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Cited by 3Vaccine Coverage and HesitancyDecision-Making and Behavioral EconomicsEconomic and Environmental Valuation

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Appealing to Americans’ altruism is not enough to nudge them to accept novel vaccines

Drabo, Emmanuel F, Kelley, Marcella A, Gong, Cynthia L·2024·Journal of Public Health
DOI 10.1093/pubmed/fdae048
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Abstract

Background: The role of altruism in the acceptance of novel preventive healthcare technologies like vaccines has not been thoroughly elucidated. Methods: We 1:1 randomized n = 2004 Amazon Mechanical Turk (MTurk) participants residing in the USA into a control or treatment arm with vaccination decisions framed altruistically, to elicit their preferences for COVID-19 vaccination using web-based discrete choice experiments. We used conditional and mixed logit models to estimate the impact of framing decisions in terms of altruism on vaccination acceptance. Results: Valid responses were provided by 1674 participants (control, n = 848; treatment, n = 826). Framing vaccination decisions altruistically had no significant effect on vaccination acceptance. Further, respondents’ degree of altruism had no association with vaccination acceptance. Limitations: The MTurk sample may not be representative of the American population. We were unable to ascertain concordance between stated and revealed preferences. Conclusions and Implications: Framing vaccination decisions in terms of altruism does not appear to significantly influence vaccination acceptance and may not be an effective nudging mechanism to increase the uptake of novel vaccines. Instead, a favorable vaccination profile appears to be the primary driver of uptake.

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Metadata

Authors
Drabo, E. F., Kelley, M. A., & Gong, C. L.
Affiliations
  • Johns Hopkins University (US)
  • University of Southern California (US)
Corresponding author
Gong, Cynthia L
ORCID
Venue
Journal of Public Health
Publisher
Oxford University Press (OUP)
Published
2024-04-03
Volume
46
Issue
3
Pages
e494-e499
ISSN
  • 0943-1853 (ISSN-L)
  • 1741-3842
  • 1741-3850
DOI
10.1093/pubmed/fdae048
OpenAlex
W4393946671
Cited by
3
References
13
Citations by year
2025: 1 · 2024: 2
FWCI
1.36
Type
journal article
Language
en
Open access
closed
Licence
academic.oup.com/pages/standard-publication-reuse-rights (vor)
Locations
  • Journal of Public Health (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Teresa and Byron Pollitt Family Chair in Fetal & Neonatal Medicine at Children’s Hospital Los Angeles
  • Fetal and Neonatal Institute
  • Division of Neonatology
  • Department of Pediatrics
  • Children's Hospital Los Angeles
  • Keck School of Medicine
  • University of Southern California
Topics
  • Social Sciences › Health › Vaccine Coverage and Hesitancy
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
Keywords
altruism, vaccine acceptance, COVID-19 vaccination, framing effects, nudging, vaccine uptake, discrete choice experiment, stated versus revealed preferences
MeSH terms
COVID-19, SARS-CoV-2, COVID-19 Vaccines, Adult, Aged, Altruism, Choice Behavior, Female, Humans, Male, Middle Aged, Patient Acceptance of Health Care, United States, Vaccination, Young Adult

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CoChat. (2026). Citation check: Appealing to Americans’ altruism is not enough to nudge them to accept novel vaccines. https://app.cochat.ai/papers/10.1093/pubmed/fdae048
The paper
Drabo, E. F., Kelley, M. A., & Gong, C. L. (2024). Appealing to Americans’ altruism is not enough to nudge them to accept novel vaccines. Journal of Public Health. https://doi.org/10.1093/pubmed/fdae048

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.