• H Fisher Raymond, Yea-Hung Chen, and Willi McFarland.
• School of Public Health, Rutgers University, Piscataway, NJ, USA.
• J Urban Health. 2019 Feb 1; 96 (1): 55-62.

AbstractWe sought to leverage the strengths of time location sampling (TLS) and respondent-driven sampling (RDS) for surveys of hidden populations by combing elements of both methods in a new approach we call "starfish sampling." Starfish sampling entails random selection of venue-day-time units from a mapping of the locations where the population can be found, combined with short chains of peer referrals from their social networks at the venue or presenting to the study site later. Using the population of transmen in San Francisco as a case example, we recruited 122 eligible participants using starfish sampling: 79 at randomly selected venues, 11 on dating applications, and 32 by referral. Starfish sampling produced one of the largest community-recruited samples specifically for transmen to date. Starfish sampling is a flexibility method to recruit and sample hidden populations for whom conventional TLS and RDS may not work in theory or practice.

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