Journal of Urban Health

, Volume 83, Issue 3, pp 459–476

Effectiveness of Respondent-Driven Sampling for Recruiting Drug Users in New York City: Findings from a Pilot Study

  • Abu S. Abdul‐Quader
  • Douglas D. Heckathorn
  • Courtney McKnight
  • Heidi Bramson
  • Chris Nemeth
  • Keith Sabin
  • Kathleen Gallagher
  • Don C. Des Jarlais
Article

Abstract

A number of sampling methods are available to recruit drug users and collect HIV risk behavior data. Respondent-driven sampling (RDS) is a modified form of chain-referral sampling with a mathematical system for weighting the sample to compensate for its not having been drawn randomly. It is predicated on the recognition that peers are better able than outreach workers and researchers to locate and recruit other members of a “hidden” population. RDS provides a means of evaluating the reliability of the data obtained and also allows inferences about the characteristics of the population from which the sample is drawn. In this paper we present findings from a pilot study conducted to assess the effectiveness of RDS to recruit a large and diversified group of drug users in New York City. Beginning with eight seeds (i.e., initial recruits) we recruited 618 drug users (injecting and non-injecting) in 13 weeks. The data document both cross-gender and cross-race and -ethnic recruitment as well as recruitment across drug-use status. Sample characteristics are similar to the characteristics of the drug users recruited in other studies conducted in New York City. The findings indicate that RDS is an effective sampling method for recruiting diversified drug users to participate in HIV-related behavioral surveys.

Keywords

Human immunodeficiency virus Recruitment of drug users Respondent-driven sampling Sampling hidden populations 

References

  1. 1.
    Ramirez-Valles J, Heckathorn DD, Vázquez R, Diaz RM, Campbell RT. From networks to populations: the development and application of respondent-driven sampling among IDUs and Latino gay men. AIDS Behav. 2005;9:387–402.PubMedCrossRefGoogle Scholar
  2. 2.
    Watters JK, Biernacki P. Targeted sampling: options for the study of hidden populations. Soc Probl. 1989;36:416–430.CrossRefGoogle Scholar
  3. 3.
    Bluthanthal RN, Watters JK. Multimethod research: from targeted sampling to HIV risk behaviors. Qualitative Methods in Drug Abuse and HIV Research, No. 157. Rockville, Md: National Institute on Drug Abuse; 1994.Google Scholar
  4. 4.
    Carlson RG, Wang J, Siegal HA, et al. An ethnographic approach to targeted sampling: problems and solutions in AIDS prevention research among injection drug and crack‐cocaine users. Hum Organ. 1994;53:279–286.Google Scholar
  5. 5.
    Semaan S, Lauby J, Liebman J. Street and network sampling in evaluation studies of HIV risk-reduction interventions. AIDS Rev. 2002;4:213–223.PubMedGoogle Scholar
  6. 6.
    Griffiths P, Gossop M, Powis B, Strang J. Reaching hidden populations of drug users by privileged access interviewers: methodological and practical issues. Addiction. 1993;88:1617–1626.PubMedCrossRefGoogle Scholar
  7. 7.
    van Meter KM. Methodological and design issues: techniques for assessing the representativeness of snowball samples. The Collection and Interpretation of Data from Hidden Populations, No. 98. Rockville, Maryland: National Institute on Drug Abuse; 1990.Google Scholar
  8. 8.
    Heckathorn DD. Respondent driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44:174–199.CrossRefGoogle Scholar
  9. 9.
    Heckathorn DD. Respondent driven sampling, II. Deriving population estimates from chain-referral samples of hidden populations. Soc Probl. 2002;49:11–34.CrossRefGoogle Scholar
  10. 10.
    Salganik MJ, Heckathorn DD. Sampling and estimation in hidden populations using respondent-driven sampling. Sociol Methodol. 2004;34:193–239.CrossRefGoogle Scholar
  11. 11.
    Wang J, Carlson RG, Falck RS, Siegal HA Rahman A, Li L. Respondent-driven sampling to recruit MDMA users: a methodological assessment. Drug Alcohol Depend. 2005;78:147–157.PubMedCrossRefGoogle Scholar
  12. 12.
    Heckathorn DD, Semaan S, Broadhead RS, Hughes JJ. Extensions of respondent-driven sampling: a new approach to the study of injection drug users aged 18–25. AIDS Behav. 2002;6(1):55–67.CrossRefGoogle Scholar
  13. 13.
    Kemeny J, Snell JL. Finite Markov Chains. Princeton, New Jersey: Van Nostrand; 1960.Google Scholar
  14. 14.
    Fararo TJ, Skvoretz J. Biased networks and social structure theorems, Part II. Soc Networks. 1984; 6:223–258.CrossRefGoogle Scholar
  15. 15.
    Des Jarlais DC, Perlis T, Arasteh K, et al. “Informed altruism” and “partner restriction” in the reduction of HIV infection in injecting drug users entering detoxification treatment in New York City, 1990–2001. J Acquir Immune Defic Syndr. 2004;35:158–166.PubMedCrossRefGoogle Scholar
  16. 16.
    Des Jarlais DC, Diaz T, Perlis T, et al. Variability in the incidence of human immunodeficiency virus, hepatitis B virus, and hepatitis C virus infection among young injecting drug users in New York City. Am J Epidemiol. 2003;157:467–471.PubMedCrossRefGoogle Scholar
  17. 17.
    Courtwright D. Dark Paradise: Opiate Addiction in America Before 1940. Cambridge, Massachusetts: Harvard University Press; 1982.Google Scholar
  18. 18.
    Preble E, Casey J Jr. Taking care of business: the heroin user's life on the street. Int J Addict. 1969;4:1–24.Google Scholar
  19. 19.
    Curtis R. Crack, cocaine and heroin: drug eras in Williamsburg, Brooklyn, 1960–2000. Addiction Research and Theory. 2003;11(1):47–63.CrossRefGoogle Scholar
  20. 20.
    Des Jarlais DC, Friedman SR, Novick D, et al. HIV-1 infection among intravenous drug users in Manhattan, New York City, from 1977 through 1987. JAMA. 1989;261:1008–1012.PubMedCrossRefGoogle Scholar
  21. 21.
    Des Jarlais DC, Perlis T, Friedman SR, et al. Behavioral risk reduction in a declining HIV epidemic: injection drug users in New York City, 1990–1997. Am J Public Health. 2000;90:1112–1116.PubMedCrossRefGoogle Scholar

Copyright information

© The New York Academy of Medicine 2006

Authors and Affiliations

  • Abu S. Abdul‐Quader
    • 1
  • Douglas D. Heckathorn
  • Courtney McKnight
  • Heidi Bramson
  • Chris Nemeth
  • Keith Sabin
  • Kathleen Gallagher
  • Don C. Des Jarlais
  1. 1.Behavioral and Clinical Surveillance Branch, Division of HIV/AIDS Prevention-Surveillance and Epidemiology, National Center for HIV, STD and TB Prevention, Centers for Disease Control and PreventionAtlantaUSA

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