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Assessment of Response Consistency and Respective Participant Profiles in the Internet-based NutriNet-Santé Cohort.
- Source :
- American Journal of Epidemiology; Apr2014, Vol. 179 Issue 7, p910-916, 7p
- Publication Year :
- 2014
-
Abstract
- 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 one's 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-Santé 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- DATABASE evaluation
EPIDEMIOLOGY research methodology
CONFIDENCE intervals
EPIDEMIOLOGY
INTERNET
LONGITUDINAL method
RESEARCH methodology
MULTIVARIATE analysis
QUESTIONNAIRES
RESEARCH funding
LOGISTIC regression analysis
DATA analysis
QUANTITATIVE research
SECONDARY analysis
SOCIOECONOMIC factors
CONTENT mining
DESCRIPTIVE statistics
Subjects
Details
- Language :
- English
- ISSN :
- 00029262
- Volume :
- 179
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- American Journal of Epidemiology
- Publication Type :
- Academic Journal
- Accession number :
- 95094570
- Full Text :
- https://doi.org/10.1093/aje/kwt431