Methodological challenges in collecting social and behavioural data regarding the HIV epidemic among gay and other men who have sex with men in Australia

BACKGROUND: Behavioural surveillance and research among gay and other men who have sex with men (GMSM) commonly relies on non-random recruitment approaches. Methodological challenges limit their ability to accurately represent the population of adult GMSM. We compared the social and behavioural profiles of GMSM recruited via venue-based, online, and respondent-driven sampling (RDS) and discussed their utility for behavioural surveillance.

METHODS: Data from four studies were selected to reflect each recruitment method. We compared demographic characteristics and the prevalence of key indicators including sexual and HIV testing practices obtained from samples recruited through different methods, and population estimates from respondent-driven sampling partition analysis.

RESULTS: Overall, the socio-demographic profile of GMSM was similar across samples, with some differences observed in age and sexual identification. Men recruited through time-location sampling appeared more connected to the gay community, reported a greater number of sexual partners, but engaged in less unprotected anal intercourse with regular (UAIR) or casual partners (UAIC). The RDS sample overestimated the proportion of HIV-positive men and appeared to recruit men with an overall higher number of sexual partners. A single-website survey recruited a sample with characteristics which differed considerably from the population estimates with regards to age, ethnically diversity and behaviour. Data acquired through time-location sampling underestimated the rates of UAIR and UAIC, while RDS and online sampling both generated samples that underestimated UAIR. Simulated composite samples combining recruits from time-location and multi-website online sampling may produce characteristics more consistent with the population estimates, particularly with regards to sexual practices.

CONCLUSION: Respondent-driven sampling produced the sample that was most consistent to population estimates, but this methodology is complex and logistically demanding. Time-location and online recruitment are more cost-effective and easier to implement; using these approaches in combination may offer the potential to recruit a more representative sample of GMSM.