Publication Trends of Pediatric and Adult Randomized Controlled Trials in General Medical Journals, 2005–2018: A Citation Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Policy has been developed to promote the conduct of high-quality pediatric randomized controlled trials (RCTs). Whether these strategies have influenced publication trends in high-impact journals is unknown. We aim to evaluate characteristics, citation patterns, and publication trends of pediatric RCTs published in general medical journals (GMJs) compared with adult RCTs over a 13-year period. Studies were identified using Medline, and impact metrics were collected from Web of Science and Scopus. All RCTs published from 2005–2018 in 7 GMJs with the highest impact factors were identified for analysis. A random sample of matched pediatric and adult RCTs were assessed for publication characteristics, academic and non-academic citation. Citations were counted from publication until June 2019. Among 4146 RCTs, 2794 (67.3%) enrolled adults, 591 (14.2%) enrolled children, and 761 RCTs (18.3%) enrolled adult and pediatric patients. Adult RCTs published in GMJs grew by 5.1 publications per year (95% CI: 3.3–6.9), while the number of pediatric RCTs did not show significant change (−0.4 RCTs/year, 95% CI: −1.4–0.6). Adult RCTs were cited more than pediatric RCTs (median(IQR): 29.9 (68.5–462.8) citations/year vs. 13.2 (6.8–24.9) citations/year; p < 0.001); however, social media attention was similar (median(IQR) Altmetric Attention Score: 37 (13.75–133.8) vs. 26 (6.2–107.5); p = 0.25). Despite policies which may facilitate conduct of pediatric RCTs, the publishing gap in high-impact GMJs is widening.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.322 | 0.500 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.005 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.000 |
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 it