Prominent themes in shoulder dystocia research: A bibliometric and document-based analysis

被引:1
|
作者
Konac, Ayse [1 ]
Orhan, Fatih [2 ]
机构
[1] Gelisim Univ, Sch Hlth Sci, Istanbul, Turkiye
[2] Univ Hlth Sci, Gulhane Vocat Sch Hlth, Ankara, Turkiye
关键词
co-citation analysis; consolidated themas; co-occurrence analysis; shoulder dystocia; RISK-FACTORS; FETAL MACROSOMIA; MANAGEMENT; DELIVERY; COMPETENCE; PREDICTION; EMERGENCY; MANEUVER; OUTCOMES; INFANTS;
D O I
10.1097/MD.0000000000038903
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background:This study aims to comprehensively examine the academic development of shoulder dystocia (SD) through bibliometric and document analysis and to identify topics that can guide future research.Methods:In this study, performance, co-citation, co-word, and document analyses were used as bibliometric analysis techniques.Results:The study identified 3 main themes in terms of the intellectual structure of Shoulder Dystocia (SD): "Management of SD, Risk Factors and Associated Complications," "Clinical Practices, Birth Abnormalities and Effects of Complications," and "Impact of Education, Clinical Maneuvers and Fetal Health Outcomes." Co-occurrence analysis identified 4 significant themes: "Management and Clinical Practice of SD," "Fetal Macrosomia and Risk Factors," "Obstetric Maneuvers and Brachial Plexus Injury," and "Clinical Trends and Risks in SD." Additionally, ten consolidated themes were identified as a result of thematic coding analysis.Conclusion:Shoulder dystocia remains a critical component of obstetric practice. Themes such as training and simulation, risk factors, and technical and management approaches are consistently emphasized. Technological advances and studies on how machine learning techniques can be used effectively in this field reflect innovative approaches in the scientific literature. This analysis confirms that shoulder dystocia is a complex topic requiring a multidisciplinary approach and that research in this field is constantly evolving.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Prominent Themes and Blind Spots in Diversity and Inclusion Literature: A Bibliometric Analysis
    van Bommel, H. M.
    Hubers, F.
    Maas, K. E. H.
    JOURNAL OF BUSINESS ETHICS, 2024, 192 (03) : 487 - 499
  • [2] Integrated deep learning paradigm for document-based sentiment analysis
    Atandoh, Peter
    Zhang, Fengli
    Adu-Gyamfi, Daniel
    Atandoh, Paul H.
    Nuhoho, Raphael Elimeli
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2023, 35 (07)
  • [3] Searching for a Method to Optimize the Scientific Activities of the Institute Based on Bibliometric Analysis of Research Themes
    Beskaravajnaja, E., V
    Kharybina, T. N.
    SCIENTIFIC AND TECHNICAL INFORMATION PROCESSING, 2021, 48 (02) : 87 - 96
  • [4] Searching for a Method to Optimize the Scientific Activities of the Institute Based on Bibliometric Analysis of Research Themes
    E. V. Beskaravajnaja
    T. N. Kharybina
    Scientific and Technical Information Processing, 2021, 48 : 87 - 96
  • [5] A bibliometric analysis of research on fish and floristic diversity: Trends and themes
    Al-Mutairi, Khalid Awadh
    JOURNAL OF FISHERIES, 2024, 12 (02)
  • [6] Health journalism: a bibliometric analysis of research themes and future directions
    Feng, Shi
    FRONTIERS IN COMMUNICATION, 2024, 9
  • [7] Integrating document-based and knowledge-based models for clinical guidelines analysis
    Georg, Gersende
    Cavazza, Marc
    ARTIFICIAL INTELLIGENCE IN MEDICINE, PROCEEDINGS, 2007, 4594 : 421 - 430
  • [8] Mapping Business Model Research: A Document Bibliometric Analysis
    Belussi, Fiorenza
    Orsi, Luigi
    Savarese, Maria
    SCANDINAVIAN JOURNAL OF MANAGEMENT, 2019, 35 (03)
  • [9] Comparative Analysis between Document-based and Model-based Compliance Management Approaches
    Ghanavati, Sepideh
    Amyot, Daniel
    Peyton, Liam
    RELAW: 2008 REQUIREMENTS ENGINEERING AND LAW, 2008, : 39 - 43
  • [10] Categories, themes and research evolution of the study of digital literacy: a bibliometric analysis
    Wu, Dongping
    Sukumaran, Sheiladevi
    Zhi, Xiaomin
    Zhou, Wenjing
    Li, Lihua
    You, Hongnan
    EDUCATION AND INFORMATION TECHNOLOGIES, 2025, 30 (04) : 4907 - 4931