ArticleBMC medical research methodology2025
Recruitment of a probability-based general population health panel for public health research in Germany: the panel 'Health in Germany'.
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.
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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.
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Who cites it
6 citing papers in PubMed.
- [Barriers to cycling for transportation: findings from the population-based survey "Health in Germany"].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026Article
- Accidents at work among employed persons in Germany: Results from the 2024 'Health in Germany' panel.Journal of health monitoring · 2026Article
- Accidents among adults in Germany - Results from the accident module of the Panel 'Health in Germany' 2024.Journal of health monitoring · 2026Article
- Depressive and anxiety symptoms among adults in Germany: Results from the RKI Panel 'Health in Germany' 2024.Journal of health monitoring · 2025Article
- Background and Methodology of the 2024 annual survey from the panel 'Health in Germany' by the Robert Koch Institute.Journal of health monitoring · 2025Article
- Health monitoring at the Robert Koch Institute - Effects of a change in study design on sample composition and prevalence estimates due to the start of the 'Health in Germany' Panel.Journal of health monitoring · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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