Abstract
Background:
The COVID-19 pandemic disproportionately impacts youth and young adults (YYA) and YYA with multiple marginalized identities, yet little is known about differences in uptake, testing access and vaccine concerns among YYA by diverse demographic identities.
Methods:
Between 2/2021 and 2/2022, we conducted a national, cross-sectional online survey focused on diverse YYA ages 14–24 (n = 983). We explored the prevalence of COVID-19 testing and vaccination among YYA by age, race/ethnicity, and sexual and gender identities. Bivariate and multivariable logistic regression models were developed to estimate associations between individual variables and COVID-19 testing and vaccination.
Results:
The overall COVID-19 testing and vaccination rates in our sample were high (75.99% and 69.07%, respectively). No differences in testing by demographics were found. Compared to individuals aged 14–17 years, those aged 18–21 years and 22–24 years were over two times and four times as likely to report receiving a vaccine, respectively. All race/ethnicity groups except for Asian individuals were more likely to report being vaccinated compared to their white peers.
Conclusion:
Our findings showed critical disparities in COVID-19 vaccination among YYA with marginalized identities and emphasized the urgency for data collection and research on pandemic prevention for vulnerable YYA populations.
Keywords: COVID-19, Vaccination, Testing, Prevention, Adolescents, Health Disparities
Introduction
The COVID-19 pandemic continues to have a disproportionate impact on youth and young adults (YYA) in the United States, especially those ages 14 to 24 (1). This group remains particularly vulnerable to harms related to COVID-19 including high parental and personal job losses, educational disruptions, and food and housing insecurity, which influence a critical period of growth and development for YYA (2, 3). Despite receiving little public health attention, YYA are at risk for developing severe chronic conditions following COVID-19 infection, including multisystem inflammatory syndrome (MIS-C) (4) or long COVID (5). This is in addition to greater traumatic stressors and mental health challenges following exposure to COVID-19 (6). The impacts of the COVID-19 pandemic were disproportionately experienced by minoritized YYA, particularly those racial/ethnic minority and sexual and gender minority (SGM) identities. Robust research demonstrates that Black and Hispanic/Latinx individuals were at the highest risk of COVID-19 infection, in comparison to all other racial/ethnic groups (7). Early pandemic research found SGM YYA experienced elevated rates of homelessness, uninsurance, and unequal access to healthcare resources – all factors associated with COVID-19 infection and morbidity (8, 9).
COVID-19 testing and vaccination are currently the best strategies for prevention; however, few studies have examined the prevalence of testing and vaccination, as well as barriers to testing and vaccination, among YYA, with even fewer focusing on SGM and racial/ethnic minorities (10). To date, much of the data collection and research on prevention only focuses on people 18 years and older, including the COVID-19 Trends and Impact Survey (CTIS), one of the largest continuous health surveys collecting information on COVID-19 symptoms, testing, vaccination, and other key factors (11). Although the online, interactive data tracker for COVID-19 developed by the Centers for Disease Control and Prevention (CDC) for disease prevention and monitoring does provide vaccine uptake data for youth 12 years and older (12), health equity data were not available by sexual and gender identity. Another study from the CDC found that about one-half of unvaccinated individuals aged 12 to 17 years old reported intent to receive a COVID-19 vaccination, however, the study did not collect data on sexual identities and consequently did not factor this into their analysis (13).
While prior research on the vaccine beliefs and behaviors of YYA are scarce, related research among adult participants (aged >18 and older) suggests robust disparities. In one such study, adult Black sexual minority men were significantly less likely to accept a COVID-19 vaccine, and adult Asian sexual minority men participants were significantly more likely to accept a vaccine, compared to White sexual minority male peers (14). A national survey found that Black adults reported being less likely to get a COVID-19 vaccine even if it was free and determined safe by scientists, and cited concerns about safety and side effects more often than distrust in health systems (15). Taken together, these results suggest that concerns related to vaccine safety, potential vaccine side effects, distrust in the political administration, and lack of representation in clinical trials may have also impacted COVID-19 vaccination efforts among SGM and racial/ethnic minority communities (16, 17).
To date, much of the literature on COVID-19 vaccines and testing has focused on individuals over the age of 18, limiting its applicability and generalizability to younger cohorts. This gap in the literature leaves us unable to tailor future pandemic intervention and response programs to meet the needs of this vulnerable population. Consequently, in this study we sought to (1) examine the prevalence of COVID-19 testing and vaccination among YYA by age, race/ethnicity, gender identity, gender modality, and sexual identity in the US; (2) examine the association between demographics and individual-level factors of testing access with COVID-19 testing; and (3) examine the association between demographics and individual-level factors of vaccine concerns with COVID-19 vaccination.
Methods
Procedure
Baseline data for the YYA COVID-19 Study were collected between February 2021 and March 2022 using Research Electronic Data Capture (REDCap). Participants were recruited through social media advertisements, outreach to organizations that serve SGM, Indigenous, and Latinx youth, and an existing participant registry. Over half of the participants (53%) were recruited from social media including Instagram, TikTok, Facebook, Twitter, GroupMe and Reddit, followed by organizations (33%), and individual referrals or existing registries (28%). To be included in the study, participants had to be aged 14–24, reside in the US/US territories, have access to the internet, and provide informed consent/assent. For participants under 18 years, the ability to understand study procedures and decisional capacity was first assessed, based on the UCSD Task Force on Decisional Capacity’s procedures for the determination of decisional capacity in persons participating in research (18), using a modified version of the Evaluation to Consent Form. Participants who completed the baseline survey received a digital $30 VISA card. Study procedures were approved by Northwestern University’s Institutional Review Board (IRB) through expedited review.
Measures
Demographics
A detailed description of demographic measures is presented in the supplement (Supplement A). Demographic measures included age in three groups: 1) 14–17 years, 2) 18–21 years, and 3) 22–24 years; race/ethnicity in seven groups: 1) American Indian/Alaska Native, 2) Asian, 3) Black or African American, 4) Hispanic, 5) Multiracial, and 7) White; sexual identity in six groups: 1) Asexual or asexual spectrum, 2) Bisexual or pansexual, 3) Gay or lesbian, 4) Straight, 5) Queer, and 6) Questioning; gender identity in six groups: 1) Agender, 2) Gender Queer, 3) Man/Boy, 4) Non-binary, 5) Questioning, and 6) Woman/Girl; gender modality in three groups: 1) Cisgender, 2) Trans and Gender Diverse, and 3) Not Sure; and self-report health status in five groups: 1) Excellent, 2) Good, 3) Very good, 4) Fair, and 5) Poor. Participants were asked to enter a five-digit ZIP Code, and were assigned to regions using 2010 Census Regions and Divisions: 1) Northeast, 2) Midwest, 3) South, and 4) West.
COVID-19 Testing
Tested for COVID-19.
Participants were asked to respond “Yes,” “No,” “Prefer not to answer,” or “Don’t know” to the question, “Have you ever been tested for COVID-19?” Individuals who responded “Yes” were asked if they had ever tested positive for COVID-19.
Access to COVID-19 Testing.
Participants were asked to respond to the statement “I know where I can get COVID-19 testing in my community” with “Yes” or “No.” Participants were also asked, “Have you ever sought testing but were unable to get tested?”
COVID-19 Vaccination
Vaccine Receipt.
Participants were asked to respond “Yes,” “No,” “Prefer not to answer,” or “Don’t know” to the question, “Have you received a COVID-19 vaccine?”
COVID-19 Vaccine Concerns.
Participants were asked to respond “Yes” or “No” to two statements, 1) “I don’t think that the vaccine will be safe” and 2) “I’m concerned about side effects from the vaccine.”
Analytic Sample
Three rounds of data-cleaning procedures were implemented to ensure that all individuals within the final analytic sample were unique responses (n=1,055; Figure 1). Responses with missing values (n=7), “Not listed” (n=12), “Prefer not to answer” (n =1), or “Not sure about the question” (n = 1) to demographics, “Native Hawaiian or other Pacific Islander” for race/ethnicity (n=4), and “Two-spirit” for gender identity (n=6), were excluded due to small sample size. For the purpose of this study, we only included individuals who reported “Yes” or “No” to COVID-19 testing and vaccine receipt measures, resulting in a final analytic sample of 983.
Figure 1.
Data Cleaning Flow Chart
Statistical Analyses
Data cleaning, recoding, and statistical analyses were conducted in RStudio version 4.2.1 (RStudio, Boston, MA). Frequencies and percentages were calculated for categorical variables. Chi-square tests were used to determine significant associations between demographics, self-reported health status, and two outcomes: testing for COVID-19 and receiving a COVID-19 vaccine. Bivariate and multivariable logistic regression models were developed to estimate associations between individual variables and each of the two main outcomes: 1) tested for COVID-19 and 2) received a COVID-19 vaccine. Model A1 presented multivariable logistic regression results for demographics and health status as predictors of testing for COVID-19, and Model A2 included additional adjustments for testing-related risk factors: knowing where to get tested and being able to get tested (Table 3). Model B1 presented multivariable logistic regression results for demographics and health status as predictors of COVID-19 vaccine receipt, and Model B2 included additional adjustments for vaccine-related risk factors: distrust in vaccine safety and vaccine side effects concerns (Table 4). Odds ratios (ORs), adjusted odds ratios (aORs), and 95% confidence intervals (CIs) were calculated for all regression models.
Table 3:
Associations Between Demographics, Health Status, Testing Access, and COVID-19 Prevention Testing (N = 983).
| Tested for COVID-19 | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Prevalence | Unadjusted Models | Adjusted Model A1 | Adjusted Model A2 | |||||||
| OR | 95% CI | aOR | 95% CI | aOR | 95% CI | |||||
| Demographics | ||||||||||
| Age, Years | ||||||||||
| 14–17 | 86 (11.51) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| 18–21 | 381 (51.00) | 3.345 | 2.284 | 4.907 | 3.666 | 2.447 | 5.514 | 3.349 | 2.186 | 5.147 |
| 22–24 | 280 (37.48) | 3.765 | 2.497 | 5.706 | 4.249 | 2.758 | 6.592 | 3.655 | 2.320 | 5.792 |
| Race/Ethnicity | ||||||||||
| White | 175 (23.43) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| American Indian or Alaska Native | 76 (10.17) | 1.206 | 0.670 | 2.249 | 1.185 | 0.618 | 2.338 | 1.168 | 0.599 | 2.337 |
| Asian | 50 (6.69) | 0.752 | 0.411 | 1.413 | 0.678 | 0.352 | 1.335 | 0.711 | 0.357 | 1.450 |
| Black | 124 (16.6) | 0.754 | 0.476 | 1.195 | 0.615 | 0.373 | 1.011 | 0.653 | 0.387 | 1.100 |
| Hispanic | 248 (33.2) | 0.908 | 0.604 | 1.358 | 0.874 | 0.565 | 1.345 | 0.877 | 0.555 | 1.376 |
| Multiracial | 74 (9.91) | 0.881 | 0.508 | 1.556 | 0.948 | 0.528 | 1.734 | 0.896 | 0.484 | 1.691 |
| Sexual Identity | ||||||||||
| Straight | 159 (21.29) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Asexual/Ace Spectrum | 33 (4.42) | 0.662 | 0.340 | 1.324 | 0.686 | 0.326 | 1.474 | 0.714 | 0.329 | 1.587 |
| Bisexual/Pansexual | 264 (35.34) | 1.144 | 0.759 | 1.716 | 1.178 | 0.742 | 1.864 | 1.277 | 0.789 | 2.066 |
| Gay/Lesbian | 172 (23.03) | 1.103 | 0.706 | 1.725 | 1.019 | 0.624 | 1.665 | 0.962 | 0.579 | 1.597 |
| Queer | 107 (14.32) | 0.928 | 0.570 | 1.519 | 0.790 | 0.439 | 1.428 | 0.658 | 0.357 | 1.217 |
| Questioning | 12 (1.61) | 0.481 | 0.188 | 1.289 | 0.621 | 0.228 | 1.772 | 0.851 | 0.293 | 2.593 |
| Gender | ||||||||||
| Woman/Girl | 366 (49) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Agender | 7 (0.94) | 0.759 | 0.207 | 3.562 | 0.606 | 0.139 | 3.236 | 0.458 | 0.100 | 2.522 |
| Gender Queer | 19 (2.54) | 0.618 | 0.285 | 1.418 | 0.496 | 0.188 | 1.351 | 0.473 | 0.171 | 1.350 |
| Man/Boy | 206 (27.58) | 1.116 | 0.786 | 1.598 | 1.182 | 0.789 | 1.785 | 1.269 | 0.833 | 1.948 |
| Non-binary | 129 (17.27) | 1.198 | 0.788 | 1.856 | 1.049 | 0.531 | 2.053 | 1.052 | 0.515 | 2.126 |
| Questioning | 20 (2.68) | 0.723 | 0.329 | 1.708 | 1.976 | 0.233 | 12.845 | 1.571 | 0.174 | 11.006 |
| Gender Modality | ||||||||||
| Cisgender | 475 (63.59) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Trans and Gender Diverse | 248 (33.2) | 1.065 | 0.778 | 1.469 | 1.385 | 0.802 | 2.452 | 1.561 | 0.880 | 2.844 |
| Not Sure | 24 (3.21) | 0.694 | 0.340 | 1.504 | 0.451 | 0.084 | 3.344 | 0.560 | 0.098 | 4.414 |
| Health Status | ||||||||||
| Self-reported Health Status | ||||||||||
| Good | 84 (11.24) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Excellent | 269 (36.01) | 1.032 | 0.643 | 1.687 | 1.237 | 0.743 | 2.097 | 1.144 | 0.672 | 1.980 |
| Very good | 247 (33.07) | 1.376 | 0.967 | 1.965 | 1.526 | 1.051 | 2.225 | 1.516 | 1.025 | 2.252 |
| Fair | 120 (16.06) | 1.078 | 0.706 | 1.666 | 1.210 | 0.771 | 1.924 | 1.300 | 0.811 | 2.109 |
| Poor | 27 (3.61) | 4.974 | 1.451 | 31.225 | 4.762 | 1.354 | 30.290 | 5.411 | 1.478 | 35.151 |
| Access to Testing | ||||||||||
| Know where to get tested | ||||||||||
| Agree | 310 (41.50) | Ref | -- | -- | -- | -- | -- | Ref | -- | -- |
| Strongly agree | 358 (47.93) | 2.207 | 1.550 | 3.170 | -- | -- | -- | 2.201 | 1.518 | 3.222 |
| Neutral | 24 (3.21) | 0.307 | 0.169 | 0.555 | -- | -- | -- | 0.301 | 0.160 | 0.565 |
| Disagree | 24 (3.21) | 0.251 | 0.141 | 0.442 | -- | -- | -- | 0.259 | 0.139 | 0.476 |
| Strongly disagree | 31 (4.15) | 0.823 | 0.424 | 1.682 | -- | -- | -- | 0.730 | 0.362 | 1.539 |
| Be able to get tested | ||||||||||
| Yes | 630 (84.34) | Ref | -- | -- | -- | -- | -- | Ref | -- | -- |
| No | 117 (15.66) | 1.032 | 0.694 | 1.566 | -- | -- | -- | 1.072 | 0.688 | 1.701 |
Adjusted Model A1 was adjusted for demographics and health status.
Adjusted Model A2 was adjusted for demographics, health status and factors of access to testing.
aOR is adjusted Odds Ratio; 95%CI is 95% confidence intervals.
Table 4:
Associations Between Demographics Factors, Health Status, Vaccine Concerns, and COVID-19 Vaccination Status (N = 983).
| Received a COVID-19 vaccine | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Prevalence | Unadjusted Models | Adjusted Model B1 | Adjusted Model B2 | |||||||
| OR | 95% CI | aOR | 95% CI | aOR | 95% CI | |||||
| Demographics | ||||||||||
| Age, Years | ||||||||||
| 14–17 | 75 (11.05) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| 18–21 | 338 (49.78) | 2.717 | 1.883 | 3.931 | 2.717 | 1.827 | 4.058 | 2.562 | 1.680 | 3.922 |
| 22–24 | 266 (39.18) | 3.865 | 2.597 | 5.786 | 4.142 | 2.693 | 6.420 | 4.218 | 2.671 | 6.718 |
| Race/Ethnicity | ||||||||||
| White | 114 (16.79) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| American Indian/Alaska Native | 73 (10.75) | 3.385 | 1.980 | 5.987 | 3.915 | 2.157 | 7.328 | 6.965 | 3.590 | 14.070 |
| Asian | 40 (5.89) | 1.343 | 0.781 | 2.330 | 1.423 | 0.793 | 2.580 | 1.409 | 0.767 | 2.616 |
| Black | 127 (18.7) | 2.810 | 1.836 | 4.354 | 2.891 | 1.829 | 4.626 | 4.536 | 2.757 | 7.599 |
| Hispanic | 255 (37.56) | 3.497 | 2.421 | 5.085 | 3.624 | 2.444 | 5.412 | 4.713 | 3.104 | 7.229 |
| Multiracial | 70 (10.31) | 2.434 | 1.474 | 4.102 | 2.800 | 1.644 | 4.874 | 3.055 | 1.751 | 5.464 |
| Sexual Identity | ||||||||||
| Straight | 139 (20.47) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Asexual/Ace Spectrum | 29 (4.27) | 0.741 | 0.393 | 1.415 | 1.052 | 0.510 | 2.200 | 0.813 | 0.380 | 1.761 |
| Bisexual/Pansexual | 233 (34.32) | 1.133 | 0.784 | 1.635 | 1.296 | 0.846 | 1.985 | 0.967 | 0.608 | 1.532 |
| Gay/Lesbian | 163 (24.01) | 1.411 | 0.935 | 2.137 | 1.593 | 1.001 | 2.544 | 1.207 | 0.728 | 2.001 |
| Queer | 98 (14.43) | 1.088 | 0.694 | 1.716 | 1.260 | 0.723 | 2.211 | 1.054 | 0.584 | 1.909 |
| Questioning | 17 (2.5) | 2.894 | 0.934 | 12.690 | 3.647 | 1.075 | 17.002 | 2.615 | 0.751 | 12.343 |
| Gender | ||||||||||
| Woman/Girl | 342 (50.37) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Agender | 6 (0.88) | 0.627 | 0.177 | 2.484 | 0.666 | 0.156 | 3.133 | 0.480 | 0.106 | 2.400 |
| Gender Queer | 18 (2.65) | 0.684 | 0.319 | 1.530 | 0.756 | 0.297 | 1.972 | 0.757 | 0.284 | 2.067 |
| Man/Boy | 181 (26.66) | 0.890 | 0.645 | 1.233 | 0.995 | 0.680 | 1.462 | 0.924 | 0.616 | 1.391 |
| Non-binary | 114 (16.79) | 0.953 | 0.651 | 1.409 | 1.327 | 0.718 | 2.451 | 1.239 | 0.651 | 2.356 |
| Questioning | 18 (2.65) | 0.684 | 0.319 | 1.530 | 3.411 | 0.483 | 24.147 | 2.157 | 0.273 | 17.826 |
| Gender Modality | ||||||||||
| Cisgender | 445 (65.54) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Trans and Gender Diverse | 213 (31.37) | 0.795 | 0.596 | 1.062 | 0.846 | 0.514 | 1.405 | 0.848 | 0.501 | 1.448 |
| Not Sure | 21 (3.09) | 0.610 | 0.306 | 1.251 | 0.218 | 0.036 | 1.310 | 0.357 | 0.050 | 2.427 |
| Health Status | ||||||||||
| Self-reported Health Status | ||||||||||
| Good | 73 (10.75) | Ref | -- | -- | Ref | -- | -- | Ref | -- | -- |
| Excellent | 224 (32.99) | 0.770 | 0.493 | 1.210 | 0.828 | 0.507 | 1.362 | 0.933 | 0.553 | 1.587 |
| Very good | 236 (34.76) | 0.827 | 0.599 | 1.142 | 0.894 | 0.631 | 1.266 | 1.018 | 0.704 | 1.473 |
| Fair | 124 (18.26) | 1.448 | 0.944 | 2.256 | 1.786 | 1.117 | 2.904 | 1.991 | 1.218 | 3.311 |
| Poor | 22 (3.24) | 1.358 | 0.589 | 3.527 | 1.467 | 0.605 | 3.978 | 1.465 | 0.573 | 4.230 |
| Vaccine Concerns | ||||||||||
| Distrust in Vaccine Safety | -- | -- | -- | -- | -- | |||||
| No | 630 (92.78) | Ref | -- | -- | -- | -- | -- | Ref | -- | -- |
| Yes | 49 (7.22) | 0.229 | 0.155 | 0.337 | -- | -- | -- | 0.202 | 0.123 | 0.329 |
| Vaccine Side Effects Concerns | ||||||||||
| No | 544 (81.59) | Ref | -- | -- | -- | -- | -- | Ref | -- | -- |
| Yes | 125 (18.41) | 0.356 | 0.263 | 0.481 | -- | -- | -- | 0.456 | 0.315 | 0.661 |
Adjusted Model B1 was adjusted for demographics and health status.
Adjusted Model B2 was adjusted for demographics, health status and factors of vaccine concerns.
aOR is adjusted Odds Ratio; 95%CI is 95% confidence intervals.
Results
Demographics Characteristics
Nearly half of participants (48.73%) were between the ages of 14 and 17 years (Table 1). The majority of the sample identified as cisgender (63.68%), with 32.76% identifying as transgender or gender diverse. Approximately one-half (49.34%) of the sample identified as woman/girl followed by man/boy (27.06%) and gender non-binary (16.68%). Nearly one-third of the sample identified as Hispanic (33.16%), followed by white (22.89%) and Black (17.40%). Over one-third (34.38%) of the sample was bisexual/pansexual, followed by gay/lesbian (22.58%), straight (21.36%) and queer (14.65%). The majority (69.07%) reported very good or good health with 16.38% reporting fair health. One-third of participants (30.42%) were from the South, followed by the Northeast (25.13%), Midwest (22.89%), and West (21.16%). Four participants were from the US territories of Puerto Rico and Guam.
Table 1:
Differences in COVID-19 Testing and Vaccination by Demographics and Health Status (N = 983).
| Tested for COVID-19 | Received a COVID-19 vaccine | ||||||
|---|---|---|---|---|---|---|---|
| N (%) | Yes | No | Chi- Square d p-value | Yes | No | Chi- Square d p-value | |
| Total | 983 | 747 (75.99) | 236 (24.01) | 679 (69.07) | 304 (30.93) | ||
| Demographics | |||||||
| Age, Years | <0.001 | <0.001 | |||||
| 14–17 | 160 (48.73) | 86 (53.75) | 74 (46.25) | 75 (46.88) | 85 (53.12) | ||
| 18–21 | 479 (16.28) | 381 (79.54) | 98 (20.46) | 338 (70.56) | 141 (29.44) | ||
| 22–24 | 344 (34.99) | 280 (81.40) | 64 (18.60) | 266 (77.33) | 78 (22.67) | ||
| Race/Ethnicity | 0.665 | <0.001 | |||||
| White | 225 (22.89) | 175 (77.78) | 50 (22.22) | 114 (50.67) | 111 (49.33) | ||
| American Indian or Alaska Native | 94 (9.56) | 76 (80.85) | 18 (19.15) | 73 (77.66) | 21 (22.34) | ||
| Asian | 69 (7.02) | 50 (72.46) | 19 (27.54) | 40 (57.97) | 29 (42.03) | ||
| Black | 171 (17.40) | 124 (72.51) | 47 (27.49) | 127 (74.27) | 44 (25.73) | ||
| Hispanic | 326 (33.16) | 248 (76.07) | 78 (23.93) | 255 (78.22) | 71 (21.78) | ||
| Multiracial | 98 (9.97) | 74 (75.51) | 24 (24.49) | 70 (71.43) | 28 (28.57) | ||
| Sexual Identity | 0.293 | 0.188 | |||||
| Straight | 210 (21.36) | 159 (75.71) | 51 (24.29) | 139 (66.19) | 71 (33.81) | ||
| Asexual/Ace Spectrum | 49 (4.98 ) | 33 (67.35) | 16 (32.65) | 29 (59.18) | 20 (40.82) | ||
| Bisexual/Pansexual | 338 (34.38) | 264 (78.11) | 74 (21.89) | 233 (68.93) | 105 (31.07) | ||
| Gay/Lesbian | 222 (22.58) | 172 (77.48) | 50 (22.52) | 163 (73.42) | 59 (26.58) | ||
| Queer | 144 (14.65) | 107 (74.31) | 37(25.69) | 98 (68.06) | 46 (31.94) | ||
| Questioning | 20 (2.03) | 12 (60.00) | 8 (40.00) | 17 (85.00) | 3 (15.00) | ||
| Gender | 0.587 | 0.801 | |||||
| Woman/Girl | 485 (49.34) | 366 (75.46) | 119 (24.54) | 342 (70.52) | 143 (29.48) | ||
| Agender | 10 (1.02 ) | 7 (70.00) | 3 (30.00) | 6 (60.00) | 4 (40.00) | ||
| Gender Queer | 29 (2.95) | 19 (65.52) | 10 (34.48) | 18 (62.07) | 11 (37.93) | ||
| Man/Boy | 266 (27.06) | 206 (77.44) | 60 (22.56) | 181 (68.05) | 85 (31.95) | ||
| Non-binary | 164 (16.68) | 129 (78.66) | 35 (21.34) | 114 (69.51) | 50 (30.49) | ||
| Questioning | 29 (2.95) | 20 (68.97) | 9 (31.03) | 18 (62.07) | 11 (37.93) | ||
| Gender Modality | 0.536 | 0.148 | |||||
| Cisgender | 626 (63.68) | 475 (75.88) | 151 (24.12) | 445 (71.09) | 181 (28.91) | ||
| Trans and Gender Diverse | 322 (32.76) | 248 (77.02) | 74 (22.98) | 213 (66.15) | 109 (33.85) | ||
| Not Sure | 35 (3.56) | 24 (68.57) | 11 (31.43) | 21 (60.00) | 14 (40.00) | ||
| Self-report Health Status | 0.081 | 0.07 | |||||
| Health Status | 0.081 | 0.07 | |||||
| Excellent | 114 (11.6) | 84 (73.68) | 30 (26.32) | 73 (64.04) | 41 (35.96) | ||
| Good | 338 (34.38) | 247 (73.08) | 91 (26.92) | 236 (69.82) | 102 (30.18) | ||
| Very good | 341 (34.69) | 269 (78.89) | 72 (21.11) | 224 (65.69) | 117 (34.31) | ||
| Fair | 161 (16.38) | 120 (74.53) | 41 (25.47) | 124 (77.02) | 37 (22.98) | ||
| Poor | 29 (2.95) | 27 (93.10) | 2 (6.90) | 22 (75.86) | 7 (24.14) | ||
COVID-19-related Measures
Per Table 2, 75.99% of participants were tested for COVID-19, with 14.19% of them testing positive. Most participants knew where to get tested in the community and were able to get tested (84.44%). Nearly one-third (32.03%) identified limited test availability as the key reason for their inability to get tested. The majority of the sample reported receiving at least one dose of the COVID-19 vaccine (69.07%). 12.82% and 24.72% of the participants expressed concerns about vaccine safety and side effects, respectively.
Table 2:
Measures related to COVID-19 Testing, Testing Access, Vaccination and Vaccine Concerns (N = 983).
| Measures | N (%) |
|---|---|
| COVID-19 Testing | |
| Tested for COVID-19 | |
| No | 236 (24.01) |
| Yes | 747 (75.99) |
| Tested positive for COVID-19 | |
| Yes | 106 (14.19) |
| No | 636 (85.14) |
| Don’t know | 4 (0.54) |
| Prefer not to answer | 1 (0.13) |
| COVID-19 Testing Access | |
| Know where to get tested | |
| Agree | 417 (42.42) |
| Strongly agree | 414 (42.12) |
| Neutral | 51 (5.19) |
| Disagree | 57 (5.8) |
| Strongly disagree | 44 (4.48) |
| Able to get tested | |
| Yes | 830 (84.44) |
| No | 153 (15.56) |
| Reasons why unable to get tested | |
| Limited available tests | 49 (32.03) |
| Did not meet criteria for testing | 46 (23.53) |
| Unable to find a testing site | 44 (28.76) |
| Other reasons | 24 (15.69) |
| COVID-19 Vaccination | |
| Received Vaccine | |
| Yes | 679 (69.07) |
| No | 304 (30.93) |
| COVID-19 Vaccine Concerns | |
| Distrust in Vaccine Safety | |
| Yes | 126 (12.82) |
| No | 857 (87.18) |
| Vaccine Side Effects Concerns | |
| Yes | 243 (24.72) |
| No | 740 (75.28) |
Tested for COVID-19 Outcome
In unadjusted models, significant differences in COVID-19 testing were found by age, health status, and two testing-related risk factors: testing site awareness and being able to get tested (Table 3). Adjusted models (i.e., Models A1 and A2) continue to show a significant association between age and COVID-19 testing. Specifically, compared with individuals ages 14–17 years, those 18–21 (aOR = 3.349; 95% CI: [2.186, 5.147]) and 22–24 (aOR = 3.655; 95% CI: [2.320, 5.792]) were over three times as likely to report COVID-19 testing. After controlling for other factors (i.e., Model A2), those with “poor” health status were more likely to get tested (aOR = 5.411; 95% CI: [1.478, 35.151]) compared to their counterparts with “good” health. Individuals who disagreed with (aOR = 0.259; 95% CI: [0.139, 0.476]) or were neutral towards (aOR = 0.301; 95% CI: [0.160, 0.565]) knowing where to get tested were less likely to test for COVID-19 compared to their knowledgeable peers.
Received a COVID-19 Vaccine Outcome
Unadjusted models also show COVID-19 vaccination status was significantly different based on participants’ age, race/ethnicity, and other vaccine-related risk factors (Table 4). Similar to above, adjusted models (see Model B1, Model B2) continue to show significant differences in COVID-19 vaccination based on age. Specifically, those 22–24 years were four times as likely to report receiving the COVID-19 vaccine when compared to their peers in the 14–17 year age group (aOR = 4.218; 95% CI: [2.671, 6.718]). Controlling for vaccine-related concerns (Model B1) including distrust in vaccines and concerns about side effects led to a significant increase in vaccination odds among all groups except Asian individuals. For instance, American Indian/Alaska Native individuals were nearly seven times as likely to report receiving the vaccine (aOR = 6.965; 95% CI: [3.590–14.070]) when compared to their white peers. Similarly, Black (aOR = 4.536; 95% CI: [2.757, 7.599]) and Hispanic (aOR = 4.713; 95% CI: [3.104, 7.229]) individuals were nearly 5 times as likely to report receiving the vaccine when compared to their white counterparts.
Model B1 also indicated a significant difference based on sexual identities. When compared to straight individuals, gay and lesbian individuals (aOR = 1.593; 95% CI: [1.001, 2.544]), as well as those who are questioning their sexual identity (aOR = 3.647; 95% CI: [1.075, 17.002]), were more likely to report receiving a vaccine. The wide confidence intervals here indicate estimation instability due to the smaller sample size of individuals who were questioning their sexual identities (n = 17). Although vaccine-related concerns significantly lowered the likelihood of receiving a vaccine, no significant differences based on sexual identity were found after adjusting for vaccine-related concerns.
Discussion
COVID-19 Testing
The overall COVID-19 testing rate in our sample was high (75.99%), with 14.19% of participants reporting having tested positive at least once in their lifetime. Individuals aged 14–17 reported the lowest testing rate in our sample (11.51%). These results are likely to be related to a number of testing sites- including healthcare centers and private or public schools- requiring a parent or legal guardian to sign a consent form for children under 18 (19, 20). Our findings affirmed prior research demonstrating that age was a strong predictor of COVID-19 testing among youth; however, inclusion of other potential factors such as geographic location and employment status could provide additional nuance (21). For instance, YYA living in urban areas may have more access to COVID-19 testing. Indeed, prior research indicates that rural counties consistently yield lower adjusted testing rates than regional urban counties (22).
We found no differences in COVID-19 testing rates by race/ethnicity, sexual orientation, or gender identity, and no significant associations between testing and race/ethnicity, sexual orientation, and gender identity, either before or after controlling for access to testing. Perhaps this can be explained by the broad availability of COVID-19 tests in the US, such as free at-home COVID-19 antigen tests offered by the federal government and federally-funded school-based testing programs for YYA (23). Besides testing access, other crucial factors related to testing location (e.g., school, home, clinic), and types of tests (e.g., PCR-based tests, antigen tests) were not included in our models.
Significant differences in COVID-19 testing were found in self-reported health status. Individuals with “poor” health status were more likely to get tested compared to their counterparts with “good” health in adjusted models. Our wide CIs can be attributed to the small sample size of those with “poor” health conditions. However, as COVID-19 did not affect all population groups equally, a person with an underlying medical condition such as cancer, chronic lung disease, diabetes, or HIV, was more likely to get sick from COVID-19 and therefore, was suggested to test often (24). For example, YYA with HIV may have higher rates of vaccine acceptance and may more willingly engage in protective behaviors due to parallels with messaging around behavior change and prevention for HIV (25).
COVID-19 Vaccination
The majority of our participants had received at least one shot of the vaccine (69.07%), and we observed significant differences in vaccination rates by age group. When compared to individuals aged 14–17 years, those aged 18–21 years and 22–24 years were over two times and four times as likely to report receiving the COVID-19 vaccine, respectively. First, this could be explained by delayed and limited vaccination authorization among youth, which did not occur until July 2021, four months after our data collection began. Also, among the three COVID-19 vaccines authorized for use in the US, only Pfizer’s was authorized for adolescents aged 12–17 years (26). Besides availability, youth’s attitude and intention to get vaccine needs to be considered. On the one hand, younger adults might have more concerns about vaccine safety and necessity, as studies have found significant and negative associations between vaccine-related concerns and vaccination intentions among youth (27), which may lead to lower vaccination rates among younger YYA compared to older YYA. On the other hand, vaccine uptake was contingent on parental-related factors including parents’ intentions to vaccinate their children (28), parents’ concerns about vaccine safety and side effects (29), and parental vaccine status (30), which may affect the differences in vaccination rates. However, research in this area is mixed. Another study demonstrated that while there were no significant changes in parental intention to vaccinate their adolescent children over time, receipt of ≥1 dose of COVID-19 vaccine among adolescents aged 12–17 years increased across four months (31). These data suggest that youth’s personal beliefs and intentions may be a more salient driver of their vaccine behavior (32, 33). In addition, youth preferred “an easy sign-up process” and convenient locations for getting a vaccination (34), which could bolster low vaccination rates.
In our sample, Hispanic individuals made up the largest share of people who received at least one dose of the COVID-19 vaccine (37.56%), followed by Black (18.70%) and white YYA (16.79%). We found that all race/ethnicity groups except for Asian individuals were significantly more likely to report receiving a vaccine compared to their white peers. Our results stand at odds with prevailing COVID-19 vaccine uptake research among racial/ethnic minorities. Differences in parental vaccine hesitancy and intentions by race/ethnicity groups may explain the disparities, as parents or guardians are often the decision-makers regarding their children’s vaccinations (35). Prior studies found that, compared to other racial/ethnic groups, white parents reported higher vaccine hesitancy, significantly more COVID-19 misconceptions, and overall less support for vaccinating young children against COVID-19 (36).
In addition, disparities in vaccine intentions may relate to youth’s status as sexual and gender minorities. While research in this area is scarce, a diverse survey conducted in the US and Canada of more than 7,000 SGM participants from June 2021, almost 70% of respondents including 80% of Hispanic-identifying respondents had already been vaccinated with 84% of non-vaccinated individuals reporting a desire to get vaccinated as soon as possible (37). A more recent study demonstrated high levels of COVID-19 vaccine uptake among Hispanic sexual minority men, as over 60% of their sample had scheduled an appointment to get the vaccine or already received the vaccine (38). Due to the nascency of this literature in this area, we are unable to clearly elucidate the full extent of this disparity. Future vaccine uptake research would benefit from considering how intersectional identities of participants may influence vaccine-related attitudes and behaviors.
Gay/lesbian YYA were more likely to report receiving a vaccination than straight YYA, after adjusting for demographics and health status; however, this association was no longer significant after adjusting for vaccine-related concerns. A potential explanation for this finding is that vaccine concerns were common factors of vaccination hesitancy among YYA, regardless of sexual identity. In fact, one study that comprehensively assessed vaccine attitudes among SGM youth found no significant differences in vaccine acceptance between gay/bisexual and heterosexual youth, which supports our interpretation (25). However, critical concerns related to vaccination access, particularly among sexual minority populations, were not included in our models. Although there was limited research among YYA, negative healthcare experiences including medical mistrust, social concerns, discrimination in accessing government services, and delayed healthcare were reported among SGM adults (16, 39). It should be pointed out that most of the existing COVID-19 vaccine hesitancy studies have failed to consider the unique perspectives of SGM individuals. Such studies and research among SGM YYA are even more limited, indicating that this population needs urgent attention in future investigations.
Limitations
Our work is not without limitations. First, due to its specific focus on YYA, our findings are not generalizable to the current US population. Due to the timing of the survey and the rapidly changing prevention landscape, our study did not collect data on access, attitudes, and behavioral intent towards COVID-19 vaccine boosters, which were dubbed a crucial preventive measure against seasonal surges and the emergence of new COVID-19 variants. Another major limitation in our study is the absence of factors related to parental attitudes and intention to vaccinate their children, which might affect vaccine uptake among YYA (31, 33). Attention to attitudes toward boosters can help our understanding of the ongoing battle against the COVID-19 pandemic. Lastly, in the US, the response to the COVID-19 pandemic varied across states. For instance, studies identified higher vaccination rates among Black teenagers than white teenagers in the Southern states (40). However, regional differences were not assessed in our analyses. Future endeavors can focus on state-level differences by controlling for the impact of state-level policies and public health department responses to the COVID-19 pandemic.
Conclusion
The current study provides national data on COVID-19 testing, vaccination, and vaccine intention in a diverse sample of YYA. To date, little research has focused on COVID-19 testing and vaccination rates, barriers to testing access, and vaccine concerns among YYA; our study addressed this gap and expanded the focus to racial, ethnic, sexual, and gender minority YYA. Our results indicated the importance of and the need for further data collection and research on COVID-19 prevention among YYAs with marginalized identities.
Supplementary Material
Highlights.
The overall COVID-19 testing rate was high (76%) among youth and young adults (YYA)
The majority of YYAs had received at least one shot of the COVID-19 vaccine (69%)
Older YYAs were more likely to report being tested or received a COVID-19 vaccine
Found no differences in testing rates by race/ethnicity, sexual and gender identity
Research on COVID-19 prevention among YYAs with marginalized identities is needed
Acknowledgments
This study was supported by a grant from the National Institute on Alcohol Abuse and Alcoholism (R01 AA024409–05S1, Principal Investigator: Phillips). The study sponsors had no role in the creation of this manuscript.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Ethical Consideration
All study procedures have been reviewed and approved by the Northwestern University Institutional Review Board (approval no. STU00213711) on January 12, 2021.
References
- 1.Hawes MT, Szenczy AK, Klein DN, Hajcak G, Nelson BD. Increases in depression and anxiety symptoms in adolescents and young adults during the COVID-19 pandemic. Psychol Med. 2022;52(14):3222–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Krause KH, Verlenden JV, Szucs LE, Swedo EA, Merlo CL, Niolon PH, et al. Disruptions to School and Home Life Among High School Students During the COVID-19 Pandemic - Adolescent Behaviors and Experiences Survey, United States, January-June 2021. MMWR Suppl. 2022;71(3):28–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Glantsman O, McGarity-Palmer R, Swanson HL, Carroll JT, Zinter KE, Lancaster KM, et al. Risk of food and housing insecurity among college students during the COVID-19 pandemic. J Community Psychol. 2022;50(6):2726–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Jone PN, John A, Oster ME, Allen K, Tremoulet AH, Saarel EV, et al. SARS-CoV-2 Infection and Associated Cardiovascular Manifestations and Complications in Children and Young Adults: A Scientific Statement From the American Heart Association. Circulation. 2022;145(19):E1037–E52. [DOI] [PubMed] [Google Scholar]
- 5.Roessler MTF, Batram M, Jacob J, Loser F, Weidinger O, et al. Post-COVID-19-associated morbidity in children, adolescents, and adults: A matched cohort study including more than 157,000 individuals with COVID-19 in Germany. PLOS Medine. 2022;19(11):e1004112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chadi N, Ryan NC, Geoffroy MC. COVID-19 and the impacts on youth mental health: emerging evidence from longitudinal studies. Can J Public Health. 2022;113(1):44–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mackey K, Ayers CK, Kondo KK, Saha S, Advani SM, Young S, et al. Racial and Ethnic Disparities in COVID-19-Related Infections, Hospitalizations, and Deaths A Systematic Review. Annals of Internal Medicine. 2021;174(3):362.−+. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Fish JN, Salerno J, Williams ND, Rinderknecht RG, Drotning KJ, Sayer L, et al. Sexual Minority Disparities in Health and Well-Being as a Consequence of the COVID-19 Pandemic Differ by Sexual Identity. LGBT Health. 2021;8(4):263–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Salerno JP, Devadas J, Pease M, Nketia B, Fish JN. Sexual and Gender Minority Stress Amid the COVID-19 Pandemic: Implications for LGBTQ Young Persons’ Mental Health and Well-Being. Public Health Reports. 2020;135(6):721–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Haldar S, Artiga S. Overview of Data on Race/Ethnicity of COVID-19 Booster Shot Recipients KFF; 2021.
- 11.Salomon JA, Reinhart A, Bilinski A, Chua EJ, La Motte-Kerr W, Ronn MM, et al. The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination. P Natl Acad Sci USA. 2021;118(51). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Prevention CfDCa. COVID Data Tracker 2023. [Available from: https://covid.cdc.gov/covid-data-tracker.
- 13.Scherer AM, Gedlinske AM, Parker AM, Gidengil CA, Askelson NM, Petersen CA, et al. Acceptability of adolescent COVID-19 vaccination among adolescents and parents of adolescents—United States, April 15–23, 2021. Morbidity and Mortality Weekly Report. 2021;70(28):997. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Martino RJ, Krause KD, Griffin M, LoSchiavo C, Comer-Carruthers C, Karr AG, et al. A Nationwide Survey of COVID-19 Testing in LGBTQ+ Populations in the United States. Public Health Reports. 2021;136(4):493–507. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Liz Hamel LL, Cailey Muñana, Samantha Artiga, Mollyann Brodie. Race, Health, and COVID-19: The Views and Experiences of Black Americans. Kaiser Family Foundation; 2020. October. [Google Scholar]
- 16.da Silva DT, Biello K, Lin WY, Valente PK, Mayer KH, Hightow-Weidman L, et al. COVID-19 Vaccine Acceptance among an Online Sample of Sexual and Gender Minority Men and Transgender Women. Vaccines-Basel. 2021;9(3). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Garg I, Hanif H, Javed N, Abbas R, Mirza S, Javaid MA, et al. COVID-19 Vaccine Hesitancy in the LGBTQ plus Population: A Systematic Review. Infect Dis Rep. 2021;13(4):872–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Capacity UTFoD. Procedures for determination of decisional capacity in persons participating in research protocols. 2003. [Available from: http://irb.ucsd.edu/decisional.shtml.
- 19.Smith-Norowitz TA, Hammerschlag MR, Kohlhoff S. Coronavirus disease 2019 (COVID-19) infection rates in a private school in Brooklyn, New York. Acta Paediatr. 2021;110(5):1569–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. HealthyChildren.org. COVID-19 Testing and Kids: What you Should Know 2022. [Available from: https://www.healthychildren.org/English/health-issues/conditions/COVID-19/Pages/Should-Your-Child-Be-Tested-for-COVID-19.aspx.
- 21.Islam MI, Chadwick V, Martiniuk A. Identifying potential factors associated with PCR testing for COVID-19 among Australian young people: cross-sectional findings from a longitudinal study. Bmc Public Health. 2022;22(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Souch JM, Cossman JS. A Commentary on Rural-Urban Disparities in COVID-19 Testing Rates per 100,000 and Risk Factors. J Rural Health. 2021;37(1):188–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.House TW. FACT SHEET: Biden-Harris Administration Increases COVID-19 Testing in Schools to Keep Students Safe and Schools Open 2022. [Available from: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/12/fact-sheet-biden-harris-administration-increases-covid-19-testing-in-schools-to-keep-students-safe-and-schools-open/.
- 24.Gupta R, Hussain A, Misra A. Diabetes and COVID-19: evidence, current status and unanswered research questions. European Journal of Clinical Nutrition. 2020;74(6):864–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Swendeman D, Norwood P, Saleska J, Lewis K, Ramos W, SantaBarbara N, et al. Vaccine Attitudes and COVID-19 Vaccine Intentions and Prevention Behaviors among Young People At-Risk for and Living with HIV in Los Angeles and New Orleans. Vaccines-Basel. 2022;10(3). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hause AM, Gee J, Baggs J, Abara WE, Marquez P, Thompson D, et al. COVID-19 Vaccine Safety in Adolescents Aged 12–17 Years - United States, December 14, 2020-July 16, 2021. Mmwr-Morbid Mortal W. 2021;70(31):1053–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Rogers AA, Cook RE, Button JA. Parent and Peer Norms are Unique Correlates of COVID-19 Vaccine Intentions in a Diverse Sample of US Adolescents. J Adolescent Health. 2021;69(6):910–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Pan FM, Zhao HY, Nicholas S, Maitland E, Liu RG, Hou QZ. Parents’ Decisions to Vaccinate Children against COVID-19: A Scoping Review. Vaccines-Basel. 2021;9(12). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Szilagyi PG, Shah MD, Delgado JR, Thomas K, Vizueta N, Cui Y, et al. Parents’ Intentions and Perceptions About COVID-19 Vaccination for Their Children: Results From a National Survey. Pediatrics. 2021;148(4). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Gray A, Fisher CB. Determinants of COVID-19 Vaccine Uptake in Adolescents 12–17 Years Old: Examining Pediatric Vaccine Hesitancy Among Racially Diverse Parents in the United States. Front Public Health. 2022;10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Nguyen KH, Nguyen K, Geddes M, Allen JD, Corlin L. Trends in adolescent COVID-19 vaccination receipt and parental intent to vaccinate their adolescent children, United States, July to October, 2021. Ann Med. 2022;54(1):733–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Hilverda F, Vollmann M. The Role of Risk Perception in Students’ COVID-19 Vaccine Uptake: A Longitudinal Study. Vaccines-Basel. 2022;10(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Middleman AB, Klein J, Quinn J. Vaccine Hesitancy in the Time of COVID-19: Attitudes and Intentions of Teens and Parents Regarding the COVID-19 Vaccine. Vaccines-Basel. 2022;10(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Gorga SM, Brandt EJ, Rosenberg J, Waselewski ME, Amaro X, Chang T. Youth Perceptions of Vaccination for COVID-19 in the United States. Jama-Health Forum. 2021;2(8). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Zhang KC, Fang Y, Cao H, Chen HB, Hu T, Chen YQ, et al. Parental Acceptability of COVID-19 Vaccination for Children Under the Age of 18 Years: Cross-Sectional Online Survey. Jmir Pediatr Parent. 2020;3(2). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Fisher CB, Gray A, Sheck I. COVID-19 Pediatric Vaccine Hesitancy among Racially Diverse Parents in the United States. Vaccines (Basel). 2021;10(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Foundation TaS. It’s For Us: COVID-19 Vaccination and the LGBTQ+ community. 2021.
- 38.Weinstein ER, Balise R, Metheny N, Robba MJB, Mayo D, Michel C, et al. Factors associated with latino sexual minority men’s likelihood and motivation for obtaining a COVID-19 vaccine: a mixed-methods study. J Behav Med. 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Andraska EA, Alabi O, Dorsey C, Erben Y, Velazquez G, Franco-Mesa C, et al. Health care disparities during the COVID-19 pandemic. Semin Vasc Surg. 2021;34(3):82–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Chatlani S Why Black teens are getting vaccinated at higher rates than white teens across the South 2021. [Available from: https://www.wwno.org/news/2021-11-04/why-black-teens-are-getting-vaccinated-at-higher-rates-than-white-teens-across-the-south.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.