Better Health Through Social Networking

A team of economic sociologists from the Massachusetts Institute of Technology recently published a paper showing that dense social networks benefit users’ health. It means that people are more likely to acquire new health practices while having close contact with people they already know well.
These figures show experimentally manipulated on-line social networks. The first community (left) has a clustered network structure, while the second one is a more
These figures show experimentally manipulated on-line social networks. The first community (left) has a clustered network structure, while the second one is a more “random” casual contact network. Node colors indicate people who adopted a behavior (blue) and those who did not (white), with lighted links showing the active pathways of communication. The clustered networks spread the behavior to more people than the casual contact networks. (Credit: Damon Centola)

Prevalent opinions among social scientists are that social networks featuring many distant connections, or “long ties” — where individuals know a lot of people, but not well — produce large-scale changes most quickly. However, a new study, conducted by Damon Centola from the Massachusetts Institute of Technology (MIT) School of Management, shows a different conclusion.

The paper, published in Science, shows that people are more likely to acquire new health practices while living in networks with dense clusters of connections. Generally speaking, researchers tend to regard dense clusters of connections to be redundant. It is especially true when treating networks as abstract forms to store information. Networks featuring dense clusters are considered less efficient than networks with a greater proportion of long ties.

The surprising result that Centola found relies on people’s difficulty to change their habits; they require the extra reinforcement that comes from those redundancies. In other words, people need to hear a new idea multiple times before making a change. “For about 35 years, wisdom in the social sciences has been that the more long ties there are in a network, the faster a thing will spread,” says Centola. “It’s startling to see that this is not always the case.”

The experiments that tested the effect of each form of a social network varied. Centola used an Internet-based questionnaire, sent to a health community he developed. The 1,528 people in the study had anonymous online profiles and a series of health interests; they were matched with other participants sharing the same interests — “health buddies,” as they are called in the paper. Participants received e-mail updates notifying them about the activities of their health buddies.

The design Centola used consists of two distinct kinds of networks, to which people were divided according to their network formation. One had people with long ties, and the second had people with larger clusters of people. Six separate trials were ran over a period of a few weeks to see which groups were more likely to register for an online health forum website offering ratings of health resources.

Overall, 54 percent of the people in clustered networks registered for the health forum, compared to 38 percent in the networks oriented around longer ties. It shows that the rate of adoption in the clustered networks was also four times as fast. Moreover, people were more likely to participate regularly in the health forum if they had more health buddies who registered for it. Only 15 percent of forum participants with one friend in the forum returned to it, but more than 30 percent of subjects with two friends returned to it, and over 40 percent with three friends in the forum made repeat visits.

These results relate mainly to adoption habits. “Social reinforcement from multiple health buddies made participants much more willing to adopt the behavior,” Centola said. In his paper, he claims that this effect on individuals “translates into a system-level phenomenon whereby large-scale diffusion can reach more people, and spread more quickly, in clustered networks than in random networks.”

Centola finds practical uses for his results – for instance, health officials could learn from it. A simple contagion, in network theory, can spread with a single contact; a complex contagion requires multiple exposures for transmission. A disease, Centola suggests, can spread as a simple contagion, but behavior that can prevent the disease — such as going to a clinic for a vaccination — might spread only as a complex contagion, thus needing to be spurred by reinforcement from multiple neighbors in a social network.

“If there is a significant difference between simple and complex contagions, that actually matters for our policy interventions,” says Centola. The public promotion of screenings and other forms of disease prevention might best be aimed at communities and groups that act as closely clustered networks.

David Lazer, from Harvard’s Kennedy School of Government, was not involved in the study and yet he is full of acclaim for Centola and his team. “It’s interesting work because it shows that for the diffusion of certain kinds of things, you really need reinforcing,” he said. “You need wide bridges to transmit complex information like health data, and that is different from the traditional picture of how things spread in a network.”

While the study received many positive reviews, it has its drawbacks. Centola mentions that joining an online health forum has little cost in time or money, unlike many other kinds of health behavior, from vaccinations to changing one’s diet or adopting an exercise routine. “Getting a colonoscopy is hard; just hearing about it is probably not going to convince you to do it,” he said. The rate of adoption would likely vary widely for many forms of health behavior, and be relatively low when notable costs are involved.

Because of such costs, Centola believes there is a real need for social reinforcement, such as having multiple friends and relatives who get colonoscopies. “These redundant signals are necessary to make people adopt the behavior,” he said.

Future fieldwork should help determine how resistant people are to changing particular forms of health behavior. “One thing this study begs, in a good way, is more research in natural settings,” says Lazer. To see the effectiveness of public-health measures, he suggests, “You might try to target two neighborhoods in different ways, and then assess which is more effective.” When Centola is asked about future research, he says that further work should be done to evaluate the effects of online social networks on behavior. “There is a natural implication in terms of what this means for designing online communities,” he concludes.

For more information about the effects social networking has on health, see the official press release.

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