Abstract
Mobile health (mHealth) applications became salient tools for health and exercise management during the COVID-19 pandemic. However, large-scale studies on this topic are lacking. Therefore, in this study, we analyzed changes in the key attributes and network structure of exercise-based mHealth in South Korea during and post the COVID-19 pandemic using big data analysis. A total of 32,115 data points collected from Naver and Google over 4 years were analyzed. Frequency analysis, term frequency-inverse document frequency analysis, and convergence of iterated correlations analysis were performed using TEXTOM 6.0 to identify the key attributes and clusters. The data were further analyzed to explore network structures and cluster relationships. The frequency and term frequency-inverse document frequency analyses revealed 30 high-order terms for the periods during and post the COVID-19 pandemic. The convergence of iterated correlations analysis revealed 4 clusters during the pandemic (digital transformation; wellness and lifestyle; mobile technology and personalization; healthcare and public health services) and 4 clusters post the pandemic (digital platforms and development; exercise and mobile management; mHealth and wellness; and healthcare and public health services). The COVID-19 pandemic accelerated the adoption and evolution of mHealth in South Korea, which may indicate a shift from crisis response toward greater integration into daily lives. Further, the pandemic led to the initiation of personalized digital health solutions in the post-pandemic era. These findings highlight the growing role of mHealth in public health and wellness and provide insights into future developments in digital health solutions.