Thematic Analysis of User Experience in Mobile Health Applications: An LDABased Study Using the e-Nabız Example

This study examines the user experience of e-Nabız, Turkey’s national digital health platform, based on user reviews of the application. The aim of the research is to identify the themes that emerge in user feedback, reveal the relationship between these themes and satisfaction and sentiment orientations, and evaluate the evolution of the user experience over time. To this end, publicly available user reviews were subjected to natural language processing-based preprocessing steps; subsequently, the Latent Dirichlet Allocation (LDA) method was applied to uncover latent thematic structures. The identified themes were interpreted in an integrated manner alongside star ratings, sentiment analysis findings, and patterns of change over the years. The findings indicate that user reviews most frequently focused on the following topics: perception of service quality (24.1%), software errors and registration (18.4%), laboratory and radiology (12.4%), health and medication tracking (12.3%), and social appreciation and effort (11.4%). Additionally, the analysis identified less prominent themes such as system stability (8.0%), general satisfaction (7.5%), and access and identity verification (6.0%). The results indicate that e-Nabız is generally evaluated as a functional and useful public health platform; however, they also reveal that fundamental issues such as general data synchronization and access continuity limit user satisfaction. In particular, the polarization in star ratings and the concentration of negative sentiments in technical themes indicate that the user experience is shaped not only by the mere existence of the service but also by the system’s reliable and uninterrupted operation. The study demonstrates that large-scale user reviews provide a powerful analytical resource for health informatics research and offers data-driven insights for the development of public-sector digital health systems.