Gathering the Stakeholder’s Perspective: Experiences and Opportunities in Rare Genetic Disease Research
Bibliographic record
Abstract
BACKGROUND: Research participant feedback is rarely collected; therefore, investigators have limited understanding regarding stakeholders' (affected individuals/caregivers) motivation to participate. Members of the Genes to Mental Health Network (G2MH) surveyed stakeholders affected by copy number variants (CNVs) regarding perceived incentives for study participation, opinions concerning research priorities, and the necessity for future funding. Respondents were also asked about feelings of preparedness, research burden, and satisfaction with research study participation. METHODS: Modified validated surveys were used to assess stakeholders´ views across three domains: (1) Research Study Enrollment, Retainment, Withdrawal, and Future Participation; (2) Overall Research Experience, Burden, and Preparedness; (3) Research Priorities and Obstacles. Top box score analyses were performed. RESULTS: A total of 704 stakeholders´ responded from 29 countries representing 55 CNVs. The top reasons for initial participation in the research included reasons related to education and altruism. The top reasons for leaving a research study included treatment risks and side effects. The importance of sharing research findings and laboratory results with stakeholders was underscored by participants. Most stakeholders reported positive research experiences. CONCLUSIONS: This study provides important insight into how individuals and families affected with a rare CNV feel toward research participation and their overall experience in rare disease research. There are clear targets for areas of improvement for study teams, although many stakeholders reported positive research experiences. Key findings from this international survey may help advance collaborative research and improve the experience of participants, investigators, and other stakeholders moving forward.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".