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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Mapping the research landscape of aging population: a bibliometric study
Li Han Ting1, Mei Peng Low1, Aidi Ahmi2
1Department of International Business, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Kajang, Selangor, Malaysia.
Background And Objectives:
The aging population is a critical global issue shaped by demographic transitions. Despite growing research, a comprehensive bibliometric analysis of trends, contributors, and thematic evolution is lacking. This study aims to map the research landscape on population ageing from 1940 to 2024, identifying publication trends, key contributors, dominant themes, and emerging technological interventions.
Research Design And Methods:
Following PRISMA guidelines, a systematic search was conducted in the Scopus database. After screening titles, abstracts, and full texts according to predefined criteria, 2,568 publications were included. Bibliometric analyses were performed using biblioMagika, VOSviewer, and Biblioshiny to examine publication growth, citation patterns, co-authorship networks, and keyword co-occurrence. Sensitivity analyses using year-by-year preliminary data were employed to assess trend robustness.
Results:
Findings reveal sustained growth in ageing-related research through the sensitivity analysis, reflecting global interest. Key themes unveiled in this study are health and chronic diseases (e.g., geriatric care, longevity), Cognitive health and technology integration (e.g., AI, smart homes), Socioeconomic aspects (e.g., pensions, intergenerational equity). Also, Artificial intelligence and smart technologies emerged as pivotal for older adult care innovation. The United States, United Kingdom, and Canada led in contributions, with interdisciplinary collaboration driving advancements.
Discussion And Implications:
The study reveals the need for interdisciplinary research to address ageing challenges, offering policymakers and stakeholders a roadmap for future priorities. Emerging technologies like AI present transformative opportunities but require ethical and equitable implementation. Limitations include database coverage biases. Future research should explore multiple bases, regional disparities and practical applications of technological solutions.
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