Artificial Intelligence Augmented Qualitative Analysis: The Way of the Future?

Area of Science:

• Computer Science
• Health Research Methodology

Background:

• Artificial intelligence (AI) and natural language processing (NLP) are rapidly advancing.
• Qualitative researchers are beginning to explore AI's potential, but understanding is limited.
• NLP analyzes and generates human language from text, speech, and visual data.

Purpose of the Study:

• To define and describe NLP-based AI for qualitative research.
• To discuss the benefits and limitations of AI in reflexive thematic analysis.
• To provide a practical example of using AI in health research.

Main Methods:

• Literature review and conceptual analysis of NLP-based AI.
• Exploration of AI applications in qualitative research, focusing on reflexive thematic analysis.
• A worked example using ChatGPT to augment reflexive thematic analysis in health research.

Main Results:

• NLP-based AI offers potential benefits for qualitative analysis, including efficiency and novel insights.
• Limitations include potential biases, ethical considerations, and the need for researcher oversight.
• ChatGPT can be a practical tool to augment reflexive thematic analysis.

Conclusions:

• AI, specifically NLP tools like ChatGPT, presents a promising frontier for qualitative health research.
• Further research and discussion are needed to fully understand and ethically integrate AI into qualitative methodologies.
• Practical guidance is offered for researchers adopting AI in their work.