Characterizing Research Hotspots and Trends in Simulation-Based Training in Obstetrics and Gynecology 1961-2024: A Bibliometric Analysis
Bibliographic record
Abstract
Background: Simulation-based training (SBT) has long been applied in obstetrics and gynecology (O&G) professional education. However, its current research status and trends remained understudied. This study aimed to examine the research performance and dynamics of SBT in O&G professional education. Methods: A bibliometric analysis was conducted. Systematic searches were performed in the Web of Science. A total of 980 publications were included in the analyses. Summary statistics and visualizations were generated to present research performance and dynamics. A zero-inflated negative binomial regression model was developed to identify factors associated with total citations. Results: The number of publications showed an upward trend between 1961 and 2024, with an annual growth rate of 7.35%. The most productive country was the USA, contributing to 41.84% of total publications. The most productive author was Sorensen JL, accounting for 1.43%. Citations per publication ranged from 0 to 304, with an average of 13.31. The top 10 keywords were simulation, obstetrics, training, education, gynecology, medical education, laparoscopy, simulation training, patient safety, and surgical education. Total citations peaked in 2013 at 1203, while average citations per publication peaked in 2009 at 53.57. The keywords skills, simulation, and performance remained dominating throughout the analyzed period. The research collaboration among the USA, UK, and Canada was predominant. Regression analysis revealed that every additional year since being published, funded research, every additional ten cited references, O&G-oriented research, SCIE-indexed research and every additional ten usage counts since 2013 were significantly associated with higher total citations (all p values < 0.05). Conclusion: Although this research field is progressing rapidly, publications remain insufficient. Future research should focus on objective assessment of SBT in O&G professional education, long-term effectiveness assessment of SBT among O&G trainees, and optimization of implementation of advanced O&G simulators.
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How this classification was reachedexpand
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.309 | 0.213 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads 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".