Empirical evidence of recruitment bias in a network study of people who inject drugs

ABSTRACT

Background: Epidemiologic surveys of people who inject drugs (PWID) can be difficult to conduct because potential participants may fear exposure or legal repercussions. Respondent-driven sampling (RDS) is a procedure in which subjects recruit their eligible social contacts. The statistical validity of RDS surveys of PWID and other risk groups depends on subjects recruiting at random from among their network contacts.

Objectives: We sought to develop and apply a rigorous definition and statistical tests for uniform network recruitment in an RDS survey.

Methods: We undertook a detailed study of recruitment bias in a unique RDS study of PWID in Hartford, CT, the USA in which the network, individual-level covariates, and social link attributes were recorded. A total of $n=527$ participants (402 male, 123 female, and two individuals who did not specify their gender) within a network of 2626 PWID were recruited.

Results: We found strong evidence of recruitment bias with respect to age, homelessness, and social relationship characteristics. In the discrete model, the estimated hazard ratios regarding the significant features of recruitment time and choice of recruitee were: alter’s age 1.03 [1.02, 1.05], alter’s crack-using status 0.70 [0.50, 1.00], homelessness difference 0.61 [0.43, 0.87], and sharing activities in drug preparation 2.82 [1.39, 5.72]. Under both the discrete and continuous-time recruitment regression models, we reject the null hypothesis of uniform recruitment.

Conclusions: The results provide the evidence that for this study population of PWID, recruitment bias may significantly alter the sample composition, making results of RDS surveys less reliable. More broadly, RDS studies that fail to collect comprehensive network data may not be able to detect biased recruitment when it occurs.

KEYWORDS:

• Injection drug use
• network sampling
• social link tracing
• survival analysis

Acknowledgments

We are grateful to Gayatri Moorthi, Heather Mosher, Greg Palmer, Eduardo Robles, Chinekwu Obidoa, Mark Romano, Jason Weiss, and the staff at the Institute for Community Research for their work collecting and preparing the RDS-net data. We thank Alexei Zelenev for helping clean the RDS-net data. Drs. Margaret Weeks, Thermos Valente, and Robert Heimer contributed significantly to RDS-net study design.

Conflict of interest

None declared.

Financial disclosures

Nothing to report.

Additional information

Funding

LZ was supported by a fellowship from the Yale World Scholars Program sponsored by the China Scholarship Council. FWC was supported by NIH grants NICHD DP2 1DP2 HD091799-01, NCATS KL2 TR000140, NIMH P30 MH062294, the Yale Center for Clinical Investigation, and the Yale Center for Interdisciplinary Research on AIDS. RDS-net was funded by NIDA 5R01 DA031594-03 to Jianghong Li;Eunice Kennedy Shriver National Institute of Child Health and Human Development [DP2 HD091799-01];National Center for Advancing Translational Sciences [KL2 TR000140];National Institute of Mental Health [P30 MH062294];National Institute on Drug Abuse [5R01DA031594-03];