Cancer Patients on Facebook: A Theoretical Framework

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 504)

Abstract

The growing presence of the technology cause of an essential need to explore cancer patients’ behavior in online communities. Social Network Sites (SNS) such as Facebook provide an interactive environment to deliver health information to cancer patients. Only a few studies have looked at the role of Facebook for cancer patients despite their potential deliver health messages to large audiences. Hence, there should be more rigorous research to explain the cancer patients’ behavior in SNS. This study propose a theoretical framework to explore the cognitive, social and technological constructs that affect the performance of cancer patients in Facebook by using social cognitive theory (SCT). Based on purposive sampling, questionnaires were distributed to 178 breast cancer patients in cancer support groups in Peninsular Malaysia. Through this study, a basis for the investigation of Malaysian social network support in using SNSs is successfully established.

Keywords

Cancer E-Patients Health 2.0 Social Cognitive Theory Social Network Sites 

References

  1. 1.
    National Cancer Registry. Malaysia Cancer Statistics – Data & Figure (2007)Google Scholar
  2. 2.
    Clauser, S.B., Wagner, E.H., Bowles, E.J.A., Tuzzio, L., Greene, S.M.: Improving modern cancer care through information technology. Am. J. Prev. Med. 40(5), S198–S207 (2012)CrossRefGoogle Scholar
  3. 3.
    Bacigalupe, G.: Is there a role for social technologies in collaborative healthcare? Fam. Syst. Health 29(1), 1–14 (2011)CrossRefGoogle Scholar
  4. 4.
    Mirabolghasemi, M., Iahad, N.A.: Malaysian breast cancer patients’ performance in using social network sites: a task person technology fit model. Jurnal Teknologi 78(8–2), 42–49 (2016)Google Scholar
  5. 5.
    Van De Belt, T.H., Engelen, L.J., Berben, S.A., Schoonhoven, L.: Definition of Health 2.0 and Medicine 2.0: a systematic review. J. Med. Internet Res. 12(2), e18 (2010)CrossRefGoogle Scholar
  6. 6.
    Van de Belt, T.H., Berben, S.A., Samsom, M., Engelen, L.J., Schoonhoven, L.: Use of social media by Western European hospitals: longitudinal study. J. Med. Internet Res. 14(3), e61 (2012)CrossRefGoogle Scholar
  7. 7.
    Koskan, A., Klasko, L., Davis, S.N., Gwede, C.K., Wells, K.J., Kumar, A., Meade, C.D.: Use and taxonomy of social media in cancer-related research: a systematic review. Am. J. Public Health 104(7), e20–e37 (2014)CrossRefGoogle Scholar
  8. 8.
    Cao, J., Basoglu, K.A., Sheng, H., Lowry, P.B.: A systematic review of social networks research in information systems: building a foundation for exciting future research. Commun. Assoc. Inf. Syst. 36, 727–759 (2015)Google Scholar
  9. 9.
    Bender, J.L., Jimenez-Marroquin, M.C., Jadad, A.R.: Seeking support on Facebook: a content analysis of breast cancer groups. J. Med. Internet Res. 13(1), e16 (2011)CrossRefGoogle Scholar
  10. 10.
    Wells, T., Link, M.: Facebook user research using a probability-based sample and behavioral data. J. Comput. Mediat. Commun. 19(4), 922–937 (2014)CrossRefGoogle Scholar
  11. 11.
    Loader, B.D., Muncer, S., Burrows, R., Pleace, N., Nettleton, S.: Medicine on the line? Computer-mediated social support and advice for people with diabetes. Int. J. Soc. Welf. 11(1), 53–65 (2002)CrossRefGoogle Scholar
  12. 12.
    Turner, J.W., Grube, J.A., Meyers, J.: Developing an optimal match within online communities: an exploration of CMC support communities and traditional support. J. Commun. 51(2), 231–251 (2001)CrossRefGoogle Scholar
  13. 13.
    Griffiths, F., Cave, J., Boardman, F., Ren, J., Pawlikowska, T., Ball, R., Cohen, A.: Social networks–the future for health care delivery. Soc. Sci. Med. 75(12), 2233–2241 (2012)CrossRefGoogle Scholar
  14. 14.
    Carillo, Kévin D.: Social cognitive theory in is research – literature review, criticism, and research agenda. In: Prasad, Sushil K., Vin, Harrick M., Sahni, S., Jaiswal, Mahadeo P., Thipakorn, B. (eds.) ICISTM 2010. CCIS, vol. 54, pp. 20–31. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12035-0_4 CrossRefGoogle Scholar
  15. 15.
    Mirabolghasemi, M., Iahad, N.A., Miskon, S.: Exploring factors that affect on cancer patients performance in social networks for informational support. Int. J. Bus. Inf. Syst. 20, 348–361 (2015)Google Scholar
  16. 16.
    Sekaran, U., Bougie, R.: Research Methods for Business: A Skill Building Approach, 5th edn. Wiley, New York (2010)Google Scholar
  17. 17.
    Khalifa, M., Vanissa, L.: Determinants of satisfaction at different adoption stages of internet-based services. J. Assoc. Inf. Syst. 4, 206–233 (2003)Google Scholar
  18. 18.
    Koo, C., Wati, Y., Park, K., Lim, M.K.: Website quality, expectation, confirmation, and end user satisfaction: the knowledge-intensive website of the Korean National Cancer Information Center. J. Med. Internet Res. 13, e81 (2011)CrossRefGoogle Scholar
  19. 19.
    Wu, S.Y., Wang, S.T., Liu, F., Hu, D.C., Hwang, W.Y.: The influences of social self-efficacy on social trust and social Capital-A case study of Facebook. Turk. Online J. Educ. Technol. TOJET 11, 246–254 (2012)Google Scholar
  20. 20.
    Sherer, M., Maddux, J.E., Mercandante, B., Prentice-Dunn, S., Jacobs, B., Rogers, R.W.: The self-efficacy scale: construction and validation. Psychol. Rep. 51, 663–671 (1982)CrossRefGoogle Scholar
  21. 21.
    Gustafson, D.H., Hawkins, R., Pingree, S., McTavish, F., Arora, N.K., Mendenhall, J., Salner, A.: Effect of computer support on younger women with breast cancer. J. General Internal Med. 16(7), 435–445 (2001)CrossRefGoogle Scholar
  22. 22.
    Gustafson, D.H., McTavish, F.M., Stengle, W., Ballard, D., Hawkins, R., Shaw, B.R., Landucci, G.: Use and impact of eHealth system by low-income women with breast cancer. J. Health Commun. 10(S1), 195–218 (2005)CrossRefGoogle Scholar
  23. 23.
    Shaw, B.R., DuBenske, L.L., Han, J.Y., Cofta-Woerpel, L., Bush, N., Gustafson, D.H., McTavish, F.: Antecedent characteristics of online cancer information seeking among rural breast cancer patients: an application of the Cognitive-Social Health Information Processing (C-SHIP) model. J. Health Commun. 13(4), 389–408 (2008)CrossRefGoogle Scholar
  24. 24.
    Han, J.Y., Wise, M., Kim, E., Pingree, R., Hawkins, R.P., Pingree, S., Gustafson, D.H.: Factors associated with use of interactive cancer communication system: an application of the comprehensive model of information seeking. J. Comput. Mediat. Commun. 15(3), 367–388 (2010)CrossRefGoogle Scholar
  25. 25.
    Kim, S.C., Shah, D.V., Namkoong, K., McTavish, F.M., Gustafson, D.H.: Predictors of online health information seeking among women with breast cancer: the role of social support perception and emotional well-being. J. Comput. Mediat. Commun. 18, 98–118 (2013)CrossRefGoogle Scholar
  26. 26.
    Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable and measurement error. J. Market. Res. 34(2), 161–188 (1981)Google Scholar
  27. 27.
    Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks (2017)MATHGoogle Scholar
  28. 28.
    Bravo, E.R., Santana, M., Rodon, J.: Information systems and performance: the role of technology, the task and the individual. Behav. Inf. Technol. 34(3), 247–260 (2015)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.Lahijan BranchIslamic Azad UniversityLahijanIran
  2. 2.Universiti Teknologi MalaysiaJohor BahruMalaysia

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