Published randomized controlled trials in Otolaryngology: 2016-2020
Bibliographic record
Abstract
Importance: To provide a current evaluation of bibliometric trends in the Otolaryngology literature focused on randomized controlled trials (RCTs). RCTs hold an important role in research as bias controlled assessments of clinical interventions. Objective: The purpose of this study is to evaluate the proportion of published RCTs in the Otolaryngology literature. Design: Quality Improvement scoping bibliometric review. Setting: Published articles in eight Otolaryngology journals from January 1, 2016 - December 31, 2020. Main Outcomes and Measures: Included articles were categorized as a RCT, secondary research, other clinical research, case report, primary basic science, or other study type. Additionally, studies were categorized as American, Canadian, British, or other international origin according to the corresponding author’s institutional address. The proportion of published RCTs were compared by national origin and to an earlier bibliometric analysis investigating Otolaryngology journal publications from 2008-2012 using Pearson’s Chi-Squared testing with Bonferroni correction. Results: A total of 6797 articles were reviewed and included for analysis. There was a significant difference in the proportion of RCTs published by national origin, 1.3% USA, 2.2% Canada, 2.7% UK, 3.4% other (p < 0.01). There was a significant decrease in the proportion of RCTs published from 2008-12 to 2016-2020 (3.1% vs. 2.3% respectively, p < 0.01). Conclusions: Although the current study analyzed only a select sample of all Otolaryngology research output, this study suggests that North American researchers are publishing less RCTs than researchers in other countries. Moreover, RCTs are declining as a proportion of the published Otolaryngology literature over time, which is a threat to the evidence base for current and future Otolaryngological practice.
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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 | 0.217 | 0.592 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.077 | 0.078 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".