Advancing Randomized Controlled Trials in Pediatric Critical Care: The Perspectives of Trialists
Bibliographic record
Abstract
OBJECTIVES: Clinical research is a complex scientific and social enterprise. Our objective was to identify strategies that pediatric critical care trialists consider acceptable, feasible, and effective to improve the design and conduct randomized controlled trials in pediatric critical care. DESIGN: Qualitative descriptive study using semistructured individual interviews. SUBJECTS: We interviewed 26 pediatric critical care researchers from seven countries who have published a randomized controlled trial (2005-2015). We used purposive sampling to achieve diversity regarding researcher characteristics and randomized controlled trial characteristics. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Most participants (24 [92%]) were from high-income countries, eight (31%) had published more than one randomized controlled trial, 17 (65%) had published a multicenter randomized controlled trial, and eight (31%) had published a multinational randomized controlled trial. An important theme was "building communities"-groups of individuals with similar interests, shared experiences, and common values, bound by professional and personal relationships. Participants described a sense of community as a source of motivation and encouragement and as a means to larger, more rigorous trials, increasing researcher and clinician engagement and maintaining enthusiasm. Strategies to build communities stressed in-person interactions (both professional and social), capable leadership, and trust. Another important theme was "getting started." Participants highlighted the importance of formal research training and high-quality experiential learning through collaboration on other's projects, guided by effective mentorship. Also important was "working within the system"-ensuring academic credit for a range of contributions, not only for the principal investigator role. The longitudinal notion of "building on success" was also underscored as a cross-cutting theme. CONCLUSIONS: Coordinated, deliberate actions to build community and ensure key training and practical experiences for new investigators may strengthen the research enterprise in pediatric critical care. These strategies, potentially in combination with other novel approaches, may vitalize clinical research in this field.
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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 | 0.757 | 0.805 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.011 | 0.047 |
| Scholarly communication | 0.029 | 0.030 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.024 | 0.043 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".