Respondent-driven sampling among gay and bisexual men: experiences from a New Zealand pilot study

Respondent-driven sampling (RDS) is a method of approximating random sampling of populations that are difficult to locate and engage in research such as gay, bisexual and other men who have sex with men (GBM). However, its effectiveness among established urban gay communities in high-income countries is largely unexplored outside North America. We conducted a pilot study of RDS among urban GBM in Auckland, New Zealand to assess its local applicability for sexual health research.

Pre-fieldwork formative assessment explored RDS suitability among local GBM. Highly-networked initial participants ("seeds") and subsequent participants completed a questionnaire, took a rectal swab for chlamydia and gonorrhoea testing, and were asked to recruit up to three eligible peers over the subsequent 2 weeks using study coupons. Compensation was given for participating and for each peer enrolled. Feedback on the pilot was obtained through questionnaire items, participant follow-up, and a focus group. Nine seeds commenced recruitment, directly enrolling 10 participants (Wave One), who in turn enrolled a further three (Wave Two). Two of the 22 participants (9 %) had undiagnosed rectal chlamydia. The coupon redemption rate (23 %) was lower than the expected rate (33 %) for this population. Participants were motivated by altruism above financial incentives; however, time, transport and reluctance recruiting peers were perceived as barriers to enrolment.

Slow recruitment in our pilot study suggests that RDS might not be an effective or efficient method of sampling gay men in all high-income urban settings. However those who participated in the pilot were willing to provide anal swabs and information on their sexual behaviour, and also on the size of their GBM social network which is necessary to weight data in RDS. Refinements and adaptations such as reducing the transaction costs of taking part (e.g. offering online participation) could improve responses but these have their own drawbacks (higher set-up costs, difficulty collecting biological specimens).