Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study

ChatGPT-4 demonstrates potential as an auxiliary tool in qualitative research, particularly for efficiently identifying descriptive themes within Japanese-language datasets. However, its limited capacity to interpret cultural and emotional nuances highlights the continued necessity of human expertise in qualitative analysis. These findings emphasize the complementary role of AI-assisted qualitative research and underscore the importance of further advancements in AI models tailored to non-English linguistic and cultural contexts. Future research should explore strategies to enhance AI's interpretability, expand multilingual training datasets, and assess the applicability of emerging AI models in diverse cultural settings. In addition, ethical and legal considerations in AI-driven qualitative analysis require continued scrutiny.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2025-04-24
DOI
https://doi.org/10.2196/71521
Citations
12
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
7.85
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article

Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study

Takashi Watari, Kota Sakaguchi, Reiko Sakama
12 citations
Journal of Medical Internet Research
Artificial Intelligence in Healthcare and Education
7.85
article

Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study

Takashi Watari, Kota Sakaguchi, Reiko Sakama
article en
12 citations

Abstract

ChatGPT-4 demonstrates potential as an auxiliary tool in qualitative research, particularly for efficiently identifying descriptive themes within Japanese-language datasets. However, its limited capacity to interpret cultural and emotional nuances highlights the continued necessity of human expertise in qualitative analysis. These findings emphasize the complementary role of AI-assisted qualitative research and underscore the importance of further advancements in AI models tailored to non-English linguistic and cultural contexts. Future research should explore strategies to enhance AI's interpretability, expand multilingual training datasets, and assess the applicability of emerging AI models in diverse cultural settings. In addition, ethical and legal considerations in AI-driven qualitative analysis require continued scrutiny.

Journal of Medical Internet ResearchVol. 27
NTT Medical Center (JP), Shimane University Hospital (JP), Kyoto University Hospital (JP)
Quality Education
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
7.85
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