Patterns of Online and Offline Connectedness Among Gay, Bisexual, and Other Men Who Have Sex with Men

AIDS Behav. 2018 Jul;22(7):2147-2160. doi: 10.1007/s10461-017-1939-7.

Abstract

This study examined patterns of connectedness among 774 sexually-active gay, bisexual, and other men who have sex with men (GBM), aged ≥ 16 years, recruited using respondent-driven sampling in Metro Vancouver. Latent class analysis examined patterns of connectedness including: attendance at gay venues/events (i.e., bars/clubs, community groups, pride parades), social time spent with GBM, use of online social and sex seeking apps/websites, and consumption of gay media. Multinomial regression identified correlates of class membership. A three-class LCA solution was specified: Class 1 "Socialites" (38.8%) were highly connected across all indicators. Class 2 "Traditionalists" (25.7%) were moderately connected, with little app/website-use. Class 3 "Techies" (35.4%) had high online connectedness and relatively lower in-person connectedness. In multivariable modelling, Socialites had higher collectivism than Traditionalists, who had higher collectivism than Techies. Socialites also had higher annual incomes than other classes. Techies were more likely than Traditionalists to report recent serodiscordant or unknown condomless anal sex and HIV risk management practices (e.g., ask their partner's HIV status, get tested for HIV). Traditionalists on the other hand were less likely to practice HIV risk management and had lower HIV/AIDS stigma scores than Socialites. Further, Traditionalists were older, more likely to be partnered, and reported fewer male sex partners than men in other groups. These findings highlight how patterns of connectedness relate to GBM's risk management.

Keywords: Community; Gay and bisexual; HIV; Latent class analysis; Risk Management.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bisexuality
  • British Columbia
  • Cross-Sectional Studies
  • HIV Infections / prevention & control*
  • Homosexuality, Male
  • Humans
  • Income
  • Internet*
  • Latent Class Analysis
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Regression Analysis
  • Sexual Behavior / statistics & numerical data
  • Sexual Partners
  • Sexual and Gender Minorities*
  • Social Behavior*
  • Social Media
  • Social Stigma*