Keywords: respondent-driven sampling, RDS, diversity, hard-to-reach, minorities

Respondent-driven sampling (RDS) is a network sampling technique for surveying complex populations in the absence of sampling frames. The idea is simple: identify some people (“seeds”) who belong or have access to the target population, encourage them to start a survey invitation chain-referral process in their community, ensure that every respondent can be traced back along the referral chain. Due to the reliance on respondent referral, RDS is frequently implemented with hidden or rare target populations, where members are assumed to know each other and thus have a higher degree of access than researchers.

We conducted a pilot study in 2023 where we invited 5,000 panel study members to a general population multi-topic online survey. During the survey, we asked respondents whether they would be willing to recruit up to three of their network members. Willing respondents then received personalized links with which to recruit their network members.

We found that younger individuals, individuals with higher incomes, and individuals with migration backgrounds were all (1) more likely to recruit, and (2) they typically recruited individuals similar to themselves. We additionally found that those recruits also had a higher propensity to participate, thereby potentially increasing the overall diversity of the survey. In this paper, we present a detailed overview of our results, along with relevant methodological findings such as method of recruitment. Additionally, we discuss 2025 fielding of RDS in the Social Cohesion Panel which builds upon the findings from our pilot study.