Informed consent for paediatric clinical trials in Europe
Bibliographic record
Abstract
OBJECTIVE: Paediatric clinical trials are often conducted as multinational trials. Informed consent or assent is part of the ethics committee approval for clinical trials. The consent requirements vary between countries due to national laws and regulations, which are not harmonised in Europe. These discrepancies can present challenges for paediatric clinical trials. The aim of this study was to assemble these consent and assent requirements across the European Economic Area. The collated national requirements have not been publicly available before, despite a real need for this data. METHODS: National consent and assent requirements for paediatric clinical trials were analysed and collated for 25 European Union Member States and 2 European Free Trade Association countries until the end of 2014. The data were retrieved from existing databases and through communication with the competent authorities and selected ethics committees. Results from a literature search for international or national guidelines, declarations and conventions and academic societies' publications served as comparison material. RESULTS: Consent and assent requirements are heterogeneous across these countries. We compiled our findings in 'The Informed Consent and Assent Tool Kit', a table including 27 national consent and assent requirements listed by individual country. CONCLUSIONS: Wide variation in paediatric consents and assents presents challenges for multinational paediatric trials in Europe. The toolkit is available for all those involved in paediatric clinical trials and ethics committees, providing a new platform for proactive feedback on informed consent requirements, and may finally lead to a needed harmonisation process, including uniform standards accepted across Europe.
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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 | 0.379 | 0.509 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".