Child vs Adult Randomized Controlled Trials in Specialist Journals
Bibliographic record
Abstract
OBJECTIVE: To compare secular trends in the age representation of published randomized controlled trials (RCTs) in specialty journals during a period of 20 years. DATA SOURCE: A validated electronic search strategy using Ovid MEDLINE was conducted to identify RCTs published in the years 1985 through 2005. STUDY SELECTION: The publications retrieved were subdivided into age-specific groups: adults, children, both adults and children, and studies with no age group identified. Within 31 specialties, we chose up to 5 specialty journals and 5 pediatric specialty journals. MAIN OUTCOME MEASURE: Number of RCTs targeting children compared with adults over time. Linear trends were identified using regression modeling, and an interaction term was included to compare rates of increase between age groups. RESULTS: A total of 174 unique journals with 43 326 unique RCTs with age-specific categorization were included. Adult RCTs increased by 90.5 RCTs per year (95% confidence interval [CI], 78-103), which was significantly higher than either pediatric RCTs, which rose by 16.9 RCTs per year (95% CI, 12-22) or RCTs involving both children and adults, which rose by 22.7 RCTs per year (95% CI, 10-35). Twenty-four of 31 specialties (77%) demonstrated a greater rise in the number of published RCTs per year involving adults than those enrolling children. CONCLUSION: Adult RCT publications are increasing at a faster rate than pediatric RCTs in almost all specialties.
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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 | 0.138 | 0.444 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.018 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".