Evidence map›Paper›PMID 40658781›Full record

ArticleEthics & human research

Our Theater of Anonymity.

Sara Meeder, Megan Doerr

Abstract read
In one paragraph

Article in Ethics & human research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Ethical Considerations for Clinical Data Sharing in Craniofacial Research: Recommendations From a Multidisciplinary Working Group.The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2026
    Article
  2. Article
  3. Article
  4. Our Theater of Anonymity.Ethics & human research
    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

2 authors.

Sara MeederAssistant vice president of research administration at Maimonides Health.
Megan DoerrDirector at Sage Bionetworks.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ethics review boards are increasingly asked to review big health data research proposals using a regulatory framework written prior to the current era of machine learning and artificial intelligence. Traditional consideration of individual identifiability does not account for the growing recognition that almost all data can be reidentified. This leaves the research ethics community performing a "theater of anonymity": weighing benefit versus risk on the inclusion of participant identifiers alone. The wider research community, including U.S. federal agencies, is pushing for greater transparency and data sharing, stretching the current definition of identifiability to the breaking point. Additionally, shifting attitudes on the balance between privacy and research benefit may make a project more acceptable to individuals and communities than to the ethics boards designed to serve them. Reviewing the human research community's historical and current understanding of identity in terms of research, risk, benefit, and consent may point toward a need for a change in how consent is conceived. Particularly in the context of consent for big health data research, the research ethics community may need to shift its focus from solely considering individuals toward actively considering the interests of the communities most likely to be affected by the research.

Indexed as

Big DataConfidentialityData AnonymizationEthics Committees, ResearchInformation DisseminationPrivacyEthics, ResearchHumansInformed ConsentUnited Statesbig health data researchdeidentified dataethics review boardshuman research ethicsidentifiability

Identifiers

PMID40658781
PMCPMC12258614

What OpenQuestion holds

Textmetadata
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.