OBJECTIVE: The objective of this study was to describe the network structures of agencies and individuals engaged in HIV prevention in a North Carolina county. STUDY DESIGN: The authors conducted a cross-sectional study of interconnected agencies and individuals identified through snowball sampling. Participants were interviewed face to face with a structured questionnaire about interactions with others in the network. Network characteristics such as density and centralization were computed with UCINET software. RESULTS: The network of 11 agencies had an information exchange density of 14%. Exchanges of clients and funds were even more rare. The network of 17 individuals influential in HIV prevention was better connected with a density of 42%. CONCLUSIONS: The HIV prevention agencies in the county were not functioning as a network and thus were not benefiting the community to their full potential. Any connectedness between the agencies may be attributable to the better connections between influential individuals, several of whom worked for the agencies in the agency network.
OBJECTIVE: The objective of this study was to describe the network structures of agencies and individuals engaged in HIV prevention in a North Carolina county. STUDY DESIGN: The authors conducted a cross-sectional study of interconnected agencies and individuals identified through snowball sampling. Participants were interviewed face to face with a structured questionnaire about interactions with others in the network. Network characteristics such as density and centralization were computed with UCINET software. RESULTS: The network of 11 agencies had an information exchange density of 14%. Exchanges of clients and funds were even more rare. The network of 17 individuals influential in HIV prevention was better connected with a density of 42%. CONCLUSIONS: The HIV prevention agencies in the county were not functioning as a network and thus were not benefiting the community to their full potential. Any connectedness between the agencies may be attributable to the better connections between influential individuals, several of whom worked for the agencies in the agency network.
Authors: Kayo Fujimoto; Peng Wang; Lisa M Kuhns; Michael W Ross; Mark L Williams; Robert Garofalo; Alden S Klovdahl; Edward O Laumann; John A Schneider Journal: Med Care Date: 2017-02 Impact factor: 2.983