Developing socio-spatial knowledge networks: a qualitative methodology forchronic disease prevention

Chronic disease is a significant and costly social problem. The burden is e ven more pronounced in communities with high rates of a particular chronic disease. Assessment of health belief systems and the local geographies of h ealth beliefs can assist community health planners to create cost-effective strategic intervention programs where populations are at high risk for chr onic diseases. In this paper, we elaborate the concept of socio-spatial kno wledge networks (SSKNs) and demonstrate that SSKNs can be useful in informi ng the design of health care prevention strategies. In our project, we demo nstrate how to identify key socio-spatial information for intervention stra tegies which will prevent or delay the onset of a particular chronic diseas e, Type 2 diabetes. Our qualitative framework allows us to determine which sites might be best characterized as socio-spatial knowledge network nodes for sharing diabetes information and which sites might be less suited to su ch exchange. Our strategy explores cross-cultural similarities, differences , and overlap in a multi-ethnic rural North Carolina context through simple techniques such as mapping social networks and sites in which people share their knowledge and beliefs about diabetes. This geographical analysis all ows us to examine exactly where health knowledge coincides with other socia l support, and where such resources may be improved in a particular communi ty. Knowing precisely what people in a community understand about a chronic disease and its treatment or prevention and knowing where people go to sha re that information helps to (1) identify strategic locations within a comm unity for future interventions and, (2) evaluate the effectiveness of exist ing interventions. The geographical approach presented here is one that can serve other communities and health practitioners who hope to improve chron ic disease management in diverse local environments. (C) 2001 Elsevier Scie nce Ltd. All rights reserved.