Racial and Ethnic Differences in Mobile App Use for Meeting Sexual Partners Among Young Men Who Have Sex With Men and Young Transgender Women: Cross-Sectional Study.

Background: Young men who have sex with men and young transgender women (YMSM-YTW) use online spaces to meet sexual partners with increasing regularity, and research shows that experiences of racism online mimics the real world. Objective: We analyzed differences by race and ethnicity in web-based and mobile apps used to meet sexual partners as reported by Chicago-based YMSM-YTW in 2016-2017. Methods: A racially and ethnically diverse sample of 643 YMSM-YTW aged 16-29 years were asked to name websites or mobile apps used to seek a sexual partner in the prior 6 months, as well as provide information about sexual partnerships from the same period. We used logistic regression to assess the adjusted association of race and ethnicity with (1) use of any website or mobile apps to find a sexual partner, (2) use of a "social network" to find a sexual partner compared to websites or mobile apps predominantly used for dating or hookups, (3) use of specific websites or mobile apps, and (4) reporting successfully meeting a sexual partner online among website or mobile app users. Results: While most YMSM-YTW (454/643, 70.6%) used websites or mobile apps to find sexual partners, we found that Black non-Hispanic YMSM-YTW were significantly less likely to report doing so (comparing White non-Hispanic to Black non-Hispanic: adjusted odds ratio [aOR] 1.74, 95% CI 1.10-2.76). Black non-Hispanic YMSM-YTW were more likely to have used a social network site to find a sexual partner (comparing White non-Hispanic to Black non-Hispanic: aOR 0.20, 95% CI 0.11-0.37), though this was only reported by one-third (149/454, 32.8%) of all app-using participants. Individual apps used varied by race and ethnicity, with Grindr, Tinder, and Scruff being more common among White non-Hispanic YMSM-YTW (93/123, 75.6%; 72/123, 58.5%; and 30/123, 24.4%, respectively) than among Black non-Hispanic YMSM-YTW (65/178, 36.5%; 25/178, 14%; and 4/178, 2.2%, respectively) and Jack'd and Facebook being more common among Black non-Hispanic YMSM-YTW (105/178, 59% and 64/178, 36%, respectively) than among White non-Hispanic YMSM-YTW (6/123, 4.9% and 8/123, 6.5%, respectively). Finally, we found that while half (230/454, 50.7%) of YMSM-YTW app users reported successfully meeting a new sexual partner on an app, Black non-Hispanic YMSM-YTW app users were less likely to have done so than White non-Hispanic app users (comparing White non-Hispanic to Black non-Hispanic: aOR 2.46, 95% CI 1.50-4.05). Conclusions: We found that Black non-Hispanic YMSM-YTW engaged with websites or mobile apps and found sexual partners systematically differently than White non-Hispanic YMSM-YTW. Our findings give a deeper understanding of how racial and ethnic sexual mixing patterns arise and have implications for the spread of sexually transmitted infections among Chicago's YMSM-YTW.

Network canvas: an open-source tool for capturing social and contact network data.

MOTIVATION: Social influence and contact networks are extremely important for understanding health behaviour and the spread of disease. Yet, most traditional software tools are not optimized to capture these data, making measurement of personal networks challenging. Our team developed Network Canvas to provide an end-to-end workflow with intuitive interfaces to enable researchers to design and conduct network interviews. IMPLEMENTATION: Network Canvas consists of three applications (Architect, Interviewer and Server). All applications are written in JavaScript and run on Windows, macOS and Linux; Interviewer also runs on Android and iOS. GENERAL FEATURES: Network Canvas substantially reduces the complexity and technical knowledge required to collect network data via three point-and-click applications. The tool has wide applicability for measuring contact and social influence networks in epidemiology. AVAILABILITY: Network Canvas is open source and freely available [networkcanvas.com] under the GNU General Public License 3.

Assessing the stability of egocentric networks over time using the digital participant-aided sociogram tool Network Canvas.

This paper examines the stability of egocentric networks as reported over time using a novel touchscreen-based participant-aided sociogram. Past work has noted the instability of nominated network alters, with a large proportion leaving and reappearing between interview observations. To explain this instability of networks over time, researchers often look to structural embeddedness, namely the notion that alters are connected to other alters within egocentric networks. Recent research has also asked whether the interview situation itself may play a role in conditioning respondents to what might be the appropriate size and shape of a social network, and thereby which alters ought to be nominated or not. We report on change in these networks across three waves and assess whether this change appears to be the result of natural churn in the network or whether changes might be the result of factors in the interview itself, particularly anchoring and motivated underreporting. Our results indicate little change in average network size across waves, particularly for indirect tie nominations. Slight, significant changes were noted between waves one and two particularly among those with the largest networks. Almost no significant differences were observed between waves two and three, either in terms of network size, composition, or density. Data come from three waves of a Chicago-based panel study of young men who have sex with men.

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants.

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within-subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks.