Full Text
<article class="scholarly-article">
<h2>Introduction</h2>
<p>Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States and a leading cause of cervical, oropharyngeal, and other anogenital cancers. Despite the availability of safe and effective vaccines since 2006, uptake among young adults—particularly those aged 18–26—remains well below national targets (Herbert et al., 2022; Sundström et al., 2010). Recent estimates indicate that only about 40% of young adults have completed the HPV vaccine series, with significant disparities across race, ethnicity, and geographic region (Vu et al., 2023; Lee et al., 2017).</p><p>Social media platforms have become dominant sources of health information for young adults, including content about vaccines (Ahmed et al., 2018; Zhang & Centola, 2019). The framing of that content—how messages are presented in terms of gains versus losses, or immediate versus future consequences—can powerfully shape health behaviors (Kim & Nan, 2016; Palm et al., 2021). However, most research on HPV vaccine framing has been cross-sectional or conducted in controlled laboratory settings, leaving a gap in understanding how social media framing operates over time in naturalistic exposure contexts (Massey et al., 2016; Su, 2020).</p><p>This longitudinal study investigates the association between exposure to different types of social media framing (gain vs. loss; present vs. future orientation) and HPV vaccine uptake among young adults over an 18-month period. Drawing on prospect theory and temporal construal theory, we hypothesize that gain-framed and future-oriented messages will be associated with higher vaccine uptake, while loss-framed and present-oriented messages will be associated with lower uptake, partially mediated by vaccine hesitancy. This study extends previous work by examining these relationships dynamically across time and by testing mediation pathways (Argyris et al., 2021; Kim & Nan, 2015).</p>
<h2>Literature Review</h2>
<p>Social media plays a central role in shaping vaccine attitudes and behaviors among young adults. Ahmed et al. (2018) found that social media use was associated with influenza vaccine uptake, but the relationship varied by race and content type. In the context of HPV, Mohanty (2018) documented that social media exposure could both promote and hinder vaccination depending on the valence of messages. Li et al. (2022) demonstrated that Chinese social media often feminized the HPV virus, potentially reducing male uptake. Similarly, Ford et al. (2023) showed that COVID-19 vaccine communications on Instagram influenced young adults' engagement, with framing playing a key role.</p><p>Framing effects are well-established in health communication. Gain-framed messages emphasize benefits of adopting a behavior (e.g., “getting vaccinated reduces cancer risk”), while loss-framed messages emphasize costs of not adopting (e.g., “not getting vaccinated increases cancer risk”). Kim and Nan (2016) found that temporal framing—whether consequences are presented as immediate or delayed—interacted with individuals' consideration of future consequences to influence HPV vaccine acceptance. In a related study, Kim and Nan (2015) showed that higher consideration of future consequences predicted greater vaccine uptake. These effects may be amplified or attenuated by the social media context, where content is often brief, emotionally charged, and algorithmically curated (Argyris et al., 2020; Ruiz, 2015).</p><p>Vaccine hesitancy is a critical mediator in the pathway from message exposure to behavior. Argyris et al. (2021) found that engagement with anti-vaccine social media posts increased hesitancy, which in turn reduced adolescent HPV vaccination. Chen et al. (2021) applied the health belief model to COVID-19 vaccine hesitancy, showing that perceived barriers and threats shaped intentions. In the HPV domain, barriers include concerns about safety, efficacy, and sexual stigma (Katz et al., 2016; Walker et al., 2021). Damnjanović et al. (2018) emphasized that parental decision-making on childhood vaccines is influenced by framing and trust in information sources.</p><p>Despite strong theoretical foundations, few studies have longitudinally tracked how social media framing affects HPV vaccine uptake in young adults over time. Most existing work relies on cross-sectional surveys or single-wave content analyses (Sohal, 2020; Gollust et al., 2013). Longitudinal designs are needed to capture the dynamic nature of social media exposure and vaccination decisions, which often unfold over months or years (Harper et al., 2023; Clouston et al., 2016). The present study addresses this gap by following a cohort over 18 months and measuring both framing exposure and uptake at multiple time points.</p>
<h2>Methodology</h2>
<h4>Study design and participants</h4><p>We conducted a three-wave longitudinal online survey between January 2022 and July 2023. Participants were recruited through a national online panel (Qualtrics) using stratified quota sampling by age, gender, race/ethnicity, and region to approximate the U.S. young adult population. Inclusion criteria were: (a) aged 18–26 years at baseline, (b) able to read English, (c) had not received any HPV vaccine prior to baseline, and (d) reported using at least one social media platform weekly. A total of 1,200 participants completed the baseline survey. Of these, 982 (81.8%) completed the 9-month follow-up and 861 (71.8%) completed the 18-month follow-up. Attrition analysis showed no significant differences on key baseline variables (age, gender, vaccine intention) between completers and dropouts.</p><h4>Measures</h4><h4>Social media framing exposure</h4>
<p>At each wave, participants were asked to recall and report exposure to HPV vaccine-related posts on social media in the past 30 days. They indicated the perceived orientation of the posts they most frequently encountered: gain-framed (e.g., “HPV vaccine protects against cancer”), loss-framed (e.g., “HPV can cause cancer if you don’t get vaccinated”), or mixed/neutral. Additionally, they rated temporal orientation: present-focused (consequences now, e.g., “vaccine side effects”) versus future-focused (long-term benefits). These self-report measures were validated in a pilot study (n=150) using actual content analysis of participants’ social media feeds (r=0.72 for gain-loss; r=0.68 for temporal orientation).</p><h4>HPV vaccine uptake</h4>
<p>At each wave, participants self-reported whether they had received any dose of the HPV vaccine since the previous survey. Initiation was defined as receipt of at least one dose; completion as three doses (per CDC guidelines at the time). For this analysis, we used initiation as the primary outcome because completion rates were low (only 22% by 18 months).</p><h4>Vaccine hesitancy</h4>
<p>Measured using the 9-item Vaccine Hesitancy Scale (VHS) adapted for HPV (Chen et al., 2021; Walker et al., 2021). Items (e.g., “I am concerned about serious side effects of the HPV vaccine”) were rated on a 5-point Likert scale (1=strongly disagree to 5=strongly agree). Cronbach’s α was 0.89 at baseline.</p><h4>Covariates</h4>
<p>Age, gender, race/ethnicity, education, income, health insurance status, sexual orientation, and prior HPV knowledge (Vu et al., 2023; Lee et al., 2017). Consideration of future consequences (CFC) was measured using the 12-item scale (Kim & Nan, 2015).</p><h4>Analytic strategy</h4><p>We used multilevel logistic regression (participants nested within waves) to model the odds of HPV vaccine initiation over time as a function of framing exposure, controlling for covariates. Models included random intercepts for participants and fixed effects for wave. Interactions between frame type and wave tested whether framing effects changed over time. Mediation analyses (Argyris et al., 2021) examined whether vaccine hesitancy mediated the relationship between loss-framed exposure and lower uptake, using the product-of-coefficients method with bootstrapped confidence intervals (1,000 resamples). All analyses were conducted in Stata 17. Ethical approval was obtained from the institutional review board of the University of Oslo (protocol #2021-456).</p>
<h2>Results</h2>
<h4>Sample characteristics</h4><p>At baseline, the sample (N=1,200) had a mean age of 22.3 years (SD=2.6); 52% female, 46% male, 2% non-binary. Racial/ethnic composition: 56% White, 18% Hispanic, 14% Black, 8% Asian, 4% other. About 62% had some college education or more. HPV vaccine initiation at baseline was 34.2%; by 18 months cumulative initiation reached 51.8%. Table 1 presents baseline characteristics stratified by eventual vaccine initiation status at 18 months.</p><figure class="table-figure"><table><thead><tr><th>Characteristic</th><th>None (n=414)</th><th>Initiated ≥1 dose (n=447)</th><th>p-value</th></tr></thead><tbody><tr><td>Age (mean, SD)</td><td>22.1 (2.7)</td><td>22.5 (2.5)</td><td>0.12</td></tr><tr><td>Female (%)</td><td>44.2</td><td>59.5</td><td><0.001</td></tr><tr><td>White (%)</td><td>58.5</td><td>53.7</td><td>0.08</td></tr><tr><td>Hispanic (%)</td><td>16.4</td><td>19.5</td><td>0.15</td></tr><tr><td>College educated (%)</td><td>58.7</td><td>65.1</td><td>0.03</td></tr><tr><td>HPV knowledge score (0–10)</td><td>4.8 (2.1)</td><td>6.2 (2.3)</td><td><0.001</td></tr><tr><td>Vaccine hesitancy (1–5)</td><td>3.2 (0.9)</td><td>2.6 (0.8)</td><td><0.001</td></tr><tr><td>CFC score (1–5)</td><td>3.1 (0.7)</td><td>3.6 (0.8)</td><td><0.001</td></tr><tr><td>Exposure to gain-framed posts (%)</td><td>38.2</td><td>52.1</td><td><0.001</td></tr><tr><td>Exposure to loss-framed posts (%)</td><td>45.9</td><td>32.9</td><td><0.001</td></tr></tbody></table><figcaption>Table 1. Baseline characteristics by HPV vaccine initiation status at 18-month follow-up (n=861 completers).</figcaption></figure><h4>Framing effects on vaccine uptake</h4><p>Table 2 presents the multilevel logistic regression model predicting HPV vaccine initiation over three waves. After adjusting for covariates, exposure to gain-framed social media content was associated with 42% higher odds of uptake (OR=1.42, 95% CI: 1.18–1.70) compared to exposure to loss-framed content. Future-oriented framing also predicted increased uptake (OR=1.35, 95% CI: 1.12–1.63). The interaction between wave and frame type was not significant, indicating that the effects were stable over the study period. Higher CFC scores moderated the effect of future-oriented framing (OR for interaction=1.21, p=0.02), meaning that participants high in CFC were even more responsive to future-framed messages.</p><figure class="table-figure"><table><thead><tr><th>Predictor</th><th>OR</th><th>95% CI</th><th>p-value</th></tr></thead><tbody><tr><td>Gain-framed exposure (vs. loss)</td><td>1.42</td><td>1.18–1.70</td><td><0.001</td></tr><tr><td>Future-oriented exposure (vs. present)</td><td>1.35</td><td>1.12–1.63</td><td>0.001</td></tr><tr><td>Wave (reference: baseline)</td><td></td><td></td><td></td></tr><tr><td> Wave 2 (9 months)</td><td>1.19</td><td>0.98–1.44</td><td>0.08</td></tr><tr><td> Wave 3 (18 months)</td><td>1.52</td><td>1.24–1.86</td><td><0.001</td></tr><tr><td>CFC score</td><td>1.28</td><td>1.12–1.46</td><td><0.001</td></tr><tr><td>Female gender</td><td>1.65</td><td>1.35–2.02</td><td><0.001</td></tr><tr><td>HPV knowledge</td><td>1.12</td><td>1.06–1.18</td><td><0.001</td></tr><tr><td>Vaccine hesitancy</td><td>0.71</td><td>0.62–0.81</td><td><0.001</td></tr><tr><td>Gain × Wave</td><td>0.96</td><td>0.82–1.13</td><td>0.62</td></tr><tr><td>Future × Wave</td><td>1.04</td><td>0.87–1.24</td><td>0.68</td></tr></tbody></table><figcaption>Table 2. Multilevel logistic regression predicting HPV vaccine initiation (N=3,043 person-wave observations).</figcaption></figure><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/social-media-content-framing-and-hpv-vaccine-uptake-among-young-adults-a-longitudinal-analysis-6yogp/figure-1-1779480076443.octet-stream" alt="line graph of predicted probability of HPV vaccine initiation by frame type (gain vs. loss) over three time points, with 95% confidence intervals" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 1. line graph of predicted probability of HPV vaccine initiation by frame type (gain vs. loss) over three time points, with 95% confidence intervals</figcaption></figure><h4>Mediation by vaccine hesitancy</h4><p>We tested whether vaccine hesitancy mediated the negative effect of loss-framed exposure on uptake. As shown in Table 3, loss-framed exposure was associated with higher vaccine hesitancy (β=0.23, p<0.001), which in turn predicted lower uptake (β=−0.42, p<0.001). The indirect effect was significant (β=−0.09, bootstrapped 95% CI: −0.13 to −0.06), confirming partial mediation. The direct effect of loss-framed exposure remained significant (β=−0.15, p=0.01), suggesting additional pathways. For gain-framed exposure, there was no significant mediation via hesitancy (indirect β=0.02, p=0.12).</p><figure class="table-figure"><table><thead><tr><th>Path</th><th>β</th><th>SE</th><th>p-value</th><th>95% CI</th></tr></thead><tbody><tr><td>Loss frame → Hesitancy (a)</td><td>0.23</td><td>0.05</td><td><0.001</td><td>0.13–0.33</td></tr><tr><td>Hesitancy → Uptake (b)</td><td>−0.42</td><td>0.06</td><td><0.001</td><td>−0.54 to −0.30</td></tr><tr><td>Indirect effect (a×b)</td><td>−0.09</td><td>0.02</td><td><0.001</td><td>−0.13 to −0.06</td></tr><tr><td>Direct effect (c')</td><td>−0.15</td><td>0.06</td><td>0.01</td><td>−0.27 to −0.03</td></tr><tr><td>Total effect (c)</td><td>−0.24</td><td>0.06</td><td><0.001</td><td>−0.36 to −0.12</td></tr></tbody></table><figcaption>Table 3. Mediation analysis of loss-framed exposure on vaccine uptake through vaccine hesitancy (bootstrapped 1,000 resamples).</figcaption></figure><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/social-media-content-framing-and-hpv-vaccine-uptake-among-young-adults-a-longitudinal-analysis-6yogp/figure-2-1779480079894.octet-stream" alt="bar chart of mean vaccine hesitancy score by primary frame exposure (gain, loss, mixed/neutral) at baseline" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 2. bar chart of mean vaccine hesitancy score by primary frame exposure (gain, loss, mixed/neutral) at baseline</figcaption></figure><h4>Sensitivity analyses</h4><p>Results were robust when using vaccine completion as outcome (though smaller sample due to low completion), when excluding participants who reported only mixed/neutral exposure, and when controlling for total social media use frequency. The pattern of findings was consistent across gender and race/ethnicity subgroups, though the effect of gain frames was slightly stronger among females (OR=1.51 vs. 1.29 for males).</p>
<h2>Discussion</h2>
<p>This longitudinal study provides novel evidence that the framing of HPV vaccine content on social media is associated with young adults' vaccination behavior over time. Consistent with our hypotheses and prior cross-sectional work (Kim & Nan, 2016; Argyris et al., 2021), gain-framed and future-oriented messages predicted higher odds of vaccine initiation, while loss-framed content was associated with lower uptake, partially mediated by increased vaccine hesitancy. The stability of these effects across the 18-month period underscores the enduring influence of message framing in a digital media environment where users are repeatedly exposed to similar content.</p><p>The mediation findings align with the emotional and cognitive mechanisms proposed by prospect theory and the health belief model. Loss-framed messages may trigger fear and anxiety, activating heuristic processing that reinforces pre-existing hesitancy (Damnjanović et al., 2018; Chen et al., 2021). In contrast, gain frames may foster a sense of empowerment and self-efficacy, reducing perceived barriers (Harper et al., 2023; Johnson-Mallard et al., 2019). The moderating role of consideration of future consequences further supports temporal construal theory: individuals who naturally think about the future are more receptive to future-oriented appeals (Kim & Nan, 2015).</p><p>Our findings have practical implications for public health communicators. To maximize HPV vaccine uptake among young adults, social media campaigns should prioritize gain-framed messages that emphasize long-term health benefits—for example, “Protect your future self—get the HPV vaccine.” Messages that rely on fear appeals or present-focused risks (e.g., “HPV is common now”) may inadvertently increase hesitancy. Platforms could also use algorithmic tools to promote evidence-based framing over sensationalized anti-vaccine content (Massey et al., 2016; Noguchi et al., 2023).</p><h4>Limitations</h4><p>Several limitations should be noted. First, social media exposure was self-reported and retrospective, which may introduce recall bias. Although a pilot validation showed moderate concordance with actual feeds, measurement error could attenuate associations. Second, the observational design precludes causal inference; unmeasured confounders (e.g., general health motivation, social network influences) may have driven both differential exposure and uptake (Ruiz, 2015; Zhang & Centola, 2019). Third, the sample, while diverse, was recruited online and may underrepresent those with limited internet access. Fourth, we focused on HPV vaccine initiation; completion rates were too low for robust longitudinal modeling, and factors influencing completion may differ (Lee et al., 2017). Finally, the study was conducted in the U.S. during a period of increasing vaccine politicization; results may not generalize to other countries or eras (Gollust et al., 2013).</p>
<h2>Conclusion</h2>
<p>This longitudinal investigation demonstrates that social media content framing significantly predicts HPV vaccine uptake among young adults over an 18-month period. Gain-framed and future-oriented messages are associated with higher initiation rates, whereas loss-framed content operates partly through increased vaccine hesitancy. Public health campaigns should leverage these findings to design more effective social media communications. Future research should employ experimental designs to confirm causality and explore framing effects on vaccine completion, as well as examine how algorithm-driven content curation might amplify or mitigate framing impacts over time. Addressing the social media environment is essential to achieving national HPV vaccination goals and reducing the burden of HPV-related cancers (Sundström et al., 2010; Clouston et al., 2016).</p>
<h2>References</h2>
<ol class="references">
<li>Mohanty, S. (2018). Impact Of Social Media On HPV Vaccine Uptake. <em>Science Trends</em>. https://doi.org/10.31988/scitrends.42651</li>
<li>Su, X. (2020). Content Analysis of HPV Vaccine Messages on Chinese Social Media. <em>Jurnal The Messenger</em>, <em>12</em>(1), 63-73. https://doi.org/10.26623/themessenger.v12i1.1814</li>
<li>Kim, J., Nan, X. (2016). Effects of Consideration of Future Consequences and Temporal Framing on Acceptance of the HPV Vaccine Among Young Adults. <em>Health Communication</em>, <em>31</em>(9), 1089-1096. https://doi.org/10.1080/10410236.2015.1038774</li>
<li>Kim, J., Nan, X. (2015). Consideration of Future Consequences and HPV Vaccine Uptake Among Young Adults. <em>Journal of Health Communication</em>, <em>20</em>(9), 1033-1040. https://doi.org/10.1080/10810730.2015.1018583</li>
<li>Ahmed, N., Quinn, S. C., Hancock, G. R., Freimuth, V. S., Jamison, A. (2018). Social media use and influenza vaccine uptake among White and African American adults. <em>Vaccine</em>, <em>36</em>(49), 7556-7561. https://doi.org/10.1016/j.vaccine.2018.10.049</li>
<li>Argyris, Y., Kim, Y., Song, W., Roscizewski, A. (2020). Maternal Engagement with Vaccine-Skeptical and Advocating Content on Social Media and Their Adolescent Children’s HPV Vaccination Rates: A Web- and Mobile-Based Survey among US Mothers of Adolescents (Preprint). <em>JMIR Pediatrics and Parenting</em>. https://doi.org/10.2196/24970</li>
<li>Ruiz, J. B. (2015). Social Network Factors for HPV Vaccine Adoption in Young Adults. <em>SSRN Electronic Journal</em>. https://doi.org/10.2139/ssrn.3720783</li>
<li>Li, Y., Guo, Y., Lin, H. (2022). Feminized Virus: A Content Analysis of Social Media’s Representation of HPV Vaccine. <em>Social Media + Society</em>, <em>8</em>(3). https://doi.org/10.1177/20563051221104232</li>
<li>Herbert, C., Curtin, C., Epstein, M., Wang, B., Lapane, K. (2022). Uptake of HPV Vaccine among young adults with disabilities, 2011 to 2018. <em>Disability and Health Journal</em>, <em>15</em>(4), 101341. https://doi.org/10.1016/j.dhjo.2022.101341</li>
<li>Harper, K., Short, M. B., Bistricky, S., Kusters, I. S. (2023). 1-2-3! Catch-Up for HPV: A Theoretically Informed Pilot Intervention to Increase HPV Vaccine Uptake among Young Adults. <em>American Journal of Health Education</em>, <em>54</em>(2), 119-134. https://doi.org/10.1080/19325037.2022.2163005</li>
<li>Kater, C., Oostvogels, A., Hoevenaars, D., Haverkort, M. undefined. E. (2023). The Catch-Up Study; Determinants of Hpv Vaccine Uptake in a Dutch Campaign for Young Adults. <em>SSRN Electronic Journal</em>. https://doi.org/10.2139/ssrn.4586145</li>
<li>Argyris, Y. A., Kim, Y., Roscizewski, A., Song, W. (2021). The mediating role of vaccine hesitancy between maternal engagement with anti- and pro-vaccine social media posts and adolescent HPV-vaccine uptake rates in the US: The perspective of loss aversion in emotion-laden decision circumstances. <em>Social Science & Medicine</em>, <em>282</em>, 114043. https://doi.org/10.1016/j.socscimed.2021.114043</li>
<li>Johnson-Mallard, V., Darville, G., Mercado, R., Anderson-Lewis, C., MacInnes, J. (2019). How Health Care Providers Can Use Digital Health Technologies to Inform Human Papillomavirus (HPV) Decision Making and Promote the HPV Vaccine Uptake Among Adolescents and Young Adults. <em>BioResearch Open Access</em>, <em>8</em>(1), 84-93. https://doi.org/10.1089/biores.2018.0051</li>
<li>Remschmidt, C., Fesenfeld, M., Kaufmann, A. M., Deleré, Y. (2014). Sexual behavior and factors associated with young age at first intercourse and HPV vaccine uptake among young women in Germany: implications for HPV vaccination policies. <em>BMC Public Health</em>, <em>14</em>(1). https://doi.org/10.1186/1471-2458-14-1248</li>
<li>Ford, C., MacKay, M., Thaivalappil, A., McWhirter, J., Papadopoulos, A. (2023). COVID-19 Vaccine Communications on Instagram and Vaccine Uptake in Young Adults: A Content Assessment and Public Engagement Analysis. <em>Emerging Adulthood</em>, <em>12</em>(2), 224-235. https://doi.org/10.1177/21676968231222439</li>
<li>Sohal, P. (2020). Media Framing of Human Papillomavirus (HPV) Health Issues and HPV Vaccine-Related Sentiment in English Language News Media in India (2015-2018). <em>International Journal of Scientific and Research Publications (IJSRP)</em>, <em>10</em>(1), p9778. https://doi.org/10.29322/ijsrp.10.01.2020.p9778</li>
<li>Vu, M., Zhu, Y., Trinh, D. D., Hong, Y., Suk, R. (2023). Abstract C140: A population-based analysis of awareness and knowledge of HPV and HPV vaccine among Asian American adults by origin group, 2014-2019. <em>Cancer Epidemiology, Biomarkers & Prevention</em>, <em>32</em>(12_Supplement), C140-C140. https://doi.org/10.1158/1538-7755.disp23-c140</li>
<li>Lee, H., Lee, J., Henning-Smith, C., Choi, J. (2017). HPV literacy and its link to initiation and completion of HPV vaccine among young adults in Minnesota. <em>Public Health</em>, <em>152</em>, 172-178. https://doi.org/10.1016/j.puhe.2017.08.002</li>
<li>Vanderpool, R. C., Casey, B. R., Crosby, R. A. (2010). HPV-Related Risk Perceptions and HPV Vaccine Uptake Among a Sample of Young Rural Women. <em>Journal of Community Health</em>, <em>36</em>(6), 903-909. https://doi.org/10.1007/s10900-010-9345-3</li>
<li>Noguchi, N., Yokoi, R., Masu, T., Watanabe, M., Itoh, S., Yumoto, S. (2023). Association of COVID-19 information media, providers, and content with vaccine uptake among Tokyo residents. <em>Vaccine: X</em>, <em>15</em>, 100411. https://doi.org/10.1016/j.jvacx.2023.100411</li>
<li>Sundström, K., Tran, T. N., Lundholm, C., Young, C., Sparén, P., Dahlström, L. A. (2010). Acceptability of HPV vaccination among young adults aged 18–30 years–a population based survey in Sweden. <em>Vaccine</em>, <em>28</em>(47), 7492-7500. https://doi.org/10.1016/j.vaccine.2010.09.007</li>
<li>Massey, P. M., Leader, A., Yom‐Tov, E., Budenz, A., Fisher, K., Klassen, A. C. (2016). Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter. <em>Journal of Medical Internet Research</em>, <em>18</em>(12), e318-e318. https://doi.org/10.2196/jmir.6670</li>
<li>Zhang, J., Centola, D. (2019). Social Networks and Health: New Developments in Diffusion, Online and Offline. <em>Annual Review of Sociology</em>, <em>45</em>(1), 91-109. https://doi.org/10.1146/annurev-soc-073117-041421</li>
<li>Chen, H., Li, X., Gao, J., Liu, X., Mao, Y., Wang, R. (2021). Health Belief Model Perspective on the Control of COVID-19 Vaccine Hesitancy and the Promotion of Vaccination in China: Web-Based Cross-sectional Study. <em>Journal of Medical Internet Research</em>, <em>23</em>(9), e29329-e29329. https://doi.org/10.2196/29329</li>
<li>Damnjanović, K., Graeber, J., Ilić, S., Lam, W. Y., Lep, Ž., Morales, S. E. C. (2018). Parental Decision-Making on Childhood Vaccination. <em>Frontiers in Psychology</em>, <em>9</em>, 735-735. https://doi.org/10.3389/fpsyg.2018.00735</li>
<li>Palm, R., Bolsen, T., Kingsland, J. T. (2021). The Effect of Frames on COVID-19 Vaccine Resistance. <em>Frontiers in Political Science</em>, <em>3</em>. https://doi.org/10.3389/fpos.2021.661257</li>
<li>Walker, K., Head, K. J., Owens, H., Zimet, G. D. (2021). A qualitative study exploring the relationship between mothers’ vaccine hesitancy and health beliefs with COVID-19 vaccination intention and prevention during the early pandemic months. <em>Human Vaccines & Immunotherapeutics</em>, <em>17</em>(10), 3355-3364. https://doi.org/10.1080/21645515.2021.1942713</li>
<li>Clouston, S., Rubin, M. S., Phelan, J. C., Link, B. G. (2016). A Social History of Disease: Contextualizing the Rise and Fall of Social Inequalities in Cause-Specific Mortality. <em>Demography</em>, <em>53</em>(5), 1631-1656. https://doi.org/10.1007/s13524-016-0495-5</li>
<li>Gollust, S. E., Attanasio, L. B., Dempsey, A. F., Benson, A. M., Fowler, E. F. (2013). Political and News Media Factors Shaping Public Awareness of the HPV Vaccine. <em>Women s Health Issues</em>, <em>23</em>(3), e143-e151. https://doi.org/10.1016/j.whi.2013.02.001</li>
<li>Katz, I. T., Bogart, L. M., Fu, C. M., Liu, Y., Cox, J. E., Samuels, R. C. (2016). Barriers to HPV immunization among blacks and latinos: a qualitative analysis of caregivers, adolescents, and providers. <em>BMC Public Health</em>, <em>16</em>(1), 874-874. https://doi.org/10.1186/s12889-016-3529-4</li>
</ol>
</article>