IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v310y2022ics0277953622005834.html
   My bibliography  Save this article

COVID-19 booster uptake among US adults: Assessing the impact of vaccine attributes, incentives, and context in a choice-based experiment

Author

Listed:
  • Raman, Shyam
  • Kriner, Douglas
  • Ziebarth, Nicolas
  • Simon, Kosali
  • Kreps, Sarah

Abstract

Evidence shows that booster shots offer strong protection against the Omicron variant of COVID-19. However, we know little about why individuals would receive a booster compared to the initial decision to vaccinate. We investigate and assess the factors that affect individuals' reported willingness to receive the COVID-19 vaccine booster. This information can aid in tailoring public health messaging to communicate attributes that are associated with individuals’ attitudes toward the COVID-19 booster.

Suggested Citation

  • Raman, Shyam & Kriner, Douglas & Ziebarth, Nicolas & Simon, Kosali & Kreps, Sarah, 2022. "COVID-19 booster uptake among US adults: Assessing the impact of vaccine attributes, incentives, and context in a choice-based experiment," Social Science & Medicine, Elsevier, vol. 310(C).
    • Handle: RePEc:eee:socmed:v:310:y:2022:i:c:s0277953622005834
    DOI: 10.1016/j.socscimed.2022.115277
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953622005834
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2022.115277?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    2. Leeper, Thomas J. & Hobolt, Sara B. & Tilley, James, 2020. "Measuring Subgroup Preferences in Conjoint Experiments," Political Analysis, Cambridge University Press, vol. 28(2), pages 207-221, April.
    3. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
    4. Carlos E. Carpio & Ioana A. Coman & Oscar Sarasty & Manuel García, 2021. "COVID-19 Vaccine Demand and Financial Incentives," Applied Health Economics and Health Policy, Springer, vol. 19(6), pages 871-883, November.
    5. Barak Mizrahi & Roni Lotan & Nir Kalkstein & Asaf Peretz & Galit Perez & Amir Ben-Tov & Gabriel Chodick & Sivan Gazit & Tal Patalon, 2021. "Correlation of SARS-CoV-2-breakthrough infections to time-from-vaccine," Nature Communications, Nature, vol. 12(1), pages 1-5, December.
    6. Mickael Bech & Trine Kjaer & Jørgen Lauridsen, 2011. "Does the number of choice sets matter? Results from a web survey applying a discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 273-286, March.
    7. Yi, Youjae, 1990. "The Effects of Contextual Priming in Print Advertisements," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(2), pages 215-222, September.
    8. Matthew Quaife & Fern Terris-Prestholt & Gian Luca Di Tanna & Peter Vickerman, 2018. "How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1053-1066, November.
    9. Sophia L. Pink & James Chu & James N. Druckman & David G. Rand & Robb Willer, 2021. "Elite party cues increase vaccination intentions among Republicans," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(32), pages 2106559118-, August.
    10. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
    11. Motta, Matt, 2021. "Can a COVID-19 vaccine live up to Americans’ expectations? A conjoint analysis of how vaccine characteristics influence vaccination intentions," Social Science & Medicine, Elsevier, vol. 272(C).
    12. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    13. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    14. Leeper, Thomas J. & Hobolt, Sara & Tilley, James, 2020. "Measuring subgroup preferences in conjoint experiments," LSE Research Online Documents on Economics 100944, London School of Economics and Political Science, LSE Library.
    15. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    Full references (including those not matched with items on IDEAS)

    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. Chu, Haoran & Liu, Sixiao, 2021. "Light at the end of the tunnel: Influence of vaccine availability and vaccination intention on people’s consideration of the COVID-19 vaccine," Social Science & Medicine, Elsevier, vol. 286(C).
    2. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    3. Barceló, Joan & Sheen, Greg Chih-Hsin & Tung, Hans H. & Wu, Wen-Chin, 2022. "Vaccine nationalism among the public: A cross-country experimental evidence of own-country bias towards COVID-19 vaccination," Social Science & Medicine, Elsevier, vol. 310(C).
    4. Henrik Serup Christensen & Lauri Rapeli, 2021. "Immediate rewards or delayed gratification? A conjoint survey experiment of the public’s policy preferences," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(1), pages 63-94, March.
    5. Janne Tukiainen & Sebastian Blesse & Albrecht Bohne & Leonardo M. Giuffrida & Jan Jäässkeläinen & Ari Luukinen & Antti Sieppi, 2021. "What Are the Priorities of Bureaucrats? Evidence from Conjoint Experiments with Procurement Officials," EconPol Working Paper 63, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    6. Michael J. Frith, 2021. "Analysing conjoint experiments in Stata: the conjoint command," London Stata Conference 2021 14, Stata Users Group.
    7. Lim, Sijeong & Dolsak, Nives & Prakash, Aseem & Tanaka, Seiki, 2022. "Distributional concerns and public opinion: EV subsidies in the U.S. and Japan," Energy Policy, Elsevier, vol. 164(C).
    8. Aaron R Kaufman, 2020. "Implementing novel, flexible, and powerful survey designs in R Shiny," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    9. KASUYA Yuko & MIWA Hirofumi & ONO Yoshikuni, 2022. "Why are There More Women in the Upper House?," Discussion papers 22094, Research Institute of Economy, Trade and Industry (RIETI).
    10. IGARASHI Akira & MIWA Hirofumi & ONO Yoshikuni, 2022. "How Do Racial Cues Affect Attitudes toward Immigrants in a Racially Homogeneous Country? Evidence from a survey experiment in Japan," Discussion papers 22091, Research Institute of Economy, Trade and Industry (RIETI).
    11. Michael J. Nelson & Christopher Witko, 2020. "Government reputational effects of COVID-19 public health actions: A job opportunity evaluation conjoint experiment," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(1).
    12. Henrik S Christensen & Marco S La Rosa & Kimmo Grönlund, 2020. "How candidate characteristics affect favorability in European Parliament elections: Evidence from a conjoint experiment in Finland," European Union Politics, , vol. 21(3), pages 519-540, September.
    13. Liam F. Beiser-McGrath & Thomas Bernauer & Jaehyun Song & Azusa Uji, 2021. "Understanding public support for domestic contributions to global collective goods," Climatic Change, Springer, vol. 166(3), pages 1-20, June.
    14. Knotz, Carlo Michael & Gandenberger, Mia Katharina & Fossati, Flavia & Bonoli, Giuliano, 2021. "Public attitudes toward pandemic triage: Evidence from conjoint survey experiments in Switzerland," Social Science & Medicine, Elsevier, vol. 285(C).
    15. Tellez,Juan Fernando & Balcells,Laia, 2022. "Social Cohesion, Economic Security, and Forced Displacement in the Long-Run : Evidence from Rural Colombia," Policy Research Working Paper Series 10019, The World Bank.
    16. Christensen, Henrik Serup, 2020. "How design features affect evaluations of participatory platforms," SocArXiv 4ubwh, Center for Open Science.
    17. Becker, Malte & Krüger, Finja & Heidland, Tobias, 2022. "Country, culture or competition: What drives attitudes towards immigrants in Sub-Saharan Africa?," Kiel Working Papers 2224, Kiel Institute for the World Economy (IfW Kiel).
    18. Yoshiaki Kubo & Isamu Okada, 2022. "COVID-19 health certification reduces outgroup bias: evidence from a conjoint experiment in Japan," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    19. Brian Burgoon & Theresa Kuhn & Francesco Nicoli & Frank Vandenbroucke, 2022. "Unemployment risk-sharing in the EU: How policy design influences citizen support for European unemployment policy," European Union Politics, , vol. 23(2), pages 282-308, June.
    20. Pieter Vanhuysse & Michael Jankowski & Markus Tepe, 2021. "Vaccine alliance building blocks: a conjoint experiment on popular support for international COVID-19 cooperation formats," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(3), pages 493-506, September.

    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:eee:socmed:v:310:y:2022:i:c:s0277953622005834. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.