Harvesting the fruits of "Connected" for healthcare

Tuesday, February 9, 2010  | Joseph Ternullo, JD, MPH


About the Author:  Joseph Ternullo, JD, MPH is the Associate Director of the Center for Connected Health.


At last year’s Connected Health Symposium, Nicholas Christakis, MD, PhD, MPH, held forth brilliantly, and with spirit and wit, on the health influences of social networks, explaining why my friends, their friends, and their friends’ friends are to blame for my weight gain or deserve credit for my weight loss.

Dr. Christakis and James H. Fowler, PhD, his co-author, got started by doing an ingenious analysis of a population sample drawn from the Framingham Heart Study. In summarizing Connected, the extraordinary new book that reports on what they found, a New York Times writer notes, “Good behaviors -- like quitting smoking or staying slender or being happy -- pass from friend to friend almost as if they were contagious viruses. The Framingham participants, the data suggested, influenced one another’s behavior just by socializing. And the same was true for bad behaviors -- clusters of friends appeared to ‘infect’ one another with obesity, unhappiness and smoking.  Staying healthy isn’t just a matter of genes and diet, it seems. Good health is also a product, in part, of sheer proximity to other healthy people.”

Speaking all over the world on this fascinating phenomenon, Christakis and Fowler are seeking new data sets and collaborators for the next phase of their work.

Here are the seeds of a few interesting research questions (please, chip in with thoughts and suggestions of your own):

  1. Will health authorities have to "map" each naturally-occuring social network before they can hope to influence it?  If yes, can such mapping be done in a scalable way?  Should health authorities distribute health and wellness messages and information through self-constructed social networks like Facebook?

  2. Do the super-connected people exercise disproportionate influence on the formation of a network's norms and behaviors?  If their influence varies according to demographics, norms, or health-related condition, how should health promoters adjust outreach and communication strategies?

  3. Do differences exist depending on whether a network is organic (arising "naturally," perhaps due to kinship, geography, employement, religion, etc.) as opposed to self-constructed (created deliberately by network members themselves) or externally constructed (created by a third party for any number of reasons...health promotion, commerce, etc.)?

  4. What do social network analysts and behavioral economists have to say to one other?  These two fascinating research communities start from different places (group behavior vs. individual behavior), highlight different forces (bad behavior caused by group contagion vs. bad behavior "hard-wired" into individuals) and propose different solutions (map the network and find the super-connectors vs. spot the biases in personal decision-making and nudge the individual back on track).

Differences aside, both social network analysts and behavioral economists pose brilliant challenges to the rational actor model of mainstream economists. Both do their work in the hope of countering the unhealthy and self-wounding choices that people make.

What insights and tips do the two camps have for one another? Their admirers at the Center for Connected Health would like to know.

 

Member Comments


Indeed, very interesting research questions. One thing I would like to add is that, besides social network analysts and behavioral economists, computer scientists also work towards the goal of identifying emerging communities. As an example the references below, address the issues of online community identification and community factorization respectively:
[Wan08] Wang, X. and A. Kabán, A Dynamic Bibliometric Model for Identifying Online Communities, Data Mining and Knowledge Discovery, vol. 16, pp. 67-107, 2008.
[Chi07] Chi, Y. et al., Structural and Temporal Analysis of the Blogosphere Through Community Factorization, Proceedings of the KDD Conference, pp. 163-172, 2007.

Theophano Mitsa

Data Mining-Analytics Consultant

 

Posted by: Theophano Mitsa
2/16/2010

 

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