Methods for Collection of Participant-aided Sociograms for the Study of Social, Sexual and Substance-using Networks Among Young Men Who Have Sex with Men. - Kuhns, Lisa M.; Birkett, M.; Mustanski, B.; Muth, S. Q.; Latkin, C.; Ortiz-Estes, I.; Garofalo, R. (Connections (02261766), 2015)
In this study, we adapted and tested a participant-aided sociogram approach for the study of the social, sexual, and substance use networks of young men who have sex with men (YMSM); a population of increasing and disproportionate risk of HIV infection. We used a combination of two interviewer-administered procedures: completion of a prenumbered list form to enumerate alters and to capture alter attributes; and a participant-aided sociogram to capture respondent report of interactions between alters on an erasable whiteboard. We followed the collection of alter interactions via the sociogram with a traditional matrix-based tie elicitation approach for a sub-sample of respondents for comparison purposes. Digital photographs of each network drawn on the whiteboard serve as the raw data for entry into a database in which group interactions are stored. Visual feedback of the network was created at the point of data entry, using NetDraw network visualization software for comparison to the network structure elicited via the sociogram. In a sample of 175 YMSM, we found this approach to be feasible and reliable, with high rates of participation among those eligible for the study and substantial agreement between the participant-aided sociogram in comparison to a traditional matrix-based approach. We believe that key strengths of this approach are the engagement and maintenance of participant attention and reduction of participant burden for alter tie elicitation. A key weakness is the challenge of entry of interview-based list form and sociogram data into the database. Our experience suggests that this approach to data collection is feasible and particularly appropriate for an adolescent and young adult population. This builds on and advances visualization-based approaches to social network data collection.