It’s fairly well established that behavioral change is one of the toughest things we can hope to achieve, especially on a large scale.  I’ve written previously on the important role social networks can play in such a change, and a recent study serves to further emphasize this point.

The researchers discovered that public health interventions often work best when influential people within a social network pass on the message.  Whilst this may sound intuitive, the study found that these influential nodes aren’t always the most connected nodes in the network.

The authors contend that they can identify such influencers through a survey method that’s informed by the structure of the network itself rather than more traditional forms of network mapping.

“People are connected, and so their health is connected. Why not exploit this basic fact so as to improve health care delivery?” the authors say.

“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,” they continue.

The role of social networks in change

The study measured the effectiveness of a water purification and multivitamin program in Honduras.  The campaign, which featured over 5,700 residents spread across 32 villages.  The residents were chosen according to three criteria:

1. a random sample of villagers
2. those who were most connected
3. one nominated friend from the random sample

The residents were given vouchers that they were asked to distribute among their network, with the vouchers redeemable for various health products.

The aim was to see which group achieved the most successful uptake of the intervention.

The results suggest that targeting key influencers within the random sample of villagers achieved the best uptake, with a 12.2 percent gain on the other two methods.

It’s particularly surprising that targeting the most connected individual seemed to have no impact, as this is the traditional approach used when trying to spread adoption.

“Over the past decade, we’ve learned a great deal about how network structure affects the diffusion of information and behaviors,” the authors say. “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 implications for behavior change

The authors contend that their findings have notable implications for both health related programs but also wider behavioral change.  The approach of targeting friends of randomly chosen individuals is generally a lot easier and cheaper than more traditional methods, and the study suggests it is significantly more effective also.

The authors suggest that the traditional approach of targeting highly connected people may fail because of the high levels of interconnectivity between such people, resulting in them clustering tightly together.

“Because highly connected people tend to be friends with one another, targeting only the best-connected people risks creating an ‘echo chamber’ of influence that fails to reach other parts of the network,” they conclude.