Harnessing Chatgpt For Thematic Analysis: Are We Ready?

V Vien Lee, Stephanie C. C. van Der Lubbe, Lay Hoon Goh, Jose M. Valderas . Journal of Medical Internet Research 2024 – 48 citations

[Paper]    
Applications Compositional Generalization Content Enrichment Efficiency Image Text Integration Interactive Environments Interdisciplinary Approaches Multimodal Semantic Representation Neural Machine Translation Productivity Enhancement Question Answering Training Techniques

ChatGPT is an advanced natural language processing tool with growing applications across various disciplines in medical research. Thematic analysis, a qualitative research method to identify and interpret patterns in data, is one application that stands to benefit from this technology. This viewpoint explores the utilization of ChatGPT in three core phases of thematic analysis within a medical context: 1) direct coding of transcripts, 2) generating themes from a predefined list of codes, and 3) preprocessing quotes for manuscript inclusion. Additionally, we explore the potential of ChatGPT to generate interview transcripts, which may be used for training purposes. We assess the strengths and limitations of using ChatGPT in these roles, highlighting areas where human intervention remains necessary. Overall, we argue that ChatGPT can function as a valuable tool during analysis, enhancing the efficiency of the thematic analysis and offering additional insights into the qualitative data.

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