Taking a Shot: The Impact of Information Frames and Channels on Vaccination Willingness in a Pandemic
Abstract
:1. Introduction
Theory and Hypothesis
2. Materials and Methods
2.1. Research Design
2.2. Statistical Analysis
3. Results
3.1. Descriptive Results
3.2. Regression Results
4. Discussion
Policy Implications
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Health Information Channel | |||
---|---|---|---|
Government | Religious Organization | ||
Health information Frame | No science | Imagine that there is a global health pandemic and millions have died across the world. Vaccines were developed 12 months into the pandemic by the world’s leading pharmaceutical companies and there is a lot of information circulating on various social media platforms about the safety of the vaccine. Some state that the vaccine is dangerous and should not be taken. Below is an excerpt from a speech released by your state’s Public Health Department:“It took selfless individuals like you and I working in collaboration with both public organizations and private companies to make the vaccines available to us. While the vaccines were developed rapidly, all steps have been taken to ensure their safety and effectiveness. We recommend you get the vaccine as soon as you can to help protect yourself and others.” | Imagine that there is a global health pandemic and millions have died across the world. Vaccines were developed 12 months into the pandemic by the world’s leading pharmaceutical companies and there is a lot of information circulating on various social media platforms about the safety of the vaccine. Some state that the vaccine is dangerous and should not be taken. Below is an excerpt from a speech released by a well-respected religious organization“It took selfless individuals like you working in collaboration with both public organizations and private companies to make the vaccines available to us. While the vaccines were developed rapidly, all steps have been taken to ensure their safety and effectiveness. Upon deliberate contemplation and research, I recommend you get the vaccine as soon as you can to help protect yourself and others.” |
Science | Imagine that there is a global health pandemic and millions have died across the world. Vaccines were developed 12 months into the pandemic by the world’s leading pharmaceutical companies and there is a lot of information circulating on various social media platforms about the safety of the vaccine. Some state that the vaccine is dangerous and should not be taken. Below is an excerpt from a speech released by your state’s Public Health Department:“It took selfless individuals like you working in collaboration with both public organizations and private companies to make these vaccines available to us. While the vaccines were developed rapidly, all steps have been taken to ensure their safety and effectiveness. Our team of scientific and medical experts has evaluated scientific data gathered from numerous sources and analyzed the efficacy of the vaccines. While there is still a lot we are learning about the virus, we are committed to providing the public with the best and most up-to-date scientific research as it unfolds. We recommend you get the vaccine as soon as you can to help protect yourself and others.” | Imagine that there is a global health pandemic and millions have died across the world. Vaccines were developed 12 months into the pandemic by the world’s leading pharmaceutical companies and there is a lot of information circulating on various social media platforms about the safety of the vaccine. Some state that the vaccine is dangerous and should not be taken. Below is an excerpt from a speech released by a well-respected religious organization“It took selfless individuals like you working in collaboration with both public organizations and private companies to make the vaccines available to us. While the vaccines were developed rapidly, all steps have been taken to ensure their safety and effectiveness. A team of scientific and medical experts has evaluated scientific data gathered from numerous sources and analyzed the efficacy of the vaccines. While there is still a lot being learned about the virus, I am committed to providing you with the best and most up-to-date scientific research as it unfolds. Upon deliberate contemplation and research, I recommend you get the vaccine as soon as you can to help protect yourself and others.” |
Respondent’s Skepticism Toward the Vaccine |
---|
After reading the scenario above: Were you skeptical about the vaccine? 1. Yes 2. No 3. I’d rather not answer |
DV = Vaccination Willingness | Model 1 | Model 2 |
---|---|---|
Either frame or channel | ||
Frame: (Baseline = Without science) | ||
With science | −0.415 *** | |
(0.18) | ||
Channel: (Baseline = Government) | ||
Religious organization | 0.094 | |
(0.179) | ||
Skepticism | −0.955 *** | |
(0.201) | ||
Science × Skepticism | 0.465 ** | |
(0.227) | ||
Religious organization×Skepticism | −0.364 | |
(0.223) | ||
Both Frame and Channel: | ||
(baseline: Government, no science) | ||
Government, science | −0.463 * | |
(0.249) | ||
Religious organization, no science | 0.044 | |
(0.252) | ||
Religious organization, science | −0.315 | |
(0.261) | ||
Skepticism | −1.017 *** | |
(0.211) | ||
Government, science × Skepticism | 0.581 * | |
(0.314) | ||
Religious organization, no science × Skepticism | −0.235 | |
(0.326) | ||
Religious organization, science × Skepticism | 0.105 | |
(0.323) | ||
Demographics | ||
Age | −0.004 | −0.004 |
(0.005) | (0.005) | |
College Education | 0.472 *** | 0.469 *** |
(0.164) | (0.165) | |
Married | 0.505 *** | 0.502 *** |
(0.139) | (0.140) | |
Conservative | −0.095 | −0.095 |
(0.115) | (0.116) | |
Gender (Baseline = Female) | ||
Male | 0.021 | 0.018 |
(0.114) | (0.115) | |
Ethnicity (Baseline= White) | ||
Black or African American | 0.131 | 0.137 |
(0.168) | (0.169) | |
Asian | 0.423 | 0.424 |
(0.292) | (0.293) | |
American Indian | 0.423 | 0.34 |
(0.292) | (0.215) | |
Other races | −0.043 | −0.05 |
(0.428) | (0.431) | |
HH income (Baseline = < = $5000–$49,999) | ||
$50,000–$99,999 | 0.008 | 0.008 |
(0.12) | (0.12) | |
$100,000–$199,999 | −0.036 | −0.052 |
(0.189) | (0.193) | |
$200,000–> = $300,000 | −0.048 | −0.039 |
(0.528) | (0.533) | |
Observations | 357 | 357 |
R-squared | 0.24 | 0.24 |
References
- Machingaidze, S.; Wiysonge, C.S. Understanding COVID-19 vaccine hesitancy. Nat. Med. 2021, 27, 1338–1339. [Google Scholar] [CrossRef] [PubMed]
- Jaiswal, J.; LoSchiavo, C.; Perlman, D.C. Disinformation, misinformation, and inequality-driven mistrust in the time of COVID-19: Lessons unlearned from AIDS denialism. AIDS Behav. 2020, 24, 2776–2780. [Google Scholar] [CrossRef] [PubMed]
- Goldenberg, M.J. Vaccine Hesitancy: Public Trust, Expertise, and the War on Science; University of Pittsburgh Press: Pittsburgh, PA, USA, 2021. [Google Scholar]
- Gao, J.; Radford, B.J. Death by political party: The relationship between COVID-19 deaths and political party affiliation in the United States. World Med. Health Policy 2021, 13, 224–249. [Google Scholar] [CrossRef] [PubMed]
- Sweileh, W.M. Bibliometric Analysis of Global Scientific Literature on Vaccine Hesitancy in Peer-Reviewed Journals (1990–2019). BMC Public Health 2020, 20, 1252. [Google Scholar] [CrossRef]
- Palm, R.; Bolsen, T.; Kingsland, J.T. The effect of frames on COVID-19 vaccine resistance. Front. Political Sci. 2021, 3, 41. [Google Scholar] [CrossRef]
- Ophir, Y.; Jamieson, K.H. Intentions to use a novel Zika vaccine: The effects of misbeliefs about the MMR vaccine and perceptions about Zika. J. Public Health 2018, 40, e531–e537. [Google Scholar] [CrossRef]
- Nyhan, B.; Reifler, J.; Richey, S.; Freed, G.L. Effective messages in vaccine promotion: A randomized trial. Pediatrics 2014, 133, e835–e842. [Google Scholar] [CrossRef] [Green Version]
- Wakefield, A.J. MMR vaccination and autism. Lancet 1999, 354, 949–950. [Google Scholar] [CrossRef] [Green Version]
- Motta, M. Can a COVID-19 Vaccine Live up to Americans’ Expectations? A Conjoint Analysis of How Vaccine Characteristics Influence Vaccination Intentions. Soc. Sci. Med. 2021, 272, 113642. [Google Scholar] [CrossRef]
- Jennings, W.; Stoker, G.; Bunting, H.; Valgarðsson, V.O.; Gaskell, J.; Devine, D.; McKay, L.; Mills, M.C. Lack of trust, conspiracy beliefs, and social media use predict COVID-19 vaccine hesitancy. Vaccines 2021, 9, 593. [Google Scholar] [CrossRef]
- Van der Weerd, W.; Timmermans, D.R.; Beaujean, D.J.; Oudhoff, J.; van Steenbergen, J.E. Monitoring the level of government trust, risk perception, and intention of the general public to adopt protective measures during the influenza A (H1N1) pandemic in the Netherlands. BMC Public Health 2011, 11, 575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Siegrist, M.; Zingg, A. The role of public trust during pandemics. Eur Psych. 2014, 19, 23–32. [Google Scholar] [CrossRef]
- Apuke, O.D.; Omar, B. Social media affordances and information abundance: Enabling fake news sharing during the COVID-19 health crisis. Health Inform. J. 2021, 27, 14604582211021470. [Google Scholar] [CrossRef] [PubMed]
- Gursoy, D.; Ekinci, Y.; Can, A.S.; Murray, J.C. Effectiveness of message framing in changing COVID-19 vaccination intentions: Moderating role of travel desire. Tour. Manag. 2022, 90, 104468. [Google Scholar] [CrossRef]
- Thompson, O.P.; Ademu, L.O.; Ademu, L.A. Opium or Elixir? How Adherence to Major World Religions Influence Africans’ Health-Related Behavior During a Pandemic: A Case Study of Nigeria. In The Palgrave Handbook of Africa and the Changing Global Order; Palgrave Macmillan: Cham, Switzerland, 2022; pp. 1025–1046. [Google Scholar]
- Gerend, M.A.; Shepherd, J.E. Using message framing to promote acceptance of the human papillomavirus vaccine. Health Psychol. 2007, 26, 745. [Google Scholar] [CrossRef]
- Park, S.Y. The effects of message framing and risk perceptions for HPV vaccine campaigns: Focus on the role of regulatory fit. Health Mark. Q. 2012, 29, 283–302. [Google Scholar] [CrossRef]
- Tu, Y.C.; Lin, Y.J.; Fan, L.W.; Tsai, T.I.; Wang, H.H. Effects of multimedia framed messages on human papillomavirus prevention among adolescents. West. J. Nurs. Res. 2019, 41, 58–77. [Google Scholar] [CrossRef]
- Piltch-Loeb, R.; Savoia, E.; Goldberg, B.; Hughes, B.; Verhey, T.; Kayyem, J.; Miller-Idriss, C.; Testa, M. Examining the effect of information channels on COVID-19 vaccine acceptance. PLoS ONE 2021, 16, e0251095. [Google Scholar] [CrossRef]
- Cacciatore, M.A. Misinformation and public opinion of science and health: Approaches, findings, and future directions. Proc. Natl. Acad. Sci. USA 2021, 118, e1912437117. [Google Scholar] [CrossRef]
- Presseau, J.; Desveaux, L.; Allen, U.; Arnason, T.; Buchan, J.; Corace, K.; Dubey, V.; Evans, G.A.; Fabrigar, L.R.; Grimshaw, J.M. Behavioural science principles for supporting COVID-19 vaccine confidence and uptake among Ontario health care workers. Sci. Briefs Ont. COVID-19 Sci. Advis. Table 2021, 2, 12. [Google Scholar]
- Guenther, L.; Gaertner, M.; Zeitz, J. Framing as a concept for health communication: A systematic review. Health Commun. 2021, 36, 891–899. [Google Scholar] [CrossRef] [PubMed]
- Bullock, O.M.; Shulman, H.C. Utilizing framing theory to design more effective health messages about tanning behavior among college women. Commun. Stud. 2021, 72, 319–332. [Google Scholar] [CrossRef]
- Vaala, S.E.; Ritter, M.B.; Palakshappa, D. Framing Effects on US Adults’ Reactions to COVID-19 Public Health Messages: Moderating Role of Source Trust. Am. Behav. Sci. 2022. [Google Scholar] [CrossRef]
- Unger, F.; Steul-Fischer, M. The effect of message framing and the presentation of health vs. social consequences on health risk perception. Z. Die Gesamte Versicher. 2020, 109, 399–411. [Google Scholar] [CrossRef]
- Van’t Riet, J.; Ruiter, R.A.; Werrij, M.Q.; De Vries, H. Investigating message-framing effects in the context of a tailored intervention promoting physical activity. Health Educ. Res. 2010, 25, 343–354. [Google Scholar] [CrossRef] [Green Version]
- Elbert, S.P.; Ots, P. Reading or listening to a gain-or loss-framed health message: Effects of message framing and communication mode in the context of fruit and vegetable intake. J. Health Commun. 2018, 23, 573–580. [Google Scholar] [CrossRef]
- Von Sikorski, C.; Matthes, J. Framing-Effekte in Gesundheitsbereich [Framing effects in health communication]. In Handbuch der Gesundheitskommunikation [Handbook of Health Communication]; Rossmann, C., Hastall, M., Eds.; Springer VS: Wiesbaden, Germany, 2019; pp. 1–13. [Google Scholar]
- Penţa, M.A.; Băban, A. Message framing in vaccine communication: A systematic review of published literature. Health Commun. 2018, 33, 299–314. [Google Scholar] [CrossRef]
- Poland, C.M.; Poland, G.A. Vaccine education spectrum disorder: The importance of incorporating psychological and cognitive models into vaccine education. Vaccine 2011, 37, 6145–6148. [Google Scholar] [CrossRef]
- Zhang, Y.; Jin, Y. Thematic and episodic framing of depression: How Chinese and American newspapers framed a major public health threat. Athens J. Mass Media Commun. 2017, 3, 91–106. [Google Scholar] [CrossRef]
- Druckman, J.N. Political preference formation: Competition, deliberation, and the relevance of framing effects. Am. Political Sci. Rev. 2004, 98, 671–686. [Google Scholar] [CrossRef] [Green Version]
- Kahneman, D.; Tversky, A. Prospect theory: An analysis of decision under risk. In Handbook of the Fundamentals of Financial Decision Making: Part I; 2013; pp. 99–127. Available online: https://www.worldscientific.com/doi/10.1142/9789814417358_0006 (accessed on 9 October 2022).
- Evans, A.M.; Krueger, J.I. The psychology (and economics) of trust. Soc. Personal. Psychol. Compass 2009, 3, 1003–1017. [Google Scholar] [CrossRef]
- Hall, M.A. Researching medical trust in the United States. J. Health Organ. Manag. 2006, 20, 456–467. [Google Scholar] [CrossRef]
- Olson, O.; Berry, C.; Kumar, N. Addressing parental vaccine hesitancy towards childhood vaccines in the United States: A systematic literature review of communication interventions and strategies. Vaccines 2020, 8, 590. [Google Scholar] [CrossRef] [PubMed]
- Idler, E.L. (Ed.) Religion as a Social Determinant of Public Health; Oxford University Press: Oxford, UK, 2014. [Google Scholar]
- Pargament, K.I.; Exline, J.J.; Jones, J.W. APA Handbook of Psychology, Religion, And spirituality (Vol 1): Context, Theory, and Research; American Psychological Association: Washington, DC, USA, 2013. [Google Scholar]
- Seddig, D.; Maskileyson, D.; Davidov, E.; Ajzen, I.; Schmidt, P. Correlates of COVID-19 vaccination intentions: Attitudes, institutional trust, fear, conspiracy beliefs, and vaccine skepticism. Soc. Sci. Med. 2022, 302, 114981. [Google Scholar] [CrossRef] [PubMed]
- Coustasse, A.; Kimble, C.; Maxik, K. COVID-19 and vaccine hesitancy: A challenge the United States must overcome. J. Ambul. Care Manag. 2021, 44, 71–75. [Google Scholar] [CrossRef] [PubMed]
- Schmid, B.; Thomas, E.; Olivier, J.; Cochrane, J.R. The Contribution of Religious Entities to Health Sub-Saharan Africa [Executive Summary]; African Religious Health Assets Program: Cape Town, South Africa, 2008. [Google Scholar]
- Weinberger-Litman, S.L.; Litman, L.; Rosen, Z.; Rosmarin, D.H.; Rosenzweig, C. A look at the first quarantined community in the USA: Response of religious communal organizations and implications for public health during the COVID-19 pandemic. J. Relig. Health 2020, 59, 2269–2282. [Google Scholar] [CrossRef] [PubMed]
- Levin, J. Partnerships between the faith-based and medical sectors: Implications for preventive medicine and public health. Prev. Med. Rep. 2016, 4, 344–350. [Google Scholar] [CrossRef] [Green Version]
- Dubé, E.; Laberge, C.; Guay, M.; Bramadat, P.; Roy, R.; Bettinger, J.A. Vaccine hesitancy: An overview. Hum. Vaccines Immunother. 2013, 9, 1763–1773. [Google Scholar] [CrossRef] [Green Version]
- Puri, N.; Coomes, E.A.; Haghbayan, H.; Gunaratne, K. Social media and vaccine hesitancy: New updates for the era of COVID-19 and globalized infectious diseases. Hum. Vaccines Immunother. 2020, 16, 2586–2593. [Google Scholar] [CrossRef]
- Thunström, L.; Ashworth, M.; Finnoff, D.; Newbold, S.C. Hesitancy toward a COVID-19 vaccine. Ecohealth 2021, 18, 44–60. [Google Scholar] [CrossRef]
- Holton, A.; Weberling, B.; Clarke, C.E.; Smith, M.J. The blame frame: Media attribution of culpability about the MMR–autism vaccination scare. Health Commun. 2012, 27, 690–701. [Google Scholar] [CrossRef] [PubMed]
- Leland, S.; Mohr, Z.; Piatak, J. Accountability in government contracting arrangements: Experimental analysis of blame attribution across levels of government. Am. Rev. Public Adm. 2021, 51, 251–262. [Google Scholar] [CrossRef]
- Piatak, J.; Mohr, Z.; Leland, S. Bureaucratic accountability in third-party governance: Experimental evidence of blame attribution during times of budgetary crisis. Public Adm. 2017, 95, 976–989. [Google Scholar] [CrossRef]
- Barends, A.J.; de Vries, R.E. Noncompliant responding: Comparing exclusion criteria in MTurk personality research to improve data quality. Personal. Individ. Differ. 2019, 143, 84–89. [Google Scholar] [CrossRef]
- Zack, E.S.; Kennedy, J.; Long, J.S. Can nonprobability samples be used for social science research? A cautionary tale. Surv. Res. Methods 2019, 13, 215–227. [Google Scholar]
- Hydock, C. Assessing and overcoming participant dishonesty in online data collection. Behav. Res. Methods 2018, 50, 1563–1567. [Google Scholar] [CrossRef]
- Aguinis, H.; Villamor, I.; Ramani, R.S. MTurk research: Review & recommendations. J. Manag. 2021, 47, 823–837. [Google Scholar]
- Stritch, J.M.; Pedersen, M.J.; Taggart, G. The opportunities and limitations of using Mechanical Turk (Mturk) in public administration and management scholarship. Int. Public Manag. J. 2017, 20, 489–511. [Google Scholar] [CrossRef] [Green Version]
- Angrist, J.D.; Pischke, J.S. Parallel worlds: Fixed effects, differences-in-differences, and panel data. In Mostly Harmless Econometrics; Princeton University Press: Princeton, NJ, USA, 2008; pp. 221–248. [Google Scholar]
- Henderson, J.; Ward, P.R.; Tonkin, E.; Meyer, S.B.; Pillen, H.; McCullum, D.; Toson, B.; Webb, T.; Coveney, J.; Wilson, A. Developing and maintaining public trust during and post-COVID-19: Can we apply a model developed for responding to food scares? Front. Public Health 2020, 8, 369. [Google Scholar] [CrossRef]
- Kuru, O.; Chan, M.P.S.; Lu, H.; Stecula, D.A.; Jamieson, K.H.; Albarracín, D. Religious affiliation and philosophical and moral beliefs about vaccines: A longitudinal study. J. Health Psychol. 2022. [Google Scholar] [CrossRef]
- Iannelli, V. Are There Religious Exemptions to Vaccines? 2019. Available online: https://www.verywellfamily.com/religious-exemptions-to-vaccines-2633702 (accessed on 9 June 2019).
- Patrick, B. Studying COVID-19 in light of critical approaches to risk and uncertainty: Research pathways, conceptual tools, and some magic from Mary Douglas. Health Risk Soc. 2020, 22, 1–14. [Google Scholar]
- Sammut, G.E.; Andreouli, E.E.; Gaskell, G.E.; Valsiner, J.E. The Cambridge Handbook of Social Representations; Cambridge University Press: Cambridge, UK, 2015. [Google Scholar]
- Sturgis, P.; Brunton-Smith, I.; Jackson, J. Trust in science, social consensus, and vaccine confidence. Nat. Hum. Behav. 2021, 5, 1528–1534. [Google Scholar] [CrossRef] [PubMed]
- MacDonald, N.E. Vaccine hesitancy: Definition, scope, and determinants. Vaccine 2015, 33, 4161–4164. [Google Scholar] [CrossRef] [PubMed]
- Cummings, L. The “trust” heuristic: Arguments from an authority in public health. Health Commun. 2014, 29, 1043–1056. [Google Scholar] [CrossRef] [PubMed]
- Kennedy, B.; Tyson, A.; Funk, C. Americans’ Trust in Scientists, Other Groups Declines. 2022. Available online: https://www.pewresearch.org/science/2022/02/15/americans-trust-in-scientists-other-groups-declines/ (accessed on 9 October 2022).
- Mede, N.G.; Schäfer, M.S. Science-related populism declining during the COVID-19 pandemic: A panel survey of the Swiss population before and after the Coronavirus outbreak. Public Underst. Sci. 2022, 31, 211–222. [Google Scholar] [CrossRef]
- Wintterlin, F.; Hendriks, F.; Mede, N.G.; Bromme, R.; Metag, J.; Schäfer, M.S. Predicting Public Trust in Science: The Role of Basic Orientations Toward Science, Perceived Trustworthiness of Scientists, and Experiences with Science. Front. Commun. 2022, 6, 822757. [Google Scholar] [CrossRef]
- O’Brien, T.C.; Palmer, R.; Albarracin, D. Misplaced trust: When trust in science fosters a belief in pseudoscience and the benefits of critical evaluation. J. Exp. Soc. Psychol. 2021, 96, 104184. [Google Scholar] [CrossRef]
- Merkley, E.; Loewen, P.J. Anti-intellectualism and the mass public’s response to the COVID-19 pandemic. Nat. Hum. Behav. 2021, 5, 706–715. [Google Scholar] [CrossRef]
- Sulik, J.; Deroy, O.; Dezecache, G.; Newson, M.; Zhao, Y.; El Zein, M.; Tunçgenç, B. Trust in Science Boosts Approval, but Not Following COVID-19 Rules. 2021. Available online: https://scholarworks.iupui.edu/handle/1805/25719 (accessed on 9 October 2022).
- Gross, K. The limits of framing: How framing effects may be limited or enhanced by individual-level predispositions. In Proceedings of the Annual Meeting of the Midwest Political Science Association, Chicago, IL, USA, 4–7 April 2000; Volume 27, p. 30. [Google Scholar]
- Brewer, P.R. Value words and lizard brains: Do citizens deliberate about appeals to their core values? Political Psychol. 2001, 22, 45–64. [Google Scholar] [CrossRef]
- Chong, D.; Druckman, J.N. Framing theory. Annu. Rev. Polit. Sci. 2007, 10, 103–126. [Google Scholar] [CrossRef]
- Druckman, J.N.; Nelson, K.R. Framing and deliberation. Am. J. Polit. Sci. 2003, 47, 728–744. [Google Scholar] [CrossRef]
- Lin, C.; Tu, P.; Beitsch, L.M. Confidence and receptivity for COVID-19 vaccines: A rapid systematic review. Vaccines 2020, 9, 16. [Google Scholar] [CrossRef] [PubMed]
- Callaghan, T.; Moghtaderi, A.; Lueck, J.A.; Hotez, P.J.; Strych, U.; Dor, A.; Franklin Fowler, E.; Motta, M. Correlates and disparities of COVID-19 vaccine hesitancy. Available at SSRN 3667971. 2020. Available online: https://www.vaccineacceptance.org/correlates-and-disparities-of-covid-19-vaccine-hesitancy/ (accessed on 9 October 2022).
- Peretti-Watel, P.; Seror, V.; Cortaredona, S.; Launay, O.; Raude, J.; Verger, P.; Fressard, L.; Beck, F.; Legleye, S.; l’Haridon, O. A future vaccination campaign against COVID-19 at risk of vaccine hesitancy and politicization. Lancet Infect. Dis. 2020, 20, 769–770. [Google Scholar] [CrossRef] [PubMed]
- Soares, P.; Rocha, J.V.; Moniz, M.; Gama, A.; Laires, P.A.; Pedro, A.R.; Dias, S.; Leite, A.; Nunes, C. Factors associated with COVID-19 vaccine hesitancy. Vaccines 2021, 9, 300. [Google Scholar] [CrossRef]
- Ruisch, B.C.; Moore, C.; Granados Samayoa, J.; Boggs, S.; Ladanyi, J.; Fazio, R. Examining the left-right divide through the lens of a global crisis: Ideological Differences and their implications for responses to the COVID-19 pandemic. Political Psychol. 2021, 42, 795–816. [Google Scholar] [CrossRef]
- Krämer, B.; Klingler, M. A bad political climate for climate research and trouble for gender studies: Right-wing populism as a challenge to science communication. Perspect. Popul. Media Ave. Res. 2020, 7, 253. [Google Scholar]
- Murphy, K. Regulating more effectively: The relationship between procedural justice, legitimacy, and tax non-compliance. J. Law Soc. 2005, 32, 562–589. [Google Scholar] [CrossRef]
- Scholz, J.T. Trust, taxes, and compliance. In Trust and Governance; Braithwaite, V., Levi, M., Eds.; Russell Sage Foundation: New York, NY, USA, 1998; pp. 135–166. [Google Scholar]
- Chanley, V.A.; Rudolph, T.J.; Rahn, W.M. The origins and consequences of public trust in government: A time series analysis. Public Opin. Q. 2000, 64, 239–256. [Google Scholar] [CrossRef]
Treatments | % Male | Average Age | % White | % Married | % Conservative | % College Graduates |
---|---|---|---|---|---|---|
Government, no science | 62.9 | 39.72 | 75.81 | 71.8 | 48.39 | 84.68 |
Government, science | 57.14 | 39.07 | 81.95 | 74.43 | 46.61 | 87.22 |
Religious org, no science | 52.17 | 36.83 | 80 | 71.3 | 42.61 | 84.34 |
Religious org, science | 67.4 | 38.81 | 80.95 | 75.39 | 38.09 | 88.1 |
N | 497 | 497 | 497 | 497 | 497 | 497 |
ANOVA (p-value) | F= 2.26 | F = 1.50 | F = 0.57 | F = 0.25 | F = 1.07 | F = 0.35 |
0.08 | 0.21 | 0.64 | 0.86 | 0.36 | 0.79 |
Percentage (Mean) | SD | |
Male | 0.60 | 0.49 |
Age | 38.65 | 11.07 |
Married | 0.73 | 0.44 |
Conservative | 0.44 | 0.5 |
College graduates | 0.86 | 0.35 |
White | 0.79 | 0.4 |
Black | 0.12 | 0.33 |
DV = Vaccination Willingness | Model 1 | Model 2 |
---|---|---|
Either frame or channel | ||
Frame: (Baseline = No science) | ||
With science | −0.470 *** | |
(0.162) | ||
Channel: (Baseline = Government) | ||
Religious organization | 0.115 | |
(0.162) | ||
Skepticism | −0.830 *** | |
(0.171) | ||
Science × Skepticism | 0.492 ** | |
(0.227) | ||
Religious organization × Skepticism | −0.364 | |
(0.223) | ||
Both Frame and Channel: | ||
(baseline: Government, no science) | ||
Government, science | −0.541 ** | |
(0.268) | ||
Religious organization, no science | 0.041 | |
(0.227) | ||
Religious organization, science | −0.344 | |
(0.239) | ||
Skepticism | −0.899 *** | |
(0.196) | ||
Government, science × Skepticism | 0.624 ** | |
(0.268) | ||
Religious organization, no science × Skepticism | −0.134 | |
(0.276) | ||
Religious organization, science × Skepticism | 0.209 | |
(0.281) | ||
Demographics | ||
Age | −0.006 | −0.006 |
(0.004) | (0.004) | |
College Education | 0.471 *** | 0.467 *** |
(0.142) | (0.142) | |
Married | 0.535 *** | 0.530 *** |
(0.116) | (0.117) | |
Conservative | −0.159 * | −0.153 |
(0.094) | (0.094) | |
Gender (Baseline = Female) | ||
Male | 0.05 | 0.05 |
(0.095) | (0.095) | |
Ethnicity (Baseline= White) | ||
Black or African American | 0.162 | 0.163 |
(0.135) | (0.135) | |
Asian | 0.241 | 0.241 |
(0.263) | (0.263) | |
American Indian | 0.223 | 0.217 |
(0.199) | (0.199) | |
Other races | −0.384 | −0.395 |
(0.382) | (0.384) | |
HH income (Baseline: < = $5000–$49,999) | ||
$50,000–$99,999 | 0.086 | 0.086 |
(0.097) | (0.097) | |
$100,000–$199,999 | −0.114 | −0.126 |
(0.172) | (0.172) | |
$200,000–> = $300,000 | −0.285 | −0.289 |
(0.414) | (0.417) | |
Observations | 488 | 488 |
R-squared | 0.19 | 0.19 |
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Ademu, L.O.; Gao, J.; de Assis, J.R.; Uduebor, A.; Atawodi, O. Taking a Shot: The Impact of Information Frames and Channels on Vaccination Willingness in a Pandemic. Vaccines 2023, 11, 137. https://doi.org/10.3390/vaccines11010137
Ademu LO, Gao J, de Assis JR, Uduebor A, Atawodi O. Taking a Shot: The Impact of Information Frames and Channels on Vaccination Willingness in a Pandemic. Vaccines. 2023; 11(1):137. https://doi.org/10.3390/vaccines11010137
Chicago/Turabian StyleAdemu, Lilian O., Jingjing Gao, Janine Rangel de Assis, Aanuoluwapo Uduebor, and Ojonoka Atawodi. 2023. "Taking a Shot: The Impact of Information Frames and Channels on Vaccination Willingness in a Pandemic" Vaccines 11, no. 1: 137. https://doi.org/10.3390/vaccines11010137
APA StyleAdemu, L. O., Gao, J., de Assis, J. R., Uduebor, A., & Atawodi, O. (2023). Taking a Shot: The Impact of Information Frames and Channels on Vaccination Willingness in a Pandemic. Vaccines, 11(1), 137. https://doi.org/10.3390/vaccines11010137