Narrative-Integrated Thematic Analysis (NITA): An innovative approach to generate themes without coding

The coding approach has dominated qualitative data analysis (QDA) for a while. Recent development of generative AI (GenAI) has led to an emerging debate about whether this technology can help qualitative researchers shift away from the coding paradigm. Yet, the application of GenAI in QDA to date has largely focused on replacing human coding to improve efficiency and effectiveness, while the attention to facilitating the transition to alternative methods remains limited.

In this session, we introduce a Narrative-Integrated Thematic Analysis procedure (NITA) that allows qualitative researchers to design, train and guide a GenAI in conducting thematic analysis. This NITA approach is regarded as a thematic analysis approach that positions researchers’ reflexivity, intellect and judgement at the centre of the analysis process. This approach combines a reflexive, iterative monitoring, evaluation and learning procedure (PERFECT) with a conversational method for interacting with and guiding GenAI.

Using an publicly available interview dataset provided by Lumivero and custom ChatGPT, we applied this approach through six stages: planning an initial PERFECT procedure, preparation, generating candidate themes, constructing individual narratives, constructing meta-narrative, and writing up. Compared to our previous experiment on the same dataset using the coding approach, we have found that the themes generated this time had similar qualities. This reveals the transformative potential of GenAI to redefine thematic analysis.

Speakers

Kien Nguyen-Trung, PhD, is GEDSI Lead and Research Fellow at Water Sensitive Cities Australia, Monash University, Australia. He is an editor at The Qualitative Report and serves on editorial boards at Sociological Research Online, and International Journal of Qualitative Methods. As founder of the Vietnam Social Research Methodology and Qualitative Methods Centre, he advances methodological innovation and capacity building in Southeast Asia. His interests span qualitative methods, generative AI, climate change adaptation, and disaster vulnerability.

Ngoc Lan Nguyen, PhD is a lecturer at the National Economics University, Vietnam, with a PhD in Business Administration. Her research focuses on strategic management, entrepreneurship, innovation and applications of generative AI in research. She has published in international journals such as Current Psychology, Journal of Entrepreneurship in Emerging Economies, and Corporate Governance.

Narrative-Integrated Thematic Analysis: Generate Qual Themes without Coding

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