Testing theoretical network classes and HIV-related correlates with latent class analysis

Abstract

Scientists designing network-based interventions intending to improve the adoption or maintenance of healthy behaviors are well-advised to classify potential adopters into network roles, such as opinion leaders, brokers, members, and isolates, and to work closely with existing opinion leaders. In past studies focusing on HIV, opinion-leader interventions have had mixed results. This may be addressed, in part, by empirically validating these network roles. To this end, we used latent class analysis to test whether people's social connections fall into mutually exclusive and exhaustive subgroups of social capital that represent theorized network roles well with a dataset collected in Nyangana, Namibia (n = 400). A four-class model best fits the dataset, but the categories identified do not clearly represent the theorized roles. Rather, this study revealed the following four network classes: single-group members (59%), connectors (24%), single-group loyalists (15%), and selective connectors (2%). The implications of their findings for opinion-leader interventions focused on HIV are discussed.

Keywords:

• opinion leader
• intervention
• latent class
• social networks
• social distancing

Acknowledgements

Our thanks to Erna Keulder, Research Facilitation Services (Windhoek, Namibia), and JHUCCP/Namibia. This project was supported by Award Number P50-DA010075 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health. The data were collected with primary support from the United States Agency for International Development under the Health Communication Partnership project (GPH-A-02-00008-00) based at Johns Hopkins/Bloomberg School of Public Health/Center for Communication Programs. Most importantly, we are grateful to the leaders and citizens of Nyangana, for sharing their information with us.