Advanced consent for participation in acute care randomised control trials: protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: Informed consent is essential to clinical research, though obtaining informed consent for participation in research for emergency conditions is challenging. Adapted consent methods include consent from a substitute-decision maker, deferral of consent and waiver of consent. A novel approach is to use advanced consent, where a potential participant provides consent in the present in the event that they become eligible for enrolment into a future study. This scoping review will map and synthesise the literature on the use of advanced consent for participation and enrolment in randomised control trials for emergency conditions. METHODS AND ANALYSIS: Guided by Arksey and O'Malley's scoping review methodology framework, we will search electronic databases (Medline, Embase, Web of Science and the Cochrane Register of Clinical Trials), the grey literature sources and reference lists of relevant studies. Eligible studies will include English language articles that discuss, examine or employ the use of advanced consent for enrolment in randomised control trials, specifically related to emergency conditions or emergency treatment. Diverse types of articles will be eligible for inclusion, including peer-reviewed qualitative and quantitative studies such as randomised control trials, observational studies, surveys, systematic reviews, as well as narrative reviews and ethics papers. Studies will be screened by two independent reviewers to determine eligibility for inclusion. Data on bibliographic information, study characteristics and methodology, and reported results, specifically author disposition, will be extracted and described using qualitative analysis. ETHICS AND DISSEMINATION: Formal ethics review is not required as primary data will not be collected. The findings of this study will be disseminated through a peer-reviewed publication. The findings of this study will help identify knowledge gaps that may guide areas for future research and may aid in the design of future clinical trials using advanced consent.
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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 | 0.190 | 0.223 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.143 | 0.041 |
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".