Pan Ding , Kyungsik Kim , Tianyu Li , Wang Yuan
DOI:10.46695/ASCS.4.2.2
Abstract
PURPOSE This study aimed to analyze core keywords of knowledge structure to explore the research trend of Yoga therapy, so as to understand the interaction between sub-areas research in Yoga therapy. METHOD This study searched the journal articles on the Web of Science to identify research trends related to Yoga therapy. To achieve this goal, keyword network analysis was performed for 226 papers related to the studies of Yoga therapy, which were published between 1992 and 2022. The Netminer was used to conduct the keyword network analysis. RESULT The analysis result showed that the keywords concerning patient, treatment, effect, intervention, health, quality, and anxiety have continuously occurred in the past 30 years; thus, they can be considered the main concepts symbolizing the research in Yoga therapy. In addition, a few keywords only appeared in a certain period; for example, intensity and posture appeared before 2011, but team, education, increase, interaction, and methodology evolved only in the 2020s, which perhaps implies that a new research field related to Yoga therapy has sprung-up. Finally, based on the results of the cohesion group analysis, five sub-research domains were identified as follows: Group 1, comprising 12 keywords with a focus on 'therapist' and 'strategy'; Group 2, made up of 13 keywords with emphasis on 'technique' and 'survivor'; Group 3, consisting of 20 keywords centered around 'well-being' and 'symptom'; Group 4, incorporating 19 keywords with a concentration on 'woman' and 'treatment'; and Group 5, encompassing 17 keywords centered on 'weight' and 'system'. CONCLUSION Keyword network analysis is employed to investigate the research trend in Yoga therapy. These keywords contribute to the formation of an intellectual structure, playing a vital role in facilitating more detailed exploration of sub-research areas related to Yoga therapy in the future.
Key Words
Yoga therapy, Research trend, Keyword network, Centrality