Supporting Trial Participation in People with the Huntington’s Gene: A Patient-Centered, Theory-Guided Survey of Barriers and Enablers
Bibliographic record
Abstract
BACKGROUND: Under-recruitment regularly impedes clinical trials, leading to wasted resources and opportunity costs. Methods for designing trial participation strategies rarely consider behavior change theory. OBJECTIVE: Informed by the Theoretical Domains Framework, we identified factors important to participating in Huntington's disease research and provide examples of how such a theory-informed approach can make specific suggestions about how to design targeted recruitment strategies. METHODS: We identified a range of trial participation barriers and enablers based on interviews of key informants and implemented an online survey of members of the Huntington's disease community, asking them to rate the extent to which different factors would affect likelihood to participate in a generic Huntington's disease trial. RESULTS: From 4,195 members, we received 323 responses and 243 completed surveys (323/4,195 or 8% participation, 243/323 or 75% completion). Respondents endorsed 9 barriers and 23 enablers relevant to trial participation. Most frequently endorsed barriers were travel to the study site (69%), worry about unknown side effects (65%), trial documents being difficult to understand (64%), and participation affecting other activities (49%). Enablers included optimism about likelihood of trial participation leading to a cure (98%), helping others (98%), contributing to science (97%), and having helpful people available to help with the participation decision (89%). CONCLUSION: Our theory-informed survey to identify barriers to and enablers of Huntington's disease trial participation identified 32 factors, from 13 theoretical domains relevant to trial participation, and suggests effective approaches for improving trial participation and patient experience.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".