Journal of Korean Society of Dental Hygiene (J Korean Soc Dent Hyg)
Review Article

Research trends in artificial intelligence chatbots for oral health education and consultation: a narrative review

Department of Dental Hygiene, Daejeon Institute of Science and Technology

Correspondence to Su-Yeon Hwang, Department of Dental Hygiene, Daejeon Institute of Science and Technology, 100, Hyechon-ro, Seo-gu, Daejeon, 35406, Korea. Tel: +82-42-580-6449, E-mail: hsyen@naver.com

Volume 26, Number 4, Pages 437–45, August 2026.
J Korean Soc Dent Hyg 2026;26(4):437–45. https://doi.org/10.13065/jksdh.2026.26.4.3
Received on July 14, 2026, Revised on August 16, 2026, Accepted on August 22, 2026, Published on August 30, 2026.
Copyright © 2026 Journal of Korean Society of Dental Hygiene.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/licenses/by-nc/4.0).

Abstract

Objectives: This narrative review examined research trends in artificial intelligence (AI) chatbots for oral health education and counseling, with a particular focus on differences between Korean and international studies in their progress toward clinical application. Methods: International studies were searched in PubMed and Web of Science, and Korean studies in RISS, KCI, and DBpia, with the search limited to publications from 2019 onward. Of the 63 eligible international studies, 12 were purposively sampled to balance dental subspecialty and country of origin, with all studies reporting user or clinical outcomes retained; both Korean studies meeting the criteria were included. The 14 studies were categorized into three translational stages: development, performance evaluation, and effectiveness validation. Results: International studies spanned all three stages and included randomized controlled trials that assessed clinical and behavioral outcomes in patients. In contrast, the Korean studies remained at the development stage, with no assessment of response quality and no effectiveness validation involving actual users. However, many international studies were also preliminary or small in scale, indicating that widespread clinical adoption has not yet been achieved. Conclusions: A pronounced gap exists between Korean and international research in the clinical translation of AI chatbots for oral health education and counseling. To bridge this gap, Korean research should move beyond development toward user-centered evaluation and effectiveness validation, supported by the construction of Korean-language datasets, standardized assessment metrics, and multidisciplinary collaboration involving dental hygienists.
Keywords

Generative artificial intelligence, Health education dental, Patient education as topic

서론

이하 퍼블리싱 중.

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