Skip to main content

Encouraging Vaccination Behavior Through Online Social Media

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Information Systems and Organisation ((LNISO,volume 19))

Abstract

We explore the suitability of online social media (OSM) for influencing the public’s decision-making process regarding a vaccination to protect girls against HPV, a virus associated with cervical cancer. Parents of girls in the target cohort were invited to online discussion forums where they could discuss their opinions on the vaccination. They were exposed to promotion of the vaccination in one of four different ways, and coming from one of two different sources, i.e., peers or government health representatives. Following the health belief model (HBM), these messages served as cues to action. Using a novel network analysis approach, we find that the HBM does not adequately account for influence via OSM. Specifically we show that vaccination decisions are not taken in social isolation, a fact thus far ignored by various forms of the HBM. Implications for studies assessing the use of online channels for health communication are discussed.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    Literal texts have been translated from Dutch.

  2. 2.

    The research ethics committee of the Netherlands Organisation for Applied Scientific Research was consulted during the design of this study.

References

  1. Bosch, F.X., Lorincz, A., Munoz, N., Meijer, C.J.L.M., Shah, K.V.: The causal relation between human papillomavirus and cervical cancer. J. Clin. Pathol. 55(4), 244–265 (2002)

    Article  Google Scholar 

  2. Clifford, G.M., Gallus, S., Herrero, R., Munoz, N., Snijders, P.J.F., Vaccarella, S., Franceschi, S.: Worldwide distribution of human papillomavirus types in cytologically normal women in the international agency for research on cancer HPV prevalence surveys: a pooled analysis. Lancet 366(9490), 991–998 (2005)

    Article  Google Scholar 

  3. Dunne, E.F., Unger, E.R., Sternberg, M., McQuillan, G., Swan, D.C., Patel, S.S., Markowitz, L.E.: Prevalence of HPV infection among females in the United States. J. Am. Med. Assoc. 297(8), 813–819 (2007)

    Article  Google Scholar 

  4. van Keulen, H.M., Otten, W., Ruiter, R.A., Fekkes, M., van Steenbergen, J., Dusseldorp, E., Paulussen, T.W.: Determinants of HPV vaccination intentions among Dutch girls and their mothers: a cross-sectional study. BMC Public Health 13(1), 111 (2013)

    Article  Google Scholar 

  5. Fox, S.: Pew internet and american life project: the engaged E-patient population. http://www.pewinternet.org/Reports/2008/The-Engaged-Epatient-Population.aspx (2008)

  6. Betsch, C., Sachse, K.: Dr. Jekyll or Mr. Hyde? (How) the internet influences vaccination decisions: Recent evidence and tentative guidelines for online vaccine communication. Vaccine 30(25), 3723–3726 (2012)

    Article  Google Scholar 

  7. Grajales III, F.J., Sheps, S., Ho, K., Novak-Lauscher, H., Eysenbach, G.: Social media: a review and tutorial of applications in medicine and health care. J. Med. Internet Res. 16(2), e13 (2014)

    Article  Google Scholar 

  8. Campbell, E., Salathé, M.: Complex social contagion makes networks more vulnerable to disease outbreaks. arXiv:1211.0518 (2012)

  9. Kata, A.: Anti-vaccine activists, Web 2.0, and the postmodern paradigm–An overview of tactics and tropes used online by the anti-vaccination movement. Vaccine 30(25), 3778–3789 (2012)

    Article  Google Scholar 

  10. Nan, X., Madden, K.: HPV vaccine information in the blogosphere: how positive and negative blogs influence vaccine-related risk perceptions. Attitudes Behav. Intentions Health Commun. 27, 829–836 (2012)

    Google Scholar 

  11. Nicholson, M.S., Leask, J.: Lessons from an online debate about measles–mumps–rubella (MMR) immunization. Vaccine 30(25), 3806–3812 (2012)

    Article  Google Scholar 

  12. Zimmerman, R.K., Wolfe, R.M., Fox, D.E., Fox, J.R., Nowalk, M.P., Troy, J.A., Sharp, L.K.: Vaccine criticism on the world wide web. J. Med. Internet Res. 7(2), e17 (2005)

    Article  Google Scholar 

  13. Kaplan, A.M., Haenlein, M.: Users of the world, unite! The challenges and opportunities of social media. Bus. Horiz. 53(1), 59–68 (2010)

    Article  Google Scholar 

  14. Stieglitz, S., Dang-Xuan, L.: Emotions and information diffusion in social media—sentiment of microblogs and sharing behavior. J. Manag. Inf. Syst. 29(4), 217–248 (2013)

    Article  Google Scholar 

  15. Matook, S., Brown, S.A., Rolf, J.: Forming an intention to act on recommendations given via online social networks. Eur. J. Inf. Syst. 24(1), 76–92 (2015)

    Article  Google Scholar 

  16. Fichman, R.G., Kohli, R., Krishnan, R.: The role of information systems in healthcare: current research and future trends. Inf. Syst. Res. 22(3), 419–428 (2011)

    Article  Google Scholar 

  17. Yan, L., Tan, Y.: Feeling blue? Go online: an empirical study of social support among patients. Inf. Syst. Res. 25(4), 690–709 (2014)

    Article  Google Scholar 

  18. Keelan, J., Pavri, V., Balakrishnan, R., Wilson, K.: An analysis of the human papilloma virus vaccine debate on myspace blogs. Vaccine 28(6), 1535–1540 (2010)

    Article  Google Scholar 

  19. Rosenstock, I.M.: Historical origins of the health belief model. Health Educ. Monogr. 2, 328–335 (1974)

    Article  Google Scholar 

  20. Janz, N.K., Becker, M.H.: The health belief model: a decade later. Health Educ. Q. 11, 1–47 (1984)

    Article  Google Scholar 

  21. Carpenter, C.J.: A meta-analysis of the effectiveness of health belief model variables in predicting behavior. Health Commun. 25(8), 661–669 (2010)

    Article  Google Scholar 

  22. Watts, D.J., Dodds, P.S: Influentials, networks, and public opinion formation, J. Consum. Res. (2007)

    Google Scholar 

  23. Sassenberg, K., Boos, M.: Attitude change in computer-mediated communication: effects of anonymity and category norms. Group Processes Intergroup Relat. 6(4), 405–422 (2003)

    Article  Google Scholar 

  24. Pornpitakpan, C.: The persuasiveness of source credibility: a critical review of five decades’ evidence. J. Appl. Soc. Psychol. 34(2), 243–281 (2004)

    Article  Google Scholar 

  25. Cialdini, R.B., Goldstein, N.J.: Social influence: compliance and conformity. Annu. Rev. Psychol. 55, 591–621 (2004)

    Article  Google Scholar 

  26. Anagnostopoulos, A., Brova, G., Terzi, E.: Peer and authority pressure in information-propagation models. In: Machine Learning and Knowledge Discovery in Databases, pp. 76–91. Springer: Berlin (2011)

    Google Scholar 

  27. Knowles, E.S., Linn, J.A.: Approach-avoidance model of persuasion: alpha and omega strategies for change. Resist. Persuasion, 117–148 (2004)

    Google Scholar 

  28. Epskamp, S., Cramer, A.O., Waldorp, L.J., Schmittmann, V.D., Borsboom, D.: Qgraph: Network visualizations of relationships in psychometric data. J. Stat. Softw. 48(4), 1–18 (2012)

    Article  Google Scholar 

  29. Lauritzen, S.L.: Graphical Models. Oxford University Press (1996)

    Google Scholar 

  30. Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L.J., Cramer, A.O.: State of the aRt personality research: a tutorial on network analysis of personality data in R. J. Res. Pers. 54, 13–29 (2015)

    Article  Google Scholar 

  31. Fried, E.I., Bockting, C., Arjadi, R., Borsboom, D., Amshoff, M., Cramer, A.O.J., Epskamp, S., Tuerlinckx, F., Carr, D., Stroebe, M.: From loss to loneliness: the relationship between depressive symptoms and bereavement. J. Abnorm. Psychol. (in press)

    Google Scholar 

  32. McNally, R.J., Robinaugh, D.J., Wu, G.W.Y., Wang, L., Deserno, M., Borsboom, D.: Mental disorders as causal systems: a network approach to posttraumatic stress disorder. Clin. Psychol. Sci. (2014)

    Google Scholar 

  33. Epskamp, S., Maris, G., Waldorp, L., Borsboom, D.: Network psychometrics. In: P. Irwing, D. Hughes, T. Booth (eds.), Handbook of psychometrics. Wiley, New York (in press)

    Google Scholar 

  34. Liu, H., Lafferty, J., Wasserman, L.: The nonparanormal: semiparametric estimation of high dimensional undirected graphs. J. Mach. Learn. Res. 10, 2295–2328 (2009)

    Google Scholar 

  35. Zhao, T., Liu, H., Roeder, K., Lafferty J., Wasserman, L.: Huge: high-dimensional undirected graph estimation. R package version 1.2.6. http://CRAN.R-project.org/package=huge (2014)

  36. Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Ser. B (Methodol.), 267–288 (1996)

    Google Scholar 

  37. Friedman, J., Hastie, T., Tibshirani, R.: Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9, 432–441 (2008)

    Article  Google Scholar 

  38. Witten, D.M., Friedman, J.H., Simon, N.: New insights and faster computations for the graphical lasso. J. Comput. Graph. Stat. 20, 892–900 (2011)

    Article  Google Scholar 

  39. Chen, J., Chen, Z.: Extended Bayesian information criteria for model selection with large model spaces. Biometrika 95, 759–771 (2008)

    Article  Google Scholar 

  40. Borkulo, C.D. van, Borsboom, D., Epskamp, S., Blanken, T.F., Boschloo, L., Schoevers, R.A., Waldorp, L.J.: A new method for constructing networks from binary data. Nat. Sci. Rep. 4 (2014)

    Google Scholar 

  41. Epskamp, S., Costantini, G., Cramer, A.O.J., Waldorp, L.J., Schmittmann, V.D., Borsboom, D.: qgraph: graph plotting methods, psychometric data visualization and graphical model estimation. R package version 1.3.1.http://CRAN.R-project.org/package=qgraph (2015)

  42. Pourahmadi, M.: Covariance estimation: the GLM and regularization perspectives. Stat. Sci. 26, 369–387 (2011)

    Article  Google Scholar 

  43. Park, C., Lee, T.M.: Information direction, website reputation and eWOM effect: a moderating role of product type. J. Bus. Res. 62(1), 61–67 (2009)

    Article  Google Scholar 

  44. Hofstede, G.: Cultures and Organizations, pp. 159–166. London: McGraw-Hill (1991)

    Google Scholar 

  45. Johnson, E.J., Shu, S.B., Dellaert, B.G., Fox, C., Goldstein, D.G., Häubl, G., Larrick, R.P., Payne, J.W., Peters, E., Schkade, D., Wansink, B., Weber, E.U.: Beyond nudges: tools of a choice architecture. Mark. Lett. 23(2), 487–504 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David J. Langley .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Langley, D.J., Wijn, R., Epskamp, S., van Bork, R. (2016). Encouraging Vaccination Behavior Through Online Social Media. In: D'Ascenzo, F., Magni, M., Lazazzara, A., Za, S. (eds) Blurring the Boundaries Through Digital Innovation. Lecture Notes in Information Systems and Organisation, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-38974-5_24

Download citation

Publish with us

Policies and ethics