Co-designing and Pilot Testing an Infographic to Support Patients/Families through the REMAP-CAP Consent Process: A Mixed Methods Study Protocol
Bibliographic record
Abstract
Abstract Background: Informed consent is critical to the ethical conduct of clinical research and requires understanding of a trial including its purpose, process, potential risks and benefits, and alternatives to participation. This can be challenging for complex trials, such as platform trials, and in high stress environments, such as the Intensive Care Unit (ICU). REMAP-CAP (Randomized, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia) is a platform trial which studies treatments for ICU patients with community-acquired pneumonia, including COVID-19. Patient/Family Partners (PFP) identified challenges during the REMAP-CAP consent process. Methods: This is a patient-centred co-design study to refine and test an infographic to supplement current REMAP-CAP consent documents. Infographic prototypes were developed by patients, families, and researchers with lived experience in the ICU or with ICU research. We will apply a two-phase exploratory sequential, mixed methods research design. In phase 1 we will conduct focus groups with ICU patients, substitute decision makers (SDMs) and research coordinators (RCs). We will use inductive content analysis to inform infographic refinement, to be pilot tested in phase 2. Phase 2 is a prospective study within a trial (SWAT) at < 5 REMAP-CAP sites. We will collect self-reported data from patients/SDMs and RCs. The primary outcome is feasibility (eligible consent encounters, receipt of infographic, consent to follow-up, completion of follow-up surveys). Data will be integrated to understand if/how quantitative results build upon the qualitatively informed infographic. Discussion: Phase one results will be used to co-design an infographic, directly informed by the perspectives of patients, families and RCs involved in ICU research consent discussions. Results from phase two will determine the feasibility of infographic implementation in REMAP-CAP consent encounters. These feasibility data will inform a larger SWAT to evaluate our consent infographic. If successful, use of a co-designed infographic to support REMAP-CAP consent documents may improve the experience of consent for RCs, patients and their families. Trial Registration: The Northern Ireland Hub for Trials Methodology Research SWAT Repository (SWAT #176)
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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 | 0.174 | 0.188 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".