Evidence map›Paper›PMID 34779661›Full record

ArticleJournal of empirical research on human research ethics : JERHRE

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study.

Agata Ferretti, Marcello Ienca, Minerva Rivas Velarde, Samia Hurst, Effy Vayena

Abstract read
In one paragraph

Article in Journal of empirical research on human research ethics : JERHRE. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Big Data in Laboratory Medicine-FAIR Quality for AI?Diagnostics (Basel, Switzerland) · 2022
    Review
  13. Article
  14. Article
  15. Article
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

5 authors.

Agata FerrettiHealth Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland.ORCID 0000-0001-6716-5713
Marcello IencaHealth Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland.
Minerva Rivas VelardeDepartment of Radiology and Medical Informatics, Faculty of Medicine, 27212University of Geneva, Switzerland.
Samia HurstInstitute for Ethics, History, and the Humanities, Faculty of Medicine, 27212University of Geneva, Switzerland.
Effy VayenaHealth Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

Indexed as

Big DataEthics Committees, ResearchEthics, ResearchHumansSwitzerlandUncertaintybig databiomedical researchethicsIRBsresearch ethicsresponsible research

Identifiers

PMID34779661
PMCPMC8721531

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.