Purpose: Endometriosis is a chronic inflammatory disease affecting reproductive-age women, often associated with pelvic pain, reduced quality of life, and complex treatment needs. Despite growing research interest, the thematic, structural, and collaborative aspects of this field remain poorly understood. Therefore, this study evaluates the scientific literature on endometriosis, chronic pelvic pain, pain management, and quality of life through bibliometric analysis, with the aim of identifying research trends, collaboration patterns, and thematic concentrations within the field. Methods: A total of 297 scientific publications (197 original research articles and 100 review articles) published between January 1, 2014, and December 31, 2024, were retrieved from the Web of Science Core Collection database. The included publications were analyzed using the VOSviewer 1.6.20 software. Visualizations were generated for keyword co-occurrence, citation analysis, author collaboration, document clustering, and international cooperation between countries. Results: The most frequently studied themes were “endometriosis,” “pelvic pain,” and “quality of life.” Topics such as pain, depression, and psychosocial impacts were identified as central in the literature. The most highly cited publications were by Dunselman et al. (2014) and Chapron et al. (2019), while the United States, the United Kingdom, and Canada emerged as the leading countries in scientific output. Notably, contributions from Türkiye have shown a marked increase in recent years. Conclusion: This study reveals that the endometriosis literature has evolved toward a holistic, biopsychosocial approach, with increasing interdisciplinary collaboration and growing attention to psychosocial interventions. The findings offer valuable insights for setting research priorities and guiding health policy development.
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Analyzing shared references across papers
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Nermin Altunbaş
Nurdan Kaya Yılmaz
Sabuncuoglu Serefeddin Health Sciences
Ondokuz Mayıs University
Sivas Cumhuriyet Üniversitesi
Building similarity graph...
Analyzing shared references across papers
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Altunbaş et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69f6e6ab8071d4f1bdfc76bf — DOI: https://doi.org/10.55895/sshs.1808169