Social Networks Help To Improve Public Health When They're Face-To-Face

New findings published in The Lancet reveal how face-to-face social networks work best as certain interventions when it comes to influencing people.

They also found that certain individuals can be identified via a survey method informed by network structure rather than costly and time-consuming social network mapping that may result in a cascade of behavior changes that help boost the ability of certain programs.

"People are connected, and so their health is connected. Why not exploit this basic fact so as to improve healthcare delivery?" said corresponding study author Nicholas A. Christakis, in a news release. "We humans construct elaborate social networks in which we live out our lives. If scientists can understand the structure and function of these social networks, we can take advantage of this understanding to turbo-charge behavioral interventions so that whole groups of people change their behavior for the better, and not just isolated individuals."

During the study, researchers tracked the effectiveness of a water purification program and multivitamin program in the Lempira region of Honduras. They recruited 5,773 residents from 32 villages to participate with the help of three methods for initial programs involved: randomly selected villagers, villagers with the most social ties, and one nominated friend for each of a set of random villagers. Targets were given vouchers to distribute to their social contacts, who could redeem them for the health products and for additional vouchers.

Researchers found that targeting methods that nominated friends--key influences--of random villagers sparked the highest level of adoption for the nutritional program; this method increased adoption of the program by 12.2 percent, compared with random distribution. Meanwhile, targeting the most highly connected people produced no increase in adoption of either public health program.

"Over the past decade, we've learned a great deal about how network structure affects the diffusion of information and behaviors," concluded lead study author David A. Kim. "The question now is whether we can meaningfully use this knowledge to enhance the spread of useful information and practices in the real world."

Yet as to why most socially connected members of a network weren''t the key influencers, the researchers said they believed it may have something to do with popular individuals being overly clustered amongst themselves, according to an accompaning editorial.

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