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Ethics, big data and computing in epidemiology and public health

Overview of attention for article published in Annals of Epidemiology, May 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

policy
2 policy sources
twitter
8 X users
facebook
2 Facebook pages

Readers on

mendeley
251 Mendeley
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Article details
Title
Ethics, big data and computing in epidemiology and public health
Published in
Annals of Epidemiology, May 2017
DOI 10.1016/j.annepidem.2017.05.002
Pubmed ID
Authors
Abstract

This article reflects on the activities of the Ethics Committee of the American College of Epidemiology (ACE). Members of the Ethics Committee identified an opportunity to elaborate on knowledge gained since the inception of the original Ethics Guidelines published by the ACE Ethics and Standards of Practice Committee in 2000. The ACE Ethics Committee presented a symposium session at the 2016 Epidemiology Congress of the Americas in Miami on the evolving complexities of ethics and epidemiology as it pertains to "big data." This article presents a summary and further discussion of that symposium session. Three topic areas were presented: the policy implications of big data and computing, the fallacy of "secondary" data sources, and the duty of citizens to contribute to big data. A balanced perspective is needed that provides safeguards for individuals but also furthers research to improve population health. Our in-depth review offers next steps for teaching of ethics and epidemiology, as well as for epidemiological research, public health practice, and health policy. To address contemporary topics in the area of ethics and epidemiology, the Ethics Committee hosted a symposium session on the timely topic of big data. Technological advancements in clinical medicine and genetic epidemiology research coupled with rapid advancements in data networks, storage, and computation at a lower cost are resulting in the growth of huge data repositories. Big data increases concerns about data integrity; informed consent; protection of individual privacy, confidentiality, and harm; data reidentification; and the reporting of faulty inferences.

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 251 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 251 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 32 13%
Student > Postgraduate 32 13%
Student > Ph. D. Student 29 12%
Researcher 27 11%
Student > Bachelor 24 10%
Other 50 20%
Unknown 57 23%
Readers by discipline
Readers by discipline Count As %
Computer Science 45 18%
Medicine and Dentistry 36 14%
Social Sciences 18 7%
Nursing and Health Professions 16 6%
Biochemistry, Genetics and Molecular Biology 11 4%
Other 54 22%
Unknown 71 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 December 2019.
All research outputs
#3,906,168
of 28,583,110 outputs
Outputs from Annals of Epidemiology
#475
of 2,199 outputs
Outputs of similar age
#60,189
of 333,544 outputs
Outputs of similar age from Annals of Epidemiology
#6
of 24 outputs
Altmetric has tracked 28,583,110 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,199 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,544 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.