Development of a Research Participants’ Perception Survey to Improve Clinical Research
Bibliographic record
Abstract
INTRODUCTION: Clinical research participants' perceptions regarding their experiences during research protocols provide outcome-based insights into the effectiveness of efforts to protect rights and safety, and opportunities to enhance participants' clinical research experiences. Use of validated surveys measuring patient-centered outcomes is standard in hospitals, yet no instruments exist to assess outcomes of clinical research processes. METHODS: We derived survey questions from data obtained from focus groups comprised of research participants and professionals. We assessed the survey for face/content validity, and privacy/confidentiality protections and fielded it to research participants at 15 centers. We conducted analyses of response rates, sample characteristics, and psychometrics, including survey and item completion and analysis, internal consistency, item internal consistency, criterion-related validity, and item usefulness. Responses were tested for fit into existing patient-centered dimensions of care and new clinical research dimensions using Cronbach's alpha coefficient. RESULTS: Surveys were mailed to 18,890 individuals; 4,961 were returned (29%). Survey completion was 89% overall; completion rates exceeded 90% for 88 of 93 evaluable items. Questions fit into three dimensions of patient-centered care and two novel clinical research dimensions (Cronbach's alpha for dimensions: 0.69-0.85). CONCLUSIONS: The validated survey offers a new method for assessing and improving outcomes of clinical research processes.
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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 | 0.073 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".