Smartphone-based Respondent Driven Sampling (RDS): a methodological advance in surveying small or ‘hard-to-reach’ populations

Sosenko, F. L. and Bramley, G. (2022) Smartphone-based Respondent Driven Sampling (RDS): a methodological advance in surveying small or ‘hard-to-reach’ populations. PLoS ONE, 17(7), e0270673. (doi: 10.1371/journal.pone.0270673) (PMID:35862382) (PMCID:PMC9302716)

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Producing statistically robust profiles of small or ‘hard-to-reach’ populations has always been a challenge for researchers. Since surveying the wider population in order to capture a large enough sample of cases is usually too costly or impractical, researchers have been opting for ‘snowballing’ or ‘time-location sampling’. The former does not allow for claims to representativeness, and the latter struggles with under-coverage and estimating confidence intervals. Respondent Driven Sampling (RDS) is a method that combines snowballing sampling with an analytical algorithm that corrects for biases that arise in snowballing. For all its advantages, a major weakness of RDS has been around data collection. Traditionally done on-site, the process is costly and lengthy. When done online, it is cheaper and faster but under a serious threat from fraud, compromising data quality and validity of findings. This paper describes a real-life application of a RDS data collection system that maximizes fraud prevention while still benefiting from low cost and speedy data collection.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Sosenko, Dr Filip
Authors: Sosenko, F. L., and Bramley, G.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN (Online):1932-6203
Copyright Holders:Copyright © 2022 Sosenko, Bramley
First Published:First published in PLoS ONE 17(7): e0270673
Publisher Policy:Reproduced under a Creative Commons License

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