Artificial Intelligence Augmented Qualitative Analysis

The Way of the Future

Datos Bibliográficos

ID5455477
AutoresDanielle Hitch (0000-0003-2798-2246, Deakin University, Geelong, VIC, Australia, autor de correspondencia)
Año2024
Volumen34
Número7
Páginas595-606
Fecha de publicación2024-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaQualitative Health Research (JOURNAL)
Identificadores de la revistaISSN: 1049-7323 • E-ISSN: 1552-7557
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/10497323231217392
PMID38064244
OpenAlexW4389490285
IdiomaEN
Citas recibidas52
Referencias citadas21

The artificial intelligence (AI) revolution is here and gathering momentum, thanks to new models of natural language processing (NLP) and rapidly increasing adoption by the public. NLP technology uses statistical analysis of language structures to analyse and generate human language, using text or speech as its source material. It can also be applied to visual mediums like images and videos. A few qualitative research early adopters are beginning to adopt this technology into their work, but our understanding of its potential remains in its infancy. This article will define and describe NLP-based AI and discuss its benefits and limitations for reflexive thematic analysis in health research. While there are many platforms available, ChatGPT is the most well-known and accessible. A worked example using ChatGPT to augment reflexive thematic analysis is provided to illustrate potential application in practice. This article is intended to inspire further conversation around the role of AI in qualitative research and offer practical guidance for researchers seeking to adopt this technology

Conversation · Data science · Natural language processing · Qualitative research · Reflexivity · Sociology · Thematic analysis · Communication · Computer Science · Focus Groups and Qualitative Methods · Psychology · Qualitative Research Methods and Applications · Qualitative Research Methods and Ethics · Artificial Intelligence