Partners: Queen Margaret University (UK), HERD International (Nepal), American University of Beirut (Lebanon), and Institute for Development (Sierra Leone)
Social networks play a constitutive role in how health care and systems are organised, how services or interventions are planned and delivered, and how and by what metrics outcomes are evaluated. Despite social network analysis having been long identified as a promising methodology for health policy and systems research and compatible with complex systems frameworks, network analytic approaches in the study of health system resilience remain somewhat nascent (eg Blanchet et al. (2017); Sheaff et al. (2010) [open new tabs]).
To date most studies using social network analysis and relating to resilience have been under-theorised and largely confined to singular case studies rather than the health system. Some studies exemplify how social network analysis can be used to identify attributes of those most consistently occupying structural positions of power, influence and brokerage, thereby enabling the identification of those actors that could be involved in efforts to strengthen health systems and achieve resilience, however, they frequently focus on singular case studies and do not explicitly adopt a resilience lens. One outstanding example of how social network analysis could be used is that of Bertoni et al (2022) [opens new tab], who apply social network analysis to the study of actors in one intensive care unit (ICU) in relation to specific resilience-related capabilities (monitoring, anticipating, responding and learning). By doing this, the authors unpack how ICUs remain resilient and able to deliver critical care services.
As noted above, the potential for social network analysis to be used for resilience research is recognised to be high and the literature widely acknowledges this, eg Wilkin et al (2019) [opens new tab] point to the emerging use of social network analysis for community resilience and disaster risk-reduction. They note that resilience enhancing strategies frequently used as part of disaster risk reduction routinely fail at implementation stage precisely due to lack of consideration of the complexity of social networks and their potential to inhibit action.
This social network analysis research focuses on Lebanon, Nepal and Sierra Leone. It seeks to address gaps in the literature by contributing a cross-country case study that uses social network analysis to study a theory-informed resilience research question (on how network inclusiveness can inhibit or foster system resilience). The focus is on collaborating with local teams to embed network analytic approaches into their own planning, implementation, and evaluation work, as well as creating opportunities for cross-country learning and knowledge exchange. The project also seeks to generate learning materials (eg written and video guidance) that can be used by others active in the health policy and research field, or resilience research field, to undertake further social network analysis studies.
The objectives of the research are to:
The research comprises two phases, each bookended by a knowledge exchange component:
Phase 1:
Analysis of already-collected data from each of the countries (from learning sites or other empirical research conducted as part of ReBUILD for Resilience) using a network perspective. The focus of this analysis is on the social networks present in the learning sites/ supporting the in-country research, the networks’ inclusiveness (as relates specifically to equity considerations) and influence in sustaining health system resilience. As part of the phase, we will also generate guidance and training materials around the analytic process.
Phase 2:
Drawing upon the guidance material generated in phase 1, the group will collaboratively design and implement social network analysis research based on specific sub-elements of the resilience framework. Country teams will identify how they wish to further apply social network analysis in each setting, design and carry out a small research project (as embedded in the learning sites).
There’s more on the ReBUILD learning sites here: