Evidence map›Paper›PMID 33475521›Full record

ReviewJMIR public health and surveillance2021

Toward a Working Definition of eCohort Studies in Health Research: Narrative Literature Review.

Vasileios Nittas, Milo Alan Puhan, Viktor von Wyl

Abstract readReview
In one paragraph

Review in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Vasileios NittasEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-6685-8275
Milo Alan PuhanEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-4721-1879
Viktor von WylEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-8754-9797

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe wide availability of internet-connected devices and new sensor technologies increasingly infuse longitudinal observational study designs and cohort studies. Simultaneously, the costly and time-consuming nature of traditional cohorts has given rise to alternative, technology-driven designs such as eCohorts, which remain inadequately described in the scientific literature.

objectiveThe aim of this study was to outline and discuss what may constitute an eCohort, as well as to formulate a first working definition for health researchers based on a review of the relevant literature.

methodsA two-staged review and synthesis process was performed comparing 10 traditional cohorts and 10 eCohorts across the six core steps in the life cycle of cohort designs.

resultseCohorts are a novel type of technology-driven cohort study that are not physically linked to a clinical setting, follow more relaxed and not necessarily random sampling procedures, are primarily based on self-reported and digitally collected data, and systematically aim to leverage the internet and digitalization to achieve flexibility, interactivity, patient-centeredness, and scalability. This approach comes with some hurdles such as data quality, generalizability, and privacy concerns.

conclusionseCohorts have similarities to their traditional counterparts; however, they are sufficiently distinct to be treated as a separate type of cohort design. The novelty of eCohorts is associated with a range of strengths and weaknesses that require further exploration.

Indexed as

Cohort StudiesDigital TechnologyInternetResearch DesignBiomedical ResearchHumanscohortsdigital epidemiologyeCohortseHealth

Identifiers

PMID33475521
PMCPMC7861999

What OpenQuestion holds

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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.