Top 100 Cited Papers on Premenstrual Syndrome/Premenstrual Dysphoric Disorder: A Bibliometric Study
Bibliographic record
Abstract
Background: Premenstrual syndrome/premenstrual dysphoric disorder is a serious condition affecting women worldwide, causing clinically significant distress or interference. Therefore, solving these diseases has become the utmost concern worldwide, culminating in numerous studies. In this study, we performed bibliometric analysis on the 100 most cited papers with the aim of identifying research hot spots and trends in this field. Methods: We screened the Science Citation Index Expanded (SCIE) of Web of Science (WOS) to identify the top 100 cited studies on PMS/PMDD. Next, we analyzed relevant literature from various journals, countries/regions, institutions, authors, and keywords. Finally, we used VOSviewer and Citespace software to generate knowledge maps and identify hot spots and trends. Results: The top 100 highly cited studies were published in 55 journals, between 1999 and 2017, across 24 countries/regions around the world. Most articles were published in Obstetrics and Gynecology, whereas Psych neuroendocrinology had the largest average number of citations per paper. The United States had the highest number of publications, followed by England, Canada, and Sweden. The top three institutions that published the highly cited literature were the University of Pennsylvania, Yale University, and National Institute of Mental Health (NIMH). Obstetrics, Gynecology, Psychiatry, and Reproductive Biology were the main research directions, whereas the top 10 Co-occurrence of Keywords included double-blind, fluoxetine, efficacy, prevalence, epidemiology, phase sertraline treatment, depression, progesterone, placebo, and placebo-controlled trial. Results from cluster analysis indicated that more comprehensive epidemiology and steroid pathogenesis have gradually become the hot spots and trends. Conclusion: These findings demonstrated that bibliometric analysis can intuitively and rapidly reveal the frontiers and hot spots of research in PMS/PMDD. Notably, epidemiology, steroid pathogenesis, GABAA receptor delta subunits, and double-blind placebo-controlled trials are potential areas of focus for future research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.055 | 0.077 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".