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# Public attitudes toward COVID-19 vaccination: The role of vaccine attributes, incentives, and misinformation

## Abstract

While efficacious vaccines have been developed to inoculate against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; also known as COVID-19), public vaccine hesitancy could still undermine efforts to combat the pandemic. Employing a survey of 1096 adult Americans recruited via the Lucid platform, we examined the relationships between vaccine attributes, proposed policy interventions such as financial incentives, and misinformation on public vaccination preferences. Higher degrees of vaccine efficacy significantly increased individuals’ willingness to receive a COVID-19 vaccine, while a high incidence of minor side effects, a co-pay, and Emergency Use Authorization to fast-track the vaccine decreased willingness. The vaccine manufacturer had no influence on public willingness to vaccinate. We also found no evidence that belief in misinformation about COVID-19 treatments was positively associated with vaccine hesitancy. The findings have implications for public health strategies intending to increase levels of community vaccination.

## Introduction

In less than a year, an array of vaccines was developed to bring an end to the SARS-CoV-2 pandemic. As impressive as the speed of development was the efficacy of vaccines such as Moderna and Pfizer, which are over 90%. Despite the growing availability and efficacy, however, vaccine hesitancy remains a potential impediment to widespread community uptake. While previous surveys indicate that overall levels of vaccine acceptance may be around 70% in the United States1, the case of Israel may offer a cautionary tale about self-reported preferences and vaccination in practice. Prospective studies2 of vaccine acceptance in Israel showed that about 75% of the Israeli population would vaccinate, but Israel’s initial vaccination surge stalled around 42%. The government, which then augmented its vaccination efforts with incentive programs, attributed unexpected resistance to online misinformation3.

Research on vaccine hesitancy in the context of viruses such as influenza and measles, mumps, and rubella, suggests that misinformation surrounding vaccines is prevalent4,5. Emerging research on COVID-19 vaccine preferences, however, points to vaccine attributes as dominant determinants of attitudes toward vaccination. Higher efficacy is associated with greater likelihood of vaccinating6,7, whereas an FDA Emergency Use Authorization6 or politicized approval timing8 is associated with more hesitancy. Whether COVID-19 misinformation contributes to vaccine preferences or whether these attributes or policy interventions such as incentives play a larger role has not been studied. Further, while previous research has focused on a set of attributes that was relevant at one particular point in time, the evidence and context about the available vaccines has continued to shift in ways that could shape public willingness to accept the vaccine. For example, governments, employers, and economists have begun to think about or even devise ways to incentivize monetarily COVID-19 vaccine uptake, but researchers have not yet studied whether paying people to receive the COVID-19 vaccine would actually affect likely behavior. As supply problems wane and hesitancy becomes a limiting factor, understanding whether financial incentives can overcome hesitancy becomes a crucial question for public health. Further, as new vaccines such as Johnson and Johnson are authorized, knowing whether the vaccine manufacturer name elicits or deters interest in individuals is also important, as are the corresponding efficacy rates of different vaccines and the extent to which those affect vaccine preferences. The purpose of this study is to examine how information about vaccine attributes such as efficacy rates, the incidence of side effects, the nature of the governmental approval process, identity of the manufacturers, and policy interventions, including economic incentives, affect intention to vaccinate, and to examine the association between belief in an important category of misinformation—false claims concerning COVID-19 treatments—and willingness to vaccinate.

## Results

### General characteristics of study population

Table 1 presents sample demographics, which largely reflect those of the US population as a whole. Of the 1335 US adults recruited for the study, a convenience sample of 1100 participants consented to begin the survey, and 1096 completed the full questionnaire. The sample was 51% female; 75% white; and had a median age of 43 with an interquartile range of 31–58. Comparisons of the sample demographics to those of other prominent social science surveys and U.S. Census figures are shown in Supplementary Table 1.

### Vaccination preferences

Each subject was asked to evaluate a series of seven hypothetical vaccines. For each hypothetical vaccine, our conjoint experiment randomly assigned values of five different vaccine attributes—efficacy, the incidence of minor side effects, government approval process, manufacturer, and cost/financial inducement. Descriptions of each attribute and the specific levels used in the experiment are summarized in Table 2. After seeing the profile of each vaccine, the subject was asked whether she would choose to receive the vaccine described, or whether she would choose not to be vaccinated. Finally, subjects were asked to indicate how likely they would be to take the vaccine on a seven-point likert scale.

Across all choice sets, in 4419 cases (58%) subjects said they would choose the vaccine described in the profile rather than not being vaccinated. As shown in Fig. 1, several characteristics of the vaccine significantly influenced willingness to vaccinate.

## Methods

### Survey sample and procedures

This study was approved by the Cornell Institutional Review Board for Human Participant Research (protocol ID 2004009569). We conducted the study on October 29–30, 2020, prior to vaccine approval, which means we captured sentiments prospectively rather than based on information emerging from an ongoing vaccination campaign. We recruited a sample of 1096 adult Americans via the Lucid platform, which uses quota sampling to produce samples matched to the demographics of the U.S. population on age, gender, ethnicity, and geographic region. Research has shown that experimental effects observed in Lucid samples largely mirror those found using probability-based samples45. Supplementary Table 1 presents the demographics of our sample and comparisons to both the U.S. Census American Community Survey and the demographics of prominent social science surveys.

After providing informed consent on the first screen of the online survey, participants turned to a choice-based conjoint experiment that varied five attributes of the COVID-19 vaccine. Conjoint analyses are often used in marketing to research how different aspects of a product or service affect consumer choice. We build on public health studies that have analyzed the influence of vaccine characteristics on uptake within the population42,46.

### Conjoint experiment

We first designed a choice-based conjoint experiment that allowed us to evaluate the relative influence of a range of vaccine attributes on respondents’ vaccine preferences. We examined five attributes summarized in Table 2. Past research has shown that the first two attributes, efficacy and the incidence of side effects, are significant drivers of public preferences on a range of vaccines47,48,49, including COVID-196,7,13,50. In this study, we increased the expected incidence of minor side effects from previous research6 to reflect emerging evidence from Phase III trials. The third attribute, whether the vaccine received full FDA approval or an EUA, examines whether the speed of the approval process affects public vaccination preferences6. The fourth attribute, the manufacturer of the vaccine, allows us to examine whether the highly public pause in the AstraZeneca trial following an adverse event, and the significant differences in brand familiarity between smaller and less broadly known companies like Moderna and household name Johnson & Johnson affects public willingness to vaccinate. The fifth attribute examines the influence of a policy tool—offsetting the costs of vaccination or even incentivizing it financially—on public willingness to vaccinate.

Attribute levels and attribute order were randomly assigned across participants. A sample choice set is presented in Supplementary Fig. 1. After viewing each profile individually, subjects were asked: “If you had to choose, would you choose to get this vaccine, or would you choose not to be vaccinated?” Subjects then made a binary choice, responding either that they “would choose to get this vaccine” or that they “would choose not to be vaccinated.” This is the dependent variable for the regression analyses in Table 3. After making a binary choice to take the vaccine or not be vaccinated, we also asked subjects “how likely or unlikely would you be to get the vaccine described above?” Subjects indicated their vaccination preference on a seven-point scale ranging from “extremely likely” to “extremely unlikely.” Additional analyses using this ordinal dependent variable reported in Supplementary Table 3 yield substantively similar results to those presented in Table 3.

To determine the effect of each attribute-level on willingness to vaccinate, we followed Hainmueller, Hopkins, and Yamamoto and employed an ordinary least squares (OLS) regression with standard errors clustered on respondent to estimate the average marginal component effects (AMCEs) for each attribute51. The AMCE represents the average difference in a subject choosing a vaccine when comparing two different attribute values—for example, 50% efficacy vs. 90% efficacy—averaged across all possible combinations of the other vaccine attribute values. The AMCEs are nonparametrically identified under a modest set of assumptions, many of which (such as randomization of attribute levels) are guaranteed by design. Model 1 in Table 3 estimates the AMCEs for each attribute. These AMCEs are illustrated in Fig. 1.

### Analyzing additional correlates of vaccine acceptance

To ensure that any association observed between belief in misinformation and willingness to vaccinate is not an artifact of how we operationalized susceptibility to misinformation, we also constructed two alternate measures of belief in misinformation. These measures are described in detail in the Supplementary Information (see Supplementary Figs. 3 and 4). Additional regression analyses using these alternate measures of misinformation beliefs yield substantively similar results (see Supplementary Table 4). Additional analyses examining whether belief in misinformation moderates the effect of efficacy and an FDA EUA on vaccine acceptance are presented in Supplementary Fig. 6.

Finally, model 2 of Table 3 includes a range of additional control variables. Following past research, it includes a number of demographic variables, including indicator variables identifying subjects who identify as Democrats or Republicans; an indicator variable identifying females; a continuous variable measuring age (alternate analyses employing a categorical variable yield substantively similar results); an eight-point measure of educational attainment; and indicator variables identifying subjects who self-identify as Black or Latinx. Following previous research6, the model also controlled for three additional factors often associated with willingness to vaccinate: an indicator variable identifying whether each subject had health insurance; a variable measuring past frequency of influenza vaccination on a four-point scale ranging from “never” to “every year”; beliefs about the general safety of vaccines measured on a four-point scale ranging from “not at all safe” to “extremely safe”; and a measure of attitudes toward the pharmaceutical industry ranging from “very positive” to “very negative.”

### Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

## Data availability

All data and statistical code to reproduce the tables and figures in the manuscript and Supplementary Information are published at the Harvard Dataverse via this link: 10.7910/DVN/ZYU6CO.

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## Acknowledgements

S.K. and D.K. would like to thank the Cornell Atkinson Center for Sustainability for financial support.

## Author information

Authors

### Contributions

S.K. and D.K. designed the experiment/survey instrument and conducted the statistical analysis. S.K., N.D., J.B., Y.H., and D.K. all contributed to the conceptual design of the research and to the writing of the paper.

### Corresponding author

Correspondence to Douglas L. Kriner.

## Ethics declarations

### Competing interests

The authors declare no competing interests.

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Kreps, S., Dasgupta, N., Brownstein, J.S. et al. Public attitudes toward COVID-19 vaccination: The role of vaccine attributes, incentives, and misinformation. npj Vaccines 6, 73 (2021). https://doi.org/10.1038/s41541-021-00335-2

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• DOI: https://doi.org/10.1038/s41541-021-00335-2

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