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Cited by 331

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Sampling Hard-to-Reach Populations with Respondent Driven Sampling

Open access
Johnston, Lisa G., Sabin, Keith·2010·Methodological Innovations Online

Abstract

Cost effective and targeted prevention, intervention and treatment programs for hard-to-reach populations at risk for HIV and other infections rely on the collection of quality data through biological and behavioral surveillance surveys (BBSS). Over the past decade, there has been a global expansion of BBSS to measure the prevalence of HIV and other infections, and related risk behaviors among injecting drug users, males who have sex with males, and female sex workers. However, a major challenge to sampling these hard-to-reach populations is that they are usually stigmatised and/or practice illegal behaviors which, in turn, make them difficult to access and unwilling to participate in research efforts. Over the past decade, respondent driven sampling (RDS) has become recognised as a viable option for rigorous sampling of hard-to-reach populations. This paper introduces RDS methods and describes some of the advantages and challenges to implementing and analysing surveys that use RDS.

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Metadata

Authors
Johnston, L. G., & Sabin, K.
Venue
Methodological Innovations Online
Published
2010-08
Volume
5
Issue
2
Pages
38-48
ISSN
1748-0612 (ISSN-L)
OpenAlex
W2309460329
Cited by
331
References
18
FWCI
9.43
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Sampling Hard-to-Reach Populations with Respondent Driven Sampling. https://app.cochat.ai/papers/10.4256/mio.2010.0017
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Johnston, L. G., & Sabin, K. (2010). Sampling Hard-to-Reach Populations with Respondent Driven Sampling. Methodological Innovations Online. https://doi.org/10.4256/mio.2010.0017

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.