Evaluating Strength of Evidence of Pediatric Otolaryngology Research Literature: A 20‐Year Review
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Quantity and quality of Otolaryngology-Head and Neck Surgery (OTL-HNS) research are increasing, yet patterns within Pediatric OTL-HNS publications are unknown. This study examines trends in the level of evidence of pediatric OTL-HNS articles over a 20-year period to quantify the growth and characterize contributing factors. STUDY DESIGN: Review article. METHODS: A retrospective review was conducted on 12 peer-reviewed OTL-HNS journals at three time-points: 1996, 2006, and 2016. Pediatric-specific OTL-HNS journals were selected; all were among the top 10 highest impact factor journals, with one pediatric-specific and one Canadian journal. Publication details, author characteristics, and study focus were collected. Papers were classified based on the Oxford Centre for Evidence-Based Medicine Levels of Evidence by two independent reviewers. RESULTS: Of the 1,733 articles reviewed, 727 met inclusion criteria. A greater absolute number of pediatric OTL-HNS articles were published over the years studied: from 95 in 1996 to 359 in 2016 (P < .001). As well, the absolute number of high-quality studies has increased over the study period, from 28 articles in 1996 to 100 articles in 2016. However, the relative percentage of high-quality papers remained stable between 27.9% and 32.2% with an average of 29.7% (P = .89). Higher impact factor journals did not tend to publish higher-quality pediatric OTL-HNS articles (P = .48). CONCLUSIONS: Over the past 20 years, there is no appreciable improvement in the proportion of high-quality publications in pediatric OTL-HNS; however, there is an overall greater number of high-quality papers within OTL-HNS literature. These findings likely relate to challenges of research within pediatric surgical specialties. LEVEL OF EVIDENCE: NA Laryngoscope, 132:1869-1876, 2022.
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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 | 0.030 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.044 | 0.034 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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; 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".