Delaying and withholding interventions: ethics and the stepped wedge trial
Bibliographic record
Abstract
Ethics has been identified as a central reason for choosing the stepped wedge trial over other kinds of trial designs. The potential advantage of the stepped wedge design is that it provides all arms of the trial with the active intervention over the course of the study. Some groups receive it later than others, but the study intervention is not withheld from any group. This feature of the stepped wedge design seems particularly ethically advantageous in two instances: (1) when the study intervention appears especially likely to be effective and (2) when the consequences of not receiving the intervention may be dire. But despite an increase in the use of the stepped wedge design and appeals to its ethical superiority as the motivation for its selection, there has been limited attention to the stepped wedge trial in the ethics literature. In the following, I examine whether there are persuasive ethical reasons to prefer or to require a stepped wedge trial. I argue that while the stepped wedge design is ethically permissible, it is not morally superior to other kinds of trials. To this end, I examine the ethical justification for providing, withholding, and delaying interventions in research.
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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 | 0.214 | 0.381 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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; the direct Gemma label and the distilled Codex classifier 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".