Are pragmatism and ethical protections in clinical trials a zero-sum game?
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials with pragmatic intent aim to generate evidence that directly informs clinical decisions. Some have argued that the ethical protection of informed consent can be in tension with the goals of pragmatism. But the impact of other ethical protections on trial pragmatism has yet to be explored. PURPOSE: In this article, we analyze the relationship between additional ethical protections for vulnerable participants and the degree of pragmatism within the PRagmatic Explanatory Continuum Indicator Summary-2 (PRECIS-2) domains of trial design. METHODS: We analyze three example trials with pragmatic intent that include vulnerable participants. CONCLUSION: The relationship between ethical protections and trial pragmatism is complex. In some cases, additional ethical protections for vulnerable participants can promote the pragmatism of some of the PRECIS-2 domains of trial design. When designing trials with pragmatic intent, researchers ought to look for opportunities wherein ethical protections enhance the degree of pragmatism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.547 | 0.936 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.006 | 0.023 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".