Exploring Design Aspects of Web-Based Respondent-Driven Sampling for Racial/Ethnic Minorities

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ABSTRACT Increasing minority data availability is a priority of the HHS Action Plan to Reduce Racial and Ethnic Health Disparities. Currently available research data for racial/ethnicity minorities are, however, inadequate in their sample sizes and, hence, do not provide sufficient statistical power for analysis. Web-based respondent driven sampling (Web-RDS) is an extension of RDS, which exploits existing social networks for recruiting research participants, specifically, of rare, hidden and/or hard-to-reach groups. Rather than researchers recruiting participants directly, in RDS, participants recruit other eligible persons from own social networks. This recruitment process continues in waves and is mostly handled by incentivized recruitment coupons. Hence, RDS has potential to capture those who, otherwise, are difficult for researchers to reach and is much less cost intensive than traditional sampling methods. While RDS is typically administered in person, Web-RDS applies RDS on the Web, which leads to eliminating the need for interviewers and the constraints associated with the time and geography. Once the data collection system is established, marginal costs for Web-RDS is considerably lower than RDS, further reducing cost burdens. At the same time, racial/ethnicity minorities are reported to form tight ingroup social networks and to access the Web at a remarkably high rate, around 90%, a figure virtually the same as non-minorities'. The strong social network combined with the high Web access rate among minorities makes Web-RDS an attractive platform for minority data collection. However, there is a notable void in the literature on design aspects of RDS. Design issues are not only practical questions for which any Web-RDS studies are likely to seek answers but also a critical factor influencing data quality. This study attempts to fill this gap by providing practical design guidelines and tools for Web-RDS for a goal of improving data quality through successful implementations, where success is measured with sample composition and recruitment propensity. Specifically, we will explore two specific design elements (seed selection and coupon design) through randomized experiments and develop a data collection monitoring system. For doing so, Web-RDS will be applied to a national survey of Korean Americans, a rare minority group that comprises less than 1% of the U.S. population. Despite being rare, basic socio-demographic information is available for many racial/ethnic minority groups, such as Korean Americans, from the American Community Survey. This is particularly advantageous as the quality of the Web-RDS data under different experimental conditions can be verified against the minority-specific ACS data. By empirically demonstrating Web- RDS as a method for minority-specific data collection and its data quality through design experiments, the proposed study will bring these practical RDS-specific design issues to the literature and increase the awareness about the importance of design issues for data quality.