The gamification of risk: how health apps foster self-confidence and why this is not enough

Author(s):

• Maturo, Antonio
• Setiffi, Francesca

Abstract:

Weight loss apps enable users to quantify many aspects of food consumption, beginning with calories intake. Users of weight loss apps can also participate in online forums that act as digital self-help groups. These apps also include several features related to game playing or gamification such as avatars, points and virtual awards. Gamification has the aim of strengthening motivation to carry out a (boring) task. We downloaded the 20 most popular free weight loss apps in Google Play. We analysed app descriptions provided by developers, comments about the selected apps in online forums and user reviews. We focused on four of these apps, since they had some special functions. We found that users’ risk management was based on a mixed method that combined quantification and gamification, that is, rationality and emotions. Quantification, which includes self-tracking, data analysis and graphic layout, provides the ‘rational’ basis for dietary regimes, while gamification provides the emotional support needed to maintain motivation and continue with the diet. Our analysis provides support for the emotion–risk assemblage theory and the in-between strategy. Our analysis reinforces the importance of emotions in risk management. However, these dieting apps are based on a reductionist approach to obesity and weight loss, as obesity is framed as an individual problem, while weight loss is seen as dependent on individual motivation. Such framing tends to conceal the social determinant of health and the social and political causes of obesity.

Document:

https://doi.org/10.1080/13698575.2015.1136599

References:

• Austin, J. L. (1962). How to do things with words. London: Oxford University Press. [Crossref], [Google Scholar]
• Barker, K. K. (2010). The social construction of illness: Medicalization and contested illness. In C. Bird, P. Conrad, A. Freemont, & S. Timmermans (Eds.), Handbook of medical sociology (pp. 147–162). Nashville: Vanderbilt U.P. [Google Scholar]
• Bryman, A. (1984). The debate about qualitative and quantitative research. A question of methods or epistemology. The British Journal of Sociology, 35(1), 75–92. doi:10.2307/590553 [Crossref], [Web of Science ®], [Google Scholar]
• Choe, E. K., Lee, N. B., Bongshin, L., & Kientz, J. A. (2014). Understanding quantified-selfers’ practices in collecting and exploring personal data. Proceedings ACM Human Factors in Computing Systems, 1143–1152. doi:10.1145/2556288.2557372 [Google Scholar]
• Cipolla, C., & De Lillo, A. (Eds.). (2004). Il sociologo e le sirene. La sfida dei metodi qualitativi [The Sociologist and the Sirens. The Challenge of Qualitative Methods]. Milano: FrancoAngeli Editore. [Google Scholar]
• Conrad, P. (2007). The medicalization of society: On the transformation of human conditions into treatable disorders. Baltimore: Johns Hopkins University Press. [Google Scholar]
• Cummings, P., Goodman, D., Nonamaker, L., & Golson, M. (2013). Gaming to engage the healthcare consumer (White paper: ICF International, 1-7). Retrieved from http://www.icfi.com/insights/white-papers/2013/gaming-to-engage-healthcare-consumer [Google Scholar]
• Erikson, E. H. (1963). Childhood and Society. New York, NY: Norton. [Google Scholar]
• Espeland, W. N., & Stevens, M. L. (2008). A sociology of quantification. European Journal of Sociology, 49(3), 401–436. doi:10.1017/S0003975609000150 [Crossref], [Web of Science ®], [Google Scholar]
• European Commission. (2014). Green paper on mobile health (mHealth) (Paper No. 219). Retrieved from European Commission – Digital Agenda for Europe: http://ec.europa.eu/digital-agenda/en/news/green-paper-mobile-health-mhealth [Google Scholar]
• Flegal, K. M., Graubard, B. I., Williamson, D. F., & Gail, M. H. (2005). Excess deaths associated with underweight, overweight, and obesity. The Journal of the American Sociological Association, 93(15), 1861–1867. doi:10.1001/jama.293.15.1861 [Crossref], [Web of Science ®], [Google Scholar]
• Food and Drug Administration. (2015), Mobile medical applications. Guidance for Industry and Food and Drug Administration Staff, Document issued on February 9, 2015. Retrieved from http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM263366.pdf [Google Scholar]
• Foucault, M. (1977). Discipline and punish: The birth of the prison. New York, NY: Pantheon. [Crossref], [Google Scholar]
• Freud, S. (1920). On metaphyschology. London: Penguin Books. [Google Scholar]
• Furedi, F. (2004). Therapy culture. London: Routledge. [Google Scholar]
• Guseva, A. (2013). Consumerism in health care. Oxford: The Wiley-Blackwell Encyclopaedia of Health, Illness, Behavior, and Society, Wiley-Blackwell. [Google Scholar]
• Habermas, J. (1985). The theory of communicative action. Boston, MA: Beacon Press. [Google Scholar]
• Hadis, B. F. (2014). Risk, social protection and trust amidst cuts in welfare spending. Health, Risk & Society, 16(5), 459–480. doi:10.1080/13698575.2014.936832 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
• Hadler, N. M. (2004). The last well person: How to stay well despite the health-care system. Montreal: McGill-Queen’s University Press. [Google Scholar]
• Herring, S. C. (2010). Web content analysis: Expanding the paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International handbook of internet research (pp. 233–249). New York, NY: Springer. [Google Scholar]
• Joyce, K. A. (2008). Magnetic appeal. MRI and the Myth of transparency. Ithaca: Cornell University Press. [Google Scholar]
• Jutel, A., & Lupton, D. (2015). Digitizing diagnosis: A review of mobile applications in the diagnostic process. Diagnosis, 1–8. doi:10.1515/dx-2014-0068 [Crossref], [Web of Science ®], [Google Scholar]
• Kwan, S., & Trautner, M. N. (2011). Weighty concerns. Contexts, 10(2), 52–57. doi:10.1177/1536504211408907 [Crossref], [Google Scholar]
• Light, D., & Maturo, A. (2015). Good pharma. The public-health model of the Mario Negri Institute. New York, NY: Palgrave. [Google Scholar]
• Link, B., & Phelan, J. (2010). Social conditions as fundamental causes of health inequalities. In C. Bird, P. Conrad, A. Freemont, & S. Timmermans (Eds.), Handbook of medical sociology (pp. 3–17). Nashville: Vanderbilt University Press. [Google Scholar]
• Lupton, D. (1999). Risk. London: Routledge. [Google Scholar]
• Lupton, D. (2012). M-health and health promotion: The digital cyborg and surveillance society. Social Theory & Health, 10(3), 229–244. doi:10.1057/sth.2012.6 [Crossref], [Web of Science ®], [Google Scholar]
• Lupton, D. (2013a). Risk (2nd ed.). London: Routledge. [Crossref], [Google Scholar]
• Lupton, D. (2013b). The digitally engaged patient: Self-monitoring and self-care in the digital health era. Social Theory & Health, 11(3), 256–270. doi:10.1057/sth.2013.10 [Crossref], [Web of Science ®], [Google Scholar]
• Lupton, D. (2013c). Risk and emotion: Towards an alternative theoretical perspective. Health, Risk & Society, 15(8), 634–647. doi:10.1080/13698575.2013.848847 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
• Lupton, D. (2014a). The commodification of patient opinion: The digital patient experience economy in the age of big data. Sociology of Health & Illness, 36, 856–869. doi:10.1111/1467-9566.12109 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
• Lupton, D. (2014b). Quantified sex: A critical analysis of sexual and reproductive self-tracking apps. Culture, Health & Sexuality, 17(4), 440–453. doi:10.1080/13691058.2014.920528 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
• Lupton, D. (2014c). Apps as artefacts: Towards a critical perspective on mobile health and medical apps. Societies, 4(4), 606–622. doi:10.3390/soc4040606 [Crossref], [Google Scholar]
• Lupton, D. (2014d). Risk. The Wiley-Blackwell Encyclopaedia of Health, Illness, Behavior, and Society. Oxford: Wiley-Blackwell. [Crossref], [Google Scholar]
• Lupton, D. (2015). Digital sociology. London: Routledge. [Google Scholar]
• Lupton, D., & Jutel, A. (2015). ‘It’s like having a physician in your pocket!’ A critical analysis of selfdiagnosis smartphone apps. Social Science and Medicine, 133, 128–135. doi:10.1016/j.socscimed.2015.04.004 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
• Lupton, D., & Thomas, G. M. (2015). Playing pregnancy: The ludification and gamification of expectant motherhood in smartphone apps. M/C Journal, 18(5), 1–8. Retrieved from http://journal.media-culture.org.au/index.php/mcjournal/article/viewArticle/1012 [Google Scholar]
• Mackenzie, A. (2013). From validating to verifying: Public appeals in synthetic biology. Science as Culture, 22(4), 476–496. doi:10.1080/14636778.2013.764067 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]
• Mackenzie, D. (2014, June). A Sociology of Algorithms: High-Frequency Trading and the Shaping of Markets. Working paper. Retrieved from http://www.sps.ed.ac.uk/__data/assets/pdf_file/0004/156298/Algorithms25.pdf [Google Scholar]
• Maturo, A. (2004). Network governance as a response to risk society’ dilemmas: A proposal from sociology of health. Topoi – International Review of Philosophy, 23(2), 195–202. doi:10.1023/B:TOPO.0000046066.21486.82 [Crossref], [Web of Science ®], [Google Scholar]
• Maturo, A. (2012). Social justice and human enhancement in today’s bionic society. Salute e Società, XI(2), 15–28. Retrieved from http://www.francoangeli.it/riviste/Scheda_rivista.aspx?IDArticolo=47776 [Google Scholar]
• Maturo, A. (2014). Fatism, self-monitoring and the pursuit of healthiness in the time of technological solutionsim. Italian Sociological Review, 4(2), 157–171. Retrieved from http://www.italiansociologicalreview.org/attachments/article/173/3%20Fatism%20SelfMonitoring%20and%20the%20Pursuit%20of%20Healthiness%20in%20the%20Time%20of%20Technological%20Solutionism_Maturo.pdf [Google Scholar]
• McGonigal, J. (2011). Reality is broken. How games are making us better and how they can change the world. New York, NY: The Penguin Press. [Google Scholar]
• Mead, G. H. (1934). Mind, self and society. Chicago: University of Chicago Press. [Google Scholar]
• Morford, Z. H., Witts, B. N., & Killingsworth, M. P. (2014). Gamification: The intersection between behavior analysis and game design technologies. The Behavior Analyst, 37, 25–40. doi:10.1007/s40614-014-0006-1 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
• Morozov, E. (2013). To save everything, click here: Technology, solutionism, and the urge to fix problems that don’t exist. London: Penguin. [Google Scholar]
• Nichols, S. (2015). A RECIPE for meaningful gamification. In T. Reiners & L. C. Wood (Eds.), Gamification in education and business (pp. 1-20)). Switzerland: Springer. [Google Scholar]
• Olsen, W., & Morgan, J. (2005). A critical epistemology of analytical statistics: Addressing the sceptical realist. Journal for the Theory of Social Behaviour, 35, 255–284. doi:10.1111/j.1468-5914.2005.00279.x [Crossref], [Web of Science ®], [Google Scholar]
• Pickett, K., & Wilkinson, R. (2011). The spirit level: Why greater equality makes societies stronger. New York, NY: Bloomsbury. [Google Scholar]
• Prochaska, J. O., & Velicer, W. F. (1997). The transtheoretical model of health behavior change. American Journal of Health Promotion, 12(1), 38–48. doi:10.4278/0890-1171-12.1.38 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
• Rabinow, P. (1996). Anthropology of Reason. Princeton: Princeton U.P. [Google Scholar]
• Ruckenstein, M. (2014). Visualized and interacted life: Personal analytics and engagements with data doubles. Societies, 4(1), 68–84. doi:10.3390/soc4010068 [Crossref], [Google Scholar]
• Secondulfo, D. (2014). Born to buy. The socialization of young consumers. Italian Journal of Sociology of Education, 6(3), 26–40. Retrieved from http://www.ijse.eu/wp-content/uploads/2014/10/2014_3_3.pdf [Google Scholar]
• Setiffi, F. (2014). Becoming consumers: Socialization into the world of goods. Italian Journal of Sociology of Education, 6(3), 6–25. Retrieved from http://www.ijse.eu/wp-content/uploads/2014/10/2014_3_2.pdf [Google Scholar]
• Suchman, L. (2011). Practice and its overflows: Reflections on order and mess, Tecnoscienza. Italian Journal of Science and Technology, 2(1), 21–30. [Google Scholar]
• Sullivan, D. A. (2010). A social change model of the obesity epidemic. In A. Mukherjea (Ed.), Understanding emerging epidemics: Social and political approaches (pp. 315–342). London: Emerald. [Crossref], [Google Scholar]
• Sztompka, P. (2000). Trust. A sociological theory. Cambridge: Cambridge University Press. [Google Scholar]
• The Royal Society. (1992), Risk Analysis, Perception and Management. Retrieved from The Royal Society: https://royalsociety.org/topics-policy/publications/1992/risk/ [Google Scholar]
• Van Loon, E., Oudshoorn, N., & Bal, R. (2014). Studying design and use of healthcare technologies in interaction: The social learning perspective in a dutch quality improvement collaborative program. Health, 6, 1903–1918. doi:10.4236/health.2014.615223 [Crossref], [Google Scholar]
• Van Manen, M. (2010). The pedagogy of Momus technologies: Facebook, privacy and online intimacy. Qualitative Health Research, 20(8), 1023–1032. doi:10.1177/1049732310364990 [Crossref], [PubMed], [Web of Science ®], [Google Scholar]
• Weber, M. (1992). The protestant ethic and the spirit of capitalism. New York, NY: Routledge. [Google Scholar]
• Whitson, J. R. (2013). Gaming the quantified self. Surveillance & Society, 11(1/2), 163–172. Retrieved from http://library.queensu.ca/ojs/index.php/surveillance-and-society/article/view/gaming/0 [Crossref], [Google Scholar]
• Wolf, G. (2010, April 28). The data-driven life. The New York Times Magazine. Retrieved from http://www.nytimes.com/2010/05/02/magazine/02self-measurement-t.html?_r=0 [Google Scholar]
• Zinn, J. O. (2008). Heading into the unknown: Everyday strategies for managing risk and uncertainty. Health, Risk & Society, 10(5), 439–450. doi:10.1080/13698570802380891 [Taylor & Francis Online], [Web of Science ®], [Google Scholar]