Evidence map›Paper›PMID 27756715›Full record

ArticleJMIR public health and surveillance2016

Lessons Learned From Methodological Validation Research in E-Epidemiology.

Emmanuelle Kesse-Guyot, Karen Assmann, Valentina Andreeva, Katia Castetbon, Caroline Méjean, Mathilde Touvier, Benoît Salanave, Valérie Deschamps, Sandrine Péneau, Léopold Fezeu and 4 more

Erratum issuedAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Trial
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  3. Observational
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  15. Review
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  17. Clustering of Small Territories Based on Axes of Inequality.International journal of environmental research and public health · 2022
    Article
  18. Article
  19. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Emmanuelle Kesse-GuyotÉquipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, COMUE Sorbonne Paris Cité, Inserm (U1153), Inra (U1125), Cnam, Université Paris 13, Bobigny, France. e.kesse@eren.smbh.univ-paris13.fr.ORCID 0000-0002-9715-3534
Valentina AndreevaORCID 0000-0001-9480-5210
Valérie DeschampsORCID 0000-0002-9000-0180

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional 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.

objectiveThe objective of this viewpoint is to summarize findings from methodological studies carried out in the NutriNet-Santé study, a French Web-based cohort study.

methodsOn 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.

resultsOverall, 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.

conclusionsGiven 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.

Indexed as

bias, epidemiologycohort studies

Identifiers

PMID27756715
PMCPMC5087563

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.