MODYS—A Modular Control and Documentation System for Epidemiological Studies

Part of the Springer Series on Epidemiology and Public Health book series (SSEH)


The quality of data collected in epidemiological observational research critically depends on the appropriate procedures for recruitment of study subjects. In this chapter, we describe the requirements and standard procedures for contacting, recruiting and documenting in field studies. We present a software tool, MODYS (modular control and documentation system), that was specifically designed to control and document all recruitment steps in population-based studies. The general design of MODYS is outlined, and its implementation for the IDEFICS study is presented in detail. Furthermore, the analysis of paradata recorded by MODYS is demonstrated with examples from the IDEFICS study.


IDEFICS Study Recruitment Step Paradata Contact Attempts Proportional Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The development of instruments, the baseline data collection and the first follow-up work as part of the IDEFICS study ( were financially supported by the European Commission within the Sixth RTD Framework Programme Contract No. 016181 (FOOD). The most recent follow-up including the development of new instruments and the adaptation of previously used instruments was conducted in the framework of the I.Family study ( which was funded by the European Commission within the Seventh RTD Framework Programme Contract No. 266044 (KBBE 2010-14).

We thank all families for participating in the extensive examinations of the IDEFICS and I.Family studies. We are also grateful for the support from school boards, headmasters and communities.


  1. Ahrens W, Bammann K, Siani A, Buchecker K, De Henauw S, Iacoviello L, et al. IDEFICS consortium. The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obes (Lond). 2011;35(Suppl 1):S3–15.CrossRefGoogle Scholar
  2. Ahrens W, Siani A, Adan R, De Henauw S, Eiben G, Gwozdz W, et al. I.Family consortium. Cohort profile: the transition from childhood to adolescence in European children—how I.Family extends the IDEFICS cohort. Int J Epidemiol. 2017;46(5):1394–1395j.Google Scholar
  3. American Association for Public Opinion Research (AAPOR). Standard definitions: final dispositions of case codes and outcome rates for surveys. Ann Arbor, Michigan: American Association for Public Opinion Research; 2016.Google Scholar
  4. Asch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol. 1997;50(10):1129–36.CrossRefGoogle Scholar
  5. Cohen SB, Machlin SR, Branscome JM. Patterns of survey attrition and reluctant response in the 1996 medical expenditure panel survey. Health Serv Outcomes Res Methodol. 2000;1(2):131–48.CrossRefGoogle Scholar
  6. Cotter RB, Burke JD, Loeber R, Navratil JL. Innovative retention methods in longitudinal research: a case study of the developmental trends study. J Child Fam Stud. 2002;11(4):485–98.CrossRefGoogle Scholar
  7. Dillman DA, Phelps G, Tortora R, Swift K, Kohrell J, Berck J, et al. Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response and internet. Soc Sci Res. 2009;38:1–18.CrossRefGoogle Scholar
  8. Fletcher AC, Hunter AG. Strategies for obtaining parental consent to participate in research. Fam Relat. 2003;52(3):216–21.CrossRefGoogle Scholar
  9. German National Cohort. (GNC) Consortium. The German National Cohort: aims, study design and organization. Eur J Epidemiol. 2014;29(5):371–82.CrossRefGoogle Scholar
  10. Haring R, Alte D, Völzke H, Sauer S, Wallaschofski H, John U, et al. Extended recruitment efforts minimize attrition but not necessarily bias. J Clin Epidemiol. 2009;62(3):252–60.CrossRefGoogle Scholar
  11. Jöckel KH, Stang A. Cohort studies with low baseline response may not be generalisable to populations with different exposure distributions. Eur J Epidemiol. 2013;28(3):223–7.CrossRefGoogle Scholar
  12. Kreuter F, Couper M, Lyberg L. The use of paradata to monitor and manage survey data collection. In: Proceedings of the joint statistical meetings, American Statistical Association; 2010, p. 282–296.Google Scholar
  13. Lacey JV Jr, Savage KE. 50% response rates: half-empty, or half-full? Cancer Causes Control. 2016;27(6):805–8.CrossRefGoogle Scholar
  14. Langeheine M, Pohlabeln H, Ahrens W, Rach S. IDEFICS consortium. Consequences of an extended recruitment on participation in the follow-up of a child study: Results from the German IDEFICS cohort. Paediatr Perinat Epidemiol. 2017;31(1):76–86.CrossRefGoogle Scholar
  15. Lynn P, Beerten R, Laiho J, Martin J. Towards standardization of survey outcome categories and response rate calculations. Res Official Stat. 2002;1:61–84.Google Scholar
  16. Morton LM, Cahill J, Hartge P. Reporting participation in epidemiologic studies: a survey of practice. Am J Epidemiol. 2006;163(3):197–203.CrossRefGoogle Scholar
  17. Nederhof E, Jörg F, Raven D, Veenstra R, Verhulst FC, Ormel J, et al. Benefits of extensive recruitment effort persist during follow-ups and are consistent across age group and survey method. The TRAILS study. BMC Med Res Methodol. 2012;93:3–15.Google Scholar
  18. Nohr EA, Frydenberg M, Henriksen TB, Olsen J. Does low participation in cohort studies induce bias? Epidemiology. 2006;17(4):413–8.CrossRefGoogle Scholar
  19. Rothman KJ, Gallacher JE, Hatch EE. Why representativeness should be avoided. Int J Epidemiol. 2013;42(4):1012–4.CrossRefGoogle Scholar
  20. Schilpzand EJ, Sciberras E, Efron D, Anderson V, Nicholson JM. Improving survey response rates from parents in school-based research using a multi-level approach. PLoS ONE. 2015;10(5):e0126950.CrossRefGoogle Scholar
  21. Schnell R. Nonresponse in Bevölkerungsumfragen: Ausmaß, Entwicklung und Ursachen. Opladen: Leske und Buderich; 1997.CrossRefGoogle Scholar
  22. Schulz KF, Altman DG, Moher D, Group C. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. J Clin Epidemiol. 2010;63(8):834–40.CrossRefGoogle Scholar
  23. Slattery ML, Edwards SL, Caan BJ, Kerber RA, Potter JD. Response rates among control subjects in case-control studies. Ann Epidemiol. 1995;5(3):245–9.CrossRefGoogle Scholar
  24. Stang A. Nonresponse research—an underdeveloped field in epidemiology. Eur J Epidemiol. 2003;18(10):929–31.CrossRefGoogle Scholar
  25. Stang A, Ahrens W, Jöckel KH. Control response proportions in population-based case-control studies in Germany. Epidemiology. 1999;10(2):181–3.CrossRefGoogle Scholar
  26. Stang A, Jöckel KH. Studies with low response proportions may be less biased than studies with high response proportions. Am J Epidemiol. 2004;159(2):204–10.CrossRefGoogle Scholar
  27. Stoop I, Billiet J, Koch A, Fitzgerald R. Improving survey response: lessons learned from the European Social Survey. Chichester: Wiley; 2010.CrossRefGoogle Scholar
  28. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18(6):805–35.CrossRefGoogle Scholar
  29. Wolfenden L, Kypri K, Freund M, Hodder R. Obtaining active parental consent for school-based research: a guide for researchers. Aust N Z J Public Health. 2009;33(3):270–5.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Leibniz Institute for Prevention Research and Epidemiology—BIPSBremenGermany
  2. 2.Faculty of Mathematics and Computer ScienceUniversity of BremenBremenGermany

Personalised recommendations