Funded by the Bill and Melinda Gates Foundation
Award number OPP1135005
Update: The data for the project described here is being collected in Kenya instead of Ethiopia. The Principal Investigator for this project, Dr. Wolfgang Munar, has moved from Washington University to George Washington University.
While barriers to family planning (FP) due to the lack of access to and insufficient knowledge about contraception have markedly dropped, developing countries still face significant challenges in promoting the use of modern-day contraceptives (MC) as a result of perceived health risks (28%) and opposition by partner or someone close (24%).
Unfortunately, policy programs and interventions aimed at reducing demand-side barriers to the adoption and sustained use of MC have traditionally focused on informing women about the safety of their use, but have failed to address other barriers likes the ones mentioned above. This may be in part accounted by the fact that classic policy tools are not well-equipped to generate knowledge about how behaviors come to be, or how effects of social and collective norms play on individual, group, and community-level behavioral trends.
Social Networks Analysis (SNA) stands as a robust and novel alternative to address these short-comings. Not only can it support the study of the diffusion of cultural dynamics through the imitation of influential “others”, it can also provide more efficient ways of sampling the targeted population in a more timely and cost-effective manner.
Therefore, this program seeks to harness the potential of SNA to contribute to the promotion of contraceptives in Kenya by tackling the following questions:
(1) Can a social networks-based methodology result in valid measurements of the adoption of modern contraceptives (MC) in rural areas in Kenya?
(2) Does this methodology provide a rigorous and superior understanding about demand-side drivers of MC adoption for the purposes of measuring program performance and improving policy- and program design?
(3) Under what conditions will the methodology be suitable to be included in the toolkit of methods that are routinely used for family planning policy and program design as well as for measuring implementation progress and program performance?
(4) What are the technical and economic drivers that will determine the feasibility of scaling-up and replicating this methodology across Kenya as well as in other geographies.