Evaluating the impact of a SIMPlified LaYered consent process on recruitment of potential participants to the <i>Staphylococcus aureus</i> Network Adaptive Platform trial: study protocol for a multicentre pragmatic nested randomised clinical trial (SIMPLY-SNAP trial)
Bibliographic record
Abstract
INTRODUCTION: Informed consent forms (ICFs) for randomised clinical trials (RCTs) can be onerous and lengthy. The process has the potential to overwhelm patients with information, leading them to miss elements of the study that are critical for an informed decision. Specifically, overly long and complicated ICFs have the potential to increase barriers to trial participation for patients with mild cognitive impairment, those who do not speak English as a first language or among those with lower medical literacy. In turn, this can influence trial recruitment, completion and external validity. METHODS AND ANALYSIS: Network Adaptive Platform (SNAP) trial. We will randomise potentially eligible participants of the SNAP trial 1:1 to a full-length ICF or a SIMPlified LaYered (SIMPLY) consent process where basic information is summarised with embedded hyperlinks to supplemental information and videos. The primary outcome is recruitment into the SNAP trial. Secondary outcomes include patient understanding of the clinical trial, patient and research staff satisfaction with the consent process, and time taken for consent. As an exploratory outcome, we will also compare measures of diversity (eg, gender, ethnicity), according to the consent process randomised to. The planned sample size will be 346 participants. ETHICS AND DISSEMINATION: The study has been approved by the ethics review board (Sunnybrook Health Sciences Research Ethics Board) at sites in Ontario. We will disseminate study results via the SNAP trial group and other collaborating clinical trial networks. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT06168474; www. CLINICALTRIALS: gov).
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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 | 0.211 | 0.280 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.055 | 0.014 |
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".