Updated research trend and clustering algorithm on virtual reality and pulmonary rehabilitation: Scopus-based bibliometric and visual analysis

Abstract

Background: Virtual reality (VR) is a new innovative technology that can enhance intervention and should promote the effectiveness of rehabilitation, but there is a lack of scientific evidence on the clustering and topic research trend, especially on VR and pulmonary rehabilitation (PR). More evidence about network clusters and trends will encourage the research in the future. Objective: This study aimed to explore, identify, cluster, and forecast analysis for the research trend of VR and PR from the research articles on the SCOPUS database. Materials and methods: In this study, the search terms “virtual reality” AND “pulmonary rehabilitation” were extracted from specific English research articles published on the SCOPUS database between 2013-2023. RStudio software was used to perform bibliometric and visual analysis. During the analysis in the bibliometric tool, the normalization process with Salton’s Cosine and network clustering via trend topic with the Walktrap algorithm was analyzed before specific visualization with the network clustering mapping, Treemap, and trend topic line by KamadaKawai layout algorithm. Results: From the 1,396 articles on “VR” published between 2010 and 2023, there were 13 research articles on “VR AND PR” published between 2013 and 2023. The bibliometric result from 13 articles showed total of 36 subdisciplines correlated networks among virtual reality (20, 7%), male (16, 6%), female (15, 5%), aged (12, 4%), chronic obstructive lung disease (12, 4%), exercise (11, 4%), human (10, 4%), humans (10, 4%), middle-aged (10, 4%), quality of life (10, 4%), article (9, 3%), pulmonary rehabilitation (9, 3%), controlled study (8, 3%), adult (6, 2%), chronic obstructive (6, 2%), clinical article (6, 2%), forced expiratory volume (6, 2%), pulmonary disease (6, 2%), randomized controlled trial (6, 2%), and forced vital capacity (5, 2%), etc., respectively. Three network clusters were reported after the normalization process and clustering evaluation by factorial analysis. The first cluster was composed of virtual reality, male, female, aged, chronic obstructive lung disease, exercise, human, humans, middle-aged, quality of life, article, pulmonary rehabilitation, controlled study, adult, chronic obstructive, clinical article, forced expiratory volume, randomized controlled trial, forced vital capacity, six-minute walk test, depression, technology, telerehabilitation, breathing exercise, Covid-19, dyspnea, functional status, hospital patient, and physical activity, respectively. The second cluster consisted of procedure and exercise therapy, and the last cluster consisted of exercise tolerance, lung, treatment outcome, health program, and convalescence. Finally, trend research topics were presented in virtual reality, male, female, aged, chronic obstructive lung disease, human, exercise, quality of life, and middle-aged, respectively, in 2023. Conclusion: Therefore, the contribution from data analysis in this article can identify the clustering and trend topics of VR, chronic obstructive lung disease, aging participants, exercise, and quality of life in future research.