Research trends and hotspots of COVID-19 impact on sexual function: A bibliometric analysis based on Web of Science
Bibliographic record
Abstract
Background The outbreak of coronavirus disease 2019 (COVID-19) has brought indelible harms to the world and aroused great concern worldwide. This paper aims to analyze the impact of COVID-19 on sexual function using bibliometrics, and summarize research hotspots in this field. Methods Relevant publications concerning the impact of COVID-19 on sexual function in the Web of Science collection database (WoSCC) between January 1, 2020 and March 12, 2022 were screened and analyzed by bibliometric analysis using the visualization software CiteSpace and VOSviewer. Results Of the 1,054 publications screened, the United States (US) contributed the most (398/37.8%), followed by the United Kingdom (UK) (119/11.3%). Among all institutions, the University of Toronto in Canada enjoyed the largest number of publications (30), and Johns Hopkins University in the US enjoyed the highest frequency of citation (235). The journal INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH published the largest number of studies in this field (31), and the most-cited journal was LANCET. “Chow, Eric,” “Ong, Jason J,” and “Stephenson, Rob” tied for first place in publications (8), and “Fish, Jessica N.” enjoyed the highest number of citations (99). Burstness analysis of references and keywords showed that the developing research trends in this field mainly focused on “sexual transmission” and “angiotensin converting-enzyme 2 (ACE2)” during the COVID-19 pandemic. Conclusion The impact of COVID-19 on sexual function remains an urgent concern at present, and the management of sexual health during the pandemic needs to be further improved. More frequent and deeper cooperation between countries and institutions is required in future. Meanwhile, searching for more evidence on whether COVID-19 can achieve sexual transmission and the pathophysiological mechanisms underlying the impact of COVID-19 on sexual function remains a focus of research in the coming years.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.133 | 0.162 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".