This is one of the first studies to apply RDS to recruit young adult, non-dependent, illicit users of pharmaceutical opioids for longitudinal research. RDS was used successfully in reaching recruitment quotas within the planned time frame (about 12 months). The small differences between the actual and equilibrium sample compositions indicate that the sample converged in terms of age and gender compositions. However, despite lengthy recruitment chains, the sample did not reach equilibrium for ethnicity.
Usually, 4–5 recruitment waves should be sufficient for the sample to reach equilibrium (Heckathorn, 1997
). Our sample contained 17 chains that had 4 or more waves, and 7 chains that had 7 or more waves. The absence of equilibrium in terms of ethnic composition is most likely due to high homophily levels observed among Whites and African Americans. Generally, RDS is considered to have greater efficiency when sampling populations that have equal and low to moderate homophily (Heckathorn, 2002
). Although African Americans and Whites had similar homophily levels, the rate of in-group recruitment was very high (close to complete homophily), indicating that the two groups recruited almost exclusively from their own group, producing a “bottleneck” in the network and impacting the quality of RDS estimates (Goel and Salganik, 2009
). Further, there were large differences in average network sizes reported by White and African American participants (). Although RDS controls for biases related to the differences in average network size among groups by giving less weight to proportions with large average network sizes and more weight to proportions with small network sizes, large differences in network size can introduce bias (Johnston, 2008
) and potentially contribute to a lack of equilibrium in terms of ethnic composition.
The social distance observed in recruitment tendencies between African American and White participants is one of the most interesting aspects of the current study. The level of in-group ethnic recruitment in our study contrasts markedly with other studies involving illicit drug users. For example, in a study of MDMA/Ecstasy users in Columbus, Ohio, homophily among Whites was 0.54, and among African Americans, 0.49 (Wang et al., 2005
). In a study with illicit stimulant users recruited in rural Ohio, where ethnic integration is expected to be much lower than that in a city like Columbus, the homophily index was 0.58 among Whites and 0.39 among Non-Whites (Wang et al., 2007
). The high level of social distance observed between Whites and African Americans in the current study might be because illicit pain pill use more commonly occurs in private settings rather than public venues, and has a less-well defined “subculture” of use, compared to drugs like MDMA/Ecstasy or crack cocaine. Consequently, there are fewer opportunities for social interaction, as compared, for example, to mixing in dance clubs or crack houses. Notably, formative research failed to alert us of potential issues related to social distance between Whites and African Americans, as key informants reported ethnically mixed social networks of users.
The recruitment process generated a sample with a much larger proportion of African Americans than initially expected; the sample was 50% White and 44% African American. The expectation was that the sample would contain a larger proportion of Whites because: 1) the Columbus, OH, population is about 66% White and 26% African American (the corresponding numbers for Franklin County are 73% and 19%) (U.S. Census Bureau, 2009
); and 2) prior studies and epidemiological reports have consistently shown higher rates of illicit use of pharmaceutical opioids among Whites than African Americans (Simoni-Wastila et al., 2004
; McCabe et al., 2005
; OSAM Network, 2008, June
; Daniulaityte et al., 2009
; SAMHSA, 2010b
). The high proportion of African American recruits in our study might indicate local and/or emerging drug use trends that have not been reflected in national studies. Alternatively, it may indicate larger than expected over-sampling of certain segments of drug user populations. Others have challenged the claim that RDS increases sample representativeness, compared to traditional sampling methods (Heimer, 2005
The growth of the RDS recruitment process was much slower than the theoretically expected geometric growth proposed by Heckathorn (1997
, and reported in other studies. For example, in a study with illicit drug users in New York City, 618 participants were enrolled from 8 seeds over a period of 13 weeks (Abdul-Quader et al., 2006a
). As noted, after the first 8 weeks, our study had only 15 participants. There are a number of potential factors responsible for the slower than expected recruitment rate.
First, unlike many other studies using RDS, ours had very narrow eligibility criteria, which created very unique demands for referral and recruitment. This resulted in many referrals not qualifying for the study. In comparison, a study that used RDS to recruit illicit users of pharmaceutical opioids in Maine needed 23 seeds and only three months to recruit a total sample of 237 participants. However, eligibility criteria for that study were less stringent (Grau et al., 2007
). Second, since our sample was limited to individuals who were not opioid dependent and, consequently, may have experienced fewer adverse consequences from their drug use, perhaps they were less motivated by the financial incentive and/or by altruistic motives to participate. Notably, prior research indicated significant difficulties recruiting non-dependent opioid users. A study conducted in Amsterdam that used ethnographic fieldwork, snowball sampling, newspaper advertisements and website announcements to recruit non-dependent opiate users (including heroin and opium) was only able to recruit 127 individuals over 2 years. Further, monetary compensation had to be increased from €40 to €100 to assure participation (Korf et al., 2010
). Third, because of the financial constraints, multiple interview sites, which might have facilitated the RDS process, were not feasible. Fourth, participants were required to show valid IDs to verify age and identity, which might have presented a barrier for some individuals. Fifth, in our previous studies using RDS, we employed a full-time ethnographer who had the ability to expand formative research and help identify seeds (Draus et al., 2005
; Wang et al., 2005
; Wang et al., 2007
). We did not employ a full-time ethnographer in this study due to financial constraints and because the phenomenon of non-medical use of pharmaceutical opioids is less public with a less well defined “sub-culture” of beliefs, attitudes, behaviors, and identifiable locations of use. Finally, the lack of social connectedness in the target population and the “bottleneck” in the network of target population (Goel and Salganik, 2009
), which were not detected during formative work, may also have contributed to the slower than expected recruitment.
Prior research indicates that financial pressures may introduce significant biases in sample recruitment. It has been suggested that RDS’s dual incentive system has a potential to minimize such biases, since those who are too affluent to care about material rewards might give in to the social pressure from recruiting peers (Heckathorn, 1997
). However, it is very likely these biases, although somewhat offset by social pressures of peer recruitment and the secondary incentive system, are not completely eliminated. Most RDS-based studies that displayed efficiency and productivity in recruitment targeted economically marginalized groups such as injection drug users or sex workers (Heckathorn, 1997
; Heckathorn, 2002
; Johnston et al., 2006
), and/or were conducted with communities that were very active in their social welfare, such as MSM in sub-Saharan Africa where no economic incentive was used to recruit the sample (Johnston, 2008
). However, RDS recruitment failed with “mainstream” marijuana users since it targeted individuals who represented wealthier and better socially adjusted segments of drug using populations (Hathaway et al., 2010
). Other studies have also shown that individuals of higher socioeconomic status and/or those who were not sufficiently motivated by the amount of the monetary initiatives, were less likely to recruit others (de Mello et al., 2008
; Reisner et al., 2010
; Uuskula et al., 2010
; Rudolph et al., 2011
). Although RDS sample analysis based on the economic status of our participants was not performed, formative research suggested that economically challenged individuals with ample disposable time might have been more likely to participate and recruit others for the study. Reaching wealthier substance users presents a challenge not only for RDS-based recruitment (Ramirez-Valles et al., 2005
; Rudolph et al., 2011
Sample analysis was limited because questions about network size did not include the definition of the population with all the eligibility restrictions, as required by RDS standards (Johnston, 2008
). This omission was made so as not to reveal all eligibility criteria to potential participants and to minimize misrepresentations among referred individuals. However, precision in the estimation of social network size is important since it determines the probability of someone being selected into the study. Omission of eligibility criteria may result in the possible over-estimation of participants’ network sizes. In addition, inaccuracies in estimates of network sizes, which may have resulted in part because all eligibility criteria were not divulged to participants, may have also contributed to the discrepancies in network size by ethnicity. Issues related to the artificial nature of how the study population and social/drug user networks are defined have been noted in prior research (e.g., Platt et al., 2006) and perhaps are inherent with many applications of RDS.
In summary, this study details our experiences using RDS as a recruitment method with a narrowly-defined target population. Although the sample did not converge in terms of ethnic composition, the sampling quota was eventually met within the specified time frame. Recruitment of non-dependent illicit drug users with stringent eligibility criteria presents significant challenges to the drug abuse field (Korf et al., 2010
). Strict eligibility criteria were necessary to determine the characteristics of those who transition to opioid dependence and/or heroin use. Use of alternative recruitment methods, such as time-space or ethnographic targeted sampling, was hardly feasible, since illicit pain pill use more commonly occurs in private settings rather than public venues, and non-dependent users are little involved in “street culture” of illicit drug use (Sifaneck and Neaigus, 2001
). As a result, we felt that RDS was the best available recruitment strategy. Nevertheless, our experience also suggests that integrating elements of other recruitment strategies, including recruitment via newspapers and flyers (“targeted canvassing”) (Sifaneck and Neaigus, 2001
; Korf et al., 2010
) improved the efficiency of RDS in recruiting our narrowly defined sample. Further, although we followed a common practice of including a broad range of “cultural experts” in the formative research stage (Allen et al., 2009
), our experience suggests that RDS planning and implementation would have benefited if we included a greater number of key informants who also met all eligibility criteria for the main study, although this might have increased the time frame and resources. Finally, our study suggests caution in the use of RDS and stresses the importance of formative work to determine whether the target population is socially connected enough (given eligibility criteria) to generate a "representative" sample using RDS. RDS may be a practical recruitment approach to reach hidden populations, but claims regarding representativeness and subsequent generalizability cannot always be made.