Respondent-Driven Sampling: a Sampling Method for Hard-to-Reach Populations and Beyond

Purpose of Review We provided an overview of sampling methods for hard-to-reach populations and guidance on implementing one of the most popular approaches: respondent-driven sampling (RDS). Recent Findings Limitations related to generating a sampling frame for marginalized populations can make them...

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Veröffentlicht in:Current epidemiology reports Jg. 9; H. 1; S. 38 - 47
Hauptverfasser: Raifman, Sarah, DeVost, Michelle A., Digitale, Jean C., Chen, Yea-Hung, Morris, Meghan D.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 22.03.2022
Springer Nature B.V
Schlagworte:
Epidemiologic Methods (PP Howards
Epidemiology
Estimates
Identification methods
Marginalized groups
Medicine
Medicine & Public Health
Population characteristics
Population statistics
Sampling
Sampling methods
Section Editors
Topical Collection on Epidemiologic Methods
Time-location sampling
Hard-to-reach populations
Probability sampling
Respondent-driven sampling
Snowball sampling
ISSN:2196-2995, 2196-2995
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Zusammenfassung:Purpose of Review We provided an overview of sampling methods for hard-to-reach populations and guidance on implementing one of the most popular approaches: respondent-driven sampling (RDS). Recent Findings Limitations related to generating a sampling frame for marginalized populations can make them “hard-to-reach” when conducting population health research. Data analyzed from non-probability-based or convenience samples may produce estimates that are biased or not generalizable to the target population. In RDS and time-location sampling (TLS), factors that influence inclusion can be estimated and accounted for in an effort to generate representative samples. RDS is particularly equipped to reach the most hidden members of hard-to-reach populations. Summary TLS, RDS, or a combination can provide a rigorous method to identify and recruit samples from hard-to-reach populations and more generalizable estimates of population characteristics. Researchers interested in sampling hard-to-reach populations should expand their toolkits to include these methods.
Bibliographie:ObjectType-Article-1
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ISSN:2196-2995
2196-2995
DOI:10.1007/s40471-022-00287-8