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

Abstract

Purpose: The purpose of this paper is to provide readers with a comprehensive overview of scholarly work on the depression of informal caregivers through bibliometric and text mining analyses. Methods: A total of 426 articles published between 2000 and 2018 were retrieved from the Clarivate Analytics Web of Science, and computer-aided bibliometric analysis as well as topic modeling based on unsupervised machine learning were conducted on the collection of the data. Findings: Descriptive statistics on the increasing number of publications, network analysis of scientific collaboration between countries, keyword co-occurrence analysis, conceptual structure, and six themes (k= 6) identified through bibliometrics and topic modeling are discussed. Conclusions: Understanding and preventing depression among informal 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. Clinical Relevance: This study will contribute to the field of psychological distress of informal caregivers in looking a big picture of the current position through data and moving forward towards a better direction.

Publication
Issues in Mental Health Nursing
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