Evidence map›Paper›PMID 37550411›Full record

Trial reportNature human behaviour2023

Empowering women facing gender-based violence amid COVID-19 through media campaigns.

Fotini Christia, Horacio Larreguy, Elizabeth Parker-Magyar, Manuel Quintero

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Preventing gender-based violence: A global imperative.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    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.

Fotini ChristiaSSRC, IDSS and Department of Political Science, MIT, Cambridge, MA, USA.ORCID 0000-0003-1076-9879
Horacio LarreguyDepartments of Economics and Political Science, Instituto Tecnológico Autónomo de México, Mexico City, Mexico. horacio.larreguy@itam.mx.ORCID 0000-0001-8491-6400
Elizabeth Parker-MagyarDepartment of Political Science, MIT, Cambridge, MA, USA.ORCID 0000-0002-2732-369X
Manuel QuinteroDepartment of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK.ORCID 0000-0003-1615-930X

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-17-EURE-0010
6 · The paper itself

Abstract

COVID-19 heightened women's exposure to gender-based and intimate partner violence, especially in low-income and middle-income countries. We tested whether edutainment interventions shown to successfully combat gender-based and intimate partner violence when delivered in person can be effectively delivered using social (WhatsApp and Facebook) and traditional (TV) media. To do so, we randomized the mode of implementation of an intervention conducted by an Egyptian women's rights organization seeking to support women amid COVID-19 social distancing. We found WhatsApp to be more effective in delivering the intervention than Facebook but no credible evidence of differences across outcomes between social media and TV dissemination. Our findings show little credible evidence that these campaigns affected women's attitudes towards gender or marital equality or on the justifiability of violence. However, the campaign did increase women's knowledge, hypothetical use and reported use of available resources.

Indexed as

COVID-19Gender-Based ViolenceIntimate Partner ViolenceSocial MediaAdultEgyptEmpowermentFemaleHumansSARS-CoV-2Women's RightsYoung Adult

Identifiers

What OpenQuestion holds

Textmetadata
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.