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KMID : 0869120210230030170
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기초간호자연과학회지
2021 Volume.23 No. 3 p.170 ~ p.179
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Research Trend on Diabetes Mobile Applications: Text Network Analysis and Topic Modeling
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Park Seung-Mi
Kwak Eun-Ju
Kim Young-Ji
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Abstract
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Purpose: The aim of this study was to identify core keywords and topic groups in the ‘Diabetes mellitus and mobile applications’ field of research for better understanding research trends in the past 20 years.
Methods: This study was a text-mining and topic modeling study including four steps such as ‘collecting abstracts’, ‘extracting and cleaning semantic morphemes’, ‘building a co-occurrence matrix’, and ‘analyzing network features and clustering topic groups’.
Results: A total of 789 papers published between 2002 and 2021 were found in databases (Springer). Among them, 435 words were extracted from 118 articles selected according to the conditions: ‘analyzed by text network analysis and topic modeling’. The core keywords were ‘self-management’, ‘intervention’, ‘health’, ‘support’, ‘technique’ and ‘system’. Through the topic modeling analysis, four themes were derived: ‘intervention’, ‘blood glucose level control’, ‘self-management’ and ‘mobile health’. The main topic of this study was ‘self-management’.
Conclusion: While more recent work has investigated mobile applications, the highest feature was related to self-management in the diabetes care and prevention. Nursing interventions utilizing mobile application are expected to not only effective and powerful glycemic control and self-management tools, but can be also used for patient-driven lifestyle modification.
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KEYWORD
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Diabetes mellitus, Mobile applications, Data mining, Telemedicine, Self-management
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