IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0240005.html
   My bibliography  Save this article

Countering misinformation via WhatsApp: Preliminary evidence from the COVID-19 pandemic in Zimbabwe

Author

Listed:
  • Jeremy Bowles
  • Horacio Larreguy
  • Shelley Liu

Abstract

We examine how information from trusted social media sources can shape knowledge and behavior when misinformation and mistrust are widespread. In the context of the COVID-19 pandemic in Zimbabwe, we partnered with a trusted civil society organization to randomize the timing of the dissemination of messages aimed at targeting misinformation about the virus to 27,000 newsletter WhatsApp subscribers. We examine how exposure to these messages affects individuals’ beliefs about how to deal with the virus and preventative behavior. In a survey of 864 survey respondents, we find a 0.26σ increase in knowledge about COVID-19 as measured by responses to factual questions. Through a list experiment embedded in the survey, we further find that potentially harmful behavior—not abiding by lockdown guidelines—decreased by 30 percentage points. The results show that social media messaging from trusted sources may have substantively large effects not only on individuals’ knowledge but also ultimately on related behavior.

Suggested Citation

  • Jeremy Bowles & Horacio Larreguy & Shelley Liu, 2020. "Countering misinformation via WhatsApp: Preliminary evidence from the COVID-19 pandemic in Zimbabwe," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-11, October.
    • Handle: RePEc:plo:pone00:0240005
    DOI: 10.1371/journal.pone.0240005
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240005
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0240005&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0240005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kosuke Imai & Gary King & Elizabeth A. Stuart, 2008. "Misunderstandings between experimentalists and observationalists about causal inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 481-502, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Goette, Lorenz & Tripodi, Egon, 2024. "The limits of social recognition: Experimental evidence from blood donors," Journal of Public Economics, Elsevier, vol. 231(C).
    2. Armand, Alex & Augsburg, Britta & Bancalari, Antonella & Kameshwara, Kalyan Kumar, 2022. "Social Proximity and Misinformation: Experimental Evidence from a Mobile Phone-Based Campaign in India," CEPR Discussion Papers 16492, C.E.P.R. Discussion Papers.
    3. Armand, Alex & Augsburg, Britta & Bancalari, Antonella & Kameshwara, Kalyan Kumar, 2024. "Religious proximity and misinformation: Experimental evidence from a mobile phone-based campaign in India," Journal of Health Economics, Elsevier, vol. 96(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marco Caliendo & Stefan Tübbicke, 2020. "New evidence on long-term effects of start-up subsidies: matching estimates and their robustness," Empirical Economics, Springer, vol. 59(4), pages 1605-1631, October.
    2. Christoph Dworschak, 2024. "Bias mitigation in empirical peace and conflict studies: A short primer on posttreatment variables," Journal of Peace Research, Peace Research Institute Oslo, vol. 61(3), pages 462-476, May.
    3. Wendy Chan, 2018. "Applications of Small Area Estimation to Generalization With Subclassification by Propensity Scores," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 182-224, April.
    4. Jasjeet Singh Sekhon & Richard D. Grieve, 2012. "A matching method for improving covariate balance in cost‐effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 695-714, June.
    5. Solomon Asfaw & Silvio Daidone & Benjamin Davis & Josh Dewbre & Alessandro Romeo & Paul Winters & Katia Covarrubias & Habiba Djebbari, 2012. "Analytical Framework for Evaluating the Productive Impact of Cash Transfer Programmes on Household Behaviour – Methodological Guidelines for the From Protection to Production Project," Working Papers 101, International Policy Centre for Inclusive Growth.
    6. Weneyam Hippolyte Balima & Jean-Louis Combes & Alexandru Minea, 2015. "Sovereign Debt Risk in Emerging Countries: Does Inflation Targeting Adoption Make Any Difference?," CERDI Working papers halshs-01128239, HAL.
    7. Shen, Chung-Hua & Wu, Meng-Wen & Chen, Ting-Hsuan & Fang, Hao, 2016. "To engage or not to engage in corporate social responsibility: Empirical evidence from global banking sector," Economic Modelling, Elsevier, vol. 55(C), pages 207-225.
    8. Mareike Heimeshoff & Jonas Schreyögg & Oliver Tiemann, 2014. "Employment effects of hospital privatization in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 747-757, September.
    9. James B. Kau & Lu Fang & Henry J. Munneke, 2019. "An Unintended Consequence of Mortgage Financing Regulation – a Racial Disparity," The Journal of Real Estate Finance and Economics, Springer, vol. 59(4), pages 549-588, November.
    10. Ragni, Alessandra & Ippolito, Daniel & Masci, Chiara, 2024. "Assessing the impact of hybrid teaching on students’ academic performance via multilevel propensity score-based techniques," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    11. Srhoj, Stjepan & Walde, Janette, 2020. "Getting ready for EU Single Market: The effect of export-oriented grant schemes on firm performance," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 279-293.
    12. Geraldo, Pablo, 2024. "Credible causal inference beyond toy models," SocArXiv x4526_v1, Center for Open Science.
    13. Berta, Paolo & Callea, Giuditta & Martini, Gianmaria & Vittadini, Giorgio, 2010. "The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation," Economic Modelling, Elsevier, vol. 27(4), pages 812-821, July.
    14. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
    15. Maurizio Canavari & Andreas C. Drichoutis & Jayson L. Lusk & Rodolfo M. Nayga, Jr., 2018. "How to run an experimental auction: A review of recent advances," Working Papers 2018-5, Agricultural University of Athens, Department Of Agricultural Economics.
    16. Moreno-Serra R, "undated". "Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil," Health, Econometrics and Data Group (HEDG) Working Papers 09/05, HEDG, c/o Department of Economics, University of York.
    17. Tingting Zhou & Michael R. Elliott & Roderick J. A. Little, 2022. "Addressing Disparities in the Propensity Score Distributions for Treatment Comparisons from Observational Studies," Stats, MDPI, vol. 5(4), pages 1-17, December.
    18. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LLC, vol. 9(4), pages 524-546, December.
    19. Arndt R. Reichert, 2015. "Obesity, Weight Loss, and Employment Prospects: Evidence from a Randomized Trial," Journal of Human Resources, University of Wisconsin Press, vol. 50(3), pages 759-810.
    20. Luca Zanin & Rosalba Radice & Giampiero Marra, 2013. "Estimating the Effect of Perceived Risk of Crime on Social Trust in the Presence of Endogeneity Bias," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(2), pages 523-547, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0240005. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.