Using ChatGPT to Evaluate User Reviews of Mobile Applications in the Field of Oral Health: A Study in Iran, 2025

Document Type : Original Article

Authors

1 Department of Medical Informatics, School of Allied Medical Sciences, Urmia University of Medical Sciences, Urmia, Iran

2 Clinical Informatics Research and Development Lab, Clinical Research Development Unit, Shafa Hospital, Kerman University of Medical Sciences, Kerman, Iran

Abstract

Background: Oral health is a vital component of overall human health. In recent years, mobile health applications (mHealth applications) have emerged as innovative tools to enhance health literacy and promote behavior change related to oral hygiene. Analyzing user feedback in app stores provides actionable insights into user experience, functional limitations, and opportunities for improvement. Leveraging artificial intelligence, particularly advanced language models such as ChatGPT, offers a novel opportunity for precise, rapid, and structured processing of these reviews.
Methods: This descriptive-analytical study was conducted in 2025. A total of 135 applications from Bazaar and 28 applications from Myket were initially retrieved. After applying screening criteria—removing duplicates, irrelevant applications, child-specific games, and applications with fewer than 1000 installs—12 applications were selected for final analysis. Screenshots of user reviews were processed using ChatGPT for sentiment and semantic analysis, categorizing comments into positive, negative, or neutral groups and five rating levels from excellent to very poor. Key themes and improvement suggestions were subsequently extracted by the model.
Results: Users primarily emphasized the need for regular updates, improved technical performance, and enhanced user interface design. The AI-based analysis demonstrated structured output and efficiency in providing a comprehensive overview of user needs and perceptions.
Conclusion: Advanced language models such as ChatGPT may serve as useful tools for analyzing user feedback and improving the quality and usability of digital health applications.

Keywords

Main Subjects


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