Recruiting Injection Drug Users: A Three-Site Comparison of Results and Experiences with Respondent-Driven and Targeted Sampling Procedures

Robinson, William T.; Risser, Jan M. H.; McGoy, Shanell L.; Becker, Adam B; Rehman, Hafeez ur; Jefferson, Mary; Griffin, Vivian; Wolverton, Marcia; Tortu, Stephanie

doi:10.1007/s11524-006-9100-3

Cited by 103 publications

(86 citation statements)

References 17 publications

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“…Although there is a possibility that some non-IDUs enrolled in the study, participants were screened for physical signs of recent injection. RDS has been shown to be an effective recruitment strategy for hidden populations including IDU [47][48][49][50][51] ; despite concerns that RDS could negatively impact data collection or interpretation of analysis, we found no untoward effect of RDS on the participants. Finally, cross-sectional studies are not able to demonstrate causality.…”

Section: Discussionmentioning

confidence: 46%

Differing HIV Risks and Prevention Needs among Men and Women Injection Drug Users (IDU) in the District of Columbia

et al. 2012

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Washington, DC has among the highest HIV/AIDS rates in the US. Gender differences among injection drug users (IDUs) may be associated with adoption of prevention opportunities including needle exchange programs, HIV testing, psychosocial support, and prevention programming. National HIV Behavioral Surveillance data on current IDUs aged ≥18 were collected from 8/09 to 11/09 via respondent-driven sampling in Washington, DC. HIV status was assessed using oral OraQuick with Western Blot confirmation. Weighted estimates were derived using RDSAT. Stata was used to characterize the sample and differences between male and female IDU, using uni-, bi-, and multivariable methods. Factors associated with HIV risk differed between men and women. Men were more likely than women to have had a history of incarceration (86.6% vs. 66.8%, pG0.01). Women were more likely than men to have depressive symptoms (73.9% vs. 47.4%, pG 0.01), to have been physically or emotionally abused (66.1% vs. 16.1%, pG0.0001), to report childhood sexual abuse (42.7% vs. 4.7%, pG0.0001), and pressured or forced to have sex (62.8% vs. 4.0%, pG0.0001); each of these differences was significant in the multivariable analysis. Despite a decreasing HIV/AIDS epidemic among IDU, there remain significant gender differences with women experiencing multiple threats to psychosocial health, which may in turn affect HIV testing, access, care, and drug use. Diverging needs by gender are critical to consider when implementing HIV prevention strategies.

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Section: Discussionmentioning

confidence: 46%

Differing HIV Risks and Prevention Needs among Men and Women Injection Drug Users (IDU) in the District of Columbia

et al. 2012

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“…[1][2][3] Through the use of mathematical modeling and under certain strong assumptions to compensate for potential recruitment bias, RDS has been regarded as an innovative and useful means for accessing a potentially representative sample of difficult-to-reach populations at risk for or living with HIV, including injection drug users, sex workers, and men who have sex with men (MSM), both domestically and internationally. [4][5][6][7][8][9][10][11][12][13][14][15] Prior studies utilizing RDS to sample MSM have compared RDS to snowball, targeted, and time-location sampling. 9,16 In these comparisons, RDS performed similarly on ability to recruit, demonstrating the potential to successfully reach highly marginalized populations.…”

Section: Introductionmentioning

confidence: 99%

What Makes a Respondent-Driven Sampling “Seed” Productive? Example of Finding At-Risk Massachusetts Men Who Have Sex with Men

et al. 2010

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Several recent studies have sought to elaborate upon the applicability and validity of respondent-driven sampling (RDS) to find hard-to-reach samples in general and men who have sex with men (MSM) in particular. Few published studies have elucidated the characteristics associated with initial RDS participants ("seeds") who successfully recruited others into a study. A total of 74 original seeds were analyzed from four Massachusetts studies conducted between 2006 and 2008 that used RDS to reach high-risk MSM. Seeds were considered "generative" if they recruited two or more subsequent participants and "non-generative" if they recruited zero or one participant. Overall, 34% of seeds were generative. In separate multivariable logistic regression models controlling for age, race, health insurance, HIV status, and the study for which the seed was enrolled, unprotected anal sex in the past 12 months [adjusted odds ratio (AOR)=6.68; 95% confidence interval (95% CI)=1.27-35.12; p=0.03], cocaine use during sex at least monthly during the past 12 months (AOR=8.81; 95% CI=1.68-46.27; p=0.01), and meeting sex partners at social gatherings (AOR=7.42; 95% CI= 1.58-34.76; p=0.01) and public cruising areas (AOR=4.92; 95% CI=1.27-19.01; p= 0.02) were each significantly associated with increased odds of being a generative seed. These findings have methodological and practical implications for the recruitment of MSM via RDS. Finding ways to identify RDS seeds that are consistently generative may facilitate collecting a sample that is closer to reflecting the MSM who live in all of the communities in a given location or study sample.

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“…Because only a single RDS sample was taken, however, it is difficult to ascertain sample-to-sample variability of estimates. ‡ Second, RDS estimates have been compared to estimates derived from alternative sampling methods (15)(16)(17)(18)(19)(20)(21) (Table S1). These comparisons have not yielded consistent patterns and are hindered by the fact that true population values remain unknown.…”

mentioning

confidence: 99%

Assessing respondent-driven sampling

Goel

Salganik

2010

Proc. Natl. Acad. Sci. U.S.A.

330

351

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Respondent-driven sampling (RDS) is a network-based technique for estimating traits in hard-to-reach populations, for example, the prevalence of HIV among drug injectors. In recent years RDS has been used in more than 120 studies in more than 20 countries and by leading public health organizations, including the Centers for Disease Control and Prevention in the United States. Despite the widespread use and growing popularity of RDS, there has been little empirical validation of the methodology. Here we investigate the performance of RDS by simulating sampling from 85 known, network populations. Across a variety of traits we find that RDS is substantially less accurate than generally acknowledged and that reported RDS confidence intervals are misleadingly narrow. Moreover, because we model a best-case scenario in which the theoretical RDS sampling assumptions hold exactly, it is unlikely that RDS performs any better in practice than in our simulations. Notably, the poor performance of RDS is driven not by the bias but by the high variance of estimates, a possibility that had been largely overlooked in the RDS literature. Given the consistency of our results across networks and our generous sampling conditions, we conclude that RDS as currently practiced may not be suitable for key aspects of public health surveillance where it is now extensively applied.disease surveillance | snowball sampling | social networks T he development and evaluation of public health policies often require detailed information about so-called hard-to-reach or hidden populations. For example, HIV researchers are especially interested in monitoring risk behavior and disease prevalence among injection drug users, men who have sex with men, and commercial sex workers-the groups at highest risk for HIV in most countries. Unfortunately, however, these high-risk groups are not easily studied with standard sampling methods, including institutional sampling, targeted sampling, and time-location sampling (1).Respondent-driven sampling (RDS) (2-4) facilitates examination of such hidden populations via a chain-referral procedure in which participants recruit one another, akin to snowball sampling. RDS is now widely used in the public health community and has been recently applied in more than 120 studies in more than 20 countries, involving a total of more than 32,000 participants (5). In particular, in helping to track the HIV epidemic, RDS is used by the Centers for Disease Control and Prevention (CDC) (6, 7) and by the United States President's Emergency Plan for AIDS Relief.RDS is a method both for data collection and for statistical inference. To generate an RDS sample, one begins by selecting a small number of initial participants ("seeds") from the target population who are asked-and typically provided financial incentive-to recruit their contacts in the population (2). The sampling proceeds with current sample members recruiting the next wave of sample members, continuing until the desired sample size is reached. Participants are usually all...

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Recruiting Injection Drug Users: A Three-Site Comparison of Results and Experiences with Respondent-Driven and Targeted Sampling Procedures

Cited by 103 publications

References 17 publications

Differing HIV Risks and Prevention Needs among Men and Women Injection Drug Users (IDU) in the District of Columbia

Differing HIV Risks and Prevention Needs among Men and Women Injection Drug Users (IDU) in the District of Columbia

What Makes a Respondent-Driven Sampling “Seed” Productive? Example of Finding At-Risk Massachusetts Men Who Have Sex with Men

Assessing respondent-driven sampling

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