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基于互联网的 NutriNet-Santé 队列中反应一致性的评估及其参与者特征。

Assessment of response consistency and respective participant profiles in the Internet-based NutriNet-Santé Cohort.

出版信息

Am J Epidemiol. 2014 Apr 1;179(7):910-6. doi: 10.1093/aje/kwt431. Epub 2014 Feb 11.

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.

摘要

虽然基于互联网的流行病学研究的可行性和有效性已经得到证实,但对于此类数据质量的方法学支持仍在不断积累。我们旨在根据参与者提供其 15 位数字的国家识别号码(个人社会保险号码(PSSN))的意愿,识别法国队列成员之间的社会人口统计学差异,并根据社会人口统计学问卷中报告的信息和 PSSN 中反映的信息来评估响应一致性。我们研究了 2009 年至 2013 年间参与基于互联网的前瞻性队列研究 NutriNet-Santé 研究的 100,118 人。年龄在 18 岁及以上、居住在法国并能上网的人有资格参加。通过双侧多项逻辑回归,将数据不一致的参与者的社会人口统计学特征与数据一致的参与者的特征进行比较。共有 84,442 名参与者(84.3%)提供了他们的 PSSN 的前 7 位数字,其中 5,141 名(6.1%)有数据不一致。我们的多变量分析揭示了性别、年龄、教育和就业方面对响应一致性模式的差异。结果支持从大型和多样化的志愿者样本在线获得的社会人口统计学数据的质量。根据响应一致性模式对参与者概况的定量描述可以为电子流行病学的未来方法学工作提供信息。

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