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

Nature Human Behaviour volume 7, pages 1740–1752 (2023)Cite this article

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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.

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Fig. 1: Comparison of demographics between Arab Barometer and experimental sample respondents.
Fig. 2: Treatment effects on TV show consumption, Facebook and WhatsApp treatment consumption, and knowledge of resources delivered in treatment.
Fig. 3: Treatment effects on attitudes towards gender and marital equality and towards sexual violence.
Fig. 4: Treatment effects on violence experienced during COVID-19 and hypothetical and recent use of online resources or contact with a support organization when responding to domestic or sexual violence.
Fig. 5: Treatment effects on women’s future outlook towards gender and marital equality.
Fig. 6: Comparison of attitudes and behaviour between Arab Barometer and experimental sample respondents.

Data availability

All the data used in this research, including de-identified baseline and endline survey data, server data on server visits, YouTube channel views, and supplementary Google Mobility data (https://www.google.com/covid19/mobility/), are available in the Harvard Dataverse repository, https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/VFFZRM. These include the de-identified original and derived datasets.

Code availability

All the code developed by the authors using the statistical software R for data construction and analysis (that is, to generate figures, tables and other summary statistics) is available in the Harvard Dataverse repository: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/VFFZRM.

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Acknowledgements

N. Muhab provided invaluable assistance in the design and implementation of the project. Z. Asal, S. Eid and H. Hegazy provided excellent research assistance. A. El-Kayaty, J. Marshall, A. Nagy, M. Shalaby, and conference, seminar and workshop participants at the American Political Science Association 2021 Conference, the Institute for Advanced Study in Toulouse, the Joint Initiative for Latin American Experimental Economics, MIT’s Political Experiments Research Lab and Global Diversity Lab, and Toulouse School of Economics provided useful feedback. H.L. acknowledges funding from the French Agence Nationale de la Recherche under the Investissement d’Avenir programme ANR-17-EURE-0010. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. SSRC, IDSS and Department of Political Science, MIT, Cambridge, MA, USA

    Fotini Christia

  2. Departments of Economics and Political Science, Instituto Tecnológico Autónomo de México, Mexico City, Mexico

    Horacio Larreguy

  3. Department of Political Science, MIT, Cambridge, MA, USA

    Elizabeth Parker-Magyar

  4. Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, UK

    Manuel Quintero

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  1. Fotini Christia
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Contributions

F.C., H.L. and E.P.-M. developed and designed the experiment and oversaw and conducted the data collection. F.C., H.L., E.P.-M. and M.Q. devised the statistical analyses. E.P.-M. and M.Q. wrote the analysis code. M.Q. performed the statistical analyses. All authors wrote the manuscript, provided revisions and finalized the text.

Corresponding author

Correspondence to Horacio Larreguy.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Survey responses by Egyptian Governorate.

The graph shows the distribution of survey responses by governorate, with Cairo having the highest frequency of responses at 2341. The median governorates are Luxor and Bahera, with 37 and 42 responses, respectively. Matrouh had the lowest number of responses, with only one respondent. The survey data was collected and analyzed by our team. Adapted from the Humanitarian Data Exchange under a CC BY 4.0 licence.

Extended Data Fig. 2 Number of treatment web pages visited per web page user across treatments.

Panel (a) shows the total number of visits to the server hosting videos and YouTube videos for the 14 pages/videos delivered. Panel (b) shows the number of visits for the Facebook treatment group, panel (c) for the WhatsApp individual treatment group, and panel (d) for the WhatsApp group pages. For more detailed results, refer to Extended Data Tables 4 and 5.

Extended Data Fig. 3 Video landing web page visits for Facebook and WhatsApp Individual treatment before and after participants assigned to the Facebook treatment were shifted to the WhatsApp Individual treatment.

Difference-in-differences analysis of the impact of transitioning the Facebook treatment group from receiving videos on Facebook to receiving videos via WhatsApp. The left panel shows the distribution shift in the total number of video views before and after the transition for the Facebook treatment group. The right panel compares the same distribution shift for the WhatsApp individual treatment group. Analyzing the distribution shift helps us understand the relative effectiveness of Facebook vis-a-vis WhatsApp.

Extended Data Fig. 4 Mobility in Egypt during the intervention.

We plot the daily percent change in mobility relative to the prior to the COVID-19 pandemic across different industries (panel (a) is Retail and recreation, panel (b) grocery and pharmacy, panel (c) parks, panel (d) transit stations, panel (e) workplaces, and panel (f) residential) in Egypt during the first year of the COVID-19 pandemic. Vertical lines demarcate the intervention, which ran from July 10, 2020, to September 05, 2020. All data comes from Google Mobility public data.

Extended Data Table 1 Content of videos hosted on the website and delivered via message
Full size table
Extended Data Table 2 Content of TV shows hosted on satellite channel
Full size table
Extended Data Table 3 Block sizes, treatment probabilities and responses rates by treatment assignment
Full size table
Extended Data Table 4 Unique Ips, users, visits, and average visit time by treatment assignment
Full size table
Extended Data Table 5 Website and YouTube analytics
Full size table

Supplementary information

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Christia, F., Larreguy, H., Parker-Magyar, E. et al. Empowering women facing gender-based violence amid COVID-19 through media campaigns. Nat Hum Behav 7, 1740–1752 (2023). https://doi.org/10.1038/s41562-023-01665-y

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