Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras

Abstract

IntroductionDespite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change.Methods and analysisWe will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions.Ethics and disseminationThe Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a ‘toolkit’ for practitioners to use in network-based intervention efforts, including public release of our network mapping software.Trial registration numberNCT02694679; Pre-results.

Social normative and social network factors associated with adolescent pregnancy: a cross-sectional study of 176 villages in rural Honduras

“…Our study uses full population census data from the western municipalities of the largely rural Copán department of Honduras to analyse the social network determinants of adolescent childbirth at the individual level. Data were collected as part of a randomised controlled trial of social network targeting of a maternal and neonatal health intervention in a study area comprised of 176 villages located in the municipalities of Copán Ruinas, Santa Rita, Cabañas, and San Jerónimo [33,39]. The area was chosen because the villages were geographically diverse, the population experiences high vulnerability to maternal and neonatal health complications, and the location was suitable for data collection.…”

“…The area was chosen because the villages were geographically diverse, the population experiences high vulnerability to maternal and neonatal health complications, and the location was suitable for data collection. A full description of the study design and data collection methods is published elsewhere [39]. This part of Honduras also has a traditionally high rate of adolescent fertility [4], making it an ideal study setting for understanding the social dynamics around adolescent childbirth.…”

Using social networks to understand and overcome implementation barriers in the global HIV response

“…pattern social networks -we should expect social networks to evolve under the pressure of new ideas spreading across them (114).…”

“…Such algorithms can then be tested in randomized studies to determine whether such non-network-identified seeds are more effective than randomly-or network-selected seeds at reducing HIV risk within the network. More evaluations of SNIs are also required, although such studies can be prohibitively expensive as they require the collection of sociocentric social network data from many independent networks that can then be randomized to different SNIs (115,116).…”

Reference guide for data collection: Qualitative social network interviews

“…Source: Shakya et al 2017a. reported by a selected respondent (ego) with individuals (alters) they identify in response to the name generator questions. The ties between any ego and alter in the survey are independent of the ties enumerated by other egos, and there is not necessarily any connection between one person's ties and another's.…”