Assessing the Impact of u‐link.care: Implementation of a Pediatric Cancer Clinical Trials Finder Website to Improve Healthcare Provider Knowledge and Identify Barriers to Enrollment
Bibliographic record
Abstract
BACKGROUND: The Canadian u-link.care website is an online database of early phase clinical trials in Canada for children with cancer. It includes information regarding trial design, study objectives, and eligibility, comprising both scientific and family-friendly content. It was launched in September 2021. The objective of this study is to assess the impact of u-link.care on healthcare providers' (HCP) knowledge of phase 1 and 2 early phase clinical trial options available in Canada for children with cancer. PROCEDURE: Surveys with multiple choice and short answer questions relating to the website were distributed to HCP from Canadian pediatric oncology centers in May 2021 (survey 1, prior to the launch) and in January 2023 (survey 2, 16 months postlaunch). RESULTS: We received significant feedback from HCP (attending physicians, fellows, nurse practitioners, physician assistants, clinical assistants, and research nurses) across Canada, with 53 responses across 13 centers (survey 1) and 59 responses across 15 centers (survey 2). Most providers felt knowledgeable about early phase clinical trials and comfortable counseling their patients. Barriers to referral and enrollment were identified including lack of trial availability/knowledge, cost, and distance. Survey 2 showed that 45.7% of surveyed HCP used u-link.care for information on innovative therapies. 87.5% of HCP who used the website declared it increased their knowledge. CONCLUSION: u-link.care has become an important tool for Canadian pediatric oncology HCP. Still, the lack of trial availability and high cost of travel to relevant centers continue to be the leading obstacles to early phase clinical trials access. Further initiatives are needed to address these barriers.
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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 | 0.024 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".