The proliferation of mis- and disinformation threatens to erode the credibility of public institutions and limit their capacity to implement policies that enhance public well-being. While misinformation represents an urgent global challenge, relatively little research has examined solutions in low- and middle-income countries. We experimentally test the impact of a novel WhatsApp chatbot game prebunking inoculation intervention in Jordan to boost capacity to identify common misinformation techniques and reduce the likelihood of sharing misleading headlines with others−effectively ‘inoculating’ them against misinformation. A sample of 2,851 participants was recruited online and randomly assigned to five study arms: (1) comprehensive game-based inoculation, (2) brief game-based inoculation that highlighted examples of only misinformation, (3) infographics-based inoculation, (4) exposure to placebo infographics unrelated to misinformation, and (5) pure control. To evaluate the impact of our intervention, we assess two main outcomes: (i) ability to accurately discern headlines using misinformation techniques and headlines that do not use misinformation techniques, and (ii) discernment in sharing the two types of headlines. Compared to the placebo group, the comprehensive game significantly improved discernment of misinformation and reduced likelihood of sharing misleading headlines. A brief version of the game yielded weaker effects on discernment of misinformation, but similarly reduced intentions to share misleading headlines. In contrast, exposure to infographics teaching similar techniques showed no significant impacts on discernment of misinformation, and marginal effects on intention to share misleading headlines. These findings suggest that games can effectively inoculate the public against misinformation in the context of a middle-income country in the short term. Future research is also needed to explore the boundary conditions of our findings.
Repository name | URI |
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Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
– OS: Windows 11 Enterprise
– Processor: Intel(R) Core(TM) i5-1145G7 CPU @ 2.60GHz
– Memory available: 15.7 GB
– Software version: Stata version 17
Runtime: 4 hours
All data is confidential and has not been included in the reproducibility package.
Author | Affiliation | |
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Daniel Pinzón | World Bank | dpinzonhernandez@worldbank.org |
JungKyu Rhys Lim | World Bank | rhyslim@worldbank.org |
Michelle Dugas | World Bank | mdugas@worldbank.org |
Renos Vakis | World Bank | rvakis@worldbank.org |
Zeina Afif | World Bank | zafif@worldbankgroup.org |
Takahiro Hasumi | World Bank | thasumi@worldbank.org |
Diya Elfadel | World Bank | delfadel@worldbank.org |
2024-05
Location | Code |
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Jordan | JOR |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
Name | URI |
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MIT | https://opensource.org/license/MIT |
Name | Affiliation | |
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Daniel Pinzon | World Bank | dpinzonhernandez@worldbank.org |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
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Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
2024-05-09
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