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Smartphone-based Respondent Driven Sampling (RDS): A methodological advance in surveying small or 'hard-to-reach' populations.

ABSTRACT: 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.

SUBMITTER: Sosenko FL

PROVIDER: S-EPMC9302716 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data.Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample).We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion.Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required when interpreting findings based on the sampling method.

Project description:BackgroundMany respondent-driven sampling (RDS) methodologies have been employed to investigate hard-to-reach populations; however, these methodologies present some limits. We describe a minimally investigated RDS methodology in which peer recruitment and interviewing are phone-based. The feasibility of the methodology, field experiences, validity of RDS assumptions and characteristics of the sample obtained are discussed.MethodsWe conducted a phone-based RDS survey among men who have sex with men (MSM) aged 18 or above and living in Côte d'Ivoire. Eight initial MSM across Côte d'Ivoire were selected. Participants were asked to call a hotline to be registered and interviewed by phone. After the participants completed the questionnaire, they were asked to recruit a maximum of 3 MSM from their acquaintances.ResultsDuring the 9 months of the survey, 576 individuals called the hotline, and 518 MSM completed the questionnaire. The median delay between the invitation to participate and the completion of the questionnaire by peer-recruited MSM was 4 days [IQR: 1-12]. The recruitment process was not constant, with high variation in the number of people who called the hotline during the survey period. RDS chain convergence to equilibrium was reached within 6 waves for most of the selected variables. For the network size estimation assumption, participants who incorrectly estimated their network size were observed. Regarding the sample obtained, MSM were recruited from all the regions of Côte d'Ivoire with frequent interregional recruitment; 23.5% of MSM were recruited by someone who does not live in the same region. Compared to the MSM who participated in two other surveys in Côte d'Ivoire, the MSM in our sample were less likely to know about an MSM non-governmental organisation. However, MSM aged 30 years old and above and those with a low level of education were underrepresented in our sample.ConclusionWe show that phone-based RDS surveys among MSM are feasible in the context of sub-Saharan Africa. Compared to other classical RDS survey methodologies, the phone-based RDS methodology seems to reduce selection bias based on geography and proximity with the MSM community. However, similar to other methodologies, phone-based RDS fails to reach older and less-educated MSM.

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Smartphone-based Respondent Driven Sampling (RDS): A methodological advance in surveying small or 'hard-to-reach' populations.

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