109: Advancing Child Health Research Through Evidence-Based Guidance for Pediatric Clinical Trial Protocols
Bibliographic record
Abstract
Complete reporting of clinical trial protocols is essential to allow stakeholders to critically assess trial methodology, ethics, and validity. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) initiative aims to standardize protocol reporting guidelines and tackle inadequate reporting. However, SPIRIT does not offer guidance on the scientific, ethical and safety considerations unique to trials with children. To address this gap in guidance and advance child health research, we present SPIRIT-Children (SPIRIT-C): An evidence-based SPIRIT extension for pediatric clinical trial protocols. Potential reporting items to be included in the SPIRIT-C extension were identified through environmental scans of existing reporting recommendations and a three-stage Delphi process. A systematic literature review was conducted to gather empirical evidence regarding the importance of potential reporting items in pediatric clinical trial protocols, as well as to identify additional reporting recommendations. The results of the Delphi process and systematic review, along with feedback from youth advisors, were presented to an international group of pediatric clinical trial experts and stakeholders, who subsequently reached consensus on potential reporting items using nominal group techniques. The SPIRIT-C pediatric protocol reporting guideline includes nine additional reporting items that are recommended be addressed in all pediatric clinical trial protocols (Table 1). SPIRIT-C is the first evidence-based reporting guideline for pediatric clinical trial protocols, filling a gap in existing research guidance, thus helping researchers to improve their trials' impact and child health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.578 | 0.760 |
| Meta-epidemiology (narrow) | 0.003 | 0.006 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.009 | 0.016 |
| Research integrity | 0.022 | 0.027 |
| Insufficient payload (model declined to judge) | 0.021 | 0.029 |
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".