Bibliometric Analysis of Alzheimer's Disease and Depression

Abstract

Background: The link between Alzheimer's disease and depression has been confirmed by clinical and epidemiological research. Therefore, our study examined the literary landscape and prevalent themes in depression-related research works on Alzheimer's disease through bibliometric analysis. Methods: Relevant literature was identified from the Web of Science core collection. Bibliometric parameters were extracted, and the major contributors were defined in terms of countries, institutions, authors, and articles using Microsoft Excel 2019 and VOSviewer. VOSviewer and CiteSpace were employed to visualize the scientific networks and seminal topics. Results: The analysis of literature utilised 10,553 articles published from 1991 until 2023. The three countries or regions with the most publications were spread across the United States, China, and England. The University of Toronto and the University of Pittsburgh were the major contributors to the institutions. Lyketsos, Constantine G., Cummings, JL were found to make outstanding contributions. Journal of Alzheimer's Disease was identified as the most productive journal. Furthermore, “Alzheimer’s”, “depression”, “dementia”, and “mild cognitive decline” were the main topics of discussion during this period. Limitations: Data were searched from a single database to become compatible with VOSviewer and CiteSpace, leading to a selection bias. Manuscripts in English were considered, leading to a language bias. Conclusion: Articles on “Alzheimer’s” and “depression” displayed an upward trend. The prevalent themes addressed were the mechanisms of depression-associated Alzheimer's disease, the identification of depression and cognitive decline in the early stages of Alzheimer's, alleviating depression and improving life quality in Alzheimer's patients and their caregivers, and diagnosing and treating neuropsychiatric symptoms in Alzheimer. Future research on these hot topics would promote understanding in this field.