammLeiden University, The Netherlands.
Barbara MedenicaLeiden University, The Netherlands.
Marc L MolendijkLeiden University, The Netherlands.
Leiden University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Worldwide, an increase in cases and severity of domestic violence (DV) has been reported as a result of social distancing measures implemented to decrease the spreading of the Coronavirus Disease (COVID-19). As one's language can provide insight in one's mental health, this pre-registered study analyzed word use in a DV online support group, aiming to investigate the impact of the COVID-19 pandemic on DV victims in an ex post facto research design. Words reflecting social support and leisure activities were investigated as protective factors against linguistic indicators of depression in 5,856 posts from the r/domesticviolence subreddit and two neutral comparison subreddits (r/changemyview & r/femalefashionadvice). In the DV support group, the average number of daily posts increased significantly by 22% from pre- to mid-pandemic. Confirmatory analysis was conducted following a registered pre-analysis plan. DV victims used significantly more linguistic indicators of depression than individuals in the comparison groups. This did not change with the onset of COVID-19. The use of negative emotion words was negatively related to the use of social support words (Spearman's rho correlation coefficient [rho] = -0.110) and words referring to leisure activities (rho = -0.137). Pre-occupation with COVID-19 was associated with the use of negative emotion words (rho = 0.148). We conclude that language of DV victims is characterized by indicators of depression and this characteristic is stable over time. Concerns with COVID-19 could contribute to negative emotions, whereas social support and leisure activities could function to some degree as protective factors. A potential weakness of this study is its cross-sectional design and the lack of experimental control. Future studies could make use of natural language processing and other advanced methods of linguistic analysis to learn about the mental health of DV victims.

Indexed as

COVID-19domestic violenceleisurelinguistic analysismental healthRedditsocial support

Identifiers

PMID36650826
PMCPMC9834616
OpenAlexW4313908198

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.