Abstract
Vaccine uptake variation across demographic groups remains a public health barrier to overcome the coronavirus pandemic despite substantial evidence demonstrating the effectiveness of COVID-19 vaccines against severe illness and death. Generational cohorts differ in their experience with historical and public health events, which may contribute to variation in beliefs about COVID-19 vaccines. Nationally representative longitudinal data (December 20, 2020 to July 23, 2021) from the Understanding America Study (UAS) COVID-19 tracking survey (N = 7279) and multilevel logistic regression were used to investigate whether generational cohorts differ in COVID-19 vaccine beliefs. Regression models adjusted for wave, socioeconomic and demographic characteristics, political affiliation, and trusted source of information about COVID-19. Birth-year cutoffs define the generational cohorts: Silent (1945 and earlier), Boomer (1946–1964), Gen X (1965–1980), Millennial (1981–1996), and Gen Z (1997–2012). Compared to Boomers, Silents had a lower likelihood of believing that COVID-19 vaccines have many known harmful side effects (OR = 0.52, 95%CI = 0.35–0.74) and that they may lead to illness and death (OR = 0.53, 95%CI = 0.37–0.77). Compared to Boomers, Silents had a higher likelihood of believing that the vaccines provide important benefits to society (OR = 2.27, 95%CI = 1.34–3.86) and that they are useful and effective (OR = 1.97, 95%CI = 1.17–3.30). Results for Gen Z are similar to those reported for Silents. Beliefs about COVID-19 vaccines markedly differ across generations. This is consistent with the idea of generational imprinting—the idea that some beliefs may be resistant to change through adulthood. Policy strategies other than vaccine education may be needed to overcome this pandemic and future public health challenges.
Keywords: Vaccine hesitancy, Generational cohort, Public health policy, COVID-19
1. Introduction
Mass vaccination against COVID-19 is a major public health goal to return to normalcy, but vaccine uptake variation across demographic groups remains a major obstacle to achieving this goal. While vaccine incentives and mandates have driven up vaccination rates across different populations, many eligible adults in the United States (US) remain unvaccinated (Centers for Disease Control and Prevention, 2021). Evidence regarding COVID-19 vaccine hesitancy to date has largely focused on socioeconomic and demographic characteristics such as race/ethnicity, sex, education, income level, and health insurance coverage. Studies using nationally representative surveys suggest that vaccine uptake is relatively low for populations characterized as female, Black, young adults (ages 18–34 years), having a high school education, low income, or without health insurance coverage (Daly and Robinson, 2021; Savoia et al., 2021; Nguyen et al., 2021). Concerns about vaccine safety, potential side effects, spread of misinformation, experience of racism, and political party leaning have been reported as drivers of vaccine hesitancy (Daly and Robinson, 2021; Savoia et al., 2021; Fridman et al., 2021). However, we know much less about how political views and consumption of news information shape our perceptions of vaccine threats and benefits. These perceptions can be explained by heuristics and prior similar experiences. Different heuristics informing our understanding of transmissibility of the coronavirus and severity of the disease can motivate or discourage vaccination uptake (Madison et al., 2021).
Anchoring bias, the idea of remaining focused on initial knowledge despite new and updated information availability about that knowledge (Southwell et al., 2020), may explain the impact of political and health beliefs on vaccination decisions. More specifically, “generational imprinting” suggests that political views formed during our youth persist, are resilient to change into adulthood, and may differ by generation (Alwin et al., 1991). Stemming from Mannheim's 1952 work The Problem of Generations, a rich literature has investigated the relative importance of generational effects that stem from the unique experiences of that cohort, or life cycle effects, which result from one's age and that shape political views (Elder Jr, 1985; Braungart and Braungart, 1986). Some of that literature has demonstrated the importance of generational context for conceptualizing families, defining conservatism and liberalism, as well as views on materialism, abortion, and social mobility (Barringer et al., 2020; Fisher, 2020; Cleveland and Chang, 2009; OECD, 2018).
Generational differences are also consistent with the use of personal technology which may be particularly relevant since social media plays a significant role in spreading misinformation (Wilson and Wiysonge, 2020). Misinformation about vaccine safety affecting perceptions are more likely to spread through social media platforms than traditional media such as local TV and newspapers. People who rely on traditional media, largely Baby Boomers born in 1946–1964, have higher vaccine acceptance compared to those who rely on social media (Wang et al., 2019; Piltch-Loeb et al., 2021).
This study uses nationally representative survey data on US adults to investigate how beliefs about COVID-19 vaccines vary by generational cohort since the first COVID-19 vaccine became available in the US in December 2020. The findings may help determine whether public health strategies to address vaccine hesitancy should be developed in ways that focus on the different characteristics of these generations that go beyond factors such as age, ethnicity, or race.
2. Methods
2.1. Study sample
We analyzed data from the Understanding America Study (UAS), a probability-based Internet panel representative of noninstitutionalized adult US residents that are recruited using address-based sampling. The panel members were invited to participate in a longitudinal biweekly web-based COVID tracking survey that was conducted from March 10, 2020 to July 20, 2021. Respondents were provided a tablet and Internet access as needed and received $20 for every 30 min they spent answering survey questions.
The survey included topics ranging from risk perceptions to behaviors and socioeconomic and health impacts. While these core topics are covered in every wave, other topics, such as COVID-19 vaccine acceptance, were asked in a subset of waves. This study includes data from the first wave after the first COVID-19 vaccine became available (Wave 21, administered between December 23, 2020 and January 19, 2021) until the last wave of the tracking survey (Wave 29, administered between June 9, 2021 and July 20, 2021). These nine waves included the outcomes of interest, which are four statements on beliefs about COVID-19 vaccines.
UAS is maintained by the Center for Economic and Social Research (CESR) at the University of Southern California, which follows the American Association for Public Opinion Research (AAPOR) reporting guidelines for survey studies. Survey weights were constructed by CESR to account for respondent recruitment and differential nonresponse rates. A detailed description of how survey weights were estimated is available from the CESR COVID-19 Task Force (Kapteyn et al., 2020).
Distribution of outcomes and predictors of interest for each wave are listed in Table S1. Each respondent included in this study participated on an average of seven waves. Our final and unweighted sample included a total of 7279 unique respondents and 50,940 observations with no missing data in the variables used in the study.
2.2. Measures
2.2.1. Outcome variables
Beliefs about COVID-19 vaccines were the outcomes of interest in this study. Beginning in Wave 21, UAS asked respondents the following question: Do you agree or disagree with the following statements? Survey participants responded whether they strongly disagree, disagree, agree, or strongly agree the following four items: COVID-19 vaccines have many known harmful side effects; COVID-19 vaccines may lead to illness and death; COVID-19 vaccines provide important benefits to society; COVID-19 vaccines are useful and effective (Cronbach's alpha = 0.90). The responses to these four statements were converted to a binary outcome of disagree (strongly disagree or disagree) and agree (agree or strongly agree).
2.2.2. Predictor
Generational cohort was the exposure of interest, which is determined based on the birth-year cutoffs defined by the Pew Research Center (Dimock, 2019) as follows: Greatest Generation/Silent (“Silent”), born 1945 and earlier; Baby Boomer (“Boomer”), born 1946–1964; Generation X (“Gen X"), born 1965–1980; Millennial, born 1981–1996; and Generation Z (“Gen Z"), born 1997–2012. The Greatest Generation (born 1901–1927) contributes to 1.88% (N = 74) of the Silent cohort.
2.2.3. Covariates
Key socioeconomic, demographic and health-related characteristics were included to depict the variations across the sample population: sex (male, female), race/ethnicity (non-Hispanic (NH) White, NH Black, Hispanic, NH American Indian or Alaskan Native, NH Asian, Hawaiian/Pacific Islander, Multiracial), immigrant status (non-immigrant, first/s/third generation immigrant), marital status (married, not married), education (less than high school (HS), HS graduate, and Bachelor's degree and above), household income (<$30,000, $30–$74,999, $75,000+), employment status (yes, no), residence by Census Bureau-designated regions and divisions (“Census region” and “Census division”), and six trusted sources of information about COVID-19—CNN, Fox News, your contacts on social media (Facebook, Twitter, etc.), your coworkers, classmates or other acquaintances, your physician, and your close friends or family (do not trust at all, trust somewhat, trust mostly, and trust completely).
Age was rescaled (divided by 10) and included as a continuous variable. Immigrant status by generation was generated by the team behind the UAS and defined and designated based on country of birth of the respondents, their parents, and their grandparents. First generation immigrants (“1st gen”) are those who migrated to the US; second generation immigrants (“2nd gen”) are US-born children to at least one foreign-born parent; and third generation immigrant (“3rd gen”) are US-born children to at least one US-born parent, with at least one foreign-born grandparent. Four Census regions correspond to nine Census divisions (Northeast–New England, Middle Atlantic; Midwest–East North Central, West North Central; South–South Atlantic, East South Central, West South Central; and West–Mountain, Pacific) and were displayed as two separate covariates, but only Census divisions were included in the final model. Survey questions about political affiliation were not asked in the waves included in this study; however, evidence has shown that Americans who lean Democrat are more likely to prefer CNN whereas those who lean Republican are more likely to prefer Fox News, and polarizing opinions and behaviors remain evident during the coronavirus pandemic (Iyengar and Hahn, 2009; Motta et al., 2020). Therefore, we included responses to the following question regarding trust in CNN or Fox News as a trusted source of information about the coronavirus for representation: “How much do you trust the following sources of information about the coronavirus (COVID-19)?” Wave was included as a continuous variable.
2.3. Statistical analysis
We performed descriptive analyses to assess the differences across generational cohorts in individual-level and household-level characteristics, including age, sex, race/ethnicity, immigrant status, marital status, education, household income, employment status, and trust of information source and beliefs about COVID-19 vaccines with χ2 tests. To account for the nonindependence of repeated measures of respondents across the waves and control biases due to unmeasured respondent heterogeneity, we constructed four multilevel logistic regression models with a random intercept for respondents. Socioeconomic and demographic variables were considered time-fixed variables in our study, including age, sex, race/ethnicity, immigrant status, marital status, education, household income, employment status, residence by Census division, political affiliation, and trusted source of information about COVID-19. For the regression models, We first assessed the unadjusted association between generational cohort and beliefs about COVID-19 vaccines, and then with multivariate models, we adjusted for wave, socioeconomic and demographic characteristics, political affiliation, and trust in four different information sources. Odds ratios (ORs or adjusted ORs, AORs) and 95% confidence intervals (95% CIs) were reported. Statistical significance was assessed at the p < 0.05 level. The analyses were conducted with survey weights and were performed using Stata 17 (StataCorp, College Station, TX).
3. Results
This analysis included 7279 unique respondents and 50,940 observations from nine waves. The sample size for each of the nine waves ranged from 5428 to 5813 responses. Table 1 presents the pooled characteristics of UAS respondents by generational cohort between December 23, 2020 and July 30, 2021. As of January 1, 2021, Gen Z referred to those 18-24 years; Millennial referred to those 25–40 years; Gen X referred to those 4156 years; Boomer referred to those 57–75 years; and Silent referred to those ages 76 years and above.
Table 1.
Socioeconomic and demographic characteristics and trust in seven sources of information about coronavirus by generational cohort among US adults 18 and above in the Understanding America Study panel, December 23, 2020 to July 20, 2021 (N = 7279).†, ‡
Generational cohort |
|||||||
---|---|---|---|---|---|---|---|
Gen Z (1997–2002) |
Millennial (1981–1996) |
Gen X (1965–1980) |
Boomer (1946–1964) |
Silent (−1945) |
|||
Total | 1322 (4.1%) | 11,451 (32.18%) | 14,916 (25.44%) | 19,307 (31.17%) | 3944 (7.11%) | p-value | |
Age (mean, SE) | 49.5 (0.10) | 21.1 (0.06) | 33.3 (0.05) | 47.8 (0.06) | 64.4 (0.05) | 80.2 (0.10) | <0.001 |
Sex (%) | |||||||
Male | 49.1 | 32.2 | 43.0 | 49.1 | 54.4 | 64.1 | <0.001 |
Female | 50.9 | 67.8 | 57.0 | 50.9 | 45.6 | 35.9 | |
Race/ethnicity (%) | |||||||
Non-Hispanic (NH) white | 63.4 | 45.9 | 59.0 | 55.4 | 72.7 | 81.0 | <0.001 |
NH Black | 11.4 | 12.2 | 10.9 | 14.8 | 10.0 | 7.9 | |
Hispanic | 16.2 | 25.2 | 18.7 | 21.0 | 11.2 | 4.9 | |
American Indian/ Alaskan native | 0.4 | 1.9 | 0.5 | 0.3 | 0.3 | 0.0 | |
Asian | 5.4 | 11.6 | 6.7 | 5.6 | 3.4 | 4.2 | |
Hawaiian/Pacific Islander | 0.1 | 0.0 | 0.2 | 0.1 | 0.1 | 0.1 | |
Multiracial | 3.0 | 3.2 | 4.0 | 2.8 | 2.4 | 1.9 | |
Immigrant status (%) | |||||||
Non-immigrant | 59.4 | 57.3 | 62.2 | 59.6 | 58.8 | 49.6 | <0.001 |
1st generation | 11.9 | 12.8 | 11.9 | 17.1 | 8.6 | 6.6 | |
2nd generation | 13.1 | 24.6 | 16.5 | 11.3 | 9.0 | 14.9 | |
3rd generation | 15.7 | 5.2 | 9.4 | 12.0 | 23.6 | 28.8 | |
Marital status (%) | |||||||
Married | 56.7 | 6.1 | 53.5 | 60.9 | 63.1 | 57.3 | <0.001 |
Not married | 43.3 | 93.9 | 46.5 | 39.1 | 36.9 | 42.7 | |
Education (%) | |||||||
Less than high school (HS) | 5.5 | 3.9 | 4.4 | 4.2 | 4.5 | 4.2 | <0.001 |
HS graduate | 76.6 | 46.3 | 48.7 | 55.6 | 49.7 | 51.6 | |
Bachelor's degree and above | 17.9 | 49.8 | 47.0 | 40.2 | 45.8 | 44.2 | |
Household income (%) | |||||||
<$30,000 | 25.9 | 39.6 | 22.7 | 24.0 | 28.2 | 29.5 | <0.001 |
$30,000-74,999 | 37.3 | 29.7 | 37.5 | 32.6 | 40.6 | 43.0 | |
$75,000+ | 36.8 | 30.7 | 39.9 | 43.5 | 31.2 | 27.5 | |
Currently employed (%) | |||||||
Employed | 55.1 | 48.4 | 72.9 | 70.0 | 36.0 | 8.3 | <0.001 |
Not employed | 44.9 | 51.6 | 27.1 | 30.0 | 64.0 | 91.7 | |
Residence (census region) (%) | |||||||
Northeast | 17.3 | 15.7 | 15.1 | 16.1 | 20.0 | 20.7 | <0.001 |
Midwest | 20.9 | 24.5 | 22.2 | 19.6 | 21.2 | 16.4 | |
South | 38.0 | 34.1 | 37.3 | 41.4 | 36.5 | 38.0 | |
West | 23.8 | 25.8 | 25.3 | 22.9 | 22.4 | 24.9 | |
Residence (census division) (%) | |||||||
Division 1: New England | 4.0 | 5.2 | 3.4 | 3.9 | 4.5 | 3.7 | <0.001 |
Division 2: Middle Atlantic | 13.3 | 10.5 | 11.7 | 12.2 | 15.5 | 17.1 | |
Division 3: East north central | 14.4 | 17.6 | 15.0 | 14.0 | 14.2 | 11.7 | |
Division 4: West north central | 6.5 | 6.9 | 7.2 | 5.6 | 7.0 | 4.7 | |
Division 5: South Atlantic | 20.0 | 16.0 | 20.6 | 21.7 | 18.4 | 21.4 | |
Division 6: East south central | 7.8 | 5.2 | 8.0 | 8.2 | 7.8 | 7.4 | |
Division 7: West south central | 10.1 | 12.8 | 8.8 | 11.5 | 10.3 | 9.1 | |
Division 8: Mountain | 7.8 | 5.3 | 8.5 | 7.6 | 8.0 | 5.3 | |
Division 9: Pacific | 16.0 | 20.4 | 16.8 | 15.3 | 14.4 | 19.6 | |
How much do you trust the following sources of information about the coronavirus (COVID-19): | |||||||
CNN (%) | |||||||
Do not trust at all | 43.9 | 41.2 | 46.1 | 43.0 | 42.9 | 43.5 | <0.001 |
Trust somewhat | 34.4 | 37.0 | 35.5 | 36.5 | 31.5 | 32.9 | |
Trust mostly | 18.4 | 18.2 | 16.6 | 17.1 | 21.0 | 20.1 | |
Trust completely | 3.3 | 3.6 | 1.8 | 3.4 | 4.6 | 3.4 | |
Fox News (%) | |||||||
Do not trust at all | 56.5 | 53.9 | 62.3 | 55.9 | 54.3 | 44.2 | <0.001 |
Trust somewhat | 32.6 | 34.5 | 29.6 | 34.9 | 32.8 | 36.6 | |
Trust mostly | 9.3 | 10.8 | 7.1 | 7.7 | 10.7 | 17.6 | |
Trust completely | 1.6 | 0.9 | 1.1 | 1.5 | 2.2 | 1.7 | |
Your contacts on social media (Facebook, Twitter, etc.) (%) | |||||||
Do not trust at all | 51.3 | 45.5 | 50.0 | 49.9 | 52.2 | 61.7 | <0.001 |
Trust somewhat | 42.7 | 45.0 | 43.7 | 44.2 | 41.8 | 34.5 | |
Trust mostly | 5.4 | 8.8 | 5.6 | 5.2 | 5.4 | 3.6 | |
Trust completely | 0.6 | 0.7 | 0.7 | 0.7 | 0.6 | 0.2 | |
Your coworkers, classmates or other acquaintances (%) | |||||||
Do not trust at all | 30.3 | 33.7 | 30.0 | 31.4 | 29.5 | 29.8 | <0.001 |
Trust somewhat | 56.6 | 49.8 | 55.8 | 56.2 | 58.0 | 59.2 | |
Trust mostly | 12.0 | 15.3 | 12.9 | 11.2 | 11.7 | 10.6 | |
Trust completely | 1.0 | 1.2 | 1.3 | 1.2 | 0.8 | 0.4 | |
Your physician (%) | |||||||
Do not trust at all | 6.7 | 13.1 | 9.5 | 7.0 | 3.9 | 1.7 | <0.001 |
Trust somewhat | 27.9 | 30.3 | 31.1 | 31.7 | 23.0 | 19.5 | |
Trust mostly | 44.0 | 38.3 | 41.7 | 41.6 | 47.1 | 52.5 | |
Trust completely | 21.4 | 18.3 | 17.7 | 19.7 | 25.9 | 26.3 | |
Your close friends or family (%) | |||||||
Do not trust at all | 17.1 | 22.3 | 18.3 | 19.7 | 14.2 | 12.3 | <0.001 |
Trust somewhat | 51.6 | 45.7 | 49.4 | 51.6 | 53.4 | 57.8 | |
Trust mostly | 26.2 | 27.2 | 26.7 | 23.6 | 27.6 | 26.1 | |
Trust completely | 5.1 | 4.8 | 5.6 | 5.1 | 4.8 | 3.8 |
Understanding America study (UAS) is a probability-based Internet panel representative of US adults. Waves 21–29 included in this study are part of a bi-weekly tracking survey, which was first administered on March 20, 2020 and ended on July 20, 2021. Details about the methodology and the complete questionnaire can be found in elsewhere (USC Dornsifie Center for Economic and Social Research, 2021).
# of observations = 50,940.
Female-to-male ratio was two to one for Gen Z (67.8 vs. 32.2%) and one to two for Silent (35.9 vs. 64.1%). Gen Zers had the highest proportion of Hispanic (25.2% vs. lowest among Silents, 7.9%) and Asian (11.6% vs. lowest among Boomers, 3.4%) populations and the lowest proportion of NH white (45.9% vs. highest among Silents, 81.0%) and Hawaiian/Pacific Islander (0.0% vs. highest among Millennials, 0.2%) respondents. Millennials had the highest proportion of non-immigrants (62.2% vs. lowest among Silents, 49.6%); 12.8% of Gen Z were of 1st gen (vs. highest among Gen Xers, 17.1%); Gen Z had the highest proportion of 2nd gen (24.6% vs. lowest among Boomers, 9.0%) and the lowest proportion of 3rd gen (5.2% vs. highest within Silent, 28.8%). Gen Zers had the lowest marriage rate (6.1% vs. highest among Boomers, 63.1%). Gen Zers had the lowest rate of attaining a bachelor's degree and above (17.9% vs. highest rate among Millennials, 49.8%). Gen Zers had the highest proportion earning less than $30,000 (39.6% vs. lowest among Gen X, 24.0%; p < 0.001) and unemployed (51.6%), except for Silents (91.7%) who were least likely to be a part of the workforce at a retirement age.
Generational cohorts varied in their residence in terms of Census Region and Census Division. About 16% of Gen Zers lived in the Northeast (15.7% vs. largest share of Silent, 20.7%); Gen Zers had the largest share living in the Midwest (24.5% vs. smallest share of Silents, 16.4%) and the West (25.8% vs. smallest share of Boomers, 22.4%); and Gen Zers had the smallest share living in the South (34.1% vs. largest share of Gen X, 41.4%).
Generational cohorts also varied in their trusted source of information about COVID. About 41.2% of Gen Zers did not trust CNN at all (vs. 43.5% of Silents) and about 53.9% of Gen Zers did not trust Fox News at all (vs. 44.2% of Silents). About 45.5% of Gen Zers did not trust their contacts on social media at all (vs. 61.7% of Silents).
About 1.2% of Gen Zers completely trusted their coworkers, classmates, or other acquaintances (vs. 0.4% of Silents). About 18.3% of Gen Zers completely trusted their physician (vs. 26.3% Silents). About 22.3% of Gen Zers did not trust their close friends or family at all (vs. 12.3% of Silents).
Table 2 reports the respondents' beliefs about COVID-19 vaccines across generational cohorts. Most respondents agreed or strongly agreed that the COVID-19 vaccines provide important benefits to society (45.6% and 37.5%, respectively) or are useful and effective (48.5% and 33.3%, respectively) and disagreed or strongly disagreed that the vaccines have many known harmful side effects (44.1% and 17.5%, respectively) or may lead to illness and death (39.8% and 20.6%, respectively).
Table 2.
Generational difference in beliefs about COVID-19 vaccines among adults ages 18 years and above, the Understanding America Study panel, December 23, 2020 to July 20, 2021 (N = 7279).†, ‡
Generational cohort |
|||||||
---|---|---|---|---|---|---|---|
Gen Z (1997–2002) |
Millennial (1981–1996) |
Gen X (1965–1980) |
Boomer (1946–1964) |
Silent (−1945) |
|||
n(%) | Total | 1320 (4.1%) | 11,436 (32.18%) | 14,896 (25.44%) | 19,299 (31.17%) | 3944 (7.11%) | p-value |
COVID-19 vaccines have many known harmful side effects (%) | |||||||
Strongly disagree | 17.5 | 10.4 | 17.9 | 14.2 | 19.5 | 22.6 | <0.001 |
Disagree | 44.1 | 45.0 | 37.4 | 42.6 | 48.7 | 58.7 | |
Agree | 30.3 | 35.7 | 34.0 | 33.9 | 26.1 | 16.2 | |
Strongly agree | 8.1 | 8.9 | 10.7 | 9.3 | 5.7 | 2.5 | |
COVID-19 vaccines may lead to illness and death (%) | |||||||
Strongly disagree | 20.6 | 14.3 | 20.6 | 17.0 | 22.7 | 27.1 | <0.001 |
Disagree | 39.8 | 41.5 | 33.6 | 39.4 | 43.8 | 50.8 | |
Agree | 32.1 | 35.6 | 35.6 | 35.2 | 28.3 | 20.4 | |
Strongly agree | 7.5 | 8.6 | 10.3 | 8.4 | 5.2 | 1.7 | |
COVID-19 vaccines provide important benefits to society (%) | |||||||
Strongly disagree | 4.3 | 3.9 | 6.1 | 4.5 | 3.0 | 1.2 | <0.001 |
Disagree | 12.6 | 16.4 | 16.8 | 13.3 | 9.2 | 4.1 | |
Agree | 45.6 | 49.8 | 41.6 | 49.9 | 46.0 | 44.5 | |
Strongly agree | 37.5 | 29.9 | 35.6 | 32.2 | 41.8 | 50.1 | |
COVID-19 vaccines are useful and effective (%) | |||||||
Strongly disagree | 4.7 | 4.2 | 6.8 | 5.0 | 3.0 | 1.3 | <0.001 |
Disagree | 13.5 | 18.8 | 17.7 | 14.3 | 9.9 | 4.4 | |
Agree | 48.5 | 52.3 | 44.1 | 52.8 | 49.0 | 48.9 | |
Strongly agree | 33.3 | 24.7 | 31.4 | 27.9 | 38.1 | 45.3 |
Understanding America Study (UAS) is a probability-based Internet panel representative of US adults. Waves 21–29 included in this study are part of a bi-weekly tracking survey, which was first administered on March 20, 2020 and ended on July 20, 2021. Details about the methodology and the complete questionnaire can be found in elsewhere (USC Dornsifie Center for Economic and Social Research, 2021).
# of observations = 50,940.
Among Gen Zers, 44.6% strongly agreed/agreed that vaccines have many known harmful side effects, 44.2% strongly agreed/agreed that vaccines may lead to illness and death, 79.7% strongly agreed/agreed that vaccines provide important benefits to society, and 77% strongly agreed/agreed that the vaccines are useful and effective. In contrast, among Silents, 18.7% strongly agreed/agreed that vaccines have many known harmful side effects, 22.1% strongly agreed/agreed that vaccines may lead to illness and death, 94.6% strongly agreed/agreed that vaccines provide important benefits to society, and 94.2% strongly agreed/agreed that the vaccines are useful and effective.
Table 3 reports the results of the multilevel logistic regression models examining the association between generational cohort and beliefs about COVID-19 vaccines. The unadjusted models showed that compared to Boomers, Gen Zers had a higher likelihood of agreeing that COVID-19 vaccines have many known harmful side effects (OR = 5.20, 95% confidence interval (CI) = 3.29–8.21) and that they may lead to illness and death (OR = 4.95, 95% CI = 3.04–8.04) and had a lower likelihood of agreeing that COVID-19 vaccines provide important benefits to society (OR = 0.33, 95% CI = 0.22–0.50) and are useful and effective (OR = 6.52, 95% CI = 2.53–16.80). Millennials and Gen Xers had similar results to those of Gen Zers when compared to Boomers. Compared to Boomers, Silents had a lower likelihood of agreeing that COVID-19 vaccines have many known harmful side effects (OR = 0.18, 95% CI = 0.14–0.23) and may lead to illness and death and had a higher likelihood of agreeing that the vaccines provide important benefits to society (OR = 4.01, 95%CI = 2.87–5.59) and are useful and effective (OR = 3.91, 95%CI = 2.84–5.38).
Table 3.
Multilevel mixed-effects logistic regression models: association between generational cohort and agreement with beliefs about COVID-19 vaccines among US adults ages 18 and above: the Understanding America Study panel, December 23, 2020 to July 20, 2021 (N = 7279).†⁎⁎
COVID-19 vaccines…‡ |
||||||||
---|---|---|---|---|---|---|---|---|
Have many known harmful side effects |
May lead to illness and death |
Provide important benefits to society |
Are useful and effective |
|||||
OR§ | AOR¶ | OR | AOR | OR | AOR | OR | AOR | |
Gen Z (1997–2002) | 5.20 [3.29,8.21] |
0.23 [0.11,0.50] |
4.95⁎⁎ [3.04,8.04] |
0.19⁎⁎ [0.09,0.43] |
0.33⁎⁎ [0.22,0.50] |
2.05 [0.83,5.05] |
0.32⁎⁎ [0.21,0.47] |
2.19 [0.91,5.25] |
Millennial (1981–1996) | 5.17⁎⁎ [4.18,6.38] |
0.74 [0.44,1.23] |
5.39⁎⁎ [4.30,6.76] |
0.65 [0.38,1.09] |
0.23⁎⁎ [0.18,0.28] |
0.60 [0.33,1.09] |
0.19⁎⁎ [0.15,0.23] |
0.59 [0.33,1.05] |
Gen X (1965–1980) | 3.39⁎⁎ [2.78,4.12] |
1.17 [0.85,1.59] |
3.16⁎⁎ [2.57,3.89] |
0.97 [0.70,1.33] |
0.42⁎⁎ [0.35,0.51] |
0.69 [0.48,1.00] |
0.37⁎⁎ [0.31,0.44] |
0.62⁎⁎ [0.44,0.89] |
Boomer (1946–1964) | Ref | |||||||
Silent (− 1945) | 0.18⁎⁎ [0.14,0.23] |
0.55⁎⁎ [0.38,0.79] |
0.17⁎⁎ [0.13,0.22] |
0.59⁎⁎ [0.41,0.85] |
4.01⁎⁎ [2.87,5.59] |
2.27⁎⁎ [1.35,3.82] |
3.91 [2.84,5.38] |
2.13⁎⁎ [1.28,3.56] |
p < 0.01.
Understanding America Study (UAS) is a probability-based Internet panel representative of US adults. Waves 21–29 included in this study are part of a bi-weekly tracking survey, which was first administered on March 20, 2020 and ended on July 20, 2021. Details about the methodology and the complete questionnaire can be found in elsewhere (USC Dornsifie Center for Economic and Social Research, 2021).
Responses to the four statements in each corresponding model were included as a binary outcome of disagree (reference group; strongly disagree and disagree) and agree (agree and strongly agree).
OR = unadjusted odds ratio; 95% confidence interval in brackets.
AOR = OR adjusted for wave, age, sex, race & ethnicity, immigrant status, education level, household income, employment status, residence by census division, and trusted source of information about COVID-19 (CNN, Fox News, your physician, your close friends or family, your coworkers, classmates, or other acquaintances, your contacts on social media (Facebook, Twitter, etc.))
After adjusting for socioeconomic and demographic characteristics, political affiliation, and trusted source of information about COVID-19, results from the regression model for Gen Zers beliefs in vaccines were reversed—compared to Boomers, Gen Zers had a lower likelihood of agreeing that COVID-19 vaccines have many known harmful side effects (OR = 0.23, 95% CI = 0.11–0.50) and may lead to illness and death (OR = 0.19, 95% CI = 0.09–0.43). For the most part, both Millennials and Gen Xers were no different from Boomers in their beliefs about COVID-19 vaccines. However, Gen Xers still had a lower likelihood of believing that the vaccines are useful and effective (OR = 0.62, 95%CI = 0.44–0.89) compared to Boomers. Silents' likelihood of believing in these vaccine statements compared to Boomers remained the same in unadjusted and adjusted models.
4. Discussion
While other studies have suggested the role of age in predicting beliefs about COVID-19 vaccines (Karpman et al., 2021; Adams et al., 2020; Schwarzinger et al., 2021; Bhagianadh and Arora, 2021), to our knowledge this is the first study to examine the beliefs across different generations using a longitudinal and nationally representative survey. Consistent with other studies, COVID-19 vaccine beliefs had strong age effects, where the likelihood of believing in benefits and harms of COVID-19 vaccines increased and decreased with age, respectively. However, there were also generational cohort effects that persisted after controlling for survey wave, age, and socioeconomic and demographic characteristics, political affiliation, trusted source of information, and random effects within individuals over time.
It has been argued that generational cohorts described in our study differ by “a specific set of social, economic, technological, and/or political circumstances” during their formative years. Silents were born to families who experienced the 1918 Great Influenza and have been characterized by conformity given that they grew up during World Wars and the Great Depression (Warner, 2018).In contrast to other generational cohorts, Silents (including the Greatest Generation in this analysis) in our study remained persistent in their vaccine beliefs (i.e., COVID-19 vaccines are beneficial) even after adjusting for covariates. Silents experienced the promise of vaccination efforts against polio when it was first administered in 1955 during their formative years. The experiences of seeing scientific advances in vaccination against a deadly disease and growing up in a period of instability during an economic downturn are, to some extent, similar to what we are currently experiencing in the ongoing pandemic since early 2020. Generational imprinting suggests that the memories about these historical events may have followed them through adulthood into later years, where Silents may be more likely to believe that COVID-19 vaccines would do more good than harm.
In our study, over 80% of Gen Xers agreed that COVID-19 vaccines are useful and effective. Yet, Gen Xers had a lower likelihood of agreeing with this statement than Boomers. Unlike earlier generations, Gen Xers joined the workforce at a time when college or higher education was becoming essential for success (Currier, 2018). They also grew up during the rise of the Internet and are known for individualism and risk-taking behavior (Twenge, 2018; Howe and Strauss, 2007).
COVID-19 vaccine beliefs among Millennials did not differ from those held by the generation of their parents (Boomer generation) (Dimock, 2019). Millennials experienced the 2008 Great Recession as young adults, grew up in an increasingly digitized world, and have relatively low rates of marriage and home ownership (Tyson, 2018).
Gen Zers readily connect with a global community through social media platforms and during their formative years voted for the first time in the 2016 and 2020 presidential elections. They are now experiencing the coronavirus pandemic as some of them enter the workforce. As suggested in our bivariate analyses, Gen Zers were most likely to trust contacts on social media and were least likely to trust their coworkers, classmates, or other acquaintances, physician, close friends, or family than previous generations. Although trust in different sources of information varied across generations and somewhat trended with age, in our regression analysis Gen Zers were just as likely as Silents to disagree with the negative consequences associated with COVID-19 vaccines, suggesting that trust in these different sources may not affect the vaccine beliefs in the same way. Further research is needed to examine these associations and how different sources of information contribute to health beliefs and actions across generations.
It should be noted that age plays a role in the generational differences observed. Table 1 illustrates the expected demographic patterns that differ across generations. Younger generations were more racially/ethnically diverse and less likely to be married and Boomers and Silents were more likely to be out of the workforce. Specifically, the relationship of Silents with doctors in our sample is consistent with the literature that trust in health care is associated with age (Tanco et al., 2016; O'Malley et al., 2004). Silents were the most likely to trust their physician of all generational cohorts—they were 40% more likely than Gen Zers to trust their physicians. Compared to Silents, Gen Zers were more than seven times more likely not to trust their physicians at all as a source of information about coronavirus. Silents not only have had more opportunities over the years to develop trusting relationships with their physicians due to their age but they are also more likely to utilize health care services. The physician–patient relationship in Silents may be stronger as a result, leading them to a higher likelihood of trusting vaccination efforts.
Our study has several strengths and limitations. UAS is a nationally representative survey. The large sample size and longitudinal nature of the UAS panel data allowed us to examine random and fixed effects over a seven-month period since the beginning of the vaccine rollout, so that we could account for the time effects on beliefs about the vaccines. The richness of the data allowed us to consider important factors that are seldom captured in non-panel population-based surveys such as immigrant status by generation and trusted sources of information about COVID-19. We used trust in either CNN or Fox News as proxy to understand the context of political affiliation; these variables may not be fully aligned but they are highly correlated. Also, non-response bias could potentially impact our results. For Wave 29, for example, weighted data (benchmarked to the Current Population Survey) and unweighted data by age groups (18–34, 35–54, 55–64, and 65 years of age and over) deviate on average by only four percentage points. The margin of sampling error reported for the full sample is plus or minus one percentage point (Kapteyn et al., 2021). We did a robustness check to examine whether generational cohort masks the variation within each cohort. We found that the associations between vaccine beliefs and age group as increments of five were consistent within each generational cohort (Table S3), which justifies the use of generational cohort as a unique variable from age. Lastly, the generational cohort assignment may be limited to the US population.
5. Conclusion
The US remains divided by political affiliation on multiple public health issues, including the ongoing coronavirus pandemic. This study adds to the literature that generational membership may be a robust predictor of beliefs about COVID-19 vaccines as a result of connections with different momentous events by generations. Public health messaging should therefore be shaped differently for these cohorts. Whether the COVID-19 pandemic as a historic event and trust in news media explain future responses to national emergencies for younger generations like Gen Z remains an area for future research.
Funding
This research study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Financial disclosure
No financial disclosures were reported by the authors of this paper.
CRediT authorship contribution statement
Vivian Hsing-Chun Wang: Conceptualization, Data curation, Methodology, Formal analysis, Writing – original draft, Writing – review & editing. Diana Silver: Conceptualization, Data curation, Methodology, Writing – review & editing. José A. Pagán: Conceptualization, Data curation, Methodology, Writing – review & editing, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The project described in this paper relies on data from surveys administered by the Understanding America Study, which is maintained by the Center for Economic and Social Research (CESR) at the University of Southern California. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of USC or UAS.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ypmed.2022.107005.
Appendix A. Supplementary data
Supplementary tables
References
- Adams S.H., Park M.J., Schaub J.P., Brindis C.D., Irwin C.E. Medical vulnerability of young adults to severe COVID-19 illness—data from the National Health Interview Survey. J. Adolesc. Health. 2020;67(3):362–368. doi: 10.1016/j.jadohealth.2020.06.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Alwin D.F., Cohen R.L., Newcomb T.M. Univ of Wisconsin Press; 1991. Political Attitudes over the Life Span: The Bennington Women after Fifty Years. [Google Scholar]
- Barringer M.N., Sumerau J.E., Gay D.A. Generational variation in young adults’ attitudes toward legal abortion: contextualizing the role of religion. Soc. Curr. 2020;7(3):279–296. [Google Scholar]
- Bhagianadh D., Arora K. COVID-19 vaccine hesitancy among community-dwelling older adults: the role of information sources. J. Appl. Gerontol. 2021 doi: 10.1177/07334648211037507. Published online August 7. 07334648211037507. [DOI] [PubMed] [Google Scholar]
- Braungart R.G., Braungart M.M. Life-course and generational politics. Annu. Rev. Sociol. 1986;12(1):205–231. [Google Scholar]
- Centers for Disease Control and Prevention . Centers for Disease Control and Prevention; 2021. COVID Data Tracker.https://covid.cdc.gov/covid-data-tracker/#vaccinations_vacc-total-admin-rate-total Published March 28, 2020. Accessed October 5. [Google Scholar]
- Cleveland M., Chang W. Migration and materialism: the roles of ethnic identity, religiosity, and generation. J. Bus. Res. 2009;62(10):963–971. doi: 10.1016/j.jbusres.2008.05.022. [DOI] [Google Scholar]
- Currier E. Trend by The Pew Charitable Trusts; 2018. How Generation X Could Change the American Dream.https://www.pewtrusts.org/-/media/post-launch-images/trend-magazine/winter-2018/trend_winter_2018.pdf March. Accessed January 4, 2022. [Google Scholar]
- Daly M., Robinson E. Willingness to vaccinate against COVID-19 in the U.S.: representative longitudinal evidence from April to October 2020. Am. J. Prev. Med. 2021;60(6):766–773. doi: 10.1016/j.amepre.2021.01.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Dimock M. Pew Research Center; 2019. Defining Generations: Where Millennials End and Generation Z Begins.https://www.pewresearch.org/fact-tank/2019/01/17/where-millennials-end-and-generation-z-begins/ January 17. Accessed May 8, 2021. [Google Scholar]
- Elder G.H. Jr., editor. Life Course Dynamics: Trajectories and Transitions, 1968–1980. Cornell University Press; 1985. [Google Scholar]
- Fisher P. Generational cycles in American politics, 1952–2016. Society. 2020;57(1):22–29. [Google Scholar]
- Fridman A., Gershon R., Gneezy A. COVID-19 and vaccine hesitancy: a longitudinal study. PLoS One. 2021;16(4) doi: 10.1371/journal.pone.0250123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Howe N., Strauss W. The next 20 years: how customer and workforce attitudes will evolve. Harv. Bus. Rev. 2007;85(7–8):41–52, 191. [PubMed] [Google Scholar]
- Iyengar S., Hahn K.S. Red media, blue media: evidence of ideological selectivity in media use. J. Commun. 2009;59(1):19–39. [Google Scholar]
- Kapteyn A., Angrisani M., Bennett D., et al. Tracking the effect of the COVID-19 pandemic on the lives of American households. Surv. Res. Method. 2020;14(2):179–186. doi: 10.18148/srm/2020.v14i2.7737. [DOI] [Google Scholar]
- Kapteyn A., Bennett D., Thomas K., Darling J.E. USC Dornsifie Center for Economic and Social Research; 2021. Understanding America study’s Understanding Coronavirus in America Tracking Survey – Methodology and Topline UAS 348 Wave 29.https://uasdata.usc.edu/page/Covid-19+Documentation Accessed Jan 5, 2022. [Google Scholar]
- Karpman M., Zuckerman S., Gonzalez D., Kenney G.M. Urban Institute; 2021. Confronting COVID-19 Vaccine Hesitancy among Nonelderly Adults.https://www.urban.org/sites/default/files/publication/103713/confronting-covid-19-vaccine-hesitancy-among-nonelderly-adults_0_1.pdf February. Accessed October 5, 2021. [Google Scholar]
- Madison A.A., Way B.M., Beauchaine T.P., Kiecolt-Glaser J.K. Risk assessment and heuristics: how cognitive shortcuts can fuel the spread of COVID-19. Brain Behav. Immun. 2021;94:6–7. doi: 10.1016/j.bbi.2021.02.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Motta M., Stecula D., Farhart C. How right-leaning media coverage of COVID-19 facilitated the spread of misinformation in the early stages of the pandemic in the US. Can. J. Polit. Sci. 2020;53(2):335–342. [Google Scholar]
- Nguyen K.H., Yankey D., Coy K.C., et al. COVID-19 vaccination coverage, intent, knowledge, attitudes, and beliefs among essential workers, United States. Emerg. Infect. Dis. 2021;27(11):2908–2913. doi: 10.3201/eid2711.211557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- OECD . OECD Publishing; 2018. Catching Up? Country Studies on Intergenerational mobility and Children of Immigrants. [DOI] [Google Scholar]
- O’Malley A.S., Sheppard V.B., Schwartz M., Mandelblatt J. The role of trust in use of preventive services among low-income African-American women. Prev. Med. 2004;38(6):777–785. doi: 10.1016/j.ypmed.2004.01.018. [DOI] [PubMed] [Google Scholar]
- Piltch-Loeb R., Savoia E., Goldberg B., et al. Examining the effect of information channel on COVID-19 vaccine acceptance. medRxiv. 2021 doi: 10.1101/2021.01.18.21250049. Published online January 1, 2021. 01.18.21250049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Savoia E., Piltch-Loeb R., Goldberg B., et al. Predictors of COVID-19 vaccine hesitancy: socio-demographics, co-morbidity, and past experience of racial discrimination. Vaccines (Basel) 2021;9(7):767. doi: 10.3390/vaccines9070767. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schwarzinger M., Watson V., Arwidson P., Alla F., Luchini S. COVID-19 vaccine hesitancy in a representative working-age population in France: a survey experiment based on vaccine characteristics. Lancet Public Health. 2021;6(4):e210–e221. doi: 10.1016/S2468-2667(21)00012-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Southwell B.G., Kelly B.J., Bann C.M., Squiers L.B., Ray S.E., McCormack L.A. Mental models of infectious diseases and public understanding of COVID-19 prevention. Health Commun. 2020;35(14):1707–1710. doi: 10.1080/10410236.2020.1837462. [DOI] [PubMed] [Google Scholar]
- Tanco K., Rhondali W., Park M., Liu D., Bruera E. Predictors of trust in the medical profession among cancer patients receiving palliative care: a preliminary study. J. Palliat. Med. 2016;19(9):991–994. doi: 10.1089/jpm.2016.0089. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Twenge J.M. Trend by The Pew Charitable Trusts; 2018. Forward—What’s in a Name?https://www.pewtrusts.org/-/media/post-launch-images/trend-magazine/winter-2018/trend_winter_2018.pdf March. Accessed January 4, 2022. [Google Scholar]
- Tyson A. Trend by The Pew Charitable Trusts; 2018. The Millennials aren’t Kids Anymore.https://www.pewtrusts.org/-/media/post-launch-images/trend-magazine/winter-2018/trend_winter_2018.pdf Published online March. [Google Scholar]
- USC Dornsifie Center for Economic and Social Research Understanding America Study COVID-19 Longitudinal Files Data Description. 2021. https://uasdata.usc.edu/page/Covid-19+Documentation Accessed Jan 5, 2022.
- Wang Y., McKee M., Torbica A., Stuckler D. Systematic literature review on the spread of health-related misinformation on social media. Soc. Sci. Med. 2019;240:112552. doi: 10.1016/j.socscimed.2019.112552. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Warner J. Trend by The Pew Charitable Trusts; 2018. Lessons from the Greatest Generation.https://www.pewtrusts.org/-/media/post-launch-images/trend-magazine/winter-2018/trend_winter_2018.pdf March. Accessed January 4, 2022. [Google Scholar]
- Wilson S.L., Wiysonge C. Social media and vaccine hesitancy. BMJ Glob. Health. 2020;5(10) doi: 10.1136/bmjgh-2020-004206. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Supplementary Materials
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