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Abstract
BackgroundPersonal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky.ObjectiveWe explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky.MethodsA total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio.ResultsOpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher’s perspective, and hindering practicality in the field.ConclusionsOpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations.
Highlights
Social science research has established the powerful role that our personal social networks play in our lives [1]
We explored the feasibility of using interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of ego network data in Appalachian Kentucky, which is a geographically and technologically isolated http://www.researchprotocols.org/2017/6/e124/
We aimed to demonstrate the benefits and challenges of using OpenEddi and a network visualization approach in this population and setting, thereby informing long-term goals of applying OpenEddi as a tool to facilitate the delivery of network-based health communication and social support interventions
Summary
Social science research has established the powerful role that our personal social networks play in our lives [1]. In order to understand this structure and measure the impact of networks on the lives of individuals and communities, we need to properly collect and analyze network data. An ego network may consist of the people one individual relies on for social support, or seeks health advice from. This approach is different from a whole network or sociometric approach, which analyzes an entire bounded network (eg, the network of romantic relationships in a specific high school, or a network of organizations in a coalition advocating for health policy). A video of Version 0.3, which is in development, can be viewed in Multimedia Appendix 2
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