Evidence map›Paper›PMID 27453034›Full record

ArticleApplied clinical informatics2016

Electronic data collection in epidemiological research. The use of REDCap in the Pelotas birth cohorts.

Cauane Blumenberg, Aluísio J D Barros

Abstract read
In one paragraph

Article in Applied clinical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  5. Observational
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  10. Stealthing among university students: associated factors.Revista da Escola de Enfermagem da U S P · 2022
    Article
  11. Article
  12. Article
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  14. Observational
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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

2 authors.

Cauane BlumenbergCauane Blumenberg, Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, Brazil, 1160 Marechal Deodoro St. - 3rd floor, Pelotas, RS, 96020-220, Brazil, Phone: +55 53 32841300, Email: cauane.epi@gmail.com.
Aluísio J D Barros

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesThis paper describes the use of Research Electronic Data Capture (REDCap) to conduct one of the follow-up waves of the 2004 Pelotas birth cohort. The aim is to point out the advantages and limitations of using this electronic data capture environment to collect data and control every step of a longitudinal epidemiological research, specially in terms of time savings and data quality.

methodsWe used REDCap as the main tool to support the conduction of a birth cohort follow-up. By exploiting several REDCap features, we managed to schedule assessments, collect data, and control the study workflow. To enhance data quality, we developed specific reports and field validations to depict inconsistencies in real time.

resultsUsing REDCap it was possible to investigate more variables without significant increases on the data collection time, when comparing to a previous birth cohort follow-up. In addition, better data quality was achieved since negligible out of range errors and no validation or missing inconsistencies were identified after applying over 7,000 interviews.

conclusionsAdopting electronic data capture solutions, such as REDCap, in epidemiological research can bring several advantages over traditional paper-based data collection methods. In favor of improving their features, more research groups should migrate from paper to electronic-based epidemiological research.

Indexed as

Electronic Health RecordsEpidemiologic Research DesignParturitionBrazilCohort StudiesData CollectionFemaleHumansQuality ControlTime Factorselectronic data captureEpidemiologymedical informaticspublic health informaticstranslational research

Identifiers

PMID27453034
PMCPMC5052541

What OpenQuestion holds

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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.