{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2024-07-30","version":"1"},"project_desc":{"title_statement":{"idno":"RR_WLD_2024_165","title":"Reproducibility package for Behaviorally Informed Messages Boost COVID-19 Vaccination Intentions: Global Insights from a Meta-Analysis with 23 Countries and Territories"},"authoring_entity":[{"name":"Daniel Pinzon","email":"dpinzonhernandez@worldbank.org","affiliation":"World Bank"},{"name":"Mohamad Chatila","email":"mchatila@worldbank.org","affiliation":"World Bank"},{"name":"JungKyu Rhys Lim","affiliation":"World Bank","email":"rhyslim@worldbank.org"},{"name":"Michelle Dugas","affiliation":"World Bank","email":"mdugas@worldbank.org"}],"output":[{"type":"Working paper","description":"Policy Research Working Paper (PRWP)","title":"Behaviorally Informed Messages Boost COVID-19 Vaccination Intentions: Global Insights from a Meta-Analysis with 23 Countries and Territories","authors":"Daniel Pinzon, JungKyu Rhys Lim, Michelle Dugas, Ellen Moscoe, Mohamad Chatila, Corey Cameron, Renos Vakis, Zeina Afif, Victor Orozco"}],"datasets":[{"name":"Experiment data on the COVID-19 Vaccination Intentions","note":"The authors conducted survey-experiments using Facebook. This study was approved by the Health Media Lab Institutional Review Board (HML IRB) approval number # 1017TWBG21.","access_type":"The dataset is confidential. Researchers interested in access to the data may contact the World Bank\u2019s Mind, Behavior, and Development (eMBeD) at eMBeD@worldbank.org."}],"software":[{"name":"Stata","version":"18 MP"}],"scripts":[{"file_name":"RR_WLD_2024_165.zip","zip_package":"RR_WLD_2024_165.zip","title":"Reproducibility package (code) for Behaviorally Informed Messages Boost COVID-19 Vaccination Intentions: Global Insights from a Meta-Analysis with 23 Countries and Territories","date":"2024-07","dependencies":"All dependencies are stored in the ado folder.","instructions":"See README in the reproducibility package.","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank"}],"contacts":[{"name":"Daniel Pinzon","email":"dpinzonhernandez@worldbank.org","affiliation":"World Bank"},{"name":"Rhys Lim","affiliation":"World Bank","email":"rhyslim@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"disclaimer":"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.","license":[{"name":"MIT","uri":"https:\/\/opensource.org\/license\/MIT"}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"reproduction_instructions":"The data used in this study is confidential and cannot be shared publicly, nor is there a standard procedure available for acquiring it. As a result, reproducing the study's results may be challenging. For more details on how a replicator might gain access to the data, please refer to the README file. This package includes detailed code and a comprehensive reproducibility report that outlines the analytical processes used by the authors. These resources are intended to help replicators understand and evaluate the methodologies employed, even though independent verification of the exact results is not possible due to data access restrictions.","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 10 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz 2.90 GHz (2 processors)\n\u2022 Memory available: 32 GB\n\u2022 Software version: Stata version 18 \n","technology_requirements":"~60 minutes runtime","data_statement":"All data is confidential and has not been included in the reproducibility package.","language":[{"name":"English","code":"EN"}],"abstract":"During the COVID-19 pandemic, low- and middle-income countries (LMICs) struggled with lower  vaccination rates compared to wealthier countries, posing challenges to reducing virus transmission, \n mitigating healthcare system pressures, and promoting economic recovery. Communications campaigns  offer low-cost opportunities to overcome such challenges by strengthening vaccine confidence and  intentions to get vaccinated, but empirical testing is needed to identify which messages will be most  effective in different contexts. To support policymaking efforts to rapidly design effective  communication during the pandemic, a global research program of 28 online experiments was  conducted by recruiting respondents (N = 123,270) through social media between January 2021 and  June 2022 across 23 mostly low and middle-income countries and territories. This individual participant  data meta-analysis summarizes the results of this research program testing the impact of behaviorally  informed messaging on vaccine intentions. Results from the meta-analysis show that, among  unvaccinated survey respondents, behaviorally informed messages significantly increased the odds of  vaccination intention by 1.28 times overall and up to 1.93 times in individual studies (safety messages in  Papua New Guinea). Significant pooled effects of specific framings ranged from increasing vaccination intentions by 1.16 times (variant framing) to 1.45 times (experts and religious leaders framing). This  research underscores the importance of communication tailored to address different drivers of vaccine  hesitancy and offers insights for handling future health crises with behavioral communication strategies leveraging rapid insights afforded by social media.","geographic_units":[{"name":"World","code":"WLD","type":"Region"}],"keywords":[{"name":" infectious disease"},{"name":"coronavirus"},{"name":"immunization"},{"name":"message framing"}],"topics":[{"id":"I10","vocabulary":"Journal of Economic Literature (JEL)","parent_id":"I1","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Health - General"},{"id":"I12","vocabulary":"Journal of Economic Literature (JEL)","parent_id":"I1","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Health Behavior"},{"id":"I18","vocabulary":"Journal of Economic Literature (JEL)","parent_id":"I1","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Government Policy \u2022 Regulation \u2022 Public Health"},{"id":"D91","vocabulary":"Journal of Economic Literature (JEL)","parent_id":"D9","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making"}],"production_date":"2024-07","acknowledgment_statement":"The authors express their gratitude to all who contributed to the implementation of this project, especially colleagues from regional and global Health, Nutrition, and Population (HNP) teams, Poverty and Equity teams, External and Corporate Relations (ECR) teams, the Virtual Lab, Meta for their ad credits and support, and country government partners. The authors would like to thank David Wilson (Director, HHNDR), Timothy A. Johnston (Manager, IEGHC), Sherin Varkey (Program Leader, HAEDR), Reena Badiani-Magnusson (Senior Economist, Program Leader, EECDR), Christopher H. Herbst (Senior Health Specialist, Program Leader, HMNDR),  Aneesa Arur (Program Leader, HAEDR), Son Nam Nguyen (Lead Health Specialist, HMNHN), Laura Zoratto (Senior Economist, EGVPI), Tom Bundervoet (Lead Economist, EAEPV), Lombe Kasonde (Senior Health Specialist, HHNGE), Laura Di Giorgio (Senior Economist, HLCHN), Yohana Dukhan (Senior Health Economist, HAWH3), Takahiro Hasumi (Senior Health Specialist, HECHN), Olena Doroshenko (Senior Health Economist, HECHN), Opope Oyaka Tshivuila Matala (Senior Health Specialist, HAWH2), Denizhan Duran (Senior Health Economist, HMNHN), Nicolas Rosemberg (Senior Economist, Health, HAWH3), Fernando Xavier Montenegro Torres (Senior Health Economist, HAEH1), Rochelle Se Yun Eng (Senior Health Economist, HEAH1), Leonardo Ramiro Lucchetti (Senior Economist, EAEPV), Christopher Alexander Hoy (Economist, EPVGE), Agnes Couffinhal (Senior Economist, HHNGE), Phillis Kim (Consultant, HHNGE), and Haena Kim (Consultant, EPVGE). The team is grateful to Alexandru Cojocaru (Senior Economist, EECPV) for his valuable comments as a peer reviewer. This study was partially funded by the Advancing Health Online (AHO) Initiative, a fiscally sponsored project of Global Impact and funded by Meta and MSD to advance public understanding of how social media and behavioral sciences can be leveraged to improve the health of communities around the world. The findings, opinions, interpretations, recommendations, and conclusions expressed herein do not reflect the views of the World Bank, its board of executive directors, or the governments they represent. "},"tags":[{"tag":"DOI"}],"schematype":"script"}