Pragmatic design and inclusion of patient–partner representatives improves participant experience in clinical research
Bibliographic record
Abstract
Objectives: Patient engagement in the design and implementation of clinical trials is necessary to ensure that the research is relevant and responsive to patients. The PREP-IT trials, which include 2 pragmatic trials that evaluate different surgical preparation solutions in orthopaedic trauma patients, followed the patient-centered outcomes research (PCOR) methodology throughout the design, implementation, and conduct. We conducted a substudy within the PREP-IT trials to explore participants' experiences with trial participation. Methods: At the final follow-up visit (12 months after their fracture), patients participating in the PREP-IT trials were invited to participate in the substudy. After providing informed consent, participants completed a questionnaire that asked about their experience and satisfaction with participating in the PREP-IT trials. Descriptive statistics are used to report the findings. Results: Four hundred two participants participated in the substudy. Most participants (394 [98%]) reported a positive experience, and 376 (94%) participants felt their contributions were appreciated. The primary reasons for participation were helping future patients with fracture (279 [69%]) and to contribute to science (223 [56%]). Two hundred seventeen (46%) participants indicated that their decision to participate was influenced by the minimal time commitment. Conclusions: Most participants reported a positive experience with participating in the PREP-IT trials. Altruism was the largest motivator for participating in this research. Approximately half of the participants indicated that the pragmatic, low-participant burden design of the trial influenced their decision to participate. Meaningful patient engagement, a pragmatic, and low-burden protocol led to high levels of participant satisfaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".