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Research Article

A comprehensive examination of association between belief in vaccine misinformation and vaccination intention in the COVID-19 context

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References

  • Bono, S. A., Faria de Moura Villela, E., Siau, C. S., Chen, W. S., Pengpid, S., Hasan, M. T., Colebunders, R. (2021). Factors affecting COVID-19 vaccine acceptance: An international survey among low- and middle-income countries. Vaccines, 9, 515. doi:10.3390/vaccines9050515
  • Brennen, J. S., Simon, F. M., Howard, P. N., & Nielsen, R. K. (2020). Types, sources, and claims of COVID-19 misinformation. Reuters Institute for the Study of Journalism. Accessed Oct 26, 2021. https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2020-04/Brennen%20-%20COVID%2019%20Misinformation%20FINAL%20(3).pdf
  • Breslin, G., Dempster, M., Berry, E., Cavanagh, M., Armstrong, N. C., & Gesser-Edelsburg, A. (2021). COVID-19 vaccine uptake and hesitancy survey in Northern Ireland and republic of Ireland: Applying the theory of planned behaviour. PLOS ONE, 16(11), e0259381. doi:10.1371/journal.pone.0259381
  • Burke, M. (2012). Reading, writing, relationships: The impact of social network sites on relationships and well-being [PhD Thesis]. Carnegie Mellon University.
  • Callegaro, M., & DiSogra, C. (2008). Computing response metrics for online panels. Public Opinion Quarterly, 72(5), 1008–1032. doi:10.1093/poq/nfn065
  • Centola, D. (2020). Considering network interventions. Proceedings of the National Academy of Sciences, 117( 52), 32833–32835. doi:10.1073/pnas.2022584118
  • Chae, J. (2015). A three-factor cancer-related mental condition model and its relationship with cancer information use, cancer information avoidance, and screening intention. Journal of Health Communication, 20(10), 1133–1142. doi:10.1080/10810730.2015.1018633
  • Chen, M., Bell, R. A., & Barnett, G. A. (2021). From network positions to language use: Understanding the effects of brokerage and closure structures from a linguistic perspective. Health Communication, 36(8), 1001–1008. doi:10.1080/10410236.2020.1731776
  • Chia, S., Lu, F, C., & Sun, Y. (2021). Tracking the influence of misinformation on elderly people’s perceptions and intention to accept COVID-19 vaccines. Health Communication, 1–11. doi:10.1080/10410236.2021.1980251
  • Chou, W.-Y. S., & Budenz, A. (2020). Considering emotion in COVID-19 vaccine communication: Addressing vaccine hesitancy and fostering vaccine confidence. Health Communication, 35(14), 1718–1722. doi:10.1080/10410236.2020.1838096
  • Damian, A. J., & Gallo, J. J. (2020). Promoting health literacy during the COVID-19 pandemic: A call to action for healthcare professionals. Harvard Kennedy School Misinformation Review. doi:10.37016/mr-2020-027
  • Eveland, J.W. P., Hayes, A. F., Shah, D. V., & Kwak, N. (2005). Understanding the relationship between communication and political knowledge: A model comparison approach using panel data. Political Communication, 22(4), 423–446. doi:10.1080/10584600500311345
  • Fan, C.-W., Chen, I.-H., Ko, N.-Y., Yen, C.-F., Lin, C.-Y., Griffiths, M. D., & Pakpour, A. H. (2021). Extended theory of planned behavior in explaining the intention to COVID-19 vaccination uptake among mainland Chinese university students: An online survey study. Human Vaccines & Immunotherapeutics, 17(10), 3413–3420. doi:10.1080/21645515.2021.1933687
  • Featherstone, J. D., & Zhang, J. (2020). Feeling angry: The effects of vaccine misinformation and refutational messages on negative emotions and vaccination attitude. Journal of Health Communication, 25(9), 692–702. doi:10.1080/10810730.2020.1838671
  • Fernandes, N., Costa, D., Costa, D., Keating, J., & Arantes, J. (2021). Predicting COVID-19 vaccination intention: The determinants of vaccine hesitancy. Vaccines, 9(10), 1161. doi:10.3390/vaccines9101161
  • Fishbein, M. (2000). The role of theory in HIV prevention. AIDS Care, 12(3), 273–278. doi:10.1080/09540120050042918
  • Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.
  • Fisher, M., & Sang-Hun, C. (2020, March 23). How South Korea flattened the curve. The New York Times. https://www.nytimes.com/2020/03/23/world/asia/coronavirus-south-korea-flatten-curve.html
  • Granovetter, M. (1983). The strength of weak ties: A network theory revisited. Sociological Theory, 1, 201–233. doi:10.2307/202051
  • Holbert, R. L., & Stephenson, M. T. (2008). Commentary on the uses and misuses of structural equation modeling in communication research. In Andrew F. Hayes, Michael D. Slater & Leslie B. Snyder (Eds.), The sage sourcebook of advanced data analysis methods for communication research (pp. 185–218). Thousand Oaks, CA: Sage Publications, Inc. doi:10.4135/9781452272054.n7
  • Hornik, R. C., Kikut, A., Jesch, E., Woko, C., Siegel, L., & Kim, K. (2020). Association of COVID-19 misinformation with face mask wearing and social distancing in a nationally representative US sample. Health Communication, 36, 1. doi:10.31234/osf.io/k8pds
  • Hotez, P., Batista, C., Ergonul, O., Figueroa, J. P., Gilbert, S., Gursel, M., … Bottazzi, M. E. (2021). Correcting COVID-19 vaccine misinformation. EClinicalMedicine, 33, 100780. doi:10.1016/j.eclinm.2021.100780
  • Husain, F., Shahnawaz, M. G., Khan, N. H., Parveen, H., & Savani, K. (2021). Intention to get COVID-19 vaccines: Exploring the role of attitudes, subjective norms, perceived behavioral control, belief in COVID-19 misinformation, and vaccine confidence in Northern India. Human Vaccines & Immunotherapeutics, 17(11), 1–13. doi:10.1080/21645515.2021.1967039
  • Ihm, J., & Lee, C. (2021). Toward more effective public health interventions during the COVID-19 pandemic: Suggesting audience segmentation based on social and media resources. Health Communication, 36(1), 12. doi:10.1080/10410236.2020.1847450
  • Jaspal, R., & Breakwell, G. M. (2021). Social support, perceived risk and the likelihood of COVID-19 testing and vaccination: Cross-sectional data from the United Kingdom. Current Psychology, 41(1), 492–504. doi:10.1007/s12144-021-01681-z
  • Jensen, J. D., Bernat, J. K., Davis, L. A., & Yale, R. (2010). Dispositional cancer worry: Convergent, divergent, and predictive validity of existing scales. Journal of Psychosocial Oncology, 28(5), 470–489. doi:10.1080/07347332.2010.498459
  • Kahlor, L. (2010). PRISM: A planned risk information seeking model. Health Communication, 25(4), 345–356. doi:10.1080/10410231003775172
  • Kasperson, R. E., Renn, O., Slovic, P., Brown, H. S., Emel, J., Goble, R., … Ratick, S. (1988). The social amplification of risk: A conceptual framework. Risk Analysis, 8(2), 177–187. doi:10.1111/j.1539-6924.1988.tb01168.x
  • KDCA. (2021, May 2). Updates on COVID-19 in Republic of Korea. Korea Disease Control and Prevention Agency. http://ncov.mohw.go.kr/upload/viewer/skin/doc.html?fn=1620259744791_20210506090904.pdf&rs=/upload/viewer/result/202202/
  • Kim, S. (2021, December 12). Moon stresses Korea’s democratic values in summit hosted by Biden. Korea JoongAng Daily. https://koreajoongangdaily.joins.com/2021/12/12/national/diplomacy/Moon-Jaein-Joe-Biden-Summit-for-Democracy/20211212170910831.html
  • Kim, E., & Ihm, J. (2020). More than virality: Online sharing of controversial news with activated audience. Journalism & Mass Communication Quarterly, 97(1), 118–140. doi:10.1177/1077699019836950
  • Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York, NY: Guilford Press.
  • Krackhardt, D. (1992). The strength of strong ties: The importance of philos in organizations. In N. Nohria & R. G. Eccles (Eds.), Networks and organizations: Structure form, and action (pp. 216–239). Boston: Harvard Business School Press.
  • Kreps, S. E., Goldfarb, J. L., Brownstein, J. S., & Kriner, D. L. (2021). The Relationship between US adults’ misconceptions about COVID-19 vaccines and vaccination preferences. Vaccines, 9(8), 901. doi:10.3390/vaccines9080901
  • Lazarus, J. V., Ratzan, S. C., Palayew, A., Gostin, L. O., Larson, H. J., Rabin, K., … El-Mohandes, A. (2021). A global survey of potential acceptance of a COVID-19 vaccine. Nature Medicine, 27(2), 225–228. doi:10.1038/s41591-020-1124-9
  • Lee, E. J., Lee, H. Y., & Chung, S. (2017). Age differences in health literacy: Do younger Korean adults have a higher level of health literacy than older Korean adults? Health & Social Work, 42(3), 133–142. doi:10.1093/hsw/hlx026
  • Little, T. D. (2013). Longitudinal structural equation modeling. New York, NY: Guilford press.
  • Loomba, S., de Figueiredo, A., Piatek, S. J., de Graaf, K., & Larson, H. J. (2021). Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nature Human Behaviour, 5(3), 337–348. doi:10.1038/s41562-021-01056-1
  • Marsden, P. V., & Campbell, K. E. (1984). Measuring tie strength. Measuring Tie Strength. Social Forces, 63(2), 482–501. JSTOR. 10.2307/2579058.
  • Mello, S., & Hovick, S. R. (2016). Predicting behaviors to reduce toxic chemical exposures among new and expectant mothers: The role of distal variables within the integrative model of behavioral prediction. Health Education & Behavior, 43(6), 705–715. doi:10.1177/1090198116637600
  • Molino, A. R., Andersen, K. M., Sawyer, S. B., Ðoàn, L. N., Rivera, Y. M., James, B. D., … Jarrett, B. A. (2021). The expert next door: Interactions with friends and family during the COVID-19 pandemic. American Journal of Epidemiology, 1–5. doi:10.1093/aje/kwab245
  • Monselise, M., Chang, C.-H., Ferreira, G., Yang, R., & Yang, C. C. (2021). Topics and sentiments of public concerns regarding COVID-19 vaccines: Social media trend analysis. Journal of Medical Internet Research, 23(10), e30765. doi:10.2196/30765
  • Rosenstock, I. M. (1974). Historical origins of the health belief model. Health Education Monographs, 2(4), 328–335. doi:10.1177/109019817400200403
  • Scannell, D., Desens, L., Guadagno, M., Tra, Y., Acker, E., Sheridan, K., Fulk, M. (2021). COVID-19 vaccine discourse on twitter: A content analysis of persuasion techniques, sentiment and mis/disinformation. Journal of Health Communication, 26(7), 443–459. doi:10.1080/10810730.2021.1955050
  • Seaman, C. S., & Weber, R. (2015). Undisclosed flexibility in computing and reporting structural equation models in communication science. Communication Methods and Measures, 9(4), 208–232. doi:10.1080/19312458.2015.1096329
  • Shim, J.-G., Ryu, K.-H., Lee, S. H., Cho, E.-A., Lee, Y. J., & Ahn, J. H. (2021). Text mining approaches to analyze public sentiment changes regarding COVID-19 vaccines on social media in Korea. International Journal of Environmental Research and Public Health, 18(12), 6549. doi:10.3390/ijerph18126549
  • Shin, J. (2021, March 2). More than 23,000 vaccinated as officials warn against fake news. The Korea Herald. http://www.koreaherald.com/view.php?ud=20210302000840
  • Sjöberg, L. (1998). Worry and risk perception. Risk Analysis, 18(1), 85–93. doi:10.1111/j.1539-6924.1998.tb00918.x
  • Slater, M. D., Hayes, A. F., & Ford, V. L. (2007). Examining the moderating and mediating roles of news exposure and attention on adolescent judgments of alcohol-related risks. Communication Research, 34(4), 355–381. doi:10.1177/0093650207302783
  • Smith, K. P., & Christakis, N. A. (2008). Social networks and health. Annual Review of Sociology, 34(1), 405–429. doi:10.1146/annurev.soc.34.040507.134601
  • Tannenbaum, M. B., Hepler, J., Zimmerman, R. S., Saul, L., Jacobs, S., Wilson, K., & Albarracín, D. (2015). Appealing to fear: A meta-analysis of fear appeal effectiveness and theories. Psychological Bulletin, 141(6), 1178–1204. doi:10.1037/a0039729
  • Thaker, J., & Ganchoudhuri, S. (2021). The role of attitudes, norms, and efficacy on shifting COVID-19 vaccine intentions: A longitudinal study of COVID-19 vaccination intentions in New Zealand. Vaccines, 9(10), 1132. doi:10.3390/vaccines9101132
  • van der Weerd, W., Timmermans, D. R., Beaujean, D. J., Oudhoff, J., & van Steenbergen, J. E. (2011). Monitoring the level of government trust, risk perception and intention of the general public to adopt protective measures during the influenza A (H1N1) pandemic in the Netherlands. BMC Public Health, 11(1), 575. doi:10.1186/1471-2458-11-575
  • Vulpe, S.-N., & Rughiniş, C. (2021). Social amplification of risk and “probable vaccine damage”: A typology of vaccination beliefs in 28 European countries. Vaccine, 39(10), 1508–1515. doi:10.1016/j.vaccine.2021.01.063
  • Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior, 27(5), 591–615. doi:10.1177/109019810002700506
  • Xiao, X., & Wong, R. M. (2020). Vaccine hesitancy and perceived behavioral control: A meta-analysis. Vaccine, 38(33), 5131–5138. doi:10.1016/j.vaccine.2020.04.076
  • Yang, Z. J. (2015). Predicting young adults’ intentions to get the H1N1 vaccine: An integrated model. Journal of Health Communication, 20(1), 69–79. doi:10.1080/10810730.2014.904023
  • Yang, A., Shin, J., Zhou, A., Huang-Isherwood, K. M., Lee, E., Dong, C., … Liu, W. (2021). The battleground of COVID-19 vaccine misinformation on facebook: Fact checkers vs. misinformation spreaders. Harvard Kennedy School Misinformation Review. doi:10.37016/mr-2020-78
  • Yuan, Y. C., Fulk, J., Monge, P. R., & Contractor, N. (2010). Expertise directory development, shared task interdependence, and strength of communication network ties as multilevel predictors of expertise exchange in transactive memory work groups. Communication Research, 37(1), 20–47. doi:10.1177/0093650209351469
  • Yzer, M. C., Cappella, J. N., Fishbein, M., Hornik, R. C., Sayeed, S., & Ahern, R. K. (2004). The role of distal variables in behavior change: Effects of adolescents’ risk for marijuana use on intention to use marijuana. Journal of Applied Social Psychology, 34(6), 1229–1250. doi:10.1111/j.1559-1816.2004.tb02005.x
  • Yzer, M. C., & van den Putte, B. (2014). Control perceptions moderate attitudinal and normative effects on intention to quit smoking. Psychology of Addictive Behaviors, 28(4), 1153–1161. doi:10.1037/a0037924
  • Zhang, J., & Centola, D. (2019). Social networks and health: New developments in diffusion, online and offline. Annual Review of Sociology, 45(1), 91–109. doi:10.1146/annurev-soc-073117-041421

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