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Introduction: This study presents a global research scenario in the broad domain of osteoarthritis (OA) research, using quantitative and qualitative publication and citation indicators. Methods: The study is based on 45,368 global publications, sourced from the Scopus bibliographical database, covering three decades (1994–2023). We studied the performance of the top 12 developed and top 12 developing countries. The key countries, organizations and authors at national and international levels were identified. The broad subject areas and key journals contributing to global OA research were delineated, besides identifying the broad characteristics of highly cited papers in the field. Results: The United States and China were the most productive countries, while the Netherlands and Canada made the largest citation impact. Harvard Medical School and the University of Sydney made the most contribution, while Boston University and Pfizer Inc., USA registered the highest citation impact. Hunter DJ and Guermazi A were the most productive authors, while Lohmander LS, and Hochberg MC registered the highest citation impact. Osteoarthritis and Cartilage (n = 4879) and Annals of the Rheumatic Diseases (n = 786) published the maximum papers, while Arthritis and Rheumatism and Nature Reviews Rheumatology registered the largest citation impact. The highly cited papers with 100 or more citations constituted 6.25% of the total publications. Conclusions: There has been a systematic growth of publications on OA. The research on OA was mainly done in developed countries, with the maximum publications coming from the United States of America, China and Canada. The most impactful publications on OA were from the Netherlands, Canada and the United States of America. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is commonly defined as a transitional subclinical state between normal aging and dementia. A growing body of research indicates that health behaviors may play a protective role against cognitive decline and could potentially slow down the progression from MCI to dementia. The aim of this study is to conduct a bibliometric analysis of literature focusing on health behaviors and MCI to summarize the factors and evidence regarding the influence of health behaviors on MCI. Methods: The study performed a bibliometric analysis by retrieving publications from the Science Citation Index and Social Sciences Citation Index subdatabases within the Web of Science Core Collection. Utilizing VOSviewer and CiteSpace software, a total of 2,843 eligible articles underwent co-citation, cokeywords, and clustering analyses. This methodology aimed to investigate the current status, trends, major research questions, and potential future directions within the research domain. Results: The bibliometric analysis indicates that research on healthy behaviors in individuals with MCI originated in 2002 and experienced rapid growth in 2014, reflecting the increasing global interest in this area. The United States emerged as the primary contributor, accounting for more than one-third of the total scientific output with 982 articles. Journals that published the most articles on MCI-related health behaviors included "Journal of Alzheimer's Disease," "Neurobiology of Aging," "Frontiers in Aging Neuroscience," and other geriatricsrelated journals. High-impact papers identified by VOSviewer predominantly cover concepts related to MCI, such as diagnostic criteria, assessment, and multifactorial interventions. Co-occurrence keyword analysis highlights five research hotspots in health behavior associated with MCI: exercise, diet, risk factors and preventive measures for dementia, cognitive decline-related biomarkers, and clinical trials. Conclusion: This study provides a comprehensive review of literature on health behavior in individuals with MCI, emphasizing influential documents and journals. It outlines research trends and key focal points, offering valuable insights for researchers to comprehend significant contributions and steer future studies. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to analyze publications on artificial intelligence (AI) for falls in older people from a bibliometric perspective. Methods: The Web of Science database was searched for titles of English‐language articles containing the words "artificial intelligence," "deep learning," "machine learning," "natural language processing,", "neural artificial network," "fall," "geriatric," "elderly," "aging," "older," and "old age." An R‐based application (Biblioshiny for bibliometrics) and VOSviewer software were used for analysis. Results: Thirty‐seven English articles published between 2018 and 2024 were included. The year 2023 is the year with the most publications with 16 articles. The most productive research field was "Engineering Electrical Electronic" with seven articles. The most productive country was the United States, followed by China. The most common words were "injuries," "people," and "risk factors." Conclusion: Publications on AI and falls in the elderly are both few in number and the number of publications has increased in recent years. Future research should include relevant analyses in scientific databases, such as Scopus and PubMed. [ABSTRACT FROM AUTHOR]