Related Experiment Video
Updated: Jun 3, 2026

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
Published on: April 23, 2019
Accessing a diverse sample of injection drug users in San Francisco through respondent-driven sampling
Mohsen Malekinejad1, Willi McFarland, Jason Vaudrey
1University of California, San Francisco, Global Health Sciences, 50 Beale Street, 12th Floor, San Francisco, CA 94105, USA.
Aims:
Injection drug users (IDU) are the second most affected population by HIV in San Francisco and the United Stated after men who have sex with men (MSM). Behavioral surveillance data that include the diversity of the population at risk are necessary to develop effective programs for IDU.
Design:
We conducted a cross-sectional behavioral survey of IDU using respondent-driven sampling (RDS) in San Francisco. The present analysis focuses the performance of the sampling method in reaching the diversity of the population as a pre-requisite for representative data.
Participants:
Over 32 weeks, 571 eligible IDU were recruited, of whom 477 (83.5%) with complete records were included in analysis.
Findings:
The age range was 18-70 years, with 36% age 50 years or older. The majority (56%) were homeless. Male, MSM, African-Americans and Non-Hispanic Whites comprised 71%, 28%, 36% and 35% of IDU, respectively. Twenty-two percent had "ever shared needles in the past 12 months," and 57% reported that they had "shared drugs" in the past 12 months. Peer referral chains were able to cross-recruit IDU by diverse demographic characteristics, drug use related behaviors, program access and use, and other factors relevant to reaching and conducting prevention research on this population.
Conclusion:
RDS appears to be an effective sampling tool that reaches diverse populations of IDU, including many who may be missed by drug treatment and HIV prevention services in San Francisco and potentially in other urban areas.
Related Concept Videos
Convenience Sampling Method
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Drug Accumulation During Multiple Dosing: Repetitive IV Injections
Systematic Sampling Method
Systematic sampling is one of the simplest methods...
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...

