Second , we show that network composition , individual network central ity , and network structure are associated with important health behaviors and health and development outcomes in different context s across multiple levels of analysis and across distinct network types .
Lastly , we highlight the opportunities for health research ers and practitioners in LMICs to 1 ) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure , 2 ) measure the spread of outcomes or intervention externalities , and 3 ) enhance the effectiveness and efficiency of aid based on knowledge of social structure .
In low- and middle-income countries ( LMICs ) , naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various re sources .
Cooperative behavior cascades in human social networks
Theoretical models suggest that social networks influence the evolution of cooperation , but to date there have been few experimental studies . Observational data suggest that a wide variety of behaviors may spread in human social networks , but subjects in such studies can choose to befriend people with similar behaviors , posing difficulty for causal inference . Here , we exploit a seminal set of laboratory experiments that originally showed that voluntary costly punishment can help sustain cooperation . In these experiments , subjects were r and omly assigned to a sequence of different groups to play a series of single-shot public goods games with strangers ; this feature allowed us to draw networks of interactions to explore how cooperative and uncooperative behaviors spread from person to person to person . We show that , in both an ordinary public goods game and in a public goods game with punishment , focal individuals are influenced by fellow group members ’ contribution behavior in future interactions with other individuals who were not a party to the initial interaction . Furthermore , this influence persists for multiple periods and spreads up to three degrees of separation ( from person to person to person to person ) . The results suggest that each additional contribution a subject makes to the public good in the first period is tripled over the course of the experiment by other subjects who are directly or indirectly influenced to contribute more as a consequence . These results show experimentally that cooperative behavior cascades in human social networks
Second , we show that network composition , individual network central ity , and network structure are associated with important health behaviors and health and development outcomes in different context s across multiple levels of analysis and across distinct network types .
Lastly , we highlight the opportunities for health research ers and practitioners in LMICs to 1 ) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure , 2 ) measure the spread of outcomes or intervention externalities , and 3 ) enhance the effectiveness and efficiency of aid based on knowledge of social structure .
In low- and middle-income countries ( LMICs ) , naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various re sources .