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Cash versus lottery video messages: online COVID-19 vaccine incentives experiment

Author

Listed:
  • Raymond M Duch
  • Adrian Barnett
  • Maciej Filipek
  • Javier Espinosa-Brito
  • Laurence S J Roope
  • Mara Violato
  • Philip M Clarke

Abstract

During the COVID-19 pandemic, governments offered financial incentives to increase vaccine uptake. We evaluate the impact on COVID-19 vaccine uptake of cash equivalents versus being entered into lotteries. We randomly assign 1628 unvaccinated US participants into one of three 45-second informational videos promoting vaccination with messages about (a) health benefits of COVID-19 vaccines (control), (b) being entered into lotteries or (c) receiving cash equivalent vouchers. After seeing the control health information video, 16% of individuals wanted information on COVID-19 vaccination. This compared with 14% of those assigned to the lottery video (odds ratio of 0.82 relative to control: 95% credible interval, 0.58–1.17) and 22% of those assigned to the cash voucher video (odds ratio of 1.53 relative to control: 95% credible interval, 1.11–2.11). These results support greater use of cash vouchers to promote information seeking about COVID-19 vaccination and do not support the use of lottery incentives.

Suggested Citation

  • Raymond M Duch & Adrian Barnett & Maciej Filipek & Javier Espinosa-Brito & Laurence S J Roope & Mara Violato & Philip M Clarke, 2023. "Cash versus lottery video messages: online COVID-19 vaccine incentives experiment," Oxford Open Economics, Oxford University Press, vol. 2, pages 9-8.
  • Handle: RePEc:oup:ooecxx:v:2:y:2023:i::p:9-8.
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    References listed on IDEAS

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    1. Emma L Giles & Shannon Robalino & Elaine McColl & Falko F Sniehotta & Jean Adams, 2014. "The Effectiveness of Financial Incentives for Health Behaviour Change: Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-16, March.
    2. Simon Munzert & Peter Selb & Anita Gohdes & Lukas F. Stoetzer & Will Lowe, 2021. "Tracking and promoting the usage of a COVID-19 contact tracing app," Nature Human Behaviour, Nature, vol. 5(2), pages 247-255, February.
    3. Florian H. Schneider & Pol Campos-Mercade & Stephan Meier & Devin Pope & Erik Wengström & Armando N. Meier, 2023. "Financial incentives for vaccination do not have negative unintended consequences," Nature, Nature, vol. 613(7944), pages 526-533, January.
    4. Moore, Ryan T., 2012. "Multivariate Continuous Blocking to Improve Political Science Experiments," Political Analysis, Cambridge University Press, vol. 20(4), pages 460-479.
    5. Hopkins, Daniel J., 2015. "The Upside of Accents: Language, Inter-group Difference, and Attitudes toward Immigration," British Journal of Political Science, Cambridge University Press, vol. 45(3), pages 531-557, July.
    6. Gordon Pennycook & Ziv Epstein & Mohsen Mosleh & Antonio A. Arechar & Dean Eckles & David G. Rand, 2021. "Shifting attention to accuracy can reduce misinformation online," Nature, Nature, vol. 592(7855), pages 590-595, April.
    7. Zhang, Baobao & Mildenberger, Matto & Howe, Peter D. & Marlon, Jennifer & Rosenthal, Seth A. & Leiserowitz, Anthony, 2020. "Quota sampling using Facebook advertisements," Political Science Research and Methods, Cambridge University Press, vol. 8(3), pages 558-564, July.
    8. Guess, Andrew & Coppock, Alexander, 2020. "Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments – CORRIGENDUM," British Journal of Political Science, Cambridge University Press, vol. 50(4), pages 1517-1517, October.
    9. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Linde, 2014. "The deviance information criterion: 12 years on," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(3), pages 485-493, June.
    10. Guess, Andrew & Coppock, Alexander, 2020. "Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments," British Journal of Political Science, Cambridge University Press, vol. 50(4), pages 1497-1515, October.
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