title: [The problem of response in epidemiological studies in Germany (part I)].
abstract: To achieve high response rates in German epidemiological studies is growing more difficult. Low response in epidemiological studies may decrease the acceptance of the results. Response, however, is not identical with the quality of a study. In the first part of this paper various definitions of response (contact, cooperation, response, recruitment proportions) are introduced and discussed in the context of different study designs with reference to practical examples. A population-based survey such as the Study of Health in Pomerania (SHIP) investigates the distribution of risk factors and health-related endpoints. Surveys should yield representative results which can be generalised to apply to the entire population (external validity). This study design usually requires large participitation proportions. In a prospective cohort study such as the European Investigation into Cancer and Nutrition (EPIC) the emphasis is on internal validity. A stable study population willing to participate in regular follow-ups is a primary recruitment goal. If the response in a case-control study such as the Northern Germany Leukaemia and Lymphoma Study (NLL) is low, the priority is to achieve approximately equal response proportions for cases and controls. Simultaneous public relation and media activities can improve participitation in a study. Multidimensional strategies combining public communications, cooperation with local and regional officials and frequent press and media coverage are emphasised. The second part of this paper will discuss methods to quantify the effects of the response proportions on the validity of the study results.
authors.affiliation: Betriebliche Epidemiologie, Zentralinstitut für Arbeitsmedizin, Freie Universität Hamburg, Universität Hamburg. Latza@uke.uni-hamburg.de
authors.forename: U
authors.initials: U
authors.lastname: Latza
authors.forename: A
authors.initials: A
authors.lastname: Stang
authors.forename: M
authors.initials: M
authors.lastname: Bergmann
authors.forename: A
authors.initials: A
authors.lastname: Kroke
authors.forename: S
authors.initials: S
authors.lastname: Sauer
authors.forename: R
authors.initials: R
authors.lastname: Holle
authors.forename: P
authors.initials: P
authors.lastname: Kamtsiuris
authors.forename: C
authors.initials: C
authors.lastname: Terschüren
authors.forename: W
authors.initials: W
authors.lastname: Hoffmann
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D040343:Behavioral Risk Factor Surveillance System; D015982:Bias; D003625:Data Collection / Q000706:statistics & numerical data*; D016021:Epidemiologic Studies; D005260:Female; D005858:Germany; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012307:Risk Factors