Implications of the concept of minimal risk in research on informed choice in clinical practice
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.512 | 0.546 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.197 |
| Scholarly communication | 0.024 | 0.059 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.027 | 0.040 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".