Evidence map›Paper›PMID 30662996›Full record

ArticleInternational journal of public health2019

Feasibility of using respondent-driven sampling to recruit participants in superdiverse neighbourhoods for a general health survey.

Florence Samkange-Zeeb, Ronja Foraita, Stefan Rach, Tilman Brand

Abstract read
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In one paragraph

Article in International journal of public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Results and Strategies for a Diversity-Oriented Public Health Monitoring in Germany.International journal of environmental research and public health · 2022
    Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Florence Samkange-ZeebLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany. samkange@leibniz-bips.de.ORCID http://orcid.org/0000-0001-8175-1719
Ronja ForaitaLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Stefan RachLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Tilman BrandLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.

Funding

NORFACE Grant No.462-14-091
6 · The paper itself

Abstract

objectivesRespondent-driven sampling (RDS), a modified chain-referral system, has been proposed as a strategy for reaching 'hidden' populations. We applied RDS to assess its feasibility to recruit 'hard-to-reach' populations such as migrants and the unemployed in a general health survey and compared it to register-based sampling (RBS).

methodsRDS was applied parallel to standard population RBS in two superdiverse neighbourhoods in Bremen, Germany. Prevalences of sample characteristics of interest were estimated in RDS Analyst using the successive sampling estimator. These were then compared between the samples.

resultsOnly 115 persons were recruited via RDS compared to 779 via RBS. The prevalence of (1) migrant background, (2) unemployment and (3) poverty risk was significantly higher in the RDS than in the RBS sample. The respective estimates were (1) 51.6 versus 32.5% (95% CI

conclusionsAlthough recruitment was difficult and the number of participants was small, RDS proved to be a feasible method for reaching migrants and other disadvantaged persons in our study.

Indexed as

Health StatusPatient SelectionAdultAgedAged, 80 and overFemaleGermanyHealth SurveysHumansMaleMiddle AgedSampling StudiesSurveys and QuestionnairesVulnerable PopulationsYoung AdultFeasibilityHard-to-reachMigrantsRespondent-driven samplingSuperdiverse

Identifiers

PMID30662996

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.