Evidence map›Paper›PMID 41436963›Full record

ArticleBMC medical research methodology2025

Recruitment of a probability-based general population health panel for public health research in Germany: the panel 'Health in Germany'.

Johannes Lemcke, Ilter Öztürk, Stefan Damerow, Tobias Heller, Sabine Born, Matthias Wetzstein, Jennifer Allen, Patrick Schmich

Abstract read
In one paragraph

Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. [Barriers to cycling for transportation: findings from the population-based survey "Health in Germany"].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026
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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

8 authors.

Johannes LemckeDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany. lemckej@rki.de.
Ilter ÖztürkDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Stefan DamerowDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Tobias HellerDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Sabine BornDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Matthias WetzsteinDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Jennifer AllenDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.
Patrick SchmichDepartment 2 Epidemiology and Health Monitoring, Robert Koch Institute, Gerichtstraße 27, Berlin, 13347, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis report presents the study design and recruitment outcomes for the 'Health in Germany' panel, a long-term population-based health survey infrastructure developed by the Robert Koch Institute. The initial recruitment was conducted using a stratified random sample of the German population and a mixed-mode approach combining web-based and paper questionnaires. We examine participation rates across demographic subgroups, assess sample composition, and analyze potential selection effects.

methodThe panel recruitment survey for the 'Health in Germany' panel utilized the residents' registration offices as the sampling frame. A two-stage stratified (cluster) sample was drawn from 359 primary sampling units across Germany. A mixed-mode approach was employed, offering both online and paper survey-mode on the basis of age groups. The sequence of survey modes was differentiated by age groups based on information from the residents' registration offices. For respondents aged 16-69 years, a sequential mixed-mode design, offering the online mode first and only with the second reminder the paper survey-mode (also called push-to-web strategy), was applied. For respondents aged 70 years and older a simultaneous mixed-mode design was used, offering the online and paper survey-mode with the invitation. Participants completed a first panel recruitment survey in which socio-demographic and health data were collected. Selection effects and sample composition were analyzed via logistic regression models and compared with official population data.

resultsA total of 62,556 interviews were conducted, with 49,766 participants consenting to join the panel. After double opt-in registration process (for online participants), 47,863 remained. Response rates were higher among women and younger participants. Online participation predominated in the sequential design, whereas offline participation was more common in the simultaneous design. Logistic regression indicated higher participation among women and residents of smaller municipalities. Overall, the sample composition aligned broadly with population benchmarks, except for education and citizenship.

conclusionsThe first recruitment study for the 'Health in Germany' panel established one of Europe's largest population-based health panels through a mixed-mode design. Future expansions include regular health surveys, biometric measurements, complementary self-recruitment alongside the probability-based sample, and the development of a mobile survey app.

Indexed as

Health SurveysPatient SelectionPopulation HealthPublic HealthAdolescentAdultAgedFemaleGermanyHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultIncentivesMixed-mode surveyPanel recruitment studyPanel studyProbability-samplingSelection effectsStudy infrastructure

Identifiers

PMID41436963
PMCPMC12853828

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LicenceCC BY
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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.