Barriers and Facilitators to Cancer Clinical Trial Participation: Perspectives of Patients in the ICON-3 Practice-Based Research Network, Nigeria
Bibliographic record
Abstract
PURPOSE: Africa faces a growing burden of cancer yet remains under-represented in global cancer clinical trials. This disparity limits the generation of population-specific evidence needed to improve cancer outcomes. Recruitment and retention in cancer clinical trials are particularly challenging because of various systemic and individual barriers in Nigeria. This study explores patients' perspectives on barriers and facilitators to recruitment and retention in cancer clinical trials. METHODS: A convergent parallel mixed-methods design was used, which comprised a cross-sectional survey and a descriptive qualitative approach. Participants were recruited from multiple oncology centers and secondary facilities within Nigeria's ICON-3 Practice-Based Research Network. Quantitative data were collected through interviewer-administered questionnaires, whereas qualitative data were gathered via semistructured interviews and analyzed thematically. RESULTS: A total of 317 patients participated in the quantitative survey, 18 of whom participated in interviews. Barriers included limited understanding of clinical trials, logistical challenges such as transportation and visit frequency, distrust in researchers and the health care system, and lack of family support. Facilitators included effective communication, incentives, flexible research visits, and culturally tailored interventions. CONCLUSION: To optimize cancer clinical trial participation in low-resource settings, interventions must be tailored to local contexts, addressing structural and cultural barriers. Enhanced communication, community involvement, and supportive policies can significantly improve trial participation and outcomes.
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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 | 0.022 | 0.174 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".