Journal
AMERICAN JOURNAL OF EPIDEMIOLOGY
Volume 179, Issue 7, Pages 910-916Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kwt431
Keywords
cohort studies; data quality; e-epidemiology; epidemiologic methods; general population; Internet; prospective studies; response consistency
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Funding
- French Ministry of Health (DGS)
- French Institute for Health Surveillance (INVS)
- National Institute for Prevention and Health Education (INPES)
- Foundation for Medical Research (FRM)
- National Institute for Health and Medical Research (INSERM)
- National Institute for Agricultural Research (INRA)
- National Conservatory of Arts and Crafts (CNAM)
- University of Paris 13
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Whereas the feasibility and effectiveness of Internet-based epidemiologic research have been established, methodological support for the quality of such data is still accumulating. We aimed to identify sociodemographic differences among members of a French cohort according to willingness to provide part of ones 15-digit national identification number (personal Social Security number (PSSN)) and to assess response consistency based on information reported on the sociodemographic questionnaire and that reflected in the PSSN. We studied 100,118 persons enrolled in an Internet-based prospective cohort study, the NutriNet-Sant Study, between 2009 and 2013. Persons aged 18 years or more who resided in France and had Internet access were eligible for enrollment. The sociodemographic profiles of participants with discordant data were compared against those of participants with concordant data via 2-sided polytomous logistic regression. In total, 84,442 participants (84.3) provided the first 7 digits of their PSSN, and among them 5,141 (6.1) had discordant data. Our multivariate analysis revealed differences by sex, age, education, and employment as regards response consistency patterns. The results support the quality of sociodemographic data obtained online from a large and diverse volunteer sample. The quantitative description of participant profiles according to response consistency patterns could inform future methodological work in e-epidemiology.
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