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Record W4283069378 · doi:10.1001/amajethics.2022.518

Why We Need Stricter Oversight of Research Involving Human Subjects Affected by Conflict

2022· review· en· W4283069378 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe AMA Journal of Ethic · 2022
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of WaterlooCentre for Global Health ResearchHospital for Sick Children
FundersDirektoratet for UtviklingssamarbeidHospital for Sick ChildrenInternational Development Research CentreUNICEFBill and Melinda Gates Foundation
KeywordsWaiverResearch ethicsPolitical scienceInformed consentGuidelineConflict of interestPublic relationsMedicineLawAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

Background: Despite the potential for ethical violations when research is conducted with conflict-affected populations, there is limited information on how and the extent to which ethical considerations specific to doing research with these populations are integrated into national and international ethics guidelines and, in turn, how these guidelines translate into practice. This study aims to fill this gap by systematically analyzing the existing research ethics guidance of humanitarian donor countries, conflict-affected countries, United Nations (UN) agencies, and funding agencies, as well as ethics reporting in research articles on conflict-affected populations published in peer-reviewed journals. Methods: A review of 32 research ethics guidelines and granting regulations from UN agencies, donor agencies, and governments was conducted, and the reporting of ethics procedures and practices of 498 articles published in peer-reviewed journals was analyzed. Results: Of the reviewed guidelines and regulations, 87.5% did not mention conflict-affected populations, and only one guideline (3.1%) catalogued any of the complexities of conducting research with conflict-affected populations. Among the reviewed published research articles on conflict-affected populations, obtaining ethics approval or a waiver was reported in only 48.2% of articles, and obtaining informed consent was reported in only 46.6% of studies. In the subset of articles that did not report receiving ethics approval, 88.5% were published in journals that required reporting of ethics approval. Conclusions: This study highlighted a gap in current research guidelines and granting regulations on the ethical conduct of research with conflict-affected populations and illustrated the need for such guidance to be integrated into governing documents and research practices. Moreover, this study demonstrated that there is a need for stricter enforcement of reporting requirements by journals to ensure that research with conflict-affected populations meets the required ethical standard. Partnerships among institutional ethics committees, donor agencies, and journals can ensure that the rights of conflict-affected populations are protected.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.052
metaresearch head score (Gemma)0.058
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.038
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.761
GPT teacher head0.639
Teacher spread0.122 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it