European Journal of Epidemiology

, Volume 22, Issue 12, pp 831–837 | Cite as

Feasibility of recruiting a birth cohort through the Internet: the experience of the NINFEA cohort

  • Lorenzo Richiardi
  • Iacopo Baussano
  • Loredana Vizzini
  • Jeroen Douwes
  • Neil Pearce
  • Franco Merletti
Methods

Abstract

The NINFEA cohort is an Italian birth cohort aiming at recruiting pregnant women through the Internet and following-up their children. To understand whether Internet-based recruitment was feasible we started a pilot in July 2005 targeted to pregnant women visiting the hospitals of the city of Turin (900,000 inhabitants), where we advertised the study. For this purpose we constructed a website (www.progettoninfea.it), with on-line questionnaires to be completed during pregnancy and at 6 and 18 months after delivery. Participants’ characteristics were compared with those of women giving birth in Turin, which are routinely released as individual anonymous records. We also compared complete with partial respondents. We also carried out a survey of 122 women giving birth in the main Turin obstetric hospital to estimate the proportion of pregnant women with access to the Internet and awareness of the NINFEA cohort. By December 2006, we had recruited 670 women. Participation was associated with being older, a university graduate, primiparous and born in Italy. Complete response (n = 633) was associated with being primiparous and participation after the first trimester. In the survey, 66% (95% confidence interval: 56–74%; n = 80) of the women had access to the Internet and 42% (33–51%; n = 51) were aware of the study; 6.5% (2.9–12.5%; n = 8) had participated in the NINFEA cohort. Our study indicates that recruitment of an Internet-based birth cohort is feasible. As with many other types of birth cohort study, the participants are a self-selected sample. To minimise selection bias analyses should therefore be limited to internal comparisons.

Keywords

Longitudinal study Internet Bias Birth cohort 

References

  1. 1.
    Ekman A, Litton JE. New times, new needs; e-epidemiology. Eur J Epidemiol 2007;22:285–92.PubMedCrossRefGoogle Scholar
  2. 2.
    Baer A, Saroiu S, Koutsky LA. Obtaining sensitive data through the Web: an example of design and methods. Epidemiology 2002;13:640–45.PubMedCrossRefGoogle Scholar
  3. 3.
    Braithwaite D, Emery J, De Lusignan S, Sutton S. Using the Internet to conduct surveys of health professionals: a valid alternative? Fam Pract 2003;20:545–51.PubMedCrossRefGoogle Scholar
  4. 4.
    Wolters FL, van Zeijl G, Sijbrandij J, et al. Internet-based data inclusion in a population-based European collaborative follow-up study of inflammatory bowel disease patients: description of methods used and analysis of factors influencing response rates. World J Gastroenterol 2005;11:7152–8.PubMedGoogle Scholar
  5. 5.
    Link MW, Mokdad AH. Alternative modes for health surveillance surveys: an experiment with web, mail, and telephone. Epidemiology 2005;16:701–4.PubMedCrossRefGoogle Scholar
  6. 6.
    Balter KA, Balter O, Fondell E, Lagerros YT. Web-based and mailed questionnaires: a comparison of response rates and compliance. Epidemiology 2005;16:577–9.PubMedCrossRefGoogle Scholar
  7. 7.
    Silver RC, Holman EA, McIntosh DN, Poulin M, Gil-Rivas V. Nationwide longitudinal study of psychological responses to September 11. JAMA 2002;288:1235–44.PubMedCrossRefGoogle Scholar
  8. 8.
    Wang J, Etter JF. Administering an effective health intervention for smoking cessation online: the international users of Stop-Tabac. Prev Med 2004;39:962–8.PubMedCrossRefGoogle Scholar
  9. 9.
    Tate DF, Jackvony EH, Wing RR. Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: a randomized trial. JAMA 2003;289:1833–6.PubMedCrossRefGoogle Scholar
  10. 10.
    Ekman A, Dickman PW, Klint A, Weiderpass E, Litton JE. Feasibility of using web-based questionnaires in large population-based epidemiological studies. Eur J Epidemiol 2006;21:103–11.PubMedCrossRefGoogle Scholar
  11. 11.
    Smith B, Smith TC, Gray GC, Ryan MA. When Epidemiology meets the Internet: web-based surveys in the millennium cohort study. Am J Epidemiol 2007. In press.Google Scholar
  12. 12.
    Marquet RL, Bartelds AI, van Noort SP, et al. Internet-based monitoring of influenza-like illness (ILI) in the general population of the Netherlands during the 2003–2004 influenza season. BMC Public Health 2006;6:242.PubMedCrossRefGoogle Scholar
  13. 13.
    Ross MW, Mansson SA, Daneback K, Cooper A, Tikkanen R. Biases in internet sexual health samples: comparison of an internet sexuality survey and a national sexual health survey in Sweden. Soc Sci Med 2005;61:245–52.PubMedCrossRefGoogle Scholar
  14. 14.
    Ritter P, Lorig K, Laurent D, Matthews K. Internet versus mailed questionnaires: a randomized comparison. J Med Internet Res 2004;6:e29.PubMedCrossRefGoogle Scholar
  15. 15.
    Gosling SD, Vazire S, Srivastava S, John OP. Should we trust web-based studies? A comparative analysis of six preconceptions about internet questionnaires. Am Psychol 2004;59:93–104.PubMedCrossRefGoogle Scholar
  16. 16.
    Kogevinas M, Andersen AM, Olsen J. Collaboration is needed to co-ordinate European birth cohort studies. Int J Epidemiol 2004;33:1172–3.PubMedCrossRefGoogle Scholar
  17. 17.
    Eaton W. The logic for a conception-to-death cohort study. Ann Epidemiol 2002;12:445–51.PubMedCrossRefGoogle Scholar
  18. 18.
    Frank J, Di Ruggiero E, McInnes RR, Kramer M, Gagnon F. Large life-course cohorts for characterizing genetic and environmental contributions: the need for more thoughtful designs. Epidemiology 2006;17:595–8.PubMedCrossRefGoogle Scholar
  19. 19.
    Boldrini R, Di Cesare M, Pennazza F. Certificato di assistenza al parto (CeDAP). Analisi dell’evento nascita—Anno 2002. Roma: Ministero della Salute, Dipartimento della Qualità, Direzione Generale Sistema Informativo, Ufficio di Direzione Statistica; 2004.Google Scholar
  20. 20.
    Armitage P, Berry G, Matthews JNS. Statistical methods in medical research, 4th ed. Oxford: Blackwell Science; 2002.Google Scholar
  21. 21.
    Nohr EA, Frydenberg M, Henriksen TB, Olsen J. Does low participation in cohort studies induce bias? Epidemiology 2006;17:413–8.PubMedCrossRefGoogle Scholar
  22. 22.
    Hernan MA, Hernandez-Diaz S, Robins JM. A structural approach to selection bias. Epidemiology 2004;15:615–25.PubMedCrossRefGoogle Scholar
  23. 23.
    Greenland S. Response and follow-up bias in cohort studies. Am J Epidemiol 1977;106:184–7.PubMedGoogle Scholar
  24. 24.
    Ekman A, Klint A, Dickman PW, Adami HO, Litton JE. Optimizing the design of web-based questionnaires—experience from a population-based study among 50,000 women. Eur J Epidemiol 2007;22:293–300.PubMedCrossRefGoogle Scholar
  25. 25.
    Etter JF, Neidhart E, Bertrand S, Malafosse A, Bertrand D. Collecting saliva by mail for genetic and cotinine analyses in participants recruited through the Internet. Eur J Epidemiol 2005;20:833–8.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Lorenzo Richiardi
    • 1
  • Iacopo Baussano
    • 1
    • 2
  • Loredana Vizzini
    • 1
  • Jeroen Douwes
    • 3
  • Neil Pearce
    • 3
  • Franco Merletti
    • 1
  1. 1.Cancer Epidemiology Unit, CeRMS and Center for Oncologic PreventionUniversity of TurinTurinItaly
  2. 2.Division of Epidemiology, Public Health and Primary CareImperial College LondonLondonUK
  3. 3.Centre for Public Health ResearchMassey University Wellington CampusWellingtonNew Zealand

Personalised recommendations