An Exploratory Study of the Research on Caregiver Depression: Using Bibliometrics and LDA Topic Modeling

Purpose: The purpose of this paper is to provide readers with a comprehensive overview of scholarly work on the depression of caregivers using bibliometrics and text mining. Methods: A total of 426 articles published between 2000 and 2018 were retrieved from the Clarivate Analytics Web of Science, and then, computer-aided bibliometric analysis as well as Latent Dirichlet Allocation (LDA) topic modeling were conducted on the collection of the data. Results: Descriptive statistics on the increasing number of publications, network analysis of scientific collaboration between countries, word co-occurrence analysis, conceptual structure, and six latent topics (k = 6) identified are discussed. Conclusions: Preventing or managing depression among caregivers is a growing field with the highest priority for the aging population. In the future, collaborating between countries and reflecting cultural backgrounds in caregiver depression research are needed. This study is expected to contribute to the field of psychological distress of caregivers in looking a big picture of the current position through data-driven analysis and moving forward towards a better direction.