Skip to main content
Download PDF

Predictors of COVID-19 vaccine uptake: an online three-wave survey study of US adults

BMC Infectious Diseases volume 24, Article number: 304 (2024) Cite this article

Abstract

Background

To effectively promote vaccine uptake, it is important to understand which people are most and least inclined to be vaccinated and why. In this study, we examined predictors of COVID-19 vaccine uptake and reasons for non-vaccination.

Methods

We conducted an online English-language survey study in December-2020, January-2021, and March-2021. A total of 930 US respondents completed all surveys. Multiple logistic regression models were run to test whether the early vaccine eligibility, demographic factors, and psychological factors predict getting at least one dose of a COVID-19 vaccination in January-2021 and in March-2021.

Results

The proportion of respondents who received ≥ 1-dose of a COVID-19 vaccine increased from 18% (January) to 67% (March). Older age predicted vaccine uptake in January (OR = 2.02[95%CI = 1.14–3.78], p < .001) and March (10.92[6.76–18.05], p < .001). In January, additional predictors were higher numeracy (1.48[1.20–1.86], p < .001), COVID-19 risk perceptions (1.35[1.03–1.78], p = .029), and believing it is important adults get the COVID-19 vaccine (1.66[1.05–2.66], p = .033). In March, additional predictors of uptake were believing it is important adults get the COVID-19 vaccine (1.63[1.15–2.34], p = .006), prior COVID-19 vaccine intentions (1.37[1.10–1.72], p = .006), and belief in science (0.84[0.72–0.99], p = .041). Concerns about side effects and the development process were the most common reasons for non-vaccination. Unvaccinated respondents with no interest in getting a COVID-19 vaccine were younger (0.27[0.09–0.77], p = .016), held negative views about COVID-19 vaccines for adults (0.15[0.08–0.26], p < .001), had lower trust in healthcare (0.59[0.36–0.95], p = .032), and preferred to watch and wait in clinically ambiguous medical situations (0.66[0.48–0.89], p = .007).

Conclusions

Evidence that attitudes and intentions towards COVID-19 vaccines were important predictors of uptake provides validation for studies using these measures and reinforces the need to develop strategies for addressing safety and development concerns which remain at the forefront of vaccine hesitancy.

Peer Review reports

Background

COVID-19 continues to pose a significant threat to public health. Widespread uptake of the multiple vaccines authorized by the U.S. Food and Drug Administration for use against COVID-19 represents the safest and most effective strategy for limiting the impact of the disease [1]. However, with the Centers for Disease Control and Prevention (CDC) COVID Data Tracker reporting that ~20% of adults in the United States have not received a primary dose of a COVID-19 [2], public hesitancy and refusal to get vaccinated remains a major challenge to realizing the full preventative health benefits of the authorized COVID-19 vaccines.

In order to effectively promote vaccine uptake, it is important to first understand which people are most and least inclined to be vaccinated and why. Over the course of the pandemic, research identifying important demographic (e.g., age, race, ethnicity, and education) [3, 4] and psychological factors (e.g., COVID-19 risk perceptions [3,4,5,6], belief in conspiracy theories [7], political affiliation [3, 5, 6, 8], exposure to misinformation [9], and trust in scientists [5, 10], and the government [10, 11]) associated with public attitudes and intentions towards COVID-19 vaccines has accumulated at a rapid rate. This research has been of great value to policy makers and health communicators aiming to develop strategies and interventions to address concerns about COVID-19 vaccines and promote vaccine uptake.

However, although attitudes and intentions towards vaccination are often useful predictors of actual vaccine uptake [12, 13] this relationship does not always hold true [14,15,16,17,18]. For example, it is well documented that many people who intend to receive an influenza vaccine ultimately do not go on to receive one [14, 16]. While evidence regarding the predictors of attitudes and intentions towards COVID-19 vaccination and characteristics associated with uptake has accumulated at a dramatic rate during the pandemic, there are fewer studies that have sought to predict actual uptake of COVID-19 vaccination. Among studies that have examined factors associated with COVID-19 vaccine uptake, most have tended to consider the influence of demographic factors such as age, gender, and socioeconomic status [19,20,21]. Only a minority have also considered potential psychological influences, with those that do focussing on one or two specific factors such as vaccine attitudes [22, 23], mistrust [24], and risk perceptions [23, 25]. As a result, there is a lack of data on the extent to which demographic and psychological factors, when considered together, predict actual uptake of COVID-19 vaccination. Furthermore, many cross-sectional studies of COVID-19 vaccine uptake may not capture changes in public behaviour across evolving periods of the pandemic.

Thus, data is therefore needed to identify attitudinal and sociodemographic factors that predict future vaccine uptake over time. The aim of the present study is to identify factors that predicted uptake of COVID-19 vaccination when vaccines first became available in January and March, 2021. In addition, we report the reasons given for not getting vaccinated by those who had not and did not intend to do so, following the rollout of the COVID-19 vaccines in the US in December, 2020.

We hypothesized that older age, living in a state with a greater proportion of people vaccinated, Veteran status, having a greater number of pre-existing health conditions, higher health literacy, higher numeracy,Footnote 1 and being non-Hispanic White, would be associated with having received at least one dose of a COVID-19 vaccine in both January and March, 2021. Based on existing research on psychological factors associated with COVID-19 vaccine attitudes and intentions, we also expected that greater worry about COVID-19, greater COVID-19 risk perceptions, greater confidence in vaccines, greater intentions to get a COVID-19 vaccine, greater trust in health care, greater belief in science, less belief in conspiracies, more liberal political views, and medical maximizing would be associated with COVID-19 vaccine uptake.

Methods

Study design and population

Respondents were recruited and compensated by Qualtrics Online Panels for three nonprobability internet surveys as part of a longitudinal study conducted in December 2–27, 2020 (nVeteran=1060; nnonVeteran=1025), January 21-February 6, 2021 (nVeteran=746; nnonVeteran=511), and March 8–23, 2021 (nVeteran=688; nnonVeteran=387) [26]. Our sample size was determined a-priori to achieve a sample of 1,000 Veteran and 1,000 non-Veteran respondents for the first survey and to account for a 20% attrition rate for the 2nd and 3rd surveys, but did not include any formal power analysis. In past studies we have conducted on pandemic communication, a sample size of 1000 was more than sufficient to find clinically meaningful significant effects [27,28,29,30]. To meet the study inclusion criteria potential respondents were required to be 18 years or older, US residents, and have access to the internet. We implemented several strategies to ensure that the survey could not be completed by “bots” or cheaters including Google’s invisible reCAPTCHA, security scan monitor, preventing multiple submissions, and blocking search engines access (for further details see: https://www.qualtrics.com/support/survey-platform/survey-module/survey-checker/fraud-detection/).

Surveys were presented in English and administered online. This study was deemed exempt by the University of Utah and the Salt Lake City VA IRBs and follows the reporting guidelines of the American Association for Public Opinion Research (AAPOR). Invited participants first read a consent cover letter which stated that consent was indicated by completing the questionnaires.

Procedure and measures

Over a four-month period (December, 2020 to March, 2021), respondents completed a three-wave survey study with the first survey (Wave 1) sent to respondents in December, 2020, the second (Wave 2) in January, 2021, and the third (Wave 3) in March, 2021. All three surveys are available on the project repository (https://osf.io/63gte/) and consisted of questions about respondents’ current behaviors, well-being, healthcare experiences, and attitudes regarding the COVID-19 pandemic [26]. Both the January and March surveys also contained short message-based experiments regarding the COVID-19 vaccines published elsewhere [31, 32]. All three surveys were developed by the study team, which includes psychologists and health services researchers with extensive experience with online survey methodology. We used validated measures and measures from prior studies where possible and only adapted or created new measures when absolutely necessary. Descriptions of all measures included in the analyses are available in the online supplementary materials.

Primary outcome measure. Self-reported vaccination status was measured using a single question with three options (0 = No; 1 = Yes, 1 dose; 2 = Yes, 2 doses) in January and March, 2021. As responses 1 and 2 indicated receiving at least one dose of a COVID-19 vaccine, they were considered vaccinated for analyses (0 = Not vaccinated; 1 = Vaccinated).

Early vaccine eligibility. Respondents’ age and the total number of pre-existing conditions [33] were included based on recommendation by the Centers for Disease Control and Prevention (CDC) for these populations to be offered vaccines first [34]. As the speed of vaccine distribution within each state may affect vaccine availability for those eligible we also included the proportion of each state that had received at least one dose of a COVID-19 vaccine (retrieved from publicly available data: https://www.kff.org/coronavirus-covid-19/issue-brief/state-covid-19-data-and-policy-actions/). Veteran status (0 = non-Veteran; 1 = Veteran) was also included given the involvement of the U.S. Department of Veterans Affairs in the distribution of COVID-19 vaccines following their authorization [35].

Demographic factors. We included respondents’ health literacy [36], numeracy [37, 38] and Race/Ethnicity (dummy coded as 0 = any other race/ethnicity; 1 = non-Hispanic White).

Psychological factors. We included respondents’ worries and risk perceptions about COVID-19, the Emory Vaccine Confidence Index [39], perceived importance of influenza and COVID-19 vaccines, COVID-19 vaccine intentions, trust in healthcare [40], (lack of) belief in science [41], belief in conspiracy theories [42], political views, and the single-item maximizer-minimizer elicitation question (the MM1; which measures preference for either waiting or taking action in medical situations where it is unclear whether action is needed) [43].

Statistical analysis

All the analyses were conducted in R Studio Version 1.4.1106. We used the “psych” package to run bivariate correlations between our predictor variables and vaccine uptake. Using the “stats” package, we ran a multiple logistic regression model to test whether the early vaccine eligibility and demographic factors predict getting at least one dose of a COVID-19 vaccination in January 2021. Using a hierarchical approach, we then included the psychological factors to the original model. We then repeated this analytical approach with receiving at least one dose of a COVID-19 vaccine in March, 2021 as the dependent variable. Reported estimates are without adjustment for non-response bias with comparisons between respondents who completed all three surveys with those who completed only one or two surveys reported elsewhere [44]. No imputation methods were used to account for missingness as the overall rate of missingness across study variables was low (< 0.2%). Respondents who reported having received at least one dose of a COVID-19 vaccination in January 2021 were not included in the March 2021 analyses.

Results

Sociodemographic information

A total of 930 respondents completed all three surveys and were included in the analyses. Information on the 1,155 respondents who did not complete all three surveys is available on the project repository (https://osf.io/63gte/) (26, 44). The completion rate was 44% overall, 55% for Veterans, and 33% for non-Veterans. Respondents in our sample were generally older (median age ranged between 55 and 74 years old), male (735, 79%), non-Hispanic White (720, 77%), US Veterans (584, 63%), and with a median household income between $50,000-$99,999. Over half of respondents (440, 64%) reported having a pre-existing condition that made them more vulnerable to COVID-19; 186 respondents (27%) indicated that they did not have such a pre-existing condition and 67 respondents (10%) were not sure. In January, 165 respondents (18%) reported having received a COVID-19 vaccine; 160 (97%) of those were first doses and only 5 (3%) had received both doses. The number of respondents reported having been vaccinated increased to 620 (67%) in March with 206 (33%) first doses and 414 (67%) both doses. Full demographics are shown in Table 1.

Table 1 Respondent demographics overall and according to Veteran status
Full size table

Reasons for not getting a COVID-19 vaccine

In the March, 2021 survey, a total of 310 respondents (33% of the total sample) had not received a vaccine. Almost a quarter of those respondents (69, 22%) reported that they did not want to get one. Among the 69 unvaccinated respondents who did not want to receive a COVID-19 vaccine, concerns about possible side effects and the vaccine development process were the most frequently endorsed reason for not getting vaccinated (Table 2). Other reasons for not getting vaccinated included not believing COVID-19 poses a serious threat, personal beliefs (e.g., religious and philosophical) that conflicted with getting vaccinated, and distrust of the institutions involved with promoting vaccines (e.g., pharmaceutical companies and the government). A few respondents cited doubts about the efficacy of the vaccines and a very small proportion reported access issues (e.g., not having enough time or vaccines being unavailable) as reasons for not getting vaccinated.

Table 2 Reasons for not getting a COVID-19 vaccine among unvaccinated respondents who were not interested in getting a COVID-19 vaccine
Full size table

Logistic regressions

In the regression models which only included the early vaccine eligibility and demographic factors, we found that older age (OR = 2.54[95%CI = 1.47–4.65], p = .001), the proportion of the state vaccinated (OR = 1.09[1.00–1.19], p = .041), increased number of pre-existing conditions (OR = 1.17[1.03–1.33], p = .034), and higher numeracy (OR = 1.59[1.30–1.97], p < .001) predicted vaccine uptake in January. Older age (OR = 9.10[6.01–14.03], p < .001), increased number of pre-existing conditions (OR = 1.19[1.04–1.35], p = .011), and higher numeracy (OR = 1.18[1.01–1.37], p = .035) were significant predictors of later vaccine uptake (in March).

After including the psychological variables, older age remained a predictor of vaccine uptake in both January and March (Fig. 1). Higher numeracy, higher COVID-19 risk perceptions, and believing that it is important for all adults to get the COVID-19 vaccine were also predictors of vaccine uptake in January. In March, believing that it is important for all adults to get the COVID-19 vaccine, prior intentions to get a COVID-19 vaccine, and general belief in science predicted vaccine uptake alongside older age.

Fig. 1
figure 1

Odds ratios with 95% confidence intervals for predictors of respondents’ vaccination status in both January and March 2021. Reference categories were 64 or younger (for Age), non-Veteran (for Veteran), and any other Race/Ethnicity (for Non-Hispanic White)

Full size image

In a further exploratory analyses, we found that younger age (OR = 0.27[0.09–0.77], p = .016), believing it is not important for all adults to get a COVID-19 vaccine (OR = 0.15[0.08–0.26], p < .001), low trust in healthcare (OR = 0.59[0.36–0.95], p = .032), and preferring to watch and wait in medical situations where it is not clear whether or not medical action is necessary (OR = 0.66[0.48–0.89], p = .007), were significant predictors of being unvaccinated and not wanting to receive a COVID-19 vaccine by March 2021 (Fig. 2).

Fig. 2
figure 2

Odds ratios with 95% confidence intervals for predictors of being unvaccinated and not wanting a COVID-19 vaccine by March 2021 (N = 925, R2 Tjur = 0.63)

Full size image

Discussion

The aim of the present study was to identify key predictors of, and objections to, COVID-19 vaccine uptake using a nonprobability online longitudinal survey of US Veterans and non-Veterans between December 2020 and March 2021. Building on previous work, we considered a range of demographic and psychological factors that may be associated with COVID-19 vaccine uptake. Findings from our sample, revealed that older age, higher numeracy, higher COVID-19 risk perceptions, and positive attitudes towards COVID-19 vaccines were important predictors of early vaccine uptake (by January 2021). As the rollout progressed, the influence of numeracy and risk perceptions remitted and we found that only older age, positive attitudes towards COVID-19 vaccines, and intentions to receive a COVID-19 vaccine were significant predictors of later vaccine uptake (by March 2021).

Consistent with prior research [20, 21], older age was the strongest predictor of vaccine uptake for both timepoints, which reflects its emphasis as key criterion for early vaccine eligibility by the CDC [34]. In contrast, the proportion of other people within the state who had been vaccinated, Veteran status, and the total number of pre-existing conditions were not associated with COVID-19 vaccine uptake at either time points. The combination of numeracy, risk perceptions, and attitudes towards COVID-19 vaccines as predictors of early vaccine uptake supports prior research demonstrating that assessment of the risks and benefits offered by vaccination as well as the threat of the disease that the vaccine protects against have a substantial influence on whether or not someone is likely to get vaccinated [45, 46]. While clear communication about the risks and benefits associated with the vaccine and the threat posed by the disease is crucial at all times, these findings suggest that it may be particularly effective at encouraging uptake during the early stages of rollouts and for novel vaccines and diseases, given that numeracy and risk perceptions did not remain significant predictors of vaccine uptake later in the pandemic.

Our findings offer important evidence that attitudes and intentions towards COVID-19 predict uptake and provide validation for the many studies that have used these measures as a proxy for vaccination uptake [3, 5,6,7,8, 10, 11]. In fact, of our respondents who were 65 years or older, 90% of those who reported that they intended to vaccinate had done so by the March 2021 survey. In addition, the present findings also build on prior research exploring characteristics associated with COVID-19 vaccination uptake, which has tended to overlook psychological and behavioral factors [19,20,21]. Taken together, these findings reinforce the need to develop effective strategies for addressing people’s concerns and negative attitudes towards COVID-19 vaccines in order to increase uptake.

The findings from the present study may also contribute to informing health communication efforts aimed at those least likely to get a COVID-19 vaccine. Around 10% of the respondents in our study both had not been vaccinated at the time of the final survey in March and also indicated that they did not intend to do so in the future. These respondents tended to be younger, had negative views about the COVID-19 vaccines for adults, low trust in healthcare, and preferred to watch and wait before taking action in medical situations where there is clinical equipoise on whether action is necessary. In addition, the most important reasons given by these respondents for not getting a COVID-19 vaccine focused on safety concerns (particularly regarding side effects and the development process), beliefs that COVID-19 is not a serious threat, personal beliefs conflicting with vaccination and distrust of institutions involved with the vaccines.

Our findings are aligned with prior studies on the reasons given by people who are hesitant towards or refuse COVID-19 vaccines [3, 47, 48], and offer an empirical basis for targeting public health messages to those who are least likely to vaccinate and tailoring messages to address their concerns. As these beliefs are often deeply held and traditional models of health communication have been largely ineffective at addressing them [32, 49], we encourage health researchers and communicators to move beyond such traditional models of information provision and instead generate alternative strategies for addressing the concerns of those who are reluctant to get vaccinated. This is particularly important, given that the CDC COVID Data Tracker currently estimates that ~20% of adults in the United States are without a primary dose of a COVID-19 vaccine and 83% have not received an updated booster vaccine [2].

One limitation of the study is that the findings rely on the accuracy and consistency of respondents’ self-reported data over the duration of the survey period. Although self-reports have been shown to be highly concordant with healthcare utilization and vaccine records [50, 51], replication of these findings with a method for confirming respondents’ reported vaccine uptake would increase confidence in these findings.

Furthermore, our sample consisted of Veteran and non-Veteran respondents who were unique in being sufficiently motivated and able to complete three online surveys during the pandemic and therefore are not representative of the general U.S. population. The finding that Veteran status did not predict vaccine uptake at either time point was surprising given the efforts and widespread outreach of the U.S. Department of Veterans Affairs in supporting COVID-19 vaccine distribution [52]. However, it is likely that the greater proportion of older adults in the Veteran sample compared to the non-Veteran sample may have limited our ability to observe a significant effect of Veteran status in the full model.

The unique makeup of our sample may also explain why the only early eligibility and demographic factors associated with vaccine uptake in this study were older age and numeracy. Our findings might also differ from prior research as our sample was overrepresented by respondents without many pre-existing health conditions (70% reported ≤ 1 pre-existing health condition), with high health literacy (94% of respondents reported high health literacy), and who identified as non-Hispanic White (78%). For instance, due to the high proportion respondents in our sample who identified as non-Hispanic White, we did not have sufficient power to explore differences across other specific racial and ethnic subgroups, which have been shown in prior studies to be associated with vaccine intentions and uptake [11].

Conclusion

Despite these limitations, the findings from the present study offer important insights regarding the predictors of vaccine uptake during the early stages of the COVID-19 vaccine rollout in the US, which can help guide health communications and public outreach. In this study, we found that early uptake of COVID-19 vaccines (i.e., by January 2021) was associated with older age, greater numeracy skills, higher COVID-19 risk perceptions, and positive attitudes towards COVID-19 vaccines, while later vaccine uptake (i.e., by March 2021) was characterized by older age, positive attitudes towards COVID-19 vaccines, and intentions to receive the vaccine. Younger age, negative attitudes towards COVID-19 vaccines, low trust in healthcare, and medical minimizing, were significant predictors of being unvaccinated and not wanting to receive a COVID-19 vaccine, as of March 2021. These findings reinforce the need for developing effective strategies for promoting positive attitudes and intentions towards vaccines to promote uptake and highlight the importance of tailoring efforts to address the unique concerns of those who are least likely to get vaccinated. A major strength of our study is that we were able to cover the initial stages of the COVID-19 vaccine distribution. However, given the changes observed between January and March and the unique characteristics of our sample, further studies are needed to re-evaluate the key predictors of vaccine uptake as the rollout progresses and with wider representation, particularly as individuals become eligible for booster vaccines and considering the circulation of novel SARS-CoV-2 variants.

Data availability

The materials and datasets for this study are publicly available at: https://osf.io/63gte/. Citation: Thorpe, A., Fagerlin, A., Scherer, L., Drews, F., Butler, J., Stevens, V., Shoemaker, H., Burpo, N., & Riddoch, M. (2022). Veterans Experiences during the COVID-19 pandemic (VISION-19). https://doi.org/10.17605/OSF.IO/63GTE. The pre-registration protocol for this study is available at: https://aspredicted.org/MKS_HRZ. This manuscript has been uploaded as a pre-print, available at: https://www.medrxiv.org/content/https://doi.org/10.1101/2022.04.19.22273818v2.

Notes

  1. In our pre-registration (https://aspredicted.org/MKS_HRZ) we erroneously stated that we would expect “lower health literacy, lower numeracy” to be associated with vaccine uptake. This was an error and is therefore corrected in the manuscript.

References

  1. Bartsch SM, O’Shea KJ, Ferguson MC, Bottazzi ME, Wedlock PT, Strych U, et al. Vaccine efficacy needed for a COVID-19 coronavirus vaccine to prevent or stop an epidemic as the Sole intervention. Am J Prev Med. 2020;59(4):493–503.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Centers for Disease Control and Prevention. COVID Data Tracker [Internet]. 2023 [cited 2023 Nov 30]. Available from: https://covid.cdc.gov/covid-data-tracker.

  3. Callaghan T, Moghtaderi A, Lueck JA, Hotez P, Strych U, Dor A, et al. Correlates and disparities of intention to vaccinate against COVID-19. Soc Sci Med. 2021;272:113638.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kelly BJ, Southwell BG, McCormack LA, Bann CM, MacDonald PDM, Frasier AM, et al. Predictors of willingness to get a COVID-19 vaccine in the U.S. BMC Infect Dis. 2021;21(1):1–7.

    Google Scholar 

  5. Viswanath K, Bekalu M, Dhawan D, Pinnamaneni R, Lang J, McLoud R. Individual and social determinants of COVID-19 vaccine uptake. BMC Public Health. 2021;21(1):818.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ruiz JB, Bell RA. Predictors of intention to vaccinate against COVID-19: results of a nationwide survey. Vaccine. 2021;39(7):1080–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Allington D, McAndrew S, Moxham-Hall V, Duffy B. Coronavirus conspiracy suspicions, general vaccine attitudes, trust and coronavirus information source as predictors of vaccine hesitancy among UK residents during the COVID-19 pandemic. Psychological Medicine. undefined/ed;1–12.

  8. Fridman A, Gershon R, Gneezy A. COVID-19 and vaccine hesitancy: a longitudinal study. PLoS ONE. 2021;16(4):e0250123.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Loomba S, de Figueiredo A, Piatek SJ, de Graaf K, Larson HJ. Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nat Hum Behav. 2021;5(3):337–48.

    Article  PubMed  Google Scholar 

  10. Lindholt MF, Jørgensen F, Bor A, Petersen MB. Public acceptance of COVID-19 vaccines: cross-national evidence on levels and individual-level predictors using observational data. BMJ Open. 2021;11(6):e048172.

    Article  PubMed  Google Scholar 

  11. Momplaisir F, Haynes N, Nkwihoreze H, Nelson M, Werner RM, Jemmott J. Understanding Drivers of Coronavirus Disease 2019 Vaccine Hesitancy Among Blacks. Clinical Infectious Diseases [Internet]. 2021 Feb 9 [cited 2021 Jul 6];(ciab102). https://doi.org/10.1093/cid/ciab102.

  12. Schmid P, Rauber D, Betsch C, Lidolt G, Denker ML. Barriers of influenza vaccination intention and behavior – a systematic review of Influenza Vaccine Hesitancy, 2005–2016. PLoS ONE. 2017;12(1):e0170550.

  13. de Figueiredo A, Simas C, Karafillakis E, Paterson P, Larson HJ. Mapping global trends in vaccine confidence and investigating barriers to vaccine uptake: a large-scale retrospective temporal modelling study. Lancet. 2020;396(10255):898–908.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Harris KM, Maurer J, Lurie N. Do people who intend to get a Flu Shot actually get one? J GEN INTERN MED. 2009;24(12):1311.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ye L, Fang T, Cui J, Zhu G, Ma R, Sun Y, et al. The intentions to get vaccinated against influenza and actual vaccine uptake among diabetic patients in Ningbo, China: identifying motivators and barriers. Hum Vaccines Immunotherapeutics. 2021;17(1):106–18.

    Article  Google Scholar 

  16. Maurer J. Inspecting the mechanism: a longitudinal analysis of socioeconomic status differences in Perceived Influenza risks, Vaccination intentions, and vaccination behaviors during the 2009–2010 Influenza Pandemic. Med Decis Mak. 2016;36(7):887–99.

    Article  Google Scholar 

  17. Galarce EM, Minsky S, Viswanath K. Socioeconomic status, demographics, beliefs and A(H1N1) vaccine uptake in the United States. Vaccine. 2011;29(32):5284–9.

    Article  PubMed  Google Scholar 

  18. McEachan RRC, Conner M, Taylor NJ, Lawton RJ. Prospective prediction of health-related behaviours with the theory of planned behaviour: a meta-analysis. Health Psychol Rev. 2011;5(2):97–144.

    Article  Google Scholar 

  19. Whiteman A. Demographic and Social Factors Associated with COVID-19 Vaccination Initiation Among Adults Aged ≥ 65 Years — United States, December 14, 2020–April 10, 2021. MMWR Morb Mortal Wkly Rep [Internet]. 2021 [cited 2023 Nov 30];70. Available from: https://www.cdc.gov/mmwr/volumes/70/wr/mm7019e4.htm.

  20. Painter EM. Demographic Characteristics of Persons Vaccinated During the First Month of the COVID-19 Vaccination Program — United States, December 14, 2020–January 14, 2021. MMWR Morb Mortal Wkly Rep [Internet]. 2021 [cited 2023 Nov 30];70. Available from: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005e1.htm.

  21. Diesel J. COVID-19 Vaccination Coverage Among Adults — United States, December 14, 2020–May 22, 2021. MMWR Morb Mortal Wkly Rep [Internet]. 2021 [cited 2023 Nov 30];70. Available from: https://www.cdc.gov/mmwr/volumes/70/wr/mm7025e1.htm.

  22. Latkin C, Dayton L, Miller J, Yi G, Balaban A, Boodram B, et al. A longitudinal study of vaccine hesitancy attitudes and social influence as predictors of COVID-19 vaccine uptake in the US. Hum Vaccines Immunotherapeutics. 2022;18(5):2043102.

    Article  Google Scholar 

  23. Datar RS, Fette LM, Hinkelman AN, Hammershaimb EA, Friedman-Klabanoff DJ, Mongraw-Chaffin M, et al. Factors associated with COVID-19 vaccination during June–October 2021: a multi-site prospective study. Vaccine. 2023;41(20):3204–14.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Thompson HS, Manning M, Mitchell J, Kim S, Harper FWK, Cresswell S, et al. Factors Associated with Racial/Ethnic group–based Medical Mistrust and perspectives on COVID-19 Vaccine Trial Participation and Vaccine Uptake in the US. JAMA Netw Open. 2021;4(5):e2111629.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Rane MS, Kochhar S, Poehlein E, You W, Robertson MM, Zimba R, et al. Determinants and trends of COVID-19 Vaccine Hesitancy and Vaccine Uptake in a National Cohort of US adults: a longitudinal study. Am J Epidemiol. 2022;191(4):570–83.

    Article  PubMed  Google Scholar 

  26. Thorpe A, Fagerlin A, Scherer L, Drews F, Butler J, Stevens V et al. Veterans Experiences during the COVID-19 pandemic (VISION-19). 2022 Apr 13 [cited 2022 Jun 28]; Available from: https://osf.io/63gte/.

  27. Thorpe A, Scherer AM, Han PKJ, Burpo N, Shaffer V, Scherer L, et al. Exposure to Common Geographic COVID-19 prevalence maps and public knowledge, risk perceptions, and behavioral intentions. JAMA Netw Open. 2021;4(1):e2033538.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Thorpe A, Gurmankin Levy A, Scherer LD, Scherer AM, Drews FA, Butler JM, et al. Impact of prior COVID-19 infection on perceptions about the benefit and safety of COVID-19 vaccines. Am J Infect Control. 2024;52(1):125–8.

    Article  PubMed  Google Scholar 

  29. Levy AG, Thorpe A, Scherer LD, Scherer AM, Drews FA, Butler JM, et al. Misrepresentation and nonadherence regarding COVID-19 Public Health measures. JAMA Netw Open. 2022;5(10):e2235837.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Han PKJ, Scharnetzki E, Scherer AM, Thorpe A, Lary C, Waterston LB, et al. Communicating scientific uncertainty about the COVID-19 pandemic: online experimental study of an uncertainty-normalizing strategy. J Med Internet Res. 2021;23(4):e27832.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Thorpe A, Fagerlin A, Drews FA, Butler J, Stevens V, Riddoch MS, et al. Communications to promote interest and confidence in COVID-19 vaccines. Am J Health Promot. 2022;36(6):976–86.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Thorpe A, Fagerlin A, Butler J, Stevens V, Drews FA, Shoemaker H, et al. Communicating about COVID-19 vaccine development and safety. PLoS ONE. 2022;17(8):e0272426.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.

    Article  CAS  PubMed  Google Scholar 

  34. Dooling K, The Advisory Committee on Immunization Practices. ’ Updated Interim Recommendation for Allocation of COVID-19 Vaccine — United States, December 2020. MMWR Morb Mortal Wkly Rep [Internet]. 2021 [cited 2021 Jul 25];69. Available from: https://www.cdc.gov/mmwr/volumes/69/wr/mm695152e2.htm.

  35. Office of Public and Intergovernmental Affairs. VA announces initial plans for COVID-19 vaccine distribution [Internet]. [cited 2021 Dec 2]. Available from: https://www.va.gov/opa/pressrel/pressrelease.cfm?id=5580.

  36. Morris NS, MacLean CD, Chew LD, Littenberg B. The single item literacy screener: evaluation of a brief instrument to identify limited reading ability. BMC Fam Pract. 2006;7(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  37. McNaughton CD, Cavanaugh KL, Kripalani S, Rothman RL, Wallston KA. Validation of a short, 3-Item Version of the subjective numeracy scale. Med Decis Mak. 2015;35(8):932–6.

    Article  Google Scholar 

  38. Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the subjective numeracy scale. Med Decis Making. 2007;27(5):672–80.

    Article  PubMed  Google Scholar 

  39. Frew PM, Murden R, Mehta CC, Chamberlain AT, Hinman AR, Nowak G, et al. Development of a US trust measure to assess and monitor parental confidence in the vaccine system. Vaccine. 2019;37(2):325–32.

    Article  PubMed  Google Scholar 

  40. Shea JA, Micco E, Dean LT, McMurphy S, Schwartz JS, Armstrong K. Development of a revised Health Care System Distrust Scale. J Gen Intern Med. 2008;23(6):727–32.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hartman RO, Dieckmann NF, Sprenger AM, Stastny BJ, DeMarree KG. Modeling attitudes toward science: development and validation of the credibility of science scale. Basic Appl Soc Psychol. 2017;39(6):358–71.

    Article  Google Scholar 

  42. Piltch-Loeb R, Zikmund-Fisher BJ, Shaffer VA, Scherer LD, Knaus M, Fagerlin A, et al. Cross-sectional psychological and Demographic Associations of Zika Knowledge and Conspiracy beliefs before and after local Zika transmission. Risk Anal. 2019;39(12):2683–93.

    Article  PubMed  Google Scholar 

  43. Scherer LD, Zikmund-Fisher BJ. Eliciting medical maximizing-minimizing preferences with a single question: development and validation of the MM1. Med Decis Making. 2020;40(4):545–50.

    Article  PubMed  Google Scholar 

  44. Thorpe A, Zhong L, Scherer LD, Drews FA, Shoemaker H, Fagerlin A. Demographic, structural, and psychological predictors of risk-increasing and mask wearing behaviors among US adults between December 2020–March 2021. Patient Educ Couns. 2023;114:107792.

    Article  PubMed  Google Scholar 

  45. Betsch C, Schmid P, Heinemeier D, Korn L, Holtmann C, Böhm R. Beyond confidence: development of a measure assessing the 5 C psychological antecedents of vaccination. PLoS ONE. 2018;13(12):e0208601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Karafillakis E, Larson HJ. The benefit of the doubt or doubts over benefits? A systematic literature review of perceived risks of vaccines in European populations. Vaccine. 2017;35(37):4840–50.

    Article  PubMed  Google Scholar 

  47. Dror AA, Eisenbach N, Taiber S, Morozov NG, Mizrachi M, Zigron A, et al. Vaccine hesitancy: the next challenge in the fight against COVID-19. Eur J Epidemiol. 2020;35(8):775–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Paul E, Steptoe A, Fancourt D. Attitudes towards vaccines and intention to vaccinate against COVID-19: Implications for public health communications. The Lancet Regional Health – Europe [Internet]. 2021 Feb 1 [cited 2021 Jul 6];1. Available from: https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(20)30012-0/abstract.

  49. Freeman D, Loe BS, Yu LM, Freeman J, Chadwick A, Vaccari C, et al. Effects of different types of written vaccination information on COVID-19 vaccine hesitancy in the UK (OCEANS-III): a single-blind, parallel-group, randomised controlled trial. Lancet Public Health. 2021;6(6):e416–27.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Ritter PL, Stewart AL, Kaymaz H, Sobel DS, Block DA, Lorig KR. Self-reports of health care utilization compared to provider records. J Clin Epidemiol. 2001;54(2):136–41.

    Article  CAS  PubMed  Google Scholar 

  51. King JP, McLean HQ, Belongia EA. Validation of self-reported influenza vaccination in the current and prior season. Influenza Other Respir Viruses. 2018;12(6):808–13.

    Article  PubMed  PubMed Central  Google Scholar 

  52. COVID-19 Vaccines At VA.| Veterans Affairs [Internet]. [cited 2021 Jul 25]. Available from: https://www.va.gov/health-care/covid-19-vaccine/.

Download references

Acknowledgements

Not applicable.

Funding

Dr. Thorpe was supported in part by grant No. 51300302 from the American Heart Association Children’s Strategically Focused Research Network fellowship awarded to Dr. Fagerlin. Funding for the study was provided by the VA (VA C-19-20-205; for recruitment of Veterans) to Drs. Fagerlin & Scherer and Dr. Fagerlin’s Jon M. Huntsman Presidential Endowed Chair (for recruitment of non-Veterans). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this paper are those of the authors and do not necessarily represent the position or policy of the U.S. Department of Veterans Affairs or the United States Government.

Author information

Authors and Affiliations

  1. Department of Population Health Sciences, Spencer Fox Eccles School of Medicine at University of Utah, Salt Lake City, UT, USA

    Alistair Thorpe, Angela Fagerlin, Holly Shoemaker & Federica S. Brecha

  2. Department of Applied Health Research, University College London, London, UK

    Alistair Thorpe

  3. Salt Lake City VA Informatics Decision- Enhancement and Analytic Sciences (IDEAS) Center for Innovation, Salt Lake City, UT, USA

    Angela Fagerlin, Frank A. Drews & Holly Shoemaker

  4. University of Utah College of Social and Behavioral Science, Salt Lake City, UT, USA

    Frank A. Drews

  5. Department of Pediatrics, Columbia University, New York, NY, USA

    Federica S. Brecha

  6. Division of Cardiology, University of Colorado, School of Medicine, Aurora, CO, USA

    Laura D. Scherer

  7. Denver VA Center of Innovation, Denver, CO, USA

    Laura D. Scherer

Authors
  1. Alistair Thorpe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Angela Fagerlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Frank A. Drews
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Holly Shoemaker
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Federica S. Brecha
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Laura D. Scherer
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AT contributed to the concept and design of the study, the acquisition, analysis, and interpretation of data, drafted the manuscript, and critically revised the manuscript for important intellectual content. AF contributed to the concept and design of the study, the acquisition, analysis, and interpretation of data, critically revised the manuscript for important intellectual content, and contributed to supervision of the project. FD contributed to the concept and design of the study and critically revised the manuscript for important intellectual content. HS contributed to the acquisition, analysis, and interpretation of data and critically revised the manuscript for important intellectual content. FSB contributed to the interpretation of data and critically revised the manuscript for important intellectual content. LDS contributed to the concept and design of the study, the acquisition, analysis, and interpretation of data, critically revised the manuscript for important intellectual content, and contributed to supervision of the project. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alistair Thorpe.

Ethics declarations

Ethics approval and consent to participate

This study was approved (deemed exempt) by the IRBs at the University of Utah and the Salt Lake City VA (Veterans Experiences During the COVID-19 Pandemic: IRB_00133198). Informed consent was obtained from the study participants; invited participants first read a consent cover letter which stated that consent was indicated by completing the questionnaires.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no known competing interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material:

Online Supplementary Materials

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thorpe, A., Fagerlin, A., Drews, F.A. et al. Predictors of COVID-19 vaccine uptake: an online three-wave survey study of US adults. BMC Infect Dis 24, 304 (2024). https://doi.org/10.1186/s12879-024-09148-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-024-09148-9

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us