Assessing Research Participants’ Perceptions of their Clinical Research Experiences
Bibliographic record
Abstract
INTRODUCTION: Participants' perceptions of their research experiences provide valuable measures of ethical treatment, yet no validated instruments exist to measure these experiences. We conducted focus groups of research participants and professionals as the initial step in developing a validated instrument. METHODS: Research participants enrolled in 12 focus groups, consisting of: (1) individuals with disorders undergoing interventions; (2) in natural history studies; or (3) healthy volunteers. Research professionals participated in six separate groups of: (1) institutional review board members, ethicists, and Research Subject Advocates; (2) research nurses/coordinators; or (3) investigators. Focus groups used standard methodologies. RESULTS: Eighty-five participants and 29 professionals enrolled at eight academic centers. Altruism and personal relevance of the research were commonly identified motivators; financial compensation was less commonly mentioned. Participants were satisfied with informed consent processes but disappointed if not provided test results, or study outcomes. Positive relationships with research teams were valued highly. Research professionals were concerned about risks, undue influence, and informed consent. CONCLUSIONS: Participants join studies for varied, complex reasons, notably altruism and personal relevance. They value staff relationships, health gains, new knowledge, and compensation, and expect professionalism and good organization. On the basis of these insights, we propose specific actions to enhance participant recruitment, retention, and satisfaction.
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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 | 0.027 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".