Our research shows that TS and RDS both resulted in sizable and diverse samples of IDUs in San Francisco. IDUs in San Francisco are easily accessible through community-based street-intercept methods, as demonstrated by the TS study. They are socially networked and suitable for peer-recruitment sampling, as demonstrated by the RDS study. We were able to satisfy the RDS methodological requirements, which means that we were theoretically able to generate representative estimates of demographic variables and indicators of access to health care of the IDU population.
We found that the TS and RDS studies reached similar samples of IDU in terms of demographic characteristics, with the exception of African Americans. African Americans represent a small minority of the population in San Francisco (6.9% in 2007 per the US Census Bureau39
) and are largely concentrated in one neighborhood in the southeastern part of the city (Bayview/Hunter's Point, zip code 94124), which in 2005 was isolated from the rest of the city geographically by highway systems and poor access via public transportation (two bus lines, no streetcar, no subway). Through the secondary analysis and ethnography components of TS methodology, this neighborhood was identified as having a large population of IDUs, and a field site was placed in its midst. While the RDS study attempted to include IDUs from this neighborhood (three seeds), we hypothesize that the long travel time between the neighborhood and the RDS data collection site may have limited study participation. This finding suggests that when utilizing RDS, it may be wise to implement some of the steps of TS during the planning stages, which can be used to decide how many and where to establish data collection sites. This could include collecting secondary indicator data and conducting a brief ethnography to figure out where IDUs are located and what cultural factors may be important to consider in designing the procedures of the study. The finding also underscores the importance of including geographic markers (zip codes or census tracts) on surveys of IDUs to assess geographic reach.
The two samples differed substantially with respect to the proportion of participants who had utilized current prevention and care programs in San Francisco. Fewer RDS participants reported use of drug treatment and SEP, although SEP use was very high overall. This finding implies that RDS may be more effective than TS at reaching IDUs not receiving services. If the use of RDS is coupled with a proactive system of referral to services, the study can potentially bring IDU with less access to care into prevention and treatment programs.
The TS sample had a higher proportion of IDU who had reported “ever testing positive” for HCV, compared to the RDS sample. This finding might be because the TS sample included more IDU who had ever been in drug treatment. Those who have access to care are more likely to be tested for HCV. Another explanation is that the TS study provided HCV testing for participants from 1998 to 2001, and many in the 2005 TS sample had participated in the earlier cross-sections. HCV prevalence among IDUs in the TS study during those years was 91%.34
There are several limitations to this study that need to be considered when interpreting its results. Although TS and RDS were both very effective in generating diverse samples, there is no way of knowing whether these samples are representative of the target population as a whole. TS has several limitations that should be noted. It requires that IDUs are part of a street culture that is easily accessed by an outreach worker, relying on the talents of the outreach workers who are involved in the ethnography and recruitment. For example, younger IDUs may not be interested in talking with or may not trust an older outreach worker. In RDS, it is possible to assess whether homophily exists and then corrects for it using weighting in RDSAT. Another limitation of the study is that the TS sample consisted of the 37th cross-section of a long-standing study, which may have generated a different sample than if it had been a first-time TS sample. The reputation of the study in the community may have biased the attributes of those who were willing to participate. RDS also has several limitations. It cannot access those who are not socially networked or isolated. For example, in an RDS survey of IDU in Cairo, Egypt, chains of referrals did not reach women.35
In a survey of IDU in Tehran, Iran, the final sample lacked women and Afghan IDUs, despite empirical evidence supporting the existence of such groups.36
Because RDS does not generally involve an intensive formative research phase, it is not easy to understand how the study procedures might bias who decides to participate.
There are also limitations common to both of these studies. Response bias is a limitation of all surveys, regardless of sampling methods, particularly when studying populations most at risk for HIV. Measuring the response rate is more challenging in surveys of IDUs, given that researchers usually are not present when study subjects are recruiting their peers to find out how many potential subjects are approached by recruiters. There were some differences in eligibility criteria in the two studies, which may account for some of the observed differences. Specifically, the RDS study was limited to English speakers while the TS study also included questionnaires in Spanish. However, in reality, no study participants in the TS study chose to be interviewed in Spanish. The time frame for injection criteria was 12 months in the RDS study and 30 days in the TS study. This may mean that some of the participants in the RDS study were less likely to be active IDUs. This could have biased the drug treatment estimates for example, even though drug treatment was less prevalent in the RDS sample. Finally, the RDS study required San Francisco residency. From our 20 years of experience conducting research with IDUs in San Francisco, we feel it is highly unlikely that more than 2% of the TS sample consisted of IDUs who reside outside of San Francisco. The majority of variables is self-reported and subject to recall bias and social desirability responses. However, we expect that these sources of biases would affect both samples similarly given that populations and type of questions were relatively comparable. Moreover, previous studies of IDUs have found good reliability with respect to the measures we used to assess the main outcomes in this study.37,38
And finally, because of the different statistical methods needed for analyzing RDS and TS data, we were not able to combine the datasets and conduct multivariate comparisons to assess whether the data are significantly different. Instead, we relied on assessing whether the 95% CIs overlapped in the estimates.
In order for quantitative studies of IDUs to be useful for identifying the prevalence and factors associated with various social and medical outcomes, it is important they use a sampling methodology that optimizes generalizability to the target population. Given that it is not feasible to carry out population-based randomized sampling of drug users, it is important to choose methods that are most likely to fit the geographic, social, and political characteristics of the area. It appears that in San Francisco, both RDS and TS are useful tools for recruiting IDUs. Our study suggests that perhaps a hybrid model is best suited for San Francisco, whereby the ethnographic and secondary analysis components of TS would precede initiation of RDS. This would optimize the benefits of both methods by assuring that study procedures enable RDS sampling to actualize its promise of representation.