Abstract
Objective
This study evaluated vaccine hesitancy (VH) scores in transgender and gender-diverse patients for four vaccines: human papillomavirus (HPV), hepatitis B (HBV), influenza, and COVID-19.
Methods
A cross-sectional study was conducted at a gender-affirming care clinic in New Mexico, USA. Participants aged >18 years with a diagnosis of gender dysphoria were eligible for inclusion. Participants completed an electronic survey during their clinic visit. Demographic characteristics were collected, and additional survey items were adapted from the Vaccine Hesitancy Scale developed by the SAGE Working Group. Higher VH scores indicated greater hesitancy.
Results
181 participants completed surveys. The mean age was 30.0 years and the majority of participants were white (64.1%). Gender was reported as male (39.8%), female (31.5%), non-binary/non-conforming (24.3%), and prefer not to respond (4.4%). Vaccination rates were: COVID-19 (92.8%), influenza (74.0%), HBV (65.7%), and HPV (61.4%). For all vaccines, overall VH scores were higher (p < 0.01) in the unvaccinated groups. For HBV and influenza vaccines, there were significant differences for each of the 3Cs (confidence, complacency, convenience) between vaccinated and unvaccinated groups (p < 0.001). For HPV, there was a significant difference in confidence (p = 0.03) and convenience (p < 0.01) scores. For COVID-19, there were significant differences in confidence (p < 0.0001) and complacency (p < 0.0001). Hesitancy scores ≥ 2.0 were significantly (p < 0.05) associated with being unvaccinated for all but the HPV vaccine (p > 0.05).
Conclusion
Survey responses from unvaccinated participants indicate a higher degree of VH compared to vaccinated participants. Differing VH determinants were associated with unvaccinated status for the HPV, HBV, influenza, and COVID-19 vaccines.
Keywords: Gender expansive, transgender persons, hesitancy, vaccination, vaccines
Introduction
Vaccine hesitancy is defined by the World Health Organization (WHO) as a delay in acceptance or outright refusal to receive vaccination, even when vaccination services are available (MacDonald & SAGE Working Group on Vaccine Hesitancy, 2015; WHO, 2015). This phenomenon is complex and context-dependent, varying across different times, locations, and types of vaccines. Determinants of vaccine hesitancy, factors associated with or influences on decisions to delay vaccination or refuse vaccination, include various contextual influences, such as socio-cultural factors and group dynamics, as well as vaccine-specific concerns (WHO, 2015). Individuals who are hesitant may refuse or delay some vaccines but agree to others. The 3 C’s model of vaccine hesitancy identifies core factors that determine a person’s willingness to get vaccinated including: (1) their Confidence in the effectiveness and safety of vaccines; (2) their Complacency regarding the perceived risk of preventable diseases; and (3) the Convenience of accessing vaccination services, which may include systemic factors. In the United States (US), vaccination rates have remained stable overall, but there has been a decline in specific states and communities (Wagner et al., 2020). Interest in understanding the determinants of vaccine hesitancy has increased, especially in light of recent experiences with the COVID-19 vaccine and related public controversies over vaccination refusal (Coustasse et al., 2021; McAteer et al., 2020). Vaccine-specific reasons for hesitancy have been identified for various vaccines, including the human papillomavirus (HPV), hepatitis B virus (HBV), and pandemic influenzas such as H1N1 (Bednarczyk, 2019; Constable & Caplan, 2020; Helmkamp et al., 2021; Karafillakis et al., 2017; Moyroud et al., 2017; Szilagyi et al., 2020).
Individual and group influences on vaccine hesitancy have been evaluated in different populations (Karafillakis et al., 2017; MacDonald & SAGE Working Group on Vaccine Hesitancy, 2015; Mitchell et al., 2023; Moyroud et al., 2017; Paterson et al., 2016; Szilagyi et al., 2020; Tankwanchi et al., 2021); however, there is a notable lack of published literature examining vaccine hesitancy in transgender and gender diverse (TGD) populations. TGD individuals encompass a diverse group of people with gender identities and behaviors that extend beyond the traditional binary of male and female, including transgender and non-binary individuals. Reported healthcare barriers for TGD patients include mistrust of the healthcare system, concerns about providers’ clinical competence in delivering appropriate gender-affirming care, potential interactions with gender-affirming therapies, underrepresentation in research, and systemic discrimination - often exacerbated by intersecting identities (Ahuja et al., 2024; Garg et al., 2021; Johnson et al., 2020; Pratt-Chapman et al., 2021). This diminished confidence in healthcare may contribute to individual vaccine hesitancy. For example, a survey of COVID-19 vaccine acceptance among sexual and gender minority men and transgender women found that medical mistrust was significant factor associated with decreased vaccine acceptance (Teixeira da Silva et al., 2021).
Identifying factors that contribute to vaccine hesitancy among TGD patients is essential for understanding the barriers and opportunities for improving vaccination outcomes in this population. The purpose of this study was to: (1) evaluate vaccine hesitancy scores in TGD patients for specific vaccinations, including the human papillomavirus (HPV), hepatitis B (HBV), influenza (Flu), and coronavirus disease 2019 (COVID-19) vaccines; and (2) identify factors, which may include vaccine hesitancy scores, that influence vaccination status. TGD patients have historically been underrepresented in research and the findings of this study will provide valuable data regarding vaccine hesitancy to several vaccines that are important for this population. Insights from this study regarding the factors driving vaccine hesitancy in TGD populations can inform targeted public health strategies aimed at enhancing vaccine uptake and addressing specific barriers, potentially mitigating the risk of vaccine-preventable diseases in this underserved group.
Materials and methods
Study design
A cross-sectional survey study was conducted at the Truman Health Services (THS) Gender-Affirming Clinic at the University of New Mexico (UNM) Health Sciences Center (HSC) in Albuquerque, New Mexico (NM), USA, from 10/12/2022 to 3/13/2024. The UNM THS clinic provides a range of services, including HIV care, HCV care, gender-affirming care, and HIV pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP). THS was founded in 1985 and is the largest provider of gender-affirming care in NM, serving approximately 600 patients. All vaccines recommended on the Centers for Disease Control and Prevention Adult Immunization schedule are available at the clinic.
English-speaking participants aged 18 years or older with a diagnosis of gender dysphoria were eligible for inclusion in the study. Study participant recruitment was conducted through clinic study flyers and by study investigators offering study participation during patients’ regularly scheduled appointments between 12 October 2022 to 13 March 2024. Study investigators prescreened patient charts to confirm study eligibility basted on inclusion criteria (i.e. diagnosis of gender dysphoria, age ≥ 18 years) before offering study participation. Participants completed a self-administered Research Electronic Data Capture (REDCap) survey (Appendix A) on a wireless portable tablet during their scheduled on-site clinic visit. All survey responses were entered directly into REDCap as de-identified responses. However, study participation was documented by study investigators to ensure that no participant completed more than one survey. Participants were compensated for their time with a $25 Target gift card.
Survey design
Survey items (see Appendix A) were adapted from the Vaccine Hesitancy Scale developed by the SAGE Working Group on Vaccine Hesitancy (WHO, 2014). Additional items were also included to assess engagement with and trust of healthcare providers (i.e. “I trust my healthcare providers” [hcp_trust] and “I generally follow what my healthcare provider recommends about vaccines” [hcp_follow]).
Participants completed separate sections of the survey for each of the four vaccines: HPV, HBV, influenza, and COVID-19. Vaccination status for each vaccine was based on self-reported data collected through the survey. Individuals were classified as “vaccinated” or “non-hesitant” if they reported receiving at least one dose of the respective vaccine.
Survey items were categorized according to the “3Cs” model of vaccine hesitancy determinants—Complacency (i.e. perceived disease risk), Convenience (i.e. access to vaccination), and Confidence (i.e. belief in vaccine safety and efficacy)—as defined by the SAGE Working Group on Vaccine Hesitancy [22]. Survey responses were recorded using a 5-point Likert scale and were converted to numerical values. For positively worded items, higher values reflected greater hesitancy (e.g. “Strongly Disagree” = 5 to “Strongly Agree” = 1); for negatively worded items, the scale was reversed (e.g. “Strongly Disagree” = 1 to “Strongly Agree” = 5).
Additional data collected included age, sex assigned at birth, gender identity, race/ethnicity, religion, education level, and whether vaccination was mandated for the participant.
Analysis
Only participants with complete survey responses were included. Descriptive statistics (means and standard deviations [SD] for continuous measures; frequency and percentage for categorical measures) were used to summarize demographic data of the study participants. Differences in participant characteristics between vaccinated and unvaccinated individuals were compared using Chi-square or Fisher’s exact test for categorical variables and t-test or Kruskal-Wallis test for continuous variables, as appropriate. Participants aged ≥18 years were included in the analysis of the HBV, Flu, and COVID-19 vaccines, while the analysis of the HPV vaccine focused on participants aged 18–45 years, in accordance with the current Advisory Committee on Immunization Practices (ACIP) recommendations for adult HPV vaccination.
A vaccine hesitancy score was calculated for each vaccine by averaging responses across all 14 vaccine hesitancy-specific survey items (4 items for Confidence, 5 items for Complacency, and 5 items for Convenience). Higher scores indicated greater vaccine hesitancy.
The association between each vaccine-specific hesitancy score and vaccination status (not vaccinated vs vaccinated) was first investigated using univariate logistic regression models. Next, multivariable regression models were conducted in which models were further adjusted for these sociodemographic characteristics: age (categories), gender (male, female, non-binary/non-conforming/prefer-not-to-answer), race (White, Non-White, Other, Two or more races), Hispanic ethnicity, income (<$20,000, $20,000-$49,000, $50,000 or higher), and education (high school or less, some college/associate degree, college degree or higher). Additional factors related to vaccine hesitancy considered for multivariable regressions were responses for the survey items about: (1) following provider recommendations about vaccines; and (2) whether the vaccine was mandated for the participant (yes/no/don’t know).
For secondary outcomes, predictor variables for the logistic regression model included age, gender, race, ethnicity, income, education, trust in healthcare providers, history of prior infection, comorbidities including HIV, and total vaccine hesitancy score. The influenza and COVID-19 vaccine models also included vaccination mandate as a predictor variable. Vaccination status for each vaccine was the dependent variable in the multivariable logistic regression.
Based on prior published literature (Faul et al., 2009), a priori power calculation was conducted using G*Power (Version 3.1.9.6, Düsseldorf, Germany). With power set to 0.80 and a medium effect size of 0.25, the required sample size was estimated at 180 patients. Statistical tests were two-sided, with a p-value less <0.05 considered statistically significant Study data was analyzed using SAS software (version 9.4, Cary, NC USA) (SAS, 2023).
Results
A total of 193 participants were initially enrolled in the study. However, survey data from 12 participants were excluded from the final analysis; nine participants had incomplete survey responses, two participants had complete survey responses but unverified vaccination status, and one participant was confirmed to be 17 years old. A total of 181 participants completed the full survey and had confirmed vaccination status for each of the vaccines.
Table 1 presents the sociodemographic characteristics of the full cohort (n = 181) and the subset of participants aged 18–45-years (n = 153), which was used for the HPV vaccine-related data analysis throughout the study. In the overall cohort, participants had a mean (± SD) age of 30.0 ± 13.0 years, with 84.5% of the participants aged 45 years or younger. Gender demographics were reported as follows: 39.8% male, 31.5% female, 24.3% non-binary/non-conforming, and 4.4% preferred not to respond. Additionally, 154 (85.1%) participants reported a different assigned sex at birth compared to their gender identity, the additional 14.9% may have identified as non-binary or gender non-conforming. Race was reported as 64.1% white; 37% of participants reported Hispanic/Latinx ethnicity. Educational level reported was some college (no degree) or lower by 58.1% of the population, and 63.5% reported a yearly income of ≤ $35,000. Overall, sociodemographic characteristics were similar for both cohorts.
Table 1.
Patient characteristics.
| Characteristic | Full Cohort (N = 181) N (Freq) |
Age 18–45 (N = 153) N (Freq) |
|---|---|---|
| Age (Mean ± SD) | 33.9 ± 13.0 | 29.5 ± 7.7 |
| Age Category | ||
| Age 18–25 | 57 (31.5%) | 57 (37.3%) |
| Age 26–35 | 56 (30.9%) | 56 (36.6%) |
| Age 36–45 | 40 (22.1%) | 40 (26.1%) |
| Age 46+ | 28 (15.5%) | |
| Gender | ||
| Male | 72 (39.8%) | 65 (42.5%) |
| Female | 57 (31.5%) | 49 (32.0%) |
| Non-binary/non-conforming | 44 (24.3%) | 34 (22.2%) |
| Prefer not to respond | 8 (4.4%) | 5 (3.3%) |
| Sex assigned at birth | ||
| Male | 70 (38.7%) | 56 (36.6%) |
| Female | 98 (54.1%) | 86 (56.2%) |
| Prefer not to respond | 13 (7.2%) | 11 (7.2%) |
| Birth assigned sex vs gender | ||
| Different | 154 (85.1%) | 132 (86.3%) |
| Same | 8 (4.4%) | 7 (4.6%) |
| Unknown | 19 (10.5%) | 14 (9.2%) |
| Race | ||
| American Indian or Alaska Native | 8 (4.4%) | 8 (5.2%) |
| Asian | 2 (1.1%) | 1 (0.7%) |
| Black or African American | 9 (5.0%) | 8 (5.2%) |
| White | 116 (64.1%) | 98 (64.1%) |
| Two or more races | 27 (14.9%) | 24 (15.7%) |
| Other | 19 (10.5%) | 14 (9.2%) |
| Hispanic Ethnicity | 67 (37.0%) | 57 (37.3%) |
| Religion (Religious affiliation) | ||
| Agnostic | 36 (19.9%) | 35 (22.9%) |
| Atheist | 29 (16.0%) | 26 (17.0%) |
| Buddhist | 3 (1.7%) | 0 (0.0%) |
| Catholic | 9 (5.0%) | 8 (5.2%) |
| Christian | 15 (8.3%) | 11 (7.2%) |
| Jewish | 7 (3.9%) | 4 (2.6%) |
| Other | 62 (34.3%) | 53 (34.6%) |
| Prefer not to respond | 20 (11.0%) | 16 (10.5%) |
| Estimated yearly income | ||
| Less than $20,000 | 73 (40.3%) | 67 (43.8%) |
| $20,000 to $34,999 | 42 (23.2%) | 34 (22.2%) |
| $35,000 to $49,999 | 25 (13.8%) | 20 (13.1%) |
| $50,000 to $74,999 | 20 (11.0%) | 16 (10.5%) |
| $75,000 or higher | 21 (11.6%) | 16 (10.5%) |
| Education | ||
| ≤ high school degree or equivalent | 52 (28.8%) | 47 (30.7%) |
| Some college or Associate degree | 76 (42.0%) | 61 (39.9%) |
| Bachelor’s degree or higher | 53 (29.3%) | 45 (29.4%) |
Table 2 summarizes survey responses relating to healthcare providers. More than 90% of participants had a visit with their primary care provider within the prior year. Nearly all participants (176 [97.2%]) strongly agreed/agreed that they, “Trusted their health provider” and 171 (94.4%) strongly agreed/agreed that they, “Generally followed what their healthcare provider recommends about vaccines”. A majority (90.6%) of participants indicated that “Their provider recommended that they receive a vaccine in the last year” and of those receiving vaccine recommendations, 73.2% received all vaccines that were recommended, 19.5% received some of the vaccines that were recommended and 7.3% did not receive the vaccines that were recommended.
Table 2.
Survey responses concerning provider.
| Full Cohort (N = 181) | Age 18–45 (N = 153) | |
|---|---|---|
| Have you attended a visit with a primary care provider in the past year? | ||
| No | 10 (5.5%) | 10 (6.5%) |
| Yes | 171 (94.5%) | 143(93.5%) |
| If yes, approximately how many appointments have you had with a primary care provider in the past year? (Mean ± SD (N)) | 2.7 ± 1.9 (N = 171) | 2.7 ± 1.9 (N = 143) |
| If yes, approximately how many appointments have you had with a primary care provider in the past year? (Median (min-max)) | 2.0 (1.0–12.0) | 2.0 (1.0–12.0) |
| I trust my healthcare providers | ||
| Strongly Disagree | 2 (1.1%) | 1 (0.7%) |
| Neither Agree nor Disagree | 3 (1.7%) | 2 (1.3%) |
| Agree | 71 (39.2%) | 59 (38.6%) |
| Strongly Agree | 105 (58.0%) | 91 (59.5%) |
| I trust my healthcare providers | ||
| Strongly Disagree/Disagree/Neither Agree nor Disagree | 5 (2.8%) | 3 (2.0%) |
| Agree/Strongly Agree | 176 (97.2%) | 150 (98.0%) |
| I generally follow what my healthcare provider recommends about vaccines | ||
| Strongly Disagree | 2 (1.1%) | 1 (0.7%) |
| Disagree | 1 (0.6%) | 1 (0.7%) |
| Neither Agree nor Disagree | 7 (3.9%) | 6 (3.9%) |
| Agree | 75 (41.4%) | 62 (40.5%) |
| Strongly Agree | 96 (53.0%) | 83 (54.2%) |
| I generally follow what my healthcare provider recommends about vaccines | ||
| Strongly Disagree/Disagree/Neither Agree nor Disagree | 10 (5.5%) | 8 (5.2%) |
| Agree/Strongly Agree | 171 (94.5%) | 145 (94.8%) |
| Has your provider recommended that you receive a vaccine in the last year? | ||
| No | 17 (9.4%) | 16 (10.5%) |
| Yes | 164 (90.6%) | 137 (89.5%) |
| If answered yes, whether vaccine received | ||
| Yes, received all of the vaccines that were recommended | 120 (73.2%) | 99 (72.3%) |
| Yes, but only some of the vaccines that were recommended | 32 (19.5%) | 27 (19.7%) |
| No | 12 (7.3%) | 11 (8.0%) |
Table 3 summarizes survey responses regarding receipt of each vaccine and whether the vaccine was mandated. The vaccine with the highest vaccination percentage was COVID-19 (92.8%) followed by Flu (74.0%), HBV (65.7%), and then HPV (61.4%). Everyone who reported the COVID-19 vaccine was a mandated vaccine (66 participants [36.5%]) also reported receiving the vaccine.
Table 3.
Summary of mandate for vaccine and vaccination status.
| HBV | HPV | FLU | Covid | |
|---|---|---|---|---|
| Total (N = 181) | Total (N = 153) | Total (N = 181) | Total (N = 181) | |
| Mandate (Vaccine) | ||||
| Yes | 22 (12.2%) | 8 (5.2%) | 29 (16.0%) | 66 (36.5%) |
| No | 117 (64.6%) | 103 (67.3%) | 126 (69.6%) | 97 (53.6%) |
| Don’t know | 42 (23.2%) | 42 (27.5%) | 26 (14.4%) | 18 (9.9%) |
| Status (vaccine) | ||||
| Vaccinated | 119 (65.7%) | 94 (61.4%) | 134 (74.0%) | 168 (92.8%) |
| Unvaccinated | 62 (34.3%) | 59 (38.6%) | 47 (26.0%) | 13 (7.2%) |
Vaccine specific (HBV, HPV, FLU and COVID-19) questions indicated that participants more often: (1) agreed that the COVID-19 vaccine carried more risk; (2) were more likely to be concerned about the serious adverse effects of the COVID-19 vaccine; and (3) that the COVID-19 vaccine was mandated compared to other vaccines (Table 3). Despite concerns related to the COVID-19 vaccine compared to other vaccines, 168 (92.8%) of participants report being vaccinated for COVID-19.
For all vaccines, the overall hesitancy score was significantly higher (p < 0.01) in unvaccinated vs vaccinated groups (see Figure 1 and Table 4). For HBV and for Flu vaccine there were significant differences for each of the 3Cs (Confidence, Complacency, Convenience) between vaccinated and unvaccinated groups (p < 0.001). For HPV, there was a significant difference in Confidence (p = 0.03) and Convenience (p < 0.01), for COVID-19 there were significant differences in Confidence (p < 0.0001) and Complacency (p < 0.0001). Among the unvaccinated for each vaccine, the COVID-19 vaccine had the highest hesitancy scores for confidence, complacency, and the overall vaccine hesitancy score, and the lowest hesitancy score for convenience, suggesting in unvaccinated patients access was not the issue.
Table 4.
Summary of provider trust, follow provider recommendations, hesitancy Scale components and overall hesitancy Scale score.
|
Variable |
HBV = Vaccinated | HBV = Unvaccinated | P-Value | HPV = Vaccinated | HPV = Unvaccinated | P-Value | FLU = Vaccinated | FLU = Unvaccinated | P-Value | COVID = Vaccinated | COVID = Unvaccinated | P-Value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| /(N = 119) | /(N = 62) | /(N = 94) | /(N = 59) | /(N = 134) | /(N = 47) | /(N = 168) | /(N = 13) | |||||
| Provider Responses | ||||||||||||
| hcp_trust (I trust my healthcare provider) | ||||||||||||
| Agree/Strongly Agree | 116 (97.5%) | 60 (96.8%) | 0.78 | 92 (97.9%) | 58 (98.3%) | 0.85 | 131 (97.8%) | 45 (95.7%) | 0.47 | 163 (97.0%) | 13 (100.0%) | 0.53 |
| Do not Agree | 3 (2.5%) | 2 (3.2%) | 2 (2.1%) | 1 (1.7%) | 3 (2.2%) | 2 (4.3%) | 5 (3.0%) | 0 (0.0%) | ||||
| hcp_follow (I generally follow what my healthcare provider recommends about vaccines) | ||||||||||||
| Agree/Strongly Agree | 113 (95.0%) | 58 (93.5%) | 0.69 | 90 (95.7%) | 55 (93.2%) | 0.49 | 132 (98.5%) | 39 (83.0%) | <.0001 | 162 (96.4%) | 9 (69.2%) | <.0001 |
| Do not Agree | 6 (5.0%) | 4 (6.5%) | 4 (4.3%) | 4 (6.8%) | 2 (1.5%) | 8 (17.0%) | 6 (3.6%) | 4 (30.8%) | ||||
| Hesitancy Scale Components and Overall Hesitancy Scale Score | ||||||||||||
| Confidence | ||||||||||||
| Mean ± SD) | 1.7 ± 0.5 | 1.9 ± 0.5 | 0.001 | 1.7 ± 0.5 | 1.9 ± 0.6 | 0.04 | 1.7 ± 0.5 | 2.2 ± 0.7 | <.0001 | 1.8 ± 0.6 | 2.8 ± 1.0 | <.0001 |
| Median (min-max)) | 1.7 (1.0–3.0) | 2.0 (1.0–3.2) | 1.7 (1.0–3.3) | 1.8 (1.0–3.2) | 1.7 (1.0–3.2) | 2.3 (1.0–3.8) | 1.8 (1.0–3.8) | 2.8 (1.2–4.5) | ||||
| Complacency | ||||||||||||
| Mean ± SD) | 1.7 ± 0.5 | 2.0 ± 0.6 | 0.0003 | 1.7 ± 0.5 | 1.8 ± 0.7 | 0.31 | 1.7 ± 0.5 | 2.4 ± 0.6 | <.0001 | 1.7 ± 0.7 | 2.8 ± 0.9 | <.0001 |
| Median (min-max)) | 1.8 (1.0–3.2) | 2.0 (1.0–3.8) | 1.8 (1.0–3.2) | 1.8 (1.0–3.8) | 1.8 (1.0–3.4) | 2.4 (1.0–3.4) | 1.8 (1.0–3.8) | 2.8 (1.2–4.2) | ||||
| Convenience | ||||||||||||
| Mean ± SD) | 1.9 ± 0.6 | 2.4 ± 0.7 | <.0001 | 1.9 ± 0.6 | 2.3 ± 0.7 | 0.002 | 1.7 ± 0.5 | 2.0 ± 0.6 | 0.0003 | 1.7 ± 0.5 | 1.8 ± 0.6 | 0.41 |
| Median (min-max)) | 2.0 (1.0–3.6) | 2.5 (1.0–3.8) | 2.0 (1.0–3.6) | 2.4 (1.0–3.8) | 1.6 (1.0–3.6) | 2.0 (1.0–3.2) | 1.8 (1.0–3.4) | 2.0 (1.0–2.6) | ||||
| Hesitancy Scale | ||||||||||||
| Mean ± SD) | 1.7 ± 0.5 | 2.1 ± 0.4 | <.0001 | 1.8 ± 0.4 | 2.0 ± 0.5 | 0.01 | 1.7 ± 0.4 | 2.2 ± 0.5 | <.0001 | 1.8 ± 0.5 | 2.5 ± 0.7 | <.0001 |
| Median (min-max)) | 1.8 (1.0–2.7) | 2.1 (1.1–3.3) | 1.8 (1.0–2.7) | 1.9 (1.1–3.1) | 1.6 (1.0–2.9) | 2.3 (1.1–3.1) | 1.7 (1.0–3.3) | 2.3 (1.5–3.6) | ||||
| 2nd Hesitancy Scores:* | ||||||||||||
| Confidence | ||||||||||||
| Mean ± SD) | 1.8 ± 0.6 | 2.1 ± 0.6 | 0.001 | 1.8 ± 0.6 | 2.0 ± 0.7 | 0.03 | 1.8 ± 0.6 | 2.4 ± 0.9 | <.0001 | 2.0 ± 0.8 | 3.3 ± 1.2 | <.0001 |
| Median (min-max)) | 1.8 (1.0–4.0) | 2.0 (1.0–3.3) | 1.8 (1.0–4.0) | 2.0 (1.0–4.0) | 1.8 (1.0–4.0) | 2.5 (1.0–4.5) | 2.0 (1.0–4.8) | 3.3 (1.3–5.0) | ||||
| Hesitancy Scale | ||||||||||||
| Mean ± SD) | 1.8 ± 0.5 | 2.2 ± 0.5 | <.0001 | 1.8 ± 0.5 | 2.0 ± 0.5 | 0.004 | 1.7 ± 0.5 | 2.3 ± 0.5 | <.0001 | 1.8 ± 0.5 | 2.6 ± 0.7 | <.0001 |
| Median (min-max)) | 1.7 (1.0–2.8) | 2.2 (1.1–3.3) | 1.8 (1.0–2.9) | 1.9 (1.1–3.1) | 1.6 (1.0–3.0) | 2.3 (1.1–3.1) | 1.7 (1.0–3.4) | 2.4 (1.6–3.7) | ||||
p-values based on pooled variances t-test.
*Include the 2 additional items for provider (hcp_trust and hcp_follow).
Regarding trust in healthcare providers (hcp_trust), there were no significant differences between the vaccinated and unvaccinated for any of the vaccines between participants levels of agreement or disagreement (see Table 4). For the statement ‘I generally follow what my healthcare provider recommends about vaccines’ (hcp_follow) significantly higher percentages of unvaccinated vs vaccinated responded Strongly Disagree/Disagree/Neither Agree nor Disagree for the Flu (17.0% vs 1.5%, p < 0.0001) and COVID-19 vaccines (30.8% vs 3.6%, p < 0.0001).
In univariate analyses (Table 5) there were significant associations for all vaccines between each unit increase in hesitancy score and being unvaccinated (p < 0.01). Hesitancy scores greater than or equal to 2.0 were significantly (p < 0.05) associated with being unvaccinated for all but the HPV vaccine (p > 0.05). The boxplots of the overall hesitancy score for each vaccine (Figure 1) illustrate there was considerable overlap in hesitancy score distributions for HPV compared to the other three vaccines.
Table 5.
Univariate logistic regression model – odds ratio (95% confidence interval [CI]) for not receiving vaccination.
| Independent | HBV | HPV* | FLU | Covid | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| variable | OR | 95% CI | P-value | OR | 95% CI | P-value | OR | 95% CI | P-value | OR | 95% CI | P-value |
| Hesitancy score (unit increase) | 6.00 | (2.84, 12.69) | <.0001 | 2.76 | (1.35, 5.66) | 0.006 | 10.21 | (4.50, 23.17) | <.0001 | 8.48 | (3.06, 23.51) | <.0001 |
| Hesitancy Score ≥2 | ||||||||||||
| Hesitancy Score | 3.33 | (1.74, 6.37) | 0.0003 | 1.56 | (0.81, 3.01) | 0.19 | 8.27 | (3.82, 17.9) | <.0001 | 4.75 | (1.40, 16.11) | 0.01 |
*The HPV regression model included participants age 18–45 years.
Table 6 presents the logistic regression model results further adjusted for age category (ref = age 36 to 45 years), gender (ref = male), race (ref = white), Hispanic/Latinx ethnicity, income (ref= <$20,000), and education (ref= ≤H.S.). Each increment in hesitancy score was associated with increased odds of being unvaccinated, with the strongest associations observed for Flu (OR = 20.3, 95% CI 6.9–59.6, p < 0.0001) and COVID-19 (OR = 15.0, 95% CI 3.8–59.7, p < 0.0001). In the HPV model participants age 18–25 compared to those age 36–45 were less likely to be unvaccinated (OR 0.25, 95% CI 0.08–0.75, p = 0.01) and participants reporting female for gender were less likely to be unvaccinated (OR 0.36, 95% CI 0.14–0.94, p = 0.04). For Flu, participants reporting ‘Other’ for race were more likely to be unvaccinated (OR 4.4, 95% CI 1.2–17.1, p = 0.01) while individuals with some college/associate degree were less likely to be unvaccinated (OR 0.29, 95% CI 0.10–0.81, p = 0.02). For COVID-19, participants reporting a non-White race were more likely to be unvaccinated (OR 9.6, 95% CI 1.2–78.2, p = 0.03).
Table 6.
Multiple logistic regression model – or (95% Confidence interval [CI]) for NOT receiving vaccination.
| HBV | HPV* | FLU | Covid | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Independent Variable | OR | 95% CI | P-value | OR | 95% CI | P-value | OR | 95% CI | P-value | OR | 95% CI | P-value |
| Hesitancy Score | 6.48 | (2.83, 14.83) | <.0001 | 2.51 | (1.13, 5.56) | 0.02 | 20.33 | (6.94, 59.53) | <.0001 | 14.98 | (3.76, 59.66) | 0.0001 |
| Age | ||||||||||||
| Age 18–25 | 1.15 | (0.38, 3.51) | 0.80 | 0.25 | (0.08, 0.75) | 0.01 | 1.42 | (0.36, 5.51) | 0.61 | 1.45 | (0.18, 11.76) | 0.73 |
| Age 26–35 | 1.09 | (0.36, 3.29) | 0.88 | 0.53 | (0.19, 1.48) | 0.23 | 2.48 | (0.67, 9.2) | 0.18 | 0.79 | (0.07, 8.29) | 0.84 |
| Age 36–45 (reference) | – | – | – | – | – | – | – | – | ||||
| Age 46+* | 1.13 | (0.33, 3.85) | 0.84 | – | – | 0.29 | (0.06, 1.47) | 0.14 | 0.36 | (0.02, 5.52) | 0.46 | |
| Gender | ||||||||||||
| Male (reference) | – | – | – | – | – | – | – | – | ||||
| Female | 0.49 | (0.2, 1.22) | 0.13 | 0.36 | (0.14, 0.94) | 0.04 | 0.93 | (0.32, 2.75) | 0.90 | 0.87 | (0.15, 5.21) | 0.88 |
| Non-bin/non-conform, PNR | 0.71 | (0.29, 1.73) | 0.45 | 0.61 | (0.23, 1.58) | 0.31 | 1.19 | (0.41, 3.49) | 0.75 | 0.89 | (0.14, 5.46) | 0.90 |
| Race | ||||||||||||
| White (reference) | – | – | – | – | – | – | – | – | ||||
| Non-White | 2.82 | (0.94, 8.48) | 0.07 | 1.98 | (0.62, 6.28) | 0.25 | 3.76 | (0.93, 15.26) | 0.06 | 9.61 | (1.18, 78.15) | 0.03 |
| Other | 3.30 | (0.98, 11.1) | 0.05 | 1.74 | (0.46, 6.64) | 0.42 | 4.42 | (1.15, 17.05) | 0.03 | 2.84 | (0.30, 27.29) | 0.36 |
| Two or more races | 1.99 | (0.65, 6.11) | 0.23 | 2.20 | (0.70, 6.93) | 0.18 | 1.52 | (0.37, 6.25) | 0.56 | 2.95 | (0.30, 28.80) | 0.35 |
| Ethnicity | ||||||||||||
| Hispanic | 0.98 | (0.41, 2.32) | 0.96 | 1.78 | (0.71, 4.47) | 0.22 | 0.90 | (0.32, 2.49) | 0.83 | 2.57 | (0.46, 14.34) | 0.28 |
| Income | ||||||||||||
| Less than $20,000 (reference) | – | – | – | – | – | – | – | – | ||||
| $20,000 to $49,999 | 1.09 | (0.47, 2.56) | 0.84 | 0.90 | (0.37, 2.22) | 0.83 | 1.81 | (0.66, 4.98) | 0.25 | 0.35 | (0.05, 2.23) | 0.27 |
| $50,000 or higher | 1.21 | (0.46, 3.21) | 0.70 | 1.02 | (0.36, 2.86) | 0.97 | 1.17 | (0.36, 3.77) | 0.79 | 1.38 | (0.22, 8.80) | 0.74 |
| Education | ||||||||||||
| H.S or less (reference) | – | – | – | – | – | – | – | – | ||||
| Some college, Assoc Degree | 0.67 | (0.28, 1.60) | 0.37 | 0.65 | (0.26, 1.61) | 0.35 | 0.29 | (0.10, 0.81) | 0.02 | 0.33 | (0.06, 1.72) | 0.19 |
| College degree or higher | 0.66 | (0.24, 1.76) | 0.40 | 0.75 | (0.28, 2.06) | 0.58 | 0.34 | (0.10, 1.14) | 0.08 | 0.59 | (0.08, 4.32) | 0.60 |
*The HPV regression model included participants age 18–45 years.
When included as an additional factor to the logistic regression model summarized in Table 6, participants responding other than “Agree/Strongly Agree” for generally following provider vaccine recommendations had higher odds of being unvaccinated for Flu (OR = 11.8, 95% CI 1.2, 117.3, p = 0.04)); responses for this statement were not significantly associated with vaccination status for the other vaccinations (HBV, HPV, COVID-19). In regression models for HBV, HPV, and Flu, vaccine mandate was a significant factor for Flu, but not for HBV or HPV, though the effect estimate for HBV was suggestive that mandate had some influence (OR = 0.25, 95% CI 0.06, 1.06, p = 0.06). Note that for COVID-19 all individuals reporting that the vaccine was mandated received the COVID-19 vaccine, so mandate was not included as a factor in the COVID-19 regression model.
Discussion
TGD patients have historically been underrepresented in research. Our study results showed that TGD patients receiving care at a gender-affirming clinic had high levels of trust in their healthcare providers (97%) and willingness to follow provider recommendation (94.5%), while still expressing vaccine hesitancy based on vaccine hesitance scores (Table 4). However, vaccination rates were higher in our TGD population compared to rates reported in the general US population for all four vaccines—COVID-19 (92.8% vs 79.7%), Flu (74.0% vs 49.4%), HBV 65.7% vs 34.2%), and HPV 61.4% overall vs 57.7% for females 19–26 and 34.8% for males 19–26 years) (CDC, 2024a; 2024b)—which may be related to the level of trust that participants reported and emphasizes the importance of provider vaccine recommendations. The importance of provider recommendations in other populations to decrease vaccine hesitancy is well-documented (Chen et al., 2024; Gerretsen et al., 2021; Moretti et al., 2020; Rodriguez et al., 2024; Yoon et al., 2024).
It is worth noting that vaccination status was determined by self-report. Data may be difficult to interpret for COVID-19 vaccination when obtained by self-report, since participants may consider themselves vaccinated if they received the initial vaccine. However, CDC now only considers people vaccinated if they have received the most recent booster. It is worth noting that the majority of our enrollment occurred 2023 at the peak of the COVID-19 vaccine uptake before the updated booster was available.
There was no statistically significant difference in vaccination status or hesitancy in different annual income levels. Socio-cultural factors that did have impacts were those with college/associate degree were more likely to be vaccinated and for COVID-19 specifically, participants reporting a non-White race were less likely to be vaccinated.
Higher vaccine hesitancy scores for all four vaccines were strongly associated with being unvaccinated in our TGD population and findings were robust to adjustment for sociodemographic factors. This finding is consistent with previous literature, as individuals who express higher levels of vaccine hesitancy are less likely to receive vaccination. [Moretti et al., 2020; Quinn et al., 2019). The significant association between each unit increase in hesitancy score and unvaccinated status is expected as vaccine hesitancy influences an individual’s decision on whether they should receive any certain vaccine. The overlap in hesitancy score distributions between groups for HPV is notable given the highest percentage of unvaccinated individuals across the vaccines was for HPV.
Our TGD population had the lowest vaccination rate for the HPV vaccine, particularly among participants aged 36–45 years. For HPV vaccination, significant differences in confidence are consistent with individual attitudes toward efficacy and self-perceived risk for disease that have been previously reported (Chen et al., 2024; Yoon et al., 2024). Those with female gender and those that were 18–25 years of age were more likely to receive the HPV vaccine with lower hesitancy scores which also may be a reflection of the marketing and original age range indication for this vaccine. Based on our results, the highest hesitancy score for HPV was in convenience. Significant differences in convenience may be related to access, the requirement of multiple injections, or cost. Fewer mandates are in place for HPV vaccination, as we have seen with other vaccinations, which usually impacts the out-of-pocket cost for the patient and decreases access to the vaccination. These multiple reasons may explain the lower HPV vaccination rate seen in our population. HPV vaccine hesitancy scores were significantly different in the areas of Confidence and Convenience, suggesting that additional education regarding the vaccine and its availability could impact vaccination rates in this population.
Responses for vaccine mandates indicate that individuals may be more likely to receive vaccines that are mandated, whether that be a mandate for the workplace, school, travel, or other public spaces. For COVID-19 vaccination, higher hesitancy scores for confidence and complacency are consistent with findings presented in a study conducted by Gerretsen et al. (2021). Despite participants’ responses that the COVID-19 vaccine carried more risk and that participants were more likely to be concerned about the serious adverse effects of the COVID-19 vaccine, the COVID-19 vaccine had the greatest uptake in our population.
Systematic approaches to increasing COVID-19 vaccine uptake may have influenced convenience hesitancy scores, as convenience hesitancy was lowest for COVID-19. Confidence and overall hesitancy score being highest for COVID-19 may be related to the recent and fast-track development of this vaccination compared to the other vaccinations. Complacency hesitancy being highest for COVID-19 may be explained by individual’s perceptions of risk and severity of infection as infection rates decline with time.
The US adopted universal HBV vaccination for infants in 1991. Current US data is likely skewed by the older population. In our cohort, we had higher rates of HBV than the general US population but the average age of our participants was 30 years.
Overall, this study demonstrates high rates of vaccine hesitancy in our TGD population receiving care at a gender-affirming clinic that provides vaccinations and primary care services to TGD people. It is important to note that high percentages of participants reported engagement with their primary care provider in the past year and this survey captured participants who were present for a provider visit. This likely represents a population that may experience less access barriers to vaccination, which may help to explain the relatively high vaccination rates that were reported during this study. High levels of confidence in healthcare were expressed as more than 97% of participants agreed or strongly agreed with the statement “I trust my healthcare providers”. Given this context, this study cannot explore the impact of diminished confidence in healthcare on vaccine hesitancy and vaccination status. Strategies that incorporate strong provider recommendations should be leveraged to decrease vaccine hesitancy in this study population.
This study’s insights into the factors driving vaccine hesitancy in TGD populations can inform targeted public health strategies to enhance vaccine uptake and address specific barriers, thereby potentially mitigating the risk of vaccine-preventable diseases in this underserved group. For example, interventions for increasing HPV vaccinations should focus on addressing confidence and convenience, as the survey responses indicated a significant difference in these areas between vaccinated and unvaccinated participants. Interventions to increase confidence in HPV vaccination could include provider-initiated discussions with patients about the benefits and risks of the HPV vaccine, plus readily accessible printed or visual educational materials with this information. Increasing the availability and visibility of HPV vaccinations during routine healthcare visits could help address the convenience factor. Because survey responses did not indicate a significant difference between groups for complacency, interventions focused on educating patients on the seriousness of HPV would likely be less effective at increasing HPV vaccination rates.
Survey responses from unvaccinated participants indicate a higher degree of vaccine hesitancy compared to responses from vaccinated participants in our TGD population. Differing vaccine hesitancy determinants were associated with unvaccinated status for the HPV, HBV, influenza, and COVID-19 vaccines. This data can inform healthcare providers of opportunities to decrease vaccine hesitancy and increase vaccination uptake in the TGD population.
Acknowledgements
The authors want to thank the staff and patients at the University of New Mexico Truman Health Services clinic.
Appendix A.
Table A.
xx vaccine hesitancy score survey items and associated complacency, convenience and confidence (“3Cs”) categories
| Survey item | Reverse Scored | Construct |
|---|---|---|
| 1 This vaccine is effective at preventing disease | Y | Confidence |
| 2 This vaccine carries more risk than other vaccines | N | Confidence |
| 3 The information I receive about this vaccine is reliable and trustworthy | Y | Confidence |
| 4 I am concerned about the serious adverse effects of this vaccine | N | Confidence |
| 5 This vaccine is important for my health | Y | Complacency |
| 6 This vaccine is important for the health of others in my community | Y | Complacency |
| 7 This vaccine is a good way to protect myself from disease | Y | Complacency |
| 8 This vaccine protects against a disease that does not result in serious or severe infection | N | Complacency |
| 9 I do not need this vaccine because it protects against a disease that is not common | N | Complacency |
| 10 I have been tested and/or evaluated for the disease that this vaccine prevents | Y | Complacency |
| 11 I was offered this vaccine at a visit with a healthcare provider | Y | Convenience |
| 12 I can financially afford to receive this vaccine | Y | Convenience |
| 13 There are many places where I can receive this vaccine | Y | Convenience |
| 14 I can receive this vaccine within the area in which I currently live | Y | Convenience |
| 15 It is difficult to find the time to receive this vaccine | N | Convenience |
| Additional survey items excluding demographics |
|---|
| 16 What is your religious affiliation? |
| 17 What is your estimated yearly income? |
| 18 What is the highest degree or level of school you have completed? |
| 19 Have you attended a visit with a primary care provider in the past year? If yes, approximately how many appointments have you had with your primary care provider in the past year? |
| 20 I trust my healthcare provider(s). |
| 21 I generally follow what my healthcare provider recommends about vaccines. |
| 22 Has your provider recommended that you receive a vaccine in the last year? If yes, did you receive the vaccine(s)? |
| 23. Are you required, by your employer, school, community, or other, to receive the following vaccines? |
| 24 Have you been vaccinated for the following vaccines? Vaccinated means that you have received at least one dose in the recommended vaccine series. Unvaccinated means that you have received no doses of the vaccine (options included HBV vaccine, HPV vaccine, 2021–2022 influenza vaccine, COVID-19 vaccine). |
Appendix B.
Figure 1.
Box plot figures for hesitancy score.
Box plots illustrate the minimum, 1st quartile, median, mean (o), 3rd quartile, and maximum values for each hesitancy score.
HPV summary is for participants age 18–45.
Funding Statement
This work was supported in part by a research grant from Investigator-Initiated Studies Program of Merck Sharp & Dohme LLC. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp & Dohme LLC.
Disclosure statement
In addition to study support, Dr. Jakeman has received speaking honorariums from ASHP Continuing Education, CEimpact Education, and Pharmacy Times Continuing Education within the last 36 months. Dr. Jakeman also serves as a consultant for Wolters-Kluwer, Lexidrug. The authors have no additional conflicts of interest to declare, including, but not limited to, consulting fees, paid expert testimony, employment, grants, honoraria, patents, royalties, stocks, or other financial or material gain that may involve the subject matter of the manuscript.
References
- Ahuja, T. K., Goel, A. D., Gupta, M. K., Joshi, N., Choudhary, A., Suman, S., Taluja, K., Mittal, M., Ghuman, N. K., Suthar, N., & Bhardwaj, P. (2024). Health care needs and barriers to care among the transgender population: A study from western Rajasthan. BMC Health Services Research, 24(1), 989. 10.1186/s12913-024-11010-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bednarczyk, R. A. (2019). Addressing HPV vaccine myths: Practical information for healthcare providers. Human Vaccines & Immunotherapeutics, 15(7-8), 1628–1638. 10.1080/21645515.2019.1565267 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Centers for Disease Control and Prevention (CDC) (2024. a). Vaccination coverage among adults in the United States, National Health Interview Survey, 2022. https://www.cdc.gov/adultvaxview/publications-resources/adult-vaccination-coverage-2022.html
- Centers for Disease Control and Prevention (CDC) (2024. b). Vaccination coverage among adults in the United States, National Health Interview Survey, 2021. https://www.cdc.gov/adultvaxview/publications-resources/vaccination-coverage-adults-2021.html
- Chen, C., Chen, T., Huang, M., Huang, Y., Zhang, L., & Li, P. (2024). Factors associated with HPV vaccine hesitancy among college students: A cross-sectional survey based on 3Cs and structural equation model in China. Human Vaccines & Immunotherapeutics, 20(1), 2309731. 10.1080/21645515.2024.2309731 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Constable, C., & Caplan, A. (2020). Comparison of the implementation of human papillomavirus and hepatitis B vaccination programs in the United States: Implications for future vaccines. Vaccine, 38(5), 954–962. 10.1016/j.vaccine.2019.11.073 [DOI] [PubMed] [Google Scholar]
- Coustasse, A., Kimble, C., & Maxik, K. (2021). COVID-19 and vaccine hesitancy: A challenge the United States must overcome. The Journal of Ambulatory Care Management, 44(1), 71–75. 10.1097/JAC.0000000000000360 [DOI] [PubMed] [Google Scholar]
- Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. 10.3758/BRM.41.4.1149 [DOI] [PubMed] [Google Scholar]
- Garg, I., Hanif, H., Javed, N., Abbas, R., Mirza, S., Javaid, M. A., Pal, S., Shekhar, R., & Sheikh, A. B. (2021). COVID-19 vaccine hesitancy in the LGBTQ+ population: A systematic review. Infectious Disease Reports, 13(4), 872–887. 10.3390/idr13040079 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gerretsen, P., Kim, J., Caravaggio, F., Quilty, L., Sanches, M., Wells, S., Brown, E. E., Agic, B., Pollock, B. G., & Graff-Guerrero, A. (2021). Individual determinants of COVID-19 vaccine hesitancy. PloS One, 16(11), e0258462. 10.1371/journal.pone.0258462 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Helmkamp, L. J., Szilagyi, P. G., Zimet, G., Saville, A. W., Gurfinkel, D., Albertin, C., Breck, A., Vangala, S., & Kempe, A. (2021). A validated modification of the vaccine hesitancy scale for childhood, influenza and HPV vaccines. Vaccine, 39(13), 1831–1839. 10.1016/j.vaccine.2021.02.039 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnson, A. H., Hill, I., Beach-Ferrara, J., Rogers, B. A., & Bradford, A. (2020). Common barriers to healthcare for transgender people in the U.S. Southeast. International Journal of Transgender Health, 21(1), 70–78. 10.1080/15532739.2019.1700203 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Karafillakis, E., & Larson, H. J. (2017). The benefit of the doubt or doubts over benefits? A systematic literature review of perceived risks of vaccines in European populations. Vaccine, 35(37), 4840–4850. 10.1016/j.vaccine.2017.07.061 [DOI] [PubMed] [Google Scholar]
- MacDonald, N. E. (2015). Vaccine hesitancy: Definition, scope and determinants. Vaccine, 33(34), 4161–4164. 10.1016/j.vaccine.2015.04.036 [DOI] [PubMed] [Google Scholar]
- McAteer, J., Yildirim, I., & Chahroudi, A. (2020). The VACCINES act: Deciphering vaccine hesitancy in the time of COVID-19. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, 71(15), 703–705. 10.1093/cid/ciaa433 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mitchell, S. L., Schulkin, J., & Power, M. L. (2023). Vaccine hesitancy in pregnant women: A narrative review. Vaccine, 41(29), 4220–4227. 10.1016/j.vaccine.2023.05.047 [DOI] [PubMed] [Google Scholar]
- Moretti, F., Visentin, D., Bovolenta, E., Rimondini, M., Majori, S., Mazzi, M., Poli, A., Tardivo, S., & Torri, E. (2020). Attitudes of nursing home staff towards influenza vaccination: Opinions and factors influencing hesitancy. International Journal of Environmental Research and Public Health, 17(6), 1851. 10.3390/ijerph17061851 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Moyroud, L., Hustache, S., Goirand, L., Hauzanneau, M., & Epaulard, O. (2017). Negative perceptions of hepatitis B vaccination among attendees of an urban free testing center for sexually transmitted infections in France. Human Vaccines & Immunotherapeutics, 13(5), 998–1004. 10.1080/21645515.2016.1264549 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paterson, P., Meurice, F., Stanberry, L. R., Glismann, S., Rosenthal, S. L., & Larson, H. J. (2016). Vaccine hesitancy and healthcare providers. Vaccine, 34(52), 6700–6706. 10.1016/j.vaccine.2016.10.042 [DOI] [PubMed] [Google Scholar]
- Pratt-Chapman, M. L., Murphy, J., Hines, D., Brazinskaite, R., Warren, A. R., & Radix, A. (2021). “When the pain is so acute or if I think that I’m going to die”: Health care seeking behaviors and experiences of transgender and gender diverse people in an urban area. PLoS One, 16(2), e0246883. 10.1371/journal.pone.0246883 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Quinn, S. C., Jamison, A. M., An, J., Hancock, G. R., & Freimuth, V. S. (2019). Measuring vaccine hesitancy, confidence, trust and flu vaccine uptake: Results of a national survey of White and African American adults. Vaccine, 37(9), 1168–1173. 10.1016/j.vaccine.2019.01.033 [DOI] [PubMed] [Google Scholar]
- Rodriguez, R. M., Eucker, S. A., Rafique, Z., Nichol, G., Molina, M. F., Kean, E., O’Laughlin, K. N., Bezek, S. K., Goicochea, K., Ford, J. S., Morse, D., White, J., Arreguin, M. I., Shughart, L., Chavez, C. L., Glidden, D. V., & Rising, K. L. (2024). Promotion of influenza vaccination in the emergency department. NEJM Evidence, 3(4), EVIDoa2300197. 10.1056/EVIDoa2300197 [DOI] [PubMed] [Google Scholar]
- SAS Institute Inc . (2023). SAS/STAT® 15.3 User’s Guide. [Google Scholar]
- Szilagyi, P. G., Albertin, C. S., Gurfinkel, D., Saville, A. W., Vangala, S., Rice, J. D., Helmkamp, L., Zimet, G. D., Valderrama, R., Breck, A., Rand, C. M., Humiston, S. G., & Kempe, A. (2020). Prevalence and characteristics of HPV vaccine hesitancy among parents of adolescents across the US. Vaccine, 38(38), 6027–6037. 10.1016/j.vaccine.2020.06.074 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tankwanchi, A. S., Bowman, B., Garrison, M., Larson, H., & Wiysonge, C. S. (2021). Vaccine hesitancy in migrant communities: A rapid review of latest evidence. Current Opinion in Immunology, 71, 62–68. 10.1016/j.coi.2021.05.009 [DOI] [PubMed] [Google Scholar]
- Teixeira da Silva, D., Biello, K., Lin, W. Y., Valente, P. K., Mayer, K. H., Hightow-Weidman, L., & Bauermeister, J. A. (2021). COVID-19 Vaccine Acceptance among an Online Sample of Sexual and Gender Minority Men and Transgender Women. Vaccines, 9(3), 204. 10.3390/vaccines9030204 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wagner, C. E., Prentice, J. A., Saad-Roy, C. M., Yang, L., Grenfell, B. Y., Levin, S. A., & Laxminarayan, R. (2020). Economic and behavioral influencers of vaccination and antimicrobial use. Frontiers in Public Health, 8, 614113. 10.3389/fpubh.2020.614113 [DOI] [PMC free article] [PubMed] [Google Scholar]
- World Health Organization (WHO) . (2014). Report of the SAGE Working Group on Vaccine Hesitancy https://thecompassforsbc.org/sbcc-tools/report-sage-working-group-vaccine-hesitancy
- World Health Organization (WHO) . (2015). Summary WHO SAGE conclusions and recommendations on vaccine hesitancy. Retrieved September 9, 2025, from https://cdn.who.int/media/docs/default-source/immunization/demand/summary-of-sage-vaccinehesitancy-en.pdf
- Yoon, S., Kim, H., An, J., & Jin, S. W. (2024). Exploring human papillomavirus vaccine hesitancy among college students and the potential of virtual reality technology to increase vaccine acceptance: A mixed-methods study. Frontiers in Public Health, 12, 1331379. 10.3389/fpubh.2024.1331379 [DOI] [PMC free article] [PubMed] [Google Scholar]