Implementing a New Common Rule Requirement for Informed Consent: A Randomized Trial on Adult Asthma Patients
Bibliographic record
Abstract
Objectives. To determine how the format of a clinical trial informed consent document can affect participants’ retention of enrollment-relevant information. Background. Recent changes to the US Federal Common Rule require informed consent documents for clinical trials to be concise and start with the information most relevant for enrollment decisions. However, there is limited guidance on how to identify this information or evaluate its impact. Design. Participants with a self-reported asthma diagnosis were randomized to one of five versions of the informed consent document for a clinical trial of an injectable asthma product: the original, full-length document; a concise version, removing information identified by asthma patients in an earlier study as not relevant to their enrollment decisions; an interactive version, where participants self-navigated to the information they chose; a reordered version, moving up information deemed more relevant for enrollment in an earlier study; and a highlights version, following the suggested revised Common Rule structure, starting with a summary of enrollment-relevant information based on patient ratings. Knowledge acquisition was evaluated with a knowledge test, with submeasures for information that had high and low relevance for enrollment decisions. Results. Participants who saw the highlights (“Common Rule”) version were more likely to answer questions about high enrollment-relevant information correctly than were participants who saw the full-length version (65% v 59%, P = 0.0105). Participants who saw the other revised versions did not perform significantly differently from the full-length version. Conclusions. An informed consent document designed to implement revised US Federal Common Rule requirements performed better than other designs, in terms of readers retaining information relevant for clinical trial enrollment, as characterized by potential trial participants in a separate study.
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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 | 0.237 | 0.380 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".