Evidence map›Paper›PMID 31909724›Full record

ArticleJournal of medical Internet research2020

Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research.

Edmund W J Lee, Kasisomayajula Viswanath

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  12. Clinical research in the community.Hematology. American Society of Hematology. Education Program · 2023
    Article
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  16. Article
  17. Understanding the effects of message cues on COVID-19 information sharing on Twitter.Journal of the Association for Information Science and Technology · 2022
    Article
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  19. Article
  20. Review
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.

Edmund W J LeeDana-Farber Cancer Institute, Boston, MA, United States.ORCID 0000-0003-0536-2898
Kasisomayajula ViswanathDana-Farber Cancer Institute, Boston, MA, United States.ORCID 0000-0002-4795-5803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities.

Indexed as

AbsenteeismBig DataHealthcare DisparitiesHumansMedical Informaticsartificial intelligencebig datadigital divideelectronic health recordshealth disparitieshealth informaticsmobile healthsocial mediawearable electronic devices

Identifiers

PMID31909724
PMCPMC6996749

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.