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Lessons Learned From Methodological Validation Research in E-Epidemiology

机译:从电子流行病学中的方法验证研究中汲取的经验教训

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Background: Traditional epidemiological research methods exhibit limitations leading to high logistics, human, and financial burden. The continued development of innovative digital tools has the potential to overcome many of the existing methodological issues. Nonetheless, Web-based studies remain relatively uncommon, partly due to persistent concerns about validity and generalizability. Objective: The objective of this viewpoint is to summarize findings from methodological studies carried out in the NutriNet-Santé study, a French Web-based cohort study. Methods: On the basis of the previous findings from the NutriNet-Santé e-cohort (150,000 participants are currently included), we synthesized e-epidemiological knowledge on sample representativeness, advantageous recruitment strategies, and data quality. Results: Overall, the reported findings support the usefulness of Web-based studies in overcoming common methodological deficiencies in epidemiological research, in particular with regard to data quality (eg, the concordance for body mass index [BMI] classification was 93%), reduced social desirability bias, and access to a wide range of participant profiles, including the hard-to-reach subgroups such as young (12.30% [15,118/122,912], 25 years) and old people (6.60% [8112/122,912], ≥65 years), unemployed or homemaker (12.60% [15,487/122,912]), and low educated (38.50% [47,312/122,912]) people. However, some selection bias remained (78.00% (95,871/122,912) of the participants were women, and 61.50% (75,590/122,912) had postsecondary education), which is an inherent aspect of cohort study inclusion; other specific types of bias may also have occurred. Conclusions: Given the rapidly growing access to the Internet across social strata, the recruitment of participants with diverse socioeconomic profiles and health risk exposures was highly feasible. Continued efforts concerning the identification of specific biases in e-cohorts and the collection of comprehensive and valid data are still needed. This summary of methodological findings from the NutriNet-Santé cohort may help researchers in the development of the next generation of high-quality Web-based epidemiological studies.
机译:背景:传统流行病学研究方法展示了导致高物流,人类和金融负担的局限性。持续开发创新的数字工具有可能克服许多现有的方法问题。尽管如此,基于网络的研究仍然相对罕见,部分原因是持续对有效性和概括性的担忧。目的:这一观点的目的是总结一项法国基于Web的队列研究中的Nutrinet-Santé研究中进行的方法学研究的结果。方法:在Nutrinet-SantéE-Cohort(目前包括150,000名参与者)的先前发现的基础上,我们综合了关于样本代表性,有利的招聘策略和数据质量的电子流行病学知识。结果:总体而言,报告的发现支持基于网络的研究的有用性克服流行病学研究中的常见方法缺陷,特别是关于数据质量(例如,体重指数的一致性[BMI]分类为93%),减少社会偏转性偏见,并获得广泛的参与者概况,包括难以到达的亚组,如年轻(12.30%[15,118 / 122,912],<25岁)和老年人(6.60%[8112 / 122,912], ≥65岁),失业或家庭人(12.60%[15,487 / 122,912]),受过低等教育(38.50%[47,312 / 122,912])人。然而,一些选择偏见(78.00%(95,871 / 122,912,92,92,912)的参与者是妇女,61.50%(75,590 / 122,912)有职业教育,是队列研究纳入的固有方面;还可以发生其他特定类型的偏差。结论:鉴于社会地层迅速增长的互联网进入,招聘具有多样化的社会经济型材和健康风险暴露的参与者是非常可行的。仍然需要继续努力识别E-COSHORTS中的特定偏见以及集合的全面和有效数据。本发明的Nutrinet-SantéCohort的方法论结果摘要可能有助于研究人员在开发下一代高质量的基于Web的流行病学研究。

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