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The digital health industry has grown in popularity since the 2010s, butthere has been limited analysis of the topics discussed in the field acrossacademic disciplines. This study aims to analyze the research trends of digitalhealth-related articles published on the Web of Science until 2021, in order tounderstand the concentration, scope, and characteristics of the research.15,950 digital health-related papers from the top 10 academic fields wereanalyzed using the Web of Science. The papers were grouped into three domains:public health, medicine, and electrical engineering and computer science(EECS). Two time periods (2012-2016 and 2017-2021) were compared using LatentDirichlet Allocation (LDA) for topic modeling. The number of topics wasdetermined based on coherence score, and topic compositions were compared usinga homogeneity test. The number of optimal topics varied across domains and timeperiods. For public health, the first and second halves had 13 and 19 topics,respectively. Medicine had 14 and 25 topics, and EECS had 7 and 21 topics. Textanalysis revealed shared topics among the domains, but with variations incomposition. The homogeneity test confirmed significant differences between thegroups (adjusted p-value<0.05). Six dominant themes emerged, including journalarticle methodology, information technology, medical issues, populationdemographics, social phenomena, and healthcare. Digital health research isexpanding and evolving, particularly in relation to Covid-19, where topics suchas depression and mental disorders, education, and physical activity havegained prominence. There was no bias in topic composition among the threedomains, but other fields like kinesiology or psychology could contribute tofuture digital health research. Exploring expanded topics that reflect people'sneeds for digital health over time will be crucial.

Digital Health Discussion Through Articles Published Until the Year 2021: A Digital Topic Modeling Approach