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Record W2218954088 · doi:10.1136/medethics-2014-102231

Implications of the concept of minimal risk in research on informed choice in clinical practice

2015· article· en· W2218954088 on OpenAlexafffund
Kyoko Wada, Jeff Nisker

Bibliographic record

VenueJournal of Medical Ethics · 2015
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsChildren’s Health Research InstituteVictoria HospitalLondon Health Sciences CentreWestern University
FundersCanadian Institutes of Health Research
KeywordsInformed consentClinical PracticeComputer scienceData scienceMedicinePsychologyAlternative medicineFamily medicinePathology

Abstract

fetched live from OpenAlex

The concept of a minimal risk threshold in research, beneath which exception to informed consent and ethics review processes may occur, has been codified for over 30 years in many national research regulations and by the Council for International Organizations of Medical Sciences. Although minimal risk in research constitutes one of the criteria for allowing waiver of informed consent or modification to the consent process and a large body of literature exists, discussion of a minimal risk threshold in clinical practice has not occurred. One reason for lack of discussion may be that implicit consent is accepted for a wide range of routine clinical practices. Extending the role of minimal risk in research to clinical practice might assist clinicians in identifying circumstances for which implicit consent is indeed sufficient and circumstances in which it is not. Further, concepts from minimal risk in research might assist clinicians regarding when information provision in health promotion is required. We begin by reviewing concepts in both minimal risk in research and informed choice in clinical practice. We then explore how a clinical minimal risk concept may clarify recommendations for information provision in clinical practice and support the patient's informed choice regarding therapeutic and diagnostic procedures and also health promotion. Given that clinical practice involves a broad scope of health information, professional practice guidelines on information provision based on the application of the minimal risk threshold in research could be developed to guide clinicians in what information must be provided to their patients.

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.

How this classification was reachedexpand

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)0.221
metaresearch head score (Gemma)0.941
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2210.941
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.047
Insufficient payload (model declined to judge)0.0000.000

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 head0.864
GPT teacher head0.760
Teacher spread0.104 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2015
Admission routes2
Has abstractyes

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