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The Role of Online Social Networks in Consumer Health Informatics: An Example of the Implicit Incorporation of Lean Principles

  • Carolin Durst
  • Janine Viol
  • Nilmini Wickramasinghe
Chapter
Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)

Abstract

Consumer health informatics is a relatively new and rapidly expanding area within the field of medical informatics. Central to this discipline is the importance of providing information and support to individuals (consumers) so that they can be empowered and take a central role in their own health and well-being.

The rapidly increasing prevalence of obesity is a phenomenon often referred to as the “obesity epidemic” (Obesity: preventing and managing the global epidemic. Report of a WHO Consultation. WHO Technical Report Series 894, WHO, Geneva, 2000). Literature suggests social networks to be one of the most important dimension of people’s social environment that may enable or constrain the adoption of health-promoting behaviors (e.g., The New England Journal of Medicine, 357:370–379, 2007; Social Science & Medicine (1982), 63:1011-1022, 2006). Using data collected in qualitative interviews and via a Facebook application, this research in progress provides first insights on the relationship between online social connections, health-related behaviors, and body weight.

An outlook is given on how the use of online social networks may facilitate appropriate health-related behaviors in the context of obesity.

Keywords

Social Network Social Network Analysis Social Network Site Online Social Network Free Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Abraham, A., Hassanien, A. E., & SnáSel, V. (2009). Computational social network analysis: Trends, tools and research advances. Dordrecht: Springer.Google Scholar
  2. Arnaboldi, V., Passarella, A., Tesconi, M., & Gazze, D. (2011). Towards a characterization of egocentric networks in online social networks. Retrieved from cnd.iit.cnr.it
  3. Bahr, D. B., Browning, R. C., Wyatt, H. R., & Hill, J. O. (2009). Exploiting social networks to mitigate the obesity epidemic. Obesity (Silver Spring, Md.), 17, 723–728.CrossRefGoogle Scholar
  4. Borgatti, S. P., Jones, C., & Everett, M. G. (1998). Network measures of social capital’. Connections., 21, 27–36.Google Scholar
  5. Bos, L., Marsh, A., Carroll, D., Gupta, S., & Rees, M. (2008). Patient 2.0 empowerment. In H. R. Arabnia & A. Marsh (Eds.), Proceedings of the 2008 international conference on Semantic Web & Web Services (pp. 164–167), Las Vegas.Google Scholar
  6. Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, 210–230.CrossRefGoogle Scholar
  7. BVDW. (2010) Social Media Kompass 2010/2011. Fachgruppe Social Media im Bundesverband Digitale Wirtschaft (BVDW) e.V., Düsseldorf.Google Scholar
  8. Christakis, N. A., & Fowler, J. H. (2007). The spread of obesity in a large social network over 32 years. The New England Journal of Medicine, 357, 370–379.PubMedCrossRefGoogle Scholar
  9. Cohen-Cole, E., & Fletcher, J. M. (2008). Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic. Journal of Health Economics, 27, 1382–1387.PubMedCrossRefGoogle Scholar
  10. Eysenbach, G. (2000). Consumer health informatics. BMJ, 320, 1713–1716.PubMedCrossRefGoogle Scholar
  11. Finkelstein, E. A., Trogdon, J. G., Cohen, J. W., & Dietz, W. (2009). Annual medical spending attributable to obesity: Payer-and service-specific estimates. Health Affairs (Project Hope)., 28, w822–w831.CrossRefGoogle Scholar
  12. Flick, U. (2009). An introduction to qualitative research. London: Sage.Google Scholar
  13. Fowler, J. H., & Christakis, N. A. (2008). Estimating peer effects on health in social networks: A response to Cohen-Cole and Fletcher; Trogdon, Nonnemaker, Pais. Journal of Health Economics., 27, 1400.PubMedCrossRefGoogle Scholar
  14. Gershenson, C. (2011). Epidemiology and social networks. Sociological Methods, 22(1), 199–200.Google Scholar
  15. Granovetter, M. S. (1973). The strength of weak ties. The American Journal of Sociology, 78, 1360–1380.CrossRefGoogle Scholar
  16. Hammond, R. A. (2010). Social influence and obesity. Current Opinion in Endocrinology, Diabetes, and Obesity, 17, 467–471.PubMedCrossRefGoogle Scholar
  17. Hopf, C. (2007). Qualitative interviews—ein Überblick. In: U. Flick, E. von Kardoff, & I. Steinke, I. (Eds.), Qualitative Forschung: Ein Handbuch (pp. 349–360). Reinbek bei Hamburg: Rowohlt Taschenbuch Verlag.Google Scholar
  18. Huffman, S. K. (2011). BMI changes in Russian adults: The role of lifestyles and spousal relationships. Agricultural and Applied Economics Association, 2011 Annual Meeting, Pittsburgh, Pennsylvania. Accessed September 22, 2011, Available at: http://ageconsearch.umn.edu/bitstream/102653/2/HuffmanAAEA2011.pdf.
  19. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons., 53, 59–68.CrossRefGoogle Scholar
  20. Kneidinger, B. (2010). Facebook und Co. Wiesbaden: VS Verlag für Sozialwissenschaften.CrossRefGoogle Scholar
  21. Lakon, C. M., Godette, D. C., & Hipp, J. R. (2008). Network-based approaches for measuring social capital. In I. Kawachi, S. V. Subramanian, & D. Kim (Eds.), Social capital and health (pp. 63–81). New York, NY: Springer.CrossRefGoogle Scholar
  22. Lewis, K., Kaufman, J., Gonzalez, M., Wimmer, A., & Christakis, N. A. (2008). Tastes, ties, and time: A new social network dataset using Facebook.com. Social Networks., 30, 330–342.CrossRefGoogle Scholar
  23. Ma, X., Chen, G., & Xiao, J. (2010). Analysis of an online health social network. In: IHI’ 10 (pp. 297–306), Arlington.Google Scholar
  24. Madan, A., Moturu, S. T., Lazer, D., & Pentland, A. S. (2010). Social sensing. In Wireless Health 2010 on—WH ’10 (p. 104). New York: ACM Press. doi: 10.1145/1921081.1921094.
  25. Mayring, P. (2000). Qualitative Inhaltsanalyse. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 1(2): Art. 20.Google Scholar
  26. McNeill, L. H., Kreuter, M. W., & Subramanian, S. V. (2006). Social environment and physical activity: A review of concepts and evidence. Social Science & Medicine (1982), 63, 1011–1022.CrossRefGoogle Scholar
  27. MedStar Physician Partners/MedStar Family. (2007). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. Retrieved September 6, 2011, from http://www.medstarfamilychoice.com/documents/guidelines/obesity.pdf.
  28. Moore, S. (2010). Social networks, social capital and obesity: A literature review. In L. Dubé, A. Bechara, A. Dagher, A. Drewnowski, J. Lebel, P. James, & R. Y. Yada (Eds.), Obesity prevention (pp. 673–685). San Diego: Academic Press.CrossRefGoogle Scholar
  29. Polke-Majewski, K. (2011). Cameron hat kein digitales Problem, sondern ein soziales. Retrieved from http://www.zeit.de/politik/ausland/2011-08/grossbritannien-krawalle-cameron-twitter-facebook-scial-media/komplettansicht
  30. Prochaska, J. O., Redding, C. A., & Evers, K. E. (2008). The transtheoretical model and stages of change. In K. Glanz, B. K. Rimer, & K. V. Viswanath (Eds.), Health behavior and health education: Theory, research, and practice (pp. 1–552). San Francisco, CA: Jossey-Bass.Google Scholar
  31. Rostila, M. (2011). A resource-based theory of social capital for health research: Can it help us bridge the individual and collective facets of the concept? Social Theory & Health., 9, 109–129.CrossRefGoogle Scholar
  32. Schone, M. (2011). London riots: Blame Twitter—or BlackBerry Messenger? Retrieved from http://abcnews.go.com/Blotter/london-riots-blame-twitter-blackberry-messenger/story?id=14255618
  33. von Rohr, M. (2011). Die Revolution, die keine war. Retrieved from http://www.spiegel.de/spiegel/0,1518,742430-3,00.html
  34. Wang, Y., Beydoun, M. A., Liang, L., Caballero, B., & Kumanyika, S. K. (2008). Will all Americans become overweight or obese? Estimating the progression and cost of the US obesity epidemic. Obesity., 16, 2323–2330.PubMedCrossRefGoogle Scholar
  35. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  36. Wefing, H. (2012). Wir! Sind! Wütend! Die Zeit, 3–5.Google Scholar
  37. WHO. (2000). Obesity: Preventing and managing the global epidemic. Report of a WHO Consultation. WHO technical report series 894. Geneva: WHO.Google Scholar
  38. WHO. (2011) World health statistics 2011. Available at http://www.who.int/whosis/whostat/2011/en/accessed dec 2012.
  39. Wickramasinghe, N., Bali, R., Goldberg, S., & Troshani, I. (Eds.). (2012). Pervasive health knowledge management. New York: Springer.Google Scholar
  40. Wilson, C., Boe, B., Sala, A., Puttaswamy, K. P. N., & Zhao, B. Y. (2009). User interactions in social networks and their implications. In: Proceedings of the fourth ACM European conference on Computer systems—EuroSys ’09 (p. 205). New York: ACM.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Carolin Durst
    • 1
  • Janine Viol
    • 1
  • Nilmini Wickramasinghe
    • 2
  1. 1.Institute of Information SystemsUniversity Erlangen-NürnbergNürnbergGermany
  2. 2.Epworth HealthCare & Department of BITL & HIRiRMIT UniversityMelbourneAustralia

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