May 06, 2015 02:11 PM EDT By Staff Reporter, UniversityHerald Reporter

New research suggests that persuading a lot of people to change their behavior is no popularity contest.

Researchers at Yale University found that that certain public health interventions work best when key "influencers" in a face-to-face social network are exposed to the program. However, those key influencers are not the most socially connected people in the network. That's what surprising to researchers.

They also found that these individuals can be identified through a survey method informed by network structure rather than costly and time-consuming social network mapping. The result is a cascade of behavior changes that boosts the efficiency and reach of certain programs.

"People are connected, and so their health is connected. Why not exploit this basic fact so as to improve health care delivery?" Nicholas A. Christakis, corresponding author of the study, said in a statement. "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."

For the study, researchers tracked the effectiveness of a water purification program and a multivitamin program in the Lempira region of Honduras. Recruiting nearly 6,000 residents from 32 villages to participate, the researchers used three methods to select initial targets for the programs: 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.

The goal was to see which targeting method resulted in the greatest uptake of the health interventions. They found that targeting nominated friends -- key influencers -- of random villagers sparked the highest level of adoption for the nutritional program. That 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," said A. Kim, the study's first author. "The question now is whether we can meaningfully use this knowledge to enhance the spread of useful information and practices in the real world."

The findings are detailed in The Lancet. 

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