Research Participation in Inflammatory Bowel Disease Studies: What Do Patients Want?
Bibliographic record
Abstract
Background: We aimed to determine patient perspectives on inflammatory bowel disease (IBD) research participation and potential changes related to the COVID pandemic experience. Methods: Participants of the population-based University of Manitoba IBD Research Registry were surveyed March 2022 to March 2023. The survey inquired about views on IBD research participation in the pre-, peri- and post-COVID era. Questions included aspects of participation from home or in-person, potential reimbursement, results reporting, and study design. We determined a rank order of reasons for research participation. We assessed willingness to participate in 5 research genres: clinical trials, biospecimen collection research, research involving colonoscopies, research accessing medical records, and research with access to records and samples. Results: Of 3018 invitees, 1105 (36.6%) completed the survey. Two-thirds reported that pre-pandemic they were unlikely to participate in placebo-controlled clinical trials, and nearly half would participate in a trial if guaranteed to receive active drug. The most important aspect impacting on clinical trial participation was understanding the potential side effects (81%). Post-COVID, 20%-30% reported that their interest in research participation decreased, 15%-20% reported that their interest had increased, with the majority (55%-60%) indicating no change in research participation interest. About 80% would participate in observational research. Payment for participation was not a significant motivator for most. Conclusions: We found a low rate of interest in participating in placebo-controlled IBD clinical trial research but nearly 50% would participate in clinical trial research receiving active drug and 80% would participate in observational research. Research participation interest, however, was further lessened by the COVID pandemic.
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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 | 0.034 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".